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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

  • Urology - Original Paper
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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.

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Funding

This study has no source(s) of support in the form of grants, equipment or drugs.

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Authors and Affiliations

  1. Department of Radiology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, 40138, Bologna, Italy

    Caterina Gaudiano, Beniamino Corcioni, Federica Ciccarese, Lorenzo Braccischi, Arianna Rustici & Rita Golfieri

  2. Department of Urology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, Bologna, Italy

    Lorenzo Bianchi, Riccardo Schiavina & Eugenio Brunocilla

  3. University of Bologna, Bologna, Italy

    Lorenzo Bianchi, Riccardo Schiavina & Eugenio Brunocilla

  4. Department of Pathology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Via Albertoni 15, Bologna, Italy

    Francesca Giunchi & Michelangelo Fiorentino

  5. Department of Specialty, Diagnostic and Experimental Medicine, University of Bologna, Via Massarenti 9, Bologna, Italy

    Michelangelo Fiorentino

Authors
  1. Caterina Gaudiano
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Corresponding author

Correspondence to Caterina Gaudiano.

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The study was approved by our local institution review board and conducted in accordance with institutional guidelines, including the Declaration of Helsinki (Approval code: STUD-OF, Prot. N. 323).

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All patients were notified of the investigational nature of this study and gave their written informed consent.

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Gaudiano, C., Bianchi, L., Corcioni, B. et al. 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. Int Urol Nephrol 54, 263–271 (2022). https://doi.org/10.1007/s11255-021-03071-7

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