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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.

August 6, 2026pubmed logopapers

Authors

Mołek-Dziadosz P,Bondarchuk O,Woźniak A,Królikowska M,Mirek A,Furman-Niedziejko A,Mazur K,Ostrowska-Kaim E,Golińska-Grzybała K,Siniarski A,Szachowicz-Jaworska J,Miszalski-Jamka T,Rychlak R,Dweck MR,Nessler J,Gackowski A

Affiliations (7)

  • Department of Coronary Artery Disease and Heart Failure, St. John Paul II Hospital, Prądnicka 80, Kraków 31-202, Poland.
  • Department of Coronary Artery Disease and Heart Failure, Jagiellonian University Medical College, ul. Prądnicka 80, Kraków 31-202, Poland.
  • Department of Emergency Medicine, Jagiellonian University Medical College, Kraków, Poland.
  • Department of Diagnostics, St. John Paul II Hospital, Kraków, Poland.
  • Noninvasive Cardiovascular Laboratory, St. John Paul II Hospital, Kraków, Poland.
  • Department of Radiology, St. John Paul II Hospital, Kraków, Poland.
  • British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom.

Abstract

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. 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. Artificial intelligence-assisted echocardiography showed comparable agreement for aortic root and LVOT measurements, but physician oversight remains necessary.

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Journal Article

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