European heart journal. Digital health · 2026
Real-life clinical validation of artificial intelligence-assisted echocardiography for aortic root and left ventricular outflow tract measurements against human readers and cardiac magnetic resonance.
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Mołek-Dziadosz Patrycja, Bondarchuk Oleksandra, Woźniak Aleksandra, Królikowska Maria, Mirek Agnieszka, Furman-Niedziejko Anna, Mazur Karol, Ostrowska-Kaim Elżbieta, Golińska-Grzybała Karolina, Siniarski Aleksander, Szachowicz-Jaworska Joanna, Miszalski-Jamka Tomasz, Rychlak Radosław, Dweck Marc R, Nessler Jadwiga, Gackowski Andrzej
Аннотация
AIMS: Artificial intelligence (AI) algorithms may improve echocardiographic measurement standardization, but direct validation against cardiovascular magnetic resonance (CMR) remains limited. This study aimed to evaluate the agreement between AI-assisted transthoracic echocardiography (TTE), expert manual TTE, and CMR as a gold standard for aortic root and left ventricular outflow tract (LVOT) diameters.
METHODS AND RESULTS: Out of 183 patients with analysable TTE and CMR recordings performed within 7 days, 169 had complete measurements of LVOT, sinotubular junction (STJ), and sinus of Valsalva (SoV) by AI and were included in the primary analysis. Automated AI measurements were obtained using the US2.ai platform and compared with those of expert echocardiographers and CMR. Agreement was assessed using intraclass correlation coefficients (ICC) and Bland-Altman analysis. Agreement between Expert 1 and CMR, and Expert 2 and CMR, yielded ICCs: 0.63 (95% CI: 0.50-0.73) and 0.51 (95% CI: 0.36-0.65) for LVOT, 0.71 (95% CI: 0.63-0.78) and 0.82 (95% CI: 0.73-0.87) for STJ, and 0.85 (95% CI: 0.79-0.89) to 0.85 (95% CI: 0.78-0.89) for SoV, respectively. Artificial intelligence-derived measurements demonstrated comparable agreement with CMR: ICC 0.70 (95% CI: 0.61-0.77) for LVOT, 0.77 (95% 0.70-0.83) for STJ, and 0.77 (95% 0.70-0.83) for SoV. Clinically significant differences (≥2 mm for LVOT and ≥4 mm for STJ and SoV) between AI and CMR measurements were observed in 36.7% of LVOT, 20% of STJ, and 11.8% of SoV measurements.
CONCLUSION: Artificial intelligence-assisted echocardiography showed comparable agreement for aortic root and LVOT measurements, but physician oversight remains necessary.
METHODS AND RESULTS: Out of 183 patients with analysable TTE and CMR recordings performed within 7 days, 169 had complete measurements of LVOT, sinotubular junction (STJ), and sinus of Valsalva (SoV) by AI and were included in the primary analysis. Automated AI measurements were obtained using the US2.ai platform and compared with those of expert echocardiographers and CMR. Agreement was assessed using intraclass correlation coefficients (ICC) and Bland-Altman analysis. Agreement between Expert 1 and CMR, and Expert 2 and CMR, yielded ICCs: 0.63 (95% CI: 0.50-0.73) and 0.51 (95% CI: 0.36-0.65) for LVOT, 0.71 (95% CI: 0.63-0.78) and 0.82 (95% CI: 0.73-0.87) for STJ, and 0.85 (95% CI: 0.79-0.89) to 0.85 (95% CI: 0.78-0.89) for SoV, respectively. Artificial intelligence-derived measurements demonstrated comparable agreement with CMR: ICC 0.70 (95% CI: 0.61-0.77) for LVOT, 0.77 (95% 0.70-0.83) for STJ, and 0.77 (95% 0.70-0.83) for SoV. Clinically significant differences (≥2 mm for LVOT and ≥4 mm for STJ and SoV) between AI and CMR measurements were observed in 36.7% of LVOT, 20% of STJ, and 11.8% of SoV measurements.
CONCLUSION: Artificial intelligence-assisted echocardiography showed comparable agreement for aortic root and LVOT measurements, but physician oversight remains necessary.