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Image-guided Raman spectroscopy navigation system to improve transperineal prostate cancer detection. Part 2: in-vivo tumor-targeting using a classification model combining spectral and MRI-radiomics features
SIGNIFICANCE: The diagnosis and treatment of prostate cancer (PCa) are limited by a lack of intraoperative information to accurately target tumors with needles for biopsy and brachytherapy. An innovative image-guidance technique using optical devices could improve the diagnostic yield of biopsy and...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Society of Photo-Optical Instrumentation Engineers
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9459023/ https://www.ncbi.nlm.nih.gov/pubmed/36085571 http://dx.doi.org/10.1117/1.JBO.27.9.095004 |
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author | Grajales, David Picot, Fabien Shams, Roozbeh Dallaire, Frédérick Sheehy, Guillaume Alley, Stephanie Barkati, Maroie Delouya, Guila Carrier, Jean-Francois Birlea, Mirela Trudel, Dominique Leblond, Frédéric Ménard, Cynthia Kadoury, Samuel |
author_facet | Grajales, David Picot, Fabien Shams, Roozbeh Dallaire, Frédérick Sheehy, Guillaume Alley, Stephanie Barkati, Maroie Delouya, Guila Carrier, Jean-Francois Birlea, Mirela Trudel, Dominique Leblond, Frédéric Ménard, Cynthia Kadoury, Samuel |
author_sort | Grajales, David |
collection | PubMed |
description | SIGNIFICANCE: The diagnosis and treatment of prostate cancer (PCa) are limited by a lack of intraoperative information to accurately target tumors with needles for biopsy and brachytherapy. An innovative image-guidance technique using optical devices could improve the diagnostic yield of biopsy and efficacy of radiotherapy. AIM: To evaluate the performance of multimodal PCa detection using biomolecular features from in-situ Raman spectroscopy (RS) combined with image-based (radiomics) features from multiparametric magnetic resonance images (mpMRI). APPROACH: In a prospective pilot clinical study, 18 patients were recruited and underwent high-dose-rate brachytherapy. Multimodality image fusion (preoperative mpMRI with intraoperative transrectal ultrasound) combined with electromagnetic tracking was used to navigate an RS needle in the prostate prior to brachytherapy. This resulting dataset consisted of Raman spectra and co-located radiomics features from mpMRI. Feature selection was performed with the constraint that no more than 10 features were retained overall from a combination of inelastic scattering spectra and radiomics. These features were used to train support vector machine classifiers for PCa detection based on leave-one-patient-out cross-validation. RESULTS: RS along with biopsy samples were acquired from 47 sites along the insertion trajectory of the fiber-optics needle: 26 were confirmed as benign or grade [Formula: see text] , and 21 as grade group [Formula: see text] , according to histopathological reports. The combination of the fingerprint region of the RS and radiomics showed an accuracy of 83% ([Formula: see text] and a [Formula: see text]), outperforming by more than 9% models trained with either spectroscopic or mpMRI data alone. An optimal number of features was identified between 6 and 8 features, which have good potential for discriminating grade group [Formula: see text] [Formula: see text] ([Formula: see text]) or grade group [Formula: see text] [Formula: see text] ([Formula: see text]). CONCLUSIONS: In-situ Raman spectroscopy combined with mpMRI radiomics features can lead to highly accurate PCa detection for improved in-vivo targeting of biopsy sample collection and radiotherapy seed placement. |
format | Online Article Text |
id | pubmed-9459023 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Society of Photo-Optical Instrumentation Engineers |
record_format | MEDLINE/PubMed |
spelling | pubmed-94590232022-09-13 Image-guided Raman spectroscopy navigation system to improve transperineal prostate cancer detection. Part 2: in-vivo tumor-targeting using a classification model combining spectral and MRI-radiomics features Grajales, David Picot, Fabien Shams, Roozbeh Dallaire, Frédérick Sheehy, Guillaume Alley, Stephanie Barkati, Maroie Delouya, Guila Carrier, Jean-Francois Birlea, Mirela Trudel, Dominique Leblond, Frédéric Ménard, Cynthia Kadoury, Samuel J Biomed Opt General SIGNIFICANCE: The diagnosis and treatment of prostate cancer (PCa) are limited by a lack of intraoperative information to accurately target tumors with needles for biopsy and brachytherapy. An innovative image-guidance technique using optical devices could improve the diagnostic yield of biopsy and efficacy of radiotherapy. AIM: To evaluate the performance of multimodal PCa detection using biomolecular features from in-situ Raman spectroscopy (RS) combined with image-based (radiomics) features from multiparametric magnetic resonance images (mpMRI). APPROACH: In a prospective pilot clinical study, 18 patients were recruited and underwent high-dose-rate brachytherapy. Multimodality image fusion (preoperative mpMRI with intraoperative transrectal ultrasound) combined with electromagnetic tracking was used to navigate an RS needle in the prostate prior to brachytherapy. This resulting dataset consisted of Raman spectra and co-located radiomics features from mpMRI. Feature selection was performed with the constraint that no more than 10 features were retained overall from a combination of inelastic scattering spectra and radiomics. These features were used to train support vector machine classifiers for PCa detection based on leave-one-patient-out cross-validation. RESULTS: RS along with biopsy samples were acquired from 47 sites along the insertion trajectory of the fiber-optics needle: 26 were confirmed as benign or grade [Formula: see text] , and 21 as grade group [Formula: see text] , according to histopathological reports. The combination of the fingerprint region of the RS and radiomics showed an accuracy of 83% ([Formula: see text] and a [Formula: see text]), outperforming by more than 9% models trained with either spectroscopic or mpMRI data alone. An optimal number of features was identified between 6 and 8 features, which have good potential for discriminating grade group [Formula: see text] [Formula: see text] ([Formula: see text]) or grade group [Formula: see text] [Formula: see text] ([Formula: see text]). CONCLUSIONS: In-situ Raman spectroscopy combined with mpMRI radiomics features can lead to highly accurate PCa detection for improved in-vivo targeting of biopsy sample collection and radiotherapy seed placement. Society of Photo-Optical Instrumentation Engineers 2022-09-09 2022-09 /pmc/articles/PMC9459023/ /pubmed/36085571 http://dx.doi.org/10.1117/1.JBO.27.9.095004 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. |
spellingShingle | General Grajales, David Picot, Fabien Shams, Roozbeh Dallaire, Frédérick Sheehy, Guillaume Alley, Stephanie Barkati, Maroie Delouya, Guila Carrier, Jean-Francois Birlea, Mirela Trudel, Dominique Leblond, Frédéric Ménard, Cynthia Kadoury, Samuel Image-guided Raman spectroscopy navigation system to improve transperineal prostate cancer detection. Part 2: in-vivo tumor-targeting using a classification model combining spectral and MRI-radiomics features |
title | Image-guided Raman spectroscopy navigation system to improve transperineal prostate cancer detection. Part 2: in-vivo tumor-targeting using a classification model combining spectral and MRI-radiomics features |
title_full | Image-guided Raman spectroscopy navigation system to improve transperineal prostate cancer detection. Part 2: in-vivo tumor-targeting using a classification model combining spectral and MRI-radiomics features |
title_fullStr | Image-guided Raman spectroscopy navigation system to improve transperineal prostate cancer detection. Part 2: in-vivo tumor-targeting using a classification model combining spectral and MRI-radiomics features |
title_full_unstemmed | Image-guided Raman spectroscopy navigation system to improve transperineal prostate cancer detection. Part 2: in-vivo tumor-targeting using a classification model combining spectral and MRI-radiomics features |
title_short | Image-guided Raman spectroscopy navigation system to improve transperineal prostate cancer detection. Part 2: in-vivo tumor-targeting using a classification model combining spectral and MRI-radiomics features |
title_sort | image-guided raman spectroscopy navigation system to improve transperineal prostate cancer detection. part 2: in-vivo tumor-targeting using a classification model combining spectral and mri-radiomics features |
topic | General |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9459023/ https://www.ncbi.nlm.nih.gov/pubmed/36085571 http://dx.doi.org/10.1117/1.JBO.27.9.095004 |
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