Purpose: To evaluate clinically an automated ultrasound (US) system for detecting benign and malignant breast lesions.
Materials And Methods: A prototype automated US system was used to examine 119 patients: 38 patients with 39 proved malignant breast lesions (7-50 mm), 41 patients with 41 proved benign breast lesions (8-40 mm), and 40 patients without breast lesions. The device yields a three-dimensional set of B-mode scans and reconstructed US images comparable to mammograms. All patients had undergone mammography. Four radiologists who had not performed the examinations independently assessed the mammograms and US images to detect benign and malignant breast lesions.
Results: Each of the four readers did not recognize one to three detectable malignant lesions on mammograms, one to two detectable malignant lesions on US images, two to four detectable benign lesions on mammograms, and five to seven detectable benign lesions on US images. All readers identified the 39 cancers with at least one of the modalities. The 40 cases without lesions were diagnosed correctly more frequently on the US images by three readers and on the mammograms by one reader.
Conclusion: Depiction of breast lesions at automated US is reproducible. Automated US is complementary to mammography.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1148/radiology.205.3.9393543 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
A rare case of hydatid cyst presenting as a breast cancer. A case report.
Int J Surg Case Rep
December 2024
Debre Markos University, Surgery Department, Ethiopia. Electronic address:
Introduction And Importance: Hydatid disease, caused by the Echinococcus parasite, is a significant health concern in endemic regions. While commonly found in the liver and lungs, breast involvement is rare. We present a case of a hydatid cyst in the breast of a 34-year-old woman from Ethiopia, initially suspected to be breast cancer.
View Article and Find Full Text PDFPredicting axillary lymph node metastasis in breast cancer using a multimodal radiomics and deep learning model.
Front Immunol
December 2024
Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China.
Objective: To explore the value of combined radiomics and deep learning models using different machine learning algorithms based on mammography (MG) and magnetic resonance imaging (MRI) for predicting axillary lymph node metastasis (ALNM) in breast cancer (BC). The objective is to provide guidance for developing scientifically individualized treatment plans, assessing prognosis, and planning preoperative interventions.
Methods: A retrospective analysis was conducted on clinical and imaging data from 270 patients with BC confirmed by surgical pathology at the Third Hospital of Shanxi Medical University between November 2022 and April 2024.
Prognostic Implications of the Bethesda System in Fine-Needle Aspiration for Follicular Thyroid Carcinoma.
Arch Pathol Lab Med
December 2024
From the Department of Medicine, Thyroid Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea (SW Kim, JH Chung, TH Kim).
Context.—: Fine-needle aspiration is an effective tool for sampling thyroid nodules; its results are classified according to the Bethesda System for Reporting Thyroid Cytopathology (BSRTC), whose categories define malignancy risks.
Objective.
Deep learning radiomics on grayscale ultrasound images assists in diagnosing benign and malignant of BI-RADS 4 lesions.
Sci Rep
December 2024
Department of Medical Ultrasound, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, No. 16766, Jingshi Road, Jinan, 250014, Shandong, People's Republic of China.
This study aimed to explore a deep learning radiomics (DLR) model based on grayscale ultrasound images to assist radiologists in distinguishing between benign breast lesions (BBL) and malignant breast lesions (MBL). A total of 382 patients with breast lesions were included, comprising 183 benign lesions and 199 malignant lesions that were collected and confirmed through clinical pathology or biopsy. The enrolled patients were randomly allocated into two groups: a training cohort and an independent test cohort, maintaining a ratio of 7:3.
View Article and Find Full Text PDFCorrelation between ultrasonography and elastography parameters and molecular subtypes of breast cancer in young women.
Ann Med
December 2025
Department of Ultrasonographl, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital, Taiyuan, Shanxi Province, China.
Objective: To explore the differences of conventional ultrasound characteristics, elastic imaging parameters and clinicopathological characteristics of distinct molecular subtypes of breast cancer in young women, and to identify imaging parameters that exhibited significant associations with each molecular subtype.
Methods: We performed a retrospective analysis encompassing 310 young women with breast cancer. Observations were made regarding the ultrasonography and elastography characteristics of the identified breast lesions.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!