Confocal microscopy is in clinical use to diagnose skin cancers in the United States and in Europe. Potentially, this technology may provide bed-side pathology in breast cancer surgery during tumor removal. Initial studies have described major findings of invasive breast cancers as seen on fluorescence confocal microscopy. In many of these studies the region of interest (ROI) used in the analysis was user-selected and small (typically 15 square-mm). Although these important findings open exploration into rapid pathology, further development and implementation in a surgical setting will require examination of large specimens in a blinded fashion that will address the needs of typical surgical settings. In post surgery pathology viewing, pathologists inspect the entire pathology section with a low (2X) magnification objective lens initially and then zoomed in to ROIs with higher magnification lenses (10X to 40X) magnifications to further investigate suspected regions. In this study we explore the possibility of implementation in a typical surgical setting with a new microscope, termed confocal strip-mosaicking microscope (CSM microscope), which images an area of 400 square-mm (2 cm x 2 cm) of tissue with cellular level resolution in 10 minutes. CSM images of 34 human breast tissue specimens from 18 patients were blindly analyzed by a board-certified pathologist and correlated with the corresponding standard fixed histopathology. Invasive tumors and benign tissue were clearly identified in CSM images. Thirty specimens were concordant for images-to-histopathology correlation while four were discordant. Preliminary results from on-going work to molecularly target tumor margin will also be presented.
Sanjeewa Abeytunge, Bjorg A. Larson, Gary Peterson, Milind Rajadhyaksha, and Melissa Murray, "Assessment of fresh breast tissue specimens with confocal strip-mosaicking microscopy in an emulated pathology setting (Conference Presentation)," Proc. SPIE 10043, Diagnosis and Treatment of Diseases in the Breast and Reproductive System, 100430B (Presented at SPIE BiOS: January 28, 2017; Published: 19 April 2017); https://doi.org/10.1117/12.2252421.5370007619001.
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