Advanced MRI applications and findings of malignant phyllodes tumour: review of two cases

Phyllodes tumour or cystosarcoma phyllodes is a rare stromal breast tumour that is usually benign but on rare occasions can turn malignant. Non-specificity of the imaging features on sonography and mammography makes it difficult to distinguish malignant from benign counterparts solely based on imaging. The final diagnosis is still highly dependent on histopathological assessment. Herein, we describe two cases of malignant phyllodes tumour with emphasis on magnetic resonance (MR) imaging features using advanced MR applications

Lymphocytic Mastitis Mimicking Breast Carcinoma, Radiology and Pathology Correlation: Review of Two Cases

Lymphocytic mastitis, or diabetic mastopathy, is an unusual finding in early-onset and long-standing diabetes. It can presents as a non-tender or tender palpable breast mass. Mammogram and ultrasound frequently demonstrate findings suspicious of malignancy, thus biopsy and histological confirmation is usually required. We reviewed two cases of lymphocytic mastitis with characteristics findings on mammogram, ultrasound, and histopathology. Diagnoses were confirmed with excision biopsy

Diagnostic Efficacy of Synthesized 2D Digital Breast Tomosynthesis in Multi-ethnic Malaysian Population

Synthesized 2D images can be reconstructed from tomosynthesis images in breast imaging. This study aims to investigate the diagnostic efficacy of synthesized 2D images (C-View) in comparison to full field digital mammography (FFDM) when used with digital breast tomosynthesis (DBT) in multi-ethnic Malaysian population. FFDM and C-View images (n = 380) were independently evaluated by three readers through Breast Imaging Reporting and Data System (BI-RADS) categorisation, breast density and lesion characterisation. Statistical analysis was done comparing sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of C-View + DBT with FFDM + DBT as standard of reference. Very good interreader agreement in BI-RADS category and density assessment between C-View + DBT and FFDM + DBT, with high sensitivity, specificity, PPV and NPV of C-View + DBT when compared with FFDM + DBT. There was comparable PPV between C-View + DBT and FFDM + DBT, with histopathology as gold standard. High level of interreader agreement in BI-RADS category and density assessment for FFDM + DBT and C-View + DBT. There was good agreement between FFDM + DBT and C-View + DBT in mass characterization, and almost perfect agreement in calcification and asymmetric density. 52.2% lower radiation dose incurred when using C-View + DBT. Hence, synthesized 2D images are comparable to FFDM with reduction in radiation dose within the limits of Malaysian multi-ethnic population. © 2019, The Author(s)

Shearwave Elastography Increases Diagnostic Accuracy in Characterization of Breast Lesions

View of the elevation on Nevskiy Prospekt; In 1761 Vallen de la Motte took over the design of the Gostinyy Dvor (1758-1785) in St. Petersburg, a trading market of 200 shops with a central courtyard, which had been started by Bartolomeo Francesco Rastrelli. Vallen de la Motte achieved a clarity of concept and rationality that dispensed with Rastrelli’s planned Rococo decoration; only the handsome composition of the rounded corners hints at the Baroque. Source: Grove Art Online; http://www.oxfordartonline.com/ (accessed 1/15/2009

A Novel Algorithm for Breast Lesion Detection Using Textons and Local Configuration Pattern Features With Ultrasound Imagery

Breast cancer is the most commonly occurring cancer in women worldwide. While mammography remains the gold standard in breast cancer screening, ultrasound is an important imaging modality for both screening and cancer diagnosis. This paper presents a novel method for the detection of breast lesions in ultrasound images using texton filter banks, local configuration pattern features, and classification, without employing any segmentation technique. The developed method was able to accurately detect and classify breast lesions and achieved an accuracy, sensitivity, specificity, and positive predictive value of 96.1%, 96.5%, 95.3%, and 97.9%, respectively. The paradigm that we describe may, therefore, be useful as an effective tool to detect breast nodules during screening and in whole breast imaging, enabling clinicians to focus on images where a lesion is already known to be present. The developed method may also serve as a component for automatic breast nodule detection, and, when found, for the subsequent classification between lesion type benign versus malignant. © 2013 IEEE