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AzTrials

Endometrial NeoplasmsNCT06126393

MRI Radiomics Combined With Pathomics on the Prediction of Molecular Classification and Prognosis of Endometrial Cancer

An observational study of Endometrial Neoplasms, run by Fujian Cancer Hospital at 1 site in China.

Not yet recruiting

Opening soon. The study is approved but enrolment has not started yet. Sites may already take enquiries.

Sites and contacts
Official record
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Trial summary

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. Read more about this study

Who is it for?
Ages 18 to 80 years, women only
Conditions the study is for
Endometrial Neoplasms
What is being tested?
next generation sequencing AND Immunohistochemical examination
How many people
350 participants
Where
1 siteChina
Study dates
1 Jan 2024to 30 Jun 2027
Phase
Observational
Are there results?
Not yet: the study is under way

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 18 to 80 years
  • Women only
  • Adult, Older adult

Study population: 1. All patients were pathologically confirmed as endometrial malignant tumors, and molecular typing was performed. 2. Patients with endometrial cancer who were admitted to Fujian cancer hospital from January 2020 to December 2023 were retrospectively collected. Meanwhile, from January 1, 2024, all consecutive patients with newly diagnosed endometrial cancer were enrolled and signed the informed consent.

Who may be able to join

  • •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.

Who cannot join

  • • 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

Trial locations and contacts

1 site in 1 country. Contact the study team or a site near you to ask about taking part.

Jian Chen, Master contact

15806030009

marsz3@126.com

China1 site

  • Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital

    Fuzhou, Fujian, 350014

    Jian Chen, Master, 15806030009, marsz3@126.com

Other trials in China

About this study

Official title: Study on the Prediction of Molecular Classification and Prognosis of Endometrial Cancer Using a Model Constructed by Magnetic Resonance Imaging Radiomics Combined With Pathomics

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.

Read the detailed description

In this project, 150 cases of endometrial cancer were retrospectively collected, and 200 cases of endometrial cancer will be prospectively collected. All patients were pathologically confirmed and underwent Promise molecular typing. Before treatment, all patients completed abdominal MRI. Based on artificial intelligence technology, image features were extracted from magnetic resonance imaging, pathological features were extracted from pathological data, and clinical pathological data were collected at the same time. The treatment effect, recurrence and metastasis of patients were followed up, and the five-year survival rate and five-year progression free survival rate were calculated. It is proposed to focus on the following research:

  1. Construction of molecular typing and prognosis prediction model of endometrial cancer based on magnetic resonance imaging Radiomics
  2. Construction of molecular typing and prognosis prediction model of endometrial cancer based on pathomics.
  3. Construction of a prediction model for molecular typing of endometrial cancer by integrating pathomics and radiomics.
Being tested
next generation sequencing AND Immunohistochemical examination
Keywords
Endometrial Neoplasms, machine learning, Radiomics, Pathomics, TCGA classification
Medical subject headings
Endometrial Neoplasms

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

  • next generation sequencing AND Immunohistochemical examinationDiagnostic test

    Also called Magnetic resonance examination

    First, the mismatch repair (MMR) proteins were detected by immunohistochemistry, and the deletion of one or more proteins was classified as d-MMR subtype; Then the POLE gene mutation detection was performed, and the mutation Changes were classified as POLE mutation; Finally, p53 was detected by immunohistochemistry, and p53 mutant (p53 abn) and p53 wild-type (p53wt) were distinguished.

Study groups in NCT06126393
Study groupRoleWhat they receive
POLE MutThe POLE gene mutation detection was performed, and the mutation Changes were classified as POLE mutation.
Receives: Diagnostic Test: next generation sequencing AND Immunohistochemical examination
dMMRThe mismatch repair (MMR) proteins were detected by immunohistochemistry, and the deletion of one or more proteins was classified as d-MMR subtype
Receives: Diagnostic Test: next generation sequencing AND Immunohistochemical examination
P53abnThe 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.
Receives: Diagnostic Test: next generation sequencing AND Immunohistochemical examination
P53wtThe 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.
Receives: Diagnostic Test: next generation sequencing AND Immunohistochemical examination

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Application of magnetic resonance imaging radiomics and pathomics to construct a model for predicting the molecular classification and prognosis of endometrial cancer

    The imaging and pathological features of endometrial cancer patients were extracted by artificial intelligence method. Combined with clinicopathological risk factors and survival time, an imaging nomogram was constructed by lasso regression method to predict the molecular classification and prognosis of endometrial cancer. ROC curve was used to evaluate the test efficiency of the model.

    Measured: 2026-12-21

Secondary outcomes (1)

  1. Application of magnetic resonance imaging radiomics to construct a model for predicting the molecular classification and prognosis of endometrial cancer

    The imaging features of endometrial cancer patients were extracted by artificial intelligence method. Combined with clinicopathological risk factors and survival time, an imaging nomogram was constructed by lasso regression method to predict the molecular classification and prognosis of endometrial cancer. ROC curve was used to evaluate the test efficiency of the model.

    Measured: 2026-12-21

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted13 Nov 2023
  2. Study start1 Jan 2024 (estimated)
  3. Primary completion31 Mar 2027 (estimated)
  4. Study completion30 Jun 2027 (estimated)

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Observational
Observational model
Cohort
Time perspective
Other
Enrolment
350 participants (estimated)
IDs, dates and publications
ClinicalTrials.gov ID
NCT06126393
Sponsor's protocol ID
CHENJIAN1
Status last verified
Nov 2023
First submitted
6 Nov 2023
Last updated
15 Nov 2023
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
No: All relevant patient personal information and follow-up results of this study were saved by the principal investigator, and there was no plan to share them with other investigators

Publications

  • Song 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.

    PubMed 36656410

  • Jamieson 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.

    PubMed 36791751

  • Talhouk 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.

    PubMed 26172027

  • Hou 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.

    PubMed 32974143

  • Lefebvre 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.

    PubMed 35819326

  • Crosbie 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.

    PubMed 35397864

Questions about this trial

What is this clinical trial studying?

An observational study of Endometrial Neoplasms, run by Fujian Cancer Hospital at 1 site in China.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 5 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: opening soon, as of the sponsor's last update on 15 Nov 2023. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

This study is still under way. Results are not available in the source record yet.

How can a doctor refer a patient or contact the research team?

Contact Jian Chen, Master (15806030009, marsz3@126.com), or a site near the patient. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Application of magnetic resonance imaging radiomics and pathomics to construct a model for predicting the molecular classification and prognosis of endometrial cancer (time frame: 2026-12-21). It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT06126393, which also lists 6 linked publications.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 15 Nov 2023.

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