Open Access
15 December 2020 Diagnosing 12 prostate needle cores within an hour of biopsy via open-top light-sheet microscopy
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Abstract

Significance: Processing and diagnosing a set of 12 prostate biopsies using conventional histology methods typically take at least one day. A rapid and accurate process performed while the patient is still on-site could significantly improve the patient’s quality of life.

Aim: We develop and assess the feasibility of a one-hour-to-diagnosis (1Hr2Dx) method for processing and providing a preliminary diagnosis of a set of 12 prostate biopsies.

Approach: We developed a fluorescence staining, optical clearing, and 3D open-top light-sheet microscopy workflow to enable 12 prostate needle core biopsies to be processed and diagnosed within an hour of receipt. We analyzed 44 biopsies by the 1Hr2Dx method, which does not consume tissue. The biopsies were then processed for routine, slide-based 2D histology. Three pathologists independently evaluated the 3D 1Hr2Dx and 2D slide-based datasets in a blinded, randomized fashion. Turnaround times were recorded, and the accuracy of our method was compared with gold-standard slide-based histology.

Results: The average turnaround time for tissue processing, imaging, and diagnosis was 44.5 min. The sensitivity and specificity of 1Hr2Dx in diagnosing cancer were both >90  %  .

Conclusions: The 1Hr2Dx method has the potential to improve patient care by providing an accurate preliminary diagnosis within an hour of biopsy.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Weisi Xie, Adam K. Glaser, Funda Vakar-Lopez, Jonathan L. Wright, Nicholas P. Reder, Jonathan T. C. Liu, and Lawrence D. True "Diagnosing 12 prostate needle cores within an hour of biopsy via open-top light-sheet microscopy," Journal of Biomedical Optics 25(12), 126502 (15 December 2020). https://doi.org/10.1117/1.JBO.25.12.126502
Received: 6 August 2020; Accepted: 24 November 2020; Published: 15 December 2020
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CITATIONS
Cited by 15 scholarly publications.
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KEYWORDS
Biopsy

Diagnostics

Prostate

Tissues

Cancer

3D image processing

Image processing

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