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The feasibility of multimodal fiber optic spectroscopy analysis in bladder cancer detection, grading, and staging.
Morselli, Simone; Baria, Enrico; Cicchi, Riccardo; Liaci, Andrea; Sebastianelli, Arcangelo; Nesi, Gabriella; Serni, Sergio; Pavone, Francesco Saverio; Gacci, Mauro.
  • Morselli S; Unit of Minimally Invasive and Robotic Urologic Surgery and Kidney Transplantation, Careggi University Hospital, Florence, Italy.
  • Baria E; Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
  • Cicchi R; European Laboratory for Non-Linear Spectroscopy, University of Florence, Sesto Fiorentino, Italy.
  • Liaci A; European Laboratory for Non-Linear Spectroscopy, University of Florence, Sesto Fiorentino, Italy.
  • Sebastianelli A; National Institute of Optics, National Research Council, Sesto Fiorentino, Italy.
  • Nesi G; Unit of Minimally Invasive and Robotic Urologic Surgery and Kidney Transplantation, Careggi University Hospital, Florence, Italy.
  • Serni S; Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
  • Pavone FS; Unit of Minimally Invasive and Robotic Urologic Surgery and Kidney Transplantation, Careggi University Hospital, Florence, Italy.
  • Gacci M; Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
Urologia ; 88(4): 306-314, 2021 Nov.
Article en En | MEDLINE | ID: mdl-33789562
ABSTRACT

OBJECTIVE:

To prove the feasibility of Multimodal Fiber Optic Spectroscopy (MFOS) analysis in bladder cancer (BCa) detection, grading, and staging. MATERIALS AND

METHODS:

Bladder specimens from patients underwent TURBT or TURP were recorded and analyzed with MFOS within 30 min from excision. In detail, our MFOS combined fluorescence, Raman spectroscopy, and diffuse reflectance. We used these optical techniques to collect spectra from bladder biopsies, then we compared the obtained results to gold standard pathological analysis. Finally, we developed a classification algorithm based on principal component analysis-linear discriminant analysis.

RESULTS:

A total of 169 specimens were collected and analyzed from 114 patients, 40 (23.7%) healthy (from TURP), and 129 (76.3%) with BCa. BCa specimens were divided according to their grade-34 (26.4%) low grade (LG) and 95 (73.6%) high grade (HG) BCa-and stage-64 (49.6%) Ta, 45 (34.9%) T1, and 20 (15.5%) T2. MFOS-based classification algorithm correctly discriminated healthy versus BCa with 90% accuracy, HG versus LG with 83% accuracy. Furthermore, it assessed tumor stage with 75% accuracy for Ta versus T1, 85% for T1 versus T2, and 86% for Ta versus T2.

CONCLUSIONS:

Our preliminary results suggest that MFOS could be a reliable, fast, and label-free tool for BCa assessment, providing also grading and staging information. This technique could be applied in future for in vivo inspection as well as of ex vivo tissue biopsies. Thus, MFOS might improve urothelial cancer management. Further studies are required.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias de la Vejiga Urinaria Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Año: 2021 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias de la Vejiga Urinaria Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Año: 2021 Tipo del documento: Article