CardioSyntax: End-to-End SYNTAX Score Prediction - Dataset Benchmark and Method

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 3018 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.