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Research ArticleCharacterization of Electrograms from Multipolar DiagnosticCatheters during Atrial Fibrillation

Prasanth Ganesan1 Elizabeth M Cherry2 Arkady M Pertsov3 and Behnaz Ghoraani1

1Biomedical Engineering Department Rochester Institute of Technology Rochester NY 14623 USA2School of Mathematical Sciences Rochester Institute of Technology Rochester NY 14623 USA3Department of Pharmacology SUNY Upstate Medical University Syracuse NY 13210 USA

Correspondence should be addressed to Behnaz Ghoraani bxgbmeritedu

Received 30 November 2014 Revised 13 February 2015 Accepted 19 February 2015

Academic Editor Christof Kolb

Copyright copy 2015 Prasanth Ganesan et al This is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited

Atrial fibrillation (AF) is the most common arrhythmia in USA with more than 23 million people affected annually Catheterablation procedure is a method for treatment of AF which involves 3D electroanatomic mapping of the patientrsquos left atrium (LA)by maneuvering a conventional multipolar diagnostic catheter (MPDC) along the LA endocardial surface after which pulmonaryvein (PV) isolation is performed thus eliminating the AF triggers originating from the PVs However it remains unclear how toeffectively utilize the information provided by the MPDC to locate the AF-sustaining sites known as sustained rotor-like activities(RotAs) In this study we use computer modeling to investigate the variations in the characteristics of the MPDC electrogramsnamely total conduction delay (TCD) and average cycle length (CL) as the MPDC moves towards a RotA source Subsequentlya study with a human subject was performed in order to verify the predictions of the simulation study The conclusions from thisstudy may be used to iteratively direct an MPDC towards RotA sources thus allowing the RotAs to be localized for customized andimproved AF ablation

1 Introduction

Cardiovascular disease continues to be a major cause ofmortality in USA that results in approximately 2200 deathsa day and an approximate annual cost of $300 billion [1]Atrial fibrillation (AF) being the most common arrhythmiaamong all the cardiovascular diseases and a primary causeof stroke [2 3] results in frequent health care utilizationhospitalizations and increased risks of heart failure andmortality Several methods have been developed to treatAF such as pacemaker surgery and antiarrhythmic drugsHowever an important step forward in the treatment ofAF was based on the studies by Haıssaguerre et al [4]which demonstrated that ectopic beats from the pulmonaryveins (PVs) play an important role in triggering AF Thisstudy gave rise to the development of a nonpharmacologicalablation therapy called PV isolation where the atrial tissuein the PV junction is cauterized using radiofrequency energyfocused by the ablation catheter Similar anatomic abalation

methods may include additional lesion lines at the roof ofthe left atrium and along the mitral isthmus Unfortunatelythis procedure has a long-term success rate of only 40 to60 primarily because it targets only the abnormal electricalactivities originating from PVs and fails to count the sourcespresent outside the PVs

Previous studies on animal AF have shown that the rotor-like activities (RotAs) that exist outside the PVs contributeto sustaining the AF and hence the ablation procedureshould focus on these sites as well [5] Narayan et al [6]performed ablation of these sites using unipolar electrogramsobtained from a basket catheter which showed that targetingsites outside the PVs (predominantly the LA region) duringablation provides better results than performing PV isolationexclusively [7] However basket is associated with somelimitations such as low resolution bad precision in mappingof anatomical sites and limited torque capabilities Theselimitations can be overcome by using a conventional MPDCinstead of a basket catheter and it would still be possible

Hindawi Publishing CorporationBioMed Research InternationalVolume 2015 Article ID 272954 9 pageshttpdxdoiorg1011552015272954

2 BioMed Research International

to detect RotAs in humans [8] Although these studiesdemonstrate that the RotAs in the LA could be detectedthere is no well-defined algorithm to localize them so thatthe MPDC could be guided towards the RotAs Unlike PVisolation where the knowledge of precise location of theAF source is not required because the PV junctions can beanatomically identified and isolated the cardiac chamber sur-face is complex and the RotAs cannot be visualized directlyHence some knowledge of the location of the RotA sourcewould be beneficial and it could in turn expedite patient-specific catheter ablation through the use of a RotA localiza-tion algorithm

In recent years several methods have been developedto determine the location of the RotA source by examiningthe characteristics of electrograms obtained from catheterThe algorithm developed by Roney et al [9] which demon-strates a mathematical approach for quantification of thepropagation velocity of an action potential and measurementof direction and distance of the RotA using a multipolarcatheter is one such approach to confronting the challengesof localization along with many other existing mathematicalapproaches like polynomial surface-fitting algorithms finite-difference methods and triangulation techniques [9] How-ever detailed information on the variations in characteristicsassociated with MPDC electrograms such as conductiondelay and cycle length depending on the distance fromthe RotA source is still obscure If such variations wereunderstood it is likely that progress in addressing the currentchallenges in AF such as achieving improved identificationof ablation targets and permanent treatment via AF ablation[10] would be faster Hence the major goal of the presentstudy is to investigate the variations in characteristics of theelectrograms obtained from the MPDC as the MPDC movestowards the RotA source The result of this study is expectedto facilitate addressing the current challenges in AF ablation

2 Methods

We performed the investigation through a computer sim-ulation which facilitates positioning a simulated MPDC atany desired location and recording the electrogram Subse-quently we performed a clinical study in order to confirmthe outcome of the simulation study that is the inferenceof the variations in characteristics of the electrograms asthe simulated MPDC moves towards the RotA A detailedexplanation of our study methodology is provided in thefollowing sections

21 Simulation We studied the variations in simulatedMPDC electrogram characteristics as the MPDC movestowards the RotA source

The propagation of activations or action potentials withincardiac tissue involves complex interactions between cellularelectrical activity electrical cell-to-cell communication andcardiac tissue structure [11] The action potentials themselvesare generated due to transmembrane currents through ionchannels pumps and exchangers and can be formulatedusing various mathematical models that are often specific

to individual species and specific regions of the heart [12]Atrial models have been developed for different species suchas canine [13] and rabbit [14] Since our investigation is basedon human AF we considered human atrial models Previousstudies on the simulation of various mathematical models ofhuman atrial cells and tissue have shown that the Cherry andEvans model produces stable spiral waves [12] which serveas a sustained RotA source in our simulation study Hencewe performed the simulation study by developing a computersimulation of the Nygren et al human atrial cell model

211 Nygren Human Atrial Electrophysiology Model Nygrenet al [15] published a mathematical model of the humanatrial cell myocyte which was based on average voltage-clampdata recorded from the isolated single myocytes It consists ofan assembly of Hodgkin-Huxley-type equivalent circuits forthe sarcolemma and a fluid compartment model This atrialmodel can reproduce the action potentials produced by theatrial cells that are characterized primarily by ionic currents

A 10 cm times 10 cm 2D atrial tissue with a spatial resolutionof 0025 cm was simulated using the Nygren atrial cell modelA stable RotA was generated (Figure 1(a)) for a durationof 2 seconds which led to approximately six rotationsWe also implemented a variant of the Nygren et al atrialmodel with the following concentrations held constant [K+]

119894

[K+]119888 [Na+]

119894 [Na+]

119888 and [Ca2+]

119888[12] This model creates a

larger gyration around a virtual center and a more dynamicmeandering at the center of the rotor

212 Simulation of MPDC Electrograms The simulation wasprogrammed to store the output needed to generate pseudo-ECGs (axial current) obtained from specific locations ofthe 2D tissue (Figure 1(b)) This feature was utilized forsimulating an MPDC by providing the program with theselocation values determined according to the orientation of theelectrodes of an MPDC Using this method a 20-pole (ie10-bipole) MPDC (replication of Lasso catheter BiosenseWebster Diamond Bar CA) with a diameter of 15mm wassimulated and the pseudo-ECG values at those locations wereobtained A detailed description of these MPDC locationsand their movement towards the RotA which constitutes theobjective of our simulation study is provided in the sectionthat discusses the simulation results The activations of a10-bipole simulated MPDC are shown in Figure 1(b) wherethe numbers 1 through 10 indicate the 10-bipole simulatedelectrodes

22 Clinical Study The primary objective of performing theclinical study is to investigate if the results obtained fromthe analysis of the variations in the MPDC electrogram char-acteristics in the simulation studies conform to a practicalAF circumstance This is basically an approach to checkthe reliability and fidelity of the inference of our simulationstudy during heterogeneous situations such as AF in a realhuman atrium The clinical AF data was collected from apersistent-AF patient (age 59 male) who was undergoingthe first AF catheter ablation The study was approved bythe Institutional Review Board at Toronto General Hospital

BioMed Research International 3

110

23

45

6 789L1

0

10

20

30

minus10

minus20

minus30

minus40

minus50

minus60

minus70

minus80

(a) RotA wave and MPDC location L1

10987654321

Conduction delay (CD)

Cycle length

lowast

(b) MPDC electrograms for location L1

Figure 1 Computer simulation study (a) RotA wave with the MPDC at location L1 which has the first activated bipole at bipole 6 indicatedwith the arrow pointing towards it (b) The electrograms at location L1 The numbers at the left corner indicate the lead number of thecorresponding bipole electrode and the asterisk denotes the first activated bipole (FAB) The conduction delay between bipole 5 and the FABand the cycle length are indicated

and the patient provided written informed research con-sent Transthoracic echocardiography and transesophagealechocardiography were performed 1 day before ablation inorder to evaluate left ventricular ejection fraction and LA sizeand exclude intra-atrial thrombus The patient underwentablation in the postabsorptive state after antiarrhythmicdrugs were discontinued for 5 half-lives with the exceptionof amiodarone which was continued Vascular access wasachieved using the femoral vein A 20-pole catheter (Live-wire St Jude Medical St Paul MN) was placed in thecoronary sinus After interatrial septal puncture a 20-polevariable curve circular mappingMPDC (15ndash25mmdiameter1mm interelectrode distance Lasso Biosense Webster Dia-mond Bar CA) was placed in the LA through a guide sheathThe circular catheter was maintained at maximum diameterwhenever possible and maneuvered to the following LAregions in sequence left PV ostiaantrum posteriorinferiorwall roofappendage right PV ostiaantrum septum andanterior wall At each location 10 bipolar electrograms (30ndash500Hz) were simultaneously recorded for 25 seconds at asampling frequency of 1000Hz only after catheter stabilitywas achieved

23 Signal Processing

231 Preprocessing of MPDC Electrograms The preprocess-ing of the simulated and clinically obtained MPDC elec-trograms was performed separately using custom softwarewritten in MATLAB as explained below

Simulated ElectrogramsThe activation times of the simulatedMPDC electrograms were first annotated at the locations ofthe maximum negative deflections [16 17]

Clinically Obtained Electrograms After the ablation proce-dure was completed the analysis of clinical data was per-formed offline MPDC recordings were excluded if positional

stability was poor during the recording or if there are somemissing bipoles The data that is required by the developedalgorithm is readily available in the existing electroanatom-ical mapping systems The xyz coordinates of each bipoleas well as the 3D structure of the left atrium were obtainedfrom the clinical mapping system so identification of theunstable catheter recordings catheter deformities or poorcontact bipoles was easily done in our custom programLocal activation of the remaining bipolar electrograms wasdefined automatically from the maximum peak positive ornegative deflection with reference to the isoelectric baselineafter which far-field ventricular activation was identified andexcluded from the analysis of local activation The electro-grams obtained from the various locations of recording inthe LA were first investigated by a clinical electrophysiologistto look for RotA sources A RotA was clinically definedif the time interval between consecutive local activationsaround the circular catheter encompassed the local AF cyclelength such that the head of the advancing wavefront metthe tail of the subsequent wavefront [8] To ensure that thearrhythmias analyzedwere stable only theMPDC recordingswith electrograms consisting ofge3 cycles of similar activationpattern and bipolar electrogram morphology were retainedfor further analysis

232 Characterization of MPDC Electrograms In order toaccomplish the goal of our study which is to investigatethe variations in the characteristics of MPDC electrogramsthe following three characteristics were determined at eachrecording site (1) first activated bipole (FAB) (2) totalconduction delay (TCD) and (3) average cycle length (CL)at the FAB

FAB was determined as the first bipole that encountersthe wavefront (ie the bipole with the earliest activation time(AT)) The AT of each bipole is calculated with respect tothe beginning of the recordings For example in Figure 1(b)


12

3

9

8

76

5

4

10

FAB

AT = 619

AT = 607

AT = 593

AT = 581

AT = 580

AT = 584

AT = 598

AT = 613

AT = 622

AT = 627

CD1 = 5CD2 = 9

CD3 = 15

CD4 = 14

CD5 = 4

CD6 = 1

CD7 = 12

CD8 = 14

CD9 = 12

CD10 = 8

Figure 2This diagram illustrates the FAB and TCD calculations forthe electrograms recorded using an MPDC Bipole 6 is the FAB andTCD is 94ms which is the sum of CD

1to CD

10 AT activation time

CD conduction delay All times are given in ms

the FAB denoted by the asterisk implies that at location L1the earliest activation occurred at bipole electrode number 6(bipole 6) of the MPDCThe FAB is shown as the head of thearrow in Figure 1(a)

The conduction delay (CD) of a particular bipole iscalculated as the interval from each local activation to that ofthe neighboring bipole with respect to its FAB For examplein Figure 1(b) the conduction delay of bipole 5 (CD

5) is

calculated as the time interval between the activations ofbipole 6 (ie FAB) and bipole 5 as illustrated in the figureCD4will be calculated with respect to bipole 5 and so forth as

follows

CD119894=1003816100381610038161003816AT119894minus AT119894+1

1003816100381610038161003816

119894 = FAB minus 1 to 1(1)

The calculation of CD6to CD

9will be continued with respect

to the subsequent bipole as shown as follows

CD119894=1003816100381610038161003816AT119894+1minus AT119894

1003816100381610038161003816

119894 = FAB to 9(2)

Additionally CD10is calculated as the time interval between

bipole 1 and bipole 10 as given as follows

CD10=1003816100381610038161003816AT1minus AT10

1003816100381610038161003816 (3)

Figure 2 illustrates how our CD and TCD calculations areperformed for the MPDC in Figure 1(b) Bipole 6 is the FABwith the earliest activated time of 580ms CD

1to CD

10are

calculated as explained above and shown for each bipoleThisprocedure is continued for all cycles of the electrogram andtheCD for every bipole electrode is averaged over the numberof cycles to obtain a single value of CD for each electrodeFinally the summation of the average CD of every electrodeis calculated to obtain the TCD at each recording site

Themathematical expression for TCD at anyMPDC location119897 is given by

TCD119897=

10

sum

119894=1

CD119894 (4)

The cycle length is the time delay between two successiveactivations in the same electrode during consecutive cycles(Figure 1(b)) Here we calculate CL using only the FAB tohave a single CL for a givenMPDC locationThe cycle lengthof the FAB is calculated for different cycles and averaged overthe number of cycles to obtain an average cycle length (ieCL) for the FAB

3 Results and Discussion

31 Simulation Study Figure 3 illustrates the simulationstudy For investigating the variations in characteristics ofMPDC electrograms as the MPDC moves towards a RotAsource (L4 in Figure 3) the locations of theMPDC recordingsin the simulation were selected as shown in Figure 3 Initiallywe started by selecting a random location farther from theRotA (ie L1) The MPDC was then advanced to a randomlocation towards the direction of the RotA source (ie L2) asassessed visuallyThis procedure was repeated to L3 and thenL4 until the MPDC reached the RotA source (ie L4) Thisguidance procedure was repeated starting the MPDC from5 different locations forming 5 paths (Path A to Path E inFigure 3(a)) The MPDC electrograms obtained from Path Aare shown in Figure 3(b) We calculated the FAB TCD andCL at each location using the procedure discussed previouslyin Section 2

While moving the MPDC towards the RotA source(moving from L1 to L2 L3 and L4) and determining theelectrogram characteristics at each location along the move-ment path the variations in TCD and CL were examinedFigure 4(a) shows the TCD values of the five paths as theMPDC was moved from L1 to the RotA source at L4 Ascan be seen in this figure TCD increased along all thepaths For example as can be seen in Figure 3(b) the TCDvalue increased from 106ms to 112ms 166ms and 228msas the MPDC moved from L1 to L2 L3 and L4 (the RotAlocation) We also observed that at each location the FABwas the bipole closest to the RotA source Additionallywe generally observed a decreasing pattern in the CL ofthe FAB as the MPDC moved towards the RotA howeverthe pattern was not consistent in some cases as shown inFigure 5(a) We repeated the experiment using the modifiedNygren model as explained in Section 21 The steady-statespiral wave trajectories found using this model created alarger gyration on a circle with a radius of greater than 1 cmOur calculation resulted in a similar behavior showing thatthe TCD increased along all the paths even in the presence ofa meandering rotor These observations from the simulationstudy led to the following predictions

(i) Moving the MPDC in the direction of the FAB withrespect to the center of the catheter will guide theMPDC towards the RotA source


110

110

23

45

6 78

9

23

4

56 7

89

23

45

6 789

110

23

4

5 6 78

9

110

L 2

L1

L 3

Path A

L4

L1

L1

L1

L3

L 2

L 2

L 3

Path B

Path CPath D

L1

23

45

6 78

9

110

Path EL 2

L 3

L2

bull

0

10

20

30

minus10

minus20

minus30

minus40

minus50

minus60

minus70

minus801 cm

(a) RotA wave and MPDC locations

L1 L2 L3 L4

10987654321

(TCD = 228ms)(TCD = 166ms)(TCD = 112ms)(TCD = 106ms)

lowast

lowast

lowast

lowast

(b) MPDC electrograms along Path A

Figure 3 Simulation results (a) L4 is the location of the known RotA source The circles show the MPDC at the start point (L1) of eachof Paths A to E in every step of each path the MPDC moves forward towards the RotA source (b) the electrograms show the conductionpattern of path A from L1 to L4 The TCD increases from 106ms to 228ms as reported on the top of each MPDC electrogramThe numbersat the left corner indicate the lead number of the corresponding bipole electrode of the MPDC

(ii) A decreasing (increasing) TCD as the MPDC movesfrom one location to a neighboring location indicatesthat the MPDC is moving away from (towards) theRotA source

311 Clinical Study One RotA source was located along theposterior wall as confirmed by the clinical electrophysiologist(LRotA in Figures 6(a) and 7(a)) The RotA was reportedfor 05ms leading to 4 rotations Our objective was touse the MPDC electrogram characteristics and verify if thepredictions of the simulation study (ie the increasing TCDand the direction of FAB as the MPDC moves towards theRotA source) can be verified in a clinical AF case

In order to accomplish this objective from the locationsof MPDC recordings we selected a random location andlooked for an immediate neighboring location that satisfiedthe following criteria (1) the MPDC location was in thedirection given by the FAB of the current location and (2)the TCD at this location was greater than that of the currentlocation We continued following such locations successivelyuntil we could not find a neighboring MPDC location with

such criteria or we reached the RotA source In cases wherewe could not find a neighboring MPDC location with ourcriteria we started with any of the neighboring locations andreset the algorithm until we found a location that satisfiedthe criteria We repeated this exhaustive procedure for allthe MPDC locations that were recorded in the clinical studyand found all the paths that consisted of successive MPDClocations and started fromone location farther from theRotAsource and ended up in the location of the RotA source thusforming a path always directed towards the RotA Four suchpaths were found the two longest paths along with their elec-trograms are shown in Figures 6 and 7 In these figures eacharrow indicates the direction of the FAB of its correspondingMPDCand the TCD is calculatedwith respect to the FAB Forthe path shown in Figure 6(a) it can be seen that the valueof the TCD represents an increasing pattern which is from35ms through 64ms to 100ms until theMPDC converges onthe RotA where the TCD is observed to be 165ms The pathshown in Figure 7 presents the same behavior The overallTCD increases for all the four paths from the clinical studyas shown in Figure 4(b) However the CL corresponding


L1 L2 L3 L40

50

100

150

200

MPDC location

TCD

(ms)

Path APath BPath C

Path DPath E

(a) Simulation

L1 L2 L3 LRotA0

20

40

60

80

100

120

140

160

MPDC location

TCD

(ms)

Path APath B

(b) Human study

Figure 4 Variation of total conduction delay Variation in TCD with respect to the MPDC location (a) In simulation study the TCD showsan increasing gradient as theMPDCmoves from L1 towards the RotA at L4 in all the paths (b)The plot demonstrates the increasing gradientof TCD in the clinical study in both Path A and Path B when the MPDC moves from L1 to LRotA with the location of every successive stepdirected towards the first activated bipole of the current location

L1 L2 L3 L4

264

266

268

270

272

274

276

278

280

282

MPDC location

CL (m

s)

Path APath BPath C

Path DPath E

(a) Simulation

L1 L2 L3 LRotAMPDC location

CL (m

s)

Path APath B

154

156

158

160

162

164

168

170

(b) Human study

Figure 5 Variation of average cycle length Variation in average cycle length (CL) of the FAB with respect to the MPDC location (a) Insimulation study the CL of Path D and Path E shows a decreasing gradient as the MPDC moves from L1 towards the RotA at L4 Howeverthis decreasing gradient is not consistent in the other paths where the CL decreases as the MPDC moves from L1 to L3 but increases at L4(b) The plot demonstrates the inconsistent CL behavior observed in the clinical study In Path A the CL shows a decreasing gradient whenthe MPDC moves from L1 to LRotA with the location of every successive step directed towards the FAB of the current location howeverin Path B the CL gradient is inconsistent it increases as the MPDC moves from L1 to L3 with the location of every successive step directedtowards the FAB of the current location but it decreases at the location of RotA (ie LRotA)


LPVs RPVs

L2L3

L1

B9

LRotAB7

B8bull bull

bull

(a) MPDC locations moving towards RotA Source

L1

1

2

34

5

6

78

9

10

L2

123

4

5

6

7

8

9

10

L3

1

2

3

45

6

7

8

9

10

12

3

45

6

7

8

910

LRotA165ms)(TCD =100ms)(TCD =(TCD = 64 ms)(TCD = 35 ms)

1mv50ms

1mv50ms

1mv50ms

1mv50ms

dagger

Dagger

Dagger

Dagger

Dagger

lowast

lowast

lowast

lowast

(b) MPDC electrograms

Figure 6 Clinical study Path A (a) The dashed rings (L1 L2 and L3) show the location of MPDCs moving towards the RotA which isrepresented by a solid ring (LRotA) the direction of the first activated bipole is indicated in the figure with arrows and is B9 B7 and B8 forL1 L2 and L3 respectively The filled circle represents bipole 1 of each MPDC (b) A single cycle from the electrograms obtained at each ofL1 L2 and L3 and LRotA are shown along with the corresponding TCD reported at the top of each electrogram and the first activated bipolesare indicated by the asterisks The bipole electrode numbers 1 to 10 corresponding to each lead are indicated beside every bipole RPVs rightpulmonary veins LPVs left pulmonary veins dagger Voltage scaling decreased 4times Dagger Voltage scaling decreased 2times

to the FAB of these four paths did not show consistentvariations similar to our simulation study (Figure 5(b))Our observations suggest that the results obtained from oursimulation study are valid for a case of cinical human AFas well thereby suggesting that when the MPDC was at alocation far from the RotA it could have been guided to thelocation of the RotA source by monitoring the FAB and thevariations in TCD

In addition to calculating the TCDandCL characteristicswe studied the relationship between TCD and CL when theMPDC is exactly converging on the RotA source (ie L4)At this location the MPDC encircles the RotA source andany cycle of the RotA wave is completed at the same MPDCelectrode where the cycle started Hence the TCD (ieTCDRotA) is almost equal to the CL (ie CLRotA) TCDRotA ≃CLRotA

312 Clinical Implications Current AF ablation proceduresconstruct the 3D electroanatomic mapping of the LA bymaneuvering a conventional MPDC along the LA endo-cardial surface However the procedures are limited topulmonary vein isolation and other linear ablation (ie roofand mitral isthmus) performed on various regions of the LAwhere the regions are decided based on the atrial anatomyHence it remains unclear how to utilize the informationprovided by the MPDC to locate RotAs Based on ourprevious study which supports the ability of an MPDC todetect sustained RotAs in human AF [8] we believe thatutilizing the information recorded during MPDC move-ments can significantly improve AF target detection overthe current practice while remaining economically attractiveand safe for patients (no basket catheters) The results fromour simulation and human AF study suggest that it is


LPVs RPVs

L1L3 L2

B9B2

B1 and B10

LRotA

bull bull bull

(a) MPDC locations moving towards RotA source

L1

1

2

3

4

5

6

7

8

9

10

L2

1

2

3

4

5

6

7

8

9

10

1

2

3

4

5

67

8

910

dagger

dagger

dagger

dagger

L3

1

2

3

45

6

7

8

9

10

LRotA(TCD = 17ms) (TCD = 55ms) (TCD = 75ms) 165ms)(TCD =

1mv50ms

1mv50ms

1mv50ms

1mv50ms

dagger

◼

◼

◼

◼

◼

◼

Dagger

times

times

times

lowast

lowast

lowast

lowast

lowast


Figure 7 Clinical study Path B (a) The dashed rings (L1 L2 and L3) are the location of MPDCs moving towards the RotA represented bya solid ring (LRotA) the first activated bipole is denoted by the corresponding bipole number and an arrow pointing to it The solid ringindicates the location of the MPDC recording that encompasses the rotor source lowast represents bipole 1 of each MPDC (b) A single cyclefrom the electrograms obtained at each of L1 L2 L3 and LRotA is shown along with the corresponding TCD reported at the top of eachelectrogram the first activated bipole is indicated by the asterisks the corresponding bipole electrode numbers 1 through 10 are indicatedbeside every bipole RPVs right pulmonary veins LPVs left pulmonary veins ◼ Voltage scaling decreased 2times dagger Voltage scaling decreased4times Dagger Voltage scaling decreased 5times times Voltage scaling decreased 6times

possible to guide an MPDC towards a RotA source bymonitoring the characteristics of the MPDC recordingsPrevious electrogram characterization studies mainly use asingle bipole to characterize the electrograms such as CLor dominant frequency from the time or frequency domainto look for the RotAs In this study we investigated thecollective information froma 10-bipoleMPDC todetermine atechnique to guide a catheter towards the RotA source usingthe FAB and TCD Therefore the results of both simulationand clinical studies demonstrate that moving an MPDC inthe direction of the FAB while an increasing gradient in theTCD is observed could potentially guide the catheter towardsthe RotA source

313 Study Limitations Only a small number of all possiblepaths to the RotA that could have been formed were used inthe simulation study Hence it is possible that other MPDCelectrogramcharacteristics could exist thatwere not observedin this study The clinical AF study was limited to offlineanalysis of the recorded MPDC sites Hence there couldbe multiple simultaneous RotA sources but only one wasrecorded during the 3D electroanatomy mapping This studycan be further improved by performing a real-time dataanalysis during the 3D electroanatomy mapping Additionalclinical study can also be performed in future in order toconsider common variations in persistent AFThe simulationstudy can also be further developed by simulating multiple


RotA sources in the human atrial anatomy in order to investi-gate the changes to the MPDC characteristics in the presenceof multiple RotAs and also possibly ectopic sources in orderto replicate the effect of the ectopic beats from PVs

4 Conclusion

In this study we investigated the variations in characteristicssuch as the TCD and CL from the MPDC electrograms asthe MPDC moved towards a RotA source We used twoapproaches for the investigation a computer simulation studywas developed using an existing well-known mathematicalmodel of human atrial cell and the second approach wasperforming studies with a human subject As a result of thesimulation study we observed a consistent increase in theTCD as the MPDC moved towards a RotA source We alsoobserved that the MPDC electrode that encounters the earli-est activationwas always directed towards theRotA source Ina clinical AF case the phenomenon of the increasing gradientof TCD and the significance of the direction of FAB if fol-lowed have the potential to guide the MPDC to the locationof RotA source however we did not observe any similar con-sistent pattern from the CL Our findings may be used to iter-atively direct an MPDC towards RotAs and allow the RotAsto be successfully localized for customized and improved AFablation

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

The authors would like to acknowledge Dr Vijay S Chauhanfrom Toronto General Hospital Canada for providing theclinical AF data and his clinical input This material is basedupon work supported by the Advance RIT program which isfunded through the National Science Foundation underAward no HRD-1209115

References

[1] A Go D Mozaffarian V Roger E Benjamin and J BerryldquoAHA statistical updaterdquo Circulation vol 127 pp e62ndashe2452013

[2] J Jalife O Berenfeld A Skanes and R Mandapati ldquoMecha-nisms of atrial fibrillation mother rotors or multiple daughterwavelets or bothrdquo Journal of Cardiovascular Electrophysiologyvol 9 no 8 supplement pp S2ndashS12 1998

[3] S Nattel ldquoNew ideas about atrial fibrillation 50 years onrdquoNature vol 415 no 6868 pp 219ndash226 2002

[4] M Haıssaguerre P Jaıs D C Shah et al ldquoSpontaneousinitiation of atrial fibrillation by ectopic beats originating in thepulmonary veinsrdquo The New England Journal of Medicine vol339 no 10 pp 659ndash666 1998

[5] M Vaquero D Calvo and J Jalife ldquoCardiac fibrillation fromion channels to rotors in the human heartrdquo Heart Rhythm vol5 no 6 pp 872ndash879 2008

[6] S M Narayan D E Krummen and W-J Rappel ldquoClinicalmapping approach to diagnose electrical rotors and focalimpulse sources for human atrial fibrillationrdquo Journal of Car-diovascular Electrophysiology vol 23 no 5 pp 447ndash454 2012

[7] S M Narayan T Baykaner P Clopton et al ldquoAblation of rotorand focal sources reduces late recurrence of atrial fibrillationcompared with trigger ablation alone extended follow-up ofthe CONFIRM trial (conventional ablation for atrial fibrillationwith orwithout focal impulse and rotormodulation)rdquo Journal ofthe American College of Cardiology vol 63 no 17 pp 1761ndash17682014

[8] B Ghoraani R Dalvi S Gizurarson et al ldquoLocalized rotationalactivation in the left atrium during human atrial fibrillationrelationship to complex fractionated atrial electrograms andlow-voltage zonesrdquoHeart Rhythm vol 10 no 12 pp 1830ndash18382013

[9] C H Roney C D Cantwell N A Qureshi et al ldquoAn auto-mated algorithm for determining conduction velocity wave-front direction and origin of focal cardiac arrhythmias usinga multipolar catheterrdquo in Proceedings of the 36th Annual Inter-national Conference of the IEEE Engineering in Medicine andBiology Society (EMBC rsquo14) pp 1583ndash1586 Chicago Ill USAAugust 2014

[10] R Weerasooriya A J Shah M Hocini P Jaıs and MHaıssaguerre ldquoContemporary challenges of catheter ablationfor atrial fibrillationrdquo Clinical Therapeutics vol 36 no 9 pp1145ndash1150 2014

[11] A G Kleber andY Rudy ldquoBasicmechanisms of cardiac impulsepropagation and associated arrhythmiasrdquoPhysiological Reviewsvol 84 no 2 pp 431ndash488 2004

[12] EMCherry and S J Evans ldquoProperties of twohuman atrial cellmodels in tissue restitution memory propagation and reen-tryrdquo Journal of Theoretical Biology vol 254 no 3 pp 674ndash6902008

[13] R J Ramirez S Nattel and M Courtemanche ldquoMathemat-ical analysis of canine atrial action potentials rate regionalfactors and electrical remodelingrdquo The American Journal ofPhysiologymdashHeart and Circulatory Physiology vol 279 no 4pp H1767ndashH1785 2000

[14] D S Lindblad C R Murphey J W Clark and W R GilesldquoA model of the action potential and underlying membranecurrents in a rabbit atrial cellrdquoAmerican Journal of PhysiologymdashHeart and Circulatory Physiology vol 271 no 4 pp H1666ndashH1696 1996

[15] A Nygren C Fiset L Firek et al ldquoMathematical model ofan adult human atrial cell the role of K+ currents in repolar-izationrdquo Circulation Research vol 82 no 1 pp 63ndash81 1998

[16] T Paul J P Moak C Morris and A Garson Jr ldquoEpicardialmapping how to measure local activationrdquo Pacing and ClinicalElectrophysiology vol 13 no 3 pp 285ndash292 1990

[17] E Delacretaz K Soejima V K Gottipaty C B BrunckhorstP L Friedman and W G Stevenson ldquoSingle catheter deter-mination of local electrogram prematurity using simultaneousunipolar and bipolar recordings to replace the surface ECG as atiming referencerdquo Pacing and Clinical Electrophysiology vol 24no 4 pp 441ndash449 2001

Submit your manuscripts athttpwwwhindawicom

Stem CellsInternational

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014


MEDIATORSINFLAMMATION

of


Behavioural Neurology

EndocrinologyInternational Journal of



Disease Markers


BioMed Research International

OncologyJournal of



Oxidative Medicine and Cellular Longevity


PPAR Research

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Immunology ResearchHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

ObesityJournal of



Computational and Mathematical Methods in Medicine

OphthalmologyJournal of


Diabetes ResearchJournal of



Research and TreatmentAIDS


Gastroenterology Research and Practice


Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom


to detect RotAs in humans [8] Although these studiesdemonstrate that the RotAs in the LA could be detectedthere is no well-defined algorithm to localize them so thatthe MPDC could be guided towards the RotAs Unlike PVisolation where the knowledge of precise location of theAF source is not required because the PV junctions can beanatomically identified and isolated the cardiac chamber sur-face is complex and the RotAs cannot be visualized directlyHence some knowledge of the location of the RotA sourcewould be beneficial and it could in turn expedite patient-specific catheter ablation through the use of a RotA localiza-tion algorithm

In recent years several methods have been developedto determine the location of the RotA source by examiningthe characteristics of electrograms obtained from catheterThe algorithm developed by Roney et al [9] which demon-strates a mathematical approach for quantification of thepropagation velocity of an action potential and measurementof direction and distance of the RotA using a multipolarcatheter is one such approach to confronting the challengesof localization along with many other existing mathematicalapproaches like polynomial surface-fitting algorithms finite-difference methods and triangulation techniques [9] How-ever detailed information on the variations in characteristicsassociated with MPDC electrograms such as conductiondelay and cycle length depending on the distance fromthe RotA source is still obscure If such variations wereunderstood it is likely that progress in addressing the currentchallenges in AF such as achieving improved identificationof ablation targets and permanent treatment via AF ablation[10] would be faster Hence the major goal of the presentstudy is to investigate the variations in characteristics of theelectrograms obtained from the MPDC as the MPDC movestowards the RotA source The result of this study is expectedto facilitate addressing the current challenges in AF ablation

2 Methods

We performed the investigation through a computer sim-ulation which facilitates positioning a simulated MPDC atany desired location and recording the electrogram Subse-quently we performed a clinical study in order to confirmthe outcome of the simulation study that is the inferenceof the variations in characteristics of the electrograms asthe simulated MPDC moves towards the RotA A detailedexplanation of our study methodology is provided in thefollowing sections

21 Simulation We studied the variations in simulatedMPDC electrogram characteristics as the MPDC movestowards the RotA source

The propagation of activations or action potentials withincardiac tissue involves complex interactions between cellularelectrical activity electrical cell-to-cell communication andcardiac tissue structure [11] The action potentials themselvesare generated due to transmembrane currents through ionchannels pumps and exchangers and can be formulatedusing various mathematical models that are often specific

to individual species and specific regions of the heart [12]Atrial models have been developed for different species suchas canine [13] and rabbit [14] Since our investigation is basedon human AF we considered human atrial models Previousstudies on the simulation of various mathematical models ofhuman atrial cells and tissue have shown that the Cherry andEvans model produces stable spiral waves [12] which serveas a sustained RotA source in our simulation study Hencewe performed the simulation study by developing a computersimulation of the Nygren et al human atrial cell model

211 Nygren Human Atrial Electrophysiology Model Nygrenet al [15] published a mathematical model of the humanatrial cell myocyte which was based on average voltage-clampdata recorded from the isolated single myocytes It consists ofan assembly of Hodgkin-Huxley-type equivalent circuits forthe sarcolemma and a fluid compartment model This atrialmodel can reproduce the action potentials produced by theatrial cells that are characterized primarily by ionic currents

A 10 cm times 10 cm 2D atrial tissue with a spatial resolutionof 0025 cm was simulated using the Nygren atrial cell modelA stable RotA was generated (Figure 1(a)) for a durationof 2 seconds which led to approximately six rotationsWe also implemented a variant of the Nygren et al atrialmodel with the following concentrations held constant [K+]

119894

[K+]119888 [Na+]

119894 [Na+]

119888 and [Ca2+]

119888[12] This model creates a

larger gyration around a virtual center and a more dynamicmeandering at the center of the rotor

212 Simulation of MPDC Electrograms The simulation wasprogrammed to store the output needed to generate pseudo-ECGs (axial current) obtained from specific locations ofthe 2D tissue (Figure 1(b)) This feature was utilized forsimulating an MPDC by providing the program with theselocation values determined according to the orientation of theelectrodes of an MPDC Using this method a 20-pole (ie10-bipole) MPDC (replication of Lasso catheter BiosenseWebster Diamond Bar CA) with a diameter of 15mm wassimulated and the pseudo-ECG values at those locations wereobtained A detailed description of these MPDC locationsand their movement towards the RotA which constitutes theobjective of our simulation study is provided in the sectionthat discusses the simulation results The activations of a10-bipole simulated MPDC are shown in Figure 1(b) wherethe numbers 1 through 10 indicate the 10-bipole simulatedelectrodes

22 Clinical Study The primary objective of performing theclinical study is to investigate if the results obtained fromthe analysis of the variations in the MPDC electrogram char-acteristics in the simulation studies conform to a practicalAF circumstance This is basically an approach to checkthe reliability and fidelity of the inference of our simulationstudy during heterogeneous situations such as AF in a realhuman atrium The clinical AF data was collected from apersistent-AF patient (age 59 male) who was undergoingthe first AF catheter ablation The study was approved bythe Institutional Review Board at Toronto General Hospital


110

23

45

6 789L1

0

10

20

30

minus10

minus20

minus30

minus40

minus50

minus60

minus70

minus80


10987654321


Cycle length

lowast












12

3

9

8

76

5

4

10

FAB

AT = 619

AT = 607

AT = 593

AT = 581

AT = 580

AT = 584

AT = 598

AT = 613

AT = 622

AT = 627

CD1 = 5CD2 = 9

CD3 = 15

CD4 = 14

CD5 = 4

CD6 = 1

CD7 = 12

CD8 = 14

CD9 = 12

CD10 = 8


1to CD





5) is


follows

CD119894=1003816100381610038161003816AT119894minus AT119894+1

1003816100381610038161003816

119894 = FAB minus 1 to 1(1)




CD119894=1003816100381610038161003816AT119894+1minus AT119894

1003816100381610038161003816

119894 = FAB to 9(2)



CD10=1003816100381610038161003816AT1minus AT10

1003816100381610038161003816 (3)


1to CD

10are



TCD119897=

10

sum

119894=1

CD119894 (4)







110

110

23

45

6 78

9

23

4

56 7

89

23

45

6 789

110

23

4

5 6 78

9

110

L 2

L1

L 3

Path A

L4

L1

L1

L1

L3

L 2

L 2

L 3

Path B

Path CPath D

L1

23

45

6 78

9

110

Path EL 2

L 3

L2

bull

0

10

20

30

minus10

minus20

minus30

minus40

minus50

minus60

minus70

minus801 cm


L1 L2 L3 L4

10987654321


lowast

lowast

lowast

lowast








L1 L2 L3 L40

50

100

150

200

MPDC location

TCD

(ms)

Path APath BPath C

Path DPath E

(a) Simulation

L1 L2 L3 LRotA0

20

40

60

80

100

120

140

160

MPDC location

TCD

(ms)

Path APath B

(b) Human study


L1 L2 L3 L4

264

266

268

270

272

274

276

278

280

282

MPDC location

CL (m

s)

Path APath BPath C

Path DPath E

(a) Simulation


CL (m

s)

Path APath B

154

156

158

160

162

164

168

170

(b) Human study



LPVs RPVs

L2L3

L1

B9

LRotAB7

B8bull bull

bull


L1

1

2

34

5

6

78

9

10

L2

123

4

5

6

7

8

9

10

L3

1

2

3

45

6

7

8

9

10

12

3

45

6

7

8

910


1mv50ms

1mv50ms

1mv50ms

1mv50ms

dagger

Dagger

Dagger

Dagger

Dagger

lowast

lowast

lowast

lowast







LPVs RPVs

L1L3 L2

B9B2

B1 and B10

LRotA

bull bull bull


L1

1

2

3

4

5

6

7

8

9

10

L2

1

2

3

4

5

6

7

8

9

10

1

2

3

4

5

67

8

910

dagger

dagger

dagger

dagger

L3

1

2

3

45

6

7

8

9

10


1mv50ms

1mv50ms

1mv50ms

1mv50ms

dagger

◼

◼

◼

◼

◼

◼

Dagger

times

times

times

lowast

lowast

lowast

lowast

lowast







4 Conclusion




Acknowledgments


References























of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of

















110

23

45

6 789L1

0

10

20

30

minus10

minus20

minus30

minus40

minus50

minus60

minus70

minus80


10987654321


Cycle length

lowast












12

3

9

8

76

5

4

10

FAB

AT = 619

AT = 607

AT = 593

AT = 581

AT = 580

AT = 584

AT = 598

AT = 613

AT = 622

AT = 627

CD1 = 5CD2 = 9

CD3 = 15

CD4 = 14

CD5 = 4

CD6 = 1

CD7 = 12

CD8 = 14

CD9 = 12

CD10 = 8


1to CD





5) is


follows

CD119894=1003816100381610038161003816AT119894minus AT119894+1

1003816100381610038161003816

119894 = FAB minus 1 to 1(1)




CD119894=1003816100381610038161003816AT119894+1minus AT119894

1003816100381610038161003816

119894 = FAB to 9(2)



CD10=1003816100381610038161003816AT1minus AT10

1003816100381610038161003816 (3)


1to CD

10are



TCD119897=

10

sum

119894=1

CD119894 (4)







110

110

23

45

6 78

9

23

4

56 7

89

23

45

6 789

110

23

4

5 6 78

9

110

L 2

L1

L 3

Path A

L4

L1

L1

L1

L3

L 2

L 2

L 3

Path B

Path CPath D

L1

23

45

6 78

9

110

Path EL 2

L 3

L2

bull

0

10

20

30

minus10

minus20

minus30

minus40

minus50

minus60

minus70

minus801 cm


L1 L2 L3 L4

10987654321


lowast

lowast

lowast

lowast








L1 L2 L3 L40

50

100

150

200

MPDC location

TCD

(ms)

Path APath BPath C

Path DPath E

(a) Simulation

L1 L2 L3 LRotA0

20

40

60

80

100

120

140

160

MPDC location

TCD

(ms)

Path APath B

(b) Human study


L1 L2 L3 L4

264

266

268

270

272

274

276

278

280

282

MPDC location

CL (m

s)

Path APath BPath C

Path DPath E

(a) Simulation


CL (m

s)

Path APath B

154

156

158

160

162

164

168

170

(b) Human study



LPVs RPVs

L2L3

L1

B9

LRotAB7

B8bull bull

bull


L1

1

2

34

5

6

78

9

10

L2

123

4

5

6

7

8

9

10

L3

1

2

3

45

6

7

8

9

10

12

3

45

6

7

8

910


1mv50ms

1mv50ms

1mv50ms

1mv50ms

dagger

Dagger

Dagger

Dagger

Dagger

lowast

lowast

lowast

lowast







LPVs RPVs

L1L3 L2

B9B2

B1 and B10

LRotA

bull bull bull


L1

1

2

3

4

5

6

7

8

9

10

L2

1

2

3

4

5

6

7

8

9

10

1

2

3

4

5

67

8

910

dagger

dagger

dagger

dagger

L3

1

2

3

45

6

7

8

9

10


1mv50ms

1mv50ms

1mv50ms

1mv50ms

dagger

◼

◼

◼

◼

◼

◼

Dagger

times

times

times

lowast

lowast

lowast

lowast

lowast







4 Conclusion




Acknowledgments


References























of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of

















12

3

9

8

76

5

4

10

FAB

AT = 619

AT = 607

AT = 593

AT = 581

AT = 580

AT = 584

AT = 598

AT = 613

AT = 622

AT = 627

CD1 = 5CD2 = 9

CD3 = 15

CD4 = 14

CD5 = 4

CD6 = 1

CD7 = 12

CD8 = 14

CD9 = 12

CD10 = 8


1to CD





5) is


follows

CD119894=1003816100381610038161003816AT119894minus AT119894+1

1003816100381610038161003816

119894 = FAB minus 1 to 1(1)




CD119894=1003816100381610038161003816AT119894+1minus AT119894

1003816100381610038161003816

119894 = FAB to 9(2)



CD10=1003816100381610038161003816AT1minus AT10

1003816100381610038161003816 (3)


1to CD

10are



TCD119897=

10

sum

119894=1

CD119894 (4)







110

110

23

45

6 78

9

23

4

56 7

89

23

45

6 789

110

23

4

5 6 78

9

110

L 2

L1

L 3

Path A

L4

L1

L1

L1

L3

L 2

L 2

L 3

Path B

Path CPath D

L1

23

45

6 78

9

110

Path EL 2

L 3

L2

bull

0

10

20

30

minus10

minus20

minus30

minus40

minus50

minus60

minus70

minus801 cm


L1 L2 L3 L4

10987654321


lowast

lowast

lowast

lowast








L1 L2 L3 L40

50

100

150

200

MPDC location

TCD

(ms)

Path APath BPath C

Path DPath E

(a) Simulation

L1 L2 L3 LRotA0

20

40

60

80

100

120

140

160

MPDC location

TCD

(ms)

Path APath B

(b) Human study


L1 L2 L3 L4

264

266

268

270

272

274

276

278

280

282

MPDC location

CL (m

s)

Path APath BPath C

Path DPath E

(a) Simulation


CL (m

s)

Path APath B

154

156

158

160

162

164

168

170

(b) Human study



LPVs RPVs

L2L3

L1

B9

LRotAB7

B8bull bull

bull


L1

1

2

34

5

6

78

9

10

L2

123

4

5

6

7

8

9

10

L3

1

2

3

45

6

7

8

9

10

12

3

45

6

7

8

910


1mv50ms

1mv50ms

1mv50ms

1mv50ms

dagger

Dagger

Dagger

Dagger

Dagger

lowast

lowast

lowast

lowast







LPVs RPVs

L1L3 L2

B9B2

B1 and B10

LRotA

bull bull bull


L1

1

2

3

4

5

6

7

8

9

10

L2

1

2

3

4

5

6

7

8

9

10

1

2

3

4

5

67

8

910

dagger

dagger

dagger

dagger

L3

1

2

3

45

6

7

8

9

10


1mv50ms

1mv50ms

1mv50ms

1mv50ms

dagger

◼

◼

◼

◼

◼

◼

Dagger

times

times

times

lowast

lowast

lowast

lowast

lowast







4 Conclusion




Acknowledgments


References























of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of

















110

110

23

45

6 78

9

23

4

56 7

89

23

45

6 789

110

23

4

5 6 78

9

110

L 2

L1

L 3

Path A

L4

L1

L1

L1

L3

L 2

L 2

L 3

Path B

Path CPath D

L1

23

45

6 78

9

110

Path EL 2

L 3

L2

bull

0

10

20

30

minus10

minus20

minus30

minus40

minus50

minus60

minus70

minus801 cm


L1 L2 L3 L4

10987654321


lowast

lowast

lowast

lowast








L1 L2 L3 L40

50

100

150

200

MPDC location

TCD

(ms)

Path APath BPath C

Path DPath E

(a) Simulation

L1 L2 L3 LRotA0

20

40

60

80

100

120

140

160

MPDC location

TCD

(ms)

Path APath B

(b) Human study


L1 L2 L3 L4

264

266

268

270

272

274

276

278

280

282

MPDC location

CL (m

s)

Path APath BPath C

Path DPath E

(a) Simulation


CL (m

s)

Path APath B

154

156

158

160

162

164

168

170

(b) Human study



LPVs RPVs

L2L3

L1

B9

LRotAB7

B8bull bull

bull


L1

1

2

34

5

6

78

9

10

L2

123

4

5

6

7

8

9

10

L3

1

2

3

45

6

7

8

9

10

12

3

45

6

7

8

910


1mv50ms

1mv50ms

1mv50ms

1mv50ms

dagger

Dagger

Dagger

Dagger

Dagger

lowast

lowast

lowast

lowast







LPVs RPVs

L1L3 L2

B9B2

B1 and B10

LRotA

bull bull bull


L1

1

2

3

4

5

6

7

8

9

10

L2

1

2

3

4

5

6

7

8

9

10

1

2

3

4

5

67

8

910

dagger

dagger

dagger

dagger

L3

1

2

3

45

6

7

8

9

10


1mv50ms

1mv50ms

1mv50ms

1mv50ms

dagger

◼

◼

◼

◼

◼

◼

Dagger

times

times

times

lowast

lowast

lowast

lowast

lowast







4 Conclusion




Acknowledgments


References























of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of

















L1 L2 L3 L40

50

100

150

200

MPDC location

TCD

(ms)

Path APath BPath C

Path DPath E

(a) Simulation

L1 L2 L3 LRotA0

20

40

60

80

100

120

140

160

MPDC location

TCD

(ms)

Path APath B

(b) Human study


L1 L2 L3 L4

264

266

268

270

272

274

276

278

280

282

MPDC location

CL (m

s)

Path APath BPath C

Path DPath E

(a) Simulation


CL (m

s)

Path APath B

154

156

158

160

162

164

168

170

(b) Human study



LPVs RPVs

L2L3

L1

B9

LRotAB7

B8bull bull

bull


L1

1

2

34

5

6

78

9

10

L2

123

4

5

6

7

8

9

10

L3

1

2

3

45

6

7

8

9

10

12

3

45

6

7

8

910


1mv50ms

1mv50ms

1mv50ms

1mv50ms

dagger

Dagger

Dagger

Dagger

Dagger

lowast

lowast

lowast

lowast







LPVs RPVs

L1L3 L2

B9B2

B1 and B10

LRotA

bull bull bull


L1

1

2

3

4

5

6

7

8

9

10

L2

1

2

3

4

5

6

7

8

9

10

1

2

3

4

5

67

8

910

dagger

dagger

dagger

dagger

L3

1

2

3

45

6

7

8

9

10


1mv50ms

1mv50ms

1mv50ms

1mv50ms

dagger

◼

◼

◼

◼

◼

◼

Dagger

times

times

times

lowast

lowast

lowast

lowast

lowast







4 Conclusion




Acknowledgments


References























of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of

















LPVs RPVs

L2L3

L1

B9

LRotAB7

B8bull bull

bull


L1

1

2

34

5

6

78

9

10

L2

123

4

5

6

7

8

9

10

L3

1

2

3

45

6

7

8

9

10

12

3

45

6

7

8

910


1mv50ms

1mv50ms

1mv50ms

1mv50ms

dagger

Dagger

Dagger

Dagger

Dagger

lowast

lowast

lowast

lowast







LPVs RPVs

L1L3 L2

B9B2

B1 and B10

LRotA

bull bull bull


L1

1

2

3

4

5

6

7

8

9

10

L2

1

2

3

4

5

6

7

8

9

10

1

2

3

4

5

67

8

910

dagger

dagger

dagger

dagger

L3

1

2

3

45

6

7

8

9

10


1mv50ms

1mv50ms

1mv50ms

1mv50ms

dagger

◼

◼

◼

◼

◼

◼

Dagger

times

times

times

lowast

lowast

lowast

lowast

lowast







4 Conclusion




Acknowledgments


References























of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of

















LPVs RPVs

L1L3 L2

B9B2

B1 and B10

LRotA

bull bull bull


L1

1

2

3

4

5

6

7

8

9

10

L2

1

2

3

4

5

6

7

8

9

10

1

2

3

4

5

67

8

910

dagger

dagger

dagger

dagger

L3

1

2

3

45

6

7

8

9

10


1mv50ms

1mv50ms

1mv50ms

1mv50ms

dagger

◼

◼

◼

◼

◼

◼

Dagger

times

times

times

lowast

lowast

lowast

lowast

lowast







4 Conclusion




Acknowledgments


References























of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of


















4 Conclusion




Acknowledgments


References























of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of





















of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of
















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