The impact of multiparametric MRI features to identify the presence of prevalent cribriform pattern in the peripheral zone tumors

Purpose To assess the role of the multiparametric Magnetic Resonance Imaging (mpMRI) in predicting the cribriform pattern in both the peripheral and transition zones (PZ and TZ) clinically significant prostate cancers (csPCas). Material and methods We retrospectively evaluated 150 patients who under...

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Published in:	Radiologia medica Vol. 127; no. 2; pp. 174 - 182
Main Authors:	Gaudiano, Caterina, Bianchi, Lorenzo, De Cinque, Antonio, Corcioni, Beniamino, Giunchi, Francesca, Schiavina, Riccardo, Fiorentino, Michelangelo, Brunocilla, Eugenio, Golfieri, Rita
Format:	Journal Article
Language:	English
Published:	Milan Springer Milan 01.02.2022 Springer Nature B.V
Subjects:	Aged Diagnostic Imaging in Oncology Diagnostic Radiology Diffusion coefficient Evaluation Humans Imaging Interventional Radiology Lesions Magnetic resonance imaging Male Medicine Medicine & Public Health Middle Aged Multiparametric Magnetic Resonance Imaging - methods Multivariate analysis Neuroradiology Parameter identification Prostate - diagnostic imaging Prostate - pathology Prostate - surgery Prostatectomy Prostatic Neoplasms - diagnostic imaging Prostatic Neoplasms - pathology Prostatic Neoplasms - surgery Radiology Retrospective Studies Tumors Ultrasound Multiparametric magnetic resonance imaging PI-RADS version 2.1 Prostate cancer Cribriform pattern Gleason Pattern
ISSN:	0033-8362, 1826-6983, 1826-6983
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Abstract	Purpose To assess the role of the multiparametric Magnetic Resonance Imaging (mpMRI) in predicting the cribriform pattern in both the peripheral and transition zones (PZ and TZ) clinically significant prostate cancers (csPCas). Material and methods We retrospectively evaluated 150 patients who underwent radical prostatectomy for csPCa and preoperative mpMRI. Patients with negative ( n = 25) and positive ( n = 125) mpMRI, stratified according to the presence of prevalent cribriform pattern (PCP, ≥ 50%) and non-PCP (< 50%) at specimen, were included. Difference between the two groups were evaluated. Multivariate logistic regression was used to identify predictors of PCP among mpMRI parameters. The receiver operating characteristic (ROC) analysis was performed to evaluate the area under the curve (AUC) of apparent diffusion coefficient (ADC) and ADC ratio in detecting lesions harboring PCP. Results Considering 135 positive lesions at the mpMRI, 30 (22.2%) and 105 (77.8%) harbored PCP and non-PCP PCa. The PCP lesions had more frequently nodular morphology (83.3% vs 62.9%; p = 0.04) and significantly lower mean ADC value (0.87 ± 0.16 vs 0.95 ± 0.18; p = 0.03) and ADC ratio (0.52 ± 0.09 vs 0.60 ± 0.14; p = 0.003) when compared with non-PCP lesions. At univariate and multivariate analyses, mean ADC and ADC ratio resulted as independent predictors of the presence of the PCP of the PZ tumors(OR: 0.025; p = 0.03 and OR: 0.001; p = 0.004, respectively). At the ROC analysis, the AUC of mean ADC and ADC ratio to predict the presence of PCP in patients with PZ suspicious lesion at the mpMRI were 0.69 (95% CI 0.56–0.81P, p = 0.003) and 0.72 (95% CI 0.62–0.82P, p = 0.001), respectively. Conclusions The mpMRI may correctly identify PCP tumors of the PZ and the mean ADC value and ADC ratio can predict the presence of the cribriform pattern in the PCa.
AbstractList	Purpose To assess the role of the multiparametric Magnetic Resonance Imaging (mpMRI) in predicting the cribriform pattern in both the peripheral and transition zones (PZ and TZ) clinically significant prostate cancers (csPCas). Material and methods We retrospectively evaluated 150 patients who underwent radical prostatectomy for csPCa and preoperative mpMRI. Patients with negative ( n = 25) and positive ( n = 125) mpMRI, stratified according to the presence of prevalent cribriform pattern (PCP, ≥ 50%) and non-PCP (< 50%) at specimen, were included. Difference between the two groups were evaluated. Multivariate logistic regression was used to identify predictors of PCP among mpMRI parameters. The receiver operating characteristic (ROC) analysis was performed to evaluate the area under the curve (AUC) of apparent diffusion coefficient (ADC) and ADC ratio in detecting lesions harboring PCP. Results Considering 135 positive lesions at the mpMRI, 30 (22.2%) and 105 (77.8%) harbored PCP and non-PCP PCa. The PCP lesions had more frequently nodular morphology (83.3% vs 62.9%; p = 0.04) and significantly lower mean ADC value (0.87 ± 0.16 vs 0.95 ± 0.18; p = 0.03) and ADC ratio (0.52 ± 0.09 vs 0.60 ± 0.14; p = 0.003) when compared with non-PCP lesions. At univariate and multivariate analyses, mean ADC and ADC ratio resulted as independent predictors of the presence of the PCP of the PZ tumors(OR: 0.025; p = 0.03 and OR: 0.001; p = 0.004, respectively). At the ROC analysis, the AUC of mean ADC and ADC ratio to predict the presence of PCP in patients with PZ suspicious lesion at the mpMRI were 0.69 (95% CI 0.56–0.81P, p = 0.003) and 0.72 (95% CI 0.62–0.82P, p = 0.001), respectively. Conclusions The mpMRI may correctly identify PCP tumors of the PZ and the mean ADC value and ADC ratio can predict the presence of the cribriform pattern in the PCa. To assess the role of the multiparametric Magnetic Resonance Imaging (mpMRI) in predicting the cribriform pattern in both the peripheral and transition zones (PZ and TZ) clinically significant prostate cancers (csPCas).PURPOSETo assess the role of the multiparametric Magnetic Resonance Imaging (mpMRI) in predicting the cribriform pattern in both the peripheral and transition zones (PZ and TZ) clinically significant prostate cancers (csPCas).We retrospectively evaluated 150 patients who underwent radical prostatectomy for csPCa and preoperative mpMRI. Patients with negative (n = 25) and positive (n = 125) mpMRI, stratified according to the presence of prevalent cribriform pattern (PCP, ≥ 50%) and non-PCP (< 50%) at specimen, were included. Difference between the two groups were evaluated. Multivariate logistic regression was used to identify predictors of PCP among mpMRI parameters. The receiver operating characteristic (ROC) analysis was performed to evaluate the area under the curve (AUC) of apparent diffusion coefficient (ADC) and ADC ratio in detecting lesions harboring PCP.MATERIAL AND METHODSWe retrospectively evaluated 150 patients who underwent radical prostatectomy for csPCa and preoperative mpMRI. Patients with negative (n = 25) and positive (n = 125) mpMRI, stratified according to the presence of prevalent cribriform pattern (PCP, ≥ 50%) and non-PCP (< 50%) at specimen, were included. Difference between the two groups were evaluated. Multivariate logistic regression was used to identify predictors of PCP among mpMRI parameters. The receiver operating characteristic (ROC) analysis was performed to evaluate the area under the curve (AUC) of apparent diffusion coefficient (ADC) and ADC ratio in detecting lesions harboring PCP.Considering 135 positive lesions at the mpMRI, 30 (22.2%) and 105 (77.8%) harbored PCP and non-PCP PCa. The PCP lesions had more frequently nodular morphology (83.3% vs 62.9%; p = 0.04) and significantly lower mean ADC value (0.87 ± 0.16 vs 0.95 ± 0.18; p = 0.03) and ADC ratio (0.52 ± 0.09 vs 0.60 ± 0.14; p = 0.003) when compared with non-PCP lesions. At univariate and multivariate analyses, mean ADC and ADC ratio resulted as independent predictors of the presence of the PCP of the PZ tumors(OR: 0.025; p = 0.03 and OR: 0.001; p = 0.004, respectively). At the ROC analysis, the AUC of mean ADC and ADC ratio to predict the presence of PCP in patients with PZ suspicious lesion at the mpMRI were 0.69 (95% CI 0.56-0.81P, p = 0.003) and 0.72 (95% CI 0.62-0.82P, p = 0.001), respectively.RESULTSConsidering 135 positive lesions at the mpMRI, 30 (22.2%) and 105 (77.8%) harbored PCP and non-PCP PCa. The PCP lesions had more frequently nodular morphology (83.3% vs 62.9%; p = 0.04) and significantly lower mean ADC value (0.87 ± 0.16 vs 0.95 ± 0.18; p = 0.03) and ADC ratio (0.52 ± 0.09 vs 0.60 ± 0.14; p = 0.003) when compared with non-PCP lesions. At univariate and multivariate analyses, mean ADC and ADC ratio resulted as independent predictors of the presence of the PCP of the PZ tumors(OR: 0.025; p = 0.03 and OR: 0.001; p = 0.004, respectively). At the ROC analysis, the AUC of mean ADC and ADC ratio to predict the presence of PCP in patients with PZ suspicious lesion at the mpMRI were 0.69 (95% CI 0.56-0.81P, p = 0.003) and 0.72 (95% CI 0.62-0.82P, p = 0.001), respectively.The mpMRI may correctly identify PCP tumors of the PZ and the mean ADC value and ADC ratio can predict the presence of the cribriform pattern in the PCa.CONCLUSIONSThe mpMRI may correctly identify PCP tumors of the PZ and the mean ADC value and ADC ratio can predict the presence of the cribriform pattern in the PCa. PurposeTo assess the role of the multiparametric Magnetic Resonance Imaging (mpMRI) in predicting the cribriform pattern in both the peripheral and transition zones (PZ and TZ) clinically significant prostate cancers (csPCas).Material and methodsWe retrospectively evaluated 150 patients who underwent radical prostatectomy for csPCa and preoperative mpMRI. Patients with negative (n = 25) and positive (n = 125) mpMRI, stratified according to the presence of prevalent cribriform pattern (PCP, ≥ 50%) and non-PCP (< 50%) at specimen, were included. Difference between the two groups were evaluated. Multivariate logistic regression was used to identify predictors of PCP among mpMRI parameters. The receiver operating characteristic (ROC) analysis was performed to evaluate the area under the curve (AUC) of apparent diffusion coefficient (ADC) and ADC ratio in detecting lesions harboring PCP.ResultsConsidering 135 positive lesions at the mpMRI, 30 (22.2%) and 105 (77.8%) harbored PCP and non-PCP PCa. The PCP lesions had more frequently nodular morphology (83.3% vs 62.9%; p = 0.04) and significantly lower mean ADC value (0.87 ± 0.16 vs 0.95 ± 0.18; p = 0.03) and ADC ratio (0.52 ± 0.09 vs 0.60 ± 0.14; p = 0.003) when compared with non-PCP lesions. At univariate and multivariate analyses, mean ADC and ADC ratio resulted as independent predictors of the presence of the PCP of the PZ tumors(OR: 0.025; p = 0.03 and OR: 0.001; p = 0.004, respectively). At the ROC analysis, the AUC of mean ADC and ADC ratio to predict the presence of PCP in patients with PZ suspicious lesion at the mpMRI were 0.69 (95% CI 0.56–0.81P, p = 0.003) and 0.72 (95% CI 0.62–0.82P, p = 0.001), respectively.ConclusionsThe mpMRI may correctly identify PCP tumors of the PZ and the mean ADC value and ADC ratio can predict the presence of the cribriform pattern in the PCa. To assess the role of the multiparametric Magnetic Resonance Imaging (mpMRI) in predicting the cribriform pattern in both the peripheral and transition zones (PZ and TZ) clinically significant prostate cancers (csPCas). We retrospectively evaluated 150 patients who underwent radical prostatectomy for csPCa and preoperative mpMRI. Patients with negative (n = 25) and positive (n = 125) mpMRI, stratified according to the presence of prevalent cribriform pattern (PCP, ≥ 50%) and non-PCP (< 50%) at specimen, were included. Difference between the two groups were evaluated. Multivariate logistic regression was used to identify predictors of PCP among mpMRI parameters. The receiver operating characteristic (ROC) analysis was performed to evaluate the area under the curve (AUC) of apparent diffusion coefficient (ADC) and ADC ratio in detecting lesions harboring PCP. Considering 135 positive lesions at the mpMRI, 30 (22.2%) and 105 (77.8%) harbored PCP and non-PCP PCa. The PCP lesions had more frequently nodular morphology (83.3% vs 62.9%; p = 0.04) and significantly lower mean ADC value (0.87 ± 0.16 vs 0.95 ± 0.18; p = 0.03) and ADC ratio (0.52 ± 0.09 vs 0.60 ± 0.14; p = 0.003) when compared with non-PCP lesions. At univariate and multivariate analyses, mean ADC and ADC ratio resulted as independent predictors of the presence of the PCP of the PZ tumors(OR: 0.025; p = 0.03 and OR: 0.001; p = 0.004, respectively). At the ROC analysis, the AUC of mean ADC and ADC ratio to predict the presence of PCP in patients with PZ suspicious lesion at the mpMRI were 0.69 (95% CI 0.56-0.81P, p = 0.003) and 0.72 (95% CI 0.62-0.82P, p = 0.001), respectively. The mpMRI may correctly identify PCP tumors of the PZ and the mean ADC value and ADC ratio can predict the presence of the cribriform pattern in the PCa.
Author	Gaudiano, Caterina Bianchi, Lorenzo De Cinque, Antonio Giunchi, Francesca Corcioni, Beniamino Golfieri, Rita Schiavina, Riccardo Brunocilla, Eugenio Fiorentino, Michelangelo
Author_xml	– sequence: 1 givenname: Caterina orcidid: 0000-0002-3849-8428 surname: Gaudiano fullname: Gaudiano, Caterina email: caterina.gaudiano@aosp.bo.it, caterina.gaudiano@gmail.com organization: Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna – sequence: 2 givenname: Lorenzo surname: Bianchi fullname: Bianchi, Lorenzo organization: Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, University of Bologna – sequence: 3 givenname: Antonio surname: De Cinque fullname: De Cinque, Antonio organization: Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna – sequence: 4 givenname: Beniamino surname: Corcioni fullname: Corcioni, Beniamino organization: Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna – sequence: 5 givenname: Francesca surname: Giunchi fullname: Giunchi, Francesca organization: Department of Pathology, IRCCS Azienda Ospedaliero-Universitaria di Bologna – sequence: 6 givenname: Riccardo surname: Schiavina fullname: Schiavina, Riccardo organization: Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, University of Bologna – sequence: 7 givenname: Michelangelo surname: Fiorentino fullname: Fiorentino, Michelangelo organization: Department of Specialty, Diagnostic and Experimental Medicine, University of Bologna – sequence: 8 givenname: Eugenio surname: Brunocilla fullname: Brunocilla, Eugenio organization: Division of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, University of Bologna – sequence: 9 givenname: Rita surname: Golfieri fullname: Golfieri, Rita organization: Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna
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Keywords	Multiparametric magnetic resonance imaging PI-RADS version 2.1 Prostate cancer Cribriform pattern Gleason Pattern
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Snippet	Purpose To assess the role of the multiparametric Magnetic Resonance Imaging (mpMRI) in predicting the cribriform pattern in both the peripheral and transition... To assess the role of the multiparametric Magnetic Resonance Imaging (mpMRI) in predicting the cribriform pattern in both the peripheral and transition zones... PurposeTo assess the role of the multiparametric Magnetic Resonance Imaging (mpMRI) in predicting the cribriform pattern in both the peripheral and transition...
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SubjectTerms	Aged Diagnostic Imaging in Oncology Diagnostic Radiology Diffusion coefficient Evaluation Humans Imaging Interventional Radiology Lesions Magnetic resonance imaging Male Medicine Medicine & Public Health Middle Aged Multiparametric Magnetic Resonance Imaging - methods Multivariate analysis Neuroradiology Parameter identification Prostate - diagnostic imaging Prostate - pathology Prostate - surgery Prostatectomy Prostatic Neoplasms - diagnostic imaging Prostatic Neoplasms - pathology Prostatic Neoplasms - surgery Radiology Retrospective Studies Tumors Ultrasound
Title	The impact of multiparametric MRI features to identify the presence of prevalent cribriform pattern in the peripheral zone tumors
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