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Purpose: Age-related macular degeneration (AMD) presents a multifaceted etiopathogenesis involving ischemic, inflammatory, and genetic components. This study investigates the correlation between ocular hemodynamics, scleral rigidity (SR), and plasma endothelin-1 (ET1) levels in treatment-naive patients with asymmetrical AMD. Patients and Methods: This study included 20 treatment-naive patients (12 females and 8 males) with an average age of 76.4 ± 3.7 years, who presented with AMD with neovascular membrane formation (nAMD) in one eye, and intermediate grade 2 AMD (iAMD) in the other eye. The control group consisted of 20 healthy subjects (13 females and 7 males) with a mean age of 74.7 ± 3.9 years. All patients and healthy controls underwent color Doppler imaging (i) of the ophthalmic artery (OA), short posterior ciliary arteries (SPCAs), and central retinal artery (CRA); Plasma ET-1 levels were measured for all patients and healthy subjects. Corneal biomechanics were assessed using an Ocular Response Analyzer and two indices were obtained: corneal hysteresis (CH) and corneal resistance factor (CRF). Results: Results showed reduced blood flow velocities and increased resistance indices in AMD eyes, particularly affecting the short posterior ciliary arteries. According to mechanical theory, ARMD eyes exhibited elevated scleral rigidity and corneal resistance factor compared to controls, with a notable rise in SR in neovascular AMD (nAMD) eyes. As per the chronic subacute inflammation theory, plasma ET-1 levels were significantly higher in AMD patients, correlating with abnormal SPCAs blood flow and increased resistance indices. Conclusion: Findings suggest a multifactorial etiology of AMD involving an increase of ET-1 plasma levels with biomechanic damages of corneal and scleral tissue in nAMD.

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Prostate cancer ranks among the most prevalent tumours globally. While early detection reduces the likelihood of metastasis, managing advanced cases poses challenges in diagnosis and treatment. Current international guidelines support the concurrent use of 99Tc-Bone Scintigraphy and Contrast-Enhanced Chest and Abdomen CT for the staging of metastatic disease and response assessment. However, emerging evidence underscores the superiority of next-generation imaging techniques including PSMA-PET/CT and whole-body MRI (WB-MRI). This review explores the relevant scientific literature on the role of WB-MRI in metastatic prostate cancer. This multiparametric imaging technique, combining the high anatomical resolution of standard MRI sequences with functional sequences such as diffusion-weighted imaging (DWI) and bone marrow relative fat fraction (rFF%) has proved effective in comprehensive patient assessment, evaluating local disease, most of the nodal involvement, bone metastases and their complications, and detecting the increasing visceral metastases in prostate cancer. It does have the advantage of avoiding the injection of contrast medium/radionuclide administration, spares the patient the exposure to ionizing radiation, and lacks the confounder of FLARE described with nuclear medicine techniques. Up-to-date literature regarding the diagnostic capabilities of WB-MRI, though still limited compared to PSMA-PET/CT, strongly supports its widespread incorporation into standard clinical practice, alongside the latest nuclear medicine techniques.

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The Prostate Imaging and Reporting Data System (PI-RADS) has a key role in the management of prostate cancer (PCa). However, the clinical interpretation of PI-RADS 3 score lesions may be challenging and misleading, thus postponing PCa diagnosis to biopsy outcome. Multiparametric magnetic resonance imaging (mpMRI) radiomic analysis may represent a stand-alone noninvasive tool for PCa diagnosis. Hence, this study aims at developing a mpMRI-based radiomic PCa diagnostic model in a cohort of PI-RADS 3 lesions. We enrolled 133 patients with 155 PI-RADS 3 lesions, 84 of which had PCa confirmation by fusion biopsy. Local radiomic features were generated from apparent diffusion coefficient maps, and the four most informative were selected using LASSO, the Wilcoxon rank-sum test (p < 0.001), and support vector machines (SVMs). The selected features where augmented and used to train an SVM classifier, externally validated on a holdout subset. Linear and second-order polynomial kernels were exploited, and their predictive performance compared through receiver operating characteristics (ROC)-related metrics. On the test set, the highest performance, equally for both kernels, was specificity = 76%, sensitivity = 78%, positive predictive value = 80%, and negative predictive value = 74%. Our findings substantially improve radiologist interpretation of PI-RADS 3 lesions and let us advance towards an image-driven PCa diagnosis.

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Multiparametric magnetic resonance imaging (mpMRI) is currently the most effective diagnostic tool for detecting prostate cancer (PCa) and evaluating adenocarcinoma-mimicking lesions of the prostate gland, among which granulomatous prostatitis (GP) represents the most interesting diagnostic challenge. GP consists of a heterogeneous group of chronic inflammatory lesions that can be differentiated into four types: idiopathic, infective, iatrogenic, and associated with systemic granulomatous disease. The incidence of GP is growing due to the increase in endourological surgical interventions and the adoption of intravesical instillation of Bacillus Calmette-Guerin in patients with non-muscle invasive bladder cancer; therefore, the difficulty lies in identifying specific features of GP on mpMRI to avoid the use of transrectal prostate biopsy as much as possible.

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BACKGROUND: Benign renal tumors, such as renal oncocytoma (RO), can be erroneously diagnosed as malignant renal cell carcinomas (RCC), because of their similar imaging features. Computer-aided systems leveraging radiomic features can be used to better discriminate benign renal tumors from the malignant ones. The purpose of this work was to build a machine learning model to distinguish RO from clear cell RCC (ccRCC). METHOD: We collected CT images of 77 patients, with 30 cases of RO (39%) and 47 cases of ccRCC (61%). Radiomic features were extracted both from the tumor volumes identified by the clinicians and from the tumor's zone of transition (ZOT). We used a genetic algorithm to perform feature selection, identifying the most descriptive set of features for the tumor classification. We built a decision tree classifier to distinguish between ROs and ccRCCs. We proposed two versions of the pipeline: in the first one, the feature selection was performed before the splitting of the data, while in the second one, the feature selection was performed after, i.e., on the training data only. We evaluated the efficiency of the two pipelines in cancer classification. RESULTS: The ZOT features were found to be the most predictive by the genetic algorithm. The pipeline with the feature selection performed on the whole dataset obtained an average ROC AUC score of 0.87 ± 0.09. The second pipeline, in which the feature selection was performed on the training data only, obtained an average ROC AUC score of 0.62 ± 0.17. CONCLUSIONS: The obtained results confirm the efficiency of ZOT radiomic features in capturing the renal tumor characteristics. We showed that there is a significant difference in the performances of the two proposed pipelines, highlighting how some already published radiomic analyses could be too optimistic about the real generalization capabilities of the models.

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Background: To evaluate multiparametric magnetic resonance imaging (mpMRI) parameters, such as TransPA (transverse prostate maximum sectional area), TransCGA (transverse central gland sectional area), TransPZA (transverse peripheral zone sectional area), and TransPAI (TransPZA/TransCGA ratio) in predicting prostate cancer (PCa) in prostate imaging reporting and data system (PI-RADS) 3 lesions. Methods: Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), the area under the receiver operating characteristic curve (AUC), and the best cut-off, were calculated. Univariate and multivariate analyses were carried out to evaluate the capability to predict PCa. Results: Out of 120 PI-RADS 3 lesions, 54 (45.0%) were PCa with 34 (28.3%) csPCas. Median TransPA, TransCGA, TransPZA and TransPAI were 15.4cm2, 9.1cm2, 5.5cm2 and 0.57, respectively. At multivariate analysis, location in the transition zone (OR=7.92, 95% CI: 2.70-23.29, P<0.001) and TransPA (OR=0.83, 95% CI: 0.76-0.92, P<0.001) were independent predictors of PCa. The TransPA (OR=0.90, 95% CI: 0.082-0.99, P=0.022) was an independent predictor of csPCa. The best cut-off of TransPA for csPCa was 18 (Sensitivity 88.2%, Specificity 37.2%, PPV 35.7%, NPV 88.9%). The discrimination (AUC) of the multivariate model was 0.627 (95% CI: 0.519-0.734, P<0.031). Conclusions: In PI-RADS 3 lesions, the TransPA could be useful in selecting patients requiring biopsy.

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This is a case of [68 Ga]Ga-Prostate-specific membrane antigen (PSMA)-11 PET/CT in a 73-years old patient presenting high Prostate Specific Antigen (PSA) levels despite both multi-parametric magnetic resonance imaging (mpMRI) and 12-core saturation biopsy negative for prostate cancer (Pca). This is a highly interesting case because, despite the advanced metastatic spread at initial presentation as showed by [68Ga]Ga-PSMA-PET/CT, the primary Pca was detected by none of the diagnostic techniques (12 random sample biopsy, mpMRI, PSMA PET/CT). However, [68Ga]Ga-PSMA-PET/CT showed a suspicious axillary lesion suitable for biopsy, which finally resulted as Pca metastasis. This case report is therefore a brilliant example of how [68Ga]Ga-PSMA-PET/CT optimized patient's management.

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BACKGROUND: Latest changes in European guidelines on prostate cancer determined a widespread of multiparametric magnetic resonance imaging (mpMRI) even in less experienced centers due to an increased demand. This could decrease diagnostic accuracy of targeted biopsy (TB) since image interpretation can be challenging and requires adequate and supervised training. Therefore we aimed to evaluate the prostate cancer (PCa) detection rate on TB according to mpMRI center's volume and experience. METHODS: We retrospectively analyzed data of 737 patients who underwent mpMRI-TB at our institution. Patients were stratified according to mpMRI center: Hub (high volume >100 exams/year with dedicated radiologists and supervised training) and Spoke center (low volume <100 exams/year without dedicated radiologists and/or supervised training). Detection rate of PCa at TB and possible predictors of clinically significant PCa (csPCa) at TB. Differences in detection rate were explored using Chi-square test. Predictors of csPCa were evaluated through uni and multivariable logistic regression. The adjustment for casemix included: age, PSA, mpMRI center, lesion's location, PSA density, PI-RADS score and index lesion's size. RESULTS: Four hundred forty-nine (60.9%) and 288 (39.1%) patients underwent mpMRI at a Hub or Spoke center, respectively. Hub group had higher detection rate for both any (60.3% vs. 48.1%) and csPCa (46.9% vs 38.7%; all P≤0.001). After stratifying for PI-RADS score, Hub group had higher detection rate for PI-RADS score 3 (csPCA 25.2% vs. 15.7%; p 0.04) and 4 (csPCa 65.7% vs. 45.7%; P=0.001). At multivariable analyses, receiving an mpMRI scan at a Spoke center was an independent predictor for csPCa on TB (OR 0.65; P=0.04). CONCLUSIONS: mpMRI performed in Hub centers provided a significantly higher PCa yield on TB. A dedicated team of experienced radiologist, a supervised training for mpMRI and a central revision of mpMRI performed in non-experienced centres are essential to avoid unnecessary and potentially harmful procedures.

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PURPOSE: To define the impact of systematic biopsy (SB) cores directed in the same area of index lesion in patients undergoing targeted biopsy (TB) and SB for prostate cancer (PCa) suspicion. METHODS: We retrospectively analyzed data of biopsy-naïve patients with one single suspicious lesion at mpMRI who underwent TB plus SB at our institution between January 2015 and September 2021. A convenient sample of 336 patients was available for our analyses. The primary outcome was to evaluate the impact of overlapping SB cores directed to the index lesion at mpMRI. The secondary outcome was to evaluate the SB cores concordance in terms of highest Gleason Score Detection with TB cores. RESULTS: 56% of patients were found to have site-specific concordance. SB cores determined disease upgrade in 22.1% patients. Thirty-one (16.4%) site-concordant patients experienced upgrade through overlapping SB cores, while 149 (79.3%) had no benefit by SB cores, and 8 (4.3%) patients had the worst ISUP at TB cores. 50% of the patients with negative-TB were upgraded to insignificant PCa, and 17.5% was upgraded from negative to unfavorable-intermediate- or high-risk PCa. Overall, 14 (19.4%) patients were also upgraded from ISUP 1 on TB to csPCa, with 28.5% of these harboring high-risk PCa. In csPCas at TB, 9 (12.5%) patients were upgraded from intermediate- to high-risk disease by SB. CONCLUSIONS: TB alone consents to identify worst ISUP PCa in vast majority of patients scheduled for biopsy. A non-negligible number of patients are upgraded via-SB cores, including also index lesion overlapping cores. Omitting these cores might lead to a suboptimal patient management.

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The risk of misclassifying clinically significant prostate cancer (csPCa) by multiparametric magnetic resonance imaging is consistent, also using the updated PIRADS score and although different definitions of csPCa, patients with Gleason Grade group (GG) ≥ 3 have a significantly worse prognosis. This study aims to develop a machine learning model predicting csPCa (i.e., any GG ≥ 3 lesion at target biopsy) by mpMRI radiomic features and analyzing similarities between GG groups. One hundred and two patients with 117 PIRADS ≥ 3 lesions at mpMRI underwent target+systematic biopsy, providing histologic diagnosis of PCa, 61 GG < 3 and 56 GG ≥ 3. Features were generated locally from an apparent diffusion coefficient and selected, using the LASSO method and Wilcoxon rank-sum test (p < 0.001), to achieve only four features. After data augmentation, the features were exploited to train a support vector machine classifier, subsequently validated on a test set. To assess the results, Kruskal−Wallis and Wilcoxon rank-sum tests (p < 0.001) and receiver operating characteristic (ROC)-related metrics were used. GG1 and GG2 were equivalent (p = 0.26), whilst clear separations between either GG[1,2] and GG ≥ 3 exist (p < 10−6). On the test set, the area under the curve = 0.88 (95% CI, 0.68−0.94), with positive and negative predictive values being 84%. The features retain a histological interpretation. Our model hints at GG2 being much more similar to GG1 than GG ≥ 3.

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Objective: to evaluate the impact of 3D model for a comprehensive assessment of surgical planning and quality of partial nephrectomy (PN). Materials and methods: 195 patients with cT1-T2 renal mass scheduled for PN were enrolled in two groups: Study Group (n= 100), including patients referred to PN with revision of both 2D computed tomography (CT) imaging and 3D model; Control group (n= 95), including patients referred to PN with revision of 2D CT imaging. Overall, 20 individuals were switched to radical nephrectomy (RN). The primary outcome was the impact of 3D models-based surgical planning on Trifecta achievement (defined as the contemporary absence of positive surgical margin, major complications and ≤30% postoperative eGFR reduction). The secondary outcome was the impact of 3D models on surgical planning of PN. Multivariate logistic regressions were used to identify predictors of selective clamping and Trifecta's achievement in patients treated with PN (n=175). Results: Overall, 73 (80.2%) patients in Study group and 53 (63.1%) patients in Control group achieved the Trifecta (p=0.01). The preoperative plan of arterial clamping was recorded as clampless, main artery and selective in 22 (24.2%), 22 (24.2%) and 47 (51.6%) cases in Study group vs. 31 (36.9%), 46 (54.8%) and 7 (8.3%) cases in Control group, respectively (p<0.001). At multivariate logistic regressions, the use of 3D model was found to be independent predictor of both selective or super-selective clamping and Trifecta's achievement. Conclusion: 3D-guided approach to PN increase the adoption of selective clamping and better predict the achievement of Trifecta.

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Background: We investigated the diagnostic accuracy of the new Prostate Imaging for Recurrence Reporting (PI-RR) score and its inter-observer variability. Secondly, we compared the detection rate of PI-RR and PET and analyzed the correlation between Prostate Specific Antigen (PSA) levels and the PI-RR score. Methods: We included in the analysis 134 patients submitted to multiparametric magnetic resonance imaging for suspected local recurrence. The images were independently reviewed by two radiologists, assigning a value from 1 to 5 to the PI-RR score. Inter-observer agreement and diagnostic accuracy of the PI-RR score (compared to histopathological data, available for 19 patients) were calculated. The detection rate was compared to those of choline PET/CT (46 patients) and PSMA PET/CT (22 patients). The distribution of the PSA values in relation to the PI-RR scores was also analyzed. Results: The accuracy of the PI-RR score was 68.4%. The reporting agreement was excellent (K = 0.884, p < 0.001). The PI-RR showed a higher detection rate than choline PET/CT (69.6% versus 19.6%) and PSMA PET-CT (59.1% versus 22.7%). The analysis of the PSA distribution documented an increase in the PI-RR score as the PSA value increased. Conclusion: The excellent reproducibility of the PI-RR score supports its wide use in the clinical practice to standardize recurrence reporting. The detection rate of PI-RR was superior to that of PET, but was linked to the PSA level.

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Paraganglioma (PGL) is characterized by equivocal clinical manifestations and arriving to a suspicion might be challenging. Nevertheless, diagnostic imaging and nuclear medicine are a fundamental part of the diagnosis and management of this particular neuroendocrine tumor (NET). We herein report a rare case of bladder paraganglioma with unusual onset and typical PET/CT characteristics that led to its recognition.

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BACKGROUND: The widespread use of ultrasonography has led to an increased number of incidentally detected small non-palpable lesions, with Leydig cell tumours representing the majority of them. OBJECTIVES: The ultrasonography, real-time elastography and contrast-enhanced ultrasonography features of a large series of non-palpable testicular lesions were evaluated, focusing on the differences between Leydig cell tumours and other testicular masses. MATERIALS AND METHODS: Of the 4679 testicular ultrasonography examinations performed at the Authors' Institution between January 2009 and December 2018, 78 patients (1.7%) were incidentally diagnosed with at least one non-palpable lesion and were enrolled. Thirteen patients (16.6%) declined surgery and were thus excluded. The remaining 65 underwent surgical resection with frozen section analysis. The conventional ultrasonography, colour Doppler, real-time elastography and contrast-enhanced ultrasonography were performed by a radiologist having more than 10 years of experience. Demographic and clinical data were collected. RESULTS: Leydig cell tumours were detected in 32 patients, being the most frequent benign tumours (49.2%); of the non-Leydig cell tumours, 25 patients had malignant tumours, five non-neoplastic lesions and three other benign tumours. The Leydig cell tumour group had mostly infertility problems whereas the non-Leydig cell tumour group frequently experienced pain (p < 0.001). Leydig cell tumours were all hypoechoic (32/32, 100%; p = 0.002), more frequently presented with well-defined margins compared to non-Leydig cell tumours (30/32, 93.8% vs. 19/33, 57.6%; p = 0.001) and tended to be smaller than non-Leydig cell tumours (5.3 mm [standard deviation 2.7 mm] vs. 10.6 mm [standard deviation 3.8 mm], respectively; p < 0.001). The vascular pattern characterised by the rapid wash-in followed by the delayed wash-out observed during contrast-enhanced ultrasonography was significantly associated with the Leydig cell tumour histological diagnosis, even at multivariate analysis (odds ratio 480.5, p < 0.001), and yielded a high diagnostic accuracy (area under the receiver operating characteristic curve 0.954, 95% confidence interval 0.903-1). DISCUSSION: Contrast-enhanced ultrasonography demonstrated high diagnostic accuracy in identifying benign testicular lesions, such as Leydig cell tumours; they are the most common non-palpable tumours detected in infertile men and may benefit from enucleation.

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PURPOSE: To determine the clinical, pathological, and radiological features, including the Vesical Imaging-Reporting and Data System (VI-RADS) score, independently correlating with muscle-invasive bladder cancer (BCa), in a multicentric national setting. METHOD AND MATERIALS: Patients with BCa suspicion were offered magnetic resonance imaging (MRI) before trans-urethral resection of bladder tumor (TURBT). According to VI-RADS, a cutoff of ≥ 3 or ≥ 4 was assumed to define muscle-invasive bladder cancer (MIBC). Trans-urethral resection of the tumor (TURBT) and/or cystectomy reports were compared with preoperative VI-RADS scores to assess accuracy of MRI for discriminating between non-muscle-invasive versus MIBC. Performance was assessed by ROC curve analysis. Two univariable and multivariable logistic regression models were implemented including clinical, pathological, radiological data, and VI-RADS categories to determine the variables with an independent effect on MIBC. RESULTS: A final cohort of 139 patients was enrolled (median age 70 [IQR: 64, 76.5]). MRI showed sensitivity, specificity, PPV, NPV, and accuracy for MIBC diagnosis ranging from 83-93%, 80-92%, 67-81%, 93-96%, and 84-89% for the more experienced readers. The area under the curve (AUC) was 0.95 (0.91-0.99). In the multivariable logistic regression model, the VI-RADS score, using both a cutoff of 3 and 4 (P < .0001), hematuria (P = .007), tumor size (P = .013), and concomitant hydronephrosis (P = .027) were the variables correlating with a bladder cancer staged as ≥ T2. The inter-reader agreement was substantial (k = 0.814). CONCLUSIONS: VI-RADS assessment scoring proved to be an independent predictor of muscle-invasiveness, which might implicate a shift toward a more aggressive selection approach of patients' at high risk of MIBC, according to a novel proposed predictive pathway.

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OBJECTIVE: The aim of the study was to evaluate the accuracy of multiparametric Magnetic Resonance Imaging (mpMRI) in the detection of local recurrence of prostate cancer (PCa) with the evaluation of the added value of signal Intensity/Time (I/T) curves. MATERIALS AND METHODS: A retrospective analysis of 22 patients undergoing mpMRI from 2015 to 2020 was carried out, with the following inclusion criteria: performing transrectal ultrasound guided biopsy within 3 months in the case of positive or doubtful findings and undergoing biopsy and/or clinical follow-up for 24 months in the case of negative results. The images were reviewed, and the lesions were catalogued according to morphological, diffusion-weighted imaging (DWI) and dynamic contrast- enhanced (DCE) features. RESULTS: The presence of local recurrence was detected in 11/22 patients (50%). Greater diameter, hyperintensity on DWI, positive contrast enhancement and type 2/3 signal I/T curves were more frequently observed in patients with local recurrence (all p < 0.05). Of all the sequences, DCE was the most accurate; however, the combination of DCE and DWI showed the best results, with a sensitivity of 100%, a specificity of 82%, a negative predictive value of 100% and a positive predictive value of 85%. CONCLUSIONS: The utility of MRI in the detection of local recurrence is tied to the multiparametric approach, with all sequences providing useful information. A combination of DCE and DWI is particularly effective. Moreover, specificity could be additionally improved using analysis of the signal I/T curves.

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BACKGROUND: No data are available regarding the impact of time between a previous transrectal prostate biopsy (PB) and holmium laser enucleation of the prostate (HoLEP) on perioperative outcomes. OBJECTIVE: To evaluate the impact of time from PB to HoLEP on perioperative outcomes. DESIGN, SETTING, AND PARTICIPANTS: A total of 172 consecutive patients treated with HoLEP within 12 mo of a single previous transrectal PB at two tertiary centers were included. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Patients were stratified into two groups according to the median time from PB to HoLEP (namely, ≤6 and >6 mo). The primary outcome was intraoperative complications. Multivariate logistic regressions were used to identify the predictors of intraoperative complications. Linear regressions were used to test the association between the time from PB to HoLEP and intraoperative complications, enucleation efficiency, and enucleation time. RESULTS AND LIMITATIONS: In total, 93 (54%) and 79 (46%) patients had PB ≤ 6 and >6 mo before HoLEP, respectively. Patients in PB ≤ 6 mo group experienced higher rates of intraoperative complications than those in PB > 6 mo group (14% vs 2.6%, p = 0.04). At multivariable analysis, time between PB and HoLEP was an independent predictor of intraoperative complications (odds ratio: 0.74; 95% confidence interval: 0.6-0.9; p = 0.006). Finally, the risk of intraoperative complications reduced by 1.5%, efficiency of enucleation increased by 4.1%, and enucleation time reduced by 1.7 min for each month passed from PB to HoLEP (all p ≤ 0.006). Selection of patients with only one previous PB represents the main limitation. CONCLUSIONS: The time from PB to HoLEP of ≤6 mo is associated with a higher risk of intraoperative complications, lower enucleation efficacy, and longer enucleation time. PATIENT SUMMARY: Patients with a prostate biopsy (PB) ≤6 mo before holmium laser enucleation of the prostate (HoLEP) had significantly worse outcomes than those with a PB > 6 mo before HoLEP.

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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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Multiparametric MRI has been established as the most accurate non-invasive diagnostic imaging tool for detecting prostate cancer (PCa) in both the peripheral zone and the transition zone (TZ) using the PI-RADS (Prostate Imaging Reporting and Data System) v. 2.1 released in 2019 as a guideline to reporting. TZ PCa remains the most difficult to diagnose due to a markedly heterogeneous background and a wide variety of atypical imaging presentations as well as other anatomical and pathological processes mimicking PCa. The aim of this paper was to present a spectrum of PCa in the TZ, as a guide for radiologists.

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