ESUR/ESUI consensus statements on multi-parametric MRI for the detection of clinically significant prostate cancer: quality requirements for image acquisition, interpretation and radiologists' training

An online national quality assessment survey of prostate MRI reading: interreader variability in prostate volume measurement and PI-RADS classification

Background

High-quality assessment of prostate MRI is fundamental in both clinical practice and screening. There is a lack of national level data on variability in prostate volume measurement and PI-RADS assessment. Methods of quality assurance need to be developed.

Methods

All Swedish radiology departments were invited to participate in an external quality assurance of prostate MRI reading. Ten prostate MRI cases were selected by an expert panel to reflect common findings. Readers measured whole gland volume (ellipsoid formula method) and assigned a PI-RADS score in a web-based PACS with full clinical functionality. Expert consensus was used as reference standard. Descriptive statistics were used to show the distribution of volume measurements and PSA density. Reader agreement was assessed using percentages and kappa scores. A feedback document was sent to all participants upon completion of the quality assurance program.

Results

Forty-three radiologists representing 17 departments read at least 7 out of 10 cases. The median difference in prostate volume assessment compared to the reference volume for the 10 cases ranged from -23 mL to + 6 mL. Per case agreement ranged from 33 % to 86 % for the assigned PI-RADS score and from 35 % to 98 % for PI-RADS 1-3 versus PI-RADS 4-5. Interreader agreement was moderate with a median kappa score of 0.53 (IQR 0.48-0.62).

Conclusion

This online model for national quality assurance programs was feasible. Rather large per-case reader variations in prostate volume assessment and PI-RADS scoring were shown. To reduce variability in clinical practice, systematic interreader comparisons should be encouraged.

Prognostic significance of the mEPE score in intermediate-risk prostate cancer patients undergoing ultrahypofractionated robotic SBRT

PURPOSE

This study aimed to evaluate the prognostic significance of magnetic resonance imaging (MRI) parameters on biochemical failure-free survival (BFS) in patients diagnosed with intermediate-risk prostate cancer and treated with robotic ultrahypofractionated stereotactic body radiotherapy (SBRT) without androgen deprivation therapy (ADT).

METHODS

A retrospective analysis was conducted in patients with intermediate-risk prostate cancer undergoing robotic SBRT delivered in five fractions with a total radiation dose of 35-36.25 Gy. The primary endpoint was biochemical failure as defined by the Phoenix criteria. Among other clinicopathological data, T stage, Prostate Imaging-Reporting and Data System (PI-RADS) score, and multiparametric magnetic resonance imaging-based extra-prostatic extension (mEPE) score were collected and analyzed using the log-rank test.

RESULTS

A total of 74 patients were eligible for analysis. Median age at treatment was 68.8 years and median prostate volume was 47.8 cm3. Fifty-four and 14 patients were diagnosed with Gleason scores 7a and 7b, respectively. In total, 40 patients were classified as having unfavorable intermediate-risk prostate cancer according to American Urological Association/American Society for Radiation Oncology/ Society of Urologic Oncology (AUA/ASTRO/SUO) guidelines. The median follow-up was 30 months (range: 4-91.2 months; interquartile range (IQR): 18.5-48 months). The 3‑year BFS was 92%. A total of 12 (16.2%) biochemical failures were reported. In univariate analysis, an mEPE score of 5, the delivered total radiation dose (35 Gy vs. 36.25 Gy), and a prostate-specific antigen (PSA) nadir >1 ng/ml were associated with lower BFS (mEPE-BFS: p < 0.001, total radiation dose-BFS: p = 0.04, PSA nadir-BFS: p =< 0.001).

CONCLUSION

Patients diagnosed with intermediate-risk prostate cancer with a high mEPE score are more likely to experience biochemical failure after SBRT. Treatment intensification measures, such as administration of concomitant ADT, should be considered.

Advanced Restriction Imaging and Reconstruction Technology for Prostate Magnetic Resonance Imaging (ART-Pro): A Study Protocol for a Multicenter, Multinational Trial Evaluating Biparametric Magnetic Resonance Imaging and Advanced, Quantitative Diffusion Magnetic Resonance Imaging for the Detection of Prostate Cancer

Multiparametric magnetic resonance imaging (mpMRI) is strongly recommended by current clinical guidelines for improved detection of clinically significant prostate cancer (csPCa). However, the major limitations are the need for intravenous (IV) contrast and dependence on reader expertise. Efforts to address these issues include use of biparametric magnetic resonance imaging (bpMRI) and advanced, quantitative magnetic resonance imaging (MRI) techniques. One such advanced technique is the Restriction Spectrum Imaging restriction score (RSIrs), an imaging biomarker that has been shown to improve quantitative accuracy of patient-level csPCa detection. Advanced Restriction imaging and reconstruction Technology for Prostate MRI (ART-Pro) is a multisite, multinational trial that aims to evaluate whether IV contrast can be avoided in the setting of standardized, state-of-the-art image acquisition, with or without addition of RSIrs. Additionally, RSIrs will be evaluated as a stand-alone, quantitative, objective biomarker. ART-Pro will be conducted in two stages and will include a total of 500 patients referred for multiparametric prostate MRI with a clinical suspicion of prostate cancer at the participating sites. ART-Pro-1 will evaluate bpMRI, mpMRI, and RSIrs on the accuracy of expert radiologists' detection of csPCa and will evaluate RSIrs as a stand-alone, quantitative, objective biomarker. ART-Pro-2 will evaluate the same MRI techniques on the accuracy of nonexpert radiologists' detection of csPCa, and findings will be evaluated against the expertly created dataset from ART-Pro-1. The primary endpoint is to evaluate whether bpMRI is noninferior to mpMRI among expert (ART-Pro-1) and nonexpert (ART-Pro-2) radiologists for the detection of grade group ≥2 csPCa. This trial is registered in the US National Library of Medicine Trial Registry (NCT number: NCT06579417) at ClinicalTrials.gov. Patient accrual at the first site (UC San Diego) began in December 2023. Initial results are anticipated by the end of 2026.

Automated 24-sector grid-map algorithm for prostate mpMRI improves precision and efficacy of prostate lesion location reporting

BACKGROUND

The Prostate Imaging-Reporting and Data System (PI-RADS) calls for reporting the prostate index lesion and the location within the transition (TZ) or peripheral zone (PZ) and location on a corresponding sector map. The aim of this study was to train a deep learning DL-based algorithm for automatic prostate sector mapping and to validate its' performance.

METHODS

An automatic 24-sector grid-map (ASG) of the prostate was developed, based on an automatic zone-specific deep learning segmentation of the prostate. To evaluate the efficacy of the method, fiducials for random locations within the prostate were placed, and the corresponding sectors were determined for 50 mpMRI datasets. The reference standard was defined in a consensus read by two expert uroradiologists. Annotated fiducial locations were evaluated automatically by the ASG and by four radiologists in two reads with and without the help of a superimposed sector grid-map and the success rate was compared.

RESULTS

The ASG algorithm identified the correct prostate sector of the annotated lesions in 80 % (40/50 reads) of the cases and outperformed readings of the four radiologists with 55 % (109/200), p < 0.0001. The added use of the 24 ASG map significantly improved the rate of correct sector annotation for the four radiologists to 71 % (141/200), p < 0.004.

CONCLUSION

The 24 ASG map was effective for prostate sector segmentation and significantly improved location reporting of prostate lesions.

Histopathologic Features and Transcriptomic Signatures Do Not Solve the Issue of Magnetic Resonance Imaging-Invisible Prostate Cancers: A Matched-Pair Analysis

BACKGROUND

Multiparametric magnetic resonance imaging (mpMRI) is pivotal in prostate cancer (PCa) diagnosis, but some clinically significant (cs) PCa remain undetected. This study aims to understand the pathological and molecular basis for csPCa visibility at mpMRI.

METHODS

We performed a retrospective matched-pair cohort study, including patients undergoing radical prostatectomy (RP) for csPCa (i.e., ISUP grade group ≥ 2) from 2015 to 2020, in our tertiary-referral center. We screened for inclusion in the "mpMRI-invisible" cohort all consecutive men (N = 45) having a negative preoperative mpMRI. The "mpMRI-visible" cohort was matched based on age, PSA, prostate volume, ISUP grade group. Included patients underwent radiological and pathological open-label revisions and characterization of the tumor mRNA expression profile (analyzing 780 gene transcripts, signaling pathways, and cell-type profiling). We compared the clinical-pathological variables and the gene expression profile between matched pairs. The analysis was stratified according to histological characteristics and lesion diameter.

RESULTS

We included 34 patients (17 per cohort); mean age at RP and PSA were 70.5 years (standard deviation [SD] = 7.7), 7.1 ng/mL (SD = 3.3), respectively; 65% of men were ISUP 2. Overall, no significant differences in histopathological features, tumor diameter and location, mRNA profile, pathways, and cell-type scores emerged between cohorts. In the stratified analysis, an upregulation of cell adhesion and motility, of extracellular matrix remodeling and of metastatic process pathways was present in specific subgroups of mpMRI-invisible cancers.

CONCLUSIONS

No PCa pathological or gene-expression hallmarks explaining mp-MRI invisibility were identified. Aggressive features can be present both in mpMRI-invisible and -visible tumors.

Strategies for improving image quality in prostate MRI

Prostate magnetic resonance imaging (MRI) stands as the cornerstone in diagnosing prostate cancer (PCa), offering superior detection capabilities while minimizing unnecessary biopsies. Despite its critical role, global disparities in MRI diagnostic performance persist, stemming from variations in image quality and radiologist expertise. This manuscript reviews the challenges and strategies for enhancing image quality in prostate MRI, spanning patient preparation, MRI unit optimization, and radiology team engagement. Quality assurance (QA) and quality control (QC) processes are pivotal, emphasizing standardized protocols, meticulous patient evaluation, MRI unit workflow, and radiology team performance. Additionally, artificial intelligence (AI) advancements offer promising avenues for improving image quality and reducing acquisition times. The Prostate-Imaging Quality (PI-QUAL) scoring system emerges as a valuable tool for assessing MRI image quality. A comprehensive approach addressing technical, procedural, and interpretative aspects is essential to ensure consistent and reliable prostate MRI outcomes.

Factors of interobserver variability in prostate tumor MRI delineation: impact of PI-QUAL score

BACKGROUND

Prostate cancer ranks as the second most common cancer in men worldwide. Dose escalation to the tumor and/or the prostate improves biochemical recurrence-free survival. However, interobserver variability in lesion contouring poses a significant limitation to such therapeutic approaches. Therefore, a study of factors influencing this variability is necessary.

MATERIALS AND METHODS

Three independent readers delineated the index prostate lesion (DIL) using T2w and ADC sequences for each patient. Clinical data were retrospectively collected for all participants. Logistic regression analysis was employed to examine the correlation between clinical features and a mean DICE coefficient > 0.7. Features exhibiting a p value < 0.05 on univariate analysis were subjected to multivariate analysis.

RESULTS

The study comprised 68 patients, with a median DICE coefficient of 0.69 (95% CI 0.65-0.71), wherein 42.6% (29/68) attained a mean DICE > 0.7. Univariate analysis identified the PI-QUAL score, maximum diameter of DIL, and mean DIL volume as significant (p < 0.05) predictors. In multivariate analysis, only the PI-QUAL score (p = 0.008) remained statistically associated with a DICE coefficient > 0.7.

CONCLUSION

The PI-QUAL score emerges as the primary predictive factor for minimizing inter-reader variability in intraprostatic dominant lesion segmentation. These findings underscore the importance of considering PI-QUAL scores when devising focal treatment plans. Adoption of a multi-reader approach involving diverse medical specialists (radiologists, radiotherapists, urologists) is advocated, particularly for MRIs with low PI-QUAL scores.

CLINICAL RELEVANCE STATEMENT

Radiotherapy is a major treatment for patients with localized prostate cancer. Dose escalation to the tumor leads to improved cancer control. Precise delineation of the dominant intraprostatic lesion (DIL) remains a limitation to focal treatments. Features influencing inter-reader variability were never evaluated. In this study, we identified that the PI-QUAL score was the sole predictor of the inter-reader delineation variability of the DIL.

Concordance Between the Expert Reading of Biparametric-MRI and the Nonexpert Multiparametric-MRI for the Detection of Clinically Significant Prostate Cancer: Clinical Implications

PURPOSE

Prostate-magnetic resonance imaging (MRI) interpretation is challenging, with expertise playing a crucial role. Biparametric MRI (bpMRI) is gaining popularity in experienced centers due to its time and cost advantages over multiparametric MRI (mpMRI). We aim to analyze concordance between nonexpert radiologist PI-RADS from mpMRI and expert radiologist PI-RADS from bpMRI, and its clinical implications.

MATERIAL AND METHODS

222 men suspected of having prostate cancer (PCa) and mpMRI reported by nonexpert radiologists were referred to a reference center for transperineal MRI-TRUS fusion biopsy where an expert radiologist reported bpMRI PI-RADS 2.1 and segmentation, blinded to external mpMRI. Mapping targeted suspected lesions and 12-core systematic biopsies were performed. Clinically significant PCa (csPCa) was diagnosed when ISUP-grade group was ≥2.

RESULTS

Concordance between both PI-RADS existed in 49.1% of cases (Kappa index 0.288). In 102 cases (45.9%), expert reclassification to lower PI-RADS existed, while an increase existed in 11 cases (5.0%), P < .001. Agreement existed in 30.8% of nonexpert PI-RADS 3, 43.6% of PI-RADS 4, and 83.7% of PI-RADS 5, P < .001. Potential clinical implications included 27% reduction in prostate biopsies when using expert bpMRI readings compared to nonexpert mpMRI readings (P < 0.001), while undetected csPCa were 4.2% and 3.4%, respectively, P = .669. Over-detection reduction of insignificant PCa was 29.4% and 0%, respectively, P = .034.

CONCLUSIONS

Concordance between nonexpert PI-RADS mpMRI and expert PI-RADS bpMRI was low, increasing with nonexpert PI-RADS. Expert reclassification would reduce prostate biopsies by more than one quarter and over-detection of iPCa, while csPCa detection remained similar.

PI-QUAL version 2 image quality categorisation and inter-reader agreement compared to version 1

OBJECTIVES

Prostate imaging quality (PI-QUAL) was developed to standardise the evaluation of prostate MRI quality and has recently been updated to version 2. This study aims to assess inter-reader agreement for PI-QUAL v1 and v2 scores and investigates changes in MRI quality score categories.

MATERIALS AND METHODS

The study retrospectively analysed 350 multiparametric MRI (mpMRI) scans. Two expert uroradiologists independently assessed mpMRI quality using PI-QUAL v1 and v2 guidelines. Biparametric MRI (bpMRI) categorisation based on PI-QUAL v2 included only T2WI and diffusion-weighted imaging (DWI) results. Inter-reader agreement was determined using percentage agreement and kappa, and categorisation comparisons were made using the chi-square test.

RESULTS

Substantial inter-reader agreement was observed for the overall PI-QUAL v1 score (κ = 0.64) and moderate agreement for v2 mpMRI (κ = 0.54) and v2 bpMRI scores (κ = 0.57). Inter-reader agreements on individual sequences were similar between v1 and v2 (kappa for individual sequences: T2WI, 0.46 and 0.49; DWI, 0.66 and 0.70; DCE, 0.71 and 0.61). Quality levels shifted from predominantly "optimal" in v1 (65%) down to "acceptable" using v2 (55%); p < 0.001. The addition of DCE increased the proportion of cases with at least "adequate" quality at mpMRI (64%) compared to bpMRI (30%); p < 0.001.

CONCLUSION

This study shows consistent inter-reader agreement between PI-QUAL v1 and v2, encompassing overall and individual sequence categorisation. A notable shift from "optimal" to "acceptable" quality was demonstrated when moving from v1 to v2, with DCE tending improving quality from "inadequate" (bpMRI) to "acceptable" (mpMRI).

KEY POINTS

Question What are the agreement levels of image quality of prostate MRI by using PI-QUAL v1 and v2? Findings Inter-reader agreement based on PI-QUAL v1 and v2 is comparable. Dynamic contrast enhancement (DCE) enables an overall shift from inadequate quality (at bpMRI) to acceptable quality (mpMRI). Clinical relevance The inter-reader agreement on PI-QUAL v1 and v2 is equivalent. PI-QUAL v2 assesses prostate bpMRI as well as mpMRI quality. Transitioning from inadequate to acceptable between v2-bpMRI and v2-mpMRI highlights the role of DCE as an "image quality safety net."

Follow-up on patients with initial negative mpMRI target and systematic biopsy for PI-RADS ≥ 3 lesions - an EAU-YAU study enhancing prostate cancer detection

PURPOSE

To investigate the detection and predictors of prostate cancer (PCA) and clinically significant prostate cancer (csPCA) in patients with positive multiparametric MRI (mpMRI) followed by a negative MRI - guided target biopsy (TB) and systematic biopsy (SB).

MATERIALS AND METHODS

This retrospective multicenter study included 694 patients from 10 tertiary referral centers with an initial positive mpMRI (PI-RADS ≥ 3) and negative results on both MRI-TB and SB. Patients were classified into three groups based on follow-up: Group 1 (prostate re-biopsy without new mpMRI), Group 2 (standardized second prostate mpMRI and subsequent re-biopsy), and Group 3 (follow-up with mpMRIs and biopsy based on clinical and radiological triggers). The primary outcomes were the detection of any PCA and csPCA during follow up. Study groups were compared according to their probability of PCA and csPCA assessed with the ERSPC-MRI risk calculator. Statistical analysis included Kaplan - Meier analysis, Cox regression, and multivariable analysis for the detection of (cs)PCa.

RESULTS

The overall detection of PCA and csPCA was 26.8% and 19.3%, respectively, with varying rates in different PI-RADS groups. Group 3 had the highest 2-year and 5-year PCA-free survival (94 and 84%) and csPCA - free survival (96 and 86%). Multivariable analysis revealed a significantly higher risk of PCA and csPCA in Group 1 and 2 compared to Group 3 (p < 0.01). Clinical and radiological predictors for PCA and csPCA included higher age, prostate volume, PI-RADS score, the presence of atypical small acinar proliferation (ASAP), and a smaller number of TB and SB performed during the initial biopsy. Study limitations, include the retrospective design and reliance on clinical and radiological triggers for follow-up decisions.

CONCLUSIONS

Patients with positive mpMRI but negative TB and SB results exhibit varying rates of PCA and csPCA depending on the follow up scheme. Tailored follow-up strategies are essential for optimal management in this clinical scenario.

PI-QUAL version 2: an update of a standardised scoring system for the assessment of image quality of prostate MRI

Multiparametric MRI is the optimal primary investigation when prostate cancer is suspected, and its ability to rule in and rule out clinically significant disease relies on high-quality anatomical and functional images. Avenues for achieving consistent high-quality acquisitions include meticulous patient preparation, scanner setup, optimised pulse sequences, personnel training, and artificial intelligence systems. The impact of these interventions on the final images needs to be quantified. The prostate imaging quality (PI-QUAL) scoring system was the first standardised quantification method that demonstrated the potential for clinical benefit by relating image quality to cancer detection ability by MRI. We present the updated version of PI-QUAL (PI-QUAL v2) which applies to prostate MRI performed with or without intravenous contrast medium using a simplified 3-point scale focused on critical technical and qualitative image parameters. CLINICAL RELEVANCE STATEMENT: High image quality is crucial for prostate MRI, and the updated version of the PI-QUAL score (PI-QUAL v2) aims to address the limitations of version 1. It is now applicable to both multiparametric MRI and MRI without intravenous contrast medium. KEY POINTS: High-quality images are essential for prostate cancer diagnosis and management using MRI. PI-QUAL v2 simplifies image assessment and expands its applicability to prostate MRI without contrast medium. PI-QUAL v2 focuses on critical technical and qualitative image parameters and emphasises T2-WI and DWI.

Rationale for adopting a combination of monoparametric MRI with the prostate-specific antigen in detecting clinically significant prostate cancer: comparison with standard biparametric and multiparametric MRI

OBJECTIVES

To compare prostate monoparametric MRI (monoMRI), which uses only diffusion-weighted imaging (DWI), with biparametric (bpMRI) and multiparametric MRI (mpMRI) in detecting clinically significant cancer (CSC) and to evaluate the effect of the combination of monoMRI results and prostate-specific antigen (PSA) level.

METHODS

In this study, 193 patients (average age 70.5 years; average PSA 7.9 ng/mL) underwent prebiopsy MRI and subsequent prostate biopsy from January 2020 to February 2022. Two radiologists independently reviewed the 3 MRI protocols using the Prostate Imaging Reporting and Data System (PI-RADS). Interreader agreement was assessed using the intraclass correlation coefficient (ICC), and diagnostic performance was evaluated with receiver operating characteristic (ROC) curve analysis. The Youden index was used to determine the new cutoff value of PSA for detecting CSCs in patients with negative monoMRI results.

RESULTS

CSC was confirmed in 109 patients (56.5%). The interreader agreement on monoMRI (ICC = 0.798) was comparable to that on bpMRI and mpMRI (ICC = 0.751 and 0.714, respectively). ROC curve analysis of the 3 protocols revealed no difference in detecting CSCs (P > 0.05). Applying a new PSA cutoff value (9.5 and 7.4 ng/mL, respectively) in monoMRI-negative patients improved the sensitivity of monoMRI from 89.9% to 96.3% for Reader 1, and from 95.4% to 99.1% for Reader 2.

CONCLUSIONS

MonoMRI based solely on DWI demonstrated similar diagnostic performance to bpMRI and mpMRI in detecting CSCs, and the combination of PSA level with monoMRI has the potential to effectively triage patients with a high likelihood of CSCs.

ADVANCES IN KNOWLEDGE

Monoparametric MRI conducted only with diffusion-weighted imaging (DWI), may show comparable performance to biparametric and multiparametric MRI in detecting clinically significant prostate cancer. In patients with negative monoparametric MRI results, implementing a new PSA cutoff value to determine the need for a biopsy could decrease the number of missed prostate cancer.

A pilot study of AI-assisted reading of prostate MRI in Organized Prostate Cancer Testing

OBJECTIVES

To evaluate the feasibility of AI-assisted reading of prostate magnetic resonance imaging (MRI) in Organized Prostate cancer Testing (OPT).

METHODS

Retrospective cohort study including 57 men with elevated prostate-specific antigen (PSA) levels ≥3 µg/L that performed bi-parametric MRI in OPT. The results of a CE-marked deep learning (DL) algorithm for prostate MRI lesion detection were compared with assessments performed by on-site radiologists and reference radiologists. Per patient PI-RADS (Prostate Imaging-Reporting and Data System)/Likert scores were cross-tabulated and compared with biopsy outcomes, if performed. Positive MRI was defined as PI-RADS/Likert ≥4. Reader variability was assessed with weighted kappa scores.

RESULTS

The number of positive MRIs was 13 (23%), 8 (14%), and 29 (51%) for the local radiologists, expert consensus, and DL, respectively. Kappa scores were moderate for local radiologists versus expert consensus 0.55 (95% confidence interval [CI]: 0.37-0.74), slight for local radiologists versus DL 0.12 (95% CI: -0.07 to 0.32), and slight for expert consensus versus DL 0.17 (95% CI: -0.01 to 0.35). Out of 10 cases with biopsy proven prostate cancer with Gleason ≥3+4 the DL scored 7 as Likert ≥4.

INTERPRETATION

The Dl-algorithm showed low agreement with both local and expert radiologists. Training and validation of DL-algorithms in specific screening cohorts is essential before introduction in organized testing.

Evaluating Biparametric Versus Multiparametric Magnetic Resonance Imaging for Diagnosing Clinically Significant Prostate Cancer: An International, Paired, Noninferiority, Confirmatory Observer Study

BACKGROUND AND OBJECTIVE

Biparametric magnetic resonance imaging (bpMRI), excluding dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), is a potential replacement for multiparametric MRI (mpMRI) in diagnosing clinically significant prostate cancer (csPCa). An extensive international multireader multicase observer study was conducted to assess the noninferiority of bpMRI to mpMRI in csPCa diagnosis.

METHODS

An observer study was conducted with 400 mpMRI examinations from four European centers, excluding examinations with prior prostate treatment or csPCa (Gleason grade [GG] ≥2) findings. Readers assessed bpMRI and mpMRI sequentially, assigning lesion-specific Prostate Imaging Reporting and Data System (PI-RADS) scores (3-5) and a patient-level suspicion score (0-100). The noninferiority of patient-level bpMRI versus mpMRI csPCa diagnosis was evaluated using the area under the receiver operating curve (AUROC) alongside the sensitivity and specificity at PI-RADS ≥3 with a 5% margin. The secondary outcomes included insignificant prostate cancer (GG1) diagnosis, diagnostic evaluations at alternative risk thresholds, decision curve analyses (DCAs), and subgroup analyses considering reader expertise. Histopathology and ≥3 yr of follow-up were used for the reference standard.

KEY FINDINGS AND LIMITATIONS

Sixty-two readers (45 centers and 20 countries) participated. The prevalence of csPCa was 33% (133/400); bpMRI and mpMRI showed similar AUROC values of 0.853 (95% confidence interval [CI], 0.819-0.887) and 0.859 (95% CI, 0.826-0.893), respectively, with a noninferior difference of -0.6% (95% CI, -1.2% to 0.1%, p < 0.001). At PI-RADS ≥3, bpMRI and mpMRI had sensitivities of 88.6% (95% CI, 84.8-92.3%) and 89.4% (95% CI, 85.8-93.1%), respectively, with a noninferior difference of -0.9% (95% CI, -1.7% to 0.0%, p < 0.001), and specificities of 58.6% (95% CI, 52.3-63.1%) and 57.7% (95% CI, 52.3-63.1%), respectively, with a noninferior difference of 0.9% (95% CI, 0.0-1.8%, p < 0.001). At alternative risk thresholds, mpMRI increased sensitivity at the expense of reduced specificity. DCA demonstrated the highest net benefit for an mpMRI pathway in cancer-averse scenarios, whereas a bpMRI pathway showed greater benefit for biopsy-averse scenarios. A subgroup analysis indicated limited additional benefit of DCE MRI for nonexperts. Limitations included that biopsies were conducted based on mpMRI imaging, and reading was performed in a sequential order.

CONCLUSIONS AND CLINICAL IMPLICATIONS

It has been found that bpMRI is noninferior to mpMRI in csPCa diagnosis at AUROC, along with the sensitivity and specificity at PI-RADS ≥3, showing its value in individuals without prior csPCa findings and prostate treatment. Additional randomized prospective studies are required to investigate the generalizability of outcomes.

Perspectives on technology: Prostate Imaging-Reporting and Data System (PI-RADS) interobserver variability

OBJECTIVES

To explore the topic of Prostate Imaging-Reporting and Data System (PI-RADS) interobserver variability, including a discussion of major sources, mitigation approaches, and future directions.

METHODS

A narrative review of PI-RADS interobserver variability.

RESULTS

PI-RADS was developed in 2012 to set technical standards for prostate magnetic resonance imaging (MRI), reduce interobserver variability at interpretation, and improve diagnostic accuracy in the MRI-directed diagnostic pathway for detection of clinically significant prostate cancer. While PI-RADS has been validated in selected research cohorts with prostate cancer imaging experts, subsequent prospective studies in routine clinical practice demonstrate wide variability in diagnostic performance. Radiologist and biopsy operator experience are the most important contributing drivers of high-quality care among multiple interrelated factors including variability in MRI hardware and technique, image quality, and population and patient-specific factors such as prostate cancer disease prevalence. Iterative improvements in PI-RADS have helped flatten the curve for novice readers and reduce variability. Innovations in image quality reporting, administrative and organisational workflows, and artificial intelligence hold promise in improving variability even further.

CONCLUSION

Continued research into PI-RADS is needed to facilitate benchmark creation, reader certification, and independent accreditation, which are systems-level interventions needed to uphold and maintain high-quality prostate MRI across entire populations.

Reduction of false positives using zone-specific prostate-specific antigen density for prostate MRI-based biopsy decision strategies

OBJECTIVES

To develop and test zone-specific prostate-specific antigen density (sPSAD) combined with PI-RADS to guide prostate biopsy decision strategies (BDS).

METHODS

This retrospective study included consecutive patients, who underwent prostate MRI and biopsy (01/2012-10/2018). The whole gland and transition zone (TZ) were segmented at MRI using a retrained deep learning system (DLS; nnU-Net) to calculate PSAD and sPSAD, respectively. Additionally, sPSAD and PI-RADS were combined in a BDS, and diagnostic performances to detect Grade Group ≥ 2 (GG ≥ 2) prostate cancer were compared. Patient-based cancer detection using sPSAD was assessed by bootstrapping with 1000 repetitions and reported as area under the curve (AUC). Clinical utility of the BDS was tested in the hold-out test set using decision curve analysis. Statistics included nonparametric DeLong test for AUCs and Fisher-Yates test for remaining performance metrics.

RESULTS

A total of 1604 patients aged 67 (interquartile range, 61-73) with 48% GG ≥ 2 prevalence (774/1604) were evaluated. By employing DLS-based prostate and TZ volumes (DICE coefficients of 0.89 (95% confidence interval, 0.80-0.97) and 0.84 (0.70-0.99)), GG ≥ 2 detection using PSAD was inferior to sPSAD (AUC, 0.71 (0.68-0.74)/0.73 (0.70-0.76); p < 0.001). Combining PI-RADS with sPSAD, GG ≥ 2 detection specificity doubled from 18% (10-20%) to 43% (30-44%; p < 0.001) with similar sensitivity (93% (89-96%)/97% (94-99%); p = 0.052), when biopsies were taken in PI-RADS 4-5 and 3 only if sPSAD was ≥ 0.42 ng/mL/cc as compared to all PI-RADS 3-5 cases. Additionally, using the sPSAD-based BDS, false positives were reduced by 25% (123 (104-142)/165 (146-185); p < 0.001).

CONCLUSION

Using sPSAD to guide biopsy decisions in PI-RADS 3 lesions can reduce false positives at MRI while maintaining high sensitivity for GG ≥ 2 cancers.

CLINICAL RELEVANCE STATEMENT

Transition zone-specific prostate-specific antigen density can improve the accuracy of prostate cancer detection compared to MRI assessments alone, by lowering false-positive cases without significantly missing men with ISUP GG ≥ 2 cancers.

KEY POINTS

• Prostate biopsy decision strategies using PI-RADS at MRI are limited by a substantial proportion of false positives, not yielding grade group ≥ 2 prostate cancer. • PI-RADS combined with transition zone (TZ)-specific prostate-specific antigen density (PSAD) decreased the number of unproductive biopsies by 25% compared to PI-RADS only. • TZ-specific PSAD also improved the specificity of MRI-directed biopsies by 9% compared to the whole gland PSAD, while showing identical sensitivity.

Application value of magnetic resonance spectroscopy imaging in the diagnosis of prostate cancer

Magnetic resonance spectroscopy (MRSI) can distinguish between benign and malignant prostate diseases. This study investigated the potential of MRSI for diagnosing prostate cancer and guiding prostate biopsy. We retrospectively reviewed 234 patients with suspected prostate cancer who underwent MRSI with targeted prostate biopsy. Patients were divided into two groups according to their puncture pathology: prostate cancer (n = 103, 44.02%) and benign prostatic disease (n = 131, 55.98%). The t-test, Mann-Whitney U test, or chi-square test was used to compare the groups. The diagnostic abilities of MRSI, prostate-specific antigen level, digital rectal examination, and magnetic resonance imaging without contrast for prostate cancer were compared using the area under the receiver operating characteristic curve (AUC-ROC); the ARC-ROC values were 0.831, 0.768, 0.692, and 0.656, respectively. The AUC-ROC value for diagnosing prostate cancer using the CC/c ratio was 0.853. CC/c ratio > 0.97 was identified as the optimal threshold for diagnosing prostate cancer (sensitivity, 86.5%; specificity, 78.6%; Youden index, 0.651). Spearman correlation analysis revealed a correlation between the CC/c ratio and Gleason score (r = 0.737, p < 0.001). Using the CC/c ratio of MRSI as an adjunct to targeted prostate biopsy can improve the detection rate of positive biopsies and evaluate prostate cancer invasiveness.

PI-QUAL version 2: A Multi-Reader reproducibility study on multiparametric MRI from a tertiary referral center

PURPOSE

To assess the inter-reader and intra-reader agreement of the Prostate imaging quality version 2 (PI-QUAL v.2) for multiparametric magnetic resonance imaging (mpMRI) among radiologists with varying levels of expertise.

METHODS

Fifty men underwent 3 T mpMRI scans in a tertiary referral center. Images were anonymized and assessed by six readers of different expertise (2 expert, 2 basic and 2 beginners) in two sessions: first using PI-QUAL v.2, and then using both PI-QUAL v.2 and v.1 after a 2-week interval. PI-QUAL v.2 scores were considered overall and, for comparison with PI-QUAL v.1, dichotomized according to the threshold of acceptable image quality. Gwet AC1 index was used to calculate the inter-reader and intra-reader agreement of the scores.

RESULTS

The inter-reader agreement for PI-QUAL v.2 scores was overall moderate (Gwet's AC1 = 0.55), being higher for expert readers compared to the beginner and basic ones (Gwet's AC1 = 0.66 versus 0.45-0-58). Intra-reader agreement varied from moderate to perfect (Gwet's AC1 = 0.43-1.00) and improved with increasing levels of expertise. The ratings were more reproducible for DWI and DCE sequences (Gwet's AC1 = 0.62-1.00) compared to T2w (Gwet's AC1 = 0.24-0.70). The intra-reader agreement between PI-QUAL v.2 and v.1 scores across readings ranged from almost perfect to perfect (Gwet's AC1 = 0.96-1.00).

CONCLUSIONS

In a tertiary referral center context, PI-QUAL v.2 is a moderately reliable tool for standardizing prostate mpMRI quality evaluations among readers with varying expertise.

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.

Transperineal or Transrectal Magnetic Resonance Imaging-targeted Biopsy for Prostate Cancer Detection

BACKGROUND AND OBJECTIVE

A notable paradigm shift has emerged in the choice of prostate biopsy approach, with a transition from transrectal biopsy (TRBx) to transperineal biopsy (TPBx) driven by the lower risk of severe urinary tract infections. The impact of this change on detection of clinically significant prostate cancer (csPCa) remains a subject of debate. Our aim was to compare the csPCa detection rate of TRBx and TPBx.

METHODS

Patients who underwent magnetic resonance imaging (MRI)-targeted and systematic biopsies for clinically localized PCa at 15 European referral centers from 2016 to 2023 were included. A propensity score matching (PSM) analysis was performed to minimize selection biases. Logistic regression models were used to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs).

KEY FINDINGS AND LIMITATIONS

Of 3949 patients who met the study criteria, 2187 underwent TRBx and 1762 underwent TPBx. PSM resulted in 1301 matched pairs for analysis. Patient demographics and tumor characteristics were comparable in the matched cohorts. TPBx versus TRBx was associated with greater detection of csPCa, whether defined as International Society of Urological Pathology grade group ≥2 (51% vs 45%; OR 1.37, 95% CI 1.15-1.63; p = 0.001) or grade group ≥3 (29% vs 23%; OR 1.38, 95% CI 1.13-1.67; p = 0.001). Similar results were found when considering MRI-targeted biopsy alone and after stratifying patients according to tumor location, Prostate Imaging-Reporting and Data System score, and clinical features. Limitations include the retrospective nature of the study and the absence of centralized MRI review.

CONCLUSIONS

Our findings bolster existing understanding of the additional advantages offered by TPBx. Further randomized trials to fully validate these findings are awaited.

PATIENT SUMMARY

We compared the rate of detection of clinically significant prostate cancer with magnetic resonance imaging (MRI)-guided biopsies in which the sample needle is passed through the perineum or the rectum. Our results suggest that the perineal approach is associated with better detection of aggressive prostate cancer.

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

BACKGROUND AND OBJECTIVE

Accurate 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.

METHODS

A 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 LIMITATIONS

Overall, 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 vs 1.39; p = 0.009). Limitations include biopsies only for men at clinical/radiological suspicion and no multidisciplinary review of MRI before biopsy.

CONCLUSIONS AND CLINICAL IMPLICATIONS

The 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 SUMMARY

The 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.

Prediction of extracapsular extension of prostate cancer by MRI radiomic signature: a systematic review

The objective of this review is to survey radiomics signatures for detecting pathological extracapsular extension (pECE) on magnetic resonance imaging (MRI) in patients with prostate cancer (PCa) who underwent prostatectomy. Scientific Literature databases were used to search studies published from January 2007 to October 2023. All studies related to PCa MRI staging and using radiomics signatures to detect pECE after prostatectomy were included. Systematic review was performed according to Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA). The risk of bias and certainty of the evidence was assessed using QUADAS-2 and the radiomics quality score. From 1247 article titles screened, 16 reports were assessed for eligibility, and 11 studies were included in this systematic review. All used a retrospective study design and most of them used 3 T MRI. Only two studies were performed in more than one institution. The highest AUC of a model using only radiomics features was 0.85, for the test validation. The AUC for best model performance (radiomics associated with clinical/semantic features) varied from 0.72-0.92 and 0.69-0.89 for the training and validation group, respectively. Combined models performed better than radiomics signatures alone for detecting ECE. Most of the studies showed a low to medium risk of bias. After thorough analysis, we found no strong evidence supporting the clinical use of radiomics signatures for identifying extracapsular extension (ECE) in pre-surgery PCa patients. Future studies should adopt prospective multicentre approaches using large public datasets and combined models for detecting ECE.

CRITICAL RELEVANT STATEMENT

The use of radiomics algorithms, with clinical and AI integration, in predicting extracapsular extension, could lead to the development of more accurate predictive models, which could help improve surgical planning and lead to better outcomes for prostate cancer patients.

PROTOCOL OF SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42021272088. Published: https://doi.org/10.1136/bmjopen-2021-052342 .

KEY POINTS

Radiomics can extract diagnostic features from MRI to enhance prostate cancer diagnosis performance. The combined models performed better than radiomics signatures alone for detecting extracapsular extension. Radiomics are not yet reliable for extracapsular detection in PCa patients.

Targeted microwave ablation for prostate cancer (FOSTINE1b): a prospective 'ablate-and-resect' study

OBJECTIVE

To assess histopathological outcomes, as well as feasibility and safety of targeted microwave ablation (TMA) via the Trinity® system (KOELIS, La Tronche, France).

PATIENTS AND METHODS

Prospective, single-institution, interventional Phase IIa study with an 'ablate-and-resect' design. In all, 11 patients diagnosed with localised prostate cancer (PCa) underwent TMA via the Trinity system under conscious sedation in an outpatient setting using a single transrectal TATO® 18-G antenna with different treatment regimens. Magnetic resonance imaging (MRI) and robot-assisted radical prostatectomy (RARP) were conducted at 7 days and 1 month after TMA, respectively. Nine patients received RARP, and two patients chose to withdraw their consent following TMA. These men chose an active surveillance protocol upon confirmation of a low-risk prostate cancer diagnosis. Functional outcomes and adverse events were evaluated at baseline and follow-up visits using validated questionnaires. Prostate volumetry and confirmation of necrosis were carried out through MRI and whole-mount histopathological examination.

RESULTS

The TMA was successfully executed, and all patients were discharged on the same day. No severe adverse events (Common Terminology Criteria for Adverse Events Grade ≥3) were reported at the 7-day and 1-month follow-up visits. Additionally, no declines were observed in urinary, sexual and ejaculation functional outcomes. T1-weighted MRI revealed clear and well-defined ablation zones. The RARP was executed without difficulty, particularly during the dissection of the posterior plane. As a result, no intraoperative complications were encountered. Histopathological assessment on surgical specimens confirmed the absence of viable cells, indicating complete necrosis of the ablative zone if a power intensity >10 W was used during TMA. Ablation zone volumetry revealed no notable distinctions between the three-dimensional segmentation of the virtual ablation zone at TMA (median volume: 2 mL) and MRI (median volume: 1.923 mL). Conversely, a significant reduction was noted in the surgical specimen (median volume: 0.221 mL).

CONCLUSIONS

Targeted microwave ablation via the Trinity system for localised PCa treatment proves to be a secure and feasible procedure, with complete necrosis evidence within the ablation zone on surgical specimens.

Partial Fourier in the presence of respiratory motion in prostate diffusion-weighted echo planar imaging

PURPOSE

To investigate the effect of respiratory motion in terms of signal loss in prostate diffusion-weighted imaging (DWI), and to evaluate the usage of partial Fourier in a free-breathing protocol in a clinically relevant b-value range using both single-shot and multi-shot acquisitions.

METHODS

A controlled breathing DWI acquisition was first employed at 3 T to measure signal loss from deep breathing patterns. Single-shot and multi-shot (2-shot) acquisitions without partial Fourier (no pF) and with partial Fourier (pF) factors of 0.75 and 0.65 were employed in a free-breathing protocol. The apparent SNR and ADC values were evaluated in 10 healthy subjects to measure if low pF factors caused low apparent SNR or overestimated ADC.

RESULTS

Controlled breathing experiments showed a difference in signal coefficient of variation between shallow and deep breathing. In free-breathing single-shot acquisitions, the pF 0.65 scan showed a significantly (p < 0.05) higher apparent SNR than pF 0.75 and no pF in the peripheral zone (PZ) of the prostate. In the multi-shot acquisitions in the PZ, pF 0.75 had a significantly higher apparent SNR than 0.65 pF and no pF. The single-shot pF 0.65 scan had a significantly lower ADC than single-shot no pF.

CONCLUSION

Deep breathing patterns can cause intravoxel dephasing in prostate DWI. For single-shot acquisitions at a b-value of 800 s/mm2, any potential risks of motion-related artefacts at low pF factors (pF 0.65) were outweighed by the increase in signal from a lower TE, as shown by the increase in apparent SNR. In multi-shot acquisitions however, the minimum pF factor should be larger, as shown by the lower apparent SNR at low pF factors.

AI-based automated evaluation of image quality and protocol tailoring in patients undergoing MRI for suspected prostate cancer

PURPOSE

To develop and validate an artificial intelligence (AI) application in a clinical setting to decide whether dynamic contrast-enhanced (DCE) sequences are necessary in multiparametric prostate MRI.

METHODS

This study was approved by the institutional review board and requirement for study-specific informed consent was waived. A mobile app was developed to integrate AI-based image quality analysis into clinical workflow. An expert radiologist provided reference decisions. Diagnostic performance parameters (sensitivity and specificity) were calculated and inter-reader agreement was evaluated.

RESULTS

Fully automated evaluation was possible in 87% of cases, with the application reaching a sensitivity of 80% and a specificity of 100% in selecting patients for multiparametric MRI. In 2% of patients, the application falsely decided on omitting DCE. With a technician reaching a sensitivity of 29% and specificity of 98%, and resident radiologists reaching sensitivity of 29% and specificity of 93%, the use of the application allowed a significant increase in sensitivity.

CONCLUSION

The presented AI application accurately decides on a patient-specific MRI protocol based on image quality analysis, potentially allowing omission of DCE in the diagnostic workup of patients with suspected prostate cancer. This could streamline workflow and optimize time utilization of healthcare professionals.

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.

Evaluating the Quality of Local Programs for Early Detection of Significant Prostate Cancer

Quality control of programs for detection of significant prostate cancer (sPCa) could be defined by the correlation between observed and reference 95% confidence intervals (CIs) for Prostate Imaging-Reporting and Data System (PI-RADS) categories. We used the area under the receiver operating characteristic curve (AUC) for the Barcelona magnetic resonance imaging (MRI) predictive model to screen the quality of ten participant centers in the sPCa opportunistic early detection program in Catalonia. We set an AUC of <0.8 as the criterion for suboptimal quality. Quality was confirmed in terms of the correlation between actual sPCa detection rates and reference 95% CIs. For a cohort of 2624 men with prostate-specific antigen >3.0 ng/ml and/or a suspicious digital rectal examination who underwent multiparametric MRI and two- to four-core targeted biopsies of PI-RADS ≥3 lesions and/or 12-core systematic biopsy, AUC values ranged from 0.527 to 0.914 and were <0.8 in four centers (40%). There was concordance between actual sPCa detection rates and reference 95% CIs for one or two PI-RADS categories when the AUC was <0.8, and for three or four PI-RADS categories when the AUC was ≥0.8. A review of procedures used for sPCa detection should be recommended in centers with suboptimal quality.

Patient summary

We tested a method for assessing quality control for centers carrying out screening for early detection of prostate cancer. We found that the method can identify centers that may need to review their procedures for detection of significant prostate cancer.

Training radiology residents to evaluate deep myometrial invasion in endometrial cancer patients on MRI: A learning curve study

PURPOSE

To evaluate the impact of a four-month training program on radiology residents' diagnostic accuracy in assessing deep myometrial invasion (DMI) in endometrial cancer (EC) using MRI.

METHOD

Three radiology residents with limited EC MRI experience participated in the training program, which included conventional didactic sessions, case-centric workshops, and interactive classes. Utilizing a training dataset of 120 EC MRI scans, trainees independently assessed subsets of cases over five reading sessions. Each subset consisted of 30 scans, the first and the last with the same cases, for a total of 150 reads. Diagnostic accuracy metrics, assessment time (rounded to the nearest minute), and confidence levels (using a 5-point Likert scale) were recorded. The learning curve was obtained plotting the diagnostic accuracy of the three trainees and the average over the subsets. Anatomopathological results served as the reference standard for DMI presence.

RESULTS

The three trainees exhibited heterogeneous starting point, with a learning curve and a trend to more homogeneous performance with training. The diagnostic accuracy of the average trainee raised from 64 % (56 %-76 %) to 88 % (80 %-94 %) across the five subsets (p < 0.001). Reductions in assessment time (5.92 to 4.63 min, p < 0.018) and enhanced confidence levels (3.58 to 3.97, p = 0.12) were observed. Improvements in sensitivity, specificity, positive predictive value, and negative predictive value were noted, particularly for specificity which raised from 56 % (41 %-68 %) in the first to 86 % (74 %-94 %) in the fifth subset (p = 0.16). Although not reaching statistical significance, these advancements aligned the trainees with literature performance benchmarks.

CONCLUSIONS

The structured training program significantly enhanced radiology residents' diagnostic accuracy in assessing DMI for EC on MRI, emphasizing the effectiveness of active case-based training in refining oncologic imaging skills within radiology residency curricula.

MRI assessment of seminal vesicle involvement by prostate cancer using T2 signal intensity and volume

BACKGROUND

Seminal vesicle involvement (SVI) in patients with newly diagnosed prostate cancer is associated with high rates of treatment failure and tumor recurrence; correct identification of SVI allows for effective management decisions and surgical planning.

METHODS

This single-center retrospective study analyzed MR images of the seminal vesicles from patients undergoing radical prostatectomy with confirmed T3b disease, comparing them to a control group without SVI matched for age and Gleason grade with a final stage of T2 or T3a. Seminal vesicles were segmented by an experienced uroradiologist, "raw" and bladder-normalized T2 signal intensity, as well as SV volume, were obtained.

RESULTS

Among the 82 patients with SVI, 34 (41.6%) had unilateral invasion, and 48 (58.4%) had bilateral disease. There was no statistically significant difference in the degree of distension between normal and involved seminal vesicles (P = 0.08). Similarly, no statistically significant difference was identified in the raw SV T2 signal intensity (P = 0.09) between the groups. In the 159 patients analyzed, SVI was prospectively suspected in 10 of 82 patients (specificity, 100%; sensitivity, 12.2%). In all these cases, lesions macroscopically invaded the seminal vesicle, and the raw T2 signal intensity was significantly lower than that in the SVI and control groups (P = 0.02 and 0.01).

CONCLUSION

While signal intensity measurements in T2-weighted images may provide insight into T3b disease, our findings suggest that this data alone is insufficient to reliably predict SVI, indicating the need for further investigation and complementary diagnostic approaches.

Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study

BACKGROUND

Artificial intelligence (AI) systems can potentially aid the diagnostic pathway of prostate cancer by alleviating the increasing workload, preventing overdiagnosis, and reducing the dependence on experienced radiologists. We aimed to investigate the performance of AI systems at detecting clinically significant prostate cancer on MRI in comparison with radiologists using the Prostate Imaging-Reporting and Data System version 2.1 (PI-RADS 2.1) and the standard of care in multidisciplinary routine practice at scale.

METHODS

In this international, paired, non-inferiority, confirmatory study, we trained and externally validated an AI system (developed within an international consortium) for detecting Gleason grade group 2 or greater cancers using a retrospective cohort of 10 207 MRI examinations from 9129 patients. Of these examinations, 9207 cases from three centres (11 sites) based in the Netherlands were used for training and tuning, and 1000 cases from four centres (12 sites) based in the Netherlands and Norway were used for testing. In parallel, we facilitated a multireader, multicase observer study with 62 radiologists (45 centres in 20 countries; median 7 [IQR 5-10] years of experience in reading prostate MRI) using PI-RADS (2.1) on 400 paired MRI examinations from the testing cohort. Primary endpoints were the sensitivity, specificity, and the area under the receiver operating characteristic curve (AUROC) of the AI system in comparison with that of all readers using PI-RADS (2.1) and in comparison with that of the historical radiology readings made during multidisciplinary routine practice (ie, the standard of care with the aid of patient history and peer consultation). Histopathology and at least 3 years (median 5 [IQR 4-6] years) of follow-up were used to establish the reference standard. The statistical analysis plan was prespecified with a primary hypothesis of non-inferiority (considering a margin of 0·05) and a secondary hypothesis of superiority towards the AI system, if non-inferiority was confirmed. This study was registered at ClinicalTrials.gov, NCT05489341.

FINDINGS

Of the 10 207 examinations included from Jan 1, 2012, through Dec 31, 2021, 2440 cases had histologically confirmed Gleason grade group 2 or greater prostate cancer. In the subset of 400 testing cases in which the AI system was compared with the radiologists participating in the reader study, the AI system showed a statistically superior and non-inferior AUROC of 0·91 (95% CI 0·87-0·94; p<0·0001), in comparison to the pool of 62 radiologists with an AUROC of 0·86 (0·83-0·89), with a lower boundary of the two-sided 95% Wald CI for the difference in AUROC of 0·02. At the mean PI-RADS 3 or greater operating point of all readers, the AI system detected 6·8% more cases with Gleason grade group 2 or greater cancers at the same specificity (57·7%, 95% CI 51·6-63·3), or 50·4% fewer false-positive results and 20·0% fewer cases with Gleason grade group 1 cancers at the same sensitivity (89·4%, 95% CI 85·3-92·9). In all 1000 testing cases where the AI system was compared with the radiology readings made during multidisciplinary practice, non-inferiority was not confirmed, as the AI system showed lower specificity (68·9% [95% CI 65·3-72·4] vs 69·0% [65·5-72·5]) at the same sensitivity (96·1%, 94·0-98·2) as the PI-RADS 3 or greater operating point. The lower boundary of the two-sided 95% Wald CI for the difference in specificity (-0·04) was greater than the non-inferiority margin (-0·05) and a p value below the significance threshold was reached (p<0·001).

INTERPRETATION

An AI system was superior to radiologists using PI-RADS (2.1), on average, at detecting clinically significant prostate cancer and comparable to the standard of care. Such a system shows the potential to be a supportive tool within a primary diagnostic setting, with several associated benefits for patients and radiologists. Prospective validation is needed to test clinical applicability of this system.

FUNDING

Health~Holland and EU Horizon 2020.

Recurrent prostate cancer: combined role for MRI and PSMA-PET in 68Ga-PSMA-11 PET/MRI

OBJECTIVES

To investigate the specific strengths of MRI and PET components in 68Ga-PSMA-11 PET/MRI for staging of patients with biochemically recurrent prostate cancer (PCa).

METHODS

Patients with biochemical recurrence of PCa and contrast-enhanced whole-body 68Ga-PSMA-11 PET/MRI including a dedicated pelvic multiparametric MRI were included in this retrospective study. Imaging datasets of MRI and PET were evaluated separately regarding local PCa recurrence (Tr), pelvic lymph node metastases (N1), distant lymph node metastases (M1a), bone metastases (M1b), and soft tissue metastases (M1c) according to PROMISE version 1. Data evaluation was performed patient- and region-/lesion-based. Cox regression revealed a PSA of 1.69 ng/mL as a cut-off for subgroup analysis. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were evaluated for each image component. Differences in staging accuracy were assessed using the Wilcoxon and McNemar test.

RESULTS

Altogether 102 patients (mean aged 68 ± 8 years, median PSA 1.33 ng/mL) were included. PCa was found in 70/102 (68%) patients. Accuracy of MRI in the detection of Tr, N1, M + , M1a, and M1b was 100%, 79%, 90%, 97%, and 95% for PSA < 1.69 ng/mL and 100%, 87%, 87%, 91%, and 96% for PSA > 1.69 ng/mL. Accuracy of 68Ga-PSMA-11 PET was 93%, 97%, 93%, 98%, and 100% for PSA < 1.69 ng/mL and 87%, 91%, 96%, 100%, and 96% for PSA > 1.69 ng/mL.

CONCLUSIONS

Combined assessment of 68Ga-PSMA-11 PET/MRI improves tumor localization in men with biochemical recurrence. The MRI detected local recurrence of PCa more often whereas 68 Ga-PSMA-11 PET detected lymph node metastases more often, especially for PSA < 1.69 ng/mL.

CLINICAL RELEVANCE STATEMENT

This study gives a scientific baseline to improve the understanding and reading of 68Ga-PSMA-11 PET/MRI imaging in patients with biochemically recurrent PCa by showing the specific strength of each imaging component.

KEY POINTS

• Combining the individual modality strengths of 68Ga-PSMA-11 PET/MRI improves tumor localization in men with biochemical recurrence of prostate cancer. • MRI component of 68 Ga-PSMA-11 PET/MRI shows its strength in detecting local recurrence of prostate cancer, especially at PSA < 1.69 ng/mL. • 68 Ga-PSMA-11 PET component shows its strength in detecting local and distant lymph node metastases, especially at PSA < 1.69 ng/mL.

Expect the unexpected: investigating discordant prostate MRI and biopsy results

OBJECTIVES

To evaluate discrepant radio-pathological outcomes in biopsy-naïve patients undergoing prostate MRI and to provide insights into the underlying causes.

MATERIALS AND METHODS

A retrospective analysis was conducted on 2780 biopsy-naïve patients undergoing prostate MRI at a tertiary referral centre between October 2015 and June 2022. Exclusion criteria were biopsy not performed, indeterminate MRI findings (PI-RADS 3), and clinically insignificant PCa (Gleason score 3 + 3). Patients with discrepant findings between MRI and biopsy results were categorised into two groups: MRI-negative/Biopsy-positive and MRI-positive/Biopsy-negative (biopsy-positive defined as Gleason score ≥ 3 + 4). An expert uroradiologist reviewed discrepant cases, retrospectively re-assigning PI-RADS scores, identifying any missed MRI targets, and evaluating the quality of MRI scans. Potential explanations for discrepancies included MRI overcalls (including known pitfalls), benign pathology findings, and biopsy targeting errors.

RESULTS

Patients who did not undergo biopsy (n = 1258) or who had indeterminate MRI findings (n = 204), as well as those with clinically insignificant PCa (n = 216), were excluded, with a total of 1102 patients analysed. Of these, 32/1,102 (3%) were classified as MRI-negative/biopsy-positive and 117/1102 (11%) as MRI-positive/biopsy-negative. In the MRI-negative/Biopsy-positive group, 44% of studies were considered non-diagnostic quality. Upon retrospective image review, target lesions were identified in 28% of cases. In the MRI-positive/Biopsy-negative group, 42% of cases were considered to be MRI overcalls, and 32% had an explanatory benign pathological finding, with biopsy targeting errors accounting for 11% of cases.

CONCLUSION

Prostate MRI demonstrated a high diagnostic accuracy, with low occurrences of discrepant findings as defined. Common reasons for MRI-positive/Biopsy-negative cases included explanatory benign findings and MRI overcalls.

CLINICAL RELEVANCE STATEMENT

This study highlights the importance of optimal prostate MRI image quality and expertise in reducing diagnostic errors, improving patient outcomes, and guiding appropriate management decisions in the prostate cancer diagnostic pathway.

KEY POINTS

• Discrepancies between prostate MRI and biopsy results can occur, with higher numbers of MRI-positive/biopsy-negative relative to MRI-negative/biopsy-positive cases. • MRI-positive/biopsy-negative cases were mostly overcalls or explainable by benign biopsy findings. • In about one-third of MRI-negative/biopsy-positive cases, a target lesion was retrospectively identified.

Multiparametric Prostate MRI Accuracy of Prostate Imaging Reporting and Data System (v2.1) Scores 4 and 5: The Influence of Image Quality According to the Prostate Imaging Quality Score

Purpose: The accuracy of multiparametric magnetic resonance imaging (mpMRI) heavily relies on image quality, as evidenced by the evolution of the prostate imaging quality (PI-QUAL) scoring system for the evaluation of clinically significant prostate cancer (csPC). This study aims to evaluate the impact of PI-QUAL scores in detecting csPC within PI-RADS 4 and 5 lesions. Methods: We retrospectively selected from our database all mpMRI performed from January 2019 to March 2022. Inclusion criteria were as follows: (1) mpMRI acquired in our institution according to the technical requirements from the PI-RADS (v2.1) guidelines; (2) single lesion scored as PI-RADS (v2.1) 4 or 5; (3) MRI-TBx performed in our institution; (4) complete histology report; and (5) complete clinical record. Results: A total of 257 male patients, mean age 70.42 ± 7.6 years, with a single PI-RADS 4 or 5 lesion undergoing MRI-targeted biopsy, were retrospectively studied. Of these, 61.5% were PI-RADS 4, and 38.5% were PI-RADS 5, with 84% confirming neoplastic cells. In high-quality image lesions (PI-QUAL ≥ 4), all PI-RADS 5 lesions were accurately identified as positive at the final histological examination (100% of CDR). For PI-RADS 4 lesions, 37 (23%) were negative, resulting in a cancer detection rate of 77% (95% CI: 67.51-84.83). Conclusions: The accuracy of mpMRI, independently of the PI-RADS score, progressively decreased according to the decreasing PI-QUAL score. These findings emphasize the crucial role of the PI-QUAL scoring system in evaluating PI-RADS 4 and 5 lesions, influencing mpMRI accuracy.

External validation and comparison of magnetic resonance imaging-based risk prediction models for prostate biopsy stratification

PURPOSE

Magnetic resonance imaging (MRI) is a promising tool for risk assessment, potentially reducing the burden of unnecessary prostate biopsies. Risk prediction models that incorporate MRI data have gained attention, but their external validation and comparison are essential for guiding clinical practice. The aim is to externally validate and compare risk prediction models for the diagnosis of clinically significant prostate cancer (csPCa).

METHODS

A cohort of 4606 patients across fifteen European tertiary referral centers were identified from a prospective maintained database between January 2016 and April 2023. Transrectal or transperineal image-fusion MRI-targeted and systematic biopsies for PI-RADS score of ≥ 3 or ≥ 2 depending on patient characteristics and physician preferences. Probabilities for csPCa, defined as International Society of Urological Pathology (ISUP) grade ≥ 2, were calculated for each patients using eight models. Performance was characterized by area under the receiver operating characteristic curve (AUC), calibration, and net benefit. Subgroup analyses were performed across various clinically relevant subgroups.

RESULTS

Overall, csPCa was detected in 2154 (47%) patients. The models exhibited satisfactory performance, demonstrating good discrimination (AUC ranging from 0.75 to 0.78, p < 0.001), adequate calibration, and high net benefit. The model described by Alberts showed the highest clinical utility for threshold probabilities between 10 and 20%. Subgroup analyses highlighted variations in models' performance, particularly when stratified according to PSA level, biopsy technique and PI-RADS version.

CONCLUSIONS

We report a comprehensive external validation of risk prediction models for csPCa diagnosis in patients who underwent MRI-targeted and systematic biopsies. The model by Alberts demonstrated superior clinical utility and should be favored when determining the need for a prostate biopsy.

Picture Perfect: The Status of Image Quality in Prostate MRI

Magnetic resonance imaging is the gold standard imaging modality for the diagnosis of prostate cancer (PCa). Image quality is a fundamental prerequisite for the ability to detect clinically significant disease. In this critical review, we separate the issue of image quality into quality improvement and quality assessment. Beginning with the evolution of technical recommendations for scan acquisition, we investigate the role of patient preparation, scanner factors, and more advanced sequences, including those featuring Artificial Intelligence (AI), in determining image quality. As means of quality appraisal, the published literature on scoring systems (including the Prostate Imaging Quality score), is evaluated. Finally, the application of AI and teaching courses as ways to facilitate quality assessment are discussed, encouraging the implementation of future image quality initiatives along the PCa diagnostic and monitoring pathway. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 3.

Deep Learning-Based T2-Weighted MR Image Quality Assessment and Its Impact on Prostate Cancer Detection Rates

BACKGROUND

Image quality evaluation of prostate MRI is important for successful implementation of MRI into localized prostate cancer diagnosis.

PURPOSE

To examine the impact of image quality on prostate cancer detection using an in-house previously developed artificial intelligence (AI) algorithm.

STUDY TYPE

Retrospective.

SUBJECTS

615 consecutive patients (median age 67 [interquartile range [IQR]: 61-71] years) with elevated serum PSA (median PSA 6.6 [IQR: 4.6-9.8] ng/mL) prior to prostate biopsy.

FIELD STRENGTH/SEQUENCE

3.0T/T2-weighted turbo-spin-echo MRI, high b-value echo-planar diffusion-weighted imaging, and gradient recalled echo dynamic contrast-enhanced.

ASSESSMENTS

Scans were prospectively evaluated during clinical readout using PI-RADSv2.1 by one genitourinary radiologist with 17 years of experience. For each patient, T2-weighted images (T2WIs) were classified as high-quality or low-quality based on evaluation of both general distortions (eg, motion, distortion, noise, and aliasing) and perceptual distortions (eg, obscured delineation of prostatic capsule, prostatic zones, and excess rectal gas) by a previously developed in-house AI algorithm. Patients with PI-RADS category 1 underwent 12-core ultrasound-guided systematic biopsy while those with PI-RADS category 2-5 underwent combined systematic and targeted biopsies. Patient-level cancer detection rates (CDRs) were calculated for clinically significant prostate cancer (csPCa, International Society of Urological Pathology Grade Group ≥2) by each biopsy method and compared between high- and low-quality images in each PI-RADS category.

STATISTICAL TESTS

Fisher's exact test. Bootstrap 95% confidence intervals (CI). A P value <0.05 was considered statistically significant.

RESULTS

385 (63%) T2WIs were classified as high-quality and 230 (37%) as low-quality by AI. Targeted biopsy with high-quality T2WIs resulted in significantly higher clinically significant CDR than low-quality images for PI-RADS category 4 lesions (52% [95% CI: 43-61] vs. 32% [95% CI: 22-42]). For combined biopsy, there was no significant difference in patient-level CDRs for PI-RADS 4 between high- and low-quality T2WIs (56% [95% CI: 47-64] vs. 44% [95% CI: 34-55]; P = 0.09).

DATA CONCLUSION

Higher quality T2WIs were associated with better targeted biopsy clinically significant cancer detection performance for PI-RADS 4 lesions. Combined biopsy might be needed when T2WI is lower quality.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 1.

Histopathological concordance between prostate biopsies and radical prostatectomy specimens-implications of transrectal and transperineal biopsy approaches

BACKGROUND

This study aimed to evaluate the histopathological concordance rates between prostate biopsies and radical prostatectomy specimens according to the applied biopsy approach (transrectal or transperineal).

METHODS

We studied patients who had been newly diagnosed with clinically significant prostate cancer and who underwent a radical prostatectomy between 2018 and 2022. Patients were included if they underwent a prebiopsy magnetic resonance imaging and if they had not been previously treated for prostate cancer. Histopathological grading on prostate biopsies was compared with that on radical prostatectomy specimens. Univariable and multivariable logistic regression analyses were performed to assess the effect of the applied biopsy approach on histopathological concordance. Additional analyses were performed to assess the effect of the applied biopsy approach on American Urological Association risk group migration, defined as any change in risk group after radical prostatectomy.

RESULTS

In total, 1058 men were studied, of whom 49.3% (522/1058) and 50.7% (536/1058) underwent transrectal and transperineal prostate biopsies, respectively. Histopathological disconcordance was observed in 37.8% (400/1058) of men while American Urological Association risk group migration was observed in 30.2% (320/1058) of men. A transperineal biopsy approach was found to be independently associated with higher histopathological concordance rates (OR 1.33 [95% CI 1.01-1.75], p = 0.04) and less American Urological Association risk group migration (OR 0.70 [95% CI 0.52-0.93], p = 0.01).

CONCLUSIONS

The use of a transperineal biopsy approach improved histopathological concordance rates compared to the use of a transrectal biopsy approach. A transperineal biopsy approach may provide more accurate risk stratification for clinical decision-making. Despite recent improvements, histopathologic concordance remains suboptimal and should be considered before initiating management.

Interpreting Prostate MRI Reports in the Era of Increasing Prostate MRI Utilization: A Urologist's Perspective

Multi-parametric prostate MRI (mpMRI) is crucial for diagnosing, staging, and assessing treatment response in individuals with prostate cancer. Radiologists, through an accurate and standardized interpretation of mpMRI, stratify patients who may benefit from more invasive treatment or exclude patients who may be harmed by overtreatment. The integration of prostate MRI into the diagnostic pathway is anticipated to generate a substantial surge in the demand for high-quality mpMRI, estimated at approximately two million additional prostate MRI scans annually in Europe. In this review we examine the immediate impact on healthcare, particularly focusing on the workload and evolving roles of radiologists and urologists tasked with the interpretation of these reports and consequential decisions regarding prostate biopsies. We investigate important questions that influence how prostate MRI reports are handled. The discussion aims to provide insights into the collaboration needed for effective reporting.

The impact of prostate volume estimation on the risk-adapted biopsy decision based on prostate-specific antigen density and magnetic resonance imaging score

PURPOSE

Utility of prostate-specific antigen density (PSAd) for risk-stratification to avoid unnecessary biopsy remains unclear due to the lack of standardization of prostate volume estimation. We evaluated the impact of ellipsoidal formula using multiparametric magnetic resonance (MRI) and semi-automated segmentation using tridimensional ultrasound (3D-US) on prostate volume and PSAd estimations as well as the distribution of patients in a risk-adapted table of clinically significant prostate cancer (csPCa).

METHODS

In a prospectively maintained database of 4841 patients who underwent MRI-targeted and systematic biopsies, 971 met inclusions criteria. Correlation of volume estimation was assessed by Kendall's correlation coefficient and graphically represented by scatter and Bland-Altman plots. Distribution of csPCa was presented using the Schoots risk-adapted table based on PSAd and PI-RADS score. The model was evaluated using discrimination, calibration plots and decision curve analysis (DCA).

RESULTS

Median prostate volume estimation using 3D-US was higher compared to MRI (49cc[IQR 37-68] vs 47cc[IQR 35-66], p < 0.001). Significant correlation between imaging modalities was observed (τ = 0.73[CI 0.7-0.75], p < 0.001). Bland-Altman plot emphasizes the differences in prostate volume estimation. Using the Schoots risk-adapted table, a high risk of csPCa was observed in PI-RADS 2 combined with high PSAd, and in all PI-RADS 4-5. The risk of csPCa was proportional to the PSAd for PI-RADS 3 patients. Good accuracy (AUC of 0.69 and 0.68 using 3D-US and MRI, respectively), adequate calibration and a higher net benefit when using 3D-US for probability thresholds above 25% on DCA.

CONCLUSIONS

Prostate volume estimation with semi-automated segmentation using 3D-US should be preferred to the ellipsoidal formula (MRI) when evaluating PSAd and the risk of csPCa.

The Association between Urine N-Glycome and Prognosis after Initial Therapy for Primary Prostate Cancer

Next to prostate-specific antigen, no biochemical biomarkers have been implemented to guide patient follow-up after primary therapy for localized prostate cancer (PCa). We evaluated the prognostic potential of urine N-glycome in terms of event-free survival (EFS) in patients undergoing primary therapy for PCa. The prognostic features of the urine N-glycosylation profile at diagnosis, assessed in 77 PCa patients, were determined in terms of EFS next to standard clinical parameters. The majority of patients were diagnosed with International Society of Urological Pathology grade ≤ 3 (82%) T1-2 tumors (79%) and without pelvic lymph node invasion (96%). The patients underwent active surveillance (14%), robot-assisted laparoscopic prostatectomy (48%), or external beam radiotherapy (37%). Decreased ratios of biantennary core-fucosylation were noted in patients who developed an event, which was linked to a shorter EFS in both the intention-to-treat cohort and all subcohort analyses. Combining the urine N-glycan biomarker with the D'Amico Risk Classification for PCa resulted in an improved nomogram for patient classification after primary therapy. The rate of urine N-glycan biantennary core-fucosylation, typically linked to more aggressive disease status, is lower in patients who eventually developed an event following primary therapy and subsequently in patients with a worse EFS. The combination of urine N-glycan biomarkers together with clinical parameters could, therefore, improve the post-therapy follow-up of patients with PCa.

Brand D, Lee E, Loblaw A, Tolan S, van As N, Tree AC. Developing and validating a simple urethra surrogate model to facilitate dosimetric analysis to predict genitourinary toxicity

Purpose

The urethra is a critical structure in prostate radiotherapy planning; however, it is impossible to visualise on CT. We developed a surrogate urethra model (SUM) for CT-only planning workflow and tested its geometric and dosimetric performance against the MRI-delineated urethra (MDU).

Methods

The SUM was compared against 34 different MDUs (within the treatment PTV) in patients treated with 36.25Gy (PTV)/40Gy (CTV) in 5 fractions as part of the PACE-B trial. To assess the surrogate's geometric performance, the Dice similarity coefficient (DSC), Hausdorff distance (HD), mean distance to agreement (MDTA) and the percentage of MDU outside the surrogate (UOS) were calculated. To evaluate the dosimetric performance, a paired t-test was used to calculate the mean of differences between the MDU and SUM for the D99, D98, D50, D2 and D1. The D(n) is the dose (Gy) to n% of the urethra.

Results

The median results showed low agreement on DSC (0.32; IQR 0.21-0.41), but low distance to agreement, as would be expected for a small structure (HD 8.4mm (IQR 7.1-10.1mm), MDTA 2.4mm (IQR, 2.2mm-3.2mm)). The UOS was 30% (IQR, 18-54%), indicating nearly a third of the urethra lay outside of the surrogate. However, when comparing urethral dose between the MDU and SUM, the mean of differences for D99, D98 and D95 were 0.12Gy (p=0.57), 0.09Gy (p=0.61), and 0.11Gy (p=0.46) respectively. The mean of differences between the D50, D2 and D1 were 0.08Gy (p=0.04), 0.09Gy (p=0.02) and 0.1Gy (p=0.01) respectively, indicating good dosimetric agreement between MDU and SUM.

Conclusion

While there were geometric differences between the MDU and SUM, there was no clinically significant difference between urethral dose-volume parameters. This surrogate model could be validated in a larger cohort and then used to estimate the urethral dose on CT planning scans in those without an MRI planning scan or urinary catheter.

Prediction of prostate cancer aggressiveness using magnetic resonance imaging radiomics: a dual-center study

PURPOSE

The Gleason score (GS) and positive needles are crucial aggressive indicators of prostate cancer (PCa). This study aimed to investigate the usefulness of magnetic resonance imaging (MRI) radiomics models in predicting GS and positive needles of systematic biopsy in PCa.

MATERIAL AND METHODS

A total of 218 patients with pathologically proven PCa were retrospectively recruited from 2 centers. Small-field-of-view high-resolution T2-weighted imaging and post-contrast delayed sequences were selected to extract radiomics features. Then, analysis of variance and recursive feature elimination were applied to remove redundant features. Radiomics models for predicting GS and positive needles were constructed based on MRI and various classifiers, including support vector machine, linear discriminant analysis, logistic regression (LR), and LR using the least absolute shrinkage and selection operator. The models were evaluated with the area under the curve (AUC) of the receiver-operating characteristic.

RESULTS

The 11 features were chosen as the primary feature subset for the GS prediction, whereas the 5 features were chosen for positive needle prediction. LR was chosen as classifier to construct the radiomics models. For GS prediction, the AUC of the radiomics models was 0.811, 0.814, and 0.717 in the training, internal validation, and external validation sets, respectively. For positive needle prediction, the AUC was 0.806, 0.811, and 0.791 in the training, internal validation, and external validation sets, respectively.

CONCLUSIONS

MRI radiomics models are suitable for predicting GS and positive needles of systematic biopsy in PCa. The models can be used to identify aggressive PCa using a noninvasive, repeatable, and accurate diagnostic method.

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.