A microscopic analysis of tissue is the gold standard for cancer detection. Hematoxylin-eosin (HE) for the reporting of prostate biopsy (PB) is conventionally based on fixation, processing, acquisition of glass slides, and analysis with an analog microscope by a local pathologist. Digitalization and real-time remote access to images could enhance the reporting process, and form the basis of artificial intelligence and machine learning. Fluorescence confocal microscopy (FCM), a novel optical technology, enables immediate digital image acquisition in an almost HE-like resolution without requiring conventional processing.

Digital Biopsy with Fluorescence Confocal Microscope for Effective Real-time Diagnosis of Prostate Cancer: A Prospective, Comparative Study / Rocco, Bernardo; Sighinolfi, Maria Chiara; Sandri, Marco; Spandri, Valentina; Cimadamore, Alessia; Volavsek, Metka; Mazzucchelli, Roberta; Lopez-Beltran, Antonio; Eissa, Ahmed; Bertoni, Laura; Azzoni, Paola; Reggiani Bonetti, Luca; Maiorana, Antonino; Puliatti, Stefano; Micali, Salvatore; Paterlini, Maurizio; Iseppi, Andrea; Rocco, Francesco; Pellacani, Giovanni; Chester, Johanna; Bianchi, Giampaolo; Montironi, Rodolfo. - In: EUROPEAN UROLOGY ONCOLOGY. - ISSN 2588-9311. - (2020), p. s2588. [10.1016/j.euo.2020.08.009]

Digital Biopsy with Fluorescence Confocal Microscope for Effective Real-time Diagnosis of Prostate Cancer: A Prospective, Comparative Study

Cimadamore, Alessia;Mazzucchelli, Roberta;Montironi, Rodolfo
2020-01-01

Abstract

A microscopic analysis of tissue is the gold standard for cancer detection. Hematoxylin-eosin (HE) for the reporting of prostate biopsy (PB) is conventionally based on fixation, processing, acquisition of glass slides, and analysis with an analog microscope by a local pathologist. Digitalization and real-time remote access to images could enhance the reporting process, and form the basis of artificial intelligence and machine learning. Fluorescence confocal microscopy (FCM), a novel optical technology, enables immediate digital image acquisition in an almost HE-like resolution without requiring conventional processing.
2020
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/290956
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