Turkish Journal of Urology
UROONCOLOGY - Original Article

Lesion Volume in a Bi- or Multivariate Prediction Model for the Management of PI-RADS v2.1 Score 3 Category Lesions

1.

Department of Urology, New Civilian Hospital of Sassuolo, Modena, Italy

2.

Division of Gynaecology, Department of Medicine and Surgery, S. Maria della Misericordia Hospital, Perugia University, Perugia, Italy

3.

Department of Radiology, New Civilian Hospital of Sassuolo, Modena, Italy

4.

Department of Urology, Usl Toscana Sud Est, San Donato Hospital, Arezzo, Italy

5.

Division of Biochemistry, Department of Agricultural, Food, and Environmental Sciences, Perugia University, Perugia, Italy

6.

Division of Anaesthesia, Casa di Cura Fogliani, Modena, Italy

7.

Division of Diagnostic Imaging, Department of Medicine and Surgery, S. Maria della Misericordia Hospital, Perugia University, Italy

8.

Division of Urology, Portogruaro Hospital, Venice, Italy

9.

Division of Radiology, Tivoli Hospital, Tivoli, Italy

10.

Division of Radiology 2, Department of Medicine and Surgery, S. Maria della Misericordia Hospital, Perugia University, Perugia, Italy

Turk J Urol 2022; 48: 268-277
DOI: 10.5152/tud.2022.22038
Read: 135 Downloads: 27 Published: 01 July 2022

Objective: This study aimed at improving the discrimination of Prostate Imaging – Reporting and Data System version 2.1 (PI-RADS v2.1) score 3 suspicious prostate cancer lesions using lesion volume evaluation.

Material and methods: Two hundred five PI-RADS v2.1 score 3 lesions were submitted to transperineal MRI/TRUS fusion-targeted biopsy. The lesion volumes were estimated on diffusion-weighted imaging sequence and distributed in PI-RADS 3a (LV < 0.5 mL) and PI-RADS 3b (LV ≥ 0.5 mL) subcategories, using a 0.5 mL cutoff value. Data were retrospectively matched with histopathological findings from the biopsy. Assuming that lesions with LV < or ≥ 0.5 mL were respectively not eligible (benign and indolent PCa lesions) or eligible for biopsy (significant PCa lesions), the diagnostic accuracy of lesion volume in determining clinically significant PCa at biopsy was evaluated using a bi- or multivariate model.

Results: About 55.1% and 44.9% of lesions were distributed in subcategories 3a and 3b, respectively. The overall PI-RADS score 3 detection rate was 273%. 3.5% (1.95% of total), and 25% (11.7% of total) significant PCa were found in PI-RADS 3a and 3b subcategory, respectively. The method showed 85.2% sensitivity, 61.2% specificity, 25% positive predictive value, and 96.5% negative predictive value and avoided 55.1% of unnecessary biopsies. The diagnostic accuracy in determining significant PCa at biopsy was 73.2% or 86.5% depending on whether lesion volume was used alone or in combination with prostate volume and patient age in a multivariate model.

Conclusion: 0.5 mL lesion volume cutoff value significantly discriminates fusion-targeted biopsy need in PI-RADS v2.1 score 3 lesions and its diagnostic accuracy improves when it combines with prostate volume and age in a multivariate model.

Cite this article as: Martorana E, Aisa MC, Grisanti R, et al. Lesion volume in a bi- or multivariate prediction model for the management of PI-RADS v2.1 score 3 category lesions. Turk J Urol. 2022;48(4):268-277.

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