Sub-regional Tumor Segmentation Based on CEUS Perfusion Characteristics: Enhancing Breast Tumor Diagnosis

Sub-regional Tumor Segmentation Based on Contrast-Enhanced Ultrasound Perfusion Characteristics: A Historical-Prospective Cohort Study for the Diagnosis of Breast Tumor

The goal of this study is to investigate breast cancer's internal heterogeneity and enhance diagnostic accuracy. The investigators aim to achieve this by utilizing Contrast-Enhanced Ultrasound (CEUS) technology, which provides detailed information about tumor perfusion dynamics. Traditional biopsy methods have limitations due to the invasive nature and complexity of breast cancer heterogeneity.

Participants in this study will undergo preoperative breast cancer diagnosis using CEUS technology, which is safe, cost-effective, and convenient. Dynamic CEUS videos will be used to cluster perfusion characteristics at the pixel level within breast tumors, allowing the investigators to divide the tumors into distinct subregions based on these clusters. The investigators will then explore the correlation between these perfusion subregions and the diagnosis of benign or malignant breast tumors.

The ultimate aim is to develop diagnostic models that utilize non-invasive imaging data to enhance breast cancer diagnosis. This approach reduces subjective judgments in the diagnostic process, potentially improving diagnostic accuracy. It also provides valuable information for personalized treatment decisions, thus advancing the field of breast cancer treatment.

Study Overview

Status

Completed

Conditions

Detailed Description

Breast cancer is one of the most prevalent cancers among women globally, and its increasing incidence poses a significant threat to women's health. Despite notable advances in early diagnosis and treatment due to the continuous progress in medical technology, the high heterogeneity within breast cancer still results in considerable variability in clinical manifestations, treatment responses, and disease progression. This diversity presents new challenges in achieving precise treatment. Thus, a profound exploration and study of the heterogeneity of breast cancer are crucial for developing more effective diagnostic models, advancing treatment strategies, and enhancing cure rates.

In current clinical practice, although biopsy is widely used for the diagnosis of benign or malignant breast tumors, its accuracy and comprehensiveness are somewhat limited due to the complex internal heterogeneity of breast cancer and the invasive nature of the procedure. In recent years, preoperative qualitative diagnosis of breast cancer using medical imaging technology has become a hot topic in research. Compared with other common imaging techniques such as CT and MRI, ultrasound examination is extensively employed due to its safety, convenience, and lower cost. Particularly, Contrast-Enhanced Ultrasound (CEUS) technology, with its superior temporal resolution, can vividly illustrate the details of tumor perfusion hemodynamics, effectively revealing key features such as enhancement patterns, blood supply, and vascular invasion of the tumor.

This study is dedicated to using dynamic CEUS videos to cluster perfusion characteristics at the pixel level within the tumor and divide the tumor into different subregions based on the clustering results. We will explore the correlation between these perfusion subregions and the diagnosis of benign or malignant breast tumors, and based on this, develop related diagnostic models. This non-invasive diagnostic approach aims to maximally mine and utilize image data, comprehensively capturing the tumor's perfusion characteristics at the pixel level, and reducing subjective judgments in the diagnostic process. The application of this method is not only expected to improve the accuracy of breast cancer diagnosis but also to provide more information support for personalized treatment of patients, thereby promoting progress in the field of breast cancer treatment.

Study Type

Observational

Enrollment (Actual)

339

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Zhejiang
      • Hangzhou, Zhejiang, China, 310000
        • Department of Ultrasound, Second Affiliated Hospital, School of Medicine, Zhejiang University

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

N/A

Sampling Method

Non-Probability Sample

Study Population

Patients with breast nodule

Description

Inclusion Criteria:

  • Prospective cohort patients voluntarily sign an informed consent form.
  • Patients who undergo breast contrast-enhanced ultrasound.
  • Patients with breast nodules that have not received any treatment.

Exclusion Criteria:

  • Patients who cannot obtain pathological results due to refusal of further diagnosis or treatment.
  • Patients whose breast lesions are too large to display their long axis under the ultrasound probe.
  • Patients contraindicated for contrast-enhanced ultrasound.
  • Historical cohort patients who cannot obtain ultrasound contrast videos of at least 45-60 seconds post contrast agent injection.
  • Patients whose ultrasound contrast videos show excessive motion displacement that cannot be corrected.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Benign breast tumors
Performing contrast-enhanced ultrasound on benign breast tumors and analyzing the video images
Malignant breast tumors
Performing contrast-enhanced ultrasound on malignant breast tumors and analyzing the video images.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Accuracy
Time Frame: 6 months
The proportion of breast tumors (benign or malignant) correctly classified by the diagnostic model.
6 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

July 1, 2023

Primary Completion (Actual)

January 3, 2025

Study Completion (Actual)

January 3, 2025

Study Registration Dates

First Submitted

December 7, 2023

First Submitted That Met QC Criteria

December 7, 2023

First Posted (Actual)

December 15, 2023

Study Record Updates

Last Update Posted (Actual)

March 25, 2025

Last Update Submitted That Met QC Criteria

January 8, 2025

Last Verified

January 1, 2025

More Information

Terms related to this study

Other Study ID Numbers

  • 2023-0555

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

The data cannot be shared because of ethical restrictions regarding human participant data.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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