Prostate Imaging Reporting And Data System Research Articles

Beyond Prostate Imaging Reporting and Data System: Combining Magnetic Resonance Imaging Prostate Imaging Reporting and Data System and Prostate-Specific Membrane Antigen-Positron Emission Tomography/Computed Tomography PRIMARY Score in a Composite (P) Score for More Accurate Diagnosis of Clinically Significant Prostate Cancer.

The Prostate Imaging Reporting and Data System (PI-RADS) score is standard of care for clinically significant prostate cancer (csPCa) diagnosis. The PRIMARY score (prostate-specific membrane antigen [PSMA]-positron emission tomography [PET]/CT) also has high diagnostic accuracy for csPCa. This study aimed to develop an easily calculated combined (P) score for csPCa detection (International Society of Urological Pathology [ISUP] ≥2) incorporating separately read PI-RADS and PRIMARY scores, with external validation. Two datasets of men with suspected PCa, no prior biopsy, recent MRI and 68Ga-PSMA-11-PET/CT, and subsequent transperineal biopsy were evaluated. These included the development sample (n = 291, 56% csPCa) a prospective trial and the validation sample (n = 227, 67% csPCa) a multicenter retrospective database. Primary outcome was detection of csPCa (ISUP ≥2), with ISUP ≥ 3 cancer detection a secondary outcome. Score performance was evaluated by area under the curve, sensitivity, specificity, and decision curve analysis. The 5-point combined (P) score was developed in a prospective dataset. In the validation dataset, csPCa was identified in 0%, 20%, 52%, 96%, and 100% for P score 1 to 5. The area under the curve was 0.93 (95% CI: 0.90-0.96), higher than PI-RADS 0.89 (95% CI: 0.85-0.93, P = .039) and PRIMARY score alone 0.84 (95% CI: 0.79-0.89, P < .001). Splitting scores at 1/2 (negative) vs 3/4/5 (positive), P score sensitivity was 94% (95% CI: 89-97) compared to PI-RADS 89% (95% CI: 83-93) and PRIMARY score 86% (95% CI: 79-91). For ISUP ≥ 3, P score sensitivity was 99% (95% CI: 95-100) vs 94% (95% CI: 88-98) and 92% (95% CI: 85-97) for PI-RADS and PRIMARY scores respectively. A maximum standardized uptake value > 12 (P score 5) was ISUP ≥ 2 in all cases with 93% ISUP ≥ 3. The P score is easily calculated and improves accuracy for csPCa over both PI-RADS and PRIMARY scores. It should be considered when PSMA-PET is undertaken for diagnosis.

A preoperative scoring system for predicting the extraprostatic extension of prostate cancer following radical prostatectomy using magnetic resonance imaging and clinical factors.

We aimed to develop a preoperative prediction model for extraprostatic extension (EPE) in prostate cancer (PCa) patients following radical prostatectomy (RP) using MRI and clinical factors. This retrospective study enrolled 266 consecutive patients who underwent RP for PCa in 2022. These patients were divided into a training set (n = 187) and a test set (n = 79) through random assignment. The evaluated variables included age, prostate-specific antigen (PSA) level, prostate volume, PSA density (PSAD), index tumor length on MRI, Prostate Imaging-Reporting and Data System (PI-RADS) category, and EPE-related MRI features as defined by PI-RADS v2.1. A predictive model was constructed through multivariable logistic regression and subsequently translated into a scoring system. The performance of this scoring system in terms of prediction and calibration was assessed using C statistics and the Hosmer‒Lemeshow test. Among patients in the training and test cohorts, 74 (39.6%) and 25 (31.6%), respectively, exhibited EPE after RP. The formulated scoring system incorporated the following factors: PSAD, index tumor length, bulging prostatic contour, and tumor-capsule interface > 10mm as identified on MRI. This scoring system demonstrated strong prediction performance for EPE in both the training (C statistic, 0.87 [95% confidence interval, 0.86-0.87]) and test cohorts (C statistic, 0.85 [0.83-0.89]). Furthermore, the scoring system exhibited good calibration in both cohorts (P = 0.988 and 0.402, respectively). Our scoring system, built upon MRI features defined by the PI-RADS, offers valuable assistance in assessing the likelihood of EPE after RP.

Diagnostic performance of regional systematic biopsy for prostate cancer stratified by PI-RADS and histologic zones.

To explore the diagnostic performance of targeted biopsy (TB) combined with regional systematic biopsy (RSB) in patients with different Prostate Imaging Reporting and Data System (PI-RADS) and histologic zones for prostate lesions. This retrospective study included 1301 patients who underwent multiparametric MRI followed by combined MRI/US fusion-guided TB+systematic biopsy (SB) between January 2019 and October 2022. RSB was defined as the four perilesional SB cores adjacent to an MRI-positive lesion. Cancer detection rates were calculated for TB + SB, TB, SB, and TB + RSB, while the McNemar test was utilized for multiple comparisons among them. Subgroup analyses were performed based on different Pl-RADS and histologic zones. Of 1301 included participants (median age, 68 years; interquartile range, 63-74 years), 16,104 total biopsy cores were performed. TB + RSB detected clinically significant prostate cancer in 70.9% (922/1301) of patients, which was significantly higher than TB (67.4%, p < 0.001) or SB (67.5%, p < 0.001) but similar to TB + SB (71.0%, p = 0.50). Compared with TB + SB, TB + RSB required fewer median biopsy cores (6.3 vs. 12.4, p < 0.001) and had a higher proportion of positive cores (56.3% vs. 39.0%, p < 0.001). Subgroup analysis showed that TB had outstanding sensitivity for detecting PI-RADS 5 lesions in the PZ. Compared with TB + SB, TB + RSB achieved a similar clinically significant prostate cancer detection rate while requiring fewer biopsy cores and exhibiting higher diagnostic efficiency. For MRI-positive prostate lesions, targeted biopsy combined with regional systematic biopsy could serve as an alternative diagnostic approach to targeted biopsy combined with systematic biopsy. The scheme of prostate biopsy needs to be optimized. Regional systematic biopsy decreases the total number of cores taken. Targeted biopsies combined with regional systematic biopsies improve prostate diagnostic efficiency.

"Seeing Is Believing": Additive Utility of 68Ga-PSMA-11 PET/CT in Prostate Cancer Diagnosis.

Widespread adoption of mpMRI has led to a decrease in the number of patients requiring prostate biopsies. 68Ga-PSMA-11 PET/CT has demonstrated added benefits in identifying csPCa. Integrating the use of these imaging techniques may hold promise for predicting the presence of csPCa without invasive biopsy. A retrospective analysis of 42 consecutive patients who underwent mpMRI, 68Ga-PSMA-11 PET/CT, prostatic biopsy, and radical prostatectomy (RP) was carried out. A lesion-based model (n = 122) using prostatectomy histopathology as reference standard was used to analyze the accuracy of 68Ga-PSMA-11 PET/CT, mpMRI alone, and both in combination to identify ISUP-grade group ≥ 2 lesions. 68Ga-PSMA-11 PET/CT demonstrated greater specificity and positive predictive value (PPV), with values of 73.3% (vs. 40.0%) and 90.1% (vs. 82.2%), while the mpMRI Prostate Imaging Reporting and Data System (PI-RADS) 4-5 had better sensitivity and negative predictive value (NPV): 90.2% (vs. 78.5%) and 57.1% (vs. 52.4%), respectively. When used in combination, the sensitivity, specificity, PPV, and NPV were 74.2%, 83.3%, 93.2%, and 51.0%, respectively. Subgroup analysis of PI-RADS 3, 4, and 5 lesions was carried out. For PI-RADS 3 lesions, 68Ga-PSMA-11 PET/CT demonstrated a NPV of 77.8%. For PI-RADS 4-5 lesions, 68Ga-PSMA-11 PET/CT achieved PPV values of 82.1% and 100%, respectively, with an NPV of 100% in PI-RADS 5 lesions. A combination of 68Ga-PSMA-11 PET/CT and mpMRI improved the radiological diagnosis of csPCa. This suggests that avoidance of prostate biopsy prior to RP may represent a valid option in a selected subgroup of high-risk patients with a high suspicion of csPCa on mpMRI and 68Ga-PSMA-11 PET/CT.

A pictorial essay of PI-RADS pearls and pitfalls: toward less ambiguity and better practice.

Prostate Imaging Reporting and Data System (PI-RADS) was designed to standardize the interpretation of multiparametric magnetic resonance imaging (MRI) of the prostate, aiding in assessing the probability of clinically significant prostate cancer. By providing a structured scoring system, it enables better risk stratification, guiding decisions regarding the need for biopsy and subsequent treatment options. In this article, we explore both the strengths and weaknesses of PI-RADS, offering insights into its updated diagnostic performance and clinical applications, while also addressing potential pitfalls using diverse, representative MRI cases.

Long-term follow-up results of multiparametric prostate MRI and the prognostic value of PI-RADS: a single-center retrospective cohort study

We aim to examine the long-term outcomes of patients who underwent multiparametric prostate magnetic resonance imaging (mp-MRI) for suspected prostate cancer (PCa), specifically based on their initial Prostate Imaging Reporting and Data System (PI-RADS) categories and various clinical factors. Our secondary aim is to evaluate the prognostic value of the PI-RADS through the National Comprehensive Cancer Network (NCCN) risk group distribution. This research was conducted as a single-center retrospective cohort study in a tertiary care hospital. A total of 1,359 cases having at least one histopathological examination after the initial mp-MRI and/or adequate clinical/radiological follow-up data were included in the clinically significant PCa (cs-PCa) diagnosis-free survival analysis. Initial mp-MRI dates were accepted as the start of follow-up for the time-to-event analysis. The event was defined as cs-PCa diagnosis (International Society of Urological Pathology ≥2). Patients who were not diagnosed with cs-PCa during follow-up were censored according to predefined literature-based criteria at the end of the maximum follow-up duration with no reasonable suspicion of PCa and no biopsy indication. The impact of various factors on survival was assessed using a log-rank test and multivariable Cox regression. Subsequently, 394 cases diagnosed with PCa during follow-up were evaluated, based on initial PI-RADS categories and NCCN risk groups. Three main risk factors for cs-PCa diagnosis during follow-up were an initial PI-RADS 5 category, initial PI-RADS 4 category, and high MRI-defined PSA density (mPSAD), with average hazard ratios of 29.52, 14.46, and 3.12, respectively. The PI-RADS 3 category, advanced age group, and biopsy-naïve status were identified as additional risk factors (hazard ratios: 2.03, 1.54-1.98, and 1.79, respectively). In the PI-RADS 1-2 cohort, 1, 3, and 5-year cs-PCa diagnosis-free survival rates were 99.1%, 96.5%, and 93.8%, respectively. For the PI-RADS 3 cohort, 1, 3, and 5-year cs-PCa diagnosis-free survival rates were 94.9%, 90.9%, and 89.1%, respectively. For the PI-RADS 4 cohort, 1, 3, and 5-year cs-PCa diagnosis-free survival rates were 56.6%, 55.1%, and 55.1%, respectively. These rates were found to all be 24.2% in the PI-RADS 5 cohort. Considering the 394 cases diagnosed with PCa during follow-up, PI-RADS ≥4 cases were more likely to harbor unfavorable PCa compared to PI-RADS ≤3 cases (P < 0.001). In the PI-RADS 3 subgroup analysis, a low mPSAD (<0.15 ng/mL2) was found to be a protective prognostic factor against unfavorable PCa (P = 0.005). The PI-RADS category has a significant impact on patient management and provides important diagnostic and prognostic information. Higher initial PI-RADS categories are associated with decreased follow-up losses, a shorter time to PCa diagnosis, increased biopsy rates, a higher likelihood of developing cs-PCa during follow-up, and a worse PCa prognosis. Combining mPSAD with PI-RADS categories could enhance diagnostic stratification in the identification of cs-PCa.

Multiparametric MRI and 18F-PSMA-1007 PET/CT for the Detection of Clinically Significant Prostate Cancer.

Background Multiparametric MRI (mpMRI) is effective for detecting prostate cancer (PCa); however, there is a high rate of equivocal Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions and false-positive findings. Purpose To investigate whether fluorine 18 (18F) prostate-specific membrane antigen (PSMA) 1007 PET/CT after mpMRI can help detect localized clinically significant PCa (csPCa), particularly for equivocal PI-RADS 3 lesions. Materials and Methods This prospective study included participants with elevated prostate-specific antigen (PSA) levels referred for prostate mpMRI between September 2020 and February 2022. 18F-PSMA-1007 PET/CT was performed within 30 days of mpMRI and before biopsy. PI-RADS category and level of suspicion (LOS) were assessed. PI-RADS 3 or higher lesions at mpMRI and/or LOS 3 or higher lesions at 18F-PSMA-1007 PET/CT underwent targeted biopsies. PI-RADS 2 or lower and LOS 2 or lower lesions were considered nonsuspicious and were monitored during a 1-year follow-up by means of PSA testing. Diagnostic accuracy was assessed, with histologic examination serving as the reference standard. International Society of Urological Pathology (ISUP) grade 2 or higher was considered csPCa. Results Seventy-five participants (median age, 67 years [range, 52-77 years]) were assessed, with PI-RADS 1 or 2, PI-RADS 3, and PI-RADS 4 or 5 groups each including 25 participants. A total of 102 lesions were identified, of which 80 were PI-RADS 3 or higher and/or LOS 3 or higher and therefore underwent targeted biopsy. The per-participant sensitivity for the detection of csPCa was 95% and 91% for mpMRI and 18F-PSMA-1007 PET/CT, respectively, with respective specificities of 45% and 62%. 18F-PSMA-1007 PET/CT was used to correctly differentiate 17 of 26 PI-RADS 3 lesions (65%), with a negative and positive predictive value of 93% and 27%, respectively, for ruling out or detecting csPCa. One additional significant and one insignificant PCa lesion (PI-RADS 1 or 2) were found at 18F-PSMA-1007 PET/CT that otherwise would have remained undetected. Two participants had ISUP 2 tumors without PSMA uptake that were missed at PET/CT. Conclusion 18F-PSMA-1007 PET/CT showed good sensitivity and moderate specificity for the detection of csPCa and ruled this out in 93% of participants with PI-RADS 3 lesions. Clinical trial registration no. NCT04487847 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Turkbey in this issue.

Deep learning image reconstruction of diffusion-weighted imaging in evaluation of prostate cancer focusing on its clinical implications.

Image-based assessment of prostate cancer (PCa) is increasingly emphasized in the diagnostic workflow for selecting biopsy targets and possibly predicting clinically significant prostate cancer (csPCa). Assessment is based on Prostate Imaging-Reporting and Data System (PI-RADS) which is largely dependent on T2-weighted image (T2WI) and diffusion weighted image (DWI). This study aims to determine whether deep learning reconstruction (DLR) can improve the image quality of DWI and affect the assessment of PI-RADS ≥4 in patients with PCa. In this retrospective study, 3.0T post-biopsy prostate magnetic resonance imaging (MRI) of 70 patients with PCa in Korea University Ansan Hospital from November 2021 to July 2022 was reconstructed with and without using DLR. Four DWI image sets were made: (I) conventional DWI (CDWI): DWI with acceleration factor 2 and conventional parallel imaging reconstruction, (II) DL1: DWI with acceleration factor 2 using DLR, (III) DL2: DWI with acceleration factor 3 using DLR, and (IV) DL3: DWI with acceleration factor 3 and half average b-value using DLR. Apparent diffusion coefficient (ADC) value, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured by one reviewer, while two reviewers independently assessed overall image quality, noise, and lesion conspicuity using a four-point visual scoring system from each DWI image set. Two reviewers also performed PI-RADSv2.1 scoring on lesions suspected of malignancy. A total of 70 patients (mean age, 70.8±9.7 years) were analyzed. The image acquisition time was 4:46 min for CDWI and DL1, 3:40 min for DL2, and 2:00 min for DL3. DL1 and DL2 images resulted in better lesion conspicuity compared to CDWI images assessed by both readers (P<0.05). DLR resulted in a significant increase in SNR, from 38.4±14.7 in CDWI to 56.9±21.0 in DL1. CNR increased from 25.1±11.5 in CDWI to 43.1±17.8 in DL1 (P<0.001). PI-RADS v2.1 scoring for PCa lesions was more agreeable with the DL1 reconstruction method than with CDWI (κ value CDWI, DL1; 0.40, 0.61, respectively). A statistically significant number of lesions were upgraded from PI-RADS <4 in CDWI image to PI-RADS ≥4 in DL1 images for both readers (P<0.05). Most of the PI-RADS upgraded lesions were from higher than unfavorable intermediate-risk groups according to the 2023 National Comprehensive Cancer Network guidelines with statistically significant difference of marginal probability in DL1 and DL2 for both readers (P<0.05). DLR in DWI for PCa can provide options for improving image quality with a significant impact on PI-RADS evaluation or about a 23% reduction in acquisition time without compromising image quality.

Evaluation of prostate cancer on MRI with PI-RADS 2.1: A serial case

Background: Cancer that affects men's prostate glands is called prostate cancer. Magnetic resonance imaging (MRI) is a much more recommended method of examination because it evaluates the prostate in detail. MRI with Prostate Imaging–Reporting and Data System (PI-RADS) 2.1 can be used as a reporting system for prostate expertise and looking at the character of a lesion. This case series aims to present the prostate cancer cases on MRI with PI-RADS 2.1. Case report: First case, a 61-year-old male patient came with complaints of bloody urine and difficulty urinating. MRI results showed a well-defined lesion at the apex to mid of the peripheral zone in the right and left posteromedial sector, without extraprostatic extension, according to PI-RADS 4, and a lesion with indistinct boundaries at the apex, mid to base of the transition zone, with extraprostatic extension to the bladder, according to PI-RADS 5. The second case, a man aged 63 years with complaints of difficulty urinating and feeling incomplete for 1 month. The MRI results suggested prostatic hypertrophy with intravesical protrusion of +/- 1.2 cm with an ill-defined lesion in the mid portion of the right and left posterolateral peripheral zone, suggesting PI-RADS 4 and an ill-defined lesion at the left anterior transitional zone apex, suggesting PI-RADS 3. In the third case, a 79-year-old man came with complaints of discomfort when urinating. The MRI showed lesions with ill-defined borders on the posterior aspect of the mid-inferior portion of the right peripheral zone according to PI-RADS 5, and multiple lesions with ill-defined borders on the anteroposterior segment of the apex-inferior portion transitional zone correspond to PI-RADS 5. Conclusion: MRI with PI-RADS 2.1 can evaluate suspected malignancy in the prostate, so it can be considered as the modality of choice in evaluating malignancy in the prostate.

Biomarker vs MRI-Enhanced Strategies for Prostate Cancer Screening

Prostate cancer guidelines often recommend obtaining magnetic resonance imaging (MRI) before a biopsy, yet MRI access is limited. To date, no randomized clinical trial has compared the use of novel biomarkers for risk estimation vs MRI-based diagnostic approaches for prostate cancer screening. To evaluate biomarker-based risk estimation (Stockholm3 risk scores or prostate-specific antigen [PSA] levels) with systematic biopsies vs an MRI-enhanced strategy (PSA levels and MRI with systematic and targeted biopsy) for the detection of clinically significant prostate cancer in a screening setting. This open-label randomized clinical trial conducted in Stockholm, Sweden, between April 4, 2018, and December 10, 2020, recruited men aged 50 to 74 years with no history of prostate cancer. Participants underwent blood sampling for PSA and Stockholm3 tests to estimate their risk of clinically significant prostate cancer (Gleason score ≥3 + 4). After the blood tests were performed, participants were randomly assigned in a 2:3 ratio to receive a Stockholm3 test with systematic biopsy (biomarker group) or a PSA test followed by MRI with systematic and targeted biopsy (MRI-enhanced group). Data were analyzed from September 1 to November 5, 2023. In the biomarker group, men with a Stockholm3 risk score of 0.15 or higher underwent systematic biopsies. In the MRI-enhanced group, men with a PSA level of 3 ng/mL or higher had an MRI and those with a Prostate Imaging-Reporting and Data System (PI-RADS) score of 3 or higher (range: 1-5, with higher scores indicating a higher likelihood of clinically significant prostate cancer) underwent targeted and systematic biopsies. Primary outcome was detection of clinically significant prostate cancer (Gleason score ≥3 + 4). Secondary outcomes included detection of clinically insignificant cancer (Gleason score ≤6) and the number of biopsy procedures performed. Of 12 743 male participants (median [IQR] age, 61 [55-67] years), 5134 were assigned to the biomarker group and 7609 to the MRI-enhanced group. In the biomarker group, 8.0% of men (413) had Stockholm3 risk scores of 0.15 or higher and were referred for systematic biopsies. In the MRI-enhanced group, 12.2% of men (929) had a PSA level of 3 ng/mL or higher and were referred for MRI with biopsies if they had a PI-RADS score of 3 or higher. Detection rates of clinically significant prostate cancer were comparable between the 2 groups: 2.3% in the biomarker group and 2.5% in the MRI-enhanced group (relative proportion, 0.92; 95% CI, 0.73-1.15). More biopsies were performed in the biomarker group than in the MRI-enhanced group (326 of 5134 [6.3%] vs 338 of 7609 [4.4%]; relative proportion, 1.43 [95% CI, 1.23-1.66]), and more indolent prostate cancers were detected (61 [1.2%] vs 41 [0.5%]; relative proportion, 2.21 [95% CI, 1.49-3.27]). Findings of this randomized clinical trial indicate that combining a Stockholm3 test with systematic biopsies is comparable with MRI-based screening with PSA levels and systematic and targeted biopsies for detection of clinically significant prostate cancer, but this approach resulted in more biopsies as well as detection of a greater number of indolent cancers. In regions where access to MRI is lacking, the Stockholm3 test can aid in selecting patients for systematic prostate biopsy. ClinicalTrials.gov Identifier: NCT03377881.

Utility of transperineal template-guided mapping prostate biopsy in biopsy-naïve men with PI-RADS 1-2 on multiparametric magnetic resonance imaging

ObjectiveTo analyze the outcomes of transperineal template-guided mapping biopsy (TTMB) in biopsy-naïve men with multiparametric magnetic resonance imaging (mpMRI) results of Prostate Imaging-Reporting and Data System (PI-RADS) 1-2. Patients and methodsWe retrospectively reviewed TTMB outcomes in biopsy naïve patients with PI-RADS 1-2 at a single center from August 2018 to May 2023. The patients' clinicopathologic data were reviewed, clinically significant prostate cancer (csPCa) detection rates were identified. We determined significant predictive factors and determined those optimal cutoff point using receiver operating characteristic (ROC) curves. Results255 biopsy naïve patients with PI-RADS 1-2 underwent TTMB. 72 (28.2%) were diagnosed with prostate cancer and 30 (11.8%) were diagnosed with csPCa. ROC curves were used to identify predictive factors for diagnosing csPCa. Age (area under ROC curve [AUC]: 0.74, 95% CI: 0.65–0.83, P < 0.001) and prostate specific antigen density (PSAD) (AUC: 0.63, 95% CI: 0.53–0.72, P = 0.025) were significant predictive factors, and the optimal cutoff points determined using the Youden index were 65 years and 0.15 ng/mL/mL, respectively. ConclusionOf biopsy-naïve patients classified as PI-RADS 1–2, 11.8% were diagnosed with csPCa, and we identified age and PSAD as significant predictive factors. Our study will help determine the biopsy method for patients with PI-RADS 1–2 without biopsy experience.

Role of Multiparametric Magnetic Resonance Imaging and Targeted Biopsy in the Detection of Clinically Significant Prostate Cancer in Patients with Suspicious Digital Rectal Examination

Objectives: Few studies have examined the role of prostate MRI in patients with suspicious digital rectal examination (DRE) and/or PSA &gt; 10 ng/mL. In a cohort of non-screened patients with suspicious DRE, we investigated the rate of avoidable prostate biopsies and potentially missed clinically significant prostate cancer (csPCa) with negative MRI, and the concordance between targeted biopsy (TBx) and systematic biopsy (SBx) in detecting csPCa with positive MRI. Methods: We retrospectively examined 199 biopsy-naïve patients with suspicious DRE who underwent prostate MRI before transperineal biopsy. Prostate Imaging—Reporting and Data System (PI-RADS) v2.1 ≥ 3 category of the index lesion defined a positive MRI. Combined TBx/SBx and SBx alone were performed for positive and negative MRI, respectively. An International Society of Urogenital Pathology Grade Group ≥ 2 defined csPCa. We calculated the csPCa detection rate of TBx, SBx, and combined TBx/SBx. The Cohen kappa statistic was used to measure the concordance between TBx and SBx. Results: Ninety-one (45.7%) csPCa cases were detected. MRI was positive in 153 (76.9%) patients. In the 46 patients with negative MRI, SBx detected 5 (10.9%) csPCa cases. Prostate biopsy could, thus, be avoided in 41/199 (20.6%) patients at the cost of missing 5/91 (5.5%) csPCa cases. The concordance between TBx and SBx in detecting csPCa with positive mpMRI was substantial (k = 0.70). Specifically, 6/86 (6.9%) csPCa cases were detected with TBx, and 17/86 (19.7%) with SBx alone. Concordance was almost perfect (k = 0.82) in patients with PSA &gt; 10 ng/mL. Only 4/38 (10.5%) csPCa cases were missed by TBx, and only 1 (2.6%) csPCa case was identified by TBx alone. Conclusions: MRI in patients with suspicious DRE could avoid roughly 21% of unnecessary biopsies at the cost of missing approximately 6% of csPCa cases. Moreover, MRI and TBx complemented SBx in detecting csPCa in the subgroup with PSA &gt; 10 ng/mL.

Novel clinical risk calculator for improving cancer predictability of mpMRI fusion biopsy in prostates.

Prostate Imaging-Reporting and Data System (PI-RADS) assists in evaluating lesions on multiparametric magnetic resonance imaging (mpMRI), but there are still ongoing efforts in improving the predictive value for the presence of clinically significant PCa (csPCa) with a Gleason grade group ≥ 2 on Fusion-Biopsy. This pilot study intends to propose an easily implementable method for augmenting predictability of csPCa for PI-RADS. A cohort of 151 consecutive patients underwent mpMRI Fusion and random US Biopsy as a result of having at least one PI-RADS lesion grade 3-5 between January 1, 2019 and December 31, 2022. A single radiologist reads all films in this study applying PI-RADS V2. Of the 151 consecutive patients, 49 had a highest lesion of PI-RADS 3, 82 had a highest lesion of PI-RADS 4, and 20 had a highest lesion of PI-RADS 5. For each respective group, 12, 42, and 18 patients had proven csPCa. Two predictive models for csPCa were created by employing a logistical regression with parameters readily available to providers. The models had an AUC of 0.8133 and 0.8206, indicating promising effective models. PI-RADS classification has relevant predictability problems for grades 3 and 4. By applying the presented risk calculators, patients with PI-RADS 3 and 4 are better stratified, and thus, a significant number of patients can be spared biopsies with potential complications, such as infection and bleeding. The presented predictive models may be a valuable diagnostic tool, adding additional information in the clinical decision-making process for biopsies.

Assessment of the accuracy of biparametric MRI/TRUS fusion-guided biopsy for index tumor evaluation using postoperative pathology specimens

BackgroundMultiparametric MRI (mpMRI) is widely used for the diagnosis, surveillance, and staging of prostate cancer. However, it has several limitations, including higher costs, longer examination times, and the use of gadolinium-based contrast agents. This study aimed to investigate the accuracy of preoperatively assessed index tumors (ITs) using biparametric MRI (bpMRI)/transrectal ultrasound (TRUS) fusion biopsy compared with radical prostatectomy (RP) specimens.MethodsWe included 113 patients diagnosed with prostate cancer through bpMRI/TRUS fusion-guided biopsies of lesions with a Prostate Imaging Reporting and Data System (PI-RADS) category ≥ 3. These patients underwent robot-assisted laparoscopic radical prostatectomy (RARP) at our institution between July 2017 and March 2023. We examined the localization of preoperative and postoperative ITs, the highest Gleason score (GS), and tumor diameter in these patients.ResultsThe preoperative cT stage matched the postoperative pT stage in 53 cases (47%), while 31 cases (27%) were upstaged, and 29 cases (26%) were downstaged (Weighted Kappa = 0.21). The preoperative and postoperative IT localizations were consistent in 97 cases (86%). The concordance rate between Gleason groups in targeted biopsies and RP specimens was 51%, with an upgrade in 25 cases (23%) and a downgrade in 27 cases (25%) (Weighted Kappa = 0.42). The maximum diameter of the IT and the maximum cancer core length on biopsy were correlated with the RP tumor's maximum diameter (p < 0.001 for both).ConclusionThe diagnostic accuracy of bpMRI/TRUS fusion biopsy is comparable to mpMRI, suggesting that it can be a cost-effective and time-saving alternative.

Prediction of false-positive PI-RADS 5 lesions on prostate multiparametric MRI: development and internal validation of a clinical-radiological characteristics based nomogram

BackgroundTo develop a risk model including clinical and radiological characteristics to predict false-positive The Prostate Imaging Reporting and Data System (PI-RADS) 5 lesions.MethodsData of 612 biopsy-naïve patients who had undergone multiparametric magnetic resonance imaging (mpMRI) before prostate biopsy were collected. Clinical variables and radiological variables on mpMRI were adopted. Lesions were divided into the training and validation cohort randomly. Stepwise multivariate logistic regression analysis with backward elimination was performed to screen out variables with significant difference. A diagnostic nomogram was developed in the training cohort and further validated in the validation cohort. Calibration curve and receiver operating characteristic (ROC) analysis were also performed.Results296 PI-RADS 5 lesions in 294 patients were randomly divided into the training and validation cohort (208 : 88). 132 and 56 lesions were confirmed to be clinically significant prostate cancer in the training and validation cohort respectively. The diagnostic nomogram was developed based on prostate specific antigen density, the maximum diameter of lesion, zonality of lesion, apparent diffusion coefficient minimum value and apparent diffusion coefficient minimum value ratio. The C-index of the model was 0.821 in the training cohort and 0.871 in the validation cohort. The calibration curve showed good agreement between the estimation and observation in the two cohorts. When the optimal cutoff values of ROC were 0.288 in the validation cohort, the sensitivity, specificity, PPV, and NPV were 90.6%, 67.9%, 61.7%, and 92.7% in the validation cohort, potentially avoiding 9.7% unnecessary prostate biopsies.ConclusionsWe developed and validated a diagnostic nomogram by including 5 factors. False positive PI-RADS 5 lesions could be distinguished from clinically significant ones, thus avoiding unnecessary prostate biopsy.

3T multiparametric MRI’s accuracy in detecting prostate cancer using Prostate Imaging Reporting and Data System (PIRADS) version 2.1 with prostate biopsy as a reference

BackgroundMultiparametric magnetic resonance imaging (MRI) is valuable in detecting prostate cancer due to its high sensitivity to malignant lesions. It is commonly utilized to improve the identification of clinically significant cancers within the prostate. This study aimed to correlate the findings from 3T multiparametric MRI of the prostate using the updated Prostate Imaging Reporting and Data System version 2.1 (PIRADSv2.1) from 2019 with reference to prostate biopsy results. Additionally, PIRADSv2.1 was used to calculate the sensitivity, specificity, positive predictive value, and negative predictive value of the 3T multiparametric MRI of the prostate.Methods and materialsA retrospective study was conducted at a tertiary center, wherein we identified patients who underwent a prostate biopsy between June 2019 and June 2021 and had a corresponding MRI of the prostate performed at the same institution, evaluated with PIRADSv2.1 criteria.ResultsA total of 50 patients were eligible for final analysis. The prevalence of prostate cancer was 69% (95% confidence interval (CI) 54–81%). Receiver operating characteristic (ROC) curves were generated for 3T multiparametric MRI of the prostate using PIRADSv2.1 to diagnose prostate cancer; the area under the ROC curve was 0.81 (95% CI 0.68–0.95, p < 0.001). The sensitivity, specificity, positive predictive value, and negative predictive value of the 3T multiparametric prostate MRI using PIRADSv2.1 were 74.0%, 87.0%, 92.9%, and 59.1%, respectively.ConclusionsPIRADSv2.1 exhibited good overall performance in the diagnosis of prostate cancer.

Correlation between Prostate-Specific Antigen Levels and Prostate Imaging Reporting and Data System score: A Retrospective Study

Introduction: Prostate cancer is a prevalent and potentially lethal malignancy affecting men worldwide. To enhance early detection and accurate risk stratification, various diagnostic methods have been developed. Prostate cancer diagnoses include a digital rectal examination, prostate-specific antigen analysis and prostate biopsy in case prostate cancer is suspected. Total prostate-specific antigen (tPSA) is a widely used, first line and acceptable biomarker for prostate cancer screening. Rising tPSA levels cannot be a definitive diagnosis for prostate cancer and further examination is needed. Мagnetic resonance imaging (MRI) is an irreplaceable part of prostate cancer diagnosis. The introduction of Prostate Imaging-Reporting and Data System (PI-RADS) in MRI of prostate gland precises the cases in which performance of target biopsy is needed by classifying suspected prostate lеsions according to the probability of detecting prostate cancer. Objectivе: The objective of this study is to assess the correlation between tPSA levels and PI-RADS scores in patients who underwent MRI of the prostate gland due to elevated tPSA levels. Material and methods: A retrospective study of 374 patients medical records was carried out from January 2019 to June 2023. All patients had tPSA over 4 ng/ml and underwent MRI. Lesions were classified according to PI-RADS v2.1. Results: Patients mean age was 67.8 ± 8.2 years. Mean prostate volume was 52.67 ± 19.6 cc. 87.5 % of the patients had a negative rectal digital exam and 12.5 % had a positive one. tPSA levels ranged from 4.10 to 500 ng/ml. Patients were categorized in four groups according to their tPSA levels: group A with tPSA levels ranging from 4 to 9.9 ng/ml; group B – tPSA from 10 to 19.9 ng/ ml; group C – tPSA from 20 to 39.9 ng/ml; group D – tPSA over 40 ng/ml. MRI and PI-RADS v2 scoring were performed in all patients. 29.4 % of the MRI exams found lesions scored as PI-RADS 3, 47.1 % – as PI-RADS 4 and 22.5 % as PI-RADS 5. There were only 3 cases of lesions categorized as PI-RADS 2 in the study. These patients did not undergo a biopsy and were followed up. 33.9 % of patients in group A were c assified with PI-RADS score 3, 52.3 % – PI-RADS score 4 and 13.8 % – PI-RADS 5. In group B 1.8 %were categorized in PI-RADS score 2, 28.9 % – PI-RADS score 3, 44.7 % were PI-RADS 4 and 24.6 % PI-RADS 5. In group C the majority of patients (47.9 % and 32.6 %) had lesions classified as PI-RADS 4 and 5. In group D most of the patients` lesions – 60.7 %, were categorized as PI-RADS 5. Conclusion: There is a significant correlation between PI-RADS score and serum total PSA levels with a tendency of higher PI-RADS scores as the tPSA level reaches 10 ng/ml. Elevation of tPSa levels over 4 ng/ml requires MRI of the prostate gland and PI-RADS classification as a diagnostic and confirmation tool for further decision making.

Efficacy of Magnetic Resonance Imaging/ Ultrasound-Guided Target Biopsy in Detecting Clinically Significant Prostate Cancer

Introduction: Prostate cancer remains a formidable health challenge, demanding diagnostic strategies that balance accuracy and invasiveness. To enhance early detection and accurate risk stratification, various diagnostic methods have been developed. Magnetic Resonance Imaging (MRI) is considered the standard imaging modality for the detection and localization of prostate cancer. Prostate Imaging Reporting and Data System (PI-RADS) is a standardized system that assigns scores to suspicious lesions based on MRI findings. This system helps distinguish the likelihood of clinically significant prostate cancer (CsPCa), guiding clinicians in decision-making. Magnetic Resonance Imaging/Ultrasound-Guided fusion target biopsy (MRI/US) has emerged as a promising technique in diagnosis of prostate cancer, fusing advanced imaging modalities with real-time ultrasound guidance. Material and methods: A retrospective study was carried out from January 2019 to June 2023. Patients included in the study had elevated tPSA levels and underwent MRI of the prostate. MRI findings were characterized on the basis of PIRADS grading. All patients with a score equal or higher than PI-RADS 3 underwent MRI/US-guided fusion target biopsy. The histopathological results were retrospectively analyzed. Results: 375 patients were included in the study. The mean age of the patients in our study was 67.8 ± 8.2 years. tPSA levels ranged 17.21 ± 31.36 ng/ml and mean prostate volume was 52.67 ± 19.6 cc. 87.5 % of the patients had a negative rectal digital exam and 12.5 % had a positive one. 29.4 % of the MRI exams had lesions scored as PI-RADS 3, 47.1 % – as PI-RADS 4 and 22.5 % as PI-RADS 5. 67.1 % of detected lesions were located in the peripheral zone, 26.5 % – in the transitional zone, 4.5 % in the anterior zone and 1.6% of the lesions were apical. 35.7 % patients had a negative for carcinoma histopathological result and were diagnosed with benign prostatic hyperplasia; 39.2 % of the histopathological results were classified as low grade prostate carcinoma and 29.5 % as high grade prostate carcinoma. All results were classified according to the Gleason score. 30.1 % were Gleason score 3+3=6, 25.1 % were Gleason 7 (13.1 % as Gleason 3+4 and 12 % as 4+3), 5.1 % were Gleason 8 and 5.6 % were Gleason 4+5 or 5+4. Conclusion: The integration of MRI/US fusion biopsy into the diagnostic pathway has significantly improved the detection and characterization of clinically significant prostate cancer. This approach enables more personalized and precise management strategies for patients with prostate cancer.

Diagnostic Utility of Artificial Intelligence–assisted Transperineal Biopsy Planning in Prostate Cancer Suspected Men: A Prospective Cohort Study

Background and objectiveAccurate magnetic resonance imaging (MRI) reporting is essential for transperineal prostate biopsy (TPB) planning. Although approved computer-aided diagnosis (CAD) tools may assist urologists in this task, evidence of improved clinically significant prostate cancer (csPCa) detection is lacking. Therefore, we aimed to document the diagnostic utility of using Prostate Imaging Reporting and Data System (PI-RADS) and CAD for biopsy planning compared with PI-RADS alone. MethodsA total of 262 consecutive men scheduled for TPB at our referral centre were analysed. Reported PI-RADS lesions and an US Food and Drug Administration–cleared CAD tool were used for TPB planning. PI-RADS and CAD lesions were targeted on TPB, while four (interquartile range: 2–5) systematic biopsies were taken. The outcomes were the (1) proportion of csPCa (grade group ≥2) and (2) number of targeted lesions and false-positive rate. Performance was tested using free-response receiver operating characteristic curves and the exact Fisher-Yates test. Key findings and limitationsOverall, csPCa was detected in 56% (146/262) of men, with sensitivity of 92% and 97% (p = 0.007) for PI-RADS– and CAD-directed TPB, respectively. In 4% (10/262), csPCa was detected solely by CAD-directed biopsies; in 8% (22/262), additional csPCa lesions were detected. However, the number of targeted lesions increased by 54% (518 vs 336) and the false-positive rate doubled (0.66 vs1.39; p = 0.009). Limitations include biopsies only for men at clinical/radiological suspicion and no multidisciplinary review of MRI before biopsy. Conclusions and clinical implicationsThe tested CAD tool for TPB planning improves csPCa detection at the cost of an increased number of lesions sampled and false positives. This may enable more personalised biopsy planning depending on urological and patient preferences. Patient summaryThe computer-aided diagnosis tool tested for transperineal prostate biopsy planning improves the detection of clinically significant prostate cancer at the cost of an increased number of lesions sampled and false positives. This may enable more personalised biopsy planning depending on urological and patient preferences.

Combination of prostate volume and apparent diffusion coefficient can stratify patients with a PI-RADS score of 3 to reduce unnecessary prostate biopsies.

Nowadays, there are many patients who undergo unnecessary prostate biopsies after receiving a prostate imaging reporting and data system (PI-RADS) score of 3. Our purpose is to identify cutoff values of the prostate volume (PV) and minimum apparent diffusion coefficient (ADCmin) to stratify those patients to reduce unnecessary prostate biopsies. Data from 224 qualified patients who received prostate biopsies from January 2019 to June 2023 were collected. The Mann-Whitney U test was used to compare non-normal distributed continuous variables, which were recorded as median (interquartile ranges). The correlation coefficients were calculated using Spearman's rank correlation analysis. Categorical variables are recorded by numbers (percentages) and compared by χ2 test. Both univariate and multivariate logistic regression analysis were used to determine the independent predictors. The receiver-operating characteristic curve and the area under the curve (AUC) were used to evaluate the diagnostic performance of clinical variables. Out of a total of 224 patients, 36 patients (16.07%) were diagnosed with clinically significant prostate cancer (csPCa), whereas 72 patients (32.14%) were diagnosed with any grade prostate cancer. The result of multivariate analysis demonstrated that the PV (p < 0.001, odds ratio [OR]: 0.952, 95% confidence interval [95% CI]: 0.927-0.978) and ADCmin (p < 0.01, OR: 0.993, 95% CI: 0.989-0.998) were the independent factors for predicting csPCa. The AUC values of the PV and ADCmin were 0.779 (95% CI: 0.718-0.831) and 0.799 (95% CI: 0.740-0.849), respectively, for diagnosing csPCa. After stratifying patients by PV and ADCmin, 24 patients (47.06%) with "PV < 55 mL and ADCmin < 685 μm2/s" were diagnosed with csPCa. However, only one patient (1.25%) with PV ≥ 55 mL and ADCmin ≥ 685 μm2/s were diagnosed with csPCa. In this study, we found the combination of PV and ADCmin can stratify patients with a PI-RADS score of 3 to reduce unnecessary prostate biopsies. These patients with "PV ≥ 55 mL and ADCmin ≥ 685 μm2/s" may safely avoid prostate biopsies.