CT and MRI in Prediction of Response in Patients With Gastric Cancer Following Neoadjuvant Chemotherapy and/or Immunotherapy

Gastric Cancer Clinical Trial

Official title:

Clinical Study of CT and MRI in Prediction of Response in Patients With Gastric Cancer Following Neoadjuvant Chemotherapy and/or Immunotherapy

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT04913896
• Other study ID #: STARS-GC03
• Status: Not yet recruiting
• Start date: June 1, 2021
• Est. completion date: June 1, 2023

Study information

• Verified date: April 2021
• Source: The First Hospital of Jilin University
• Contact: quan wang, MD
• Phone: 15843073207
• Email: wquan[@]jlu.edu.cn
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial Summary

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.

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.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 200
• Est. completion date: June 1, 2023
• Est. primary completion date: October 1, 2022
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 80 Years

Eligibility

Inclusion Criteria:

1. Age 18 Years to 80 Years

2. Consecutive patients with preoperative pathologically confirmed AGC by endoscopy and preoperative imaging data (CT/MRI) were included.

3. Clinical staging ?-? according to the UICC/AJCC 8th guideline for gastric cancer without distant metastasis.

4. Suitable for pre-operative chemotherapy, immunotherapy and surgical resection

5. No contraindications for CT/MRI examination.

6. Eastern Cooperative Oncology Group (ECOG) performance status 0-2.

7. The patients participate in this study with informed consent.

Exclusion Criteria:

1. Patients with a history of previous chemotherapy or immunotherapy.

2. The patients couldn't perform MSCT or MR scanning or artefacts affect the evaluation.

3. The patients are extremely anxious and uncooperative about surgery or neoadjuvant therapy.

4. The patients refuse to participate in the project.

5. Pregnancy, lactation or inadequate contraception

6. Pacemaker or implanted defibrillator

7. Patients with a history of psychological illness or condition such as to interfere with the patient's ability to understand requirements of the study.

8. Other situations considered by investigators, which not meet the inclusion criteria.

Related Conditions & MeSH terms

• Gastric Cancer
• Magnetic Resonance Imaging
• Neoadjuvant Chemotherapy
• Neoadjuvant Immunotherapy
• Stomach Neoplasms
• Tomography, X-Ray Computed

Intervention

Drug:
• PD-1 inhibitor
SOX regimen for 3 cycles and/or PD-1 inhibitor before surgery

Locations

Country	Name	City	State
n/a

Sponsors (1)

Lead Sponsor	Collaborator
The First Hospital of Jilin University

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Predictive value of CT and MRI after the neoadjuvant treatment for developing a pCR at surgery	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	Predictive value of CT and MRI after the neoadjuvant treatment for pathologic T staging	To evaluate the T staging of gastric cancer treated with neoadjuvant treatment through CT and MRI.	up to 2 year
Secondary	Predictive value of CT and MRI after the neoadjuvant treatment for pathologic response according to the Tumor Regression Grading (TRG)	Pathological tumour regression grading (Mandard criterion): from 1 to 5 grading.	up to 2 year
Secondary	Prediction model based on CT and MRI of response in AGC	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