AI-Based Prediction of Pathological Response in Rectal Cancer Patients Receiving Total Neoadjuvant Therapy

This study aims to better understand how body composition, inflammation, and nutrition affect how rectal cancer responds to treatment. We reviewed data from ninety-three patients who were treated with total neoadjuvant therapy (TNT), which includes both chemotherapy and radiation before surgery. Using blood tests and CT scans, we measured muscle loss (sarcopenia), inflammation, and nutritional status before and after treatment. This study aims to better understand how body composition, inflammation, and nutrition affect rectal cancer response to treatment. We retrospectively analyzed data from ninety-three patients who received total neoadjuvant therapy (TNT), including both chemotherapy and radiation prior to surgery. Blood tests and CT scans were used to assess inflammation, nutrition, and muscle loss (sarcopenia) before and after treatment. The objective was to identify predictors of complete pathological response. Two novel composite scores were developed from routine lab parameters and tested for their predictive value. Artificial intelligence (AI) was also applied to enhance model accuracy. This study was conducted at Etlik City Hospital in Ankara, Turkey. No experimental interventions were performed. All data were obtained from routine care, and no additional procedures or patient compensation were involved. The findings may support personalized treatment decisions in rectal cancer.