Multi-objective optimization framework to plan laser ablation procedure for prostate tumors through a genetic algorithm.
Journal:
Computer methods and programs in biomedicine
Published Date:
May 2, 2025
Abstract
BACKGROUND AND OBJECTIVES: Prostate cancer is the most common form of cancer in the male population. While the survival rate is high, many patients undergo surgical procedures for prostate cancer that might never progress to clinical significance. As a result, minimally invasive therapies are increasingly preferred over chemotherapy, radiotherapy, or surgical interventions. Laser-induced hyperthermia is emerging as a promising minimally invasive technique that targets tumoral tissue without damaging the surrounding healthy prostate. However, the lack of a standardized protocol makes the procedure highly dependent on the surgeon's expertise. Indeed, besides the cancerous tissue, also the healthy one could be heated and undergo a necrosis. Consequently, two contrasting objectives have to be considered during the treatment design: to treat cancer without damaging healthy tissue. Therefore, in this work, a thorough multi-objective optimization is carried out with reference to the laser-induced thermal ablation framework for prostate tumors. This is achieved by coupling finite element simulations with a genetic algorithm-based optimization to identify the best settings for the procedure.
