作者
Kelly Aubertin, Vincent Quoc Trinh, Michael Jermyn, Paul Baksic, Andrée‐Anne Grosset, Joannie Desroches, Karl St‐Arnaud, Mirela Birlea, Maria Claudia Vladoiu, Mathieu Latour, Roula Albadine, Fred Saad, Frédéric Leblond, Dominique Trudel
发表日期
2018/8
期刊
BJU international
卷号
122
期号
2
页码范围
326-336
简介
Objective
To test if Raman spectroscopy (RS) is an appropriate tool for the diagnosis and possibly grading of prostate cancer (PCa).
Patients and Methods
Between 20 and 50 Raman spectra were acquired from 32 fresh and non‐processed post‐prostatectomy specimens using a macroscopic handheld RS probe. Each measured area was characterized and categorized according to histopathological criteria: tissue type (extraprostatic or prostatic); tissue malignancy (benign or malignant); cancer grade (Grade Groups [GGs] 1–5); and tissue glandular level. The data were analysed using machine‐learning classification with neural network.
Results
The RS technique was able to distinguish prostate from extraprostatic tissue with a sensitivity of 82% and a specificity of 83% and benign from malignant tissue with a sensitivity of 87% and a specificity of 86%. In an exploratory fashion, RS differentiated benign from GG1 …
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K Aubertin, VQ Trinh, M Jermyn, P Baksic, AA Grosset… - BJU international, 2018