Raman spectroscopy system for real‐time diagnosis of clinically significant prostate cancer tissue

Prostate cancer (PCa) is a significant healthcare problem worldwide. Current diagnosis and treatment methods are limited by a lack of precise in vivo tissue analysis methods. Real‐time cancer identification and grading could dramatically improve current protocols. Here, we report the testing of a th...

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Veröffentlicht in:Journal of biophotonics 2023-05, Vol.16 (5), p.e202200334-n/a
Hauptverfasser: Breugel, Suse J., Low, Irene, Christie, Mary L., Pokorny, Morgan R., Nagarajan, Ramya, Holtkamp, Hannah U., Srinivasa, Komal, Amirapu, Satya, Nieuwoudt, Michel K., Simpson, M. Cather, Zargar‐Shoshtari, Kamran, Aguergaray, Claude
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Sprache:eng
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Zusammenfassung:Prostate cancer (PCa) is a significant healthcare problem worldwide. Current diagnosis and treatment methods are limited by a lack of precise in vivo tissue analysis methods. Real‐time cancer identification and grading could dramatically improve current protocols. Here, we report the testing of a thin optical probe using Raman spectroscopy (RS) and classification methods to detect and grade PCa accurately in real‐time. We present the first clinical trial on fresh ex vivo biopsy cores from an 84 patient cohort. Findings from 2395 spectra measured on 599 biopsy cores show high accuracy for diagnosing and grading PCa. We can detect clinically significant PCa from benign and clinically insignificant PCa with 90% sensitivity and 80.2% specificity. We also demonstrate the ability to differentiate cancer grades with 90% sensitivity and specificity ≥82.8%. This work demonstrates the utility of RS for real‐time PCa detection and grading during routine transrectal biopsy appointments. Development of a new technology to help prostate cancer (PCa) detection and treatment become less invasive and more effective. Current detection methods involve invasive and expensive tools, leading men to avoid diagnosis due to discomfort and stigma around the techniques known to miss early‐stage signs of PCa. We use a custom‐made thin probe and Raman spectroscopy to diagnose and grade PCa accurately in real‐time. We report herein results from a clinical trial on the largest cohort to date.
ISSN:1864-063X
1864-0648
DOI:10.1002/jbio.202200334