Clinical trial · Observational
Study of CT and MR in the Gastric Cancer
Clinical Study of CT and MR in Staging and Prediction of Response in Patients With Gastric Cancer
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
It is very significant that assessing staging in gastric cancer patients before surgery, furthermore, determining the optimize surgical strategy ,predict the the efficacy of neoadjuvant therapy for patients. For patients who are ineffective in neoadjuvant therapy, surgery will be more meaningful. It has been reported that the application of CT(computed tomography,CT) and MR(magnetic resonance,MR) in staging of gastric cancer, but not in predicting clinical response to neoadjuvant therapy for gastric cancer. Only a few studies focused on T staging using conventional MRI in gastric cancer, however , relatively new sequences in the chest deserve widely used. To develop a pre-treatment evaluation methods for TN staging in patient with gastric cancer by utilization of the new imaging methods (T2-TSE-BLADE,T2 maps, StarVIBE, iShim-DWI and high resolution CT). By analysing the relationship between TN staging and imaging features to find the imaging characteristics for TN staging, and to find the indicators of new technology and reference values for facilitate pre-treatment diagnosis of TN staging, optimize surgical strategy , predict the the efficacy of adjunctive therapy , and OS and define the range of lymph node for radiotherapy , as making personal treatment planning for gastric cancer .
Conditions
Conditions (4)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| CT | — | UNRESOLVED | — |
| Gastric Cancer Stage | Gastric Neoplasm | PROBABILISTIC | 0.70 |
| MRI | — | UNRESOLVED | — |
| Neoadjuvant Therapy | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| No intervention | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (1)
- measure
- MSCT and MRI staging in Gastric Cancer.
- timeFrame
- up to 2 year
- description
- To evaluate the staging of gastric cancer treated with systematic therapy through MSCT and 3 T MRI which using multiple sequences.
Secondary outcomes (1)
- measure
- MSCT and MRI prediction of prognosis in gastric cancer
- timeFrame
- up to 2 year
- description
- To construct a model,a depth convolution neural network based on MSCTand multi-modal MR quantitative images which can automatically mine key images characterization, combined with imaging features and prognosis,could further help to improve the prediction of response and OS of gastric cancer treated with systematic therapy.
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
- Maximum age
- 80 Years
Show eligibility criteria text
Inclusion Criteria: 1. Consecutive patients with preoperative pathologically con-firmed gastric cancer by endoscopy and preoperative imaging data (esophagography\\CT\\EUS\\MRI) were included. 2. No contraindications for MRI examination. No contraindications contrast. 3. The patients participate in this study with informed consent. Exclusion Criteria: 1. The patients couldn't performed MSCT or MR scanning or artefacts affect the evaluation. 2. The patients are extremely anxious and uncooperative about surgery or neoadjuvant therapy . 3. PatientsThe patients refuse to participate in the project. 4. Other situations considered by investigators not meet the inclusion criteria.
References
Publications (8)
- BACKGROUNDGiganti F, Tang L, Baba H. Gastric cancer and imaging biomarkers: Part 1 - a critical review of DW-MRI and CE-MDCT findings. Eur Radiol. 2019 Apr;29(4):1743-1753. doi: 10.1007/s00330-018-5732-4. Epub 2018 Oct 2. PMID 30280246
- BACKGROUNDPang L, Wang J, Fan Y, Xu R, Bai Y, Bai L. Correlations of TNM staging and lymph node metastasis of gastric cancer with MRI features and VEGF expression. Cancer Biomark. 2018;23(1):53-59. doi: 10.3233/CBM-181287. PMID 30010108
- BACKGROUNDBorggreve AS, Goense L, Brenkman HJF, Mook S, Meijer GJ, Wessels FJ, Verheij M, Jansen EPM, van Hillegersberg R, van Rossum PSN, Ruurda JP. Imaging strategies in the management of gastric cancer: current role and future potential of MRI. Br J Radiol. 2019 May;92(1097):20181044. doi: 10.1259/bjr.20181044. Epub 2019 Mar 5. PMID 30789792
- BACKGROUNDZhou J, Shen J, Seifer BJ, Jiang S, Wang J, Xiong H, Xie L, Wang L, Sui X. Approaches and genetic determinants in predicting response to neoadjuvant chemotherapy in locally advanced gastric cancer. Oncotarget. 2017 May 2;8(18):30477-30494. doi: 10.18632/oncotarget.12955. PMID 27802185
- BACKGROUNDKwee RM, Kwee TC. Role of imaging in predicting response to neoadjuvant chemotherapy in gastric cancer. World J Gastroenterol. 2014 Feb 21;20(7):1650-6. doi: 10.3748/wjg.v20.i7.1650. PMID 24587644
- BACKGROUNDNg J, Lee P. The Role of Radiotherapy in Localized Esophageal and Gastric Cancer. Hematol Oncol Clin North Am. 2017 Jun;31(3):453-468. doi: 10.1016/j.hoc.2017.01.005. Epub 2017 Mar 22. PMID 28501087
- BACKGROUNDAl-Batran SE, Homann N, Pauligk C, Illerhaus G, Martens UM, Stoehlmacher J, Schmalenberg H, Luley KB, Prasnikar N, Egger M, Probst S, Messmann H, Moehler M, Fischbach W, Hartmann JT, Mayer F, Hoffkes HG, Koenigsmann M, Arnold D, Kraus TW, Grimm K, Berkhoff S, Post S, Jager E, Bechstein W, Ronellenfitsch U, Monig S, Hofheinz RD. Effect of Neoadjuvant Chemotherapy Followed by Surgical Resection on Survival in Patients With Limited Metastatic Gastric or Gastroesophageal Junction Cancer: The AIO-FLOT3 Trial. JAMA Oncol. 2017 Sep 1;3(9):1237-1244. doi: 10.1001/jamaoncol.2017.0515.