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Microscopy with Ultraviolet Surface Excitation (MUSE):Innovations in Diagnostics of Neuropathological Tumors

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Abstract

Introduction: In the era of molecular diagnostics and personalized medicine, it is becoming increasingly important to save tissue for downstream testing for optimal pathologic diagnosis. Unfortunately, conventional histology processing and its expenditure of tissue for H&E imaging often results in inadequate material for essential molecular tests downstream. Microscopy Using Ultraviolet Excitation (MUSE) has emerged as a promising potential answer in providing a novel tissuesparing method of generating morphologic imaging without the need to fix or cut fresh tissue. We aim to standardize protocols for imaging an array of CNS tumor samples and demonstrate equivalency to traditional FFPE H&E in terms of generating images for tumor diagnostics.

Materials and Methods: 24 CNS tumor biopsy specimens were imaged using the MUSE interface, then subsequently fixed and paraffinembedded for traditional H&E staining. Each pair of slides (MUSE and H&E) were then read by a panel of 4 neuropathologists, and the diagnosis by each reader was recorded as correct or wrong. Combined accuracy was calculated within each diagnosis category and for each pathologist.

Results: In surgical resections of 24 adult patients (mean age 54 years) with newly diagnosed brain and spinal cord tumors, 7/24 were diagnosed by conventional methodology with diffuse astrocytic/oligodendroglial tumors, 8/24 with meningiomas, 3/24 with ependymal/choroid plexus tumors, 3/24 with tumors of cranial/paraspinal nerves, and 3/24 with metastatic tumors. 97% concordance was observed among MUSE versus light microscopy diagnostics, with 94% within the pathologist panel.

Conclusions: MUSE imaging appears to have been successful in reliably generating diagnostic-quality histological images of CNS tumors. This is supported by inter-pathologist concordance on diagnoses made through both MUSE and traditional H&E images. Ongoing studies are expected to expand to assessments of grading MUSE images of more diagnostically difficult brain and spinal cord tumors.

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