ArticleJapanese journal of radiology2021
Subcategory classifications of Breast Imaging and Data System (BI-RADS) category 4 lesions on MRI.
Article in Japanese journal of radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed, 24 citations in OpenAlex.
- Additional diagnostic value of lesion visibility on diffusion-weighted imaging for differentiating BI-RADS category 4 MRI-detected breast lesions.Japanese journal of radiology · 2026Article
- An interpretable AI system reduces false-positive MRI diagnoses by stratifying high-risk breast lesions.Nature communications · 2026Article
- Comparison of state-of-the-art biopsy systems for ultrasound-guided breast biopsy using a chicken breast phantom.Journal of medical ultrasonics (2001) · 2024Article
- Third-look contrast-enhanced ultrasonography plus needle biopsy for differential diagnosis of magnetic resonance imaging-only detected breast lesions.Journal of medical ultrasonics (2001) · 2024Review
- Investigation of imaging features in contrast-enhanced magnetic resonance imaging of benign and malignant breast lesions.Japanese journal of radiology · 2024Article
- Clinical Utility of Breast Ultrasound Images Synthesized by a Generative Adversarial Network.Medicina (Kaunas, Lithuania) · 2023Article
- Subcategorization of suspicious non-mass-like enhancement lesions(BI-RADS-MRI Category4).BMC medical imaging · 2023Article
- Use of a deep learning algorithm for non-mass enhancement on breast MRI: comparison with radiologists' interpretations at various levels.Japanese journal of radiology · 2023Article
- Magnetic resonance imaging diagnosis of non-mass enhancement of the breast.Journal of medical ultrasonics (2001) · 2023Review
- Reducing the number of unnecessary biopsies for mammographic BI-RADS 4 lesions through a deep transfer learning method.BMC medical imaging · 2023Article
- Value of breast MRI omics features and clinical characteristics in Breast Imaging Reporting and Data System (BI-RADS) category 4 breast lesions: an analysis of radiomics-based diagnosis.Annals of translational medicine · 2021Article
- Diffusion-weighted Imaging Allows for Downgrading MR BI-RADS 4 Lesions in Contrast-enhanced MRI of the Breast to Avoid Unnecessary Biopsy.Clinical cancer research : an official journal of the American Association for Cancer Research · 2021Article
- Breast MRI-the Importance of Type II and III Dynamic Curves Evaluation and Framing in BI-RADS 4C and 5 Score.Current health sciences journalArticle
- New developments in the BI-RADS for MRI.Radiologia brasileiraArticle
- Refining the assessment of BI-RADS 4 lesions on breast magnetic resonance imaging.Radiologia brasileiraArticle
- Are we ready to stratify BI-RADS 4 lesions observed on magnetic resonance imaging? A real-world noninferiority/equivalence analysis.Radiologia brasileiraArticle
- Are we ready to stratify BI-RADS 4 MRI lesions?Radiologia brasileiraArticle
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Authors and funding
10 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
purposeCategory 4 in BI-RADS for magnetic resonance imaging (MRI) has a wide range of probabilities of malignancy, extending from > 2 to < 95%. We classified category 4 lesions into three subcategories and analyzed the positive predictive value (PPV) of malignancy in a tertiary hospital. MATERIALS AND
methodsThis retrospective study included 346 breast MRIs with 434 category 2-5 lesions. All enhancing lesions were classified as category 2 (0% probability of malignancy), 3 (> 0%, ≤ 2%), 4 (> 2%, < 95%) and 5 (≥ 95%); category 4 lesions were further subcategorized into 4A (> 2%, ≤ 10%), 4B (> 10%, ≤ 50%) and 4C (> 50%, < 95%) at the time of diagnosis. Radiological and pathological reports were retrospectively analyzed, and the PPVs were calculated.
resultsWe included 149 malignant and 285 benign lesions. The PPVs of subcategories 4A, 4B and 4C were 1.8%, 11.8% and 67.5%, respectively. The PPVs were higher for lesions coexisting with category 5 or 6 lesions compared with those for isolated lesions.
conclusionCategory 4 lesions can be classified into three subcategories depending on the likelihood of malignancy. Lesions coexisting with category 5 or 6 lesions are more likely to be malignant.
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