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Using Radiomics to Predict Neoadjuvant Chemotherapy Efficacy

NCT05465512 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 193

Last updated 2022-07-19

No results posted yet for this study

Summary

Neoadjuvant chemotherapy (NC) is an important treatment for advanced gastric cancer (AGC). However, tools that effectively predict the efficacy of NC before treatment are lacking. Computed tomography images before and after NC were used to construct a deep learning-based radiomics signature to predict the efficacy of NC, prognoses and postoperative adjuvant chemotherapy benefit.

Conditions

Interventions

OTHER

response to neoadjuvant chemotherapy

Tumor regression grade (TRG) =0 or 1 was defined as a good response to neoadjuvant chemotherapy (GRNC), and TRG=2 or 3 was defined as a poor response to neoadjuvant chemotherapy (PRNC).

Sponsors & Collaborators

  • Fujian Medical University

    lead OTHER

Principal Investigators

Eligibility

Min Age
18 Years
Max Age
85 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-01-04
Primary Completion
2022-06-01
Completion
2022-07-10

Countries

  • China

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05465512 on ClinicalTrials.gov