Impact of the integration of proton magnetic resonance imaging spectroscopy to PI-RADS 2 for prediction of high grade and high stage prostate cancer
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Radiologia Brasileira (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-39842017000500299 |
Resumo: | Abstract Objective: To compare the predictions of dominant Gleason pattern ≥ 4 or non-organ confined disease with Prostate Imaging Reporting and Data System (PI-RADS v2) with or without proton magnetic resonance spectroscopic imaging (1H-MRSI). Materials and Methods: Thirty-nine men underwent 3-tesla endorectal multiparametric MRI including 1H-MRSI and prostatectomy. Two radiologists assigned PI-RADS v2 and 1H-MRSI scores to index lesions. Statistical analyses used logistic regressions, receiver operating characteristic (ROC) curves, and 2x2 tables for diagnostic accuracies. Results: The sensitivity and specificity of 1H-MRSI and PI-RADS v2 for high-grade prostate cancer (PCa) were 85.7% (57.1%) and 92.9% (100%), and 56% (68.0%) and 24.0% (24.0%). The sensitivity and specificity of 1H-MRSI and PI-RADS v2 for extra-prostatic extension (EPE) were 64.0% (40%) and 20.0% (48%), and 50.0% (57.1%) and 71.4% (64.3%). The area under the ROC curves (AUC) for prediction of high-grade prostate cancer were 0.65 and 0.61 for PI-RADS v2 and 0.72 and 0.70 when combined with 1H-MRSI (readers 1 and 2, p = 0.04 and 0.21). For prediction of EPE the AUC were 0.54 and 0.60 for PI-RADS v2 and 0.55 and 0.61 when combined with 1H-MRSI (p > 0.05). Conclusion: 1H-MRSI might improve the discrimination of high-grade prostate cancer when combined to PI-RADS v2, particularly for PI-RADS v2 score 4 lesions, but it does not affect the prediction of EPE. |
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Radiologia Brasileira (Online) |
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Impact of the integration of proton magnetic resonance imaging spectroscopy to PI-RADS 2 for prediction of high grade and high stage prostate cancerMRISpectroscopyDiagnosisProstate cancerProstatectomyAbstract Objective: To compare the predictions of dominant Gleason pattern ≥ 4 or non-organ confined disease with Prostate Imaging Reporting and Data System (PI-RADS v2) with or without proton magnetic resonance spectroscopic imaging (1H-MRSI). Materials and Methods: Thirty-nine men underwent 3-tesla endorectal multiparametric MRI including 1H-MRSI and prostatectomy. Two radiologists assigned PI-RADS v2 and 1H-MRSI scores to index lesions. Statistical analyses used logistic regressions, receiver operating characteristic (ROC) curves, and 2x2 tables for diagnostic accuracies. Results: The sensitivity and specificity of 1H-MRSI and PI-RADS v2 for high-grade prostate cancer (PCa) were 85.7% (57.1%) and 92.9% (100%), and 56% (68.0%) and 24.0% (24.0%). The sensitivity and specificity of 1H-MRSI and PI-RADS v2 for extra-prostatic extension (EPE) were 64.0% (40%) and 20.0% (48%), and 50.0% (57.1%) and 71.4% (64.3%). The area under the ROC curves (AUC) for prediction of high-grade prostate cancer were 0.65 and 0.61 for PI-RADS v2 and 0.72 and 0.70 when combined with 1H-MRSI (readers 1 and 2, p = 0.04 and 0.21). For prediction of EPE the AUC were 0.54 and 0.60 for PI-RADS v2 and 0.55 and 0.61 when combined with 1H-MRSI (p > 0.05). Conclusion: 1H-MRSI might improve the discrimination of high-grade prostate cancer when combined to PI-RADS v2, particularly for PI-RADS v2 score 4 lesions, but it does not affect the prediction of EPE.Publicação do Colégio Brasileiro de Radiologia e Diagnóstico por Imagem2017-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-39842017000500299Radiologia Brasileira v.50 n.5 2017reponame:Radiologia Brasileira (Online)instname:Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR)instacron:CBR10.1590/0100-3984.2016.0117info:eu-repo/semantics/openAccessLeapman,Michael S.Wang,Zhen J.Behr,Spencer C.Kurhanewicz,JohnZagoria,Ronald J.Carroll,Peter R.Westphalen,Antonio C.eng2017-10-30T00:00:00Zoai:scielo:S0100-39842017000500299Revistahttps://www.scielo.br/j/rb/https://old.scielo.br/oai/scielo-oai.phpradiologiabrasileira@cbr.org.br1678-70990100-3984opendoar:2017-10-30T00:00Radiologia Brasileira (Online) - Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR)false |
dc.title.none.fl_str_mv |
Impact of the integration of proton magnetic resonance imaging spectroscopy to PI-RADS 2 for prediction of high grade and high stage prostate cancer |
title |
Impact of the integration of proton magnetic resonance imaging spectroscopy to PI-RADS 2 for prediction of high grade and high stage prostate cancer |
spellingShingle |
Impact of the integration of proton magnetic resonance imaging spectroscopy to PI-RADS 2 for prediction of high grade and high stage prostate cancer Leapman,Michael S. MRI Spectroscopy Diagnosis Prostate cancer Prostatectomy |
title_short |
Impact of the integration of proton magnetic resonance imaging spectroscopy to PI-RADS 2 for prediction of high grade and high stage prostate cancer |
title_full |
Impact of the integration of proton magnetic resonance imaging spectroscopy to PI-RADS 2 for prediction of high grade and high stage prostate cancer |
title_fullStr |
Impact of the integration of proton magnetic resonance imaging spectroscopy to PI-RADS 2 for prediction of high grade and high stage prostate cancer |
title_full_unstemmed |
Impact of the integration of proton magnetic resonance imaging spectroscopy to PI-RADS 2 for prediction of high grade and high stage prostate cancer |
title_sort |
Impact of the integration of proton magnetic resonance imaging spectroscopy to PI-RADS 2 for prediction of high grade and high stage prostate cancer |
author |
Leapman,Michael S. |
author_facet |
Leapman,Michael S. Wang,Zhen J. Behr,Spencer C. Kurhanewicz,John Zagoria,Ronald J. Carroll,Peter R. Westphalen,Antonio C. |
author_role |
author |
author2 |
Wang,Zhen J. Behr,Spencer C. Kurhanewicz,John Zagoria,Ronald J. Carroll,Peter R. Westphalen,Antonio C. |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Leapman,Michael S. Wang,Zhen J. Behr,Spencer C. Kurhanewicz,John Zagoria,Ronald J. Carroll,Peter R. Westphalen,Antonio C. |
dc.subject.por.fl_str_mv |
MRI Spectroscopy Diagnosis Prostate cancer Prostatectomy |
topic |
MRI Spectroscopy Diagnosis Prostate cancer Prostatectomy |
description |
Abstract Objective: To compare the predictions of dominant Gleason pattern ≥ 4 or non-organ confined disease with Prostate Imaging Reporting and Data System (PI-RADS v2) with or without proton magnetic resonance spectroscopic imaging (1H-MRSI). Materials and Methods: Thirty-nine men underwent 3-tesla endorectal multiparametric MRI including 1H-MRSI and prostatectomy. Two radiologists assigned PI-RADS v2 and 1H-MRSI scores to index lesions. Statistical analyses used logistic regressions, receiver operating characteristic (ROC) curves, and 2x2 tables for diagnostic accuracies. Results: The sensitivity and specificity of 1H-MRSI and PI-RADS v2 for high-grade prostate cancer (PCa) were 85.7% (57.1%) and 92.9% (100%), and 56% (68.0%) and 24.0% (24.0%). The sensitivity and specificity of 1H-MRSI and PI-RADS v2 for extra-prostatic extension (EPE) were 64.0% (40%) and 20.0% (48%), and 50.0% (57.1%) and 71.4% (64.3%). The area under the ROC curves (AUC) for prediction of high-grade prostate cancer were 0.65 and 0.61 for PI-RADS v2 and 0.72 and 0.70 when combined with 1H-MRSI (readers 1 and 2, p = 0.04 and 0.21). For prediction of EPE the AUC were 0.54 and 0.60 for PI-RADS v2 and 0.55 and 0.61 when combined with 1H-MRSI (p > 0.05). Conclusion: 1H-MRSI might improve the discrimination of high-grade prostate cancer when combined to PI-RADS v2, particularly for PI-RADS v2 score 4 lesions, but it does not affect the prediction of EPE. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-10-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-39842017000500299 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-39842017000500299 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0100-3984.2016.0117 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Publicação do Colégio Brasileiro de Radiologia e Diagnóstico por Imagem |
publisher.none.fl_str_mv |
Publicação do Colégio Brasileiro de Radiologia e Diagnóstico por Imagem |
dc.source.none.fl_str_mv |
Radiologia Brasileira v.50 n.5 2017 reponame:Radiologia Brasileira (Online) instname:Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR) instacron:CBR |
instname_str |
Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR) |
instacron_str |
CBR |
institution |
CBR |
reponame_str |
Radiologia Brasileira (Online) |
collection |
Radiologia Brasileira (Online) |
repository.name.fl_str_mv |
Radiologia Brasileira (Online) - Colégio Brasileiro de Radiologia e Diagnóstico por Imagem (CBR) |
repository.mail.fl_str_mv |
radiologiabrasileira@cbr.org.br |
_version_ |
1754208939394727936 |