Extramammary masses are infrequently encountered in breast examinations. They may occur in the chest wall and axilla as neighbors of the breast. It is important to determine the nature of the lesion. However, some benign tumors, such as granular cell tumors (GCTs), also show malignant characteristics, which leads to misdiagnosis. To the best of our knowledge, multimodal ultrasound features of GCT have not been elucidated. We report two cases of women with GCTs encountered upon breast cancer screening; the tumor was not located in breast tissue. The first patient was a 37-year-old woman who presented with a slow-growing mass in the right breast and the GCT was located in the pectoralis major muscle. The second patient was a 52-year-old woman who presented with a palpable left axillary mass and the GCT was located in the axilla. Mammography failed to detect the masses in the two patients upon breast cancer screening. However, two-dimensional ultrasonography revealed a solid heterogeneous hypoechoic mass. Shear wave elastography showed that the masses had an increased hardness compared with the surrounding tissue. Further contrast-enhanced ultrasonography showed that the contrast patterns of the two masses were different. In case one, contrast-enhanced ultrasonography showed an inhomogeneous annular high enhancement, and the dynamic curve showed rapid enhancement and regression. In case two, contrast enhanced ultrasound showed slight enhancement around the lesion but no enhancement inside. Postoperative pathology confirmed that the GCT was benign in both cases. The patients showed no signs of recurrence at the 2-year follow-up. Here, we report two cases and present the multimodal ultrasonography findings of this tumor for the first time. Radiologists and surgeons should be aware of these imaging manifestations and include them in their differential diagnoses.
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http://dx.doi.org/10.3389/fonc.2023.1136770 | DOI Listing |
J Neurotrauma
January 2025
Division of Neuroscience, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, Maryland, USA.
Effective team science requires procedural harmonization for rigor and reproducibility. Multicenter studies across experimental modalities (domains) can help accelerate translation. The Translational Outcomes Project in NeuroTrauma (TOP-NT) is a pre-clinical traumatic brain injury (TBI) consortium charged with establishing and validating noninvasive TBI assessment tools through team science.
View Article and Find Full Text PDFMicrosurgery
January 2025
Service de Chirurgie Plastique, Hôpital Européen Georges Pompidou, Assistance Publique-Hôpitaux de Paris (APHP), Université Paris Descartes, Paris, France.
Background: Venous congestion due to superficial venous system dominance (SVD) in deep inferior epigastric perforator (DIEP) flap surgery occurs in approximately 2% of cases, with attendant sequelae and increased cost to healthcare systems. This study aimed to describe the predictive factors for SVD in DIEP flap breast reconstruction based on preoperative computed tomography angiography (CTA) findings.
Methods: All women who required takebacks for additional venous anastomosis to the cephalic vein because of SVD after DIEP flap breast reconstruction between 2015 and 2022 were included.
Zh Nevrol Psikhiatr Im S S Korsakova
January 2025
Vladimirskii Moscow Regional Research and Clinical Institute, Moscow, Russia.
Objective: To investigate the structural damage in patients with aphasia in the acute phase of ischemic stroke using X-ray computed tomography (CT) scans of the brain.
Material And Methods: We examined 65 right-handed individuals in the acute stage of ischemic stroke in the left middle cerebral artery, including 39 men and 26 women aged 41 to 87 years. The patients were divided into two groups: those with aphasia (group 1, 48) and those without aphasia (group 2, 17).
Background: Based on the Fukuoka and Kyoto international consensus guidelines, the current clinical management of intraductal papillary mucinous neoplasm (IPMN) largely depends on imaging features. While these criteria are highly sensitive in detecting high-risk IPMN, they lack specificity, resulting in surgical overtreatment. Artificial Intelligence (AI)-based medical image analysis has the potential to augment the clinical management of IPMNs by improving diagnostic accuracy.
View Article and Find Full Text PDFFront Public Health
January 2025
Engineering Research Center of Photoelectric Detection and Perception Technology, Yunnan Normal University, Kunming, China.
The rising incidence of Alzheimer's disease (AD) poses significant challenges to traditional diagnostic methods, which primarily rely on neuropsychological assessments and brain MRIs. The advent of deep learning in medical diagnosis opens new possibilities for early AD detection. In this study, we introduce retinal vessel segmentation methods based on U-Net ad iterative registration Learning (ReIU), which extract retinal vessel maps from OCT angiography (OCT-A) facilities.
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