State-of-the-art artificial intelligence methods for pre-operative planning of cardiothoracic surgery and interventions: a narrative review

Abstract

AI has been introduced in preoperative planning for cardiothoracic procedures to support clinicians by increasing segmentation accuracy, reducing preoperative planning time, and automating several preoperative planning steps such as tumor detection, TAVI prosthesis sizing and other planning measurements. However, the widespread adoption faces several challenges, including the need for robust validation, regulatory approval, and integration into clinical workflows. Additionally, the implementation of AI involves substantial costs, including investments in software development, computational infrastructure, and training of clinical staff. Future research should focus not only on advancing AI technology but also on evaluating the cost-effectiveness to ensure it delivers measurable benefits while remaining accessible and sustainable for healthcare systems. Addressing these issues is essential to realize the full potential of AI in cardiothoracic surgery.

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