Key result
Automated AI echocardiography shows moderate agreement with human readers, yielding an ICC of 0.65 for IVSd.
Why the study?
Detection of disease progression in transthyretin cardiomyopathy is key for personalized treatment, but echocardiography is limited by operator dependence.
Does fully automated AI-assisted echocardiographic measurement provide comparable agreement and repeatability to expert human readers for longitudinal monitoring of ATTR cardiomyopathy?
Observational (n=62)
Yes
Does fully automated AI-assisted echocardiographic measurement provide comparable agreement and repeatability to expert human readers for longitudinal monitoring of ATTR cardiomyopathy?
Fully automated AI echocardiography provides comparable repeatability to expert cardiologists for monitoring ATTR-CM, though moderate absolute agreement and volumetric underestimation suggest expert oversight remains necessary.
Detection of disease progression is key to personalize treatment strategies in transthyretin cardiomyopathy (ATTR-CM), particularly with emerging therapies. Echocardiography can detect subtle longitudinal changes but is limited by operator dependence. This study evaluates agreement and reproducibility of fully automated, AI-assisted echocardiographic measurements under real-world conditions. This retrospective study included 62 patients with ATTR-CM undergoing 178 serial annual echocardiograms assessed by a reference human reader, a second cardiologist (cardiologist 2), a novice reader, and a fully automated AI algorithm (Us2.ai). Interrater agreement was assessed using Bland-Altman analysis and intraclass correlation coefficients (ICCs). Intrarater variability for human readers was derived from repeated blinded measurements, with limits of agreement (LoA = mean difference ± 1.96 × SD) defining the minimal detectable change. AI repeatability was assessed using within-study automated pipeline variability across available acquisitions. AI showed moderate agreement with the reference human reader for IVSd and LVEDV (ICC 0.65 and 0.51), with biases of - 1.9 mm and - 39 mL, respectively. Interrater agreement between cardiologists was good (ICC 0.79 and 0.84) with minimal bias (- 0.2 mm and + 3 mL). Intrarater variability was moderate to excellent for both cardiologists (LoA 3.0 mm and 43 mL for the reference human reader; 2.7 mm and 44 mL for cardiologist 2). AI demonstrated comparable repeatability (LoA 3.6 mm and 37 mL), while the novice showed higher variability (5.1 mm and 61 mL). Fully automated measurements showed within-study variability of similar magnitude to the intrarater variability of experienced readers, although obtained with different experimental designs, supporting further prospective evaluation for serial assessment. Agreement in absolute terms was moderate for wall thickness and LV volumes, indicating expert oversight remains necessary in advanced disease.
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Walser et al. (2026) conducted an observational in Transthyretin cardiomyopathy (ATTR-CM) (n=62). Fully automated AI-assisted echocardiographic measurements (Us2.ai) vs. Reference human reader (board-certified cardiologist) was evaluated on Interrater agreement (ICC) for interventricular septal thickness in diastole (IVSd) (ICC 0.65). Fully automated AI-assisted echocardiographic measurements showed moderate agreement with a reference human reader for interventricular septal thickness (ICC 0.65) and left ventricular end-diastolic volume (ICC 0.51).
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