Evaluating the performance of clinical and radiological data in predicting prostate cancer in prostate imaging reporting and data system version 2.1 category 3 lesions of the peripheral and the transition zones

Purpose To define the value of clinical and radiological data, using multiparametric magnetic resonance imaging (mpMRI), to predict prostate cancer (PCa) in prostate imaging reporting and data system version 2.1 (PIRADSv2.1) 3 lesions of the peripheral and the transition zones (PZ and TZ). Methods T...

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Published in:	International urology and nephrology Vol. 54; no. 2; pp. 263 - 271
Main Authors:	Gaudiano, Caterina, Bianchi, Lorenzo, Corcioni, Beniamino, Giunchi, Francesca, Schiavina, Riccardo, Ciccarese, Federica, Braccischi, Lorenzo, Rustici, Arianna, Fiorentino, Michelangelo, Brunocilla, Eugenio, Golfieri, Rita
Format:	Journal Article
Language:	English
Published:	Dordrecht Springer Netherlands 01.02.2022 Springer Nature B.V
Subjects:	Aged Biopsy Data Accuracy Data Systems Diffusion coefficient Humans Lesions Magnetic resonance imaging Male Medicine Medicine & Public Health Middle Aged Multiparametric Magnetic Resonance Imaging Neoplasm Grading Nephrology Predictive Value of Tests Prostate cancer Prostate-specific antigen Prostatic Neoplasms - diagnostic imaging Prostatic Neoplasms - pathology Retrospective Studies Tumors Urology Urology - Original Paper Multiparametric magnetic resonance imaging Prostate cancer PIRADS version 2.1 PIRADS 3 lesions
ISSN:	0301-1623, 1573-2584, 1573-2584
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Abstract	Purpose To define the value of clinical and radiological data, using multiparametric magnetic resonance imaging (mpMRI), to predict prostate cancer (PCa) in prostate imaging reporting and data system version 2.1 (PIRADSv2.1) 3 lesions of the peripheral and the transition zones (PZ and TZ). Methods The mpMRI of patients with PIRADSv2.1 3 lesions who had undergone fusion targeted biopsy was reviewed. Morphological pattern, diffusion parameters and vascularisation were evaluated. The radiological/histopathological data of benign and malignant lesions, between the PZ and TZ were compared. Univariate and multivariate analyses were carried out to identify the clinical and radiological data capable of predicting PCa. Results One hundred and twenty-three lesions were assessed, 93 (76%) in the PZ and 30 (24%) in the TZ. Of these, 56 (46%) were PCa and 67 (54%) were benign. The majority of the PCas were Grade Group System (GGS) 1 (38%) and GGS 2 (39%); tumours having a GGS ≥ 3 were more frequently in the TZ ( p = 0.02). Univariate analysis showed a significant correlation between PCa and prostate volume, prostate-specific antigen (PSA) density , lesion zone and the apparent diffusion coefficient . At multivariate logistic regression PSA density > 0.15 ng/ml/ml {Odds ratio [OR] 2.38; p = 0.001} and lesion zone (i.e. TZ OR 7.55) were independent predictors of PCa (all p ≤ 0.04). Conclusion In solitary PIRADSv2.1 3 lesions, the most important predictive factor was the location zone, with a much greater risk for TZ lesions.
AbstractList	PurposeTo define the value of clinical and radiological data, using multiparametric magnetic resonance imaging (mpMRI), to predict prostate cancer (PCa) in prostate imaging reporting and data system version 2.1 (PIRADSv2.1) 3 lesions of the peripheral and the transition zones (PZ and TZ).MethodsThe mpMRI of patients with PIRADSv2.1 3 lesions who had undergone fusion targeted biopsy was reviewed. Morphological pattern, diffusion parameters and vascularisation were evaluated. The radiological/histopathological data of benign and malignant lesions, between the PZ and TZ were compared. Univariate and multivariate analyses were carried out to identify the clinical and radiological data capable of predicting PCa. ResultsOne hundred and twenty-three lesions were assessed, 93 (76%) in the PZ and 30 (24%) in the TZ. Of these, 56 (46%) were PCa and 67 (54%) were benign. The majority of the PCas were Grade Group System (GGS) 1 (38%) and GGS 2 (39%); tumours having a GGS ≥ 3 were more frequently in the TZ (p = 0.02). Univariate analysis showed a significant correlation between PCa and prostate volume, prostate-specific antigen (PSA) density, lesion zone and the apparent diffusion coefficient. At multivariate logistic regression PSA density > 0.15 ng/ml/ml {Odds ratio [OR] 2.38; p = 0.001} and lesion zone (i.e. TZ OR 7.55) were independent predictors of PCa (all p ≤ 0.04).ConclusionIn solitary PIRADSv2.1 3 lesions, the most important predictive factor was the location zone, with a much greater risk for TZ lesions. To define the value of clinical and radiological data, using multiparametric magnetic resonance imaging (mpMRI), to predict prostate cancer (PCa) in prostate imaging reporting and data system version 2.1 (PIRADSv2.1) 3 lesions of the peripheral and the transition zones (PZ and TZ).PURPOSETo define the value of clinical and radiological data, using multiparametric magnetic resonance imaging (mpMRI), to predict prostate cancer (PCa) in prostate imaging reporting and data system version 2.1 (PIRADSv2.1) 3 lesions of the peripheral and the transition zones (PZ and TZ).The mpMRI of patients with PIRADSv2.1 3 lesions who had undergone fusion targeted biopsy was reviewed. Morphological pattern, diffusion parameters and vascularisation were evaluated. The radiological/histopathological data of benign and malignant lesions, between the PZ and TZ were compared. Univariate and multivariate analyses were carried out to identify the clinical and radiological data capable of predicting PCa.METHODSThe mpMRI of patients with PIRADSv2.1 3 lesions who had undergone fusion targeted biopsy was reviewed. Morphological pattern, diffusion parameters and vascularisation were evaluated. The radiological/histopathological data of benign and malignant lesions, between the PZ and TZ were compared. Univariate and multivariate analyses were carried out to identify the clinical and radiological data capable of predicting PCa.One hundred and twenty-three lesions were assessed, 93 (76%) in the PZ and 30 (24%) in the TZ. Of these, 56 (46%) were PCa and 67 (54%) were benign. The majority of the PCas were Grade Group System (GGS) 1 (38%) and GGS 2 (39%); tumours having a GGS ≥ 3 were more frequently in the TZ (p = 0.02). Univariate analysis showed a significant correlation between PCa and prostate volume, prostate-specific antigen (PSA) density, lesion zone and the apparent diffusion coefficient. At multivariate logistic regression PSA density > 0.15 ng/ml/ml {Odds ratio [OR] 2.38; p = 0.001} and lesion zone (i.e. TZ OR 7.55) were independent predictors of PCa (all p ≤ 0.04).RESULTSOne hundred and twenty-three lesions were assessed, 93 (76%) in the PZ and 30 (24%) in the TZ. Of these, 56 (46%) were PCa and 67 (54%) were benign. The majority of the PCas were Grade Group System (GGS) 1 (38%) and GGS 2 (39%); tumours having a GGS ≥ 3 were more frequently in the TZ (p = 0.02). Univariate analysis showed a significant correlation between PCa and prostate volume, prostate-specific antigen (PSA) density, lesion zone and the apparent diffusion coefficient. At multivariate logistic regression PSA density > 0.15 ng/ml/ml {Odds ratio [OR] 2.38; p = 0.001} and lesion zone (i.e. TZ OR 7.55) were independent predictors of PCa (all p ≤ 0.04).In solitary PIRADSv2.1 3 lesions, the most important predictive factor was the location zone, with a much greater risk for TZ lesions.CONCLUSIONIn solitary PIRADSv2.1 3 lesions, the most important predictive factor was the location zone, with a much greater risk for TZ lesions. Purpose To define the value of clinical and radiological data, using multiparametric magnetic resonance imaging (mpMRI), to predict prostate cancer (PCa) in prostate imaging reporting and data system version 2.1 (PIRADSv2.1) 3 lesions of the peripheral and the transition zones (PZ and TZ). Methods The mpMRI of patients with PIRADSv2.1 3 lesions who had undergone fusion targeted biopsy was reviewed. Morphological pattern, diffusion parameters and vascularisation were evaluated. The radiological/histopathological data of benign and malignant lesions, between the PZ and TZ were compared. Univariate and multivariate analyses were carried out to identify the clinical and radiological data capable of predicting PCa. Results One hundred and twenty-three lesions were assessed, 93 (76%) in the PZ and 30 (24%) in the TZ. Of these, 56 (46%) were PCa and 67 (54%) were benign. The majority of the PCas were Grade Group System (GGS) 1 (38%) and GGS 2 (39%); tumours having a GGS ≥ 3 were more frequently in the TZ ( p = 0.02). Univariate analysis showed a significant correlation between PCa and prostate volume, prostate-specific antigen (PSA) density , lesion zone and the apparent diffusion coefficient . At multivariate logistic regression PSA density > 0.15 ng/ml/ml {Odds ratio [OR] 2.38; p = 0.001} and lesion zone (i.e. TZ OR 7.55) were independent predictors of PCa (all p ≤ 0.04). Conclusion In solitary PIRADSv2.1 3 lesions, the most important predictive factor was the location zone, with a much greater risk for TZ lesions. To define the value of clinical and radiological data, using multiparametric magnetic resonance imaging (mpMRI), to predict prostate cancer (PCa) in prostate imaging reporting and data system version 2.1 (PIRADSv2.1) 3 lesions of the peripheral and the transition zones (PZ and TZ). The mpMRI of patients with PIRADSv2.1 3 lesions who had undergone fusion targeted biopsy was reviewed. Morphological pattern, diffusion parameters and vascularisation were evaluated. The radiological/histopathological data of benign and malignant lesions, between the PZ and TZ were compared. Univariate and multivariate analyses were carried out to identify the clinical and radiological data capable of predicting PCa. One hundred and twenty-three lesions were assessed, 93 (76%) in the PZ and 30 (24%) in the TZ. Of these, 56 (46%) were PCa and 67 (54%) were benign. The majority of the PCas were Grade Group System (GGS) 1 (38%) and GGS 2 (39%); tumours having a GGS ≥ 3 were more frequently in the TZ (p = 0.02). Univariate analysis showed a significant correlation between PCa and prostate volume, prostate-specific antigen (PSA) density, lesion zone and the apparent diffusion coefficient. At multivariate logistic regression PSA density > 0.15 ng/ml/ml {Odds ratio [OR] 2.38; p = 0.001} and lesion zone (i.e. TZ OR 7.55) were independent predictors of PCa (all p ≤ 0.04). In solitary PIRADSv2.1 3 lesions, the most important predictive factor was the location zone, with a much greater risk for TZ lesions.
Author	Gaudiano, Caterina Rustici, Arianna Bianchi, Lorenzo Giunchi, Francesca Braccischi, Lorenzo Corcioni, Beniamino Golfieri, Rita Ciccarese, Federica Schiavina, Riccardo Brunocilla, Eugenio Fiorentino, Michelangelo
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Keywords	Multiparametric magnetic resonance imaging Prostate cancer PIRADS version 2.1 PIRADS 3 lesions
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Snippet	Purpose To define the value of clinical and radiological data, using multiparametric magnetic resonance imaging (mpMRI), to predict prostate cancer (PCa) in... To define the value of clinical and radiological data, using multiparametric magnetic resonance imaging (mpMRI), to predict prostate cancer (PCa) in prostate... PurposeTo define the value of clinical and radiological data, using multiparametric magnetic resonance imaging (mpMRI), to predict prostate cancer (PCa) in...
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SubjectTerms	Aged Biopsy Data Accuracy Data Systems Diffusion coefficient Humans Lesions Magnetic resonance imaging Male Medicine Medicine & Public Health Middle Aged Multiparametric Magnetic Resonance Imaging Neoplasm Grading Nephrology Predictive Value of Tests Prostate cancer Prostate-specific antigen Prostatic Neoplasms - diagnostic imaging Prostatic Neoplasms - pathology Retrospective Studies Tumors Urology Urology - Original Paper
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Title	Evaluating the performance of clinical and radiological data in predicting prostate cancer in prostate imaging reporting and data system version 2.1 category 3 lesions of the peripheral and the transition zones
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