Volumetric assessment of body composition from cardiac SPECT CT attenuation maps and association of sarcopenia measures with mortality

Jirong Yi, PhD^a Anna M. Michalowska, MD,PhD^a,b Aakash Shanbhag, MSc^a,c Robert J. Miller, MD^a,d Jolien Geers, MD^a,e Wenhao Zhang, PhD^a Aditya Killekar, MSc^a Nipun Manral, MSc^a Mark Lemley, BSc^a Jianhang Zhou, MSc^a Joanna X. Liang, MPH^a Valerie Builoff, BSc^a Terrence D. Ruddy, MD^f Andrew J. Einstein, MD,PhD^g Attila Feher, MD,PhD^h Edward J. Miller, MD,PhD^h Albert J. Sinusas, MD,PhD^h Mikolaj Buchwald, PhD^a Jacek Kwiecinski, MD,PhDⁱ Paul B. Kavanagh, MSc^a Damini Dey, PhD^a Daniel S. Berman, MD^a

Piotr J. Slomka, PhD^a

^a Cedars-Sinai Medical Center, USA ^b National Medical Institute of the Ministry of the Interior and Administration, Poland ^c University of Southern California, USA ^d University of Calgary, Calgary, Canada ^e Vrije Universiteit Brussel (VUB), Belgium ^f University of Ottawa Heart Institute, Canada ^g Columbia University Irving Medical Center and New York-Presbyterian Hospital, USA ^h Yale University School of Medicine, United States ⁱ Institute of Cardiology, Poland

2024 SNMMI ABSTRACT #2167 [Yi et al., SNMMI 2024]

Slomka Laboratory, CSMC

Body Composition

• CT attenuation correction (CTAC)
• to correct for soft-tissue attenuation
• contains additional anatomic and pathological information, which is not typically utilized in clinical assessment

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• Body composition analysis
• reflects the amount and distribution of body tissues, such as skeletal muscles or adipose tissue
• patients with abnormal body composition measurements are associated with worse outcomes and increased mortality

​

CTAC

Segmentation

• To develop fully automated and annotation-free 6-tissue body composition segmentation algorithm from SPECT CT attenuation maps and evaluate its prognostic significance

Aims

Cohort creation

• Computed tomography for attenuation correction (CTAC)
• Epicardial adipose tissue (EAT)

Cohort creation

4 sites from REFINE SPECT registry

Methods

Deep Learning

Coronary Artery Calcium

MPI

Analysis

Medical

History

SPECT/CT MPI

​

• 10,369 patients
• 4 sites

Volumetric

Quantification

Prognostic

Evaluation

CTAC – CT attenuation correction,

MPI – myocardial perfusion imaging

Algorithm design

CTAC

Rib cage segmentation (convex hull)

[1] Wasserthal Radiology: AI 2023

[2] Miller npj Digital Medicine 2024

Intramuscular adipose tissue

Skeletal muscle

Bone

Visceral adipose tissue

Subcutaneous adipose tissue

Epicardial adipose tissue

Integration

CTAC – computed tomography attenuation correction

Pretrainedmodel [2]

Pretrainedmodel [1]

5 body composition tissues segmentation (thresholding)

Volumetric Quantification

T5

T11

Compute volume index from T5-T11 (appear in 96.4% patient computed tomography attenuation correction scans)

Volume index: volume divided BSA, in cm³/m²

Analysis

• Risk stratification thresholds: Youden index-based

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• Kaplan-Meier curves

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• Unadjusted and adjusted Cox regression

Imaging quantification data (3):

stress total perfusion deficit, left ventricular ejection fraction, coronary artery calcium score

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History:

Clinical data (8): age, body mass index, gender, family coronary artery disease history, diabetes, dyslipidemia, hypertension, smoking

11 covariates for adjustment

Segmentation results

CTAC

Segmentation

Non-EAT visceral adipose tissue

Bone

Skeletal muscle

Subcutaneous adipose tissue

Intramuscular adipose tissue

Epicardial adipose tissue

Axial

Coronal

Sagittal

Results: Volume index

Non-EAT visceral adipose tissue

Bone

Skeletal muscle

Subcutaneous adipose tissue

Intramuscular adipose tissue

Epicardial adipose tissue

Cox Regression Hazard Ratio Results

EAT - Epicardial Adipose Tissue, IMAT - Intramuscular Adipose Tissue, SAT - Subcutaneous Adipose Tissue, SM - Skeletal Muscle, VAT - Visceral Adipose Tissue

Results: Epicardial adipose tissue

Epicardial adipose tissue (EAT)

HR 1.7 [1.4, 2.0], <0.01

Results: Intramuscular adipose tissue

Intramuscular adipose tissue (IMAT)

HR 1.3 [1.1, 1.6], <0.01

Results: Skeletal muscle

Skeletal muscle (SM)

HR 0.5 [0.4, 0.6], <0.01

Results

Intramuscular Adipose Tissue

Skeletal muscle

Bone

Visceral Adipose Tissue

Subcutaneous Adipose Tissue

D E F

A B C

2024 SNMMI ABSTRACT #2167 [Yi et al., SNMMI 2024]

Slomka Laboratory, CSMC

Results

Intramuscular AT

Skeletal muscle

Bone

Visceral AT

Subcutaneous Adipose

Tissue (AT)

D E F

A B C

2024 SNMMI ABSTRACT #2167 [Yi et al., SNMMI 2024]

Slomka Laboratory, CSMC

• Volumetric body composition analysis can be performed automatically from chest CT attenuations scans and is related to all-cause mortality

​

​

• Several volumetric

body composition

measures predict

all-cause mortality

Conclusions

Acknowledgement: Supported in part by Grants R01HL089765 and R35HL161195 from the National Heart, Lung, and Blood Institute/National Institutes of Health (NHLBI/NIH) (PI: Piotr Slomka).

Multivariate analysis