Key result
AccuLV AI-analyzed coronary CT matches ultrasound ejection fraction, yielding 92% specificity for diagnosing cardiac insufficiency.
Why the study?
The study investigated the agreement of ejection fraction measured by coronary CT versus cardiac ultrasound and its specificity in evaluating clinical prognosis in patients with chronic heart failure.
Does ejection fraction measured by coronary CT using AccuLV artificial intelligence software agree with cardiac ultrasound in patients with chronic heart failure?
Observational (n=321)
No
Does ejection fraction measured by coronary CT using AccuLV artificial intelligence software agree with cardiac ultrasound in patients with chronic heart failure?
Coronary CT analyzed with AccuLV artificial intelligence software provides ejection fraction measurements that are highly consistent with cardiac ultrasound in patients with chronic heart failure.
Answers are grounded in this paper and cite their sources.
May support AI-CT for EF assessment in chronic HF; leaves open prospective validation before clinical adoption.
Purpose:This study was dedicated to investigating the agreement of ejection fraction between coronary CT and cardiac ultrasound and specificity in evaluating the clinical prognosis of patients with chronic heart failure. Methods:We conducted a single-center-based retrospective study including 321 patients. All enrolled cases included cardiac ultrasound and coronary CT imaging sequences. The CT images were analyzed using AccuLV artificial intelligence software to calculate the ejection fraction (EF-CT) and compare it with the ejection fraction obtained based on ultrasound (EF). Cardiac insufficiency was determined if the ejection fraction measured by ultrasound was below 50%. Quantitative and qualitative statistical analysis will be performed between EF-CT and EF. Results: Of 319 successfully performed patients, excellent agreement between EF-CT and EF was found in quantitative comparisons and qualitative analysis. Quantitative consistency analysis showed a good correlation between EF-CT and EF values in all cases (R square=0.704, r=0.837). The results of the qualitative diagnostic study showed that the sensitivity and specificity of EF measured by coronary CT had reached a high level of more than 90%, and the positive diagnostic value was up to 96%. Conclusion:The EF-CT and EF have excellent consistency, and AccuLV-based artificial intelligence left ventricular function analysis software can meet the needs of clinical diagnosis and prognostic use.
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Wang et al. (2023) conducted an observational in Chronic heart failure (n=321). Coronary CT with AccuLV artificial intelligence software (EF-CT) vs. Cardiac ultrasound (EF) was evaluated on Diagnostic specificity of EF-CT for detecting cardiac insufficiency (EF < 50%) (Specificity 92%, 95% CI 86-96). Ejection fraction measured by coronary CT using AccuLV artificial intelligence software demonstrated excellent agreement with cardiac ultrasound, achieving 91% sensitivity and 92% specificity for diagnosing cardiac insufficiency.
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