Purpose: To determine the clinical implication of recommendation for repeat biopsy after large-core stereotaxic breast biopsy.
Materials And Methods: Repeat biopsy was recommended in 56 (18%; mean age, 51.0 years) of 314 consecutive women who underwent stereotaxic core biopsy. Biopsy was performed by using a dedicated prone stereotaxic table and digital imaging. When calcifications were present, specimen radiography was performed. Fifty of the 56 women underwent follow-up biopsy.
Results: Repeat biopsy was recommended because of ductal atypia in 30 patients, discordant imaging and histopathologic results in 15, diagnoses for which more tissue was required in 10, and radial scar in one. Twenty-two (39%) of the 56 had carcinoma. Carcinoma was detected in 15 women (50%) with ductal atypia and in seven women (47%) with discordant histopathologic and imaging findings. No other cancer was detected.
Conclusion: Rebiopsy of those lesions for which results are nonconcordant or with a high incidence of coexistent malignancy is necessary for stereotaxic core biopsy to be optimally effective. Among the 56 patients, 39% had malignancy.
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http://dx.doi.org/10.1148/radiology.198.2.8596825 | DOI Listing |
J Med Imaging Radiat Oncol
June 2024
Department of Medical Imaging, Royal Perth Hospital, Perth, Western Australia, Australia.
Introduction: Contrast-enhanced mammography (CEM) and MRI detect 'contrast-only' lesions (COLs) occult on standard breast imaging (ultrasound and conventional mammography). Until recently, MRI was the only reliable method of biopsy. This study presents the first Australian experience with CEM-guided biopsy (CEMBx) and the lessons learnt.
View Article and Find Full Text PDFAngiogenesis
August 2024
Department of Neurosurgery, Xuanwu Hospital, China International Neuroscience Institute, Capital Medical University, 45 Changchun St, Beijing, 100053, China.
Current treatments of brain arteriovenous malformation (BAVM) are associated with considerable risks and at times incomplete efficacy. Therefore, a clinically consistent animal model of BAVM is urgently needed to investigate its underlying biological mechanisms and develop innovative treatment strategies. Notably, existing mouse models have limited utility due to heterogenous and untypical phenotypes of AVM lesions.
View Article and Find Full Text PDFSeizure
April 2024
Neurosciences and Mental Health, Hospital for Sick Children, 686 Bay St, Toronto, Ontario, M5G 0A4, Canada; Institute of Biomedical Engineering, University of Toronto, 164 College St, Toronto, Ontario, M5S 3E2, Canada; Division of Neurosurgery, Hospital for Sick Children, 555 University Ave, Toronto, Ontario, M5G 1×8, Canada; Department of Surgery, University of Toronto, 149 College St, Toronto, Ontario, M5T 1P5, Canada. Electronic address:
Purpose: Stereoelectroencephalography (sEEG) is increasingly utilized for localization of seizure foci, functional mapping, and neurocognitive research due to its ability to target deep and difficult to reach anatomical locations and to study in vivo brain function with a high signal-to-noise ratio. The research potential of sEEG is constrained by the need for accurate localization of the implanted electrodes in a common template space for group analyses.
Methods: We present an algorithm to automate the grouping of sEEG electrodes by trajectories, labelled by target and insertion point.
J Clin Neurosci
May 2024
Department of Neurosurgery, Osaka Metropolitan University, Graduate School of Medicine, Osaka, Japan.
Background: Seizure onset pattern (SOP) represents an alteration of electroencephalography (EEG) morphology at the beginning of seizure activity in epilepsy. With stereotactic electroencephalography (SEEG), a method for intracranial EEG evaluation, many morphological SOP classifications have been reported without established consensus. These inconsistent classifications with ambiguous terminology present difficulties to communication among epileptologists.
View Article and Find Full Text PDFFront Neurosci
March 2024
Kavli Institute for Systems Neuroscience and Centre for Neural Computation, Norwegian University of Science and Technology, NTNU, Trondheim, Norway.
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