Comparison of biparametric MRI to full multiparametric MRI for detection of clinically significant prostate cancer

Biparametric versus multiparametric MRI for the detection of clinically significant prostate cancer in a diverse, multiethnic population

PURPOSE

There is not yet satisfactory performance data comparing multiparametric MRI (mpMRI) versus biparametric MRI (bpMRI) for detecting prostate cancer (PCa), particularly in high-risk populations. We compared both protocols for detecting overall PCa and clinically significant PCa (CS-PCa; defined as Grade Group ≥ 2) in a multiethnic urban population.

METHODS

We retrospectively reviewed electronic medical record data from men who underwent image-guided fusion prostate biopsy (FB) between 2016 and 2021 at our institution. Patient characteristics, Prostate Imaging Reporting and Data System (PI-RADS) scores, and FB outcomes were analyzed based on MRI protocol. Multivariate mixed-effects logistic regression models were used to examine associations of bpMRI versus mpMRI for detecting overall PCa and CS-PCa in targeted lesions, among all patients and stratified by race/ethnicity.

RESULTS

Overall, 566 men (44.0% Non-Hispanic Black [NHB]; 27.0% Hispanic) with 975 PI-RADS 3-5 lesions on MRI underwent FB. Of these, 312 (55%) men with 497 lesions underwent mpMRI and 254 (45%) men with 478 lesions underwent bpMRI. On multivariate analyses among all men, the odds of detecting overall PCa (OR = 1.18, 95% CI: 1.05-3.11, p = 0.031) and CS-PCa (OR = 2.15, 95% CI: 1.16-4.00, p = 0.014) on FB were higher for lesions identified on bpMRI than mpMRI. When stratified by race/ethnicity, the odds of detecting overall PCa (OR = 1.86; p = 0.15) and CS-PCa (OR = 2.20; p = 0.06) were not statistically different between lesions detected on bpMRI or mpMRI.

CONCLUSION

BpMRI has similar diagnostic performance to mpMRI in detecting overall and CS-PCa within a racially/ethnically diverse population. BpMRI can be utilized for evaluating suspected CS-PCa among NHB and Hispanic men.

Lifetime Health and Economic Outcomes of Biparametric Magnetic Resonance Imaging as First-Line Screening for Prostate Cancer : A Decision Model Analysis

BACKGROUND

Contemporary prostate cancer (PCa) screening uses first-line prostate-specific antigen (PSA) testing, possibly followed by multiparametric magnetic resonance imaging (mpMRI) for men with elevated PSA levels. First-line biparametric MRI (bpMRI) screening has been proposed as an alternative.

OBJECTIVE

To evaluate the comparative effectiveness and cost-effectiveness of first-line bpMRI versus PSA-based screening.

DESIGN

Decision analysis using a microsimulation model.

DATA SOURCES

Surveillance, Epidemiology, and End Results database; randomized trials.

TARGET POPULATION

U.S. men aged 55 years with no prior screening or PCa diagnosis.

TIME HORIZON

Lifetime.

PERSPECTIVE

U.S. health care system.

INTERVENTION

Biennial screening to age 69 years using first-line PSA testing (test-positive threshold, 4 µg/L) with or without second-line mpMRI or first-line bpMRI (test-positive threshold, PI-RADS [Prostate Imaging Reporting and Data System] 3 to 5 or 4 to 5), followed by biopsy guided by MRI or MRI plus transrectal ultrasonography.

OUTCOME MEASURES

Screening tests, biopsies, diagnoses, overdiagnoses, treatments, PCa deaths, quality-adjusted and unadjusted life-years saved, and costs.

RESULTS OF BASE-CASE ANALYSIS

For 1000 men, first-line bpMRI versus first-line PSA testing prevented 2 to 3 PCa deaths and added 10 to 30 life-years (4 to 11 days per person) but increased the number of biopsies by 1506 to 4174 and the number of overdiagnoses by 38 to 124 depending on the biopsy imaging scheme. At conventional cost-effectiveness thresholds, first-line PSA testing with mpMRI followed by either biopsy approach for PI-RADS 4 to 5 produced the greatest net monetary benefits.

RESULTS OF SENSITIVITY ANALYSIS

First-line PSA testing remained more cost-effective even if bpMRI was free, all men with low-risk PCa underwent surveillance, or screening was quadrennial.

LIMITATION

Performance of first-line bpMRI was based on second-line mpMRI data.

CONCLUSION

Decision analysis suggests that comparative effectiveness and cost-effectiveness of PCa screening are driven by false-positive results and overdiagnoses, favoring first-line PSA testing with mpMRI over first-line bpMRI.

PRIMARY FUNDING SOURCE

National Cancer Institute.

Bi-parametric prostate MRI with a recall system for contrast enhanced imaging: Improving accessibility while maintaining quality

PURPOSE

To review the efficacy of a recall system for bi-parametric non-contrast prostate MRI (bp-MRI).

METHODS

A bi-parametric protocol was instituted in July 2020 for all patients who had a prostate MRI requested, excluding those after treatment of prostate cancer, patients with hip prosthesis or pacemaker, and those who lived out-of-town. The protocol consisted of tri-planar T2-weighted and diffusion weighted images (DWI) (b = 50, 800 s/mm2 for ADC map; b = 1,500 s/mm2 acquired separately) in accordance with the Prostate Imaging Reporting & Data system (PI-RADS) v2.1 guidelines. After interpretation of bp-MRI exams, patients with equivocal (PI-RADS 3) lesions in peripheral zone (PZ) or any technical limitations were recalled for contrast administration.

RESULTS

Out of 909 bp-MRI scans performed from July 2020 to April 2021, only 52 (5.7 %) were recalled, of which 46 (88.5 %) attended. Amongst these, 41/52 (78.8 %) were recalled for PZ PI-RADS 3 lesions, while the rest of 11 (21.2 %) cases were recalled for technical reasons. Mean time to subsequent recall scan was 11.6 days. On assessment of post-contrast imaging, 29/46 (63 %) cases were upgraded to PI-RADS 4 while 17/46 (37 %) remained PI-RADS 3. This system avoided contrast-agent use in 857 patients, with contrast cost savings of €64,620 (US$68,560) and 214 hours 15 minutes of scanner time was saved. This allowed 255 additional bp-MRI scans to be performed, reducing the waitlist from 1 year to 2-3 weeks.

CONCLUSION

A bi-parametric prostate MRI protocol with a robust recall system for contrast administration not only saved time eliminating the marked backlog but was also more cost efficient without compromising the quality of patient care.

Dynamic Contrast-Enhanced Study in the mpMRI of the Prostate-Unnecessary or Underutilised? A Narrative Review

The aim of this review is to summarise recent scientific literature regarding the clinical use of DCE-MRI as a component of multiparametric resonance imaging of the prostate. This review presents the principles of DCE-MRI acquisition and analysis, the current role of DCE-MRI in clinical practice with special regard to its role in presently available categorisation systems, and an overview of the advantages and disadvantages of DCE-MRI described in the current literature. DCE-MRI is an important functional sequence that requires intravenous administration of a gadolinium-based contrast agent and gives information regarding the vascularity and capillary permeability of the lesion. Although numerous studies have confirmed that DCE-MRI has great potential in the diagnosis and monitoring of prostate cancer, its role is still inadequate in the PI-RADS categorisation. Moreover, there have been numerous scientific discussions about abandoning the intravenous application of gadolinium-based contrast as a routine part of MRI examination of the prostate. In this review, we summarised the recent literature on the advantages and disadvantages of DCE-MRI, focusing on an overview of currently available data on bpMRI and mpMRI, as well as on studies providing information on the potential better usability of DCE-MRI in improving the sensitivity and specificity of mpMRI examinations of the prostate.

Development and validation of a nomogram for predicting prostate cancer based on combining contrast-enhanced transrectal ultrasound and biparametric MRI imaging

Objectives

This study was to explore the feasibility of combining contrast-enhanced transrectal ultrasound (CE-TRUS) with biparametric MRI (CEUS-BpMRI) score for diagnosing prostate cancer (PCa).

Methods

A total of 183 patients with suspected PCa who underwent multiparametric MRI (Mp-MRI) and CE-TRUS were included. CEUS-BpMRI score was developed based on the results of Mp-MRI and CE-TRUS. The diagnostic performance was evaluated by the area under the curve (AUC). The diagnostic efficacy of the CEUS-BpMRI score, BpMRI score, and PI-RADS v2.1 score were compared. Total patients were randomly assigned to a training cohort (70%) or validation cohort (30%). A nomogram was constructed based on univariate and multivariate logistic regression. The model was evaluated by AUC and calibration curve.

Results

The diagnostic performance of CEUS-BpMRI score (AUC 0.857) was comparable to that of PI-RADS v2.1 (AUC 0.862) (P = 0.499), and both were superior to Bp-MRI score (AUC 0.831, P < 0.05). In peripheral zone lesions with Bp-MRI score of 3, there was no statistically significant difference between PI-RADS v2.1 score (AUC 0.728) and CEUS-BpMRI score (AUC 0.668) (P = 0.479). Multivariate analysis showed that age, total prostate specific antigen/free prostate specific antigen (F/T), time to peak (TTP), and CEUS-BpMRI score were independent factors. The AUC of the nomogram was 0.909 in the training cohort and 0.914 in the validation cohort.

Conclusions

CEUS-BpMRI score has high diagnostic efficacy for diagnosing PCa. A nomogram model established by combining age, F/T, TTP, and CEUS-BpMRI score can achieve the best predictive accuracy for PCa.

A nomogram based on biparametric magnetic resonance imaging for detection of clinically significant prostate cancer in biopsy-naïve patients

PURPOSE

This study aimed to develop and validate a model based on biparametric magnetic resonance imaging (bpMRI) for the detection of clinically significant prostate cancer (csPCa) in biopsy-naïve patients.

METHOD

This retrospective study included 324 patients who underwent bpMRI and MRI targeted fusion biopsy (MRGB) and/or systematic biopsy, of them 217 were randomly assigned to the training group and 107 were assigned to the validation group. We assessed the diagnostic performance of three bpMRI-based scorings in terms of sensitivity and specificity. Subsequently, 3 models (Model 1, Model 2, and Model 3) combining bpMRI scorings with clinical variables were constructed and compared with each other using the area under the receiver operating characteristic (ROC) curves (AUC). The statistical significance of differences among these models was evaluated using DeLong's test.

RESULTS

In the training group, 68 of 217 patients had pathologically proven csPCa. The sensitivity and specificity for Scoring 1 were 64.7% (95% CI 52.2%-75.9%) and 80.5% (95% CI 73.3%-86.6%); for Scoring 2 were 86.8% (95% CI 76.4%-93.8%) and 73.2% (95% CI 65.3%-80.1%); and for Scoring 3 were 61.8% (95% CI 49.2%-73.3%) and 80.5% (95% CI 73.3%-86.6%), respectively. Multivariable regression analysis revealed that scorings based on bpMRI, age, and prostate-specific antigen density (PSAD) were independent predictors of csPCa. The AUCs for the 3 models were 0.88 (95% CI 0.83-0.93), 0.90 (95% CI 0.85-0.94), and 0.88 (95% CI 0.83-0.93), respectively. Model 2 showed significantly higher performance than Model 1 (P = 0.03) and Model 3 (P < 0.01).

CONCLUSION

All three scorings had favorite diagnostic accuracy. While in conjunction with age and PSAD the prediction power was significantly improved, and the Model 2 that based on Scoring 2 yielded the highest performance.

Parametric maps of spatial two-tissue compartment model for prostate dynamic contrast enhanced MRI - comparison with the standard tofts model in the diagnosis of prostate cancer

The spatial two-tissue compartment model (2TCM) was used to analyze prostate dynamic contrast enhanced (DCE) MRI data and compared with the standard Tofts model. A total of 29 patients with biopsy-confirmed prostate cancer were included in this IRB-approved study. MRI data were acquired on a Philips Achieva 3T-TX scanner. After T2-weighted and diffusion-weighted imaging, DCE data using 3D T1-FFE mDIXON sequence were acquired pre- and post-contrast media injection (0.1 mmol/kg Multihance) for 60 dynamic scans with temporal resolution of 8.3 s/image. The 2TCM has one fast ([Formula: see text] and [Formula: see text]) and one slow ([Formula: see text] and [Formula: see text]) exchanging compartment, compared with the standard Tofts model parameters (Ktrans and kep). On average, prostate cancer had significantly higher values (p < 0.01) than normal prostate tissue for all calculated parameters. There was a strong correlation (r = 0.94, p < 0.001) between Ktrans and [Formula: see text] for cancer, but weak correlation (r = 0.28, p < 0.05) between kep and [Formula: see text]. Average root-mean-square error (RMSE) in fits from the 2TCM was significantly smaller (p < 0.001) than the RMSE in fits from the Tofts model. Receiver operating characteristic (ROC) analysis showed that fast [Formula: see text] had the highest area under the curve (AUC) than any other individual parameter. The combined four parameters from the 2TCM had a considerably higher AUC value than the combined two parameters from the Tofts model. The 2TCM is useful for quantitative analysis of prostate DCE-MRI data and provides new information in the diagnosis of prostate cancer.

Up-to-Date Imaging and Diagnostic Techniques for Prostate Cancer: A Literature Review

Prostate cancer (PCa) faces great challenges in early diagnosis, which often leads not only to unnecessary, invasive procedures, but to over-diagnosis and treatment as well, thus highlighting the need for modern PCa diagnostic techniques. The review aims to provide an up-to-date summary of chronologically existing diagnostic approaches for PCa, as well as their potential to improve clinically significant PCa (csPCa) diagnosis and to reduce the proliferation and monitoring of PCa. Our review demonstrates the primary outcomes of the most significant studies and makes comparisons across the diagnostic efficacies of different PCa tests. Since prostate biopsy, the current mainstream PCa diagnosis, is an invasive procedure with a high risk of post-biopsy complications, it is vital we dig out specific, sensitive, and accurate diagnostic approaches in PCa and conduct more studies with milestone findings and comparable sample sizes to validate and corroborate the findings.

Radiomics vs radiologist in prostate cancer. Results from a systematic review

PURPOSE

Radiomics in uro-oncology is a rapidly evolving science proving to be a novel approach for optimizing the analysis of massive data from medical images to provide auxiliary guidance in clinical issues. This scoping review aimed to identify key aspects wherein radiomics can potentially improve the accuracy of diagnosis, staging, and extraprostatic extension in prostate cancer (PCa).

METHODS

The literature search was performed on June 2022 using PubMed, Embase, and Cochrane Central Controlled Register of Trials. Studies were included if radiomics were compared with radiological reports only.

RESULTS

Seventeen papers were included. The combination of PIRADS and radiomics score models improves the PIRADS score reporting of 2 and 3 lesions even in the peripheral zone. Multiparametric MRI-based radiomics models suggest that by simply omitting diffusion contrast enhancement imaging in radiomics models can simplify the process of analysis of clinically significant PCa by PIRADS. Radiomics features correlated with the Gleason grade with excellent discriminative ability. Radiomics has higher accuracy in predicting not only the presence but also the side of extraprostatic extension.

CONCLUSIONS

Radiomics research on PCa mainly uses MRI as an imaging modality and is focused on diagnosis and risk stratification and has the best future possibility of improving PIRADS reporting. Radiomics has established its superiority over radiologist-reported outcomes but the variability has to be taken into consideration before translating it to clinical practice.

Could Biparametric MRI Replace Multiparametric MRI in the Management of Prostate Cancer?

Prostate cancer (PCa) is a worldwide epidemiological problem, since it is one of the most prevalent types of neoplasia among men, and the third-leading cause of cancer-related deaths, after lung and colorectal tumors. Unfortunately, the early stages of PCa have a wide range of unspecific symptoms. For these reasons, early diagnosis and accurate evaluation of suspicious lesions are crucial. Multiparametric MRI (mpMRI) is currently the imaging modality of choice for diagnostic screening and local staging of PCa, but also has a leading role in guiding biopsies and in treatment biparametric MRI (bpMRI) could partially replace mpMRI due to its lack of adverse reactions caused by contrast agents, relatively lower costs, and shorter acquisition time. Further, 31 relevant articles regarding the advantages and disadvantages of the aforementioned imaging techniques were scanned. As a result, while bpMRI has comparable accuracy in detecting PCa, its roles in the other steps of PCa management are limited.

Magnetic Resonance Imaging-Based Predictive Models for Clinically Significant Prostate Cancer: A Systematic Review

Simple Summary

Magnetic resonance imaging (MRI) has allowed the early detection of PCa to evolve towards clinically significant PCa (csPCa), decreasing unnecessary prostate biopsies and overdetection of insignificant tumours. MRI identifies suspicious lesions of csPCa, predicting the semi-quantitative risk through the prostate imaging report and data system (PI-RADS), and enables guided biopsies, increasing the sensitivity of csPCa. Predictive models that individualise the risk of csPCa have also evolved adding PI-RADS score (MRI-PMs), improving the selection of candidates for prostate biopsy beyond the PI-RADS category. During the last five years, many MRI-PMs have been developed. Our objective is to analyse the current developed MRI-PMs and define their clinical usefulness through a systematic review. We have found high heterogeneity between MRI technique, PI-RADS versions, biopsy schemes and approaches, and csPCa definitions. MRI-PMs outperform the selection of candidates for prostate biopsy beyond MRI alone and PMs based on clinical predictors. However, few developed MRI-PMs are externally validated or have available risk calculators (RCs), which constitute the appropriate requirements used in routine clinical practice.

Abstract

MRI can identify suspicious lesions, providing the semi-quantitative risk of csPCa through the Prostate Imaging-Report and Data System (PI-RADS). Predictive models of clinical variables that individualise the risk of csPCa have been developed by adding PI-RADS score (MRI-PMs). Our objective is to analyse the current developed MRI-PMs and define their clinical usefulness. A systematic review was performed after a literature search performed by two independent investigators in PubMed, Cochrane, and Web of Science databases, with the Medical Subjects Headings (MESH): predictive model, nomogram, risk model, magnetic resonance imaging, PI-RADS, prostate cancer, and prostate biopsy. This review was made following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) criteria and studied eligibility based on the Participants, Intervention, Comparator, and Outcomes (PICO) strategy. Among 723 initial identified registers, 18 studies were finally selected. Warp analysis of selected studies was performed with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Clinical predictors in addition to the PI-RADS score in developed MRI-PMs were age, PCa family history, digital rectal examination, biopsy status (initial vs. repeat), ethnicity, serum PSA, prostate volume measured by MRI, or calculated PSA density. All MRI-PMs improved the prediction of csPCa made by clinical predictors or imaging alone and achieved most areas under the curve between 0.78 and 0.92. Among 18 developed MRI-PMs, 7 had any external validation, and two RCs were available. The updated PI-RADS version 2 was exclusively used in 11 MRI-PMs. The performance of MRI-PMs according to PI-RADS was only analysed in a single study. We conclude that MRI-PMs improve the selection of candidates for prostate biopsy beyond the PI-RADS category. However, few developed MRI-PMs meet the appropriate requirements in routine clinical practice.

Head-to-head comparison of biparametric versus multiparametric MRI of the prostate before robot-assisted transperineal fusion prostate biopsy

Purpose

Prostate biparametric magnetic resonance imaging (bpMRI) including T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) might be an alternative to multiparametric MRI (mpMRI, including dynamic contrast imaging, DCE) to detect and guide targeted biopsy in patients with suspected prostate cancer (PCa). However, there is no upgrading peripheral zone PI-RADS 3 to PI-RADS 4 without DCE in bpMRI. The aim of this study was to evaluate bpMRI against mpMRI in biopsy-naïve men with elevated prostate-specific antigen (PSA) scheduled for robot-assisted-transperineal fusion-prostate biopsy (RA-TB).

Methods

Retrospective single-center-study of 563 biopsy-naïve men (from 01/2015 to 09/2018, mean PSA 9.7 ± 6.5 ng/mL) with PI-RADSv2.1 conform mpMRI at 3 T before RA-TB. Clinically significant prostate cancer (csPCa) was defined as ISUP grade ≥ 2 in any core. Two experienced readers independently evaluated images according to PI-RADSv2.1 criteria (separate readings for bpMRI and mpMRI sequences, 6-month interval). Reference standard was histology from RA-TB.

Results

PI-RADS 2 was scored in 5.1% of cases (3.4% cancer/3.4% csPCa), PI-RADS 3 in 16.9% (32.6%/3.2%), PI-RADS 4 in 57.6% (66.1%/58.3%) and PI-RADS 5 in 20.4% of cases (79.1%/74.8%). For mpMRI/bpMRI test comparison, sensitivity was 99.0%/97.1% (p < 0.001), specificity 47.5%/61.2% (p < 0.001), PPV 69.5%/75.1% (p < 0.001) and NPV 97.6%/94.6% (n.s.). csPCa was considered gold standard. 35 cases without cancer were upgraded to PI-RADS 4 (mpMRI) and six PI-RADS 3 cases with csPCa were not upgraded (bpMRI).

Conclusion

In patients planned for RA-TB with elevated PSA and clinical suspicion for PCa, specificity was higher in bpMRI vs. mpMRI, which could solve constrains regarding time and contrast agent.

Cost-effectiveness analysis of short biparametric magnetic resonance imaging protocol in men at risk of prostate cancer

OBJECTIVES

To compare the cost-effectiveness of a short biparametric MRI (BP-MRI) with that of contrast-enhanced multiparametric MRI (MP-MRI) for the detection of prostate cancer in men with elevated prostatespecific antigen (PSA) levels.

MATERIALS AND METHODS

We compared two diagnostic procedures for detection of prostate cancer (Pca), BP-MRI and MP-MRI, in terms of quality-adjusted life years (QALY), incremental costeffectiveness ratio (ICER) and net monetary benefit (NMB) for a hypothetical cohort of 10,000 patients. We compared two scenarios in which different protocols would be used for the early diagnosis of prostate cancer in relation to PSA values. Scenario 1. BP-MRI/MP-MRI yearly if > 3.0 ng/ml, every 2 years otherwise; Scenario 2. BP-MRI/MP-MRI yearly with age-dependent threshold 3.5 ng/ml (50-59 years), 4.5 ng/ml (60-69 years), 6.5 ng/ml (70-79 years).

RESULTS

BP-MRI was more effective than the comparator in terms of cost (160.10 € vs 249.99€) QALYs (a mean of 9.12 vs 8.46), ICER (a mean of 232.45) and NMB (a mean of 273.439 vs 251.863). BP-MRI was dominant, being more effective and less expensive, with a lower social cost. Scenario 2 was more cost-effective compared to scenario 1.

CONCLUSIONS

Our results confirmed the hypothesis that a short bi-parametric MRI protocol represents a cost-efficient procedure, optimizing resources in a policy perspective.

The role of preoperative prostatic shape in the recovery of urinary continence after robotic radical prostatectomy: a single cohort analysis

BACKGROUND

To explore the role of preoperative MRI prostate shape in urinary incontinence after robot-assisted radical prostatectomy (RARP).

METHODS

Patients were stratified into four groups based on the mpMRI prostatic apex shape: Group A (prostatic apex overlapping the membranous urethra anteriorly and posteriorly), Group B and C (overlap of the prostatic apex of the anterior or posterior membranous urethra, respectively) and Group D (no overlap). Preoperative variables and intraoperative data were compared. Continence recovery was defined as no pad/day or 1 safety pad/day by an outpatient evaluation performed at 1, 3, 6, and 12 months after RARP.

RESULTS

One hundred patients underwent RARP were classified as belonging to Group A (n = 30), Group B (n = 16), Group C (n = 14), and Group D (n = 40). Group D showed a significantly more favorable urinary continence recovery after RARP respect to all the other shapes presenting any forms of overlapping (HR = 1.9, 95% CI 1.2-3.1, p = 0.007). The estimated HR remained substantially unchanged after adjusting by age, body mass index, CCI, prostate volume, and bladder neck sparing (HR = 1.9, 95% CI 1.1-3.2, p = 0.016). The continence recovery median time was 9 months for Group A + B + C (95% CI 5-11) and 4 months for Group D (95% CI 2-6) (p = 0.023).

CONCLUSION

Shape D showed a better continence recovery when compared to other shapes presenting any kind of overlapping of the prostatic apex over the membranous urethra.

Current Status of Biparametric MRI in Prostate Cancer Diagnosis: Literature Analysis

The role of multiparametric MRI (mpMRI) in the detection of prostate cancer is well-established. Based on the limited role of dynamic contrast enhancement (DCE) in PI-RADS v2.1, the risk of potential side effects, and the increased cost and time, there has been an increase in studies advocating for the omission of DCE from MRI assessments. Per PI-RADS v2.1, DCE is indicated in the assessment of PI-RADS 3 lesions in the peripheral zone, with its most pronounced effect when T2WI and DWI are of insufficient quality. The aim of this study was to evaluate the methodology and reporting in the literature from the past 5 years regarding the use of DCE in prostate MRI, especially with respect to the indications for DCE as stated in PI-RADS v2.1, and to describe the different approaches used across the studies. We searched for studies investigating the use of bpMRI and/or mpMRI in the detection of clinically significant prostate cancer between January 2017 and April 2022 in the PubMed, Web of Science, and Google Scholar databases. Through the search process, a total of 269 studies were gathered and 41 remained after abstract and full-text screening. The following information was extracted from the eligible studies: general clinical and technical characteristics of the studies, the number of PI-RADS 3 lesions, different definitions of clinically significant prostate cancer (csPCa), biopsy thresholds, reference standard methods, and number and experience of readers. Forty-one studies were included in the study. Only 51% (21/41) of studies reported the prevalence of csPCa in their equivocal lesion (PI-RADS category 3 lesions) subgroups. Of the included studies, none (0/41) performed a stratified sub-analysis of the DCE benefit versus MRI quality and 46% (19/41) made explicit statements about removing MRI scans based on a range of factors including motion, noise, and image artifacts. Furthermore, the number of studies investigating the role of DCE using readers with varying experience was relatively low. This review demonstrates that a high proportion of the studies investigating whether bpMRI can replace mpMRI did not transparently report information inherent to their study design concerning the key indications of DCE, such as the number of clinically insignificant/significant PI-RADS 3 lesions, nor did they provide any sub-analyses to test image quality, with some removing bad quality MRI scans altogether, or reader-experience-dependency indications for DCE. For the studies that reported on most of the DCE indications, their conclusions about the utility of DCE were heavily definition-dependent (with varying definitions of csPCa and of the PI-RADS category biopsy significance threshold). Reporting the information inherent to the study design and related to the specific indications for DCE as stated in PI-RADS v2.1 is needed to determine whether DCE is helpful or not. With most of the recent literature being retrospective and not including the data related to DCE indications in particular, the ongoing dispute between bpMRI and mpMRI is likely to linger.

A narrative review of biparametric MRI (bpMRI) implementation on screening, detection, and the overall accuracy for prostate cancer

Prostate cancer is the most common malignancy in American men following skin cancer, with approximately one in eight men being diagnosed during their lifetime. Over the past several decades, the treatment of prostate cancer has evolved rapidly, so too has screening. Since the mid-2010s, magnetic resonance imaging (MRI)–guided biopsies or ‘targeted biopsies’ has been a rapidly growing topic of clinical research within the field of urologic oncology. The aim of this publication is to provide a review of biparametric MRI (bpMRI) utilization for the diagnosis of prostate cancer and a comparison to multiparametric MRI (mpMRI). Through single-centered studies and meta-analysis across all identified pertinent published literature, bpMRI is an effective tool for the screening and diagnosis of prostate cancer. When compared with the diagnostic accuracy of mpMRI, bpMRI identifies prostate cancer at comparable rates. In addition, when omitting dynamic contrast-enhanced (DCE) protocol to the MRI, patients incur reduced costs and shorter imaging time while providers can offer more tests to their patient population.

Convolutional neural network-based reconstruction for acceleration of prostate T2 weighted MR imaging: a retro- and prospective study

OBJECTIVE

The aim of this study was to develop a deep neural network (DNN)-based parallel imaging reconstruction for highly accelerated 2D turbo spin echo (TSE) data in prostate MRI without quality degradation compared to conventional scans.

METHODS

155 participant data were acquired for training and testing. Two DNN models were generated according to the number of acquisitions (NAQ) of input images: DNN-N1 for NAQ = 1 and DNN-N2 for NAQ = 2. In the test data, DNN and TSE images were compared by quantitative error metrics. The visual appropriateness of DNN reconstructions on accelerated scans (DNN-N1 and DNN-N2) and conventional scans (TSE-Conv) was assessed for nine parameters by two radiologists. The lesion detection was evaluated at DNNs and TES-Conv by prostate imaging-reporting and data system.

RESULTS

The scan time was reduced by 71% at NAQ = 1, and 42% at NAQ = 2. Quantitative evaluation demonstrated the better error metrics of DNN images (29-43% lower NRMSE, 4-13% higher structure similarity index, and 2.8-4.8 dB higher peak signal-to-noise ratio; p < 0.001) than TSE images. In the assessment of the visual appropriateness, both radiologists evaluated that DNN-N2 showed better or comparable performance in all parameters compared to TSE-Conv. In the lesion detection, DNN images showed almost perfect agreement (κ > 0.9) scores with TSE-Conv.

CONCLUSIONS

DNN-based reconstruction in highly accelerated prostate TSE imaging showed comparable quality to conventional TSE.

ADVANCES IN KNOWLEDGE

Our framework reduces the scan time by 42% of conventional prostate TSE imaging without sequence modification, revealing great potential for clinical application.

Cancer-specific outcomes for prostate cancer patients who had prebiopsy prostate MRI

PURPOSE

We characterized population-level cancer-specific outcomes for prostate cancer patients based on use of prebiopsy prostate MRI.

METHODS

Using SEER-Medicare claims, we identified men diagnosed with localized prostate cancer from 2010-2015 and prostate-specific antigen (PSA) < 20 ng/mL. Primary exposure was prebiopsy prostate MRI prior to diagnosis (i.e., CPT 72197 linked to urology-specific diagnosis). Outcomes included diagnosis of Grade Group 2+ disease on biopsy and proportion treated with prostatectomy. We assessed those treated with prostatectomy and evaluated association with prebiopsy MRI and grade concordance between biopsy and prostatectomy. We estimated adjusted odds ratios with multivariable regression after accounting for other factors (e.g., age, year, PSA, race/ethnicity).

RESULTS

We identified 48,574 patients, where 915 (1.9%) underwent prebiopsy MRI. Patients with prebiopsy MRI had more GG>2 cancer on biopsy (70.0% MRI vs. 62.8% no MRI) but lost significance after adjustment (OR 1.12, 95% CI 0.96-1.30). Patients with prebiopsy MRI were more likely to have prostatectomy (39.2% vs. 28.5%, adjusted OR 1.51, 95%CI 1.31-1.76). Downgrading from biopsy GG 3-5 to final GG 1-2 was less common after prebiopsy MRI (21.3% vs. 28.2% no MRI, P = 0.05) but not significant after adjustment (OR 0.74, 95% CI 0.51 - 1.08). Among 14,027 men with prostatectomy, accurate risk classification was not more likely with a prebiopsy MRI (48.0% no MRI vs. 49.6% prebiopsy MRI, P = 0.56).

CONCLUSION

During initial adoption, men with prebiopsy prostate MRI had marginally increased detection of significant cancer on biopsy and were more likely to be treated with prostatectomy. For those treated with prostatectomy, use of prebiopsy MRI was not associated with a greater likelihood of accurate risk classification or grade concordance between biopsy and final pathology results.

A narrative review of MRI acquisition for MR-guided-radiotherapy in prostate cancer

Magnetic resonance guided radiotherapy (MRgRT), enabled by the clinical introduction of the integrated MRI and linear accelerator (MR-LINAC), is a novel technique for prostate cancer (PCa) treatment, promising to further improve clinical outcome and reduce toxicity. The role of prostate MRI has been greatly expanded from the traditional PCa diagnosis to also PCa screening, treatment and surveillance. Diagnostic prostate MRI has been relatively familiar in the community, particularly with the development of Prostate Imaging - Reporting and Data System (PI-RADS). But, on the other hand, the use of MRI in the emerging clinical practice of PCa MRgRT, which is substantially different from that in PCa diagnosis, has been so far sparsely presented in the medical literature. This review attempts to give a comprehensive overview of MRI acquisition techniques currently used in the clinical workflows of PCa MRgRT, from treatment planning to online treatment guidance, in order to promote MRI practice and research for PCa MRgRT. In particular, the major differences in the MRI acquisition of PCa MRgRT from that of diagnostic prostate MRI are demonstrated and explained. Limitations in the current MRI acquisition for PCa MRgRT are analyzed. The future developments of MRI in the PCa MRgRT are also discussed.

MRI Based Radiomics Compared With the PI-RADS V2.1 in the Prediction of Clinically Significant Prostate Cancer: Biparametric vs Multiparametric MRI

Purpose

To compare the performance of radiomics to that of the Prostate Imaging Reporting and Data System (PI-RADS) v2.1 scoring system in the detection of clinically significant prostate cancer (csPCa) based on biparametric magnetic resonance imaging (bpMRI) vs. multiparametric MRI (mpMRI).

Methods

A total of 204 patients with pathological results were enrolled between January 2018 and December 2019, with 142 patients in the training cohort and 62 patients in the testing cohort. The radiomics model was compared with the PI-RADS v2.1 for the diagnosis of csPCa based on bpMRI and mpMRI by using receiver operating characteristic (ROC) curve analysis.

Results

The radiomics model based on bpMRI and mpMRI signatures showed high predictive efficiency but with no significant differences (AUC = 0.975 vs 0.981, p=0.687 in the training cohort, and 0.953 vs 0.968, p=0.287 in the testing cohort, respectively). In addition, the radiomics model outperformed the PI-RADS v2.1 in the diagnosis of csPCa regardless of whether bpMRI (AUC = 0.975 vs. 0.871, p= 0.030 for the training cohort and AUC = 0.953 vs. 0.853, P = 0.024 for the testing cohort) or mpMRI (AUC = 0.981 vs. 0.880, p= 0.030 for the training cohort and AUC = 0.968 vs. 0.863, P = 0.016 for the testing cohort) was incorporated.

Conclusions

Our study suggests the performance of bpMRI- and mpMRI-based radiomics models show no significant difference, which indicates that omitting DCE imaging in radiomics can simplify the process of analysis. Adding radiomics to PI-RADS v2.1 may improve the performance to predict csPCa.

Clinically Significant Prostate Cancer Detection After A Negative Prebiopsy MRI Examination: Comparison of Biparametric Versus Multiparametric MRI

Background: The frequency of clinically significant prostate cancer (csPCa) following negative biparametric MRI (bpMRI) and multiparametric MRI (mpMRI) has not been well investigated in direct comparative studies. Objective: To compare the frequency of csPCa after negative prebiopsy bpMRI and mpMRI, and to evaluate factors that predict csPca in the two cohorts. Methods: This retrospective study included 232 men (mean age, 64.5 years) with negative bpMRI from August 2017 to March 2020 and193 men (mean age, 69.0 years) with negative mpMRI from January 2018 to December 2018, defining PI-RADS category of 1 or 2 as negative. Our institution offers bpMRI as a low-cost self-pay option for patients without insurer coverage of prebiospy mpMRI. Patient characteristics and subsequent biopsy results were recorded. csPCa was defined as Gleason score ≥3+4. Multivariable regression analyses were performed to identify independent predictors of csPCa. AUC of prostate specific antigen density (PSAD) for csPCA was computed, and diagnostic performance of PSAD was assessed at a clinically established threshold of 0.15 ng/mL2. Results: Systematic biopsy was performed after negative bpMRI in 41.4% (96/232), versus after negative mpMRI in 30.5% (59/193) (p=.02). Among those undergoing biopsy, csPCa was present in 15.6% (15/96) in the mpMRI cohort versus 13.6% (8/59) in the bpMRI cohort (p=.69). NPV for csPCa was 84% (81/96) for bpMRI and 86% (51/59) for mpMRI. In multivariable analyses, independent predictors of csPCa included smaller prostate volume (OR=0.27, p<.001) and greater PSAD (OR=3.09, p<.001). In multivariable models, bpMRI (compared with mpMRI) did not independently predict csPCa (p>.05). PSAD had AUC for csPCa of 0.77 (95% CI: 0.64, 0.89) in the bpMRI cohort versus 0.68 (95% CI: 0.42, 0.93) in the mpMRI cohort. For detecting csPCa, PSAD threshold of 0.15 ng/mL2 had NPV of 90% and PPV of 28%, in the bpMRI cohort, versus NPV of 92% and PPV of 44%in the mpMRI cohort. Conclusion: The frequency of csPCa was not significantly different on systematic biopsy performed after negative bpMRI and mpMRI examinations. PSAD had similar diagnostic utility for csPca in both cohorts. Clinical Impact: Either bpMRI or mpMRI, in combination with PSAD, can help avoid negative prostate biopsies.

Modified Predictive Model and Nomogram by Incorporating Prebiopsy Biparametric Magnetic Resonance Imaging With Clinical Indicators for Prostate Biopsy Decision Making

Purpose

The purpose of this study is to explore the value of combining bpMRI and clinical indicators in the diagnosis of clinically significant prostate cancer (csPCa), and developing a prediction model and Nomogram to guide clinical decision-making.

Methods

We retrospectively analyzed 530 patients who underwent prostate biopsy due to elevated serum prostate specific antigen (PSA) levels and/or suspicious digital rectal examination (DRE). Enrolled patients were randomly assigned to the training group (n = 371, 70%) and validation group (n = 159, 30%). All patients underwent prostate bpMRI examination, and T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) sequences were collected before biopsy and were scored, which were respectively named T2WI score and DWI score according to Prostate Imaging Reporting and Data System version 2 (PI-RADS v.2) scoring protocol, and then PI-RADS scoring was performed. We defined a new bpMRI-based parameter named Total score (Total score = T2WI score + DWI score). PI-RADS score and Total score were separately included in the multivariate analysis of the training group to determine independent predictors for csPCa and establish prediction models. Then, prediction models and clinical indicators were compared by analyzing the area under the curve (AUC) and decision curves. A Nomogram for predicting csPCa was established using data from the training group.

Results

In the training group, 160 (43.1%) patients had prostate cancer (PCa), including 128 (34.5%) with csPCa. Multivariate regression analysis showed that the PI-RADS score, Total score, f/tPSA, and PSA density (PSAD) were independent predictors of csPCa. The prediction model that was defined by Total score, f/tPSA, and PSAD had the highest discriminatory power of csPCa (AUC = 0.931), and the diagnostic sensitivity and specificity were 85.1% and 87.5%, respectively. Decision curve analysis (DCA) showed that the prediction model achieved an optimal overall net benefit in both the training group and the validation group. In addition, the Nomogram predicted csPCa revealed good estimation when compared with clinical indicators.

Conclusion

The prediction model and Nomogram based on bpMRI and clinical indicators exhibit a satisfactory predictive value and improved risk stratification for csPCa, which could be used for clinical biopsy decision-making.

A risk model for detecting clinically significant prostate cancer based on bi-parametric magnetic resonance imaging in a Japanese cohort

Selective identification of men with clinically significant prostate cancer (sPC) is a pivotal issue. Development of a risk model for detecting sPC based on the prostate imaging reporting and data system (PI-RADS) for bi-parametric magnetic resonance imaging (bpMRI) and clinical parameters in a Japanese cohort is expected to prove beneficial. We retrospectively analyzed clinical parameters and bpMRI findings from 773 biopsy-naïve patients between January 2011 and December 2016. A risk model was established using multivariate logistic regression analysis and presented on a nomogram. Discrimination of the risk model was compared using the area under the receiver operating characteristic curve. Statistical differences between the predictive model and clinical parameters were analyzed using DeLong test. sPC was detected in 343 men (44.3%). Multivariate logistic regression analysis to predict sPC revealed age (P = 0.002), log prostate-specific antigen (P < 0.001), prostate volume (P < 0.001) and PI-RADS scores (P < 0.001) as significant contributors to the model. Area under the curve was higher for the risk model (0.862), than for age (0.646), log prostate-specific antigen (0.652), prostate volume (0.697) or imaging score (0.822). DeLong test results also showed that the novel risk model performed significantly better than those parameters (P < 0.05). This novel risk model performed significantly better compared with PI-RADS scores and other parameters alone, and is thus expected to prove beneficial in making decisions regarding biopsy on suspicion of sPC.

Magnetic Resonance Imaging (MRI)-Targeted Biopsy in Patients with Prostate-Specific Antigen (PSA) Levels <20 ng/mL: A Single-Center Study in Northeastern China

Background

We investigated the feasibility of applying magnetic resonance imaging (MRI)-targeted biopsy (TB) in patients with prostate-specific antigen (PSA) levels <20 ng/mL.

Material/Methods

We retrospectively analyzed 218 patients with PSA levels <20 ng/mL and suspicious lesions according to the Prostate Imaging Recording and Data System version 2.0 (PI-RADS v2). All 218 men underwent transperineal MRI-TB, followed by template-guided 12-core systematic biopsy (SB). Of the 218 patients undergoing TB, 100 received MRI-ultrasound-assisted software fusion biopsy (FB) and 118 received cognitive biopsy (CB). Clinically significant prostate cancer (csPCa) was defined as a Gleason score ≥3+4.

Results

The overall TB positive rate was similar to that of SB (P=0.156), but with a higher diagnostic rate for csPCa (P=0.034). SB misdiagnosed csPCa in 11.47% of cases; TB misdiagnosed csPCa in 5.50% of cases. SB+TB detected more tumors with a Gleason score of 7 than did SB alone (43 vs 22). Detection rates of csPCa were similar for CB and FB (P=0.217). In total, 47 men had 2 MRI-determined suspicious areas. Of 265 suspicious areas, 143 (53.96%) had a PI-RADS v2 score of 3; 92 (34.71%) had a score of 4; and 30 (11.32%) had a score of 5. The positive detection rates for csPCa in patients with PI-RADS v2 scores of 3, 4, and 5, were 11.19%, 48.91%, and 80.00%, respectively.

Conclusions

TB increased the positive biopsy detection rate but missed some cases of csPCa. TB combined with SB may be the most suitable biopsy for patients with PSA <20 ng/mL.

Diagnostic Accuracy of Single-plane Biparametric and Multiparametric Magnetic Resonance Imaging in Prostate Cancer: A Randomized Noninferiority Trial in Biopsy-naïve Men

BACKGROUND

Urological guidelines recommend multiparametric magnetic resonance imaging (mpMRI) in men with a suspicion of prostate cancer (PCa). The resulting increase in MRI demand might place health care systems under substantial stress.

OBJECTIVE

To determine whether single-plane biparametric MRI (fast MRI) workup could represent an alternative to mpMRI in the detection of clinically significant (cs) PCa.

DESIGN, SETTING, AND PARTICIPANTS

Between April 2018 and February 2020, 311 biopsy-naïve men aged ≤75 yr with PSA ≤15 ng/ml and negative digital rectal examination were randomly assigned to 1.5-T fast MRI (n = 213) or mpMRI (n = 98).

INTERVENTION

All MRI examinations were classified according to Prostate Imaging-Reporting and Data System (PI-RADS) version 2. Men scored PI-RADS 1-2 underwent 12-core standard biopsy (SBx) and those with PI-RADS 4-5 on fast MRI or PI-RADS 3-5 on mpMRI underwent targeted biopsy in combination with SBx. Equivocal cases on fast MRI (PI-RADS 3) underwent mpMRI and then biopsy according to the findings.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The primary outcome was to compare the detection rate of csPCa in both study arms, setting a 10% difference for noninferiority. The secondary outcome was to assess the role of prostate-specific antigen density (PSAD) in ruling out men who could avoid biopsy among those with equivocal findings on fast MRI.

RESULTS AND LIMITATIONS

The overall MRI detection rate for csPCa was 23.5% (50/213; 95% confidence interval [CI] 18.0-29.8%) with fast MRI and 32.7% (32/98; 95% CI 23.6-42.9%) with mpMRI (difference 9.2%; p = 0.09). The reproducibility of the study could have been affected by its single-center nature.

CONCLUSIONS

Fast MRI followed by mpMRI in equivocal cases is not inferior to mpMRI in the detection of csPCa among biopsy-naïve men aged ≤75 yr with PSA ≤15 ng/ml and negative digital rectal examination. These findings could pave the way to broader use of MRI for PCa diagnosis.

PATIENT SUMMARY

A faster MRI (magnetic resonance imaging) protocol with no contrast agent and fewer scan sequences for examination of the prostate is not inferior to the typical MRI approach in the detection of clinically significant prostate cancer. If our findings are confirmed in other studies, fast MRI could represent a time-saving and less invasive examination for men with suspicion of prostate cancer. This trial is registered at ClinicalTrials.gov as NCT03693703.

Diagnostic Ability of Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Prostate Cancer and Clinically Significant Prostate Cancer in Equivocal Lesions: A Systematic Review and Meta-Analysis

Background

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) now has been used to diagnose prostate cancer (PCa). Equivocal lesions are defined as PIRADS category 3 or a Likert scale of 1 to 5 category 3 lesions. Currently, there are no clear recommendations for the management of these lesions. This study aimed to estimate the diagnostic capacity of DCE-MRI for PCa and clinically significant prostate cancer (csPCa) in equivocal lesions.

Materials and methods

Two researchers searched PubMed, Embase and Web of Science to identify studies that met our subject. We searched for articles that mention the accuracy of the diagnosis of DCE-MRI for PCa or csPCa in equivocal lesions and used histopathological results as the reference standard. We used a tool (the Quality Assessment of Diagnostic Accuracy Studies-2 tool) to evaluate the quality of the studies that we screened out. Meta-regression was used to explore the reasons for heterogeneity in results.

Results

Ten articles were eventually included in our study. The sensitivity, specificity and 95% confidence intervals (CI) for DCE-MRI in diagnosing csPCa were 0.67 (95% CI, 0.56–0.76), 0.58 (95% CI, 0.46–0.68). The sensitivity and specificity and 95% CI for DCE-MRI in diagnosing PCa were 0.57 (95% CI, 0.46–0.68), 0.58 (95% CI, 0.45–0.70). The areas under the curve (AUC) of DCE-MRI were 0.67 (95% CI, 0.63–0.71) and 0.60 (95% CI, 0.55–0.64) while diagnosing csPCa and PCa. Through meta-regression, we found that study design, magnetic field strength, the definition of csPCa, and the scoring system were the sources of heterogeneity.

Conclusion

The results of our study indicate that the role of DCE-MRI in equivocal lesions may be limited.

A Predictive Model Based on Bi-parametric Magnetic Resonance Imaging and Clinical Parameters for Clinically Significant Prostate Cancer in the Korean Population

PURPOSE

This study aimed to develop and validate a predictive model for the assessment of clinically significant prostate cancer (csPCa) in men, prior to prostate biopsies, based on bi-parametric magnetic resonance imaging (bpMRI) and clinical parameters.

Materials and Methods

We retrospectively analyzed 300 men with clinical suspicion of prostate cancer (prostate-specific antigen [PSA] ≥ 4.0 ng/mL and/or abnormal findings in a digital rectal examination), who underwent bpMRI-ultrasound fusion transperineal targeted and systematic biopsies in the same session, at a Korean university hospital. Predictive models, based on Prostate Imaging Reporting and Data Systems scores of bpMRI and clinical parameters, were developed to detect csPCa (intermediate/high grade [Gleason score ≥ 3+4]) and compared by analyzing the areas under the curves and decision curves.

RESULTS

A predictive model defined by the combination of bpMRI and clinical parameters (age, PSA density) showed high discriminatory power (area under the curve, 0.861) and resulted in a significant net benefit on decision curve analysis. Applying a probability threshold of 7.5%, 21.6% of men could avoid unnecessary prostate biopsy, while only 1.0% of significant prostate cancers were missed.

CONCLUSION

This predictive model provided a reliable and measurable means of risk stratification of csPCa, with high discriminatory power and great net benefit. It could be a useful tool for clinical decision-making prior to prostate biopsies.

Rectal gas-induced susceptibility artefacts on prostate diffusion-weighted MRI with epi read-out at 3.0 T: does a preparatory micro-enema improve image quality?

PURPOSE

To assess whether the application of a preparatory micro-enema reduces gas-induced susceptibility artefacts on diffusion-weighted MRI of the prostate.

METHODS

114 consecutive patients who received multiparametric 3 T MRI of the prostate at our institution were retrospectively enrolled. 63 patients self-administered a preparatory micro-enema prior to imaging, and 51 patients underwent MRI without bowel preparation. Two blinded readers independently reviewed the diffusion-weighted sequences regarding gas-induced artefacts. The presence/severity of artefacts was scored ranging from 0 (no artefact) to 3 (severe artefact). A score ≥ 2 was considered a clinically relevant artefact. Maximum rectal width at the level of the prostate was correlated with the administration of a micro-enema. Scores were compared between the scans performed with and without bowel preparation using univariable and multivariable logistic regression, taking into account potential confounding factors (age and prostate volume).

RESULTS

Significantly less artefacts were found on diffusion-weighted sequences after the administration of a micro-enema shortly prior to MR imaging. Clinically relevant artefacts were found in 10% in the patient group after enema, in 41% without enema. If present, artefacts were also significantly less severe. Mean severity score was 0.3 (enema administered) and 1.2 (no enema), and odds ratio was 0.137 (p < 0.0001) in univariable ordinal logistic regression. Inter-observer agreement was excellent (κ 0.801).

CONCLUSION

The use of a preparatory micro-enema prior to 3 T multiparametric prostate MRI significantly reduces both the incidence and severity of gas-induced artefacts on diffusion-weighted sequences and thus improves image quality.

How Fast Can We Go: Abbreviated Prostate MR Protocols

PURPOSE OF REVIEW

Multiparametric MRI (mpMRI), composed of T2WI, DWI, and DCE sequences, is effective in identifying prostate cancer (PCa), but length and cost preclude its application as a PCa screening tool. Here we review abbreviated MRI protocols that shorten or omit conventional mpMRI components to reduce scan time and expense without forgoing diagnostic accuracy.

RECENT FINDINGS

The DCE sequence, which plays a limited diagnostic role in PI-RADS, is eliminated in variations of the biparametric MRI (bpMRI). T2WI, the lengthiest sequence, is truncated by only acquiring the axial plane or utilizing 3D acquisition with subsequent 2D reconstruction. DW-EPI_SMS further accelerates DWI acquisition. The fastest protocol described to date consists of just DW-EPI_SMS and axial-only 2D T2WI and runs less than 5 min. Abbreviated protocols can mitigate scan expense and increase scan access, allowing prostate MRI to become an efficient PCa screening tool.

Advances in Prostate Magnetic Resonance Imaging

Prostate magnetic resonance (MR) imaging is a widely used imaging technique to detect intraprostatic lesions and guide prostate biopsies, with continuous technical advances for better accuracy in prostate cancer diagnosis. Current evaluation of prostate multiparametric MR imaging mainly depends on qualitative evaluation, which is prone to inter-reader variation. Recent advances in prostate MR imaging, such as quantitative T2 mapping and abbreviated MR imaging protocols (eg, biparametric MR imaging), are designed to simplify prostate MR imaging acquisition and interpretation.

Biparametric prostate MRI and clinical indicators predict clinically significant prostate cancer in men with "gray zone" PSA levels

PURPOSE

To predict clinically significant prostate cancer (cs-PCa) by combining the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) score based on biparametric magnetic resonance imaging (bp-MRI) and clinical indicators in men with prostate-specific antigen (PSA) levels in the gray zone of 4-10 ng/mL.

METHOD

We retrospectively analyzed 364 patients with elevated PSA levels in the gray zone who had pathologically confirmed disease and had undergone MRI examinations from January 2015 to October 2019; a training group (n = 255) and validation group (n = 109) were randomly established. Multivariate logistic regression analysis of the training group was performed to identify the independent predictors for cs-PCa, thereby establishing a predictive model that was evaluated in the training and validation groups by analyzing the receiver operating characteristic (ROC) curve.

RESULTS

In the training group, the PI-RADS v2 score and prostate volume (PV) were independent predictors of cs-PCa (P < 0.05). The prediction model comprising the PI-RADS v2 score and PV had a larger AUC than the other predictors alone in the training group. The diagnostic sensitivity and specificity of the prediction model were 84.1 % and 83.4 %, respectively. The prediction model was indicated to have better predictive performance in the validation group.

CONCLUSIONS

The prediction model exhibits a satisfactory predictive value for cs-PCa in men with PSA levels in the gray zone. PI-RADS v2 is the strongest univariate predictor for the detection of cs-PCa in men with PSA in the gray zone, but combining this with the PV can provide superior predictive ability.

Biparametric versus multiparametric magnetic resonance imaging of the prostate: detection of clinically significant cancer in a perfect match group

Background

Biparametric (bp) magnetic resonance imaging (MRI) could be an alternative MRI for the detection of the clinically significant prostate cancer (csPCa).

Purpose

To compare the accuracies of prostate cancer detection and localization between prebiopsy bpMRI and postbiopsy multiparametric MRI (mpMRI) taken on different days, using radical prostatectomy specimens as the reference standards.

Material and methods

Data of 41 total consecutive patients who underwent the following examinations and procedures between September 2015 and March 2017 were collected: (1) magnetic resonance- and/or ultrasonography-guided biopsy after bpMRI; (2) postbiopsy mpMRI; and (3) radical prostatectomy with csPCa. Two radiologists scored suspected lesions on bpMRI and mpMRI independently using Prostate Imaging Reporting and Data System version 2. The diagnostic accuracy of detecting csPCa and the Dice similarity coefficient were obtained. Apparent diffusion coefficient (ADC) ratios were also obtained for quantitative comparison between bpMRI and mpMRI.

Results

Diagnostic accuracies on bpMRI and mpMRI were 0.83 and 0.82 for reader 1; 0.80 and 0.82 for reader 2. There are no significantly different values of diagnostic sensitivities or specificities between the readers or between MRI protocols. Intra-observer Dice similarity coefficient was significantly lower in reader 2, compared to that in reader 1 between the two MRI protocols. The range of mean ADC ratio was 0.281-0.635. There was no statistically significant difference in the ADC ratio between bpMRI and mpMRI.

Conclusions

Diagnostic performance of bpMRI without dynamic contrast enhancement MRI is not significantly different from mpMRI with dynamic contrast enhancement MRI in the detection of csPCa.

Investigating the equivalent performance of biparametric compared to multiparametric MRI in detection of clinically significant prostate cancer

PURPOSE

PIRADS v2 stipulates that dynamic contrast-enhanced (DCE) imaging be used to categorize diffusion-weighted-imaging (DWI) score 3 (DWI 3) peripheral zone (PZ) lesions as PIRADS score 3 (PIRADS 3; DCE -) or PIRADS 4 (DCE +). It's controversial for the value of DCE in improving clinically significant prostate cancer (csPCa) detection. We aimed to figure out whether DCE improves csPCa detection and explore new available measures to improve csPCa detection.

PATIENTS AND METHODS

We retrospectively enrolled 375 patients who underwent mp MRI before MRI/ultrasound (US) fusion-targeted biopsy (TB) with transperineal systematic biopsy (SB). All lesions were classified as DWI 3/DCE -, DWI 3/DCE +, DWI 4/PIRADS 4 lesions. Detection rates of csPCa for each lesion group were analyzed. The diagnostic performance of each approach was analyzed by receiver operating characteristics (ROC) analysis and decision curve analysis.

RESULTS

Totally, 109 DWI 3 or DWI 4 single lesions in PZ were analyzed (n = 109). The rates of csPCa detection for Group A, Group B, Group C is 10.3%, 13.9%, 55.9%, respectively (A vs. B, p = 0.625; B vs. C, p < 0.001). ROC analysis and decision curve analysis showed the method of combining Age, PSA Density (PSAD) and the mean apparent diffusion coefficient value (ADC_mean) outperforms individual approaches for csPCa detection.

CONCLUSION

For DWI 3 lesions in PZ, DCE sequence has not additional value for improving detection of csPCa. The integration of clinical characteristics and bpMRI parameter improves the detection of csPCa.

A Hybrid End-to-End Approach Integrating Conditional Random Fields into CNNs for Prostate Cancer Detection on MRI

Prostate Cancer (PCa) is the most common oncological disease in Western men. Even though a growing effort has been carried out by the scientific community in recent years, accurate and reliable automated PCa detection methods on multiparametric Magnetic Resonance Imaging (mpMRI) are still a compelling issue. In this work, a Deep Neural Network architecture is developed for the task of classifying clinically significant PCa on non-contrast-enhanced MR images. In particular, we propose the use of Conditional Random Fields as a Recurrent Neural Network (CRF-RNN) to enhance the classification performance of XmasNet, a Convolutional Neural Network (CNN) architecture specifically tailored to the PROSTATEx17 Challenge. The devised approach builds a hybrid end-to-end trainable network, CRF-XmasNet, composed of an initial CNN component performing feature extraction and a CRF-based probabilistic graphical model component for structured prediction, without the need for two separate training procedures. Experimental results show the suitability of this method in terms of classification accuracy and training time, even though the high-variability of the observed results must be reduced before transferring the resulting architecture to a clinical environment. Interestingly, the use of CRFs as a separate postprocessing method achieves significantly lower performance with respect to the proposed hybrid end-to-end approach. The proposed hybrid end-to-end CRF-RNN approach yields excellent peak performance for all the CNN architectures taken into account, but it shows a high-variability, thus requiring future investigation on the integration of CRFs into a CNN.

The role of gadolinium in magnetic resonance imaging for early prostate cancer diagnosis: A diagnostic accuracy study

Objective

Prostate lesions detected with multiparametric magnetic resonance imaging (mpMRI) are classified for their malignant potential according to the Prostate Imaging-Reporting And Data System (PI-RADS™2). In this study, we evaluate the diagnostic accuracy of the mpMRI with and without gadolinium, with emphasis on the added diagnostic value of the dynamic contrast enhancement (DCE).

Materials and methods

The study was retrospective for 286 prostate lesions / 213 eligible patients, n = 116/170, and 49/59% malignant for the peripheral (Pz) and transitional zone (Tz), respectively. A stereotactic MRI-guided prostate biopsy served as the histological ground truth. All patients received a mpMRI with DCE. The influence of DCE in the prediction of malignancy was analyzed by blinded assessment of the imaging protocol without DCE and the DCE separately.

Results

Significant (CSPca) and insignificant (IPca) prostate cancers were evaluated separately to enhance the potential effects of the DCE in the detection of CSPca. The Receiver Operating Characteristics Area Under Curve (ROC-AUC), sensitivity (Se) and specificity (Spe) of PIRADS-without-DCE in the Pz was 0.70/0.47/0.86 for all cancers (IPca and CSPca merged) and 0.73/0.54/0.82 for CSPca. PIRADS-with-DCE for the same patients showed ROC-AUC/Se/Spe of 0.70/0.49/0.86 for all Pz cancers and 0.69/0.54/0.81 for CSPca in the Pz, respectively, p>0.05 chi-squared test. Similar results for the Tz, AUC/Se/Spe for PIRADS-without-DCE was 0.75/0.61/0.79 all cancers and 0.67/0.54/0.71 for CSPca, not influenced by DCE (0.66/0.47/0.81 for all Tz cancers and 0.61/0.39/0.75 for CSPca in Tz). The added Se and Spe of DCE for the detection of CSPca was 88/34% and 78/33% in the Pz and Tz, respectively.

Conclusion

DCE showed no significant added diagnostic value and lower specificity for the prediction of CSPca compared to the non-enhanced sequences. Our results support that gadolinium might be omitted without mitigating the diagnostic accuracy of the mpMRI for prostate cancer.