Clinical trial NCT04913896: CT and MRI in Prediction of Response in Patients With Gastric Cancer Following Neoadjuvant Chemotherapy and/or Immunotherapy
Official title: Clinical Study of CT and MRI in Prediction of Response in Patients With Gastric Cancer Following Neoadjuvant Chemotherapy and/or Immunotherapy
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Gastric Cancer
Magnetic Resonance Imaging
Tomography, X-Ray Computed
Neoadjuvant Immunotherapy
Neoadjuvant Chemotherapy
Lead sponsor: The First Hospital of Jilin University
Sponsor class: OTHER
First posted: 2021-06-04
Enrollment: 200
Sex: ALL
Minimum age (years): 18
Maximum age (years): 80
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients with endoscopically biopsy-proven gastric cancer will receive preoperative neoadjuvant immunotherapy and/or chemotherapy.

Brief 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.

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.

Eligibility criteria: 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 Ⅱ-Ⅲ 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.

Primary outcomes:
measure: Predictive value of CT and MRI after the neoadjuvant treatment for developing a pCR at surgery
timeFrame: up to 2 year
Secondary outcomes:
measure: Predictive value of CT and MRI after the neoadjuvant treatment for pathologic T staging
timeFrame: up to 2 year
measure: Predictive value of CT and MRI after the neoadjuvant treatment for pathologic response according to the Tumor Regression Grading (TRG)
timeFrame: up to 2 year
measure: Prediction model based on CT and MRI of response in AGC
timeFrame: up to 2 year
Other outcomes:
Locations:
Study officials:
affiliation: The First Hospital of Jilin University
name: quan wang, MD
role: PRINCIPAL_INVESTIGATOR
References: