1. AI-based, automated chamber volumetry from gated, non-contrast CT
- Author
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Jacob, Athira J, Abdelkarim, Ola, Zook, Salma, Kragholm, Kristian Hay, Gupta, Prantik, Cocker, Myra, Giraldo, Juan Ramirez, Doherty, Jim O, Schoebinger, Max, Schwemmer, Chris, Gulsun, Mehmet A, Rapaka, Saikiran, Sharma, Puneet, and Chang, Su-Min
- Subjects
Physics - Medical Physics ,Electrical Engineering and Systems Science - Image and Video Processing - 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 quantification 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., Comment: Full version of JCCT technical report. Journal of Cardiovascular Computed Tomography (2023)
- Published
- 2023
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