NCT06069921

Using Deep Learning and Radiomics to Diagnose Benign and Malignant Breast Lesions Based on Ultrasound

Ultrasound-based Deep Learning Signature and Radiomics Signature Nomogram for Diagnosis of Benign and Malignant Breast Lesions of BI-RADS Category 4 Using Intratumoral and Peritumoral Regions

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 400 (actual)
• Sponsor: Ma Zhe · Academic / Other
• Sex: Female
• Age: 15 Years – 80 Years
• Healthy volunteers: Not accepted

Summary

This retrospective study aimed to create a prediction model using deep learning and radiomics features extracted from intratumoral and peritumoral regions of breast lesions in ultrasound images, to diagnose benign and malignant breast lesions with BI-RADS 4 classification. Materials and methods: Patients who visited in The First Affiliated Hospital of Shandong First Medical University ＆ Shandong Provincial Qianfoshan Hospital were collected. Their general clinical features, information on preoperative ultrasound diagnosis, and postoperative pathologic data were reviewed.

Conditions

• Breast Diseases

Timeline

• Start date: 2015-01-01
• Primary completion: 2022-12-30
• Completion: 2022-12-30
• First posted: 2023-10-06
• Last updated: 2024-06-25

Locations

1 site across 1 country: China