AI-derived cardiac volume from chest CT identified echocardiography-defined cardiomegaly with AUC of 0.81 in men, 0.77 in women, and ICC of 0.93 repeatability.
Does AI-enabled cardiac volumetry from non-contrast chest CT accurately identify echocardiography-defined cardiomegaly?
Automated AI-based cardiac volumetry from routine non-contrast chest CT can serve as an objective, opportunistic biomarker for identifying cardiomegaly.
Absolute Event Rate: 0% vs 0%
Abstract Background Cardiomegaly is a clinically significant incidental finding on chest CT associated with heart failure, arrhythmias, and sudden cardiac death. Qualitative radiologist assessment is variable, and automated AI tools may enable objective opportunistic cardiac volumetry. Purpose To evaluate whether AI–enabled total cardiac volume (TCVAI) derived from non–ECG-gated, non-contrast chest CT can identify cardiomegaly as defined by echocardiography. Methods This retrospective study included 307 consecutive patients (median age, 67 years; 56% male) who underwent non-contrast chest CT at a single center on 7 scanner types (4 vendors) and clinically indicated echocardiography within 31 days. A commercially available AI tool (AI-Rad Companion, Siemens Healthineers) automatically quantified TCVAI, indexed to body surface area (TCVAI/BSA). Echocardiography reports were reviewed for chamber dilation and left ventricular hypertrophy (LVH), collectively defined as cardiomegaly. Associations between TCVAI/BSA and echocardiographic findings were assessed using correlation, ordinal regression, and receiver operating characteristic (ROC). Interscan repeatability was evaluated in 248 patients with 544 repeat CT examinations. Prespecified sex-specific thresholds were tested in a temporally independent validation cohort of 50 patients. Results Median TCVAI was higher in patients with cardiomegaly than those without (1061.9 mL vs 798.4 mL; p 0.001). TCVAI/BSA was associated with chamber dilation and LVH severity on univariate analysis and remained associated in multivariable ordinal models, except for right ventricular dilation. Discriminatory performance was fair to good, with AUC 0.81 (95%CI: 0.75–0.87) in men and 0.77 (95%CI: 0.69–0.85) in women. Interscan repeatability was excellent (ICC: 0.93). In independent validation, performance ranged from sensitivity 89.3%/specificity 27.3% at a high-sensitivity threshold to sensitivity 28.6%/specificity 100% at a high-specificity threshold. Conclusion AI-derived cardiac volume from routine chest CT shows fair to good performance for identifying echocardiography-defined cardiomegaly with high measurement repeatability, supporting a potential role for automated cardiac volumetry as an objective, opportunistic biomarker.
Fan et al. (Tue,) reported a other. AI-derived cardiac volume from chest CT identified echocardiography-defined cardiomegaly with AUC of 0.81 in men, 0.77 in women, and ICC of 0.93 repeatability.