Radiomics Based Multimodal Transvaginal Ultrasound Imaging in Endometrial Cancer

Radiomics Based on Multimodal Transvaginal Ultrasound Imaging in Predicting Endometrial Cancer and Cervical Stromal Invasion

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.

Study Overview

• Status: Active, not recruiting
• Conditions: Endometrial Cancer; Transvaginal Ultrasound; Cervical Stromal Invasion
• Intervention / Treatment: Diagnostic test: radiomics

Detailed Description

Endometrial Cancer is the second most common gynecological cancer in China and the first in Western countries. The common clinical symptom of endometrial cancer is vaginal bleeding, which occurs in about 10% of postmenopausal women. Most patients with postmenopausal vaginal bleeding are diagnosed with benign diseases, and less than 10% of patients are diagnosed with endometrial cancer. Early diagnosis is crucial for the prognosis of patients with endometrial cancer. The 5-year survival rate of patients with endometrial cancer which lesions localized to the uterus is about 95%, while the survival rate of patients with regional and distant metastasis is reduced to less than 70% and 20%.

Surgery is the main treatment of endometrial cancer. CSI is one of the main criteria for determining the follow-up treatment. According to NCCN guidelines, Total Hysterectomy and Bilateral Salpingo-Oophorectomy (THBSO) are standard treatments for patients with endometrioid carcinoma without CSI. While extensive hysterectomy or surgery after radiotherapy is appropriate for patients with CSI. Therefore, accurate assessment of CSI status in patients with EC before operation is important for the formulation of accurate surgical strategies.

Endometrial biopsy has been considered the gold standard for assessing endometrial cancer. However, it is limited because of increased cost, sample errors, related complications such as pain, bleeding, inability to evaluate the extent of tumor invasion and easy to cause tumor spread. CT/MR are alternative ways with high cost and complications. Transvaginal ultrasound examination is considered as the first imaging investigation for endometrial cancer. ESGO/ESTRO/ESP guidelines for the management of patients with endometrial carcinoma indicate that transvaginal ultrasound can be used instead of magnetic resonance imaging to detect cervical stromal infiltration under the operation of experienced doctors. Improving the performance of ultrasonic diagnosis is significant for how to choose the follow-up treatment and reduce the cost and risk of overtreatment.

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.

• Study Type: Observational
• Enrollment (Actual): 2000

Contacts and Locations

Study Locations

• China
  • Hubei
    • Wuhan, Hubei, China, 430030
      • Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: Female

• Sampling Method: Non-Probability Sample

Study Population

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

Description

Inclusion Criteria:

1. Patients diagnosed by operation and pathology
2. Patients with preoperative transvaginal ultrasound images

Exclusion Criteria:

1. Past history of gynecological malignant tumors
2. Previous pelvic surgery or radiotherapy or chemotherapy
3. Poor image quality
4. Incomplete pathological or diagnosis report

Study Plan

How is the study designed?

Design Details

• Observational Models: Cohort
• Time Perspectives: Retrospective

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
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; 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.
validation cohort; The cohort of Women's Hospital, School of Medicine, Zhejiang University is a validation cohort	Diagnostic test: radiomics; 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
AUC value	Area under the receiver operating characteristic (ROC) curve (AUC）	through study completion, an average of 1 year

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Diagnostic specificity	diagnosis specificity of intelligent ultrasound analysis	through study completion, an average of 1 year
Diagnostic sensitivity	diagnosis sensitivity of intelligent ultrasound analysis	through study completion, an average of 1 year

Collaborators and Investigators

• Sponsor: Tongji Hospital
• Collaborators: Women's Hospital School Of Medicine Zhejiang University

Study record dates

Study Major Dates

• Study Start (Actual): October 1, 2021
• Primary Completion (Anticipated): December 1, 2022
• Study Completion (Anticipated): July 1, 2023

Study Registration Dates

• First Submitted: May 18, 2022
• First Submitted That Met QC Criteria: May 18, 2022
• First Posted (Actual): May 24, 2022

Study Record Updates

• Last Update Posted (Actual): May 24, 2022
• Last Update Submitted That Met QC Criteria: May 18, 2022
• Last Verified: May 1, 2022

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Neoplasms; Urogenital Neoplasms; Neoplasms by Site; Uterine Neoplasms; Genital Neoplasms, Female; Uterine Diseases; Endometrial Neoplasms
• Other Study ID Numbers: 2022-TJ-R-RBM

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: No

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No