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Automatic Detection of Prostate Tumor Habitats using Diffusion MRI

A procedure for identification of optimal Apparent Diffusion Coefficient (ADC) thresholds for automatic delineation of prostatic lesions with restricted diffusion at differing risk for cancer was developed. The relationship between the size of the identified Volumes of Interest (VOIs) and Gleason Sc...

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Autores principales: Tschudi, Yohann, Pollack, Alan, Punnen, Sanoj, Ford, John C., Chang, Yu-Cherng, Soodana-Prakash, Nachiketh, Breto, Adrian L., Kwon, Deukwoo, Munera, Felipe, Abramowitz, Matthew C., Kryvenko, Oleksandr N., Stoyanova, Radka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6235961/
https://www.ncbi.nlm.nih.gov/pubmed/30429515
http://dx.doi.org/10.1038/s41598-018-34916-4
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author Tschudi, Yohann
Pollack, Alan
Punnen, Sanoj
Ford, John C.
Chang, Yu-Cherng
Soodana-Prakash, Nachiketh
Breto, Adrian L.
Kwon, Deukwoo
Munera, Felipe
Abramowitz, Matthew C.
Kryvenko, Oleksandr N.
Stoyanova, Radka
author_facet Tschudi, Yohann
Pollack, Alan
Punnen, Sanoj
Ford, John C.
Chang, Yu-Cherng
Soodana-Prakash, Nachiketh
Breto, Adrian L.
Kwon, Deukwoo
Munera, Felipe
Abramowitz, Matthew C.
Kryvenko, Oleksandr N.
Stoyanova, Radka
author_sort Tschudi, Yohann
collection PubMed
description A procedure for identification of optimal Apparent Diffusion Coefficient (ADC) thresholds for automatic delineation of prostatic lesions with restricted diffusion at differing risk for cancer was developed. The relationship between the size of the identified Volumes of Interest (VOIs) and Gleason Score (GS) was evaluated. Patients with multiparametric (mp)MRI, acquired prior to radical prostatectomy (RP) (n = 18), mpMRI-ultrasound fused (MRI-US) (n = 21) or template biopsies (n = 139) were analyzed. A search algorithm, spanning ADC thresholds in 50 µm(2)/s increments, determined VOIs that were matched to RP tumor nodules. Three ADC thresholds for both peripheral zone (PZ) and transition zone (TZ) were identified for estimation of VOIs at low, intermediate, and high risk of prostate cancer. The determined ADC thresholds for low, intermediate and high risk in PZ/TZ were: 900/800; 1100/850; and 1300/1050 µm(2)/s. The correlation coefficients between the size of the high/intermediate/low risk VOIs and GS in the three cohorts were 0.771/0.778/0.369, 0.561/0.457/0.355 and 0.423/0.441/0.36 (p < 0.05). Low risk VOIs mapped all RP lesions; area under the curve (AUC) for intermediate risk VOIs to discriminate GS6 vs GS ≥ 7 was 0.852; for high risk VOIs to discriminate GS6,7 vs GS ≥ 8 was 0.952. In conclusion, the automatically delineated volumes in the prostate with restricted diffusion were found to strongly correlate with cancer aggressiveness.
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spelling pubmed-62359612018-11-20 Automatic Detection of Prostate Tumor Habitats using Diffusion MRI Tschudi, Yohann Pollack, Alan Punnen, Sanoj Ford, John C. Chang, Yu-Cherng Soodana-Prakash, Nachiketh Breto, Adrian L. Kwon, Deukwoo Munera, Felipe Abramowitz, Matthew C. Kryvenko, Oleksandr N. Stoyanova, Radka Sci Rep Article A procedure for identification of optimal Apparent Diffusion Coefficient (ADC) thresholds for automatic delineation of prostatic lesions with restricted diffusion at differing risk for cancer was developed. The relationship between the size of the identified Volumes of Interest (VOIs) and Gleason Score (GS) was evaluated. Patients with multiparametric (mp)MRI, acquired prior to radical prostatectomy (RP) (n = 18), mpMRI-ultrasound fused (MRI-US) (n = 21) or template biopsies (n = 139) were analyzed. A search algorithm, spanning ADC thresholds in 50 µm(2)/s increments, determined VOIs that were matched to RP tumor nodules. Three ADC thresholds for both peripheral zone (PZ) and transition zone (TZ) were identified for estimation of VOIs at low, intermediate, and high risk of prostate cancer. The determined ADC thresholds for low, intermediate and high risk in PZ/TZ were: 900/800; 1100/850; and 1300/1050 µm(2)/s. The correlation coefficients between the size of the high/intermediate/low risk VOIs and GS in the three cohorts were 0.771/0.778/0.369, 0.561/0.457/0.355 and 0.423/0.441/0.36 (p < 0.05). Low risk VOIs mapped all RP lesions; area under the curve (AUC) for intermediate risk VOIs to discriminate GS6 vs GS ≥ 7 was 0.852; for high risk VOIs to discriminate GS6,7 vs GS ≥ 8 was 0.952. In conclusion, the automatically delineated volumes in the prostate with restricted diffusion were found to strongly correlate with cancer aggressiveness. Nature Publishing Group UK 2018-11-14 /pmc/articles/PMC6235961/ /pubmed/30429515 http://dx.doi.org/10.1038/s41598-018-34916-4 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Tschudi, Yohann
Pollack, Alan
Punnen, Sanoj
Ford, John C.
Chang, Yu-Cherng
Soodana-Prakash, Nachiketh
Breto, Adrian L.
Kwon, Deukwoo
Munera, Felipe
Abramowitz, Matthew C.
Kryvenko, Oleksandr N.
Stoyanova, Radka
Automatic Detection of Prostate Tumor Habitats using Diffusion MRI
title Automatic Detection of Prostate Tumor Habitats using Diffusion MRI
title_full Automatic Detection of Prostate Tumor Habitats using Diffusion MRI
title_fullStr Automatic Detection of Prostate Tumor Habitats using Diffusion MRI
title_full_unstemmed Automatic Detection of Prostate Tumor Habitats using Diffusion MRI
title_short Automatic Detection of Prostate Tumor Habitats using Diffusion MRI
title_sort automatic detection of prostate tumor habitats using diffusion mri
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6235961/
https://www.ncbi.nlm.nih.gov/pubmed/30429515
http://dx.doi.org/10.1038/s41598-018-34916-4
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