csmc artificial intelligence in medicine (aim) program

CSMC Artificial Intelligence in Medicine (AIM) Program

Guido Germano, PhD

Quantitative gated nuclear imaging

Disclosure: receipt of software royalties from

Cedars-Sinai Medical Center

Cardiac perfusion SPECT: quantitative analysis

Defect extent, severity

& reversibility

Categorical, summed

& normalized scores

TPD

LVEF

ESV and EDV

Diastolic function

RWM & RWT

Phase analysis

Lung/heart ratio

TID ratio

LV shape

LV mass

PERFUSION

QUANTITATION

FUNCTION

QUANTITATION

OTHER

QUANTITATION

INTEGRATED ANALYSIS

Projections (rest & stress)

Short axis (rest & stress)

Gated short axis

(rest & stress)

Cardiac SPECT perfusion/function quantification

QGS/QPS/AutoQUANT (Cedars-Sinai)

Emory Toolbox(Emory Univ.)

4D-MSPECT(Univ. of Michigan)

Main commercially available software

Germano et al., J Nucl Cardiol 2007;14:433

Garcia et al., J Nucl Cardiol 2007;14:420

Ficaro et al., J Nucl Cardiol 2007;14:455

Validation / normal limits info: www.csaim.com/validation

Quantitative measures of perfusion

Segment-based:

Categorical scores (0-4)

Summed scores (combine extent & severity)

Normalized summed scores (indep. of # segments in model)

Pixel-based:

Extent of defect [%]

Severity of defect

Total perfusion deficit (TPD) [Berman, JNC 2004]

Quantitative measures of perfusion

Gated perfusion SPECT quantitation

LVEF = (EDV-ESV)/EDV * 100

EDV= 3D endocardium at ED

ESV= 3D endocardium at ES

WM = endocardial excursion

WT mostly from partial volume effect

Diastolic function = derivative of T-V curve

J Nucl Med 2009; 50:1418–1426Supported by NIH NHLBI R01 grant: R0HL089765

Visual contour QC Expert agreement

Automatic “bad contour” detectionIncorrect LV Incorrect VP

SQC VPO-VQC VPU-VQC

ROC Area

P value

Sensitivity

Specificity

1.0±0.00

< 0.0001

100%

98%

0.91±0.01

< 0.0001

100%

71%

0.97±0.01

< 0.0001

100%

77%

JNM 2009 J Nucl Med. 2009 Sep;50(9):1418-26 Supported by NHLBI R01 grant: R0HL089765

High accuracy for LV

segmentation detection in

MPS demonstrates that

this algorithm may improve

automated and objective

analysis of MPS.

ROC -bad

contour

Detection

Area =1.0

Abnormality thresholds of SPECT EF and volumes

Gender LVEF EDV ESV

Cedars QGS F 51% 102 ml 46 ml

8 fr, Tc-99m (60 ml/m2) (27 ml/m2)

(Sharir, JNC 2006) M 43% 149 ml 75 ml

(75 ml/m2) (39 ml/m2)

Emory ECT F+M 51% 171 ml 70 ml8 or 16 fr

(Garcia, JNC 2007)

4D-MSPECT F 56-60% 118-122 ml 44-42 ml

8-16 fr, Tc-99m (66-68 ml/m2) (25-24 ml/m2)

(Ficaro, JNC 2007) M 47-52% 183-197 ml 91-82 ml

(91-98 ml/m2) (46-41 ml/m2)

LVEF measurement: 8- vs. 16-frame gating

EDV = 114 ml

ESV = 37 ml

LVEF = 68%

EDV = 111 ml

ESV = 41 ml

LVEF = 63%

Diastolic function: normal limits (QGS)

Akincioglu, JNM 2005

90 normal patients

Mean values:

PFR: 2.62 ± 0.46 EDV/s

TTPF: 164.6 ± 21.7 ms

Abnormality thresholds:

PFR < 1.71 EDV/s

TTPF: > 216.7 ms

PFR

ESV

EDV

Phase analysis in gated perfusion SPECT

The time-volume curve

can be broken down by

segment, wall, vessel, etc.

Example

Phase analysis in gated perfusion SPECT

Van Kriekinge JNM 2008

Phase analysis helps predict response to CRT

Boogers et al, JNM 2009

Integration with CTA

Kaufmann PA, Gaemperli O. J Nucl Cardiol 2009;16: 170-72.

Complementary MPI-CTA ?

Slomka et al, Expert Rev Cardiovascular Therapy 2008 Jan;6(1):27-41

Estimate: 10-15% of patients need both

J Nucl Med 2009;

50:1621–1630

Automatically Match Cardiac Phase

•Evaluate cost functional across all phases

where k denotes phase number and n is total number of phase and E is the cost functional

*

1 2 3{1,..., }

arg min ( , , , ),kk n

k E c c c

Phase 9 Phase 16

where

Woo et al. Med Phy 2009 (accepted)

Automatically Match Cardiac

Phase

•Evaluate cost functional across all phases

where k denotes phase number and n is total number of phase and E is the cost functional

*

1 2 3{1,..., }

arg min ( , , , ),kk n

k E c c c

Phase 9 Phase 16

where

Woo et al. Med Phy 2009 (accepted)Woo et al. Med Phys. 2009;36:5467-79.

Automated MPS/CTA image fusion

Translations

0.0

1.0

2.0

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X Y Z

[mm

]

Rest

Stress

Rotations

0

1

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7

Angle X Angle Y Angle Z

Deg

ree

Rest

Stress

Accuracy of automated CTA-MPI fusion

Rigid

body

1-2 sec

Computing

time

Slomka

et al

JNM2009

QPS analysis: original contours

TPD =1%

SSS =1

#3

QPS analysis with CTA-guided contours

RCA TPD

7 %

SPECT/CTA volume/surface fusionCATH: proximal RCA 100%, no significant LAD, LCX disease

#3

RCARCA

0

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itiv

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LAD-TPD

CTA guided

LAD TPD

0

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itiv

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LCX-TPD

CTA guided

LCX TPD

0

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en

sit

ivit

y

RCA-TPD

CTA guided

RCA TPD

**

CTA-guided MPS quantification

LCX RCA

N=35

patients

J Nucl Med 2009; 50:1621–1630

CTA-MPS fusion: possible applications

comparison of CTA and MPS perfusion imaging

Cedars-Sinai Medical Center

Normal ROI, plaque lesion limits, fast luminal centerline within limits

Automatic CTA measurements/annotation

NCPNCP volume 112 mm3

Dey et al, ACC 2010

Quantitative PET

Motion-frozen perfusion imaging

Images obtained at Cedars-Sinai Project PI: Dan Berman

Lantheus clinical trial 18F- flurpiridaz (BMS747158)

EF stress QPET/QGS Rb-82 vs. post-stress CTA

EF QPET vs. CTA

10

20

30

40

50

60

70

80

90

10 20 30 40 50 60 70 80 90

EF-CT

QP

ET

EF

-str

Identity

Difference Plot

-20

-15

-10

-5

0

5

10

15

10 20 30 40 50 60 70 80 90

Mean of All

Dif

fere

nce (

QP

ET

EF

-str

- E

F-C

T)

Identity

Bias (-3.1)

95% Limits of agreement

(-17.2 to 11.1)

Bias = -3%

r =0.90

EF QGS vs CTA

10

20

30

40

50

60

70

80

90

10 20 30 40 50 60 70 80 90

EF-CT

QG

S E

F-s

tr

Identity

Difference Plot

-30

-25

-20

-15

-10

-5

0

5

10 20 30 40 50 60 70 80 90

Mean of All

Dif

fere

nce (

QG

S E

F-s

tr -

EF

-CT

)

Identity

Bias (-13.6)

95% Limits of agreement

(-28.0 to 0.9)

Bias= -14%

r =0.87

Slomka, Germano, Bengel, J Nucl Med. 2009; 50 (Supplement 2):1167

PET/CT fusion ED

Slomka, Germano, Bengel et al, SNM 2009

PET/CT fusion ES

Gated PET vs. Gated CTA

GATED SPECT FOR DIASTOLIC

PERFUSION ASSESSMENT

“Motion frozen” gated myocardial perfusion SPECT

Summed images (8 frames)

Conventional summation Summation after morphing

to ED template

Slomka et al., JNM 2004

“Motion frozen” gated myocardial perfusion SPECT

Slomka et al., JNM 2004

Displacement

vectors are used for

warping ES onto

ED

MF accuracy in obese population

0102030405060708090

100

Sensitivity Specificity Accuracy0

102030405060708090

100

Sensitivity Specificity Accuracy

S-TPD

MF-TPD

P = NS P = NS

92% 92%

59%

82% 82%88%

P < 0.05P < 0.05

P < 0.05

P < 0.05

93% 95%

55%

77%80%

89%

A B≥50% Stenosis ≥70% Stenosis

N=90

Suzuki Y et al. J Nucl Med. 2008 Jul;49(7):1075-9

QUANTITATIVE RVEF

FROM PERFUSION SPECT

Case example