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Raman spectroscopy system for real-time diagnosis of clinically significant prostate cancer tissue.
van 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.
Afiliação
  • van Breugel SJ; The Photon Factory, University of Auckland, Auckland, New Zealand.
  • Low I; School of Chemical Sciences, University of Auckland, Auckland, New Zealand.
  • Christie ML; The Dodd-Walls Centre for Photonic and Quantum Technologies, University of Otago, Dunedin, New Zealand.
  • Pokorny MR; Counties Manukau District Healthboard, Auckland, New Zealand.
  • Nagarajan R; Counties Manukau District Healthboard, Auckland, New Zealand.
  • Holtkamp HU; Counties Manukau District Healthboard, Auckland, New Zealand.
  • Srinivasa K; Auckland District Healthboard, Auckland, New Zealand.
  • Amirapu S; Counties Manukau District Healthboard, Auckland, New Zealand.
  • Nieuwoudt MK; Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.
  • Simpson MC; The Photon Factory, University of Auckland, Auckland, New Zealand.
  • Zargar-Shoshtari K; School of Chemical Sciences, University of Auckland, Auckland, New Zealand.
  • Aguergaray C; Auckland District Healthboard, Auckland, New Zealand.
J Biophotonics ; 16(5): e202200334, 2023 05.
Article em En | MEDLINE | ID: mdl-36715344
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Próstata / Análise Espectral Raman Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Próstata / Análise Espectral Raman Idioma: En Ano de publicação: 2023 Tipo de documento: Article