Prediction of Significant Prostate Cancer in Equivocal Magnetic Resonance Imaging Lesions: A High-volume International Multicenter Study

Optimizing biopsy decisions in PI-RADS 3 lesions: cross-institutional validation of a local clinical risk model

PURPOSE

To compare a locally developed risk model based on clinical parameters with previously published models and strategies to reduce MRI-targeted biopsies of indeterminate PI-RADS 3 lesions without missing clinically significant prostate cancer (csPCa) (ISUP ≥ grade 2).

METHODS

Retrospective, two-center study including 278 patients without prior PCa who underwent multiparametric MRI and MRI-targeted biopsy. For robust parameter estimation, a risk model based on clinical parameters was developed in a high-prevalence cohort (institution 1; n = 202; PI-RADS 3-5) and recalibrated to PI-RADS 3 subgroup (n = 115). The validation cohort (institution 2, same metropolitan area) consisted of 76 men with PI-RADS 3 index lesions. Model performance was compared to previously suggested strategies and risk models using decision curve analysis.

RESULTS

The local risk model provided the highest net benefit across all clinically relevant risk thresholds in the validation cohort. At a 10% risk threshold, the model could safely avoid biopsies in 547 per 1,000 men with PI-RADS 3 index lesions without missing csPCa, outperforming other strategies in number of biopsies avoided: normalized ADC (223), PSA density (210), MRI-ERSPC risk calculator (164), lesion volume (55) and the Radtke risk model (0). At low risk thresholds < 10% both normalized ADC (0.81) and PSA density (0.08 ng/ml/ml) were clinically useful.

CONCLUSION

A locally fit risk model based on clinical parameters could safely reduce unnecessary biopsies in men with PI-RADS 3 index lesions, with normalized ADC and PSA density providing useful and easy-to-use alternatives.

Evaluating the performance of existing tools to predict clinically significant prostate cancer in men with indeterminate lesions on biparametric MRI and development of a novel multiplex model: a prospective cohort study

Background

Indeterminate lesions on prostate MRI, such as PI-RADS 3, present a clinical challenge due to their equivocal nature, complicating biopsy decisions in men undergoing testing for prostate cancer. Understanding the predictive capacity of biomarkers and risk calculators is critical to improve clinical decision-making and reduce unnecessary biopsies.

Methods

In this prospective cohort study, men with PI-RADS 3 findings on biparametric MRI (bp-MRI) who underwent combined biopsy (fusion targeted and systematic) in the STHLM3-MRI randomised clinical trial (first- and second-rounds) and at Capio St Göran's Hospital (Capio PCC), Sweden were included, representing screening-by-invitation, repeat screening, and clinical practice cohorts, respectively. Data collection occurred between Feb 5th, 2018, and Mar 4th, 2020, for STHLM3-MRI first-round screening, between Nov 10th, 2021, and Feb 20th, 2023 for second-round screening, and between Jan 7th, 2017 and June 30th, 2023 for Capio PCC. The data was collected directly from the participating laboratories using standardized reporting forms, medical charts, and additional study-specific data collection forms filled by patients. The primary outcome was detection of clinically significant prostate cancer (csPCa; ISUP ≥2) in men with PSA ≥3 ng/mL confirmed by the combined biopsy. The predictive capacity of the evaluated biomarkers (PSA density, the Stockholm3 test, prostate volume, MRI lesion volume ratio, and Stockholm3 density), as well as seven risk calculators, was assessed via the area under the curve (AUC) computed using logistic regression. Sensitivity and specificity of detecting csPCa and high-grade prostate cancer (ISUP ≥3) were reported. Complete-case analysis was performed for men with complete data on their PSA, prostate volume, Stockholm3 test, MRI lesion volume, findings on the digital rectal examination, family history of prostate cancer, and previous biopsy. The findings were contrasted to the analysis from the imputed dataset.

Findings

Of the 6554 men included into the three cohorts, 1187 received PI-RADS score of 3 on the bp-MRI, and 1146 underwent combined biopsy. Of them, 900 had PSA ≥3 ng/mL, and 656 men were included in the complete-case analysis (169 from STHLM3-MRI first-round, 72 from the second-round, and 415 from Capio PCC). Overall, 370/900 men (41%) and 258/656 men (39%) had ISUP ≥2, but only 75/900 (8%) and 50/656 (8%) had ISUP ≥3. PSA density, tested risk calculators, and probability tests had low-to-moderate AUC (range 0.50-0.73; PSA density range 0.58-0.66, Stockholm3 range 0.59-0.67, lesion volume ratio range 0.54-0.63), and performed similarly across individual cohorts and the combined dataset in the complete-case and imputed dataset analysis. For detection of ISUP ≥2 based on STHLM3-MRI first-round, PSA density at 0.10 had a sensitivity of 69% (56%, 80%), specificity of 49% (39%, 58%), and missing 27% (6%, 61%) of ISUP ≥3, while a PSA density of 0.15 had a sensitivity of 37% (25%, 50%), specificity of 84% (76%, 90%), missing 45% (17%, 70%) of ISUP ≥3. The best-performing model based on STHLM3-MRI included age, prostate volume, Stockholm3 density and MRI lesion ratio, and reduced prostate biopsies by 33% (26%, 40%) while maintaining 98% (91%, 100%) sensitivity to detect ISUP ≥2 cancer, specificity of 50% (41%, 60%) and AUC of 0.82 (0.76, 0.87). Meanwhile, the best-performing model based on the complete-case combined dataset included age, prostate volume, PSA density, and Stockholm3 density, and reduce prostate biopsies by 26% (23%, 30%) with a sensitivity of 90% (85%, 93%), specificity of 36% (31%, 41%), and AUC of 0.70 (0.66, 0.74).

Interpretation

Current risk-stratification tools and individual biomarkers perform suboptimally for guiding biopsy decisions in men with PI-RADS 3 lesions. The findings highlight the limitations of relying on PSA density alone and emphasize the need for caution in clinical recommendations. However, multiplex models might offer possibility to reduce unnecessary biopsies while maintaining high sensitivity for clinically significant prostate cancer detection. These findings should be externally validated and evaluated for cost-effectiveness.

Funding

STHLM3-MRI clinical trial is funded by the Swedish Cancer Society (Cancerfonden), the Swedish Research Council (Vetenskapsrådet), the Swedish Research Council for Health Working Life and Welfare (FORTE), the Strategic Research Programme on Cancer (StratCan), Hagstrandska Minnesfonden, Region Stockholm, Svenska Druidorden, Åke Wibergs Stiftelse, the Swedish e-Science Research Centre, the Karolinska Institutet, and Prostatacancerförbundet.

The Role of Tumor Volume Ratio in Predicting Clinically Significant Prostate Cancer on Transperineal Biopsy

Objectives: Multiparametric magnetic resonance imaging (mpMRI) has made dramatic inroads into the management of localized prostate cancer (PCa); however, not all suspicious lesions represent clinically significant (cs) PCa. We aimed to analyze the hypothetical effect of incorporating tumor volume ratio (TVR) into prostate biopsy (PBx) decision-making. Materials and Methods: Two hundred and fifty-two patients with suspicious lesions at mpMRI undergoing transperineal PBx under local anesthesia between 2019 and 2022 were retrospectively evaluated. TVR was calculated by dividing the tumor volume by the prostate volume. A regression model was used to assess predictors of csPCa. Descriptive statistics were applied to evaluate the effect of including TVR in PBx decision-making. Results: Overall, 119 patients (47%) were found to have csPCa. Age (p < 0.001), prior negative PBx (p = 0.011), and TVR (p < 0.001) were found to be independent predictors of csPCa. Applying the TVR cutoff of 0.23, a total of 117/252 (46%) PBx would have been avoided at the cost of missing csPCa in 26 (10%) men. Conclusions: Age, previous biopsy status, and TVR were found to be independent predictors of csPCa in men with suspicious lesions at mpMRI. Implementation of TVR into PBx decision-making improves the accuracy of mpMRI. Future studies are required to validate our findings and evaluate the role of TVR in avoiding unnecessary PBx.

MRI-based risk stratification for clinically significant prostate cancer detection at biopsy: The value of zonal-specific PSA density and PSHS

PURPOSE

To explore the use of different, zonal-specific PSA density (PSAD) variants in combination with the Prostate Signal Intensity Homogeneity Score (PSHS) to improve the detection of clinically significant prostate cancer (csPCa) and thus potentially help in risk stratification and adequate patient selection for prostate biopsy.

METHODS

This retrospective, single-center study included patients with available PSA values who were suspected of having prostate cancer and underwent multiparametric MRI (mpMRI) in combination with a subsequent prostate biopsy. Histopathologic biopsy results served as reference standard. Whole-gland (PSAD-T), peripheral zone (PSAD-PZ), and transition zone (PSAD-TZ) PSA densities were computed based on MRI-derived volume assessment. The diagnostic performance of these PSAD variants in predicting csPCa was assessed using ROC analysis. Conditional inference trees were used to examine the value of combining PI-RADS, PSAD-TZ and PSHS.

RESULTS

Among the 297 patients included, 126 (42.4 %) were diagnosed with csPCa based on histopathologic biopsy results. PSAD-TZ demonstrated superior diagnostic performance (AUC 0.78) for csPCa prediction compared to PSAD-T (AUC 0.75) and PSAD-PZ (AUC 0.63). Conditional inference tree analysis revealed that patients with negative or indeterminate mpMRI (PI-RADS ≤ 3) and an elevated PSAD-TZ in combination with low PSHS scores (≤3), which indicate increased background signal intensity changes of the peripheral zone, were at an elevated risk for a missed csPCa.

CONCLUSIONS

Integrating PI-RADS, PSAD-TZ, and PSHS may enhance risk stratification for csPCa at biopsy, enabling more precise identification of patients at an elevated risk who may require further evaluation. This approach may consequently reduce false-negative MRI results and facilitate more precise decision-making regarding biopsy indications.

Using a novel PSMA-PET and PSA-based model to enhance the diagnostic accuracy for clinically significant prostate cancer and avoid unnecessary biopsy in men with PI-RADS ≤ 3 MRI

INTRODUCTION

The diagnostic evaluation of men with suspected prostate cancer (PCa) yet inconclusive MRI (PI-RADS ≤ 3) presents a common clinical challenge. [68Ga]Ga-labelled prostate-specific membrane antigen ([68Ga]Ga-PSMA) positron emission tomography/computed tomography (PET/CT) has shown promise in identifying clinically significant PCa (csPCa). We aim to establish a diagnostic model incorporating PSMA-PET to enhance the diagnostic process of csPCa in PI-RADS ≤ 3 men.

MATERIALS AND METHODS

This study retrospective included 151 men with clinical suspicion of PCa and PI-RADS ≤ 3 MRI. All men underwent [68Ga]Ga-PSMA PET/CT scans and ultrasound/MRI/PET fusion-guided biopsies. csPCa was defined as Grade Group ≥ 2. PRIMARY-scores from PSMA-PET scans were evaluated. A diagnostic model incorporating PSMA-PET and prostate-specific antigen (PSA)-derived parameters was developed. The discriminative performance and clinical utility were compared with conventional methods. Internal validation was conducted using a fivefold cross-validation with 1000 iterations.

RESULTS

In this PI-RADS ≤ 3 cohort, areas-under-the-curve (AUCs) for detecting csPCa were 0.796 (95%CI, 0.738-0.853), 0.851 (95%CI, 0.783-0.918) and 0.806 (95%CI, 0.742-0.870) for PRIMARY-score, SUVmax and routine clinical PSMA-PET assessment, respectively. The diagnostic model comprising PRIMARY-score, SUVmax and serum free PSA/total PSA (fPSA/tPSA) achieved a significantly higher AUC of 0.906 (95%CI, 0.851-0.961) compared to strategies based on PRIMARY-score or SUVmax (P < 0.05) and markedly superior to conventional strategies typically based on PSA density (P < 0.001). The average fivefold cross-validated AUC with 1000 iterations was 0.878 (95%CI, 0.820-0.954). Theoretically, using a threshold of 21.6%, the model could have prevented 78% of unnecessary biopsies while missing only 7.8% of csPCa cases in this cohort.

CONCLUSIONS

A novel diagnostic model incorporating PSMA-PET derived metrics-PRIMARY-score and SUVmax-along with serum fPSA/tPSA, has been developed and validated. The integrated model may assist clinical decision-making with enhanced diagnostic accuracy over the individual conventional metrics. It has great potential to reduce unnecessary biopsies for men with PI-RADS ≤ 3 MRI results and warrants further prospective and external evaluations.

Molecular and diffusion features for identification of clinically significant prostate cancer in PI-RADS 3 lesions

BACKGROUND

The recommendation to perform biopsy of PIRADS 3 lesions has not been adopted with strength as compared to higher scored lesions on multiparametric MRI. This represents a challenging scenario and an unmet need for clinicians to apply a risk adapted approach in these cases. In the present study, we examined clinical and radiologic characteristics in men with PI-RADS 3 index lesions that can predict csPCa on mpMRI-target biopsy.

METHODS

Revision of a prospective database with patients who underwent targeted and systematic biopsies from 2015 to 2023 for PI-RADS 3 lesions identified on mpMRI. Baseline variables were collected, such as PSA density (PSAd), 4Kscore, prostate size, and the apparent diffusion coefficient (ADC) value of the lesion on mpMRI. Logistic regression, receiver operating characteristic (ROC) and decision curve analyses (DCA) assessing the association between clinic-radiologic factors and csPCa were performed.

RESULTS

Overall, 230 patients were included in the study and the median age was 65 years. The median prostate size and PSA were 50 g and 6.26 ng/mL, respectively. 17.4% of patients had csPCa, while 27.5% had Gleason group 1. In univariable logistic analyses, we found that age, BMI, prostate size, PSAd, ADC, and 4Kscore were significant csPCa predictors (P < 0.05). PSAd showed the best prediction performance in terms of AUC (= 0.679). On multivariable analysis, PSAd and 4Kscore were associated with csPCa. The net benefit of PSAd combined with clinical features was superior to those of other parameters. Within patients with PSAd < 0.15, 4Kscore was a statistically significant predictor of csPCa (OR = 3.25, P = 0.032).

CONCLUSION

PSAd and 4Kscore are better predictors of csPCa in patients with PIRADS 3 lesions compared to ADC. The predictive role of 4Kscore is higher in patients with low PSAd. These results can assist practitioners in the risk stratification of patients with equivocal lesions to determine the need of biopsy.

Management of Patients With a Negative Multiparametric Prostate MRI Examination: AJR Expert Panel Narrative Review

Multiparametric MRI (mpMRI) of the prostate aids risk stratification of patients with elevated PSA levels. Although most clinically significant prostate cancers are detected by mpMRI, insignificant cancers are less evident. Thus, multiple international prostate cancer guidelines now endorse routine use of prostate MRI as a secondary screening test before prostate biopsy. Nonetheless, management of patients with negative mpMRI results (defined as PI-RADS category 1 or 2) remains unclear. This AJR Expert Panel Narrative Review summarizes the available literature on patients with an elevated screening PSA level and a negative prostate mpMRI result and provides guidance for these patients' management. Systematic biopsy should not be routinely performed after a negative mpMRI examination in patients at average risk but should be considered in patients at high risk. In patients who undergo PSA screening rather than systematic biopsy after negative mpMRI, clear triggers should be established for when to perform a repeat MRI examination. Patients with a negative MRI result followed by negative biopsy should follow their health care practitioners' preferred guidelines concerning subsequent PSA screening for the patient's risk level. Insufficient high-level data exist to support routine use of adjunctive serum or urine biomarkers, artificial intelligence, or PSMA PET to determine the need for prostate biopsy after a negative mpMRI examination.

Advances in multiparametric magnetic resonance imaging combined with biomarkers for the diagnosis of high-grade prostate cancer

Clinical decisions based on the test results for prostate-specific antigen often result in overdiagnosis and overtreatment. Multiparametric magnetic resonance imaging (mpMRI) can be used to identify high-grade prostate cancer (HGPCa; Gleason score ≥3 + 4); however, certain limitations remain such as inter-reader variability and false negatives. The combination of mpMRI and prostate cancer (PCa) biomarkers (prostate-specific antigen density, Proclarix, TMPRSS2:ERG gene fusion, Michigan prostate score, ExoDX prostate intelliscore, four kallikrein score, select molecular diagnosis, prostate health index, and prostate health index density) demonstrates high accuracy in the diagnosis of HGPCa, ensuring that patients avoid unnecessary prostate biopsies with a low leakage rate. This manuscript describes the characteristics and diagnostic performance of each biomarker alone and in combination with mpMRI, with the intension to provide a basis for decision-making in the diagnosis and treatment of HGPCa. Additionally, we explored the applicability of the combination protocol to the Asian population.

Interaction of patient age and high-grade prostate cancer on targeted biopsies of MRI suspicious lesions

OBJECTIVES

To evaluate the interaction of patient age and Prostate Imaging-Reporting and Data System (PI-RADS) score in determining the grade of prostate cancer (PCa) identified on magnetic resonance imaging (MRI)-targeted biopsy in older men.

PATIENTS AND METHODS

From a prospectively accrued Institutional Review Board-approved comparative study of MRI-targeted and systematic biopsy between June 2012 and December 2022, men with at least one PI-RADS ≥3 lesion on pre-biopsy MRI and no prior history of PCa were selected. Ordinal and binomial logistic regression analyses were performed.

RESULTS

A total of 2677 men met study criteria. The highest PI-RADS score was 3 in 1220 men (46%), 4 in 950 men (36%), and 5 in 507 men (19%). The median (interquartile range [IQR]) patient age was 66.7 (60.8-71.8) years, median (IQR) prostate-specific antigen (PSA) level was 6.1 (4.6-9.0) ng/mL, median (IQR) prostate volume was 48 (34-68) mL, and median (IQR) PSA density was 0.13 (0.08-0.20) ng/mL/mL. Clinically significant (cs)PCa and high-risk PCa were identified on targeted biopsy in 1264 (47%) and 321 (12%) men, respectively. Prevalence of csPCa and high-risk PCa were significantly higher in the older age groups. On multivariable analyses, patient age was significantly associated with csPCa but not high-risk PCa; PI-RADS score and the interaction of age and PI-RADS score were significantly associated with high-risk PCa but not csPCa.

CONCLUSION

In our cohort, the substantial rate of high-risk PCa on MRI-ultrasound fusion targeted biopsies in older men, and its significant association with MRI findings, supports the value of pre-biopsy MRI to localise disease that could cause cancer mortality even in older men.

Transition from Transrectal to Transperineal MRI-Fusion Prostate Biopsy Does Not Comprise Detection Rates of Clinically Significant Prostate Cancer at a Tertiary Care Center

BACKGROUND

A remarkable paradigm shift has emerged regarding the preferred prostate biopsy approach, favoring the transperineal (TP) over the transrectal (TR) approach due to the reduced risk of severe urinary tract infections. However, its impact on the detection of clinically significant prostate cancer (csPCa) remains unclear.

MATERIALS AND METHODS

We relied on a prospectively maintained tertiary care database to identify patients who underwent either TP or TR prostate biopsy between 01/2014 and 12/2023. Of those, only patients with suspicious magnetic resonance imaging (MRI) PIRADS lesions (Likert-scale: 3,4,5) received MRI-targeted and systematic biopsies. Detection rates of csPCa (International Society of Urological Pathology [ISUP] ≥ 2) were compared between biopsy approach (TP vs. TR) according to index lesion. Subsequently, uni- and multivariable logistic regression models were applied to investigate the predictive status of the biopsy approach within each subcohort.

RESULTS

Of 2063 patients, 1118 (54%) underwent combined MRI-guided and systematic prostate biopsy and were included in the final cohort. Of those, 127 (11%) and 991 (89%) underwent TP vs. TR. CsPCa rates, regardless of differences in patients' demographics and distribution of index PIRDAS lesions, did not differ statistically significantly and were 51 vs. 52%, respectively (p = 0.8). CsPCa detection rates for PIRDAS-3, PIRADS-4 and PIRADS-5 did not differ and were 24 vs. 23%, 48 vs. 51% and 72 vs. 76% for PIRADS-3, PIRADS-4 and PIRADS-5 subgroups for TP vs. TR, respectively (all p ≥ 0.9) Conclusions: The current results support the available data indicating that TP biopsy approach is comparable to transrectal biopsy approach regarding csPCa detection rates.

The Value of 68Ga-PSMA PET/MRI for Classifying Patients with PI-RADS 3 Lesions on Multiparametric MRI: A Prospective Single-Center Study

Prostate Imaging Reporting and Data System (PI-RADS) category 3 lesions remain a diagnostic challenge for detecting clinically significant prostate cancer (csPCa). This article evaluates the added value of 68Ga-labeled prostate-specific membrane antigen-11 (68Ga-PSMA) PET/MRI in classifying PI-RADS 3 lesions to avoid unnecessary biopsies. Methods: Sixty biopsy-naïve men with PI-RADS 3 lesions on multiparametric MRI were prospectively enrolled between February 2020 and October 2022. In all, 56 participants underwent 68Ga-PSMA PET/MRI and prostate systematic biopsy. 68Ga-PSMA PET/MRI was independently evaluated and reported by the 5-level PRIMARY score developed within the PRIMARY trial. Receiver-operating-characteristic curve analysis was used to estimate the diagnostic performance. Results: csPCa was detected in 8 of 56 patients (14.3%). The proportion of patients with csPCa and a PRIMARY score of 1, 2, 3, 4, and 5 was 0% (0/12), 0% (0/13), 6.3% (1/16), 38.5% (5/13), and 100% (2/2), respectively. The estimated area under the curve of the PRIMARY score was 0.91 (95% CI, 0.817-0.999). For a PRIMARY score of 4-5 versus a PRIMARY score of 1-3, the sensitivity, specificity, positive predictive value, and negative predictive value were 87.5%, 83.3%, 46.7%, and 97.5%, respectively. With a PRIMARY score of at least 4 to make a biopsy decision in men with PI-RADS 3 lesions, 40 of 48 patients (83.3%) could avoid unnecessary biopsies, at the expense of missing 1 of 8 (12.5%) csPCa cases. Conclusion: 68Ga-PSMA PET/MRI has great potential to classify patients with PI-RADS 3 lesions and help avoid unnecessary biopsies.

Elucidating the need for prostate cancer risk calculators in conjunction with mpMRI in initial risk assessment before prostate biopsy at a tertiary prostate cancer center

OBJECTIVE

Utilizing personalized risk assessment for clinically significant prostate cancer (csPCa) incorporating multiparametric magnetic resonance imaging (mpMRI) reduces biopsies and overdiagnosis. We validated both multi- and univariate risk models in biopsy-naïve men, with and without the inclusion of mpMRI data for csPCa detection.

METHODS

N = 565 men underwent mpMRI-targeted prostate biopsy, and the diagnostic performance of risk calculators (RCs), mpMRI alone, and clinical measures were compared using receiver operating characteristic curve (ROC) analysis and decision curve analysis (DCA). Subgroups were stratified based on mpMRI findings and quality.

RESULTS

csPCa was detected in 56.3%. PI-RADS score achieved the highest area under the curve (AUC) when comparing univariate risk models (AUC 0.82, p < 0.001). Multivariate RCs showed only marginal improvement in csPCa detection compared to PI-RADS score alone, with just one of four RCs showing significant superiority. In mpMRI-negative cases, the non-MRI-based RC performed best (AUC 0.80, p = 0.016), with the potential to spare biopsies for 23%. PSA-density and multivariate RCs demonstrated comparable performance for PI-RADS 3 constellation (AUC 0.65 vs. 0.60-0.65, p > 0.5; saved biopsies 16%). In men with suspicious mpMRI, both mpMRI-based RCs and the PI-RADS score predicted csPCa excellently (AUC 0.82-0.79 vs. 0.80, p > 0.05), highlighting superior performance compared to non-MRI-based models (all p < 0.002). Quality-assured imaging consistently improved csPCa risk stratification across all subgroups.

CONCLUSION

In tertiary centers serving a high-risk population, high-quality mpMRI provides a simple yet effective way to assess the risk of csPCa. Using multivariate RCs reduces multiple biopsies, especially in mpMRI-negative and PI-RADS 3 constellation.

Risk stratification of prostate cancer with MRI and prostate-specific antigen density-based tool for personalized decision making

OBJECTIVES

MRI is now established for initial prostate cancer diagnosis; however, there is no standardized pathway to avoid unnecessary biopsy in low-risk patients. Our study aimed to test previously proposed MRI-focussed and risk-adapted biopsy decision models on a real-world dataset.

METHODS

Single-centre retrospective study performed on 2055 biopsy naïve patients undergoing MRI. Diagnostic pathways included "biopsy all", "MRI-focussed" and two risk-based MRI-directed pathways. Risk thresholds were based on prostate-specific antigen (PSA) density as low (<0.10 ng mL-2), intermediate (0.10-0.15 ng mL-2), high (0.15-0.20 ng mL-2), or very high-risk (>0.20 ng mL-2). The outcome measures included rates of biopsy avoidance, detection of clinically significant prostate cancer (csPCa), missed csPCa, and overdiagnosis of insignificant prostate cancer (iPCa).

RESULTS

Overall cancer rate was 39.9% (819/2055), with csPCa (Grade-Group ≥2) detection of 30.3% (623/2055). In men with a negative MRI (Prostate Imaging-Reporting and Data System, PI-RADS 1-2), the risk of cancer was 1.2%, 2.6%, 9.0%, and 12.9% in the low, intermediate, high, and very high groups, respectively; for PI-RADS score 3 lesions, the rates were 10.5%, 14.3%, 25.0%, and 33.3%, respectively. MRI-guided pathway and risk-based pathway with a low threshold missed only 1.6% csPCa with a biopsy-avoidance rate of 54.4%, and the risk-based pathway with a higher threshold avoided 62.9% (1292/2055) of biopsies with 2.9% (61/2055) missed csPCa detection. Decision curve analysis found that the "risk-based low threshold" pathway has the highest net benefit for probability thresholds between 3.6% and 13.9%.

CONCLUSION

Combined MRI and PSA-density risk-based pathways can be a helpful decision-making tool enabling high csPCa detection rates with the benefit of biopsy avoidance and reduced iPCa detection.

ADVANCES IN KNOWLEDGE

This real-world dataset from a large UK-based cohort confirms that combining MRI scoring with PSA density for risk stratification enables safe biopsy avoidance and limits the over-diagnosis of insignificant cancers.

[Prostate cancer-multiparametric MRI and alternative approaches in intervention and therapy planning]

BACKGROUND

In recent years, multiparametric magnetic resonance imaging (mpMRI) of the prostate has gained importance and plays a crucial role in both personalized diagnostics and increasingly in the treatment planning for patients with prostate cancer.

OBJECTIVE

The aim of this study is to present established and innovative applications of MRI in the diagnosis and treatment of localized prostate cancer, evaluating their strengths and weaknesses. Furthermore, it will explore alternative approaches and compare them in a comprehensive manner.

MATERIALS AND METHODS

A systematic literature review on the application of mpMRI for biopsy and therapy planning was conducted.

RESULTS

The integration of modern imaging techniques, especially mpMRI, into the diagnostic algorithm has revolutionized prostate cancer diagnosis. MRI and MRI-guided biopsy detect more significant prostate cancer, with the potential to reduce unnecessary biopsies and the diagnosis of clinically insignificant carcinomas. In addition, MRI provides crucial information for risk stratification and treatment planning in prostate cancer patients, both before radical prostatectomy and during active surveillance.

CONCLUSION

Multiparametric MRI offers significant added value for the diagnosis and treatment of localized prostate cancer. The advancement of MRI analysis, such as the implementation of artificial intelligence algorithms, holds the potential for further enhancing imaging diagnostics.