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AI-based, automated chamber volumetry from gated, non-contrast CT
Journal article   Peer reviewed

AI-based, automated chamber volumetry from gated, non-contrast CT

Athira J. Jacob, Ola Abdelkarim, Salma Zook, Kristian Hay Kragholm, Prantik Gupta, Myra Cocker, Juan Ramirez Giraldo, Jim O. Doherty, Max Schoebinger, Chris Schwemmer, …
Journal of cardiovascular computed tomography, Vol.17(5), pp.336-340
09/01/2023
DOI: 10.1016/j.jcct.2023.08.001
PMID: 37612232
url
https://arxiv.org/pdf/2311.03371View
Open Access

Abstract

Background: Accurate chamber volumetry from gated, non-contrast cardiac CT (NCCT) scans can be useful for potential screening of heart failure.Objectives: To validate a new, fully automated, AI-based method for cardiac volume and myocardial mass quan-tification from NCCT scans compared to contrasted CT Angiography (CCTA). Methods: Of a retrospectively collected cohort of 1051 consecutive patients, 420 patients had both NCCT and CCTA scans at mid-diastolic phase, excluding patients with cardiac devices. Ground truth values were obtained from the CCTA scans.Results: The NCCT volume computation shows good agreement with ground truth values. Volume differences [95% CI ] and correlation coefficients were:-9.6 [-45; 26] mL, r = 0.98 for LV Total,-5.4 [-24; 13] mL, r = 0.95 for LA,-8.7 [-45; 28] mL, r = 0.94 for RV,-5.2 [-27; 17] mL, r = 0.92 for RA,-3.2 [-42; 36] mL, r = 0.91 for LV blood pool, and-6.7 [-39; 26] g, r = 0.94 for LV wall mass, respectively. Mean relative volume errors of less than 7% were obtained for all chambers.Conclusions: Fully automated assessment of chamber volumes from NCCT scans is feasible and correlates well with volumes obtained from contrast study.
 Cardiac & Cardiovascular Systems Cardiovascular System & Cardiology Life Sciences & Biomedicine Radiology, Nuclear Medicine & Medical Imaging Science & Technology

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