PI-RADS Score Research Articles

The Impact of Prostate Volume on the Prostate Imaging and Reporting Data System (PI-RADS) in a Real-World Setting.

Multiparametric magnetic resonance imaging (mpMRI) has emerged as a new cornerstone in the diagnostic pathway of prostate cancer. However, mpMRI is not devoid of factors influencing its detection rate of clinically significant prostate cancer (csPCa). Amongst others, prostate volume has been demonstrated to influence the detection rates of csPCa. Particularly, increasing volume has been linked to a reduced cancer detection rate. However, information about the linkage between PI-RADS, prostate volume and detection rate is relatively sparse. Therefore, the current study aims to assess the association between prostate volume, PI-RADS score and detection rate of csP-Ca, representing daily practice and contemporary mpMRI expertise. Thus, 1039 consecutive patients with 1151 PI-RADS targets, who underwent mpMRI-guided prostate biopsy at our tertiary referral center, were included. Prior mpMRI had been assessed by a plethora of 111 radiology offices, including academic centers and private practices. mpMRI was not secondarily reviewed in house before biopsy. mpMRI-targeted biopsy was performed by a small group of a total of ten urologists, who had performed at least 100 previous biopsies. Using ROC analysis, we defined cut-off values of prostate volume for each PI-RADS score, where the detection rate drops significantly. For PI-RADS 4 lesions, we found a volume > 61.5 ccm significantly reduced the cancer detection rate (OR 0.24; 95% CI 0.16-0.38; p < 0.001). For PI-RADS 5 lesions, we found a volume > 51.5 ccm to significantly reduce the cancer detection rate (OR 0.39; 95% CI 0.25-0.62; p < 0.001). For PI-RADS 3 lesions, none of the evaluated clinical parameters had a significant impact on the detection rate of csPCa. In conclusion, we show that enlarged prostate volume represents a major limitation in the daily practice of mpMRI-targeted biopsy. This study is the first to define exact cut-off values of prostate volume to significantly impair the validity of PI-RADS assessed in a real-world setting. Therefore, the results of mpMRI-targeted biopsy should be interpreted carefully, especially in patients with prostate volumes above our defined thresholds.

Role of Perilesional Sampling of Patients Undergoing Fusion Prostate Biopsies.

Recently, researchers have proposed perilesional sampling during prostate biopsies to avoid systematic biopsies of patients at risk of prostate cancer. The aim of our study is to evaluate the role of perilesional sampling to avoid systematic biopsies of patients undergoing fusion biopsies. A prospective cohort of patients undergoing transrectal MRI transrectal fusion biopsies were consecutively enrolled. All the patients underwent systematic biopsies (SB), targeted biopsies (TB) and perilesional biopsies within 10 mm from the lesion (PB). The detection rates of different strategies were determined. A total of 262 patients were enrolled. The median age of those enrolled was 70 years. The mean BMI was 27 kg/m2, and the mean and prostate volume was 52 mL. A PIRADS score ≥ 4 was recorded in 163/262 (40%) patients. Overall, the detection rates of cancer were 43.5% (114/262) and 35% (92/262) for csPCa. The use of the target + peri-target strategy resulted in a detection of 32.8% (86/262) of cancer cases and of 29% (76/262) of csPCa cases (Grade Group > 2). Using the target plus peri-target approach resulted in us missing 18/262 (7%) of the csPCa cases, avoiding the diagnosis of 8/262 (3%) of nsPCa cases. A biopsy strategy including lesional and perilesional sampling could avoid unnecessary prostate biopsies. However, the risk of missing significant cancers is present. Future studies should assess the cost-benefit relationship of different strategies.

Clinical study of multifactorial diagnosis in prostate biopsy.

To study the feasibility of using an artificial intelligence (AI) algorithm for the diagnosis of clinically significant prostate cancer (csPCa) on multiparametric MRI (mpMRI) in combination with conventional clinical information. A retrospective study cohort with 505 patients was collected, with complete information on age (≤60, 60-80, and >80 years), PSA (≤4, 4-10, and >10 ng/dL), and pathology results. The patients with ISUP group >2 were classified as csPCa, and the patients with ISUP = 1 or no evidence of prostate cancer were classified as non-csPCa. The diagnosis of mpMRI was made by experienced radiologists following the prostate imaging reporting and data system (PIRADS ≤ 2, PIRADS = 3, and PIRADS > 3). The mpMRI images were processed by a homemade AI algorithm, and the AI results were obtained as positive or negative for csPCa. Two logistic regression models were fitted, with pathological findings as the dependent variable, that is, a conventional model and an AI model. The conventional model used age, PSA, and PIRADS as the independent variables. The AI model took the AI result and the abovementioned clinical information as the independent variables. The predicted probability of the patients from the conventional model and the AI model were used to test the prediction efficacy of the models. The DeLong test was performed to compare differences in the area under the receiver operating characteristic (ROC) area under the curve (AUC) between the conventional model and the AI model. In total, 505 patients were included in the study; 280 were diagnosed with csPCa, and 225 were non-csPCa. The median age was 72.0 (67.0, 76.0) years, with a median PSA value of 13.0 (7.46, 27.5) ng/dL. Statically significant differences were found in age, PSA, PIRADS score and AI results between the csPCa and non-csPCa groups (all p < 0.001). In the multivariable regression models, all the variables were independently associated with csPCa. The conventional model (R2 = 0.361) and the AI model (R2 = 0.474) were compared with analysis of variance (ANOVA) and showed statistically significant differences (χ2 = 63.695, p < 0.001). The AUC of the ROC curve for the conventional model was 0.782 (95% confidence interval [CI]: 0.742-0.823), which was less than the AUC of the AI model with statistical significance (0.849 [95% CI: 0.815-0.883], p < 0.001). In combination with routine clinical information, such as age, PSA, and PIRADS category, adding information from the AI algorithm based on mpMRI could improve the diagnosis of csPCa.

Are T2WI PI-RADS sub-scores of transition zone prostate lesions biased by DWI information? A multi-reader, single-center study

PurposeAccording to PI-RADS v2.1, T2-weighted imaging (T2WI) is the dominant sequence for transition zone (TZ) lesions. This study aimed to assess, whether diffusion-weighted imaging (DWI) information influences the assignment of T2WI scores. MethodOut of 283 prostate MRI examinations with correlated biopsy results, fourty-four patients were selected retrospectively: first, 22 patients with a TZ lesion with T2WI and DWI scores ≥ 4, to represent lesions with unequivocal suspicion on T2WI and DWI. Second, 22 additional patients with TZ lesions of similar T2WI appearance but with corresponding DWI score ≤ 3 were added as control. Four residents and one board-certified radiologist each performed two assessments of the included patients: First, only T2WI was available (T2-only read); second, both T2WI and DWI sequences were available (biparametric read). Lesion scores were assessed using Wilcoxon signed-rank test, inter-reader agreement using weighted kappa and Kendall's W statistics, and sensitivity/specificity using McNemar test. ResultsThe T2WI scores were significantly different between the T2-only and biparametric read for 3 out of 4 residents (p ≤ 0.049) but not for the radiologist. The overall PI-RADS scores derived from the two reading sessions differed considerably for 35/220 cases (all readers pooled). Inter-reader agreement was fair for the T2WI and overall PI-RADS scores (mean kappa 0.27–0.30) and moderate for the DWI scores (mean kappa 0.43). ConclusionsFor inexperienced readers, assessment of T2WI is variable and potentially biased by availability of DWI information, which can lead to changes of overall PI-RADS score and consequently clinical management. Assessment of T2WI should be performed before reviewing DWI to ensure non-biased interpretation of TZ lesions in the dominant sequence.

Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) Magnetic Resonance Imaging Scoring to Predict Clinical Outcomes in Active Surveillance for Grade Group 1 Prostate Cancer

To determine whether radiological change on serial multiparametric magnetic resonance imaging (mpMRI) scored using the Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) Scoring system predicts grade reclassification (GR) at surveillance biopsy in men on active surveillance (AS) with Grade Group 1 (GG1) prostate cancer (PCa). We retrospectively reviewed records of 255 men with low risk PCa on AS with MRI-informed diagnostic (DB) and confirmatory biopsies (CB) and studied the subset who had surveillance biopsies (n = 163) within 6 months of their interval MRI. We studied 309 PRECISE scores in 255 men. 14% demonstrated radiological progression (PRECISE 4-5) on interval MRI performed within 24 months, compared to 34% of those whose interval MRI was performed at a > 3-year interval (p=0.002). 28% (46/163) of men undergoing surveillance biopsy experienced GR to ≥ GG2 PCa. There was no significant increase in the rate of GR with increasing PRECISE score (PRECISE 1-2: 24%, PRECISE 3: 23%, PRECISE 4-5: 38%; p= 0.11). There was a significant increase in the rate of GR with increasing PI-RADS score (p < 0.05). On multivariable analysis, a PI-RADS score of 4-5 was significantly associated with GR compared to men who had a highest PI-RADS ≤ 3 (OR = 1.98 [95% CI: 1.45 - 3.09, p= 0.01]). In a low risk AS cohort with limited follow-up, a patient's highest PI-RADS rather than their PRECISE score on interval MRI was predictive of GR on surveillance biopsy.

Feature and Presentations of Suspected Harboring Prostate Cancer Patients: A Study in a Tertiary Care Hospital in Bangladesh

Background: Prostate cancer is the most common cancer in males of increasing age. It is the second leading causes of cancer mortality among the men throughout the world. There are many etiological factors are associated with increased the risk of prostatic carcinoma including male hormone and its active metabolites, genetic predisposition, environmental factors, racial difference, food habits etc. A pathway with an imaging test may decide which men with an elevated PSA and/or suspected digital rectal examination will undergo biopsy. Aim of the study: The aim of this study was to assess the feature and presentations of suspected harboring prostate cancer patients. Methods: This was cross- sectional analytical study conducted in the Department of Urology, Sir Salimullah Medical College &amp; Mitford Hospital, Dhaka, Bangladesh during the period from July 2018 to June 2020. A total of 50 male patients had undergone mpMRI of prostate and TRUS biopsy and histopathology were enrolled in this study as study population. All data were processed, analyzed and disseminated by using MS Excel and SPSS version 22.0. Results: In this study, the mean age of the participants was found as 69.14±8.48 years. The most frequent complaint of them was frequency of urination in 84%. The mean S. PSA was found as 41.78 ± 28.097 ng/ml. More than one third (38%) of patients were found to have volume of prostate 41-60 cc and the mean volume was found as 57.26 ± 19.026 cc. The mean PI-RADS score of our respondent was 3.32±1.34 ranging from 1 to 5. As mpMRI of prostate, majority (36%) patients had PI-RADS: 4. As per the histopathological diagnosis, it was found that, 34% of study patients were diagnosed as benign nodular hyperplasia. On the other hand, remaining 66% were diagnosed as carcinoma of prostate. In this study, the range of Gleason scores of the participants was found as 6-10. Conclusion: PI-RADS score, mpMRI and S. PSA assessment may be considered as some prominent evaluation methods .....

Is Likert better than PI-RADS at predicting prostate cancer on MRI and can a mathematical algorithm achieve similar results?

Prostate Imaging Reporting & Data System (PI-RADS) is an internationally recognized system to quantify risk of prostate cancer on magnetic resonance imaging (MRI). However, studies have suggested methods to improve predictive accuracy. To assess two different methods that aim to improve the accuracy of PI-RADS scores: a subjective Likert score given by experienced reporters, and an objective Calculated Adjustment of PI-RADS Equivocal Score (CAPES). Five experienced reporters in a quaternary referral unit used a standardized reporting template to prospectively collect PI-RADS and Likert scores for 1467 multiparametric MRI (mpMRI) scans between January 2021 and June 2022. Histology results were recorded for patients who underwent trans-perineal biopsy. The CAPES tool was retrospectively applied to the cases scoring PI-RADS 3. A theoretical standardized biopsy protocol (assuming all patients scoring ≥3 were referred for biopsy) was used to compare the three scoring systems for sensitivity, specificity, and positive predictive value (PPV). Across all reporters, significantly fewer equivocal "3" scores were given using Likert (15.7%) or CAPES (2.2%) compared to PI-RADS (24.1%). Assuming a protocol where all patients scoring ≥3 were biopsied, Likert had a higher specificity (69.0% vs. 54.4%), sensitivity (98.3% vs. 97.7%), and PPV (49.9% vs. 40.3%) than PI-RADS for identifying ISUP ≥2 cancer. The CAPES tool had an even higher specificity (81.4%) and PPV (61.2%) with only a slightly lower sensitivity (93.4%) resulting in 37.1% (n = 316) fewer biopsies than PI-RADS, and 22.4% (n = 155) fewer biopsies than Likert across 1467 patients. Compared to PI-RADS scoring, Likert scoring or CAPES can result in fewer equivocal scores, greater PPV, and fewer unnecessary biopsies.

Association of quantifiable prostate MRI parameters with any and large cribriform pattern in prostate cancer patients undergoing radical prostatectomy

PurposeCribriform pattern has recently been recognized as an important independent risk factor for prostate cancer (PCa) outcome. This study aimed to identify the association of quantifiable prostate magnetic resonance imaging (MRI) parameters with any and large cribriform pattern at radical prostatectomy (RP) specimens. MethodsPreoperative prostate MRI’s from 188 men undergoing RP between 2010 and 2018 were retrospectively acquired. RP specimens of the patients were revised for Gleason score (GS), and presence of any and large cribriform pattern. MRI parameters such as MRI visibility, PI-RADS score, lowest apparent diffusion coefficient (ADC) value, lesion size, and radiologic extra-prostatic extension (EPE) were reviewed. The association of prostate MRI parameters for presence of any and large cribriform pattern at RP was analysed using logistic regression. Results116/188 (61.7%) PCa patients had any cribriform and 36/188 (19.1%) large cribriform pattern at RP. 171/188 (91.0%) men had MRI-visible lesions; 111/116 (95.7%) tumours with any and 36/36 (100%) with large cribriform pattern were visible at MRI. PCa with any and large cribriform pattern both had lower ADC values than those without (p < 0.001). In adjusted analysis, lowest ADC value was as an independent predictor for any cribriform (Odds Ratio (OR) 0.2, 95% Confidence Interval (CI) 0.1–0.8; p = 0.01) and large cribriform pattern (OR 0.2, 95% CI 0.1–0.7; p = 0.01), while other parameters were not. ConclusionsThe majority of PCa with cribriform pattern at RP were visible at MRI, and lowest ADC value was an independent predictor for both any and large cribriform pattern.

The role of tumor density in predicting significant cancer on targeted biopsy of the prostate.

Multiparametric magnetic resonance imaging (mpMRI) is central to diagnosing prostate cancer; however, not all imaged lesions represent clinically significant tumors. We aimed to evaluate the association between the relative tumor volume on mpMRI and clinically significant prostate cancer on biopsy. We retrospectively reviewed the medical records of 340 patients who underwent combined transperineal targeted and systematic prostate biopsies between 2017 and 2021. Tumor volume was estimated based on the mpMRI diameter of suspected lesions. Relative tumor volume (tumor density) was calculated by dividing the tumor and prostate volumes. The study outcome was clinically significant cancer on biopsy. Logistic regression analyses were used to evaluate the association between tumor density and the outcome. The cutoff for tumor density was determined with ROC curves. Median estimated prostate and peripheral zone tumor volumes were 55cm3 and 0.61cm3, respectively. Median PSA density was 0.13 and peripheral zone tumor density was 0.01. Overall, 231 patients (68%) had any cancer and 130 (38%) had clinically significant cancer. On multivariable logistic regression age, PSA, previous biopsy, maximal PI-RADS score, prostate volume, and peripheral zone tumor density were significant predictors of outcome. Using a threshold of 0.006, the sensitivity, specificity, positive and negative predictive values of peripheral zone tumor density were 0.9, 0.51, 0.57, and 0.88, respectively. Peripheral zone tumor density is associated with clinically significant prostate cancer in patients with PI-RADS 4 and 5 mpMRI lesions. Future studies are required to validate our findings and evaluate the role of tumor density in avoiding unnecessary biopsies.

Comparing 12-core and 20-core biopsy for prostate cancer diagnosis with transperineal MR/US fusion biopsy: assessing the effective number of systemic cores using propensity score matching.

For transperineal (TP) prostate biopsy, target biopsy for visible lesions on MRI is important, but there is no consensus of the number of systemic biopsy cores. Our study aimed to confirm the diagnostic efficiency of 20-core systemic biopsy by comparison with 12-core using propensity score matching (PSM). The 494 patients conducted the naive TP biopsy were retrospectively analyzed. There were 293 patients with 12-core biopsy and 201 patients with 20-core biopsy. PSM was performed for minimizing confounding variables, and the established effects' value was analyzed for 'index-positive or negative' clinically significant prostate cancer (csPCa) (Index means PIRADS Score ≥ 3 on multiparametric prostate MRI). At 12-core biopsy, there were 126 cases of prostate cancer (43.0%), and 97 cases of csPCa (33.1%). At 20-core biopsy, there were 91 cases (45.3%) and 63 cases (31.3%). After propensity score matching, for index-negative csPCa, the estimated odds ratio was 4.03 (95% CI 1.35-12.09, p value 0.0128), and for index-positive csPCa, the estimated odds ratio was 0.98 (95% CI 0.63-1.52, p value 0.9308). The 20-core biopsy did not show a higher detection rate for csPCa in comparison with the 12-core biopsy. However, when MRI did not show a suspicious lesion, 20-core biopsy showed higher odd ratio in comparison with 12-core biopsy. Therefore, if there is a suspicious lesion in MRI, 20-core biopsy is excessive and 12-core biopsy is sufficient. Whereas if there is no suspicious lesion in MRI, it is better to proceed with 20-core biopsy.

Targeted Biopsy in Men High Risk for Prostate Cancer: 68Ga-PSMA PET/CT Versus mpMRI

Introduction/BackgroundTo evaluate the accuracy of 68Ga-PSMA PET/CT versus mpMRI targeted biopsy (TPBx) in the diagnosis of clinically significant prostate cancer (csPCa) in men high risk for PCa. Materials and MethodsFrom January 2021 to March 2023, 125 men with clinical parameters high risk for PCa were evaluated by mpMRI and 68Ga-PSMA PET/CT; median PSA was 32.5 ng/mL (range: 12-160 ng/mL) and 60/125 (48%) had abnormal digital rectal examination. The mpMRI lesions with PI-RADS scores ≥ 3 and/or 68Ga-PSMA areas characterized by a standardized uptake value (SUVmax) values ≥ 8 were submitted to TPBx (4 cores); in addition, all the patients underwent systematic transperineal prostate biopsy (18 cores) under sedation and antibiotic prophylaxis. ResultsIn 80 of 125 men (64%) a csPCa was found: 10 (12.5%) had a ISUP Grade Group 3 (GG), 45 (56.2%) a ISUP GG4 and 25 (31.2%) ISUP GG5. The median intraprostatic 68Ga-PSMA SUVmax was 42.3 (range:10.5-164) and 72 of 80 (90%) had a PI-RADS score ≥ 3. 68GaPSMA PET/CT showed the presence of metastases in 20 of 80 (25%) men: the median SUVmax in bone (15 cases) and nodes (40 cases) metastases was 55 and 47, respectively. Accuracy of 68Ga PSMA PET/CT (SUVmax cut-off ≥ 8) versus mpMRI PI-RADS score ≥ 3 in the diagnosis of csPCa was 92 versus 86.2%. Conclusion68GaPSMA PET/CT demonstrated a good diagnostic accuracy as a single procedure for the diagnosis and staging of high-risk PCa.

Factors affecting the selection of eligible candidates for focal therapy for prostate cancer.

Focal therapy (FT) is a treatment modality for prostate cancer that aims to reduce side effects. However, it remains difficult to select eligible candidates. We herein examined eligibility factors for hemi-ablative FT for prostate cancer. We identified 412 patients who were diagnosed with unilateral prostate cancer by biopsy and had undergone radical prostatectomy between 2009 and 2018. Among these patients, 111 underwent MRI before biopsy, had 10-20 core biopsies performed, and did not receive other treatments before surgery. Fifty-seven patients with prostate-specific antigen ≥ 15ng/mL and biopsy Gleason score (GS) ≥ 4 + 3 were excluded. The remaining 54 patients were evaluated. Both lobes of the prostate were scored using Prostate Imaging Reporting and Data System version 2 on MRI. Ineligible patients for FT were defined as those with ≥ 0.5mL GS6 or GS ≥ 3 + 4 in the biopsy-negative lobe, ≥ pT3, or lymph node involvement. Selected predictors of eligibility for hemi-ablative FT were analyzed. Among our cohort of 54 patients, 29 (53.7%) were eligible for hemi-ablative FT. A multivariate analysis identified a PI-RADS score < 3 in the biopsy-negative lobe (p = 0.016) as an independent predictor of eligibility for FT. Thirteen out of 25 ineligible patients had GS ≥ 3 + 4 tumors in the biopsy-negative lobe, half of whom (6/13) also had a PI-RADS score < 3 in the biopsy-negative lobe. The PI-RADS score in the biopsy-negative lobe may be important in the selection of eligible candidates for FT. The findings of this study will help reduce missed significant prostate cancers and improve FT outcomes.

Combination of fusion guided multiparametric MRI-transrectal US with systematic biopsy of the prostate for the detection of clinically significant prostate cancer: A prospective single-center study.

To investigate the diagnostic efficacy of fusion guided multiparametric MRI (mpMRI)-transrectal ultrasound (TRUS) biopsy versus systematic biopsy of the prostate in patients with suspicion of prostate cancer. A total of 185 patients with PI-RADS 3 lesions or higher underwent fusion guided targeted and systematic prostate biopsy. Histology of samples was correlated with PI-RADS score and biopsy method for each patient. A total of 81/185 (43.8%) cases positive for cancer were detected; 23/81 (28.4%) cases with clinically insignificant prostate cancer-insPCa and 58/81 (71.6%) cases with clinically significant prostate cancer-csPCa. There was a statistically significant difference in the overall detection of adenocarcinomas between methods (p = .035, McNemar test). Moreover, there was a statistically significant difference in the detection of insPCa between the two methods (p = .004, McNemar test). Systematic biopsy detected 13 patients with insPCa more (14.4%) than the targeted biopsy method. However, there is no statistical difference in the detection rate of csPCa between the two methods (p = 1, McNemar test). When both techniques were combined more cases of csPCa were detected. The combined implementation of fusion-guided targeted mpMRI-TRUS and systematic biopsy of the prostate provides higher detection number of csPCa, compared to each method alone. The potential of fusion-guided mpMRI-TRUS biopsy of the prostate needs to be further assessed since each method has its limitations; therefore, systematic prostate biopsy still plays an important role in clinical practice.

The value of machine learning models based on biparametric MRI for diagnosis of prostate cancer and clinically significant prostate cancer

Objective: To evaluate the value of machine learning (ML) models based on biparametric magnetic resonance imaging (bpMRI) for diagnosis of prostate cancer (PCa) and clinically significant prostate cancer (csPCa). Methods: A total of 1 368 patients, aged from 30 to 92 (69.4±8.2) years, from 3 tertiary medical centers in Jiangsu Province were retrospectively collected from May 2015 to December 2020, including 412 cases of csPCa, 242 cases of clinically insignificant prostate cancer (ciPCa) and 714 cases of benign prostate lesions. The data of center 1 and center 2 were randomly divided into training cohort and internal testing cohort at a ratio of 7∶3 by random number sampling without replacement using Python Random package, and the data of center 3 were used as the independent external testing cohort. The training cohort includs 243 cases of csPCa, 135 cases of ciPCa and 384 cases of benign lesions, the internal testing cohort includs 104 cases of csPCa, 58 cases of ciPCa and 165 cases of benign lesions, and the external testing cohort includs 65 cases of csPCa, 49 cases of ciPCa and 165 cases of benign lesions. The radiomics features were extracted on T2-weighted imaging, diffusion-weighted imaging and apparent diffusion coefficient map, and optimal radiomics features were selected by using Pearson correlation coefficient method and analysis of variance. The ML models were built using two ML algorithms, including support vector machine and random forest (RF) and were further tested in the internal testing cohort and external testing cohort. Finally, the PI-RADS scores evaluated by the radiologists were adjusted by the ML models which had superior diagnostic performance, namely adjusted PI-RADS. The receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of the ML models and PI-RADS. DeLong test was used to compare the areas under curve (AUC) of models with those of PI-RADS. Results: For PCa diagnosis, in internal testing cohort, the AUC of ML model using RF algorithm and PI-RADS were 0.869 (95%CI: 0.830-0.908) and 0.874 (95%CI: 0.836-0.913), respectively, and the difference between the model and PI-RADS did not reach to the statistical significance (P=0.793). In the external testing cohort, the AUC of model and PI-RADS were 0.845 (95%CI: 0.794-0.897) and 0.915 (95%CI: 0.880-0.951), respectively, and the difference was statistically significant (P=0.01). For csPCa diagnosis, the AUC of ML model using RF algorithm and PI-RADS were 0.874 (95%CI: 0.834-0.914) and 0.892 (95%CI: 0.857-0.927), respectively, in internal testing cohort, and the difference between the model and PI-RADS was not statistically significant (P=0.341). In the external testing cohort, the AUC of model and PI-RADS were 0.876 (95%CI: 0.831-0.920) and 0.884 (95%CI: 0.841-0.926), respectively, and the difference between the model and PI-RADS was not statistically significant (P=0.704). When PI-RADS assessment was adjusted with the assistance of ML models, the specificities increased from 63.0% to 80.0% in the internal testing cohort and from 92.7% to 93.3% in the external test group in diagnosing PCa. In diagnosing csPCa, the specificities increased from 52.5% to 72.6% in the internal testing cohort and from 75.2% to 79.9% in the external testing cohort. Conclusions: The ML models based on bpMRI showed comparable diagnostic performance to PI-RADS assessed by senior radiologists and achieved good generalization ability in both diagnosing PCa and csPCa. The specificities of the PI-RADS were improved by ML models.

Do Concomitant Systematic Biopsies Add to Fusion Targeted Biopsies in the Diagnosis and Management of Clinically Significant Prostate Cancer?

Magnetic resonance imaging targeted biopsy clearly detects more clinically significant prostate cancer than systematic biopsy. Whether concomitant systematic biopsy adds to targeted biopsy in the detection of clinically significant prostate cancer remains uncertain. The primary outcome measure of this study was to ascertain the percentage of clinically significant prostate cancer on systematic biopsy missed by targeted biopsy. Furthermore, we sought to determine whether systematic biopsy results influenced the clinical management of patients. This prospective observational study included all men undergoing Fusion targeted biopsy in our Health Board. All men had PI-RADS scores of 3-5 on magnetic resonance imaging. Histology from targeted biopsy and systematic biopsy was reviewed to determine any additional benefit of performing systematic biopsy. Clinical outcomes were also reviewed. Clinically significant prostate cancer was defined by (i) International Society of Urological Pathology ≥ 2 and (ii) UCL criteria of any primary Gleason 4 or core length ≥ 6 mm. A total of 104 men were included in the study of whom 18 patients were biopsy naïve, 65 had at least 1 previous negative biopsy, and 20 had previous biopsies that showed clinically insignificant cancer. The percentage of clinically significant prostate cancer missed on targeted biopsy was between 9.1% and 11.1%. Moreover, 17.1% of patients with clinically significant prostate cancer would not have proceeded to radical treatment if the systematic biopsy had not been performed. Our data support a growing field of evidence that although magnetic resonance imaging targeted biopsy is more sensitive than systematic biopsy at detecting clinically significant prostate cancer, systematic biopsy adds to the number of patients diagnosed with clinically significant prostate cancer in those already undergoing prostate biopsy.

Detection Rate of Prostate Cancer in Repeat Biopsy after an Initial Negative Magnetic Resonance Imaging/Ultrasound-Guided Biopsy.

A negative multiparametric magnetic resonance imaging (mpMRI)-guided prostate biopsy in patients with suspected prostate cancer (PC) results in clinical uncertainty, as the biopsy can be false negative. The clinical challenge is to determine the optimal follow-up and to select patients who will benefit from repeat biopsy. In this study, we evaluated the rate of significant PC (sPC, Gleason score ≥7) and PC detection in patients who received a follow-up mpMRI/ultrasound-guided biopsy for persistent PC suspicion after a negative mpMRI/ultrasound-guided biopsy. We identified 58 patients at our institution that underwent repeat targeted biopsy in case of PI-RADS lesions and systematic saturation biopsy between 2014 and 2022. At the initial biopsy, the median age was 59 years, and the median prostate specific antigen level was 6.7 ng/mL. Repeat biopsy after a median of 18 months detected sPC in 3/58 (5%) patients and Gleason score 6 PC in 11/58 (19%). Among 19 patients with a downgraded PI-RADS score at the follow-up mpMRI, none had sPC. In conclusion, men with an initial negative mpMRI/ultrasound-guided biopsy had a high likelihood of not harboring sPC at repeat biopsy (95%). Due to the small size of the study, further research is recommended.

Optimal Prostate Cancer Diagnostic Pathways for Men With Prostatomegaly in the MRI Era

To evaluate utilities of multiparametric MRI and targeted biopsy to detect clinically significant prostate cancer in men with prostatomegaly. We conducted a retrospective review of multiparametric MRI obtained for elevated PSA between 2017 and 2020. We selected patients with prostates ≥80g who had undergone biopsy. Clinically significant prostate cancer was defined as grade group ≥2. Predictive and logistic regression analyses quantified impacts of diagnostic components. A total of 338 patients met inclusion criteria: 89 (26.3%) had clinically significant prostate cancer. On MRI, positive predictive value for clinically significant prostate cancer was 26.5% for PIRADS 4% and 73.5% for PIRADS 5; negative predictive value for MRI without suspicious lesions was 98.8%. Applying PSA density to MRI yielded a negative predictive value of 78.9% for PIRADS 4 lesions at PSA density <0.05 and a positive predictive value of 90.5% for PIRADS 5 lesions at PSA density ≥0.15. Targeted (versus standard) biopsy reduced likelihood of missing clinically significant prostate cancer by >50% (12.2% vs 28.3%). MRI in-bore biopsies trended towards better accuracy versus MRI-transrectal ultrasound fusion biopsies (75% versus 52%). On logistic regression analyses, MRI improved predictive accuracy (area under the curve 0.91), and PIRADS score demonstrated the strongest association with clinically significant prostate cancer (odds ratio 6.42, P<.001). For large prostates, MRI is less predictive of clinically significant prostate cancer but effectively rules out malignancy. PSA density better informs biopsy decisions for PIRADS 4 and 5 lesions. There may be a pronounced role for targeted biopsy, specifically in-bore, in prostatomegaly.

Predictors of Prostate Cancer at Fusion Biopsy: The Role of Positive Family History, Hypertension, Diabetes, and Body Mass Index

PSA density and an elevated PI-RADS score are among the strongest predictors of prostate cancer (PCa) in a fusion biopsy. Positive family history, hypertension, diabetes, and obesity have also been associated with the risk of developing PCa. We aim to identify predictors of the prostate cancer detection rate (CDR) in a series of patients undergoing a fusion biopsy. We retrospectively evaluated 736 consecutive patients who underwent an elastic fusion biopsy from 2020 to 2022. Targeted biopsies (2-4 cores per MRI target) were followed by systematic mapping (10-12 cores). Clinically significant PCa (csPCa) was defined as ISUP score ≥ 2. Uni- and multi-variable logistic regression analyses were performed to identify predictors of CDR among age, body mass index (BMI), hypertension, diabetes, positive family history, PSA, a positive digital rectal examination (DRE), PSA density ≥ 0.15, previous negative biopsy status, PI-RADS score, and size of MRI lesion. The median patients' age was 71 years, and median PSA was 6.6 ng/mL. A total of 20% of patients had a positive digital rectal examination. Suspicious lesions in mpMRI were scored as 3, 4, and 5 in 14.9%, 55.0%, and 17.5% of cases, respectively. The CDR was 63.2% for all cancers and 58.7% for csPCa. Only age (OR 1.04, p < 0.001), a positive DRE (OR 1.75, p = 0.04), PSA density (OR 2.68, p < 0.001), and elevated PI-RADS score (OR 4.02, p = 0.003) were significant predictors of the CDR in the multivariable analysis for overall PCa. The same associations were found for csPCa. The size of an MRI lesion was associated with the CDR only in uni-variable analysis (OR 1.07, p < 0.001). BMI, hypertension, diabetes, and a positive family history were not predictors of PCa. In a series of patients selected for a fusion biopsy, positive family history, hypertension, diabetes, or BMI are not predictors of PCa detection. PSA-density and PI-RADS score are confirmed to be strong predictors of the CDR.

The combined role of MRI prostate and prostate health index in improving detection of significant prostate cancer in a screening population of Chinese men.

Using prostate-specific antigen (PSA) for prostate cancer (PCa) screening led to overinvestigation and overdiagnosis of indolent PCa. We aimed to investigate the value of prostate health index (PHI) and magnetic resonance imaging (MRI) prostate in an Asian PCa screening program. Men aged 50-75 years were prospectively recruited from a community-based PSA screening program. Men with PSA 4.0-10.0 ng ml -1 had PHI result analyzed. MRI prostate was offered to men with PSA 4.0-50.0 ng ml -1 . A systematic prostate biopsy was offered to men with PSA 4.0-9.9 ng ml -1 and PHI ≥35, or PSA 10.0-50.0 ng ml -1 . Additional targeted prostate biopsy was offered if they had PI-RADS score ≥3. Clinically significant PCa (csPCa) was defined as the International Society of Urological Pathology (ISUP) grade group (GG) ≥2 or ISUP GG 1 with involvement of ≥30% of total systematic cores. In total, 12.8% (196/1536) men had PSA ≥4.0 ng ml -1 . Among 194 men with PSA 4.0-50.0 ng ml -1 , 187 (96.4%) received MRI prostate. Among them, 28.3% (53/187) had PI-RADS ≥3 lesions. Moreover, 7.0% (107/1536) men were indicated for biopsy and 94.4% (101/107) men received biopsy. Among the men received biopsy, PCa, ISUP GG ≥2 PCa, and csPCa was diagnosed in 42 (41.6%), 24 (23.8%), and 34 (33.7%) men, respectively. Compared with PSA/PHI pathway in men with PSA 4.0-50.0 ng ml -1 , additional MRI increased diagnoses of PCa, ISUP GG ≥2 PCa, and csPCa by 21.2% (from 33 to 40), 22.2% (from 18 to 22), and 18.5% (from 27 to 32), respectively. The benefit of additional MRI was only observed in PSA 4.0-10.0 ng ml -1 , and the number of MRI needed to diagnose one additional ISUP GG ≥2 PCa was 20 in PHI ≥35 and 94 in PHI <35. Among them, 45.4% (89/196) men with PSA ≥4.0 ng ml -1 avoided unnecessary biopsy with the use of PHI and MRI. A screening algorithm with PSA, PHI, and MRI could effectively diagnose csPCa while reducing unnecessary biopsies. The benefit of MRI prostate was mainly observed in PSA 4.0-9.9 ng ml -1 and PHI ≥35 group. PHI was an important risk stratification step for PCa screening.

Anatomo-radiological correlation of prostate cancer: Experience within the University Hospital of Fez (about 36 cases)

Prostate cancer is a real public health problem. It is the second most common cancer in men, due to longer life expectancy, especially in developed countries. The diagnosis is confirmed by histology after the prostate biopsy, the latter also makes it possible to assess the severity by the Gleason score. Multiparametric Magnetic Resonance Imaging (MRI) currently plays an important role in the detection and localization of intra- and extra-prostatic tumor foci by combining the 3 sequences (T2 sequence, diffusion sequence, perfusion sequence). This examination thus makes it possible to evaluate the severity of the tumoral lesion through the PIRADS score. In our series, the PIRADS score varied between 3, 4 and 5. We have illustrated through a review of the literature that multiparametric MRI data are correlated with prostate biopsy data. The presence of a clearly identifiable lesion on mpMRI is correlated with an increase in the Gleason score on the prostate biopsy. In our study, it was shown that there is a statistically significant positive correlation between the PIRADS score and the Gleason score. The use of multiparametric MRI of the prostate is therefore a good means of screening, diagnosis and locoregional extension of prostate tumors. However, its use remains limited by its availability and high cost.