MRI and Metabolomics Biomarkers for Uterine Malignancy

NCT ID: NCT02528864

Last Updated: 2019-07-30

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 150 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2015-08-01
• Study Completion Date: 2018-07-31

Brief Summary

The aims of this project are: (1) To establish a research platform in order to integrate multiparametric imaging and metabolomics data for uterine malignancy. (2) Identify potential surrogate biomarkers for early diagnosis of endometrial cancer by using multiparametric magnetic resonance imaging and metabolomics approach. (3) To develop surrogate biomarkers for uterine malignancy, in detecting tumor involvement of myometrium, cervix, and lymph nodes. The investigators propose a 3-year research project to prospectively collect data from 150 female patients 20-80 years old, with clinically diagnosed or suspected to have uterine malignancy. An additional control group comprising 30 patients with normal endometrial tissue will be enrolled. Robust magnetic resonance (MR) imaging techniques including MR spectroscopy (MRS), diffusion-weighted imaging and chemical exchange saturation transfer (CEST) imaging will be applied. Biological samples (tissue, blood, urine) will be analyzed by detailed metabolomics approach (high-resolution MRS).

Detailed Description

In the 1st year part of this project, the investigators aim to identify the differences between normal endometrium and cancer tissue. Standard conventional MR study plus MRS, diffusion-weighted imaging and CEST sequences will be carried out on 30 eligible surgical candidates for pretreatment clinical assessment.Metabolites in cancer tissue will be collected during operation and analyzed using high resolution MRS, and compared with control group. The primary endpoint of this part is to identify different imaging and metabolomic profiles between normal and cancer subjects. In the 2nd year, the investigators will continue accumulate case number, in order to evaluate the diagnostic accuracy of advanced MR imaging and metabolomics biomarker, in prediction of T staging and myometrial involvement. By the end of 3rd year, the investigators will collect 150 patients, with approximately 20 cases with cervical invasion and 20 cases with nodal metastasis, in order to answer how this approach predicts cervical stromal involvement, nodal and distant metastasis.

The clinical importance of this project is answer the most relevant questions, i.e., prediction of tumor involvement of myometrium, cervix, and lymph nodes. This will be important for understanding the background mechanism of changes identified by MR and 18-F-2-fluoro-2-deoxy-D-glucose fluorodeoxyglucose (FDG) /PET, in order to develop novel imaging biomarkers or therapeutic targets. Both molecular imaging and metabolomics are complimentary and share similarities: (1) Comprehensive data representing the information of the living system as a whole (2) information rich data which reflecting the complexity of the biological system (3) ease for longitudinal observation. Metabolomics data provides more details on biochemistry whilst imaging data provides more spatial localization details. A combination of imaging and metabolomics approach would be an ideal tool to develop biomarkers for uterine malignancy. By completion of this project, the investigators expect the most important metabolic biomarkers will be established, and potentially serve as functional tools to guide therapy for patient with uterine malignancy.

Conditions

Uterine Neoplasms

Study Design

• Observational Model Type: CASE_CONTROL
• Study Time Perspective: PROSPECTIVE

Study Groups

Normal endometrium

Control group (n=30) comprising surgical candidates with normal endometrial tissue will be collected for comparison.

No interventions assigned to this group

Endometrial/uterine cancer

1. 1st year: 50 eligible patients surgical candidates of endometrial cancer with pre-operative imaging and biological samples collected during operation.

2. 2nd year: Enroll another 50 surgical candidates and complete the data regarding clinical MRS/diffusion-weighted imaging and tissue high resolution MRS. Together with the 50 cancer subjects in the first year there will be in total 100 cancer subjects for analysis.

3. 3rd year: Collect enough positive events with any myometrial involvement (n=30), cervical stromal invasion (n=10) and nodal metastasis (n=10). Together with the 100 cancer subjects in the first and second years there will be in total 150 cancer subjects for analysis.

No interventions assigned to this group

Eligibility Criteria

Inclusion Criteria

• Female 20 ~ 80 years old.
• Clinically diagnosed or suspected to have uterine malignancy.
• Able to understand and provide signed informed consent.
• Willing to receive standard surgical treatment.

Exclusion Criteria

• Contraindicated to magnetic resonance study: cardiac pacemaker or cochlear implantation.
• Status post major pelvic surgery, total hip replacement or magnetic substance implantation in the pelvis.
• Significant major systemic disease, such as renal failure, heart failure, stroke, acute myocardial infarction/unstable angina, poor controlled diabetes mellitus, poor controlled hypertension.
• Pregnant or breast-feeding women.
• Moderate to severe dementia.

• Minimum Eligible Age: 20 Years
• Maximum Eligible Age: 80 Years
• Eligible Sex: FEMALE
• Accepts Healthy Volunteers: Yes

Sponsors

Chang Gung Memorial Hospital

OTHER

Sponsor Role: lead

Responsible Party

Gigin Lin

Department of Radiology

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Gigin Lin, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital

Locations

Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital

Guishan, Taoyuan, Taiwan

Countries

Taiwan

References

Lin Y, Wu RC, Lin YC, Huang YL, Lin CY, Lo CJ, Lu HY, Lu KY, Tsai SY, Hsieh CY, Yang LY, Cheng ML, Chao A, Lai CH, Lin G. Endometrial cancer risk stratification using MRI radiomics: corroborating with choline metabolism. Cancer Imaging. 2024 Aug 24;24(1):112. doi: 10.1186/s40644-024-00756-x.

Reference Type: DERIVED

PMID: 39182135 (View on PubMed)

Other Identifiers

103-7316A3

Identifier Type: -

Identifier Source: org_study_id