70-year-old White male patient with weight of 79.8 kg, BMI of 29.3, low cardiovascular risk factors (nonsmoker, no diabetes diagnosis, blood pressure of 120/78). Left: Axial CT image at level of L3 vertebral body. Right: Matching automated segmentation label map. Visceral fat area z score is 1.41, corresponding to the 92nd percentile. Patient experienced both subsequent myocardial infarction and stroke.

August 31, 2022 — According to ARRS’ American Journal of Roentgenology (AJR), fully automated and normalized body composition analysis of abdominal CT has promise to augment traditional cardiovascular risk prediction models. 

“Visceral fat area from fully automated and normalized analysis of abdominal CT examinations predicts subsequent myocardial infarction or stroke in Black and White patients, independent of traditional weight metrics, and should be considered as an adjunct to BMI in risk models,” wrote first author Kirti Magudia, MD, PhD, currently from the department of radiology at Duke University School of Medicine. 

Dr. Magudia and colleagues’ retrospective study numbered 9,752 outpatients (5,519 women, 4,233 men; 890 self-reported Black, 8,862 self-reported White; mean age, 53.2 years) who underwent routine abdominal CT at Brigham and Women’s Hospital or Massachusetts General Hospital from January–December 2012, sans a major cardiovascular or oncologic diagnosis within 3 months of examination. Fully automated deep learning body composition analysis was performed at the L3 vertebral level to determinate three body composition areas: skeletal muscle area, visceral fat area, and subcutaneous fat area. Subsequent myocardial infarction or stroke was established via electronic health records. 

Ultimately, after normalization for age, sex, and race, visceral fat area derived from routine CT was associated with risk of myocardial infarction (HR 1.31 [1.03–1.67], p=.04 for overall effect) and stroke (HR 1.46 [1.07–2.00], p=.04 for overall effect) in multivariable models in Black and White patients; normalized weight, BMI, skeletal muscle area, and subcutaneous fat area were not. 

Noting that their large study demonstrates a pipeline for body composition analysis and age-, sex-, and race-specific reference values to add prognostic utility to clinical practice, “we anticipate that fully automated body composition analysis using machine learning could be widely adopted to harness latent value from routine imaging studies,” the authors of this AJR article concluded

For more information: www.arrs.org 


Related Content

News | Cardiac Imaging

Aug. 20, 2026 – The novel, radiopaque, polymer-based embolic coil from Embolization, Inc. has now surpassed 125 implants ...

Time August 20, 2026
arrow
News | Breast Imaging

Aug. 13, 2026 – Perimeter Medical Imaging AI recently announced that Intermountain Health, the largest nonprofit health ...

Time August 14, 2026
arrow
News | Lung Imaging

Aug. 11, 2026 — Noah Medical has launched the Galaxy II software, the next evolution of its robotic-assisted ...

Time August 10, 2026
arrow
News | Radiology Business

Aug. 4, 2026 — Canon Medical Systems USA (CMSU) has appointed Tsuneo "Neo" Imai as president and chief executive officer ...

Time August 10, 2026
arrow
News | Computed Tomography (CT)

July 23, 2026 — HOPPR has introduced HOPPR EF Chest CT Narrative Model, a foundation model that processes 3D chest CT ...

Time July 27, 2026
arrow
News | Point-of-Care Ultrasound (POCUS)

July 21, 2026 — Fujifilm Sonosite has launched Sonosite iLOOK, a compact ultrasound solution designed specifically for ...

Time July 22, 2026
arrow
News | Radiology Imaging

June 15, 2026 — Lead Glass Pro, a supplier of radiation shielding products, has expanded its turnkey installation ...

Time June 18, 2026
arrow
News | Nuclear Imaging

June 1, 2026 — At the 2026 Society of Nuclear Medicine and Molecular Imaging (SNMMI) annual meeting, GE HealthCare will ...

Time June 02, 2026
arrow
News | Radiopharmaceuticals and Tracers

June 1, 2026 — Serac Healthcare Ltd. has presented Phase 2 data showing that SPECT-CT imaging with the radiotracer 99mTc ...

Time June 01, 2026
arrow
News | Radiology Imaging

May 18, 2026 — DICO, a company specializing in the creation of distributed diagnostic infrastructure for radiology, has ...

Time May 19, 2026
arrow
Subscribe Now