Clinical Feasibility of Artificial Intelligence-Based Autosegmentation of the Left Anterior Descending Artery in Radiotherapy for Breast Cancer

Clinical Feasibility of Artificial Intelligence-Based Autosegmentation of the Left Anterior Descending Artery in Radiotherapy for Breast Cancer

Introduction Breast cancer is a prevalent global disease, and radiotherapy plays a crucial role in its treatment. However, radiotherapy may lead to cardiac complications, particularly in patients receiving left-sided radiotherapy who may experience increased risks due to toxicity in the l...

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Main Authors: Aditi Mohan, Kaustav Talapatra, Manoj Sankhe, G. Kiron, Priyal Maniar, Akshat Kolekar, Saakshi Kushe, Prashant Kharote, Anuradha Singh, Keval Patel, Aayush Gupta, Devarsh Patel, Nikhil Bardeskar, Deepak Patkar
Format: Article
Language:English
Published: Thieme Medical and Scientific Publishers Pvt. Ltd.
Series:Indian Journal of Medical and Paediatric Oncology
Subjects:
breast cancer radiotherapy
autosegmentation
left anterior descending artery contouring
left anterior descending artery sparing
clinical feasibility
artificial intelligence–based contouring
Online Access:http://www.thieme-connect.de/DOI/DOI?10.1055/s-0044-1780510
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Summary:Introduction Breast cancer is a prevalent global disease, and radiotherapy plays a crucial role in its treatment. However, radiotherapy may lead to cardiac complications, particularly in patients receiving left-sided radiotherapy who may experience increased risks due to toxicity in the left anterior descending (LAD) artery. The manual contouring of the LAD artery is time-consuming and subject to variability. This study aimed to provide an overview of artificial intelligence (AI) based LAD artery contouring, assess its feasibility, and identify its limitations.
ISSN:0971-5851
0975-2129

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