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Predicting Gastric Cancer Response to Chemo With Multimodal AI Model

Sun Yat-sen University logo

Sun Yat-sen University

Status

Enrolling

Conditions

Chemotherapy Effect
Gastric Cancer

Treatments

Drug: Neoadjuvant chemotherapy with radical tumor resection surgery

Study type

Observational

Funder types

Other

Identifiers

NCT06451393
E2021088

Details and patient eligibility

About

This study aims to develop a multimodal model combining radiomic and pathomic features to predict pathological complete response (pCR) in advanced gastric cancer patients undergoing neoadjuvant chemotherapy (NAC). The researchers intended to collected pre-intervention CT images and pathological slides from patients, extract radiomic and pathomic features, and build a prediction model using machine learning algorithms. The model will be validated using a separate cohort of patients. This research intend to build a radiomic-pathomic model that can outperform models based on either radiomic or pathomic features alone, aiming to improve the prediction of pCR in gastric cancer.

Enrollment

500 estimated patients

Sex

All

Ages

20 to 90 years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • patients with histologically confirmed adenocarcinoma of the stomach or esophagogastric junction who received NAC and radical gastrectomy;
  • patients who underwent abdominal multidetector computed tomography (CT) inspection, gastroscope, and tumor tissue biopsy before any intervention started;
  • Lesions that are assessable according to The Response Evaluation Criteria in Solid Tumors Version 1.1

Exclusion criteria

  • Patients with indistinguishable tumor lesions on the CT images due to insufficient filling of the stomach during the CT inspection;
  • patients without indistinguishable tumor cell on the pathological slides due to inadequate sampling;
  • patients with insufficient data.

Trial design

500 participants in 1 patient group

Neoadjuvant chemotherapy with radical tumor resection surgery
Description:
(i) Patients with indistinguishable tumor lesions on the CT images due to insufficient filling of the stomach during the CT inspection; (ii) patients without indistinguishable tumor cell on the pathological slides due to inadequate sampling; (iii) patients with insufficient data.
Treatment:
Drug: Neoadjuvant chemotherapy with radical tumor resection surgery

Trial contacts and locations

1

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Central trial contact

Yonghe Chen, MD; Junsheng Peng, MD

Data sourced from clinicaltrials.gov

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