Radiomics Based Multimodal Transvaginal Ultrasound Imaging in Endometrial Cancer

NCT05387460 | Unknown

• 1 other identifier: 2022-TJ-R-RBM
• Study Type: observational
• Target: 2,000
• Locations: 1 country
• Sites: 1

Brief Summary

Retrospectively collect preoperative transvaginal B-mode ultrasound (BMUS), color Doppler flow imaging (CDFI) and three-dimensional ultrasound (3D-US) images and clinical data in patients with non-endometrial cancer diseases and endometrial cancer confirmed by pathology. They were grouped as training set(Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology) and external validation set(Women's Hospital, School of Medicine, Zhejiang University) . Radiomics features were extracted from corresponding transvaginal ultrasound images. Then, the minimum redundancy maximum relevance (mRMR) algorithm and the least absolute shrinkage and selection operator (LASSO) regression were used to select the non- malignant or malignant status-related features and cervical stromal invasion (CSI) status or non-CSI status features and construct the transvaginal ultrasound radiomics score (Rad-score). Multivariate logistic regression was performed using the three radiomics score together with clinical data, and subsequently develop a nomogram to diagnosis endometrial cancer and CSI respectively. The performance of the nomogram was assessed by discrimination, calibration, and clinical usefulness in the training and external validation set.

Conditions

Endometrial Cancer; Cervical Stromal Invasion; Transvaginal Ultrasound

Outcome Measures

Primary Outcomes (1)

• AUC value

  Area under the receiver operating characteristic (ROC) curve (AUC）

  through study completion, an average of 1 year

Secondary Outcomes (2)

• Diagnostic specificity

  through study completion, an average of 1 year

• Diagnostic sensitivity

  through study completion, an average of 1 year

Study Arms (2)

Training cohort

The cohort of Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology is a training cohort Intervention/treatment

Diagnostic Test: radiomics

validation cohort

The cohort of Women's Hospital, School of Medicine, Zhejiang University is a validation cohort

Diagnostic Test: radiomics

Interventions

radiomics DIAGNOSTIC_TEST

Radiomics refers to high-throughput mining of quantitative image features from medical imaging. Radiomics derived data, when combined with other pertinent clinicopathological features, can produce accurate and robust evidence-based decision-making systems. Multimodal radiomics can provide more imaging feature information than single modal radiomics, which showed better diagnostic performance in previous study of kinds of cancer diseases.

Training cohort; validation cohort

Eligibility Criteria

• Age: 18 Years+
• Gender Eligibility Details: Endometrial cancer can only happen in females.
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients who had Endometrial cancer or benign endometrial diseases and completed the transvaginal ultrasound examination before operation

You may qualify if:

• Patients diagnosed by operation and pathology
• Patients with preoperative transvaginal ultrasound images

You may not qualify if:

• Past history of gynecological malignant tumors
• Previous pelvic surgery or radiotherapy or chemotherapy
• Poor image quality
• Incomplete pathological or diagnosis report

Sponsors & Collaborators

• Tongji Hospital: lead
• Women's Hospital School Of Medicine Zhejiang University: collaborator

Study Sites (1)

Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology

Wuhan, Hubei, 430030, China

Location

MeSH Terms

Conditions

Endometrial Neoplasms

Interventions

Radiomics

Condition Hierarchy (Ancestors)

Uterine Neoplasms; Genital Neoplasms, Female; Urogenital Neoplasms; Neoplasms by Site; Neoplasms; Uterine Diseases; Genital Diseases, Female; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Urogenital Diseases; Genital Diseases

Intervention Hierarchy (Ancestors)

Diagnostic Imaging; Diagnostic Techniques and Procedures; Diagnosis

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: May 18, 2022
• First Posted: May 24, 2022
• Study Start: October 1, 2021
• Primary Completion: December 1, 2022
• Study Completion: July 1, 2023
• Last Updated: May 24, 2022

Record last verified: 2022-05

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)