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Contrast-enhanced digital mammography (CEDM) is a diagnostic tool for breast cancer detection. Artefacts are observed in about 10% of CEDM examinations. Understanding CEDM artefacts is important to prevent diagnostic misinterpretation. In this article, we have described the artefacts that we have commonly encountered in clinical practice; we hope to ease the recognition and help troubleshoot solutions to prevent or minimise them.
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http://dx.doi.org/10.1186/s13244-019-0811-x | DOI Listing |
PLoS One
September 2025
Korea University College of Medicine, Seoul, Republic of Korea.
Purpose: To develop and validate a deep learning-based model for automated evaluation of mammography phantom images, with the goal of improving inter-radiologist agreement and enhancing the efficiency of quality control within South Korea's national accreditation system.
Materials And Methods: A total of 5,917 mammography phantom images were collected from the Korea Institute for Accreditation of Medical Imaging (KIAMI). After preprocessing, 5,813 images (98.
Radiol Med
September 2025
Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141, Milan, Italy.
Metastatic involvement (MB) of the breast from extramammary malignancies is rare, with an incidence of 0.09-1.3% of all breast malignancies.
View Article and Find Full Text PDFDigit Health
September 2025
Department of Respiratory and Critical Care Medicine, The Sixth Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Objective: Accurate segmentation of breast lesions, especially small ones, remains challenging in digital mammography due to complex anatomical structures and low-contrast boundaries. This study proposes DVF-YOLO-Seg, a two-stage segmentation framework designed to improve feature extraction and enhance small-lesion detection performance in mammographic images.
Methods: The proposed method integrates an enhanced YOLOv10-based detection module with a segmentation stage based on the Visual Reference Prompt Segment Anything Model (VRP-SAM).
Radiol Case Rep
November 2025
Department of Clinical and Experimental Medicine, Foggia University School of Medicine, Viale L. Pinto 1, 71122 Foggia, Italy.
We report a rare case of breast and axillary metastases in a 75-year-old man diagnosed with prostate carcinoma. Initially, the patient presented with lower urinary tract symptoms (LUTS) and elevated prostate-specific antigen (PSA) levels. Prostate cancer was confirmed by biopsy and treated with androgen deprivation therapy (ADT) and radiotherapy.
View Article and Find Full Text PDFNihon Hoshasen Gijutsu Gakkai Zasshi
September 2025
Department of Radiological Technology, Faculty of Health Sciences, Gifu University of Medical Science.
Purpose: We aimed to develop an AI-based system to score the positioning in mammography (MG), with the goal of establishing a foundation for future technical support.
Methods: Using 800 mediolateral oblique (MLO) images, we developed an AI model (Mask Generation Model) for automatic extraction of three regions: the pectoralis major muscle, the mammary gland region, and the nipple. Using this model, we extracted three regions from 1544 MLO images and generated mask images.