Purpose: To quantify contrast material enhancement of breast lesions scanned with dedicated breast computed tomography (CT) and to compare their conspicuity with that at unenhanced breast CT and mammography.
Materials And Methods: Approval of the institutional review board and the Radiation Use Committee and written informed consent were obtained for this HIPAA-compliant study. Between September 2006 and April 2009, 46 women (mean age, 53.2 years; age range, 35-72 years) with Breast Imaging Reporting and Data System category 4 or 5 lesions underwent unenhanced breast CT and contrast material-enhanced breast CT before biopsy. Two radiologists independently scored lesion conspicuity for contrast-enhanced breast CT versus mammography and for contrast-enhanced breast CT versus unenhanced breast CT. Mean lesion voxel intensity was measured in Hounsfield units and normalized to adipose tissue intensity on manually segmented images obtained before and after administration of contrast material. Regression models focused on conspicuity and quantified enhancement were used to estimate the effect of pathologic diagnosis (benign vs malignant), lesion type (mass vs calcifications), breast density, and interradiologist variability.
Results: Fifty-four lesions (25 benign, 29 malignant) in 46 subjects were analyzed. Malignant lesions were seen significantly better at contrast-enhanced breast CT than at unenhanced breast CT (P < .001) or mammography (P < .001). Malignant calcifications (malignant lesions manifested mammographically as microcalcifications only, n = 7) were seen better at contrast-enhanced breast CT than at unenhanced breast CT (P < .001) and were seen similarly at contrast-enhanced breast CT and mammography. Malignant lesions enhanced 55.9 HU +/- 4.0 (standard error), whereas benign lesions enhanced 17.6 HU +/- 6.1 (P < .001). Ductal carcinoma in situ (n = 5) enhanced a mean of 59.6 HU +/- 2.8. Receiver operating characteristic curve analysis of lesion enhancement yielded an area under the receiver operating characteristic curve of 0.876.
Conclusion: Conspicuity of malignant breast lesions, including ductal carcinoma in situ, is significantly improved at contrast-enhanced breast CT. Quantifying lesion enhancement may aid in the detection and diagnosis of breast cancer.
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http://dx.doi.org/10.1148/radiol.10092311 | DOI Listing |
Oncol Lett
March 2025
Department of Imaging, The Affiliated Hospital of Beihua University, Jilin, Jilin 132011, P.R. China.
Contrast-enhanced ultrasonography (CEUS), a newly developed imaging technique, holds certain value in differentiating benign from malignant tumors. Additionally, serum tumor markers also exhibit significant clinical importance in the diagnosis and monitoring of malignant tumors. Reports have indicated abnormal expression of HER-2, CA153 and sE-cad in breast cancer.
View Article and Find Full Text PDFCureus
December 2024
Oncology/Radiation Oncolgy, Tawam Hospital, Al Ain, ARE.
Granulomatous mastitis (GM) is a chronic inflammatory breast condition that presents significant diagnostic challenges due to its clinical and imaging similarities to malignancies. Accurate diagnosis is crucial to avoid unnecessary interventions and ensure effective management. A total of 1,216 articles were initially identified through a comprehensive database search.
View Article and Find Full Text PDFAJR Am J Roentgenol
January 2025
Department of Radiology, Division of Breast Imaging and Intervention, Mayo Clinic, Phoenix, AZ.
Contrast-enhanced mammography (CEM) is growing in clinical use due to its increased sensitivity and specificity compared to full-field digital mammography (FFDM) and/or digital breast tomosynthesis (DBT), particularly in patients with dense breasts. To perform an intraindividual comparison of MGD between FFDM, DBT, a combination protocol using both FFDM and DBT (combined FFDM-DBT), and CEM, in patients undergoing breast cancer screening. This retrospective study included 389 women (median age, 57.
View Article and Find Full Text PDFInt J Comput Assist Radiol Surg
January 2025
Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nuremberg, Martensstr. 3, 91058, Erlangen, Bayern, Germany.
Purpose: Breast cancer remains one of the most prevalent cancers globally, necessitating effective early screening and diagnosis. This study investigates the effectiveness and generalizability of our recently proposed data augmentation technique, attention-guided erasing (AGE), across various transfer learning classification tasks for breast abnormality classification in mammography.
Methods: AGE utilizes attention head visualizations from DINO self-supervised pretraining to weakly localize regions of interest (ROI) in images.
JCO Clin Cancer Inform
January 2025
SimBioSys Inc, Chicago, IL.
Purpose: Perfusion modeling presents significant opportunities for imaging biomarker development in breast cancer but has historically been held back by the need for data beyond the clinical standard of care (SoC) and uncertainty in the interpretability of results. We aimed to design a perfusion model applicable to breast cancer SoC dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) series with results stable to low temporal resolution imaging, comparable with published results using full-resolution DCE-MRI, and correlative with orthogonal imaging modalities indicative of biophysical markers.
Methods: Subsampled high-temporal-resolution DCE-MRI series were run through our perfusion model and resulting fits were compared for consistency.
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