Rectal Cancer Neoadjuvant Therapy-Real World Study

• Optimisation and predictive modelling of immunotherapy combined with neoadjuvant chemoradiotherapy Through real-world studies, we will evaluate the efficacy and safety of immunotherapy combined with neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer, focusing on comparing outcomes with traditional chemoradiotherapy regimens to optimise neoadjuvant treatment protocols. By integrating radiomics and molecular subtyping data, we will develop a deep learning model to predict the rate of pathological complete response, thereby accurately forecasting treatment outcomes for patients. This model can further optimise personalised treatment decisions, enhance the effectiveness of organ-preservation strategies, and ultimately reduce surgical trauma for patients.
• A Treatment Efficacy Assessment System Combining Multi-omics Data with Artificial Intelligence Integrate multi-omics data (such as molecular subtyping, radiomics, and pathological assessment) with artificial intelligence technology to establish a treatment efficacy assessment system. Utilise deep learning models to analyse pre- and post-treatment imaging data and pathological samples, thereby achieving precise efficacy assessment.

Inclusion criteria

• The patient is informed and has provided written informed consent;
• Rectal adenocarcinoma confirmed by colonoscopic biopsy and pathology, meeting the following criteria:

• Clinical stage II/III locally advanced rectal cancer (LARC): cT1-4aN0-2M0;
• The distal edge of the tumor is ≤ 10 cm from the anal verge (measured by MRI);
• No distant metastasis;
• Scheduled to receive neoadjuvant therapy;
• Age ≥ 18 years, male or female。

Exclusion criteria

• Presence of distant organ metastasis;
• Multiple primary colorectal cancers;
• History of prior malignancy (except completely cured carcinoma in situ of the cervix, basal cell carcinoma, or squamous cell carcinoma of the skin).