Clinical trial · Observational
MRI Radiomics Combined With Pathomics on the Prediction of Molecular Classification and Prognosis of Endometrial Cancer
Study on the Prediction of Molecular Classification and Prognosis of Endometrial Cancer Using a Model Constructed by Magnetic Resonance Imaging Radiomics Combined With Pathomics
- 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)
Molecular typing provides accurate information for the diagnosis, treatment and prognosis prediction of endometrial cancer, which has important clinical significance. However, due to its high cost and complicated process, it is difficult to be widely used in clinical practice. Based on the artificial intelligence method, this study fused the characteristics of MRI radiomics and pathomics, combined with the clinical pathological information, built a model to predict the molecular typing and prognosis, analyzed the biological characteristics of endometrial cancer from the multi-scale level, guided the personalized and precise diagnosis and treatment, in order to improve the prognosis of patients.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Endometrial Neoplasms | Endometrial Neoplasm | ONTOLOGY_EXACT | 0.98 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| next generation sequencing AND Immunohistochemical examination | Diagnostic Test | — | UNRESOLVED |
Design
Arms and outcomes
Arms (4)
- label
- POLE Mut
- description
- The POLE gene mutation detection was performed, and the mutation Changes were classified as POLE mutation.
- interventionNames
- Diagnostic Test: next generation sequencing AND Immunohistochemical examination
- label
- dMMR
- description
- The mismatch repair (MMR) proteins were detected by immunohistochemistry, and the deletion of one or more proteins was classified as d-MMR subtype
- interventionNames
- Diagnostic Test: next generation sequencing AND Immunohistochemical examination
- label
- P53abn
- description
- The expression of p53 was detected by immunohistochemistry. The abnormality of p53 protein expression (completely negative or diffusely strong positive in the nucleus) or expression location (cytoplasmic expression) was judged as p53abn, otherwise it was p53wt.
- interventionNames
Eligibility
Eligibility (as posted)
- Sex
- Female
- Minimum age
- 18 Years
- Maximum age
- 80 Years
Show eligibility criteria text
Inclusion Criteria: * •Pathologically confirmed as endometrial malignant tumor with complete pathological H＆E stained sections; * Age ≥ 18 years and ≤ 80 years; * No other malignant cancers was found; * The complete immunohistochemical and second-generation sequencing results can be used for the molecular typing of ProMisE; * Magnetic resonance examination was performed within 2 weeks before treatment, and there was at least one measurable lesion according to RECIST 1.1 Criteria. Exclusion Criteria: * • The image quality is poor or the tumor is too small due to serious graphic artifact and degeneration, and the ROI cannot be accurately delineated; * Patients who received any antitumor therapy before surgery; * Diagnostic endometrial biopsy before MRI
References
Publications (6)
- RESULTSong XL, Luo HJ, Ren JL, Yin P, Liu Y, Niu J, Hong N. Multisequence magnetic resonance imaging-based radiomics models for the prediction of microsatellite instability in endometrial cancer. Radiol Med. 2023 Feb;128(2):242-251. doi: 10.1007/s11547-023-01590-0. Epub 2023 Jan 19. PMID 36656410
- RESULTJamieson A, McAlpine JN. Molecular Profiling of Endometrial Cancer From TCGA to Clinical Practice. J Natl Compr Canc Netw. 2023 Feb;21(2):210-216. doi: 10.6004/jnccn.2022.7096. PMID 36791751
- RESULTTalhouk A, McConechy MK, Leung S, Li-Chang HH, Kwon JS, Melnyk N, Yang W, Senz J, Boyd N, Karnezis AN, Huntsman DG, Gilks CB, McAlpine JN. A clinically applicable molecular-based classification for endometrial cancers. Br J Cancer. 2015 Jul 14;113(2):299-310. doi: 10.1038/bjc.2015.190. Epub 2015 Jun 30. PMID 26172027
- RESULTHou L, Zhou W, Ren J, Du X, Xin L, Zhao X, Cui Y, Zhang R. Radiomics Analysis of Multiparametric MRI for the Preoperative Prediction of Lymph Node Metastasis in Cervical Cancer. Front Oncol. 2020 Aug 20;10:1393. doi: 10.3389/fonc.2020.01393. eCollection 2020. PMID 32974143
- RESULTLefebvre TL, Ueno Y, Dohan A, Chatterjee A, Vallieres M, Winter-Reinhold E, Saif S, Levesque IR, Zeng XZ, Forghani R, Seuntjens J, Soyer P, Savadjiev P, Reinhold C. Development and Validation of Multiparametric MRI-based Radiomics Models for Preoperative Risk Stratification of Endometrial Cancer. Radiology. 2022 Nov;305(2):375-386. doi: 10.1148/radiol.212873. Epub 2022 Jul 12. PMID 35819326
- RESULTCrosbie EJ, Kitson SJ, McAlpine JN, Mukhopadhyay A, Powell ME, Singh N. Endometrial cancer. Lancet. 2022 Apr 9;399(10333):1412-1428. doi: 10.1016/S0140-6736(22)00323-3. PMID 35397864