CardioSyntax: end-to-end SYNTAX score prediction -- dataset, benchmark and method

• URL: http://arxiv.org/abs/2407.19894v2
• Date: Tue, 06 May 2025 11:18:38 GMT
• Title: CardioSyntax: end-to-end SYNTAX score prediction -- dataset, benchmark and method
• Authors: Alexander Ponomarchuk, Ivan Kruzhilov, Galina Zubkova, Artem Shadrin, Ruslan Utegenov, Ivan Bessonov, Pavel Blinov,
• Abstract summary: The SYNTAX score has become a widely used measure of coronary disease severity.<n>This paper introduces a new medical regression and classification problem - automatically estimating SYNTAX score from coronary angiography.<n>We present a comprehensive CardioSYNTAX dataset of 3,018 patients for the SYNTAX score estimation and coronary dominance classification.
• Score: 36.440495538328754
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The SYNTAX score has become a widely used measure of coronary disease severity, crucial in selecting the optimal mode of the revascularization procedure. This paper introduces a new medical regression and classification problem - automatically estimating SYNTAX score from coronary angiography. Our study presents a comprehensive CardioSYNTAX dataset of 3,018 patients for the SYNTAX score estimation and coronary dominance classification. The dataset features a balanced distribution of individuals with zero and non-zero scores. This dataset includes a first-of-its-kind, complete coronary angiography samples captured through a multi-view X-ray video, allowing one to observe coronary arteries from multiple perspectives. Furthermore, we present a novel, fully automatic end-to-end method for estimating the SYNTAX. For such a difficult task, we have achieved a solid coefficient of determination R2 of 0.51 in score value prediction and 77.3% accuracy for zero score classification.

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