- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04913896
CT and MRI in Prediction of Response in Patients With Gastric Cancer Following Neoadjuvant Chemotherapy and/or Immunotherapy
May 30, 2021 updated by: The First Hospital of Jilin University
Clinical Study of CT and MRI in Prediction of Response in Patients With Gastric Cancer Following Neoadjuvant Chemotherapy and/or Immunotherapy
This is a prospective and observational clinical study for seeking out a better way to predict the pathologic complete response (pCR) in patients with advanced gastric cancer (AGC) based on the post-neoadjuvant treatment Magnetic Resonance Imaging (MRI) and CT data.
This study will help the surgeons to better formulate treatment regimens for gastric cancer in the clinical practice.
Study Overview
Status
Not yet recruiting
Conditions
Intervention / Treatment
Detailed Description
With the gradual development of neoadjuvant immunotherapy and/or chemotherapy in the clinic, the pCR has become more and more accessible in the AGC.
Preoperative accurate prediction of pCR is of great clinical significance.
The contrast-enhanced CT and 3.0T MRI were carried out in patients within 1 week prior to commencing neoadjuvant treatment, as well as 1 week within surgery after the completion of neoadjuvant treatment, respectively.
Based on the information extracted from the CT/MRI, the clinical completed response (cCR) and the clinical T staging were compared with pCR, pathologic T staging.
The pathologic results were considered as the golden standard.
With the ROC curve analysis, the diagnosis coincidence rate, sensitivity and specificity were assessed.
The AI prediction model would be constructed and trained.
The depth convolution neural network based on contrast-enhanced CT and multi-modal MR quantitative images which can automatically mine key images characterization, combined with imaging features and histopathologic response, could further help to improve the prediction of response of gastric cancer treated with systematic therapy.
The abdominal contrast-enhanced CT will focus on parameters: Local T Staging, nodal status, diameter, according to RECIST 1.1.
MRI T2 (1-3mm slice as per NS Radiology protocol and ESGAR guideline) will focus on parameters: DWI & ADC value (preferably on a single camera with reproducible ADC value), Local T Staging, MRF involvement, EMVI, nodal status, MR volumetry, and desmoplastic reaction.
Study Type
Observational
Enrollment (Anticipated)
200
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Contact
- Name: quan wang, MD
- Phone Number: 15843073207
- Email: wquan@jlu.edu.cn
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
18 years to 80 years (Adult, Older Adult)
Accepts Healthy Volunteers
No
Genders Eligible for Study
All
Sampling Method
Non-Probability Sample
Study Population
Patients with endoscopically biopsy-proven gastric cancer will receive preoperative neoadjuvant immunotherapy and/or chemotherapy.
Description
Inclusion Criteria:
- Age 18 Years to 80 Years
- Consecutive patients with preoperative pathologically confirmed AGC by endoscopy and preoperative imaging data (CT/MRI) were included.
- Clinical staging Ⅱ-Ⅲ according to the UICC/AJCC 8th guideline for gastric cancer without distant metastasis.
- Suitable for pre-operative chemotherapy, immunotherapy and surgical resection
- No contraindications for CT/MRI examination.
- Eastern Cooperative Oncology Group (ECOG) performance status 0-2.
- The patients participate in this study with informed consent.
Exclusion Criteria:
- Patients with a history of previous chemotherapy or immunotherapy.
- The patients couldn't perform MSCT or MR scanning or artefacts affect the evaluation.
- The patients are extremely anxious and uncooperative about surgery or neoadjuvant therapy.
- The patients refuse to participate in the project.
- Pregnancy, lactation or inadequate contraception
- Pacemaker or implanted defibrillator
- Patients with a history of psychological illness or condition such as to interfere with the patient's ability to understand requirements of the study.
- Other situations considered by investigators, which not meet the inclusion criteria.
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
---|---|
Single Group Assignment
Patients with AGC who underwent neoadjuvant immunotherapy and/or chemotherapy would recieve MRI and CT examination before and after 3 cycles treatment.
|
SOX regimen for 3 cycles and/or PD-1 inhibitor before surgery
Other Names:
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Predictive value of CT and MRI after the neoadjuvant treatment for developing a pCR at surgery
Time Frame: up to 2 year
|
Predictive value of CT and MRI after the neoadjuvant treatment for developing a pathologic complete response at surgery (Grade 0 - no viable cancer cells seen in the resection specimen).
|
up to 2 year
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Predictive value of CT and MRI after the neoadjuvant treatment for pathologic T staging
Time Frame: up to 2 year
|
To evaluate the T staging of gastric cancer treated with neoadjuvant treatment through CT and MRI.
|
up to 2 year
|
Predictive value of CT and MRI after the neoadjuvant treatment for pathologic response according to the Tumor Regression Grading (TRG)
Time Frame: up to 2 year
|
Pathological tumour regression grading (Mandard criterion): from 1 to 5 grading.
|
up to 2 year
|
Prediction model based on CT and MRI of response in AGC
Time Frame: up to 2 year
|
To construct a model, a depth convolution neural network based on contrast-enhanced CT and multi-modal MR quantitative images which can automatically mine key images characterization, combined with imaging features and histopathologic response, could further help to improve the prediction of response of gastric/rectal cancer treated with systematic therapy.
|
up to 2 year
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Investigators
- Principal Investigator: quan wang, MD, The First Hospital of Jilin University
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Anticipated)
June 1, 2021
Primary Completion (Anticipated)
October 1, 2022
Study Completion (Anticipated)
June 1, 2023
Study Registration Dates
First Submitted
May 10, 2021
First Submitted That Met QC Criteria
May 30, 2021
First Posted (Actual)
June 4, 2021
Study Record Updates
Last Update Posted (Actual)
June 4, 2021
Last Update Submitted That Met QC Criteria
May 30, 2021
Last Verified
April 1, 2021
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- STARS-GC03
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
NO
IPD Plan Description
no share
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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