"PRESERVATION OF THE CONGRUENCE OF THE HIP IN PERTHES DISEASE USING SHELF ACETABULOPLASTY AND THE RELATIONSHIP TO THE KINEMATICS AND KINETICS OF THE HIP DURING GAIT, TOGETHER WITH STANDING BALANCE" MASTER’S THESIS

Florian Stul Emmeline Deloddere Student number: 01307899 Student number: 01308609

Supervisors: Prof. dr. Frank Plasschaert (promotor), Prof. dr. Malcolm Forward (copromotor) A dissertation submitted to Ghent University in partial fulfilment of the requirements for the degree

of Master of Medicine in Medicine

Academic year: 2017-2018

“The author and the promotor give the permission to use this thesis for consultation and to copy

parts of it for personal use. Every other use is subject to the copyright laws, more specifically the

source must be extensively specified when using results from this thesis.”

Date

(handtekening)

Name (student) (promotor)

Acknowledgments This thesis is part of the master of science in medicine of the UGent and is organised in

association with the university hospital of Ghent (UZ Gent). Enabling students to get a taste of

the possibilities and joys of research. We would like to express our sincere gratitude to the

people who supported us in the process of establishing our thesis.

First of all, we want to thank our promotor, Prof. Dr. F. Plasschaert (MD, Phd), to submit such an

interesting and promising study. Hereby creating the possibility to work on a study leading to a

clinically relevant result. Even though our promotor had an extremely busy agenda, he made it

possible to find time to evaluate the course of the thesis and give us usefull directions.

Secondly, we want to thank Prof. Dr. M. Forward, copromotor of the thesis. Without his help and

extensive gait analysis expertise, the research wouldn’t have been possible. He taught us how to

operate the gait lab and helped us through the elaborate process of collecting, processing and

interpreting data. At any day, any time, he was there to help us solve problems and supported us

to create the study to what it has become.

Thirdly, we want to thank Dr. Lauwagie (additional supervisor), Mrs. De Dobbelaere (gait lab

assistant) and Mrs. Fruyt (secretary pediatric orthopaedics) for the logistic support and help

when needed and Dr. Mullie and Dr. Willemot for the support on the processing of the X-rays of

the patients.

Special thanks also to our parents for always encouraging and supporting us. They made it

possible for us to study medicine and created the environment needed to succeed through the

years of the education.

We also want to thank our thesis-partner, although we didn’t know each other at the start, we

both feel that we became a good team. We shared, for a year and a half, progress and

frustrations related to the thesis, we solved problems and also created a few, but in the end we

finished the thesis.

Last, but most definitely not least, we want thank the control persons and patients (and their

parents) who participated in our study. None of this would have been possible without their

selfless participation.

Table of Contents ABSTRACT (English) .................................................................................................................. 1

Introduction ............................................................................................................................. 1

Methodology ............................................................................................................................ 1

Results .................................................................................................................................... 1

Conclusion .............................................................................................................................. 1

ABSTRACT (Nederlands) ........................................................................................................... 2

Introductie ............................................................................................................................... 2

Methodologie ........................................................................................................................... 2

Resultaten ............................................................................................................................... 2

Conclusie ................................................................................................................................ 3

PREFACE ................................................................................................................................... 4

Research question .................................................................................................................. 4

Aim of the study ....................................................................................................................... 4

Relevance ............................................................................................................................... 4

1 INTRODUCTION ................................................................................................................. 6

Legg-Calvé-Perthes Disease: What is LCP? ................................................................. 6 1.1

Clinical presentation ..................................................................................................... 6 1.2

Pathophysiology ........................................................................................................... 7 1.3

1.4 Radiological techniques and classifications ....................................................................... 8

Therapy ........................................................................................................................ 9 1.5

1.5.1 Containment therapy ........................................................................................... 10

1.5.2 Remedial therapy: ................................................................................................ 12

1.5.3 Salvage therapy: .................................................................................................. 12

Gait Analysis ............................................................................................................... 12 1.6

1.6.1 Kinematics ........................................................................................................... 13

1.6.2 Kinetics ................................................................................................................ 13

1.6.3 Construction of the 3D-model .............................................................................. 13

IOWA Hip Score ......................................................................................................... 14 1.7

2 Methodology ...................................................................................................................... 15

LCPD patients ............................................................................................................ 15 2.1

Controls ...................................................................................................................... 16 2.2

Experimental set-up .................................................................................................... 16 2.3

Radiologic evaluation of the LCPD patients ................................................................ 17 2.4

2.4.1 Pre-processing .................................................................................................... 17

2.4.2 Processing ........................................................................................................... 18

Gait Analysis ............................................................................................................... 20 2.5

2.5.1 Technical specifications of the lab for motion analysis of the UZ Ghent ............... 20

2.5.2 Positioning of the markers: .................................................................................. 20

2.5.3 Sequence of the gait analysis .............................................................................. 22

2.5.4 Data processing – gait analysis ........................................................................... 23

IOWA Hip Score ......................................................................................................... 23 2.6

Data Analysis .............................................................................................................. 23 2.7

2.7.1 Kinematics ........................................................................................................... 23

2.7.2 Kinetics ................................................................................................................ 24

Statistical Analysis ...................................................................................................... 26 2.8

2.8.1 Comparison of the PIG and the functional (PiG-Matlab) model ............................ 26

2.8.2 Group comparison ............................................................................................... 26

2.8.3 Side comparison .................................................................................................. 27

2.8.4 Correlation IOWA – gait variables ........................................................................ 28

3 Results .............................................................................................................................. 29

General variables of the groups .................................................................................. 29 3.1

Gait and balance variables comparison ...................................................................... 29 3.2

3.2.1 Group comparison PiG-Matlab Model .................................................................. 30

3.2.2 Side comparison PiG-Matlab Model ..................................................................... 32

3.2.3 Differences between both gait analysis models ................................................... 34

IOWA Hip Score ......................................................................................................... 35 3.3

3.3.1 Comparison of the patient groups ........................................................................ 35

3.3.2 Correlations IOWA – gait variables ...................................................................... 35

4 Discussion ......................................................................................................................... 37

The research question ................................................................................................ 37 4.1

Discussion of the results ............................................................................................. 37 4.2

4.2.1 Gait model ........................................................................................................... 37

4.2.2 Overall group comparison .................................................................................... 39

4.2.3 Side by side comparison ...................................................................................... 43

The study design choices ........................................................................................... 44 4.3

Study limitations .......................................................................................................... 45 4.4

Future research .......................................................................................................... 46 4.5

Conclusion .................................................................................................................. 46 4.6

5 References ........................................................................................................................ 48

6 Appendix ............................................................................................................................... I

Schematic illustration of the gait lab ............................................................................... I 6.1

Radiographic parameters .............................................................................................. II 6.2

6.2.1 Coverage and subluxation ..................................................................................... II

6.2.2 Congruence: SDS ................................................................................................. VI

IOWA hip score (chart) .............................................................................................. VIII 6.3

Results PiG Model ....................................................................................................... IX 6.4

6.4.1 Group comparison PiG Model ............................................................................... IX

6.4.2 Side comparison ................................................................................................... IX

Tables results ............................................................................................................... X 6.5

1

ABSTRACT (English)

Introduction Legg-Calvé-Perthes disease (LCPD) is a pediatric orthopedic disease, affecting the mobility of

the hip and hip joint loading, leading to premature osteoarthritis. Modified Shelf Acetabuloplasty

(mSA) is a recent developed containment therapy for severe LCPD patients. This study aims to

evaluate mSA outcome based on gait analysis. Kinematics and kinetics of the hip and pelvis are

used to obtain objective data to evaluate hip mobility, hip joint loading and gait patterns.

Methodology Twenty-eight patients are divided into four quartiles based on Principal Component Analysis

(PCA) processed X-ray measurements. Only the best and worst quartile are selected in further

analysis, creating a group of patients with good radiographic outcome and a group of patients

with bad radiographic outcome. Subsequently, in order to compare both patient groups and the

seven healthy controls, computerized gait analysis is performed based on Plug-in-Gait (PiG) and

PiG-Matlab Models. Kinematic and kinetic parameters are evaluated, for the three planes

(frontal, sagittal and transverse), in order to obtain a complete evaluation. The analysis is based

on both a group comparison and an affected/unaffected side comparison within the groups.

Results In the group comparison, a reduced Hip Extension, Hip Range of Motion (ROM) and increased

Pelvic Tilt is observed for the affected side. A trend of reduction is detected for Hip Abduction in

the group of patients with bad outcome, but no significance is detected for Pelvic Obliquity,

Balance Standing or Trendelenburg gait. The bad outcome patient group shows a significant

reduction for Hip Flexion, Hip ROM and Hip External Rotation Moment for the affected side.

Conclusion In conclusion the patient group with good outcome shows no compromised gait pattern. The

abnormalities observed in the patient group with bad outcome are mostly due to aberrant hip

extension, other affected parameters are compensation mechanisms for the affected hip

extension. The major clinically important variables: Hip Abduction, Trendelenburg gait and Hip

Internal Rotation are unaffected in both patient groups. This is an important result, especially

concerning the Hip Abduction and the Hip Abduction Moment, because of its consequences with

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respect to the long-term complications, such as premature osteoarthritis.

ABSTRACT (Nederlands)

Introductie De ziekte van Legg-Calvé-Perthes (LCPD) is een orthopedische ziekte, die voorkomt op

kinderleeftijd. Bij LCPD is de mobiliteit en belasting van de heup aangetast. Dit leidt tot

vroegtijdige artrose. Modified Shelf Acetabuloplasty (mSA) is een recent ontwikkelde

containment behandeling voor patiënten met een ernstige vorm van LCPD. Deze studie heeft als

doel het resultaat van mSA te evalueren a.d.h.v. ganganalyse. Er wordt gebruik gemaakt van

kinematica en kinetica van de heup en het bekken om objectieve data te verzamelen. Op basis

van deze data wordt een evaluatie gemaakt van de heupmobiliteit, heupbelasting en

gangpatronen.

Methodologie Achtentwintig patiënten worden onderverdeeld in vier kwartielen, gebaseerd op RX variabelen,

die a.d.h.v. Principal Component Analysis (PCA) werden verwerkt. Enkel het beste en slechtste

kwartiel wordt hierbij weerhouden voor verdere analyse. Op die manier worden twee

patiëntengroepen gecreëerd: een patiëntengroep met een goed radiografisch resultaat en een

patiëntengroep met een slecht radiografisch resultaat. Daarna wordt er een ganganalyse

afgenomen, om beide patiëntengroepen met elkaar en met de zeven controles te vergelijken. De

ganganalyse werd afgenomen gebruikmakende van het Plug-In-Gait (PiG) en PiG-Matlab

Model. Kinematische en kinetische data wordt geëvalueerd in drie vlakken (sagittaal, frontaal,

transversaal) om een complete evaluatie te verkrijgen. De analyse is gebaseerd op een

groepsvergelijking en op een vergelijking binnen de groep van het gezonde en het aangetaste

been.

Resultaten Bij het vergelijken van de drie groepen wordt voor het aangetaste been een afname van de

heupextensie en heupbewegingsbereik gezien in combinatie met een toename van de

anterieure bekkenkanteling. In de groep met slecht resultaat wordt een trend tot reductie gezien

voor heup abductie, maar er wordt geen significant verschil t.o.v. de andere groepen gezien voor

bekkenuitzakking en balans in stand. Ook een Trendelenburg gangpatroon wordt niet

waargenomen. Voor de groep met slecht resultaat wordt bij het vergelijken van beide zijden een

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significant reductie waargenomen voor heupflexie, heupbewegingsbereik en heup exorotatie

moment.

Conclusie Voor de patiënten met goed resultaat wordt geen afwijking van het gangpatroon gezien. De

abnormaliteiten die geobserveerd worden voor de groep met slecht resultaat kunnen

grotendeels verklaard worden door aberrante heupextensie. De andere afwijkende parameters

behoren namelijk tot de compensatiemechanismen van de aangetaste heupextensie. De klinisch

relevante variabelen: heupabductie, Trendelenburg gangpatroon en endorotatie van de heup,

zijn niet afwijkend in beide patiëntengroepen. Zeker voor heupabductie en heupabductie

moment, zijn dit belangrijke resultaten, aangezien beide parameters een belangrijke impact

hebben op langetermijnscomplicaties, zoals bijvoorbeeld vroegtijdige artrose.

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PREFACE

Research question What is the relationship between modified Shelf Acetabuloplasty (mSA) and the kinematics and

kinetics of the hip during gait, together with standing balance? And as an additional question, is

Plug-in-Gait (PiG) or PiG-Matlab the most valid model in patients with Legg-Calvé-Perthes

(LCPD)?

Aim of the study The aim of this thesis is to evaluate the effect of a modified Shelf Acetabuloplasty procedure on

the kinematics and kinetics of the hip as well as the standing balance, when treating children

with Legg-Calvé-Perthes (LCP). The purpose of modified Shelf Acetabuloplasty is to increase

the femoral head coverage in order to prevent malformations and incongruence of the hip joint

as they can occur, during the healing process. We therefore evaluate routine postoperative

follow-up X-rays of LCP patients treated by Prof. dr. Frank Plasschaert (UZ Gent), using his

modified Shelf Acetabuloplasty. The patients are scored for parameters representing coverage

and congruence. Based on these parameters, patients were divided into two groups: (a) better

radiographic results and (b) worse radiographic results. Instrumented Gait Assessments were

used to compare these patient groups for hip mobility and hip power, by analysing the

kinematics and kinetics.

The hypothesis states that in both groups of LCP (better and worse radiographic results) good

functional results will be obtained. This is based on the presumption that the shelf will only

influence the ultimate shape of the hip during the healing process of LCP. If the shelf is resorbed

into the acetabulum or migrates after the healing process, this will cause a bad radiographic

result. The hypothesis however states that the shelf will have already fulfilled its effect and the

resorption and/or migration has no further impact on the function of the hip. The focus of this

research is the hip function. Concerning the possible development of early onset osteoarthritis,

no predictions are made.

Relevance LCPD is a self-limiting disease in the longer-term, however deformation of the femoral head that

might develop during the process of LCP disease predisposes patients to premature secondary

degenerative arthritis. Depending on its severity, arthritis can compromise the quality of life of

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patients and entail high costs for the health care system (e.g. when total hip replacement is

needed.)

Defining a treatment for LCP that not only improves short-term outcome in maintaining the

function of the hip, but which also addresses the longer-term outcome with respect to arthritis

would offer an important break through in the management of LCP.

6

1 INTRODUCTION

Legg-Calvé-Perthes Disease: What is LCP? 1.1Arthur Thornton Legg first describes Legg-Calvé-Perthes Disease (LCPD) in 1909. In the same

period, a few years after the discovery of the X-ray technology, Jacques Calvé and Georg

Perthes report on similar observations (1).

Nowadays, the reported incidence of LCPD varies from 8 to 32 per 100 000, depending on the

literature (1). LCPD affects boys 4-5 times more than girls and bilateral LCP is more often in

girls. The impact of the development of LCPD and gender on the prognosis do remain unclear

but might be related to a lower remodelling potention in girls of similar chronological age than

boys (1,2).

Multiple causal factors of LCPD have been investigated but, to the best of our knowledge, no

distinct causal factor has been identified thus far (3,4). Hypercoagulation has more recently been

put forward as a possible cause for the femoral head necrosis. A significant relationship between

LCP and a factor V Leiden mutation was shown by a meta-analysis of Woratanarat et al.(3).

Till today, general consensus reports LCP to be a multifactorial disease with genetic

predisposition influenced by environmental causal factors. LCP could be caused by multiple

etiological factors with a common pathological and clinical presentation. For instance acetabular

retroversion and obesity are conditions frequently reported to be associated with LCPD (4).

Clinical presentation 1.2The age of onset of LCP is between 2 and 12 years of age (5), with a peak incidence in children

between 4 and 8 (1,3,5). The importance of the age of onset within the disease process of LCP

will be focussed on a bit more in the sections about pathophysiology (cfr 1.3 Pathophysiology)

and therapy (cfr. 1.5 Therapy).

The clinical presentation of LCP is highly variable and has different characteristics throughout

the phases of the disease (5). First, in the early stages, LCP is characterised by a limping gait,

followed by an ill-defined pain along the anterior side of the hip and medial thigh (3). Sometimes,

only isolated knee pain does exist (5). The range of motion of the hip joint is often affected by

LCP. Usually a loss in abduction and internal rotation are found. A progression towards a

7

Trendelenburg gait pattern might develop (1,3,5). Normally the maximum flexion and extension

of the hip are not affected by LCPD. Although less specific, the children affected by LCP show a

relatively small stature and the bone age can be delayed when compared to unaffected peers

(1). Experienced pain (due to synovitis in the early stages), range of motion, abduction, internal

rotation, flexion and extension are among the variables evaluated in this study since they seem

to be the clinical variables affected by LCP.

Pathophysiology 1.3Disruption of the blood supply in the femoral head, due to the accumulation of multiple infarcts,

is generally accepted to be the cause of LCPD (4,6,7).

The pathophysiological process of LCPD can be divided into four stages: the avascular phase

(disruption of the blood supply and necrosis of bone and cartilage), continued by the

fragmentation phase (collapse of the trabecular bone), followed by the reossification phase

(reformation of bone) and finally the healing phase (maturation of the bone) (7). The weakening

and deformation of the bone vary throughout the different healing stages. The deformation of the

femoral head, occurring in LCPD, can be approached from a mechanical point of view. The

ischaemia during the avascular phase reduces the load-carrying capacity of the femoral head

(necrotic bone) and induces an inability to resist deformation. Fractures and deformity of the

femoral head can develop within this phase due to a loading force, exceeding the capacity of the

femoral head (8).

During the avascular phase a disruption of the blood supply leads to necrosis and

apoptosis of both bone marrow and articular cartilage in the hip joint and has secondary effects

on the soft tissue. The combination of soft tissue changes and muscle spasms can cause an

extrusion of the femoral head out of the acetabulum, resulting in an increased lever arm putting

the vulnerable femoral head under pressure. Extrusion is an important factor in the development

of femoral head deformation. The abnormal loading of the hip in combination with a weakened

bone structure challenges the hip joint (9). Within this phase the femoral head is extremely

vulnerable to deformation, since fractures cannot repair themselves in avascular bone.

Following the ischaemic damage, the fragmentation phase is initiated by the

neovascularisation, inducing a first step within the healing process. The higher concentration of

osteoclasts leads to the resorption of the bone necrosis. During this phase radiolucent areas can

be determined (4,10). The resorbed bone is replaced by fibrovascular tissue. This phase is still

8

characterised by a weak bone structure and an even higher potential to develop fractures and

deformation of the femoral head. Research has shown that inhibition of bone resorption, using

bisphosphonates or RANKL inhibitors, should counter the weakening of the bone structure and

conserve both trabecular bone and sphericity of the femoral head (8).

During the reossification phase , ensuing the fragmentation phase, the fibrovascular

tissue is replaced by new-formed bone. The process ends with the healing phase : the bone

reobtains its trabecular structure and a normal radiodensity can be observed, as the maturation

of the bone in the femoral head is complete (7).

Age has an important impact on the earlier described risk for deformation of the femoral head

within the disease process. Depending on the age of the subject, a different response to

hypoxemia and angiogenesis can be observed. The neovascularisation is much more activated

in children younger than 6 years in comparison to children older than 8 years. Therefore,

younger children with LCPD are expected to experience less deformation. Furthermore, young

children have a relatively higher proportion of cartilage covering the bony core of the femoral

head. This makes younger patients less vulnerable to fractures in the underlying weakened bone

(8).

1.4 Radiological techniques and classifications

Throughout the years several radiologic classifications for LCP, using X-rays, have been

developed. The most relevant are the Waldenström, Catterall, Salter-Thompson, Herring Lateral

pillar, Stulberg and Mose classification. These classifications differ w.r.t. the phase of the

disease at which they can be applied, the measurements on which they are based and the

purpose of its use. Below we briefly summarize the main ideas of these classification methods.

To specify the stage of the disease the Waldenström classification can be used. The

classification is applied during the active phase of the disease. The Catterall, Salter-Thompson

and Herring lateral pillar classifications focus on the prognostic short-term outcome based on the

extent of necrosis, subchondral fracture or loss of height of the lateral pillar of the femoral

epiphysis. The Stulberg classification is based on deformity that develops in the later stages of

LCPD. The higher classes (II-IV) have a high risk at premature osteoarthritis (8).

The Mose classification uses a template of concentric circles, of which the radii differ 1

millimetre, to define the sphericity of the femoral head (11).

Next to the above classifications, descriptive coverage and congruence parameters can be

9

measured to classify subjects. One study reported the measurement of angles to have higher

interobserver reliability than radiographic classifications, but the importance of clearly defined

landmarks is fundamental (12,13). Coverage can be measured by the Sharp angle (SA), the

center-edge angle (CEA) of Wilberg, subluxation ratio (SR), femoral head size ratio (FHSR) and

femoral head coverage ratio (FHCR). The congruence is measured using the Sphericity

Deviation Score. The Sharp angle is a measure of acetabular dysplasia for which a good inter-

observer reliability as well as good agreement could be found in skeletally immature subjects

(14–16). The center-edge angle of Wilberg and the subluxation ratio, also referred to as “Medial

joint space ratio” are measures for subluxation (17,18). The femoral head shape is a very

important determinant of long-term outcome in LCPD (3). Significant correlations were found

between clinical outcome and femoral head size ratio (19). Wiig et al. found femoral head

coverage to be a reliable measurement for quantifying the acetabular covering of the femoral

head, characterised by relatively small inter-observer differences (13). The congruence of the

femoral head can be quantified using the, recently developed, Sphericity Deviation Score (SDS).

SDS is a continuous variable, which is an important advantage over the traditional classifications

described above. Especially because sample sizes in LCPD research are often limited (20). In

addition, it is applicable for unilateral and bilateral cases and validated for application during both

the healing stage and at skeletal maturity. In recent literature the intraobserver and interobserver

reproducibility were found to be satisfactory (21). An overview of the formulas of the variables

can be found in the appendix (6.2 Radiographic parameters (Appendix)).

Therapy 1.5LCPD is a self-limited disorder, leading to the occlusion of the femoral blood supply, which

results in bone necrosis (8). Usually a spontaneous revascularization is seen over a period of 2

to 4 years. The course of disease can occur with or without sequellae. In a significant number of

patients, influenced by age, femoral deformation can develop during the natural course of LCP.

The goal of treatment of LCP does focus on an avoidance of deformation of the femoral head

within the disease process in order to minimise physical impairments and the development of

early onset secondary degenerative osteoarthritis (2,22).

Deformation of the femoral head is commonly seen in the late stage of the fragmentation phase

or the early stage of the reossification phase. Deformation can be used as a marker point to

divide the course of the disorder into two parts: an early or pre-deformation part and a later or

post-deformation part. Following this division, preventive treatment (containment) should be

initiated during the pre-deformation part of the disorder. Any treatment started after the onset of

10

the deformation should be regarded a remedial or salvage treatment (22).

Based on the previous discussion, treatment in LCPD can be categorised into the following

categories: containment therapy (pre-deformation), remedial therapy (post-deformation) and

salvage therapy (treatment of possible sequellae). An overview of the treatment options is

depicted below (cfr. Figure 1).

1.5.1 Containment therapy

The goal of containment therapy is to stop increased loading on the antero-lateral side of the

epiphysis of the hip, by avoiding extrusion of the femoral head and preventing deformation and

the consequent incongruence (6). This goal can be reached by using a brace (to fixate the hip in

abduction and internal rotation) or by surgery. One of the options for surgery is Shelf

Acetabuloplasty (9). Whatever technique is chosen, the common goal is to protect the

anterolateral part of the femoral head against (abnormal) loading, potentially leading to

deformation of the femoral head (before it can repair itself) (7,9,23).

The decision of which treatment strategy should be applied, is based on the severity (extent of

the necrosis) and stage of disease. Age and remodeling potential do influence the prognosis of

Figure 1: overview LCPD treatment options

11

the disorder and therefore the choice of treatment. The choice of what to do (or not to do) when

is a difficult task to the clinician involved in the treatment of LCPD. Therefore, an estimation of

the prognosis and need for treatment is made based on the head at risk signs, decreased

mobility, patients age and radiological classification. At present, the radiological classification

being frequently used, is the Herring’s lateral pillar classification (24). Today, the lateral pillar

classification together with age is the dominant factor when deciding upon treatment (25,26).

Based on these principles four treatment groups have been defined:

1) group A Herring lateral pillar classification

2) group B and group B/C Herring lateral pillar classification under the age of 8

3) group B and group B/C Herring lateral pillar classification over the age of 8

4) group C Herring lateral pillar classification.

In general, a good prognosis is to be expected in patients of the first two groups. In these groups

a surgical intervention is not necessary. It is however important to advise a four monthly X-ray

follow-up in patients from the age of seven. In order to detect extrusion and proceed with

containment therapy if needed (9). For the last two groups previous studies have shown surgery

to produce significantly better results than conservative treatment (26). The goal of surgical

containment procedures is the maintenance of the sphericity (varus osteotomy, innominate

osteotomy, pelvic osteotomy) and/or centralisation of the femoral head (innominate osteotomy,

triple osteotomy). Despite the surgical options mentioned above, the prognosis in subjects older

than eight is often poor. The success rate of surgery decreases with increasing age.

Shelf Acetabuloplasty, developed to overcome the problems associated with femoral and Salter

innominate osteotomy, is probably not only effective in older subjects but also in other subjects,

older than five presenting with a severe case of LCPD (27–30). Shelf Acetabuloplasty has been

successfully applied in severe late-onset LCPD but there were concerns regarding the damage

at the lateral acetabular epiphysis, graft resorption and graft migration. However, only for the

graft migration, evidence was found (14,28,31). By stabilizing the shelf, using the reflected head

of the rectus femoris tendon, graft migration can be prevented (27,31). Modified Shelf

Acetabuloplasty, the technique studied in this thesis, is a further improvement of the Shelf

Acetabuloplasty, and combines the Albee Graft and Staheli Shelf technique. The technique

meets the principles of containment therapy. The advantages of this new technique are: the

intrinsic stability (which makes a hip spica cast obsolete and thus shortens the required hospital

admission), the in-built compression, the not-affected growth of the acetabulum, no tendency for

graft resorption and a major pain relieving effect immediately after the operation. After

performing the modified Shelf Acetabuloplasty the following effects have been observed:

12

increase of the femoral head coverage ratio, decrease of the subluxation ratio and good shelf

height ratio (32).

1.5.2 Remedial therapy:

When the disorder already proceeded to the late fragmentation phase or early reconstitution

phase, remedial therapy is indicated. The goal is to minimise the commencing deformation

effects. Results increase when the containment therapy is applied in earlier stages of the

disorder (9).

1.5.3 Salvage therapy:

After the healing process has ended, abnormalities can occur under the form of sequellae.

These abnormalities are cam and pincer impingement, functional retroversion and enlarged and

diminished trochanteric impingement. Recent attempts were made to reshape the deformed

femoral head. These treatments result in pain reduction, increased mobility and improved hip

abductor strength (9). Shelf Acetabuloplasty can be used as a salvage therapy, but the success

rate decreases compared to when it is used as containment therapy (30). Overall, the long-term

prognosis for salvage therapy is poor and often a hip prosthesis is required after a few years. As

reported by Joseph B., 39% of the patients has undergone a total hip replacement within eight

years after the salvage surgery (9). In addition, Lehmann et al. reported that 30% of the

adolescents undergoing total hip replacement for degenerative joint disease, secondary to

LCPD, had previously been treated with joint preserving salvage therapy (33). These findings

stress the importance of treatments early in the course of the disease.

Gait Analysis 1.6The purpose of using gait analysis in this study is to collect kinetic and kinematic data, derive

relevant quantitative summary parameters and obtain an objective assessment of the gait

pattern. Using gait analysis enables a more accurate assessment of the gait pattern than visual

gait assessment. It is broadly acknowledged as a useful research tool (34). The kinematics,

being the joint motions of the subject, are measured using a set of digital infrared cameras

positioned 360 ° around the gait platform (Cfr. Appendix: Figure 3: schematic illustration of the

gait lab). Simultaneously, data from force plates mounted within the walkway floor is collected,

enabling calculation of joint force and moments during gait (35).

13

1.6.1 Kinematics

Kinematic data consists of the position and orientation of body segments, angles of joints, linear

and angular velocities and accelerations. It thus describes the movements of the subject in a

(three dimensional) geometrical way over time (referred to as gait cycle). The movement of the

subject through space is monitored by the optico-electronic video cameras. The cameras

register markers attached to the subject’s skin, positioned in such a way they are seen by at

least two cameras. Photogrammetric (or stereometric) reconstruction techniques are used

(together with calibration data) to derive three dimensional coordinates of markers in space over

time. The markers placed on the subject’s skin act as repère points to digitise the subject.

Groups of three or more markers are used on each body segment of the subject to be able to

determine position and orientation in 3D space. The markers are placed onto the skin, often on

anatomical bony landmarks (36).

The correct marker placement on anatomical landmarks is extremely important to reduce data

noise and collect useful data (depending on the model used) (37–39). The goal is to place the

markers1 in a repeatable, consistent and clinically valid manner. Skin movement and muscle

contractions, interfere with the steady position of the marker and cause noise (39). To this day,

despite the development of new techniques and models, correct and repeatable marker

placement remains a major challenge in gait analysis (38).

1.6.2 Kinetics

The kinetics describe the joint forces and moments during movement. Kinetic data is most often

derived using kinematic data and data derived from force plates. The ground reaction forces,

starting at heeling strike and ending at toe offset, are measured using the force plates, built into

the walkway of the gait lab. Since the ground reaction forces result from the movement and force

generation of the entire body, they can be used to estimate kinetic data of the whole body,

based inverse dynamic calculations. When the kinetic data is combined with the kinematic data,

the joint forces and moments of separate body segments can be estimated (36).

1.6.3 Construction of the 3D-model

In 3D kinematic modelling, body segments are most commonly modelled as simplified rigid

1 The margin of error in locating the anatomical landmarks can be reduced using image techniques to determine the patient specific, individual geomitry of the hip joint (39). These techniques are not used in this study because of the exposure to radiation and the required labour-intensive processing of the data.

14

structures joined by joints.

Two methods exist to determine and digitalize the joint axes: the predictive and the functional

method.

1) Predictive method: markers are located on anatomically defined landmarks. The

landmarks are chosen to be repeatedly palpable, and not to give the best definition of the

joint axis. The joint centre and axis is estimated based on anthropometric data, derived

from empirical cadaveric data. This use of palpable bony landmarks makes this

technique more susceptible to the experience of the researcher than the functional

method (36,39).

2) Functional method: the functional joint centre and axes are defined based on movements

of the body segments relative to each other. The data of these movements is acquired

during a series of dynamic trials. Using this technique on the hip is challenging because

the hip joint can move in multiple planes. An important advantage is that it is less

susceptible to variation in marker placement (36,39). The functional method is

recommended by the International Society of Biomechanics (ISB) for subjects with

sufficient range of motion. It is especially preferred if an aberrant morphology of the joint

is expected (40). If the subject is not capable of carrying out the required movement

protocol, the functional method cannot be used (39,41).

IOWA Hip Score 1.7

The scoring system developed in 1963 by Carroll Larson, is still wildly used as a measurement

of clinical outcome. It separately scores aspects of function, gait, freedom from pain, absence of

deformity and range of motion. Disadvantages are the inter-observer variability and the fact that

the subject’s perception might be that the examined functional aspects are irrelevant (42).

15

2 Methodology

LCPD patients 2.1

The study population consists of 38 patients, treated with modified Shelf Acetabuloplasty in the

hospitals UZ Ghent and St.-Jan of Bruges. All patients were operated by the surgeon and

promoter Professor Dr. Plasschaert. Six patients are excluded based on co-existing pathology,

more precise a traumatic tetraplegia, osteomyelitis and other operations such as osteotomies,

leaving 32 patients. The exclusions are made to exclude factors, not related with Perthes

disease, but possibly interfering with the gait pattern. These patients were all diagnosed with

LCPD and operated between 2004 and 2014. Bilateral Perthes patients are not excluded in this

study, but are excluded from certain parts of the statistical analysis. Finally, four of the remaining

32 patients are excluded because the required X-rays are not available.

The residual 28 patients are divided in four quartiles, based on radiologic parameters for

coverage and congruence (cfr. 2.4 Radiologic evaluation of the LCPD patients). The most recent

follow-up X-ray photographs are used. No additional X-rays were made for this study (range in

time after operation: 1 – 102 months; mean: 36,73). All patients were observed on an

anteroposterior standing X-ray and a frog-leg Lauenstein X-ray. Based on the radiological

classification (cfr methodology: 2.4 Radiologic evaluation of the LCPD patients), the patients in

the best and worst outcome quartiles were included in the study2 (the mid 50% is excluded to

reduce confounding factors/noise). The best quartile will be referred to as the patients with good

outcome and the worst quartile will be referred to as the patients with bad outcome. Four

patients, two patients of the seven patients with good outcome and two patients of the seven

patients with bad outcome, choose not to participate in the study. Therefore, the two next

available patients with the best outcome out of the middle group are included to complete the

best quartile. The same is done with the two worse patients out of the middle group to complete

the worst quartile. The general characteristics of the both patient groups (i.e. age, height, weight

and leg length discrepancy) can be found in Table 2 (cfr Results: 3.1 General variables of the

groups). The final 14 patients are all inhabitants of Flanders.

2 One patient is included based on coverage and clinical evaluation. It is the worst patient out of 38 based on gait pattern and therefore this result does not affect the final result. It makes the result less reproducible but more realistic and the statistical tests more sensitive to differences between groups.

16

All patients went through both a clinical examination3 and a gait analysis. The Medical Ethical

committee of UZ Ghent approved this study and all patients signed an informed consent before

testing. Both examinations took place on the same day in the Lab of Gait analysis of the

University Hospital of Ghent; executed by the authors of this thesis, i.e. two students, second

master of medicine.

Controls 2.2In this study seven healthy controls participated. They are matched with the LCPD patients

based on age (mean: 14,7 years (SD: 3,93)). The general characteristics of the control group

(i.e. age, height, weight and leg length discrepancy) can be found in Table 2 (cfr Results: 3.1

General variables of the groups). All healthy controls are inhabitants of East- and West-

Flanders. The exclusion criteria are neurologic disorders affecting gait, pathology or operations

of the lower limbs and pelvis, inability to walk unaided and any disorder interfering with a normal

gait pattern. In the context of gait analysis, the healthy controls are recruited as reference group

to define the normal kinematics and kinetics in the frontal, sagittal and transverse plane. The

control group went through an identical clinical and gait examination as the patient group3. The

Medical Ethical Committee of UZ Ghent approved this study and the healthy controls signed an

informed consent before enrolment.

Experimental set-up 2.3

The modified Shelf Acetabuloplasty (mSA), as containment treatment for LCPD, is superior to

the classic Shelf Acetabuloplasty, regarding post-operative advantages and stability of the graft

(cfr.1.5.1 Containment therapy). The goal is to evaluate the functional outcome of the operation.

Therefore, a gait analysis is used (43). The patient group is divided in four quartiles based on

radiological parameters as will be explained below (cfr 2.4 Radiologic evaluation of the LCPD

patients). The outer quartiles define the patients with best and worst outcome. Both quartiles are

compared based on kinematics and kinetics in dynamic trials and standing balance in a gait

assessment. The control group defines the normal hip mobility, gait and balance. The hypothesis

of the study is that the effect of the mSA lays in the influence during the healing stage and not

the final result (measured on X-ray). Therefore, patients with the best and worst X-ray outcome

3 The anthropometric data required to construct the subject-specific kinematic model with the Vicon software, is gathered during the clinical exam prior to the gait analysis.

17

are compared. If the hypothesis is correct, then both patient groups should have acceptable gait4

and balance (based on the control group) after the mSA.

Radiologic evaluation of the LCPD patients 2.4

None of the classifications, described in the introduction (cfr 0 1.4 Radiological techniques and

classifications), are found to be applicable in the context of our study and for our study

population, as they need to be applied during the fragmentation phase of the disease or at

skeletal maturity (8). The follow-up time differed largely amongst the patients in this study and

largely exceeded the stage in which these classifications do apply.

The Mose classification is not used because of the limited discriminative possibilities for the

patients in this study. Therefore, another approach is chosen, which is explained below.

In order to determine the best and worst 25% of the patients, a ranking variable is created based

on two sets of quantitative variables. The first set of variables: the CEA (left/right), SA(left/right),

SR, FHSR and the FHCR (left/right) determines the coverage. The second set determines the

congruence of the hip. Only one variable, has proven to be sensitive to our patient group, the

SDS. Therefore, only the SDS is used to score congruence. The measurement protocol of each

parameter can be found in the appendix (cfr Appendix: 6.2 Radiographic parameters). The

coverage variables are measured using Autodesk® Graphic version 3.0.1. The SDS

measurements are made using GeoGebra 3.0.4.0.

Both coverage and congruence variables are equally important in the overall ranking system. All

variables are measured by two independent observers and compared based on the intraclass

correlation coefficient (ICC) (44). The ICC shows significance (P<0,001) for all variables. The

statistic calculations are performed using SPSS statistics version 23. Primary, the 5 coverage

variables are combined into one coverage variable. Subsequently a ranking variable is created

by combining the coverage variable and congruence variable.

2.4.1 Pre-processing

The coverage variable is based on the combination of five variables (cfr. 2.4 Radiologic

evaluation of the LCPD patients). The only patient with bilateral Perthes, was bilaterally

operated, and only the worst side is included in further analysis. All variables are continuous, but

differ in variance. In order to use the PCA (cfr. 2.4.2 Processing) it is preferable to normalise the 4 As defined by the control group.

18

variance (45). For this reason, the variables of the coverage and congruence are both

standardized by creating the z-scores (� � ����� ��� ��������

�����������������) (46), and rescaled to a

range between 0 and 1 (� ������ �!"#$#"�"�%

"�&#"�"�%.

2.4.2 Processing

Left with five coverage variables, there was a further dimension reduction based on the PCA.

Due to lack of an outcome variable or a variable describing each patient’s condition it is not

possible to use regression techniques to determine the weight for each variable. For this reason,

the PCA is used for both a dimension reduction and the determination of the weight of the PCA

components (45). The 5 variables can be reduced to 3 principle components with a 7% loss of

information by observer 1 and 11% by observer 2. Applying the K-means clustering technique it

is possible to subdivide the patients in quartiles (47). However, the scatterplot (Graph 1) shows

an important spread of the data. Consequently, K-means clustering will most likely not be able to

identify clearly separated clusters. Therefore, the components are combined to one coverage

variable as follows:

First, the three continuous components are categorized into 10 groups in order to enlarge the

differences. To each component a weight is ascribed based on the importance of the PCA

calculation5 assigned to the components (cfr. Table 1) (45)

('�()*+��,-�.�.+ ���/#�$0 �%%�2�3�4��5������

��/#�$0 �%%�2�3��������5������4��5������).

The weighted sum of the components constitute the coverage variable, i.e. coverage variable =

W1*C1 + W2*C2 + W3*C3 (Sum of the weighted Principal Components)6. Finally, the coverage

variable and the congruence variable (only consisting of the SDS) are add up to form the final

ranking variable.

5 The % of Variance is used as measure to define the importance given to each component by PCA. 6 Weight component 1 : 2,864; Weight component 2: 1,446; Weight component 3: 1 (set as the reference weight).

19

The patients are also evaluated by Professor Dr. Plasschaert based on his clinical expertise.

Eleven of the fifteen patients are classified in the same quartile, which is quite acceptable as, in

previous studies the interobserver reliability of the on-sight X-ray evaluation was found to be

poor (20).

Table 1 : Principal Component Analysis (PCA) Output: weigth Component 1: 2,864; weigth Component 2: 1,446; weigth Component 3: 1.

Graph 1: Scatterplot of the PCA components, based on the three used components

20

Gait Analysis 2.5

2.5.1 Technical specifications of the lab for motion analysis of the UZ Ghent

The Cerebral Palsy Reference Centre UZG houses a 24 x 16 megapixel camera motion capture

system (VICON Motion SystemsTM, Oxford, United Kingdom).

3D data is collected at 100 frames per second in this study, using the infrared motion capture

combined with force plate data derived from five force platforms (KistlerTM Instrument

Corporation, Amherst, New York, U.S.) located in the walkway. Conventional digital video

(movie) data, for the transverse, sagittal and coronal plane, is synchronously collected for each

trial.

Kinematic, kinetic and video data are collected and processed using Nexus® 2.6.1. (VICONTM

Motion Systems, Oxford, UK) and data presented using Polygon® 4.3.3 (VICONTM Motion

Systems, Oxford, UK)

The dimensions of the walkway in the gait lab are specified in the appendix (cfr. Appendix:

Figure 3).

2.5.2 Positioning of the markers:

Two versions of the Plug-in-Gait® model (VICON Motion Systems) are used in this study, i.e. for

the predictive method (PiG) and for the functional method (PiG-Matlab). The models and 3D

retroreflective markersets are based on the model described by Davis et al. (35). The standard

Plug-in-Gait® model (PiG) has been in clinical use in many labs for some years. A recent

revision written in Matlab (PiG-Matlab) takes advantage of new methods of analysis of specific

dynamic/functional trials to calculate the knee flexion/extension axes and hip joint centre

locations, using these in place of empirically derived hip joint centre and knee axis locations. The

methods for utilising the function joint and joint axis locations are implemented as a series of

Nexus plug-in routines connected as an “Advanced Gait Workflow” (AGW)

Markers are placed at the seventh cervical vertebra, tenth dorsal vertebra, right scapula,

posterior superior iliac spine, incisura jugularis, transition sternum-xyphoid, anterior superior iliac

spine, lateral collateral ligamentum of the knee, dorsum of the foot in line with the second

metatarsal bone, lateral malleolus and on the Achilles tendon at the level of the longitudinal axis

of the foot.

Markers are also positioned at the lateral side of the upper leg and lower leg (approximately

halfway) and on the ventral side of the upper leg, above and below the knee. In order to

21

minimise the influence of muscle contractions during gait, careful attention is payed during the

positioning of the markers (positioned as little as possible on the muscle belly). The marker

below the knee is positioned on the margo anterior of the tibia. Marker placement is illustrated

below in Figure 2. The subjects are asked to wear clothes not covering any of the markers at

any moment of the gait analysis. During the gait analysis subjects are barefoot.

Figure 2: Positioning of the markers conform the PiG-Matlab Model.

CLAV: clavicular (incisura jugularis); STERN: sternum; C7: cervical vertebral 7; D10: thoracal vertebral 10; RBAK: back of the right scapula; RASI/LASI: right and left anterior superior iliac spine; RPSI/LPSI: right and left posterior superior iliac spine; RTHI/LTHI: right and left tigh; RTHIA/LTHIA: right and left tigh additional marker; RKNEE/LKNEE: right and left knee; RTIB/LTIB: right and left tibia; RTIBA/LTIBA: right and left tibia additional marker; RANK/LANK: right and left ankle; RTOE/LTOE: right and left toe; RHE/LHE: right and left heel.

22

2.5.3 Sequence of the gait analysis

2.5.3.1 Calibration

Calibration is carried out at the start of each gait analysis.

2.5.3.2 Static analysis

Knee Alignment Devices (KAD’s)(© Motion Lab Systems, Baton Rouge, USA) (48) are used

during a standing static trial in PiG. When a KAD is used, the flexion-axis of the knee is

calculated using the VICON Clinical Manager Software application of Oxford Metrics Ltd. (VCM),

applying the empirical predictive method (cfr 1.5.3 Construction of the 3D-model). Once the axes

are calculated, the KAD is removed and medial knee markers are placed.

2.5.3.3 Advanced Gait Workflow (AGW) lower body

Following the PiG Static Trial, the subjects go through the AGW lower body protocol. This

protocol is used to recalculate the hip and knee axes, using the functional method (cfr. 1.6.3

Construction of the 3D-model). During the protocol the subject is asked to perform a combined

movement of the hip: pure anteflexion, anteflexion-abduction, pure abduction, abduction-

retroflexion and pure retroflexion. To determine the knee axis, the subject is asked to perform

about seven flexions of the knee. For the hip movement as well as for the knee flexions, the

subjects are asked to return to the anatomical position after each movement, before going

through with the subsequent movement. The combined movements of the hip and the flexions of

the knee are carried out once for each leg and the subjects are asked to carry them out in a way

that is comfortable (not forcing themselves to exceed their usual range of motion.)

2.5.3.4 Dynamic analysis

After estimating the joint axes for the lower limbs by means of the static analysis and performing

the AGW lower body protocol, the data required to construct the kinematic model is collected

and the dynamic analysis is executed. The subject is asked to walk on the walkway, from one

end to the other (following the longitudinal axis; cfr. Figure 3), at a self-selected comfortable

walking speed, in a straight line. For each subject at least 15 trials are collected to make sure at

least five runs can be withheld, that include a correct foot-force plate contact for both the left and

right foot. A correct foot-force plate contact is defined as an isolated foot contact on the force

plate, within the borders of the force plate, and during a natural, comfortable walk (a hesitant

contact should be avoided). Attention is payed to the fatigue level of the subject.

23

2.5.3.5 Balance analysis

The balance capabilities of the subject are assessed during unipodal stance. The subject is

asked to hold the unipodal position for 30 seconds, eyes closed and standing on a single force

plate. The test is performed whilst standing on each leg in turn.

2.5.4 Data processing – gait analysis

Standard reconstruction and trajectory labelling techniques are used to process the 3D data

before running the two modelling procedures for PiG and PiG-Matlab.

IOWA Hip Score 2.6In this study, the decision is made to reduce the IOWA hip score to the parameters 'pain free'

and 'function' (cfr. Appendix: 6.3 IOWA Hip Score (chart)) . The score is based on the subjective

experience of the patient and given by the researcher after questioning the patient. The score is

given by the researcher to exclude the risk of incorrect interpretation of the scale by the patient

(e.g. one of the patients wanted to give himself a score of 35, the maximum, for 'pain free', but

after further questioning by the researcher, the patient declared knee pain was present after

physical exercise. Knee pain can originate from the hip and the patient was therefore not given

the maximum score by the researcher (49).

Data Analysis 2.7During the gait assessment 21 outcome parameters of the hip are measured for both affected

and unaffected side in the two patient groups and the control group. The 21 parameters consist

of 18 dynamic parameters (11 kinematic and seven kinetic parameters), step time and two

standing balance variables. All parameters are derived from either the PiG model or the PiG-

Matlab model.

2.7.1 Kinematics

2.7.1.1 Sagittal Plane

(1) Hip Maximum Flexion(°): is calculated as the maximum of the hip flexion during gait at

comfortable speed.

(2) Hip Maximum Extension(°): is calculated as the maximum of the hip extension during gait

at comfortable speed.

(3) Hip Range of Motion(°): the hip range of motion is calculated as the difference between

24

maximal hip flexion and maximal hip extension. It describes the range of motion in the

sagittal plane during a comfortable gait speed.

(4) Anterior Pelvic tilt(°): is calculated as the maximum of the pelvic tilt during gait at

comfortable speed.

2.7.1.2 Frontal Plane

(5) Hip Maximum Abduction(°): is calculated as the maximum hip abduction during gait at

comfortable speed.

(6) Knee Maximum Varus(°): is calculated as the maximum knee abduction during gait at

comfortable speed.

(7) Knee Maximum Valgus(°): is calculated as the minimum knee abduction during gait at

comfortable speed.

(8) Knee Mean Varus(°): is calculated as the mean knee abduction during gait at comfortable

speed.

(9) Pelvic Minimum Obliquity(°): is calculated as the minimum pelvic obliquity during gait at

comfortable speed.

2.7.1.3 Transverse Plane

(10) Hip Maximum Internal Rotation(°): is the maximum internal rotation during gait at

comfortable speed.

(11) Hip Maximum External Rotation(°): is the maximum external rotation during gait at

comfortable speed.

2.7.2 Kinetics

2.7.2.1 Sagittal Plane

(12) Hip Extension Moment First Peak(Nm/kg): Is calculated as the first extension moment

peak during a cycle, meaning the maximum in the first 60% of a cycle, during gait at

comfortable speed.

(13) Hip Maximum Flexion Moment (Nm/kg): is the maximum of the flexion moment during

gait at comfortable speed.

2.7.2.2 Frontal Plane

(14) Hip Maximum Abduction Moment (Nm/kg): is calculated as the maximum of the hip

25

abduction moment during gait at comfortable speed.

(15) Hip Mean Abduction Moment (Nm/kg): the mean abduction moment is the mean of all

frames in a cycle during gait at comfortable speed.

(16) Knee varus moment (Nm/kg): is the maximal varus moment during gait at comfortable

speed.

2.7.2.3 Transverse Plane

(17) Hip Maximum Internal Rotation Moment (Nm/kg): is the maximum internal rotation

moment during gait at comfortable speed.

(18) Hip Maximum External Rotation Moment (Nm/kg): is the maximum external rotation

moment during gait at comfortable speed.

2.7.2.4 General

(19) Step Time (s): is defined as the amount of time spent during single step. It is the time

between heel strike of one side and heel strike of the contra-lateral side.

(20) Balance Path Length (mm): is the total distance (sum of all separate paths) covered

during a balance test of 30s.

(21) Balance Path Velocity (mm/s): is defined as the ratio of Path Length to Balance time.

Balance time is defined as the time a subject could hold the demanded balance position.

The maximum demanded time was 30 seconds.

26

Statistical Analysis 2.8The statistical analysis consists of five parts:

1) The possible presence of confounding factors is checked.

2) A comparison is made between the results obtained from the Plug-in-Gait (PiG) and

Matlab (PiG-Matlab) models, in order to determine which model should be used.

3) A comparison is made between the gait and balance data from the healthy controls, the

good outcome patients and the bad outcome patients using a group comparison.

4) The unaffected side and affected sides are compared within each group.

5) The correlation between IOWA function score and IOWA pain score on the one hand and

the dynamic variables on the other hand is tested.

The significance level is set on α < 0,05. The SPSS Software package version 23 is used.

2.8.1 Comparison of the PIG and the functional (PiG-Matlab) model

In the data collection process the data for both gait models (PiG and PiG-Matlab) are

simultaneously measured. Therefore, a perfect pairwise comparison of the exact same trial,

cycle and subject is possible, excluding the interference of any confounding factor. The only

difference in the outcome is the difference in the processing of the data and the identification of

the correct joint axis. In the comparison of the models a pairwise analysis is performed for all

variables and the affected and unaffected side are tested separately. The comparison is done by

performing the Wilcoxon test or Sign test (asympt. Sign. (2-tailed)), depending on the

symmetricality of the data distribution.

2.8.2 Group comparison

The comparison between the control group, the patient group with good outcome and the patient

group with bad outcome, is both carried out using the data of the separated trials7 as well as for

the means8 of the trials per subject.

The normality of the distribution of each variable is analysed by means of the Shapiro-Wilkinson

test. The Shapiro-Wilkinson test is used because the test is considered to be more robust than

the Kolmogorov-Smirnov test for small sample sizes, which applies here. The normality is tested

7 The separate trials are only tested for the PiG Model. The reason is explained later in 3.2 Gait and balance variables comparison. The means are tested in both models and compared. 8 The means are calculated based on at least seven trials for each patient.

27

for the population as a whole and for the groups separately. The null hypothesis states that the

data has a normal distribution, if a not-significant result is found, the null hypothesis is not

rejected. Further testing is done by performing the Levene’s test. The Levene’s test analyses the

homogeneity of variances. This protocol is also used for the side comparison and the correlation

testing.

The group comparison between all three groups is tested by means of the non-parametric

Kruskall-Wallis test (asympt. Sign. (2-tailed)) for continuous variables. For each variable, all four

assumptions9 of the Kruskal-Wallis test are fit. The null hypothesis states that all samples are

originate from the same population. The Mann-Whitney U-test is performed to compare the

scores of the two patient groups for IOWA function score. The Fisher’s exact test is used for the

categorical variable IOWA pain score (the conditions of the chi-square test are not met (50)). If

needed, the Mann-Whitney U-test is used as the post-hoc test for the continuous variables, to

determine between which groups the significant difference is located (α < 0,015 after Bonferroni

Adjustment for three samples10. A P-value between 0,015 and 0,05 is accepted as a possible

trend.) The comparison of the affected and unaffected side is done separately. For the healthy

control group both sides are unaffected. The ‘unaffected’ side of the bilateral affected patient,

classified in the bad outcome patient group, is excluded from the group comparison of the

unaffected sides. Both sides are excluded from the side comparison, since the 'unaffected' side

cannot act as a healthy control.

To check for possible confounding variables a comparison of the groups is performed for the

general variables: Age, Length, Weight, Leg length discrepancy, Follow-up time since shelf and

Age at time of operation.

2.8.3 Side comparison

The side difference of the affected and unaffected side of the patients (the affected and

unaffected side are considered to be paired) is assessed by the Wilcoxon test or Sign test

(asympt. Sign. (2-tailed)), depending on the symmetricality of the data distribution. The

symmetricality is assessed using a boxplot plotting the distribution of the differences between

9 The assumptions for the Kruskal-Wallis test are: 1) k > 2 (k: independent samples), 2) continuous or ordinal variable, 3) not parametric continuous variable; 4) number of each sample is at least 5. 10 Bonferroni adjustment is the significance level (α) divided by the number of possible paired tests (N) between samples, N is based on the number of sample means (n).

6 � 789:� ; <�� � �

= > �

$�$�?%

@

28

the affected and unaffected side. Only the means of the trials for each subject are used in further

analysis. The means are based on the average of 7 to 10 trials for each patient.

2.8.4 Correlation IOWA – gait variables

In order to explore correlations between the IOWA function score and IOWA pain score on one

hand and the gait variables (kinematics, kinetics, Step Time and balance variables) the

Spearman rank coefficient is used. The conditions for the Pearson correlation coefficient11 are

not met for the continuous variable IOWA function score and the ordinal variable, IOWA pain

score.

11 Conditions for the Pearson correlation coefficient: 1) the variables need to be continuous and 2) have a normal distribution (50).

29

3 Results

General variables of the groups 3.1When comparing the general variables (Age, Length, Weight, Leg length discrepancy, Follow-up

time since mSA and Age at time of operation) of the healthy controls, the good outcome patients

and the bad outcome patients, no significant differences are found. Consequently, no

confounding variables are identified (cfr. Table 2).

Gait and balance variables comparison 3.2In the dynamic trials eleven kinematic and seven kinetic variables are statistically analysed

based on the averages of the trials (cfr. 2.8.2 Group comparison). Primary the three groups are

overall tested for both kinematic and kinetic variables. Followed by a comparison between the

affected and unaffected side within each patient. Both the PiG-Matlab model and the PiG model

are statistically analysed using the same tests, therefore a comparison between both models is

possible. In the last phase of the analysis, differences between both models are tested.

When the separate trials (not the averages) are compared between the sides almost every

variable seems to be significantly different for the patient groups and even in the control group

six variables are significant (Hip Maximum Extension, Hip Range of Motion, Hip Maximum

Abduction, Hip Maximum Flexion Moment, Hip Maximum Abduction Moment, Hip Mean

Abduction Moment). In order to reduce confounding factors and compensate for the variance

between both sides within the same trial, the averages of the separate trials of each patient are

used. After this analysis a more clinical relevant result is obtained.

In order not to overload the results section, only the PiG-Matlab analysis is presented, which

Table 2: overview general variables study population (SD = standard deviation) (* Follow-up time is the time elapsed since mSA operation)

30

seems after further analysis the most superior model for this study. The reasoning for this

superiority is presented and explained in the discussion (cfr. 3.3 Differences between both gait

analysis models). This form of presenting the results is in no way to reduce the quality of the

study, but to bring brevity and structure to the results. The interested reader is referred to the

Appendix, in which all PiG data and analysis is presented (cfr. Appendix: 6.4 Results PiG Model)

3.2.1 Group comparison PiG-Matlab Model

3.2.1.1 Comparison of the unaffected sides

The comparison of the unaffected sides, between the three groups in the PiG-Matlab model,

based on the Kruskal-Wallis test, shows no significance for 15 variables (0,063 < P-value <

0,961). For Hip Maximum Extension, Hip Maximum Abduction and Anterior Pelvic Tilt a

significant difference between the groups is detected (0,015 < P-value < 0,038).

The significant variables indicate a difference between the three groups. Therefore the

unaffected side of the patients can only be used for the not-significant variables as the ‘perfectly

matched healthy control’ in the side by side comparison (cfr 3.2.2 Side comparison PiG-Matlab

Model). After performing the post hoc Mann-Whitney U-test in the PiG-Matlab model, no

significant differences are found for Hip Maximum Abduction and Anterior Pelvic Tilt. The

variable Hip Maximum Extension shows a significant difference in the comparison of the control

group and the bad outcome patients (P-value: 0,014) and a trend is detected after post hoc

comparison of the good and bad outcome patients (P-value: 0,022) (Graph 2). A trend is

detected for Hip Maximum Abduction between the controls and the bad outcome patients (P-

value: 0,022) (Graph 3). The variable Anterior pelvic Tilt shows a trend between the controls and

the bad outcome patients (P-value: 0,022) (Graph 4).

No significant differences are detected between the control group and the good outcome

patients (0,073 < P-value < 0,318).

31

3.2.1.2 Comparison of the affected sides

In the PiG-Matlab model, the variables Hip Maximum Extension (Graph 2), Anterior Pelvic Tilt

(Graph 4) and Hip Range of Motion (Graph 5) are shown to be significantly different when

Graph 3: Box plot of Hip Maximum Abduction (º); Grey : affected side, Black : unaffected side; separately the controls (n=7), good outcome patients (n=7) and the bad outcome patients (n=6). The dot represents an outlier (number = patient number). M = median.

M: 8,2

M: 12,1

M: 10,7

M: 8,0

M: 10,7

M: 5,3

Graph 2: Box plot of Hip Maximum Extension (º); Grey : affected side, Black : unaffected side; separately the controls (n=7), good outcome patients (n=7) and bad outcome patients (n=6). The dot represents an outlier (number = patient number). M = median.

M: -9,5 M: -9,3

M: -3,6

M: -6,3

M: 10,9

M: -1,3

Graph 4: Box plot of Anterior Pelvic Tilt (º); Grey : affected side, Black : unaffected side; separately the controls (n=7), good outcome patients (n=7) and bad outcome patients (n=6). The dots represent outliers (numbers = patient numbers). M = median.

M: 11,6 M: 11,2

M: 15,1 M: 15,2

M: 25, 4 M: 25,7

32

comparing the three groups (0,004 < P-value < 0,025). For the other variables no significant

differences are found (0,198 < P-value < 0,872). Further exploration of group differences,

applying Mann-Whitney U-tests, reveals the following results: significant differences between the

controls and the bad outcome patients for the variables Hip Maximum Extension, Hip Range of

Motion and Anterior Pelvic Tilt (0,001 < P-value ≤ 0,011). No significant result is detected when

comparing the healthy controls and the good outcome patients, however a trend is found for Hip

Range of Motion (P-value: 0,038). When comparing both patient groups, a trend is found for Hip

Maximum Extension (P-value: 0,026).

3.2.1.3 Step Time

No significant difference between the groups is found for this variable, both for the unaffected (p-

value: 0,581) and for the affected side (p-value: 0,71).

3.2.1.4 Balance standing

The group comparison reveals that the groups do not differ statistically when comparing the

unaffected and affected sides for the variables Balance Path Velocity and Balance Path Length

(P-values resp. 0,838 (unaff. side), 0,233 (aff. side) and 0,078 (unaff. side), 0,306 (aff. side)).

3.2.2 Side comparison PiG-Matlab Model

The affected and unaffected side are pairwise compared within the groups, using the average

values.

Graph 5: Box plot of Hip Range of Motion (º); Grey : affected side, Black : unaffected side; separately the controls (n=7), good outcome patients (n=7) and bad outcome patients (n=6). The dot represents an outlier (number = patient number). M = median.

M: 47,6 M: 46,6

M: 40,8

M: 46,8

M: 37,9

M: 43,0

33

3.2.2.1 Control group

Within the control group, no significant difference is shown based on the PiG-Matlab model

(0,125 < P-value < 1,000). Step Time and the Balance Variables are also not significant (0,453 <

P-value < 1,000).

The null hypothesis indicates no differences between the left and right sides of the control group.

3.2.2.2 Good outcome patients

The PiG-Matlab model shows no significant results for all variables (0,125 < P-value < 1,000).

No significant difference is found for Step Time (P-value 0,219) and the balance variables (0,375

< P-values < 1,000).

3.2.2.3 Bad outcome patients

Three variables are significant as indicated by the PiG-Matlab model: Hip Maximum Flexion

(Graph 6), Hip Range of Motion (Graph 5) and Hip Maximum External Rotation Moment (P-

values: 0,031) (Graph 7).

As in the control group and the good outcome patients no significant difference is found for Step

Time (P-value: 1,000) and the balance variables (P-values: 0,687).

Graph 7: Box plot of Hip Maximum External Rotation Moment (Nm/kg); Grey : affected side, Black : unaffected side; separately the controls (n=7), good outcome patients (n=7) and bad outcome patients (n=6). The dots represent outliers (numbers = patient numbers). M = median.

M: -0,10 M: -0,10 M: -0,08

M: -0,11 M: -0,06

M: -0,12

Graph 6: Box plot of Hip Maximum Flexion (º); Grey : affected side, Black : unaffected side; separately the controls (n=7), good outcome patients (n=7) and bad outcome patients (n=6). The dot represents an outlier (number = patient number). M = median.

M: 39,1 M: 38,7

M: 39,5 M: 40,2

M: 44,2

M: 49,2

34

3.2.3 Differences between both gait analysis models

For the hip variables significant results are shown for Hip Maximum Flexion (aff. and unaff. side)

Graph 10: Box plot of Hip Maximum External Rotation(º) ; Grey : affected side, Black : unaffected side; separately the controls (n=7), good outcome patients (n=7) and bad outcome patients (n=6). The dot represents an outlier (number = patient number).M = median.

M: -12,8 M: -9,0

M: -7,3 M: -7,9

M: -13,8 M: -17,9

Graph 9: Box plot of Hip Mean Abduction Moment (Nm/kg); Grey : affected side, Black : unaffected side; separately the controls (n=7), good outcome patients (n=7) and bad outcome patients (n=6). The dot represents an outlier (number = patient number). M = median.

M: 0,30

M: 0,42

M: 0,34 M: 0,38 M: 0,39

M: 0, 43

M: 0,59

M: 0,77

M: 0,70 M: 0,71 M: 0,69

M: 0,78

Graph 8: Box plot of Hip Maximum Abduction Moment (Nm/kg); Grey : affected side, Black : unaffected side; separately the controls (n=7), good outcome patients (n=7) and bad outcome patients (n=6). The dot represents an outlier (number = patient number). M = median.

35

(P-value: 0,006), Hip Maximum Abduction (aff. and unaff. side) (P-values < 0,001), Hip

Maximum Internal Rotation (aff. and unaff. side) (P-value < 0,001). All knee kinematic variables

in the frontal plane show a highly significant result (0,001 < P-value < 0,005).

IOWA Hip Score 3.3

3.3.1 Comparison of the patient groups

No significant difference between the patients with good and bad outcome is found for IOWA

function score (P-value: 0,784) and IOWA pain score (P-value: 1,000) (Graph 11).

Note that none of the patients were given a point for ability to drive, because none of them had

acquired a driver’s licence yet. The data for one of the patients within the group with good

outcome, is missing.

3.3.2 Correlations IOWA – gait variables

If the correlation is calculated including all patients, a significant correlation is found between

IOWA function score and Balance Path Velocity of the unaffected side (r =0,678) and between

the Balance Path Length of the affected side (r = -0,588).

When the correlation is calculated, including only the patients with good outcome, a significant

correlation is found for IOWA function score and Hip Maximum Flexion of the affected side (r

=0,788).

Graph 11: bar chart IOWA pain score (/35pt); Grey: patients with good outcome (n=6), Black: patients with bad outcome (n= 7).

36

When considering the patients with bad outcome, significant correlations are found for IOWA

function score and Hip Maximum Flexion of the affected side (r =0,805), IOWA function score

and Hip Maximum Internal Rotation of the affected side (r =-0,823), IOWA function score and

Maximum and Mean Varus of the knee of the affected side (r for both = -0,842), IOWA pain

score and Pelvic drop at the affected side (r = -0,917), IOWA function score and Hip Extension

Moment First Peak at the affected side (r =0,805), IOWA function score and Hip Maximum

Internal Rotation Moment at the affected side (r =0,805) and for IOWA function score and

Balance Path Length of the affected side (r =0,823).

37

4 Discussion

The research question 4.1Until today there is no uniformly accepted treatment protocol for Legg-Calvé-Perthes disease

(LCPD). The different stages of the disease have been defined, but the etiological background

remains not fully understood. Treatment has therefore been based more on an empirical basis

and historical series. Most of current management however is based on the ‘principle of

containment’ (4).

So far, there is a lack of full understanding on how specific treatment types for LCPD can lead to

an optimal (long-term) clinical outcome. Treatment is usually guided by clinical examination and

radiological follow-up, focusing on maintaining a spherical femoral head in the end stages of the

disease (43).

Studies focusing on the functional outcome of surgical treatment for Perthes are very sparse

(43). Our research aims to fill this void. Furthermore, this series studied is unique since it

focuses on a novel surgical technique alleviating the use of cumbersome hip spica casts (32).

Our thesis therefore focuses on the functional (more than radiological) outcome of modified

Shelf Acetabuloplasty (mSA) in the treatment of LCPD by collecting objective data, derived from

gait analysis.

Discussion of the results 4.2

4.2.1 Gait model

In this gait analysis study, two models are simultaneously applied, (a) the standard Plug-in-Gait

model and (b) a functional version of the Plug-in-Gait model (based on Davis’s model) (35). Both

models are compared, in order to allow for a functional evaluation of the modified Shelf

Acetabuloplasty, based on the clinically most valid model. In the PiG model, joint centres are

empirically estimated based on cadaveric studies (39). However, caution is needed when

applying the model to LCPD patients. LCPD causes an extrusion of the femoral head and

therefore leads to a more lateral position of the hip joint centre (51). Therefore, the empirical

based location of the hip joint centre should be questioned. For this reason, within this study

both models (a and b) are applied and derived measurement results compared.

In the comparison of these models, first the knee variables: Maximum Varus, Maximum Valgus

38

and Mean Varus are compared as a quality measure for the Knee Alignment Device (KAD)

placement. All three variables are shown to be significantly different (0,001 < P-value < 0,006) in

an overall comparison between both models, including all subjects. In order to determine the

clinical meaning of this significant difference, the control group is used to compare the absolute

results. A threshold of 5° is set to define clinically relevant differences between both models12.

The differences found for the knee variables, do vary from 6,8° to 18,0° (cfr. Table 5

(Appendix)). As the differences between the two models exceed the threshold, they are

considered to be clinically relevant. Based on these findings one should question the placement

of the KAD and its benefit when studying (paediatric) patients with LCPD.

Secondly, the variables important to this study are compared: Hip Maximum Flexion (P-value:

0,004) (-2,5°), Hip Maximum Abduction (P-value < 0,001) (7,7°) and Hip Internal Rotation (P-

value < 0,001) (14,2°) are shown to be significantly different (cfr. Appendix: Table 5). Note that

Hip Maximum Flexion is statistically significant, but considered not to be clinically relevant,

because of the threshold set at 5°.

In the further report of this study the functional model, i.e. PiG-Matlab, will be used. This decision

is based on the following:

- The aberrant hip joint centre location in LCPD (due to extrusion of the hip and femoral

head deformation (51), using the functional model, is defined based on the functional

joint centre and not an empirical estimation thereof.

- Using the PiG model, varus angles are observed exceeding 17º, for the healthy subjects.

This does not correspond with the physiologic values during gait in healthy subjects. The

aberrant varus angles, make us question the accuracy of the KAD.

- In contrast with other diseases often studied by gait analysis, such as cerebral palsy, the

LCPD patients included in this study do generate sufficient range of motion and muscle

power in hip and knee. This enables one to calculate the hip and knee axis based on

joint motion, and alleviates the use of the KAD.

- The gait lab, used in this study, does provide with sufficiently accurate and sensitive

equipment to apply the functional model (PiG-Matlab) correctly (52).

12 McGinley et al. suggested that errors in excess of 5° should raise concern and may be large enough to mislead clinical interpretation (38).

39

4.2.2 Overall group comparison13

Westhoff et al. did describe gait pattern differences in LCPD patients (during the florid stage of

the disease) when compared to a control group.

The affected side showed an increased anterior pelvic tilt, decreased range of motion (ROM)

and a decreased extension, both of the hip. In the unaffected side an increased ROM was

observed, due to increased maximal hip flexion (53).

At the contrary, a study of Stief et al. observed a normalisation of hip flexion and extension after

containment therapy (i.e. femoral varus osteotomy combined with a Salter osteotomy) (54).

The results observed within our study do support the findings of Westhoff et al (53). In the

overall group comparison, both the affected and unaffected side show a significantly increased

Anterior Pelvic Tilt. After post hoc analysis, a significant difference for the affected side (+9,2° )

and a trend for the unaffected side (+9,6° ) were shown to exist between the controls and the

ones classified as ‘bad outcome patients’.

When compared to the control group, a significant reduction of Hip ROM (-11,8°) was detected

for the affected side of the patients with bad outcome. This is in agreement with Whesthoff et al.

(55).

Our results do show a reduced Hip ROM, due to a significant reduction of Hip Maximum

Extension of the affected side (-15,3°). The Hip Maximum Extension of the bad outcome patients

is borderline-missed significantly reduced (-9,3° ) when compared with the good outcome

patients.

Although no firm conclusions can be made, there seems to be a gradient in the degree of Hip

ROM reduction of the affected side, dependent on the radiographic outcome of LCPD (Graph 5).

Westhoff et al did hypothesize that the decreased Hip ROM and Hip Maximum Extension in the

affected hip in LCPD are part of (developed) strategies:

- Hip ROM is reduced in order to lessen hip joint loading.

- The decrease in Hip Extension prevents the intra-articular pressure from peaking.

- An aberrant gait pattern, primarily caused by the LCPD, becomes permanent due to soft

13 Differences between both legs of the controls should be taken into account if there are greater than 1°, and therefore, any difference greater than 1° shall be reported.

40

tissue changes at the ventral side of the hip. Even if the primary cause is resolved (55).

According to Whesthoff’s findings, a reduction of Hip Maximum Extension, should lead to a

smaller step length, if not compensated by an increased Hip ROM of the unaffected hip and

increased Anterior Pelvic Tilt (55). In our study however, neither an increase nor decrease in Hip

ROM could be detected for the unaffected side. We can therefore only partially support the

findings of Westhoff et al.

Hip abduction is almost always affected in LCPD. Hip abductor muscle weakness has been

reported as causal factor. The phenomenon of hip abductor weakness has been confirmed by

Westhoff et al. (53). It is often stated as one of the primary mobility problems in LCPD and is

often accompanied by the presence of adductor tightness (and Trendelenburg gait) (24,50,52–

55). In the overall group comparison significant differences are found for Hip Maximum

Abduction, only on the unaffected side. After post hoc evaluation no significant result can be

withheld. However, a trend of reduction could be detected for the bad outcome patients (-6,9°)

(Graph 3). The reduction of Hip Maximum Abduction of the unaffected side seems clinically

relevant (> 5° difference) (cfr. Table 5). This observation is not supported by the results for

Minimum Pelvic Obliquity, Standing Balance and Hip Maximum Abduction Moment and current

literature (53,54). For the three indirect abduction measures, i.e. Minimum Pelvic Obliquity,

Standing Balance and Hip Maximum Abduction Moment, no significant differences, nor trends,

are found for the unaffected side. The findings for the indirect abduction measures are confirmed

by the study of Stief et al. In their study a resolution of differences in Pelvic Obliquity, through the

healing process, is observed (54). Regarding the affected side, of subjects included in this study,

differences in Hip Maximum Abduction, between the controls and both the good and bad

outcome patients, are not significant. The reduction varies between <0,1° and 2,4°. This

indicates a clear absence of reduction for the affected side.

When discussing all those data one should however realise that one of the objectives of the

mSA is to maintain containment of the hip affected by LCPD (32). In order to meet this

prerequisite, the maintance of (passive) abduction of the hip needs to be seen as the goal of

treatment (in order to maintain the shape of the femoral head in the final stage of LCPD) (53). A

successful containment treatment should restore abduction of the hip in those who tend to lose it

(before the femoral head collapses and loses height of the lateral pillar) (56).

The results for the group comparison of the kinetic abduction variables support our statement

that the hip abduction is not clinically relevant affected. More importantly, these results suggest

41

that the novel surgical technique (mSA) does indeed fulfill its objective.

The comparison of the three groups and the side comparison within the groups did not show any

significant differences for Hip Maximum Abduction Moment and Hip Mean Abduction Moment.

Our findings are somewhat in line with the findings of Plasschaert et al. In their study a

significant reduction is found for maximum abduction moment, when comparing the affected side

to the unaffected side, in a patient group with poor clinical outcome (defined by an IOWA hip

score lower than 90 points) (57). In our study this reduction can also be seen in the bad outcome

patient group (Max Abduction Moment unaffected side: 0,81 Nm/kg; Max Abduction Moment

affected side 0,62 Nm/kg), but it was a non-significant and probably clinically irrelevant

reduction. This does indicate that the patients in our study do not suffer from decreased

abduction capacity at either side, at least in the short-term. It also supports the objective of the

surgical technique not to add any additional trauma to the hip abductors that could weaken them

(32).

Furthermore, we cannot compare to the study of Plasschaert et al. without paying attention to

two important differences between our study and the study of Plasschaert et al. Note that in the

study of Plasschaert et al. the hip abduction was measured in a different way, using a

dynamometer, and that the classification of patients is based on a different method. Plasschaert

et al. used a clinical classification, based on the IOWA hip score, while in our study a radiological

classification is used (57).

Our finding that there is an absence of differences regarding abduction moments, could suggest

that there is no difference in the loading of the hip joint, and that at least in the short-term mSA

has been successful in changing the natural history for those hips, where negative prognosis

was criterium for surgery.

Our findings supporting absence of abductor weakness are in line also with the non-significant

results with respect to the balance variables. The abductor muscles are of great importance in

maintaining good balance (58). In our study balance seems not to be affected, again supporting

a successful procedure in protecting the hip and maintaining its biomechanics.

In our study, no statistical differences are found when comparing the IOWA function and IOWA

pain scores of the good outcome patient group and the bad outcome patient group. The

subjective functional outcome of all patients is quite good (max 32 and min 28, scored on a scale

42

of 35 points). One of the patients is even an elite swimmer. Furthermore, the IOWA scores

makes all our patients lose at least one point, because they cannot drive a car due to age

restriction. None of the patients had already acquired their driver’s license. Pain experience in

our patients ranges from “pain free” to “pain at rest without weight-bearing”.

The relatively good scores for function and pain could support our earlier assumption that

acceptable abduction function is present in all patients included in the study population. It needs

to be noted that no significant correlation is found between the abduction variables and IOWA

function score and pain score.

Svehlik et al. described two abnormal gait patterns in LCPD. The first gait pattern is a Duchenne

gait, presenting a pelvic elevation on the swing side, and increased abduction and external

rotation during stance phase, in order to decrease the hip loading (56). Increased external

rotation is a compensation mechanism to prevent impingement, due to an anterolateral hump.

Such a hump is often present in LCPD patients and was described by Yoo et al. (59). No

statements can be made about possible Duchenne gait patterns in the patient groups, because

of the absence of processed trunk data.

A second gait pattern is the Trendelenburg gait pattern, defined by a pelvic drop to the swing

side. In our study a statistically significant difference in external rotation of the hip, between the

three groups cannot be observed. However, the difference is degrees seems clinically relevant.

Remarkably, the smallest external rotation is observed in the affected side of the patients with

good outcome (cfr. Table 5). The good outcome patient group is also the group in which the

largest internal rotations are observed for the affected side. The phenomenon of the decreased

external rotation of the affected side of the good patients, remains unclear. No assertions were

found to state this observation. The absence of an abnormal gait pattern, pelvic abnormalities

and step time could not lead to a causal or suggesting factor for this aberrance. However, the

general trend of increase in external rotation for both affected and unaffected side, in relation to

the radiological outcome of the disease could be in agreement with Svehlik et al.(56). Further

analysis of causality should bring more clarity on the matter.

The absence of differences for Pelvic Obliquity, Hip Maximum Abduction Moments and Standing

Balance do support the assumption that involvement of hip abduction is most likely not clinically

relevant. Pelvic obliquity is an indicator for a Trendelenburg gait pattern. Absence of this gait

pattern is observed in both good and bad outcome patients. The absence of a Trendelenburg

gait pattern results in normal hip loading and does result in the fact that the hip coverage during

43

gait is not compromised (53).

4.2.3 Side by side comparison

Differences between both sides in the control group are analysed as a quality measure, as both

legs are assumed to be normal. As expected, neither significantly, nor clinically relevant

differences could be observed between both sides of the control group.

The patients with good outcome show no side differences.

In the bad outcome patients, significant Hip ROM reductions (-10,7º) are detected together with

a significantly reduced Hip Maximum Flexion (-5,0º). Note the differences in degree of reduction

(-5,8º) between the good and bad outcome group for the Hip ROM (cfr. Table 5). The Hip

Maximum Extension is not analysed for the patients with bad outcome, because the unaffected

side is statistically different from the control group and can therefore not be seen as a matched

healthy control side to compare with the affected side. Therefore, no evaluation can be made

between both sides for the extension and the conclusion for the Hip Max Extension should be

derived from the analysis of the overall group comparison.

Regarding Hip External Rotation Moment, significant side differences in the bad outcome

patients are detected (0,05 Nm/kg). An explanation, based on the findings of the other variables

analysed in the present study, is not found. With respect to external rotation the increase thereof

has been described by Svehlik et al and Yoo et al. (56,59). As no significant results are found for

external rotation in this study, it’s unclear how the anterolateral hump could be an explanation for

the decrease of external rotation moment.

To our knowledge, no articles have yet reported findings for internal and external rotation

moments in LCPD patients or other hip deformities. Further research is needed to explore if hip

rotation moments in LCPD patients are consistently different from healthy controls and to

explore the role of hip rotation moments in the evolution of osteoarthritis in LCPD patients.

In conclusion, the good outcome patients show no compromised gait pattern. This indicates that

the outcome after mSA is an almost perfect gait pattern recovery for the good outcome patients.

In the comparison of both patient groups, a gradient in abnormal gait could be detected,

indicating not all outcomes are superb. The abnormalities observed in the bad outcome patient

44

group are mostly due to aberrant hip extension14. The increased or decreased ROM (depending

on the side), the increased flexion and the increased pelvic tilt are all compensation mechanisms

for reduced extension (55). The secondary soft tissue changes in the hip and their lasting effect

on the gait are the cause of the differences in extension, even if the primary effect (LCPD) is

healed, as described by Westhoff et al. (55). In future studies, the reversibility of the extension

reduction should be evaluated, in order to optimise the long-term effects on gait. The major

clinically important variables, i.e. Hip abduction, Trendelenburg gait and Hip Internal Rotation are

all normal in both patient groups. This is an important result, especially regarding Hip Abduction

and Hip Abduction Moment, because of the consequences. Especially regarding abduction, both

Hip Mean Abduction Moment and Hip Maximum Abduction Moment are not significant, indicating

the absence of both chronical overloading (mean) and peak overloading (maximum) of the hip

joint. This strongly suggests a reduction of long-term complications (such as osteoarthritis), a

major problem in LCPD.

The study design choices 4.3In this study, a radiologic classification based on the PCA technique is developed (cfr. 2.4

Radiologic evaluation of the LCPD patients). Both coverage and congruence are stated to be

equally important. After surgery, two important measurements are potentially interesting: (a) the

direct effect of the operation (evaluation of the graft placement) and (b) the long-term effect of

the operation (containment of ‘normal’ congruence).

The graft, when performing an mSA, is placed in order to maximise the coverage and to obtain a

‘normal’ hip congruence (32). Coverage and congruence are considered to be equally important,

because both variables measure a different part of the post-operative evaluation (coverage

measures the direct effect, congruence measures the long-term effect) of containment.

In the analysis of the gait data, both an overall group comparison and a side-by-side comparison

is made. It was our feeling that in a group comparison, less severe gait deviations might not be

detected. Therefore, the side-by-side comparison is used, in which the unaffected leg acts as the

perfectly matched control for the affected leg. No difference, except due to physiological

variation, should be undetected.

14 In the clinical evaluation only the Hip Abduction, Hip Internal Rotation and Trendelenburg gait is disturbed (cfr. 1.2 Clinical presentation). However the gait analysis is more sensitive to abnormalities, therefore more parameters seem to be aberrant.

45

Study limitations 4.4

One of the obvious limitations of this thesis is the relatively small population that was studied.

Only 21 subjects were included (14 patients and seven controls). This is partially due to the fact

that LCPD is a rare disease and only LCPD patients, operated by Prof. Dr. Plasschaert

(paediatric orthopaedics UZ Ghent and St-Jan Bruges) in a timespan of ten years (’04-’14),

treated by a unique mSA are included. In addition, X-ray analysis and gait analyses (incl. the

data processing) are labour-intensive and time-consuming tasks.

Despite the small samplesize, a few factors should be taken into consideration when interpreting

the results. First, in a small samplesize greater variation could be expected. In our study

however, a consistent variation is shown as observed in the graphs in the result section cfr. 3

Results). Second, despite the small samplesize, enough power is obtained because differences

are shown in the analysis. Therefore, we could state, that even if a small samplesize is used, the

results are consistent and meaningful as a first study to evaluate mSA. Additionally, possible

statistical limitations, due to the samplesize, are compensated by a careful interpretation of the

absolute variables.

In order to classify the patients into good and bad outcome groups, X-ray measurements are

used. Because of the lack of an applicable, validated and descriptive classification, this study

had to rely on the Principal Component Analysis (PCA), which is not validated yet in the context

of this study. Possible errors could be caused by incorrect classification of patients and

exclusion of the worst and/or best patients. A third limitation of the technique is the lack of

reproducibility. The PCA derives components out of a set of variables, but the recombination of

the variables to each component is dependent on the sample variation and therefore might slight

differ for each study. Consequently, no repeatable radiologic classification can be extrapolated

based on the result derived in this study. Our results should however be reproducible, even

given the variation, due to the PCA method. A few arguments support the use of PCA. The

radiographic bad outcome patients are indeed shown to have a more aberrant gait pattern than

the good radiographic outcome patients, this could imply that patients are classified

appropriately. The PCA technique is not often used in orthopaedics research, but in psychology

and engineering, it is a frequently applied statistical analysis technique and accepted as a valid

data analysis technique.

The study of Westhoff et al. states the function of the gait could not be evaluated based on

radiologic data (43). As the outcomes of the gait analysis are in line with the radiologic

46

classification, this contradicts the findings of Westhoff et al. Our results are with this respect in

agreement with the study of Svehlik et al. The study of Plasschaert et al. cannot confirm this

statement based on the hip abduction function because no correlation is found between hip

abduction and RX outcome (57).

Future research 4.5This study did focus on gait as a measure of function at an intermediary endpoint of LCPD.

Despite the fact that our work does support the value of mSA in restoring/maintaining function of

the Perthes hip, further long-term evaluation of mSA is needed. This in order to document the

effect of modified Shelf Acetabuloplasty on the development of osteoarthritis. This might allow to

correlate findings regarding osteoarthritis with gait analysis outcome variables.

Despite the fact that gait analysis does already provide data that do support clinical practice, a

further improvement of the reliability of gait analysis outcomes seems mandatory. Further

research is needed to optimise methods. We should improve the interobserver repeatability

(mainly marker placement) and determine the best-suited method for defining the joint axes in

LCPD patients. In the radiological evaluation, an objective and repeatable classification is

needed. These radiological classifications should be applicable in growing patients, since most

LCPD patients are not fully grown during at least the first years of follow-up after (surgical)

treatment.

Future studies should evaluate the effect of physiotherapy and gait training in the prevention of

Hip ROM abnormalities. If gait deviations could be prevented, no aberrant parameters will be

detected in gait analysis. In that case the mid-term outcome of containment therapy would be

optimal. Osteoarthritis, a major but long-term outcome of LCPD could then be evaluated

separate from gait abnormalities. This might enable detecting the exact cause of osteoarthritis of

LCPD: due to gait abnormalities, inherent to the disease or a combination.

Finally, the small sample size is also a limitation of our study. In order to, more reliably,

extrapolate the conclusions to a larger population, the study should be repeated using larger

sample sizes in a longitudinal setting. This would also aid in defining a more reliable definition of

‘normal gait’.

Conclusion 4.6In conclusion, the differences found in our study (Hip ROM, extension, flexion, pelvic tilt), are

47

most likely all due to a reduction of the hip extension. No possible cause for the decreased hip

extension, due to the operation could be detected. Based on the findings of Westhoff et al.,

these results are a secondary effect of LCPD. In the major clinically important variables, no

abnormalities could be detected. Absence of hip overloading, based on findings regarding Hip

Abduction Moment, is an indicator for positive long-term outcome. Therefore, we can state that

the results of mSA regarding gait outcome look very promising for patients with good

radiographic outcome, this applies even for the patients with bad outcome. Based on the

function short term outcome of the involved hip, mSA should be further applied as an operative

technique for severe LCPD patients. Further research is needed to confirm our findings more

profoundly and to further specify the role of mSA and its benefits in the treatment of LCPD.

48

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I

6 Appendix

Schematic illustration of the gait lab 6.1

Figure 3: schematic illustration of the gait lab

II

Radiographic parameters 6.2

6.2.1 Coverage and subluxation

● Sharp’s angle (SA)

The SA is measured using the classic method described by Agus et al. in their article “How

Should the Acetabular Angle of Sharp Be Measured on a Pelvic Radiograph?”: The angle is

formed by a horizontal line connecting the inferior tips of both pelvic teardrops (referred to as the

“reference line”) and by a line connecting the inferior tip of the pelvic teardrop with the lateral

edge of the acetabular roof in the unaffected side or by a line connecting the inferior tip of the

pelvic teardrop with the lateral edge of the shelf in the affected side (Figure 2).

Figure 2: Sharp's angle: SA (Sharp's angle unaffected side), SA' (Sharp's angle affected side).

● Subluxation ratio (SR)

The shortest distance (D and D’) between the most medial point of the femoral head and the

vertical line through the most inferior point of the teardrop, perpendicular to the reference line.

The ratio for the affected to the unaffected side is calculated and expressed as the subluxation

ratio (Figure 3).

III

Figure 3: Subluxation ratio: D (shortest distance unaffected side), D' (shortest distance affected side).

● Femoral head size ratio (FHSR)

The femoral head size ratio is the ratio of the femoral head size of the affected side to the

femoral head size of the unaffected side. The femoral head size is defined as the shortest

distance between the most medial and most lateral point of the femoral head (Figure 4).

A�,��89*�8B�(���8+(��ACDE%:G�,��89*�8B�(��8GG��+�B�(B��8H%

G�,��89*�8B�(��:.8GG��+�(B��8%

Figure 4: Femoral head size ratio: a (femoral head size unaffected side), a' (femoral head size affected side).

IV

● Femoral head coverage ratio (FHCR)

Femoral head coverage is measured as described by Heyman and Herndon in “Legg-Calvé-

Perthes disease; a method for the measurement of the roëntgenographic result”. Coverage is

calculated as the shortest distance between the vertical line, perpendicular to the reference line,

through the lateral edge of the acetabulum for the unaffected side (A) or through the lateral edge

of the shelf in the affected side (A’). The ratio is calculated by dividing the femoral coverage by

the ipsilateral femoral head size (Figure 5).

A�,��89*�8B��7��8)��8+(�:.8GG��+�B�(B� � G�,��89*�8B��7��8)��I%

G�,��89*�8B�(���8%

A�,��89*�8B��7��8)��8+(�8GG��+�B�(�� � G�,��89*�8B��7��8)��IH%

G�,��89*�8B�(���8H%

Figure 5: a (femoral head size unaffected side), a' (femoral head size affected side), a (femoral head size unaffected side), a' (femoral head size affected side).a (femoral head size unaffected side), a' (femoral head size affected side), A (femoral head coverage unaffected side), A’ (femoral head coverage affected side).

● De center-edge angle (CEA)

To obtain the CEA, as described by hanson et al. in “Discrepancies in measuring acetabular

coverage: revisiting the anterior and lateral center edge angles”. First, the best fitting circle

around the femoral head is drawn. Second, a vertical line, perpendicular to the reference line,

and through the centre of the circle is drawn. The CEA of the unaffected side is defined by the

ventrical line and a line connecting the centre of the circle with the lateral edge of the acetabular

roof. The CEA of the affected side is defined by the vertical line and a line connecting the centre

of the circle with the lateral edge of the shelf in the affected side (Figure 6).

V

Figure 6: Center edge angle: CEA (Center edge angle unaffected side), CEA' (Center edge angle affected side)

VI

6.2.2 Congruence: SDS

The steps and formulas listed in this section are originating from the article “Quantitative

Measures for Evaluating the Radiographic Outcome of Legg-Calvé -Perthes Disease” of Shah et

al.

To calculate the SDS two radiographs are required:

an anteroposterior (AP) radiograph and a frog-leg

radiograph.

The following steps, described by Shah et al., are

applied on the anteroposterior and frog-leg

radiograph:

1. Two reference points are marked: the most

medial and the most lateral margin of the

femoral head (Figure 7-a).

2. A circle touching these reference points is

drawn to match the size of the femoral head

and lines up with the articular surface of the

femoral head (Figure 7-b).

3. If the circle perfectly lines up with the contour

of the articular margin, the radius of the circle

(r ap) is noted.

4. If the articular margin does not line up with the arc of the circle, the size of the circle is

adjusted, so that it just touches the reference points and the articular margin. The circle

does not extend outside the femoral head (maximum inscribed circle = MIC) (Figure 7-b).

5. A second concentric circle is drawn to just touch the outer limits of the articular margin

without extending inside the femoral head (minimum circumscribed circle [MCC]) (Figure

7-c).

6. The radii of the circles are noted: r MIC-ap (radius of the maximum inscribed circle on

the anteroposterior radiograph), r MCC-ap (radius of the maximum circumscribed circle

on the anteroposterior radiograph), r MIC-lat (radius of the maximum inscribed circle on

the frog-leg radiograph) and r MCC-lat (radius of the maximum circumscribed circle on

the frog-leg radiograph)

After measuring the radii, the roundness errors are calculated. They are expressed as ratios and

Figure 7: Radiographs illustrating the technique for measuring the roundness error. Illustration of Shah et al. from “Quantitative Measures for Evaluating the Radiographic Outcome of Legg-Calvé-Perthes Disease”

VII

define the sphericity of the femoral head.

• Roundness error (RE) on the AP radiograph:

EJI6 ��,��8- � �,(�8-

,�8.�G�,��8- K �,(�8-��8-%L 100

• Roundness error on the frog-leg radiograph:

EJO8+ � �,��98+ � �,(�98+

,�8.�G�,��98+ K �,(�98+��98+%L 100

The next step is calculating the Ellipsoid Deformation. The ED is present when the radius of the

femoral head on the AP-radiograph differs from the radius of the femoral head on the frog-leg

radiograph.

• If r lat > r ap

JP ��98+ � �8-

�8-L 100

• If r ap > r lat

JP ��8- � �98+

�98+L 100

The sum of the RE’s and the ellipsoid deformation is the extent to which the shape of the

femoral head deviates from sphericity: SDS = RE AP + RE Lat + ED.

VIII

IOWA hip score (chart) 6.3

IX

Results PiG Model 6.4

6.4.1 Group comparison PiG Model

6.4.1.1 Comparison of the unaffected sides

The Kruskal-Wallis test shows no differences for 13 variables (0,069 < P-value < 0,838). The

following five variables are significant: Hip Maximum flexion, Hip Maximum Extension, Hip

Maximum Internal Rotation, Hip Maximum External Rotation and Knee Mean Varus (0,014 < P-

value < 0,041).

After performing the Mann-Whitney U-test in the PiG model, significant differences between the

control group and the bad outcome patient group are shown for the following variables: Hip

Maximum flexion, Hip Maximum Extension, Hip Maximum Internal Rotation and Hip Maximum

External rotation (0,008 < P-value < 0,014). A trend is detected for Knee mean Varus (P-value:

0.022). The variable Hip Maximum Flexion and Hip Maximum Extension is also significant

different between both patient groups (P-values: 0,014).

No significant differences are detected between the control group and the good outcome patient

group (0,073 < P-value < 0,259). For the PIG model a trend is found for Knee Mean Varus (P-

value: 0,038).

6.4.1.2 Comparison of the affected sides

In the PiG model, the variable Knee Maximum Varus is borderline-missed significant (P-value:

0,054) and the variables Hip Maximum Extension and Hip ROM are shown to be significant

(0,001 < P-value < 0,005). For Hip Maximum Extension significant results are found after post-

hoc testing, when comparing the controls and the patient group with a good radiographic

outcome (P-value: 0,011) and when comparing the controls and the patient group with a bad

radiographic outcome (0,001). When comparing both patient groups a trend is found (P-value:

0,017). For Hip ROM a significant result is found as well after post-hoc comparison of the

controls and the bad outcome patient group (p-value: 0,001). A trend is found when comparing

the controls and the good outcome patient group (P-value: 0,017).

6.4.2 Side comparison

6.4.2.1 Control group

Within the control group, a significant result is detected for Knee Maximum Varus (P-value:

X

0,31).

6.4.2.2 Good outcome patient group

In the PiG model, a significant is found for Hip Maximum Rotation Internal Moment (P-value:

0,043).

6.4.2.3 Bad outcome patient group

Using the PiG model, significant results are found for the variables Hip Range of Motion, Hip

Maximum Flexion Moment, Hip Maximum Internal Rotation Moment and Hip Maximum External

Rotation (P-values: 0,031).

Tables results 6.5

Table 3: overview Abbreviations of variables used in tables

XI

Table 4: overview Signifcance of variables in PiG-Matlab and Pig Models; 1: controls, 2: patients with good outcome, 3: patients with bad outcome; Unaff: unaffected side, Aff: affected side; underlined numbers are significant

XII

Table 5: overview mean values and standard deviations (SD) of Kinematic variables in both PiG-Matlab and PiG Models; unaff: unaffected, aff: affected. Pelvic Tilt and Pelvic Obliquity is identical for both models, and therefore only reported in one table

XIII

Table 6: overview mean values and standard deviations (SD) of Kinetic variables in both PiG-Matlab and PiG Models; unaff: unaffected, aff: affected.

XIV

Table 7: overview additional variables (Balance velocity, Balance path length, step time and IOWA hip score) ; unaff: unaffected, aff: affected.