Automated pericardium delineation and epicardial fat volume quantification from noncontrast CT

Medical Physics
Xiaowei DingDamini Dey

Abstract

The authors aimed to develop and validate an automated algorithm for epicardial fat volume (EFV) quantification from noncontrast CT. The authors developed a hybrid algorithm based on initial segmentation with a multiple-patient CT atlas, followed by automated pericardium delineation using geodesic active contours. A coregistered segmented CT atlas was created from manually segmented CT data and stored offline. The heart and pericardium in test CT data are first initialized by image registration to the CT atlas. The pericardium is then detected by a knowledge-based algorithm, which extracts only the membrane representing the pericardium. From its initial atlas position, the pericardium is modeled by geodesic active contours, which iteratively deform and lock onto the detected pericardium. EFV is automatically computed using standard fat attenuation range. The authors applied their algorithm on 50 patients undergoing routine coronary calcium assessment by CT. Measurement time was 60 s per-patient. EFV quantified by the algorithm (83.60 ± 32.89 cm(3)) and expert readers (81.85 ± 34.28 cm(3)) showed excellent correlation (r = 0.97, p < 0.0001), with no significant differences by comparison of individual data points (p = 0.15). Voxe...Continue Reading

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Citations

Mar 18, 2016·Journal of Cosmetic and Laser Therapy : Official Publication of the European Society for Laser Dermatology·Diane Irvine DuncanRobbin Temaat
Jun 14, 2016·The International Journal of Cardiovascular Imaging·Bai-Chin LeeMing-Fong Chen
Jul 12, 2018·IEEE Transactions on Medical Imaging·Frederic CommandeurDamini Dey
Feb 25, 2020·Radiology. Artificial Intelligence·Frederic CommandeurDamini Dey
Nov 20, 2019·Current Atherosclerosis Reports·Andrew LinNitesh Nerlekar
Feb 27, 2021·Atherosclerosis·Marco GuglielmoGianluca Pontone
Jun 2, 2021·Medical Physics·Xiaogang LiBenqiang Yang

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