Renal Cancer Treatment

Renal cancer treatment research heavily focuses on improving surgical planning and predicting treatment response. Current efforts utilize advanced image analysis techniques, including deep learning models like U-Net and its variants, to accurately segment kidney structures (tumor, arteries, veins) from CT scans, aiding in pre-operative planning and minimally invasive procedures. Furthermore, research is exploring AI-driven methods to predict the effectiveness of anti-angiogenic therapies based on readily available histopathology slides, potentially improving patient outcomes by personalizing treatment strategies. These advancements promise to enhance the precision and efficacy of renal cancer treatment.