Development and Validation of Artificial Intelligence-Based Algorithms for Predicting the Segments Debulked by Rotational Atherectomy Using Intravascular Ultrasound Images - 29/06/24
, Daiju Ueda, MD b, Akinori Sumiyoshi, MD c, Katsuyuki Hasegawa, MD d, Rei Fukuhara, MD e, Munemitsu Otagaki, MD f, Atsunori Okamura, MD c, Wataru Yamamoto, MD d, Naoki Kawano, MD e, Akira Yamamoto, MD b, Yukio Miki, MD b, Iichiro Shiojima, MD aRésumé |
We develop and evaluate an artificial intelligence (AI)-based algorithm that uses pre-rotation atherectomy (RA) intravascular ultrasound (IVUS) images to automatically predict regions debulked by RA. A total of 2106 IVUS cross-sections from 60 patients with de novo severely calcified coronary lesions who underwent IVUS-guided RA were consecutively collected. The 2 identical IVUS images of pre- and post-RA were merged, and the orientations of the debulked segments identified in the merged images were marked on the outer circle of each IVUS image. The AI model was developed based on ResNet (deep residual learning for image recognition). The architecture connected 36 fully connected layers, each corresponding to 1 of the 36 orientations segmented every 10°, to a single feature extractor. In each cross-sectional analysis, our AI model achieved an average sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 81%, 72%, 46%, 90%, and 75%, respectively. In conclusion, the AI-based algorithm can use information from pre-RA IVUS images to accurately predict regions debulked by RA and will assist interventional cardiologists in determining the treatment strategies for severely calcified coronary lesions.
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Keywords : artificial intelligence, calcification, deep learning, rotational atherectomy
Plan
| Funding: This study was supported by the Research Grant D2 from Kansai Medical University, Hirakata, Japan, and a grant from an Academic Support Award: Japanese Association of Cardiovascular Intervention and Therapeutics, Tokyo, Japan. |
Vol 223
P. 1-6 - juillet 2024 Retour au numéro
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- Optimal Intravascular Ultrasound-Guided Percutaneous Coronary Intervention in Patients With Multivessel Disease and Diabetes
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