ArticlePloS one2016
Differentiation of Malignant and Benign Incidental Breast Lesions Detected by Chest Multidetector-Row Computed Tomography: Added Value of Quantitative Enhancement Analysis.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 26 citations in OpenAlex.
- Beyond the heart: a pictorial review of extracardiac findings on cardiac CT.The international journal of cardiovascular imaging · 2026Review
- Beyond the lung: recognizing incidental breast lesions on chest computed tomography.Translational cancer research · 2026Review
- Breast cancer assessment under neoadjuvant systemic therapy using thoracic photon-counting detector computed tomography in prone position: a pilot study.European radiology experimental · 2025Article
- Contrast-Enhanced Chest Computed Tomography forDiagnostics (Basel, Switzerland) · 2025Article
- Differentiating between benign and malignant breast lesions using dual-energy CT-based model: development and validation.Insights into imaging · 2024Article
- Dual-Energy CT in Breast Cancer: Current Applications and Future Outlooks.Precision radiation oncology · 2023Review
- A Review on the Use of Imaging Biomarkers in Oncology Clinical Trials: Quality Assurance Strategies for Technical Validation.Tomography (Ann Arbor, Mich.) · 2023Review
- Improving segmentation and detection of lesions in CT scans using intensity distribution supervision.Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society · 2023Article
- Mammary nodules as incidental findings on chest computed tomography: a retrospective analysis on their frequency and predictive value.La Radiologia medica · 2023Article
- Complete, Fully Automatic Detection and Classification of Benign and Malignant Breast Tumors Based on CT Images Using Artificial Intelligent and Image Processing.Journal of clinical medicine · 2023Article
- Dual-energy CT quantitative parameters for the differentiation of benign from malignant lesions and the prediction of histopathological and molecular subtypes in breast cancer.Quantitative imaging in medicine and surgery · 2021Article
- Subjective and Objective Assessment of Monoenergetic and Polyenergetic Images Acquired by Dual-Energy CT in Breast Cancer.Korean journal of radiology · 2021Article
- Computertomography-Based Prediction of Complete Response Following Neoadjuvant Chemoradiotherapy of Locally Advanced Rectal Cancer.Frontiers in oncology · 2021Article
- Multidetector Computed Tomography with Dedicated Protocol for Breast Cancer Locoregional Staging: Feasibility Study.Diagnostics (Basel, Switzerland) · 2020Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To retrospectively determine the association between breast lesion morphology and malignancy and to determine the optimal value of lesion enhancement (HU, Hounsfield units) to improve the diagnostic accuracy of breast cancer in patients with incidental breast lesions (IBLs). A total of 97 patients with 102 IBLs detected from July 2009 to December 2012 were enrolled in this study. Two radiologists analyzed CT images for the presence of malignancy based on the morphology of the lesions alone and in combination with an enhancement value (HU) analysis. There were 36 malignant and 66 benign IBLs. When the morphology and enhancement values were combined, the sensitivity, specificity, and accuracy were 92%, 97%, and 95%, respectively, for reader 1 and 89%, 94%, and 92%, respectively, for reader 2. The addition of HU values led to correct changes in the diagnosis; specifically, the accuracy of the diagnosis of reader 1 and reader 2 improved by 6.9% and 11.8%, respectively. The addition of the enhancement value (HU) to the CT morphology improved the diagnostic accuracy in the differentiation of malignant from benign IBLs by using the region of interest (ROI) to measure the HU within the most suspicious part of the lesion.
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