Cancer detection rate of prebiopsy MRI with subsequent systematic and targeted biopsy are superior to non-targeting systematic biopsy without MRI in biopsy naïve patients: a retrospective cohort study

Understanding Spatial Correlation Between Multiparametric MRI Performance and Prostate Cancer

BACKGROUND

Multiparametric MRI (mpMRI) has shown a substantial impact on prostate cancer (PCa) diagnosis. However, the understanding of the spatial correlation between mpMRI performance and PCa location is still limited.

PURPOSE

To investigate the association between mpMRI performance and tumor spatial location within the prostate using a prostate sector map, described by Prostate Imaging Reporting and Data System (PI-RADS) v2.1.

STUDY TYPE

Retrospective.

SUBJECTS

One thousand one hundred forty-three men who underwent mpMRI before radical prostatectomy between 2010 and 2022.

FIELD STRENGTH/SEQUENCE

3.0 T. T2-weighted turbo spin-echo, a single-shot spin-echo EPI sequence for diffusion-weighted imaging, and a gradient echo sequence for dynamic contrast-enhanced MRI sequences.

ASSESSMENT

Integrated relative cancer prevalence (rCP), detection rate (DR), and positive predictive value (PPV) maps corresponding to the prostate sector map for PCa lesions were created. The relationship between tumor location and its detection/missing by radiologists on mpMRI compared to WMHP as a reference standard was investigated.

STATISTICAL TESTS

A weighted chi-square test was performed to examine the statistical differences for rCP, DR, and PPV of the aggregated sectors within the zone, anterior/posterior, left/right prostate, and different levels of the prostate with a statistically significant level of 0.05.

RESULTS

A total of 1665 PCa lesions were identified in 1143 patients, and from those 1060 lesions were clinically significant (cs)PCa tumors (any Gleason score [GS] ≥7). Our sector-based analysis utilizing weighted chi-square tests suggested that the left posterior part of PZ had a high likelihood of missing csPCa lesions at a DR of 67.0%. Aggregated sector analysis indicated that the anterior or apex locations in PZ had the significantly lowest csPCa detection at 67.3% and 71.5%, respectively.

DATA CONCLUSION

Spatial characteristics of the per-lesion-based mpMRI performance for diagnosis of PCa were studied. Our results demonstrated that there is a spatial correlation between mpMRI performance and locations of PCa on the prostate.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 2.

A Comparison of Systematic, Targeted, and Combined Biopsy Using Machine Learning for Prediction of Prostate Cancer Risk: A Multi-Center Study

OBJECTIVES

The aims of the study were to construct a new prognostic prediction model for detecting prostate cancer (PCa) patients using machine-learning (ML) techniques and to compare those models across systematic and target biopsy detection techniques.

METHODS

The records of the two main hospitals in Riyadh, Saudi Arabia, were analyzed for data on diagnosed PCa from 2019 to 2023. Four ML algorithms were utilized for the prediction and classification of PCa.

RESULTS

A total of 528 patients with prostate-specific antigen (PSA) greater than 3.5 ng/mL who had undergone transrectal ultrasound-guided prostate biopsy were evaluated. The total number of confirmed PCa cases was 234. Age, prostate volume, PSA, body mass index (BMI), multiparametric magnetic resonance imaging (mpMRI) score, number of regions of interest detected in MRI, and the diameter of the largest size lesion were significantly associated with PCa. Random Forest (RF) and XGBoost (XGB) (ML algorithms) accurately predicted PCa. Yet, their performance for classification and prediction of PCa was higher and more accurate for cases detected by targeted and combined biopsy (systematic and targeted together) compared to systematic biopsy alone. F1, the area under the curve (AUC), and the accuracy of XGB and RF models for targeted biopsy and combined biopsy ranged from 0.94 to 0.97 compared to the AUC of systematic biopsy for RF and XGB algorithms, respectively.

CONCLUSIONS

The RF model generated and presented an excellent prediction capability for the risk of PCa detected by targeted and combined biopsy compared to systematic biopsy alone. ML models can prevent missed PCa diagnoses by serving as a screening tool.

Detection of anterior prostate cancer using a magnetic resonance imaging-transrectal ultrasound fusion biopsy in cases with initial biopsy and history of systematic biopsies

Background

Prostate cancer in the anterior region may be missed on a transrectal systematic biopsy (SBx). Therefore, this study aimed to evaluate the performance of magnetic resonance imaging-transrectal ultrasound (MRI-TRUS) fusion targeted biopsy (TBx) in detecting anterior region cancer in patients with a history of SBxs.

Methods

Prostate biopsies were performed in 224 patients after multiparametric MRI, among whom 119 patients with prostate imaging reporting and data system (PI-RADS version 2) scores of 3 to 5 underwent MRI-TRUS fusion TBxs. Afterward, cancer detection rates (CDRs) and TBx-positive core regions were compared by categorizing patients into those with or without a history of SBxs.

Results

Total CDR was 68.8% (44/64 cases) in the initial biopsy group (Initial-Bx group) and 47.3% (26/55 cases) in the previous-negative-systematic biopsy group (Pre-Neg-SBx group) (P = 0.018). Interestingly, both TBx- and SBx-core positive cases were more common in the Initial-Bx group than in the Pre-Neg-SBx group (Initial-Bx group: 75% [33/44 cases] vs. Pre-Neg-SBx group: 42.3% [11/26 cases], P = 0.006). However, only TBx-core positive cases were more common in the Pre-Neg-SBx group than in the Initial-Bx group (Initial-Bx group: 11.4% [5/44 cases] vs. Pre-Neg-SBx group: 30.8% [8/26 cases], P = 0.043). In addition, the proportion of anterior lesions detected by TBx cores was higher in the Pre-Neg-SBx group than in the Initial-Bx group (Initial-Bx group: 26.3% [10/38 cases] vs. Pre-Neg-SBx group: 52.6% [10/19 cases], P = 0.049).

Conclusion

Using MRI-TRUS fusion TBx in the evaluation of previously negative SBx cases improved the detection rate of anterior lesions, which might have been missed in previous SBxs. Especially in patients with a history of SBxs mpMRI should be performed to screen for anterior lesions.

Urinary MyProstateScore (MPS) to Rule out Clinically-Significant Cancer in Men with Equivocal (PI-RADS 3) Multiparametric MRI: Addressing an Unmet Clinical Need

OBJECTIVE

To evaluate the complementary value of urinary MyProstateScore (MPS) testing and multiparametric MRI (mpMRI) and assess outcomes in patients with equivocal mpMRI.

MATERIALS AND METHODS

Included patients underwent mpMRI followed by urine collection and prostate biopsy at the University of Michigan between 2015 -2019. MPS values were calculated from urine specimens using the validated model based on serum PSA, urinary PCA3, and urinary TMPRSS2:ERG. In the PI-RADS 3 population, the discriminative accuracy of PSA, PSAD, and MPS for GG≥2 cancer was quantified by the AUC curve. Decision curve analysis was used to assess net benefit of MPS relative to PSAD.

RESULTS

There were 540 patients that underwent mpMRI and biopsy with MPS available. The prevalence of GG≥2 cancer was 13% for PI-RADS 3, 56% for PI-RADS 4, and 87% for PI-RADS 5. MPS was significantly higher in men with GG≥2 cancer [median 44.9, IQR (29.4 -57.5)] than those with negative or GG1 biopsy [median 29.2, IQR (14.8 -44.2); P <.001] in the overall population and when stratified by PI-RADS score. In the PI-RADS 3 population (n = 121), the AUC for predicting GG≥2 cancer was 0.55 for PSA, 0.62 for PSAD, and 0.73 for MPS. MPS provided the highest net clinical benefit across all pertinent threshold probabilities.

CONCLUSION

In patients that underwent mpMRI and biopsy, MPS was significantly associated with GG≥2 cancer across all PI-RADS scores. In the PI-RADS 3 population, MPS significantly outperformed PSAD in ruling out GG≥2 cancer. These findings suggest a complementary role of MPS testing in patients that have undergone mpMRI.

Local versus general anesthesia transperineal prostate biopsy: Tolerability, cancer detection, and complications

Objectives

To compare data on transperineal template biopsy (TPTB) under general anesthesia (GA) compared with local anesthesia (LA) procedures using the PrecisionPoint™ Transperineal Access System (PPTAS) in relation to tolerability, cancer detection rate, complications, and cost.

Methods

A prospective pilot cohort study of patients undergoing transperineal biopsy was performed. Patients were excluded if they had concurrent flexible cystoscopy or language barriers. Patients had a choice of GA or LA. A prospective questionnaire on Days 0, 1, 7, and 30 was applied. The primary outcome was patient tolerability. Secondary outcomes were cancer detection rate, complication rate, and theater utilization.

Results

This study included 80 patients (40 GA TPTB and 40 LA PPTAS). Baseline characteristics including age, prostate‐specific antigen (PSA), digital rectal examination (DRE), findings, and prostate volume were comparable between the groups (p = 0.3790, p = 0.9832, p = 0.444, p = 0.3939, respectively). Higher median prostate imaging‐reporting and data system (PI‐RADS) score of 4 (interquartile range [IQR] 2) versus 3 (IQR 1) was noted in the LA group (p = 0.0326). Pain was higher leaving recovery in the GA group however not significantly (p = 0.0555). Median pain score at LA infiltration was 5/10 (IQR 3), with no difference in pain at Days 1, 7, or 30 (p = 0.2722, 0.6465, and 0.8184, respectively). For GA versus LA, the overall cancer detection rate was 55% versus 55% (p = 1.000) with clinically significant cancer in 22.5% versus 35% (p = 0.217). Acute urinary retention (AUR) occurred in 5% of GA and 2.5% of LA patients (p = 1.000). The GA cohort spent longer in theater and in recovery with a median of 93.5 min versus 57 min for the LA group (p = <0.0001).

Conclusion

This study demonstrates that transperineal biopsy is safely performed under LA with no difference between the cohorts in relation cancer detection or AUR. LA biopsy also consumed less theater and recovery resources. A further larger prospective randomized controlled trial is required to confirm the findings of this study.

Optimal Number of Systematic Biopsy Cores Used in Magnetic Resonance Imaging/Transrectal Ultrasound Fusion Targeted Prostate Biopsy

Background

In recent years, the effectiveness of magnetic resonance imaging (MRI)-ultrasound fusion targeted biopsy (MRF-TB) has been widely reported. In this study, we assessed the effect of reduction of the number of systematic biopsy (SB) cores on the cancer detection rate (CDR).

Methods

Patients with a high prostate-specific antigen (PSA) level underwent prostate MRI. The Prostate Imaging-Reporting and Data System version 2 (PI-RADS) was then used to rate the lesions. The inclusion criteria were as follows: (1) PSA level between 4.0 and 30.0 ng/mL and (2) patients with one or more lesions on MRI and a PI-RADS score of 3 or more. All enrolled patients were SB naïve or had a history of one or more prior negative SBs. A total of 104 Japanese met this selection criterion. We have traditionally performed 14-core SB following the MRF-TB. In this study, the CDRs of 10-core SB methods, excluding biopsy results at the center of the base and mid-level on both sides, were compared with those of the conventional biopsy method.

Results

We compared CDRs of the 14-core and 10-core SBs used in combination. The overall CDR was 55.8% for the former and 55.8% for the latter, thereby indicating that there was no significant difference (P = 1.00) between the two. In addition, the CDRs of csPCa were 51.9% for the former and 51.1% for the latter, which indicated that there was no significant difference (P = 0.317).

Conclusion

There was no significant difference in the CDR when the number of SB cores to be used in combination was 14 and 10.

Performance of an Automated Workflow for Magnetic Resonance Imaging of the Prostate: Comparison With a Manual Workflow

OBJECTIVES

The aim of this study was to evaluate the performance of an automated workflow for multiparametric magnetic resonance imaging (mpMRI) of the prostate compared with a manual mpMRI workflow.

MATERIALS AND METHODS

This retrospective study was approved by the local ethics committee. Two MR technicians scanned 2 healthy volunteers with a prototypical highly automated workflow (Siemens Healthineers GmbH, Erlangen, Germany) and with a manually adjusted scan protocol each. Thirty patients (mean age ± standard deviation, 68 ± 11 years; range, 41-93 years) with suspected prostate cancer underwent mpMRI on a 3 T MRI scanner. Fifteen patients were examined with the automated workflow and 15 patients with a conventional manual workflow. Two readers assessed image quality (contrast, zone distinction, organ margins, seminal vesicles, lymph nodes), organ coverage, orientation (T2w sequences), and artifacts (motion, susceptibility, noise) on a 5-point scale (1, poor; 5, excellent). Examination time and MR technicians' acceptance were compared between both groups. Interreader agreement was evaluated with Cohen's kappa (κ).

RESULTS

The automated workflow proved consistent for sequence orientation and image quality in the intraindividual comparisons. There were no significant differences in examination time (automated vs manual; median 26 vs 28 minutes; interquartile range [IQR], 25-28 minutes each; P = 0.57), study volume coverage, artifacts, or scores for T2w sequence orientation (5 vs 4 each; P > 0.3). Overall image quality was superior for automated MRI (4.6 vs 3.8; IQR, 3.9-4.8 vs 3.2-4.3; P = 0.002), especially concerning organ delineation and seminal vesicles (P = 0.045 and P = 0.013). The acceptance score was higher for the manual workflow (median, 10 vs 8; IQR, 10 vs 7-10; P = 0.002). General interreader agreement was excellent (κ = 0.832; P < 0.001).

CONCLUSIONS

The automated workflow for prostate MRI ensures accurate sequence orientation and maintains high image quality, whereas examination time remained unaffected compared with the manual procedure in our institution.

mpMRI-targeted biopsy versus systematic biopsy for clinically significant prostate cancer diagnosis: a systematic review and metaanalysis

PURPOSE OF REVIEW

We aimed to compare the accuracy of clinically significant prostate cancer (csPCa) diagnosis by magnetic resonance imaging-targeted biopsy (MRI-TB) versus systematic biopsy (SB) in men suspected of having prostate cancer (PCa).

RECENT FINDINGS

In biopsy-naïve patients, MRI-TB was more accurate to identify csPCa than SB. However, when comparing specifically MRI-TB versus transperineal (SB), we did not find any difference. Furthermore, in a repeat biopsy scenario, MRI-TB found more csPCa than SB as well. Finally, postanalysis comparing combined biopsy (SB plus MRI-TB) suggests that the later alone may play a role in both scenarios for identifying csPCa.

SUMMARY

MRI-TB found more csPCa than SB in patients with suspected PCa in both scenarios, naïve and repeat biopsies, but more studies comparing those methods are warranted before any recommendation on this topic.

Detection of prostate cancer using prostate imaging reporting and data system score and prostate-specific antigen density in biopsy-naive and prior biopsy-negative patients

Background

Few studies report on indications for prostate biopsy using Prostate Imaging–Reporting and Data System (PI-RADS) score and prostate-specific antigen density (PSAD). No study to date has included biopsy-naïve and prior biopsy-negative patients. Therefore, we evaluated the predictive values of the PI-RADS, version 2 (v2) score combined with PSAD to decrease unnecessary biopsies in biopsy-naïve and prior biopsy-negative patients.

Materials and methods

A total of 1,098 patients who underwent multiparametric magnetic resonance imaging at our hospital before a prostate biopsy and who underwent their second prostate biopsy with an initial benign negative prostatic biopsy were included. We found factors associated with clinically significant prostate cancer (csPca). We assessed negative predictive values by stratifying biopsy outcomes by prior biopsy history and PI-RADS score combined with PSAD.

Results

The median age was 65 years (interquartile range: 59-70), and the median PSA was 5.1 ng/mL (interquartile range: 3.8-7.1). Multivariate logistic regression analysis revealed that age, prostate volume, PSAD, and PI-RADS score were independent predictors of csPca. In a biopsy-naïve group, 4% with PI-RADS score 1 or 2 had csPca; in a prior biopsy-negative group, 3% with PI-RADS score 1 or 2 had csPca. The csPca detection rate was 2.0% for PSA density <0.15 ng/mL/mL and 4.0% for PSA density 0.15-0.3 ng/mL/mL among patients with PI-RADS score 3 in a biopsy-naïve group. The csPca detection rate was 1.8% for PSA density <0.15 ng/mL/mL and 0.15-0.3 ng/mL/mL among patients with PI-RADS score 3 in a prior biopsy-negative group.

Conclusion

Patients with PI-RADS v2 score ≤2, regardless of PSA density, may avoid unnecessary biopsy. Patients with PI-RADS score 3 may avoid unnecessary biopsy through PSA density results.

Tracking Changes in Clinical Practice Patterns Following Prebiopsy Biparametric Prostate MRI

RATIONALE AND OBJECTIVES

To evaluate the change in clinical practice after implementation of prebiopsy biparametric MRI followed by targeted biopsy and the benefits of prebiopsy MRI based on real clinical practice.

MATERIALS AND METHODS

A total of 1,661 patients who underwent either transrectal biopsy or prebiopsy MRI for suspected prostate cancer between October 2015 and March 2018 were enrolled in this retrospective single-center study. To evaluate temporal changes in clinical practice, the study time was divided into five periods of six months. Prebiopsy prostate MRI was officially started in April 2016 in this center. Differences in practice patterns were compared among the five periods, and differences in biopsy results were compared in three groups: no prebiopsy MRI, negative MRI and positive MRI.

RESULTS

Prostate cancers were diagnosed in 463 patients. The proportion of patients who underwent prebiopsy MRI regardless of biopsy increased from 22.6% in period 1 to 84.4% in period 5 (P < 0.001). The proportion of patients who avoided biopsy according to MRI results increased significantly from 9.0% in period 1 to 48.1% in period 5 (P < 0.001). The prostate cancer detection rate and the number of positive cores were lower in the negative MRI group than those in the positive MRI and no prebiopsy MRI groups.

CONCLUSION

Prebiopsy MRI using biparametric MRI protocol has been well adapted to the practice and it is useful in stratifying the probability of clinically significant prostate cancer.

Prostate Imaging Reporting and Data System 3 Category Cases at Multiparametric Magnetic Resonance for Prostate Cancer: A Systematic Review and Meta-analysis

CONTEXT

The Prostate Imaging Reporting and Data System (PI-RADS) 3 score represents a "grey zone" that need to be further investigated to solve the issue of whether to biopsy these equivocal cases or not.

OBJECTIVE

To critically analyze the current evidence on PI-RADS 3 cases. We evaluated the prevalence of PI-RADS 3 cases in the literature and detection rate of prostate cancer (PC) and clinically significant PC (csPC) at biopsy with regard to factors determining these rates.

EVIDENCE ACQUISITION

We searched in the Medline and Cochrane Library database from the literature from January 2009 to January 2019, following the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) guidelines.

EVIDENCE SYNTHESIS

A total of 28 studies were included in our analysis (total number of PI-RADS 3 cases: 1759, range 20-187). The prevalence of PI-RADS 3 cases reported in available studies was 17.3% (range 6.4-45.7%). The PC detection rate was 36% (95% confidence interval [CI] 33.8-37.4; range 10.3-55.8%), whereas that of csPC was 18.5% (95% CI 16.6-20.3; range 3.4-46.5%). Detection rates of PC and csPC were found to be similar in men who underwent a target biopsy versus those with a systematic biopsy (23.5% vs 23.9% and 11.4% vs 12.3%, respectively) and lower than the rates achieved with the combined strategy (36.9% and 19.6%, respectively). A prostate-specific antigen density (PSAD) of ≥0.15ng/ml/ml may represent an index to decide whether to submit a PI-RADS 3 case to biopsy.

CONCLUSIONS

In most investigations, PI-RADS 3 cases were not evaluated separately. A PI-RADS 3 lesion remains an equivocal lesion. Evaluation of clinical predictive factors in terms of csPC risk is a main aspect of helping clinicians in the biopsy decision process.

PATIENT SUMMARY

Management of Prostate Imaging Reporting and Data System 3 cases remains an unmet need, and the detection rate of clinically significant prostate cancer (csPC) among this population varies widely. Performing a combined target plus a systematic biopsy yields the highest detection of csPC. A prostate-specific antigen density of lower than 0.15ng/ml/ml may select patients for a follow-up strategy.

Automated segmentation of prostate zonal anatomy on T2-weighted (T2W) and apparent diffusion coefficient (ADC) map MR images using U-Nets

PURPOSE

Accurate regional segmentation of the prostate boundaries on magnetic resonance (MR) images is a fundamental requirement before automated prostate cancer diagnosis can be achieved. In this paper, we describe a novel methodology to segment prostate whole gland (WG), central gland (CG), and peripheral zone (PZ), where PZ + CG = WG, from T2W and apparent diffusion coefficient (ADC) map prostate MR images.

METHODS

We designed two similar models each made up of two U-Nets to delineate the WG, CG, and PZ from T2W and ADC map MR images, separately. The U-Net, which is a modified version of a fully convolutional neural network, includes contracting and expanding paths with convolutional, pooling, and upsampling layers. Pooling and upsampling layers help to capture and localize image features with a high spatial consistency. We used a dataset consisting of 225 patients (combining 153 and 72 patients with and without clinically significant prostate cancer) imaged with multiparametric MRI at 3 Tesla.

RESULTS AND CONCLUSION

Our proposed model for prostate zonal segmentation from T2W was trained and tested using 1154 and 1587 slices of 100 and 125 patients, respectively. Median of Dice similarity coefficient (DSC) on test dataset for prostate WG, CG, and PZ were 95.33 ± 7.77%, 93.75 ± 8.91%, and 86.78 ± 3.72%, respectively. Designed model for regional prostate delineation from ADC map images was trained and validated using 812 and 917 slices from 100 and 125 patients. This model yielded a median DSC of 92.09 ± 8.89%, 89.89 ± 10.69%, and 86.1 ± 9.56% for prostate WG, CG, and PZ on test samples, respectively. Further investigation indicated that the proposed algorithm reported high DSC for prostate WG segmentation from both T2W and ADC map MR images irrespective of WG size. In addition, segmentation accuracy in terms of DSC does not significantly vary among patients with or without significant tumors.

SIGNIFICANCE

We describe a method for automated prostate zonal segmentation using T2W and ADC map MR images independent of prostate size and the presence or absence of tumor. Our results are important in terms of clinical perspective as fully automated methods for ADC map images, which are considered as one of the most important sequences for prostate cancer detection in the PZ and CG, have not been reported previously.

Diagnostic Accuracy of a Rapid Biparametric MRI Protocol for Detection of Histologically Proven Prostate Cancer

OBJECTIVE

To evaluate the performance of a rapid, low cost, noncontrast MRI examination as a secondary screening tool in detection of clinically significant prostate cancer.

METHODS

In this prospective single institution study, 129 patients with elevated prostate-specific antigen levels or abnormal digital rectal examination findings underwent MRI with an abbreviated biparamatric MRI protocol consisting of high-resolution axial T2- and diffusion-weighted images. Index lesions were classified according to modified Prostate Imaging - Reporting and Data System (mPI-RADS) version 2.0. All patients underwent standard transrectal ultrasound-guided biopsy after MRI with the urologist being blinded to MRI results. Subsequently, all patients with suspicious lesions (mPI-RADS 3, 4, or 5) underwent cognitively guided targeted biopsy after discussion of MRI results with the urologist. Sensitivity and negative predictive value for identification of clinically significant prostate cancer (Gleason score 3+4 and above) were determined.

RESULTS

Rapid biparametric MRI discovered 176 lesions identified in 129 patients. Rapid MRI detected clinically significant cancers with a sensitivity of 95.1% with a negative predictive value of 95.1% and positive predictive value of 53.2%, leading to a change in management in 10.8% of the patients. False negative rate of biparametric (bp) MRI was 4.7%.

CONCLUSION

We found that a bp-MRI examination can detect clinically significant lesions and changed patient management in 10.8% of the patients. A rapid MRI protocol can be used as a useful secondary screening tool in men presenting with suspicion of prostate cancer.