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The WBLDMDCT effective dose in our institution is consistent with the values reported in previous studies. Such a dose is about 2.5- to 3-fold higher than the mean radiation dose of the conventional X-ray study. Nevertheless, considering the improved diagnostic accuracy of the CT investigation, the comfort of the patient and the old age of the MM population, dose/quality ratio can be considered favourable.

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PI-RADS 3 prostate lesions clinical management is still debated, with high variability among different centers. Identifying clinically significant tumors among PI-RADS 3 is crucial. Radiomics applied to multiparametric MR (mpMR) seems promising. Nevertheless, reproducibility assessment by external validation is required. We retrospectively included all patients with at least one PI-RADS 3 lesion (PI-RADS v2.1) detected on a 3T prostate MRI scan at our Institution (June 2016–March 2021). An MRI-targeted biopsy was used as ground truth. We assessed reproducible mpMRI radiomic features found in the literature. Then, we proposed a new model combining PSA density and two radiomic features (texture regularity (T2) and size zone heterogeneity (ADC)). All models were trained/assessed through 100-repetitions 5-fold cross-validation. Eighty patients were included (26 with GS ≥ 7). In total, 9/20 T2 features (Hector’s model) and 1 T2 feature (Jin’s model) significantly correlated to biopsy on our dataset. PSA density alone predicted clinically significant tumors (sensitivity: 66%; specificity: 71%). Our model obtained a sensitivity of 80% and a specificity of 76%. Standard-compliant works with detailed methodologies achieve comparable radiomic feature sets. Therefore, efforts to facilitate reproducibility are needed, while complex models and imaging protocols seem not, since our model combining PSA density and two radiomic features from routinely performed sequences appeared to differentiate clinically significant cancers.

Objectives: To evaluate the diagnostic accuracy of multiparametric magnetic resonance imaging in the detection of prostate cancer, according to Prostate Imaging Reporting and Data System, and the usefulness of combining clinical parameters to improve patients' risk assessment. Methods: Overall, 201 patients underwent multiparametric magnetic resonance imaging investigation with a 3-T magnet and a 32-channel body coil based on triplanar high-resolution T2-weighted, diffusion-weighted and T1-weighted dynamic contrastenhanced imaging before, during and after intravenous administration of paramagnetic contrast agent. Random transrectal ultrasound-guided biopsy was carried out for all eligible patients. If a Prostate Imaging Reporting and Data System ≥3 lesion was present, a targeted biopsy with magnetic resonance imaging-transrectal ultrasound fusion-guided system was carried out. Results: Sensitivity, specificity, positive predictive value and negative predictive value of Prostate Imaging Reporting and Data System ≥3 lesions for the detection of prostate cancer were 65.1%, 54.9%, 43.1% and 75.0% respectively, with an accuracy of 64.2% (55.1-72.7%). At uni-and multivariate analysis, age ≥70 years and prostate-specific antigen density ≥0.15 ng/mL/mL were significantly associated with prostate cancer. A new risk model named "modified Prostate Imaging Reporting and Data System" was created considering age and prostate-specific antigen density in addition to the Prostate Imaging Reporting and Data System score showing an improved correlation with prostate cancer compared with the Prostate Imaging Reporting and Data System alone (area under curve 71.4%, 95% confidence interval 62.2-80.5 vs area under curve 62.6%, 95% confidence interval 52.1-73; P ≤ 0.0001). Conclusions: The accuracy of Prostate Imaging Reporting and Data System alone in the diagnosis of prostate cancer might be suboptimal, whereas a novel risk model based on the combination of multiparametric magnetic resonance imaging data with clinical parameters could offer higher discrimination and improve the ability of diagnosing clinically significant disease.

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