Purpose: To determine whether palpable non-calcified solid breast masses with benign morphology on ultrasound can be classified as probably benign and whether these lesions fulfill the criteria required for BI-RADS (TM) category III.
Materials And Methods: This analysis includes 78 patients with 80 palpable non-calcified solid masses that were classified as probably benign at initial sonography. Of 78 patients, 66 had periodic imaging surveillance (2 - 8 years, mean 4.6 years). The remaining 12 patients had a biopsy after initial imaging.
Results: In the 64 patients under surveillance, palpable lesions remained stable at follow-up. In 2 patients lesions increased in size during follow-up and no malignancy was diagnosed at subsequent open biopsy. In 19 of the 66 patients, 29 additional nonpalpable lesions of similar morphology were detected on ultrasound. No malignancy was diagnosed in the 12 patients, who had a biopsy after initial imaging.
Conclusion: Our data suggest that palpable non-calcified solid breast masses with benign morphology on ultrasound can be classified as probably benign (BI-RADS (TM) category III). Biopsy can be averted when lesions remain stable at follow-up.
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http://dx.doi.org/10.1055/s-2004-813369 | DOI Listing |
Diagnostics (Basel)
January 2025
Department of Radiology, Inje University Haeundae Paik Hospital, Busan 48108, Republic of Korea.
: This study aimed to compare ultrasound (US) findings between automated and handheld breast ultrasound (ABUS and HHUS, respectively) in small breast cancers, based on the breast imaging reporting and data system (BI-RADS) category. : We included 51 women (mean age: 52 years; range: 39-66 years) with breast cancer (invasive or DCIS), all of whom underwent both ABUS and HHUS. Patients with tumors measuring ≤1 cm on either modality were enrolled.
View Article and Find Full Text PDFQuant Imaging Med Surg
January 2025
Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.
Background: Breast imaging reporting and data system (BI-RADS) provides standard descriptors but not detailed decision rules for characterizing breast lesions. Diffusion-weighted imaging (DWI) and T2-weighted imaging (T2WI) are also not incorporated in the BI-RADS. Several multiparametric magnetic resonance imaging (mpMRI)-based decision rules have been developed to differentiate breast lesions, but lack external validation.
View Article and Find Full Text PDFJ Breast Imaging
January 2025
Department of Radiology, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK.
Breast cancer is the most prevalent cancer in women in Europe, and while all European countries have some form of screening for breast cancer, disparities in organization and implementation exist. Breast density is a well-established risk factor for breast cancer; however, most countries in Europe do not have recommendations in place for notification of breast density or additional supplementary imaging for women with dense breasts. Various supplemental screening modalities have been investigated in Europe, and when comparing modalities, MRI has been shown to be superior in cancer detection rate and in detecting small invasive disease that may impact long-term survival, as demonstrated in the Dense Tissue and Early Breast Neoplasm Screening (DENSE) trial in the Netherlands.
View Article and Find Full Text PDFRev Esp Patol
January 2025
Department of Pathology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India. Electronic address:
Background: The diagnosis of breast cancer necessitates a multifaceted approach integrating cytopathological and radiological assessments. The International Academy of Cytology (IAC) Yokohama system and Breast Imaging Reporting and Data System (BI-RADS) are fundamental frameworks in this context. This study aims to evaluate the diagnostic potential of a combined Yokohama-BI-RADS scoring system for breast lesions.
View Article and Find Full Text PDFGland Surg
December 2024
Department of Ultrasound, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
Background: Accurate diagnosis of breast cancer is of great importance to improve the prognosis of patients. Artificial intelligence (AI)-assisted diagnostic system for breast ultrasound is gradually being applied in the identification of benign and malignant breast lesions. This study aimed to evaluate the diagnostic performance and optimal application of AIassisted ultrasonography for breast lesions in clinical setting.
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