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Uterine FibroidNCT07129005

Radiomics-Based Non-Invasive MRI Differentiation of Uterine Sarcomas and Fibroids

An observational study of Uterine Fibroid and Uterine Sarcoma, run by Tongji Hospital at 1 site in China.

Enrolling by invitation

Enrolling by invitation. The study team selects and invites participants, usually from an existing group of patients.

Sites and contacts
Official record

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Trial summary

This retrospective case-control study aims to develop and validate a diagnostic model based on multimodal big data and artificial intelligence to differentiate uterine leiomyoma from uterine sarcoma. Read more about this study

Who is it for?
Ages 18 years and older, women only
Conditions the study is for
Uterine Fibroid, Uterine Sarcoma, Diagnose Disease
How many people
520 participants
Where
1 siteChina
Study dates
1 Jan 2025to 30 Dec 2029
Phase
Observational

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 years and older
  • Women only
  • No healthy volunteers
  • Adult, Older adult

Study population: The study population will be enrolled in a multicenter study led by Tongji Hospital in collaboration with several tertiary hospitals. Patients with a pathological diagnosis of uterine leiomyoma or uterine sarcoma will be recruited for this trial.

Who may be able to join

  • Histopathological confirmation of uterine sarcoma or leiomyoma.
  • Availability of preoperative MRI, includingT2WI and DWI, performed within 2 months of the surgery.

Who cannot join

  • Tumors smaller than 2 cm. Small tumors may be difficult to accurately perform segmentation and feature extraction, which may affect the accuracy and reliability of the model.
  • Non-primary uterine sarcomas. Sarcomas from other sites with metastasis to the uterus were excluded because the biological characteristics and imaging findings of these tumors may differ from those of primary uterine sarcomas and may lead to bias in the diagnostic model.
  • Concurrent pelvic malignancies. To avoid the influence of other types of tumors on the imaging features of uterine sarcoma and leiomyoma, and to ensure the pertinence and accuracy of the model.

Trial locations and contacts

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

China1 site
  • Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology

    Wuhan, Hubei, 430000

Other trials in China

About this study

Official title: Non-invasive Differentiation of Uterine Sarcomas From Uterine Fibroids Using Multiparametric MRI Radiomics

This retrospective case-control study aims to develop and validate a diagnostic model based on multimodal big data and artificial intelligence to differentiate uterine leiomyoma from uterine sarcoma. Investigators will extract historical case data from existing inpatient and outpatient records, including medical history, physical and gynecological examination findings, MRI imaging data, laboratory results, and pathological records. The study seeks to address the question of whether integrating diverse retrospective clinical data with advanced AI techniques can accurately classify uterine tumors as benign leiomyomas or malignant sarcomas, thereby supporting clinical decision-making and optimizing diagnostic workflows.

Read the detailed description

Uterine fibroids are the most common benign gynecological tumors among women of reproductive age in China, with an incidence that has been increasing annually. Statistics show that the prevalence of uterine fibroids among women over 30 years old in China has reached 20%-30%, and the onset age is trending younger. During the "12th Five-Year Plan" period, significant progress was made in the minimally invasive and pharmacological treatment of uterine fibroids through enhanced allocation of medical resources, advancement of clinical research, and improvement of diagnostic and treatment guidelines. However, with the rapid economic and social development in China, changes in environmental factors, lifestyle shifts, and delayed childbearing associated with improved living standards have contributed to a continued rise in the incidence of uterine fibroids. Uterine fibroids have now become a major public health issue affecting women's health in China.

Elucidating the mechanisms underlying the onset, recurrence, and malignant transformation of uterine fibroids, developing individualized treatment plans based on fertility preservation, and identifying high-risk populations to reduce disease progression and recurrence have become critical challenges in the field of reproductive health and women's and children's health research in China. Solving these issues is not only essential for improving women's health and well-being but also for enhancing population quality and reducing the healthcare burden.

In collaboration with the National Clinical Research Center for Obstetrics and Gynecology and regional medical centers (under construction), participating institutions will collect clinical, imaging, pathological, laboratory, and molecular testing data to establish a multicenter, systematic database. Machine learning algorithms will be used to develop early-warning models for malignant transformation and prognostic risk prediction models. Internal validation and optimization will be performed using different grouped datasets from this database, while large-scale data accumulated in Project 1 will be used for both internal and external validation, ultimately resulting in the construction of accurate and efficient early-warning and risk prediction models.

This multicenter retrospective observational study is led by Tongji Hospital in collaboration with several tertiary hospitals, including Zhongnan Hospital of Wuhan University, The Second Hospital of Shandong University, Shenzhen Second People's Hospital, West China Second University Hospital of Sichuan University, and The Third Affiliated Hospital of Zhengzhou University. The study protocol, including the use of existing inpatient and outpatient medical records, has been reviewed and approved by the Ethics Committee of Tongji Hospital (serving as the central IRB). Participating centers have either obtained approval from their local institutional review boards (IRBs) or formally accepted the central IRB approval. All procedures strictly adhere to the Declaration of Helsinki and relevant national ethical guidelines to ensure the protection of patient privacy and data confidentiality.

Being tested
No intervention (observational study)
Keywords
Uterine sarcoma, Radiomics, Multicenter study, Uterine leiomyoma, Magnetic resonance imaging (MRI), Machine learning
Medical subject headings
Leiomyoma, Myofibroma

What participants receive

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

  • No intervention (observational study)Other

    No intervention (observational study)

Study groups in NCT07129005
Study groupRoleWhat they receive
Patients with a pathological diagnosis of uterine fibroidsNot described
Receives: Other: No intervention (observational study)
Patients with a pathological diagnosis of uterine sarcomaNot described
Receives: Other: No intervention (observational study)

What is being measured

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

  1. AUC

    AUC stands for Area Under the Curve, specifically under the ROC (Receiver Operating Characteristic) curve

    Measured: through study completion, about July.2025

  2. Sensitivity

    Ability of the test to correctly identify those with uterine sarcoma (true positive rate)

    Measured: through study completion, about July.2025

  3. Specificity

    Ability of the test to correctly identify those without uterine sarcoma (true negative rate)

    Measured: through study completion, about July.2025

  4. Positive Predictive Value (PPV)

    Probability that subjects with a positive test truly have uterine sarcoma

    Measured: through study completion, about July.2025

  5. Negative Predictive Value (NPV)

    Probability that subjects with a negative test truly don't have the uterine fibroids

    Measured: through study completion, about July.2025

Secondary outcomes (3)
  1. Intraclass Correlation Coefficient

    Measured: Immediately after VOI delineation on baseline MRI

  2. SHapley Additive exPlanations

    Measured: through study completion, about July.2025

  3. Comparative Performance of the Intratumoral, Peritumoral, and Combined Models

    Measured: At model performance evaluation (following baseline imaging analysis),about August,2025

Timeline

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

  1. First posted19 Aug 2025
  2. Study start1 Jan 2025
  3. Primary completion30 Jul 2025
  4. Study completion30 Dec 2029 (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
Case-control
Time perspective
Retrospective
Enrolment
520 participants (estimated)
IDs, dates and publications
ClinicalTrials.gov ID
NCT07129005
Sponsor's protocol ID
TJ-IRB20221167
Status last verified
Oct 2026
First submitted
3 Aug 2025
Last updated
8 Oct 2026
Results posted
No
Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
No

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