High-resolution rapid diagnostic imaging of whole prostate biopsies using video-rate fluorescence structured illumination microscopy

Rapid assessment of prostate core biopsy pathology at the point-of-procedure could provide benefit in a variety of clinical situations. Even with advanced trans-rectal ultrasound guidance and saturation biopsy protocols, prostate cancer can be missed in up to half of all initial biopsy procedures.

In addition, collection of tumor specimens for downstream histological, molecular, and genetic analysis is hindered by low tumor yield due to inability to identify prostate cancer grossly. However, current point-of-procedure pathology protocols such as frozen section analysis (FSA) are destructive, and too time- and labor-intensive to be practical or economical. Ex vivo microscopy of the excised specimens, stained with fast-acting fluorescent histology dyes, could be an attractive non-destructive alternative to FSA. In this work, we report the first demonstration of video-rate structured illumination microscopy (VR-SIM) for rapid high-resolution diagnostic imaging of prostate biopsies in realistic point-of-procedure timeframes. Large mosaic images of prostate biopsies stained with acridine orange are rendered in seconds, and contain excellent contrast and detail, exhibiting close correlation with corresponding H&E histology. A clinically-relevant review of VR-SIM images of 34 unfixed and uncut prostate core biopsies by two independent pathologists resulted in an area under the ROC curve (AUC) of 0.82-0.88, with a sensitivity ranging from 63-88% and a specificity ranging from 78-89%. When biopsies contained more than 5% tumor content, the sensitivity improved to 75-92%. The image quality, speed, minimal complexity, and ease of use of VR-SIM could prove to be features in favor of adoption as an alternative to destructive pathology at the point-of-procedure.

Cancer research 2015 Aug 17 [Epub ahead of print]

Mei Wang, Hillary Z Kimbrell, Andrew B Sholl, David B Tulman, Katherine N Elfer, Tyler C Schlichenmeyer, Benjamin R Lee, Michelle Lacey, J Quincy Brown

Biomedical Engineering, Tulane University , Pathology and Laboratory Medicine, Tulane University School of Medicine , Pathology and Laboratory Medicine, Tulane University School of Medicine , Bioinnovation Program, Tulane University , Biomedical Engineering, Tulane University , Biomedical Engineering, Tulane University , Urology, Tulane University School of Medicine , Mathematics, Tulane University , Department of Biomedical Engineering, Tulane University 



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