Research on Intelligent Screening and Decision-making for Neoadjuvant Therapy in Locally Advanced Gastric Cancer Based on Multi-omics Integration

Summary

In this study, investigators utilize a radiopathomics integrated Artificial Intelligence (AI) supportive system to predict tumor response to neoadjuvant chemoradiotherapy (nCRT) before its administration for patients with locally advanced gastric cancer (LAGC). By the system, the postoperative tumor regression grade (TRG) of the participants will be identified based on the radiopathomics features extracted from the pre-nCRT Enhanced CT and biopsy images. The ability to predict TRG will be validated in this multicenter, prospective clinical study.

Eligibility

Inclusion Criteria:

1. Pathological diagnosis of gastric adenocarcinoma
2. Gastric cancer CT evaluation is clinical stage II-IVa (≥ T3, and/or lymph node positive), with or without local tissue or organ invasion, and no distant metastasis.
3. Acceptance criteria for 2-4 courses of 5-FU+platinum neoadjuvant chemotherapy regimen, or 2-4 courses of 5-FU+platinum neoadjuvant chemotherapy combined with trastuzumab regimen, or 2-4 courses of 5-FU+platinum neoadjuvant chemotherapy combined with anti-PD-L1 treatment regimen.
4. D2 gastric cancer radical surgery after neoadjuvant therapy
5. Digital images of enhanced CT images and HE stained gastroscopy biopsy sections before neoadjuvant therapy are available.
6. Complete clinical diagnosis and treatment information, as well as expression information of targeted and immunotherapy related molecular markers.

Exclusion Criteria:

1. Has a history of other tumors.
2. Insufficient imaging quality of CT or biopsy slides, unable to obtain features.
3. Unable to extract molecular information related to research from organizational samples.
4. Interruption of neoadjuvant therapy course for any reason.

Conditions2

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