Detection of prostate cancer with multiparametric MRI (mpMRI): effect of dedicated reader education on accuracy and confidence of index and anterior cancer diagnosis

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.

Enhancing prostate MRI expertise: educational strategies for radiologists

The adoption of multiparametric MRI (mpMRI) and the Prostate Imaging Reporting and Data System has significantly changed prostate cancer diagnosis and management. These advancements, alongside novel biomarkers and updated International Society of Uropathology grade groups, have improved cancer detection and prognostication. Despite this progress, varying levels of expertise in mpMRI among radiologists have resulted in inconsistent assessments, potentially leading to unnecessary procedures and diminished confidence in the modality. This review assesses the educational landscape for prostate MRI, highlighting available resources for radiologists at all professional stages. It emphasizes the need for targeted educational strategies to bridge knowledge gaps and improve patient care outcomes in prostate cancer management.

Value of MRI - T2 Mapping to Differentiate Clinically Significant Prostate Cancer

Standardized reporting of multiparametric prostate MRI (mpMRI) is widespread and follows international standards (Pi-RADS). However, quantitative measurements from mpMRI are not widely comparable. Although T2 mapping sequences can provide repeatable quantitative image measurements and extract reliable imaging biomarkers from mpMRI, they are often time-consuming. We therefore investigated the value of quantitative measurements on a highly accelerated T2 mapping sequence, in order to establish a threshold to differentiate benign from malignant lesions. For this purpose, we evaluated a novel, highly accelerated T2 mapping research sequence that enables high-resolution image acquisition with short acquisition times in everyday clinical practice. In this retrospective single-center study, we included 54 patients with clinically indicated MRI of the prostate and biopsy-confirmed carcinoma (n = 37) or exclusion of carcinoma (n = 17). All patients had received a standard of care biopsy of the prostate, results of which were used to confirm or exclude presence of malignant lesions. We used the linear mixed-effects model-fit by REML to determine the difference between mean values of cancerous tissue and healthy tissue. We found good differentiation between malignant lesions and normal appearing tissue in the peripheral zone based on the mean T2 value. Specifically, the mean T2 value for tissue without malignant lesions was (151.7 ms [95% CI: 146.9-156.5 ms] compared to 80.9 ms for malignant lesions [95% CI: 67.9-79.1 ms]; p < 0.001). Based on this assessment, a limit of 109.2 ms is suggested. Aditionally, a significant correlation was observed between T2 values of the peripheral zone and PI-RADS scores (p = 0.0194). However, no correlation was found between the Gleason Score and the T2 relaxation time. Using REML, we found a difference of -82.7 ms in mean values between cancerous tissue and healthy tissue. We established a cut-off-value of 109.2 ms to accurately differentiate between malignant and non-malignant prostate regions. The addition of T2 mapping sequences to routine imaging could benefit automated lesion detection and facilitate contrast-free multiparametric MRI of the prostate.

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.

Comparison of procedural anxiety and pain associated with conventional transrectal ultrasound prostate biopsy to magnetic resonance imaging-ultrasound fusion-guided biopsy: a prospective cohort trial

BACKGROUND

Prostate cancer (PCa) diagnosis relies on biopsies, with transrectal ultrasound (TRUS) biopsies being common. Fusion biopsy (FB) offers improved diagnostic accuracy, but the pain and anxiety experienced by patients during biopsies is often overlooked. This study aims to compare pain and anxiety levels between standard TRUS-guided biopsy (STB) and systematic plus MRI/US fusion biopsy (STB + FB).

MATERIALS AND METHODS

The study involved adult men undergoing biopsies, receiving identical peri-procedural care, including 2% lidocaine jelly in the rectum and subsequent 1% lidocaine injections (10cc per side) into the prostate-seminal vesicle junction and prostatic apical areas bilaterally. The biopsy technique was chosen based on clinical and imaging findings. Pre- and post-biopsy anxiety levels were assessed using the State-Trait Anxiety Inventory (STAI) questionnaire, categorized as mild (20-37), moderate (38-44), or severe (45-80). Post-biopsy pain was evaluated on a numerical rating scale, ranging from 0 to 10.

RESULTS

Of the 165 patients, 99 underwent STB, and 66 underwent STB + FB. No significant differences were observed in age, race, prostate-specific antigen, prostate volume, or prior biopsies between the groups. The STB + FB group had more biopsy cores taken (16.2 vs. 12, p = 0.001) and a longer procedure time (23 vs. 10 min, p = 0.001). STB biopsy patients experienced lower post-procedural anxiety compared to STB + FB, with a mean difference of -7 (p = 0.001, d = 0.92). In the STB + FB group, 89% experienced severe post-procedural anxiety compared to 59% in STB (p = 0.002). There was no significant difference in post-procedural pain (p = 0.7). Patients with prior biopsies had significantly higher STAI(S) anxiety scores (p = 0.005), and the number of prior biopsies correlated with anxiety severity (p = 0.04) in STB + FB group.

CONCLUSION

In summary, STB + FB group demonstrated higher post-procedural anxiety levels than the STB group, with no difference in pain levels. Additionally, patients with a history of repeat biopsies were more likely to exhibit higher STAI(S) anxiety scores.

A Comparative Evaluation of Multiparametric Magnetic Resonance Imaging and Micro-Ultrasound for the Detection of Clinically Significant Prostate Cancer in Patients with Prior Negative Biopsies

BACKGROUND

The diagnostic process for prostate cancer after a negative biopsy is challenging. This study compares the diagnostic accuracy of micro-ultrasound (mUS) with multiparametric magnetic resonance imaging (mpMRI) for such cases.

METHODS

A retrospective cohort study was performed, targeting men with previous negative biopsies and using mUS and mpMRI to detect prostate cancer and clinically significant prostate cancer (csPCa).

RESULTS

In our cohort of 1397 men, 304 had a history of negative biopsies. mUS was more sensitive than mpMRI, with better predictive value for negative results. Importantly, mUS was significantly associated with csPCa detection (adjusted odds ratio [aOR]: 6.58; 95% confidence interval [CI]: 1.15-37.8; p = 0.035).

CONCLUSIONS

mUS may be preferable for diagnosing prostate cancer in previously biopsy-negative patients. However, the retrospective design of this study at a single institution suggests that further research across multiple centers is warranted.

Variability in prostate cancer detection among radiologists and urologists using MRI fusion biopsy

Objectives

The aim of this study is to evaluate the impact of radiologist and urologist variability on detection of prostate cancer (PCa) and clinically significant prostate cancer (csPCa) with magnetic resonance imaging (MRI)-transrectal ultrasound (TRUS) fusion prostate biopsies.

Patients and methods

The Prospective Loyola University MRI (PLUM) Prostate Biopsy Cohort (January 2015 to December 2020) was used to identify men receiving their first MRI and MRI/TRUS fusion biopsy for suspected PCa. Clinical, MRI and biopsy data were stratified by radiologist and urologist to evaluate variation in Prostate Imaging-Reporting and Data System (PI-RADS) grading, lesion number and cancer detection. Multivariable logistic regression (MVR) models and area under the curve (AUC) comparisons assessed the relative impact of individual radiologists and urologists.

Results

A total of 865 patients (469 biopsy-naïve) were included across 5 urologists and 10 radiologists. Radiologists varied with grading 15.4% to 44.8% of patients with MRI lesions as PI-RADS 3. PCa detection varied significantly by radiologist, from 34.5% to 66.7% (p = 0.003) for PCa and 17.2% to 50% (p = 0.001) for csPCa. Urologists' PCa diagnosis rates varied between 29.2% and 55.8% (p = 0.013) and between 24.6% and 39.8% (p = 0.36) for csPCa. After adjustment for case-mix on MVR, a fourfold to fivefold difference in PCa detection was observed between the highest-performing and lowest-performing radiologist (OR 0.22, 95%CI 0.10-0.47, p < 0.001). MVR demonstrated improved AUC for any PCa and csPCa detection when controlling for radiologist variation (p = 0.017 and p = 0.038), but controlling for urologist was not significant (p = 0.22 and p = 0.086). Any PCa detection (OR 1.64, 95%CI 1.06-2.55, p = 0.03) and csPCa detection (OR 1.57, 95%CI 1.00-2.48, p = 0.05) improved over time (2018-2020 vs. 2015-2017).

Conclusions

Variability among radiologists in PI-RADS grading is a key area for quality improvement significantly impacting the detection of PCa and csPCa. Variability for performance of MRI-TRUS fusion prostate biopsies exists by urologist but with less impact on overall detection of csPCa.

Clinical outcomes of anterior prostate cancers treated with robotic assisted radical prostatectomy

Introduction

A prospective cohort study comparing peri- and postoperative outcomes for patients with predominantly anterior prostate cancer (APC) identified preoperatively against non-anterior prostate cancer (NAPC) treated via robotic-assisted radical prostatectomy (RARP).

Patients and Methods

Of the 757 RARP's completed between January 2016 and April 2018, two comparative cohorts for anterior and an equivalent group of non-anterior prostate tumours each consisting of 152 patients were compared against each other. Data were collected on the following variables: patient age; operating consultant; preoperative PSA, ISUP grade, degree of nerve sparing; tumour staging; presence and location of positive surgical margins; PSA density, postoperative ISUP grade; treatment paradigm and postoperative PSA, erectile function, and continence outcomes with 2-year follow-up.

Results

APCs were found to have significantly lower ISUP grading postoperatively; increased diagnosis via active surveillance over new diagnosis; more frequently undertaken bilateral nerve-sparing and long-term poorer continence outcomes at 18 and 24 months postoperatively (p < 0.05). Pre- and post-op PSA levels, erectile function, PSA density, positive surgical margins (PSM), age and tumour staging showed no significant differences between the APC and NAPC cohorts (p > 0.05).

Conclusion

The lower ISUP grading could indicate APC as overall being less aggressive than NAPC, whereas the poorer long-term continence outcomes require further investigating. The non-significant differences amongst tumour staging, PSA density, preoperative PSA levels and PSM rates suggest that APC may not be as significant as predicted in diagnostic evaluation. Overall, this study provides useful information on the growing literature of anterior prostate cancer. Being the largest comparative cohort study to date on APC post-RARP, these results indicate the true characteristics of anterior tumours and their functional outcomes to help improve education, patient expectations and management.

A multicenter study of artificial intelligence-aided software for detecting visible clinically significant prostate cancer on mpMRI

BACKGROUND

AI-based software may improve the performance of radiologists when detecting clinically significant prostate cancer (csPCa). This study aims to compare the performance of radiologists in detecting MRI-visible csPCa on MRI with and without AI-based software.

MATERIALS AND METHODS

In total, 480 multiparametric MRI (mpMRI) images were retrospectively collected from eleven different MR devices, with 349 csPCa lesions in 180 (37.5%) cases. The csPCa areas were annotated based on pathology. Sixteen radiologists from four hospitals participated in reading. Each radiologist was randomly assigned to 30 cases and diagnosed twice. Half cases were interpreted without AI, and the other half were interpreted with AI. After four weeks, the cases were read again in switched mode. The mean diagnostic performance was compared using sensitivity and specificity on lesion level and patient level. The median reading time and diagnostic confidence were assessed.

RESULTS

On lesion level, AI-aided improved the sensitivity from 40.1% to 59.0% (18.9% increased; 95% confidence interval (CI) [11.5, 26.1]; p < .001). On patient level, AI-aided improved the specificity from 57.7 to 71.7% (14.0% increase, 95% CI [6.4, 21.4]; p < .001) while preserving the sensitivity (88.3% vs. 93.9%, p = 0.06). AI-aided reduced the median reading time of one case by 56.3% from 423 to 185 s (238-s decrease, 95% CI [219, 260]; p < .001), and the median diagnostic confidence score was increased by 10.3% from 3.9 to 4.3 (0.4-score increase, 95% CI [0.3, 0.5]; p < .001).

CONCLUSIONS

AI software improves the performance of radiologists by reducing false positive detection of prostate cancer patients and also improving reading times and diagnostic confidence.

CLINICAL RELEVANCE STATEMENT

This study involves the process of data collection, randomization and crossover reading procedure.

Utility of dual read in the setting of prostate MRI interpretation

PURPOSE

The purpose of this study is to assess the utility of dual reader interpretation of prostate MRI in the evaluation/detection of prostate cancer, using the PI-RADS v2.1 scoring system.

METHODS

We performed a retrospective study to assess the utility of dual reader interpretation for prostate MRI. All MRI cases compiled for analysis were accompanied with prostate biopsy pathology reports that included Gleason scores to correlate to the MRI PI-RADS v2.1 score, tissue findings and location of pathology within the prostate gland. To assess for dual reader utility, two fellowship trained abdominal imagers (each with > 5 years of experience) provided independent and concurrent PI-RADS v2.1 scores on all included MRI examinations, which were then compared to the biopsy proven Gleason scores.

RESULTS

After application of inclusion criteria, 131 cases were used for analysis. The mean age of the cohort was 63.6 years. Sensitivity, specificity and positive/negative predictive values were calculated for each reader and concurrent scores. Reader 1 demonstrated 71.43% sensitivity, 85.39% specificity, 69.77% PPV and 86.36% NPV. Reader 2 demonstrated 83.33% sensitivity, 78.65% specificity, 64.81% PPV and 90.91% NPV. Concurrent reads demonstrated 78.57% sensitivity, 80.9% specificity, 66% PPV and 88.89% NPV. There was no statistically significant difference between the individual readers or concurrent reads (p = 0.79).

CONCLUSION

Our results highlight that dual reader interpretation in prostate MRI is not needed to detect clinically relevant tumor and that radiologists with experience and training in prostate MRI interpretation establish acceptable sensitivity and specificity marks on PI-RADS v2.1 assessment.

Comparison of prostate cancer detection rate at targeted biopsy of hub and spoke centers mpMRI: experience matters

BACKGROUND

Latest changes in European guidelines on prostate cancer determined a widespread of multiparametric magnetic resonance imaging (mpMRI) even in less experienced centers due to an increased demand. This could decrease diagnostic accuracy of targeted biopsy (TB) since image interpretation can be challenging and requires adequate and supervised training. Therefore we aimed to evaluate the prostate cancer (PCa) detection rate on TB according to mpMRI center's volume and experience.

METHODS

We retrospectively analyzed data of 737 patients who underwent mpMRI-TB at our institution. Patients were stratified according to mpMRI center: Hub (high volume >100 exams/year with dedicated radiologists and supervised training) and Spoke center (low volume <100 exams/year without dedicated radiologists and/or supervised training). Detection rate of PCa at TB and possible predictors of clinically significant PCa (csPCa) at TB. Differences in detection rate were explored using Chi-square test. Predictors of csPCa were evaluated through uni and multivariable logistic regression. The adjustment for casemix included: age, PSA, mpMRI center, lesion's location, PSA density, PI-RADS score and index lesion's size.

RESULTS

Four hundred forty-nine (60.9%) and 288 (39.1%) patients underwent mpMRI at a Hub or Spoke center, respectively. Hub group had higher detection rate for both any (60.3% vs. 48.1%) and csPCa (46.9% vs 38.7%; all P≤0.001). After stratifying for PI-RADS score, Hub group had higher detection rate for PI-RADS score 3 (csPCA 25.2% vs. 15.7%; p 0.04) and 4 (csPCa 65.7% vs. 45.7%; P=0.001). At multivariable analyses, receiving an mpMRI scan at a Spoke center was an independent predictor for csPCa on TB (OR 0.65; P=0.04).

CONCLUSIONS

mpMRI performed in Hub centers provided a significantly higher PCa yield on TB. A dedicated team of experienced radiologist, a supervised training for mpMRI and a central revision of mpMRI performed in non-experienced centres are essential to avoid unnecessary and potentially harmful procedures.

Study of T2 mapping in quantifying and discriminating uterine lesions under different magnetic field strengths: 1.5 T vs. 3.0 T

BACKGROUND

MRI is the best imaging tool for the evaluation of uterine tumors, but conventional MRI diagnosis results rely on radiologists and contrast agents (if needed). As a new objective, reproducible and contrast-agent free quantification technique, T2 mapping has been applied to a number of diseases, but studies on the evaluation of uterine lesions and the influence of magnetic field strength are few. Therefore, the aim of this study was to systematically investigate and compare the performance of T2 mapping as a nonenhanced imaging tool in discriminating common uterine lesions between 1.5 T and 3.0 T MRI systems.

METHODS

A total of 50 healthy subjects and 126 patients with suspected uterine lesions were enrolled in our study, and routine uterine MRI sequences with additional T2 mapping sequences were performed. T2 maps were calculated by monoexponential fitting using a custom code in MATLAB. T2 values of normal uterine structures in the healthy group and lesions (benign: adenomyosis, myoma, endometrial polyps; malignant: cervical cancer, endometrial carcinoma) in the patient group were collected. The differences in T2 values between 1.5 T MRI and 3.0 T MRI in any normal structure or lesion were compared. The comparison of T2 values between benign and malignant lesions was also performed under each magnetic field strength, and the diagnostic efficacies of the T2 value obtained through receiver operating characteristic (ROC) analysis were compared between 1.5 T and 3.0 T.

RESULTS

The mean T2 value of any normal uterine structure or uterine lesion under 3.0 T MRI was significantly lower than that under 1.5 T MRI (p < 0.05). There were significant differences in T2 values between each lesion subgroup under both 1.5 T and 3.0 T MRI. Moreover, the T2 values of benign lesions (71.1 ± 22.0 ms at 1.5 T and 63.4 ± 19.1 ms at 3.0 T) were also significantly lower than those of malignant lesions (101.1 ± 4.5 ms at 1.5 T and 93.5 ± 5.1 ms at 3.0 T) under both field strengths. In the aspect of differentiating benign from malignant lesions, the area under the curve of the T2 value under 3.0 T (0.94) was significantly higher than that under 1.5 T MRI (0.90) (p = 0.02).

CONCLUSION

T2 mapping can be a potential tool for quantifying common uterine lesions, and it has better performance in distinguishing benign from malignant lesions under 3.0 T MRI.

Second-opinion reads in prostate MRI: added value of subspecialty interpretation and review at multidisciplinary rounds

Purpose

This study evaluates the impact of second-opinion review of multiparametric prostate MRI for cancer detection by a multidisciplinary review board at a tertiary care center when compared with the initial community radiologist interpretation.

Methods

Cases were collected retrospectively from multidisciplinary prostate MRI rounds from 2017 to 2020 at a single tertiary care center. Patients with suspected prostate cancer or on active surveillance were referred for consideration of TRUS/MRI-fusion biopsy based on community-read prostate MRIs. All MRIs were re-read by subspecialized abdominal radiologists and a PI-RADS score assigned. Targeted fusion and 8–12 core systematic biopsy was performed in patients with PIRADS ≥ 3 lesions. Cohen kappa values were used to quantify interobserver agreement. Positive predictive value (PPV) was used to determine accuracy of PI-RADS score for detection of clinically significant prostate cancer (csPCa) (ISUP Grade Group ≥ 2).

Results

Three hundred and thirty-two lesions in 303 patients were reviewed and 252 lesions in 198 patients biopsied. The PI-RADS score was concordant in 60.5% of lesions, downgraded in 17.8%, and upgraded in 7.8%. Agreement between community and tertiary center interpretation was fair (κ = 0.354), with greater agreement for PI-RADS ≥ 4 (κ = 0.523) than PI-RADS ≥ 3 (κ = 0.456), and peripheral zone (κ = 0.419) than transition zone lesions (κ = 0.251). Prevalence of csPCa in biopsied lesions was 40.9%.

Conclusion

There is variability in community and tertiary care center interpretation of prostate MRI in cancer detection, with higher concordance rates for higher grade and peripheral zone lesions. These differences demonstrate the added value of multidisciplinary round review and highlight the need for ongoing education and feedback.

Graphical abstract

The learning curve in bladder MRI using VI-RADS assessment score during an interactive dedicated training program

OBJECTIVE

The purpose of the study was to evaluate the effect of an interactive training program on the learning curve of radiology residents for bladder MRI interpretation using the VI-RADS score.

METHODS

Three radiology residents with minimal experience in bladder MRI served as readers. They blindly evaluated 200 studies divided into 4 subsets of 50 cases over a 3-month period. After 2 months, the first subset was reassessed, resulting in a total of 250 evaluations. An interactive training program was provided and included educational lessons and case-based practice. The learning curve was constructed by plotting mean agreement as the ratio of correct evaluations per batch. Inter-reader agreement and diagnostic performance analysis were performed with kappa statistics and ROC analysis.

RESULTS

As for the VI-RADS scoring agreement, the kappa differences between pre-training and post-training evaluation of the same group of cases were 0.555 to 0.852 for reader 1, 0.522 to 0.695 for reader 2, and 0.481 to 0.794 for reader 3. Using VI-RADS ≥ 3 as cut-off for muscle invasion, sensitivity ranged from 84 to 89% and specificity from 91 to 94%, while the AUCs from 0.89 (95% CI:0.84, 0.94) to 0.90 (95% CI:0.86, 0.95). Mean evaluation time decreased from 5.21 ± 1.12 to 3.52 ± 0.69 min in subsets 1 and 5. Mean grade of confidence improved from 3.31 ± 0.93 to 4.21 ± 0.69, in subsets 1 and 5.

CONCLUSION

An interactive dedicated education program on bladder MRI and the VI-RADS score led to a significant increase in readers' diagnostic performance over time, with a general improvement observed after 100-150 cases.

KEY POINTS

• After the first educational lesson and 100 cases were interpreted, the concordance on VI-RADS scoring between the residents and the experienced radiologist was significantly higher. • An increase in the grade of confidence was experienced after 100 cases. • We found a decrease in the evaluation time after 150 cases.

Multi-resolution super learner for voxel-wise classification of prostate cancer using multi-parametric MRI

Multi-parametric MRI (mpMRI) is a critical tool in prostate cancer (PCa) diagnosis and management. To further advance the use of mpMRI in patient care, computer aided diagnostic methods are under continuous development for supporting/supplanting standard radiological interpretation. While voxel-wise PCa classification models are the gold standard, few if any approaches have incorporated the inherent structure of the mpMRI data, such as spatial heterogeneity and between-voxel correlation, into PCa classification. We propose a machine learning-based method to fill in this gap. Our method uses an ensemble learning approach to capture regional heterogeneity in the data, where classifiers are developed at multiple resolutions and combined using the super learner algorithm, and further account for between-voxel correlation through a Gaussian kernel smoother. It allows any type of classifier to be the base learner and can be extended to further classify PCa sub-categories. We introduce the algorithms for binary PCa classification, as well as for classifying the ordinal clinical significance of PCa for which a weighted likelihood approach is implemented to improve the detection of less prevalent cancer categories. The proposed method has shown important advantages over conventional modeling and machine learning approaches in simulations and application to our motivating patient data.

Structured reporting in radiologic education - Potential of different PI-RADS versions in prostate MRI controlled by in-bore MR-guided biopsies

Objectives:

To evaluate the efficiency of structured reporting in radiologic education – based on the example of different PI-RADS score versions for multiparametric MRI (mpMRI) of the prostate.

Methods:

MpMRI of 688 prostate lesions in 180 patients were retrospectively reviewed by an experienced radiologist and by a student using PI-RADS V1 and V2. Data sets were reviewed for changes according to PI-RADS V2.1. The results were correlated with results obtained by MR-guided biopsy. Diagnostic potency was evaluated by ROC analysis. Sensitivity, specificity and correct-graded samples were evaluated for different cutpoints. The agreement between radiologist and student was determined for the aggregation of the PI-RADS score in three categories. The student’s time needed for evaluation was measured.

Results:

The area under curve of the ROC analysis was 0.782/0.788 (V1/V2) for the student and 0.841/0.833 (V1/V2) for the radiologist. The agreement between student and radiologist showed a Cohen‘s weighted κ coefficient of 0.495 for V1 and 0.518 for V2. Median student’s time needed for score assessment was 4:34 min for PI-RADSv1 and 2:00 min for PI-RADSv2 (p < 0.001). Re-evaluation for V2.1 changed the category in 1.4% of all ratings.

Conclusion:

The capacity of prostate cancer detection using PI-RADS V1 and V2 is dependent on the reader‘s experience. The results from the two observers indicate that structured reporting using PI-RADS and, controlled by histopathology, can be a valuable and quantifiable tool in students‘ or residents’ education. Herein, V2 was superior to V1 in terms of inter-observer agreement and time efficacy.

Advances in knowledge:

Structured reporting can be a valuable and quantifiable tool in radiologic education. Structured reporting using PI-RADS can be used by a student with good performance. PI-RADS V2 is superior to V1 in terms of inter-observer agreement and time efficacy.

End-to-end prostate cancer detection in bpMRI via 3D CNNs: Effects of attention mechanisms, clinical priori and decoupled false positive reduction

We present a multi-stage 3D computer-aided detection and diagnosis (CAD) model² for automated localization of clinically significant prostate cancer (csPCa) in bi-parametric MR imaging (bpMRI). Deep attention mechanisms drive its detection network, targeting salient structures and highly discriminative feature dimensions across multiple resolutions. Its goal is to accurately identify csPCa lesions from indolent cancer and the wide range of benign pathology that can afflict the prostate gland. Simultaneously, a decoupled residual classifier is used to achieve consistent false positive reduction, without sacrificing high sensitivity or computational efficiency. In order to guide model generalization with domain-specific clinical knowledge, a probabilistic anatomical prior is used to encode the spatial prevalence and zonal distinction of csPCa. Using a large dataset of 1950 prostate bpMRI paired with radiologically-estimated annotations, we hypothesize that such CNN-based models can be trained to detect biopsy-confirmed malignancies in an independent cohort. For 486 institutional testing scans, the 3D CAD system achieves 83.69±5.22% and 93.19±2.96% detection sensitivity at 0.50 and 1.46 false positive(s) per patient, respectively, with 0.882±0.030 AUROC in patient-based diagnosis -significantly outperforming four state-of-the-art baseline architectures (U-SEResNet, UNet++, nnU-Net, Attention U-Net) from recent literature. For 296 external biopsy-confirmed testing scans, the ensembled CAD system shares moderate agreement with a consensus of expert radiologists (76.69%; kappa = 0.51±0.04) and independent pathologists (81.08%; kappa = 0.56±0.06); demonstrating strong generalization to histologically-confirmed csPCa diagnosis.

Accuracy of Prostate Magnetic Resonance Imaging: Reader Experience Matters

Background

Prostate magnetic resonance imaging (MRI) is increasingly used in the detection, image-guided biopsy, and active surveillance of prostate cancer. The accuracy of prostate MRI may differ based on factors including imaging technique, patient population, and reader experience.

Objective

To determine whether the accuracy of prostate MRI varies with reader experience.

Design, setting, and participants

We rescored regions of interest from 194 consecutive patients who had undergone MRI/ultrasonography fusion biopsy. Original prostate MRI scans had been interpreted by one of 33 abdominal radiologists (AR group). More than 14 mo later, rescoring was performed by two blinded, prostate MRI radiologists (PR group). Likert scoring was used for both original MRI reports and rescoring.

Outcome measurements and statistical analysis

Test performance (sensitivity, specificity, positive predictive value [PPV], and negative predictive value [NPV]) of prostate MRI was defined for the AR and PR groups. A Likert score of 4–5 was considered test positive and clinically significant prostate carcinoma (csPCa; Gleason grade group [GGG] ≥2) was considered outcome positive.

Results and limitations

MRI-positive lesions (Likert 4–5) scored by the PR group resulted in csPCa more frequently than those scored by the AR group (64.9% vs 39.3%). MRI-negative lesions (Likert 2–3) were more likely to result in a clinically insignificant biopsy (benign pathology or GGG 1) when scored by the PR versus the AR group (91.8% vs 76.6%). Sensitivity and specificity of MRI to detect csPCa were higher for the PR group than for the AR group (sensitivity 85.9% vs 70.7%; specificity 77.3% vs 46.8%). Overall diagnostic accuracy was higher for the PR group than for the AR group (80.1% vs 54.6%).

Conclusions

Sensitivity, specificity, PPV, and NPV of prostate MRI were higher for the PR group than for the AR group.

Patient summary

We examined the accuracy of prostate magnetic resonance imaging (MRI) in two groups of radiologists. Experienced radiologists were more likely to detect clinically significant prostate cancer on MRI.

Education of prostate MR imaging: commentary

Multiparametric MRI (mpMRI) of the prostate has been firmly established as a tool in the diagnosis, management, and treatment of prostate cancer. The growth in this field over the past decade has led to increased acceptance and demand for multiparametric prostate MRI across the world. However, with the rising demand for prostate mpMRI, it will become increasingly necessary to train a generation of dedicated prostate imagers to yield a high-quality product.

Tackling Interobserver Variability in Multiparametric Magnetic Resonance Imaging (MRI): Is MRI Even Better than We Think for Prostate Cancer Diagnosis?

In clinical practice, the agreement between radiologists in detecting suspicious lesions on magnetic resonance images could be higher than previously thought because of biases associated with study design, patient selection, and the statistical approach in current studies of interobserver agreement.

Clinical utility of combined T2-weighted imaging and T2-mapping in the detection of prostate cancer: a multi-observer study

Background

To evaluate the clinical utility of combined T2-weighted imaging and T2-mapping for the detection of prostate cancer.

Methods

Forty patients underwent multiparametric magnetic resonance imaging (mpMRI) and T2-mapping of the prostate. Three readers each reviewed two sets of images: T2-weighted fast spin-echo (FSE) sequence (standard T2), and standard T2 in combination with T2-mapping. Each reader assigned probability scores for malignancy to each zone [peripheral zone (PZ) or transition zone (TZ)]. Inter-observer variability for standard T2 and combined standard T2 with T2-mapping were assessed. Diagnostic accuracy was compared between standard T2 and combined standard T2 with T2-mapping.

Results

There was fair agreement between all three readers for standard T2 [intraclass correlation coefficient (ICC) =0.56] and combined standard T2 with T2-mapping (ICC =0.58). There was no significant difference in the area under the receiver operator characteristics curve for standard T2 compared to combined standard T2 with T2-mapping (0.89 vs. 0.82, P=0.31). Sensitivity (Sn) for combined standard T2 with T2-mapping was significantly higher compared to standard T2 alone (73.0% vs. 49.2%, P=0.006). Specificity (Sp) for combined standard T2 with T2-mapping was borderline significantly lower compared to standard T2 alone (89.3% vs. 94.9%, P=0.05). There was no significant differences between the negative predictive values (NPVs) and positive predictive values (PPVs) (P=0.07, P=0.45).

Conclusions

Combination of T2-weighted imaging and T2-mapping could potentially increase Sn for prostate malignancy compared to T2-weighted imaging alone.

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

OBJECTIVES

This study aims to define consensus-based criteria for acquiring and reporting prostate MRI and establishing prerequisites for image quality.

METHODS

A total of 44 leading urologists and urogenital radiologists who are experts in prostate cancer imaging from the European Society of Urogenital Radiology (ESUR) and EAU Section of Urologic Imaging (ESUI) participated in a Delphi consensus process. Panellists completed two rounds of questionnaires with 55 items under three headings: image quality assessment, interpretation and reporting, and radiologists' experience plus training centres. Of 55 questions, 31 were rated for agreement on a 9-point scale, and 24 were multiple-choice or open. For agreement items, there was consensus agreement with an agreement ≥ 70% (score 7-9) and disagreement of ≤ 15% of the panellists. For the other questions, a consensus was considered with ≥ 50% of votes.

RESULTS

Twenty-four out of 31 of agreement items and 11/16 of other questions reached consensus. Agreement statements were (1) reporting of image quality should be performed and implemented into clinical practice; (2) for interpretation performance, radiologists should use self-performance tests with histopathology feedback, compare their interpretation with expert-reading and use external performance assessments; and (3) radiologists must attend theoretical and hands-on courses before interpreting prostate MRI. Limitations are that the results are expert opinions and not based on systematic reviews or meta-analyses. There was no consensus on outcomes statements of prostate MRI assessment as quality marker.

CONCLUSIONS

An ESUR and ESUI expert panel showed high agreement (74%) on issues improving prostate MRI quality. Checking and reporting of image quality are mandatory. Prostate radiologists should attend theoretical and hands-on courses, followed by supervised education, and must perform regular performance assessments.

KEY POINTS

• Multi-parametric MRI in the diagnostic pathway of prostate cancer has a well-established upfront role in the recently updated European Association of Urology guideline and American Urological Association recommendations. • Suboptimal image acquisition and reporting at an individual level will result in clinicians losing confidence in the technique and returning to the (non-MRI) systematic biopsy pathway. Therefore, it is crucial to establish quality criteria for the acquisition and reporting of mpMRI. • To ensure high-quality prostate MRI, experts consider checking and reporting of image quality mandatory. Prostate radiologists must attend theoretical and hands-on courses, followed by supervised education, and must perform regular self- and external performance assessments.

Multiparametric MRI for prostate cancer diagnosis: current status and future directions

The current diagnostic pathway for prostate cancer has resulted in overdiagnosis and consequent overtreatment as well as underdiagnosis and missed diagnoses in many men. Multiparametric MRI (mpMRI) of the prostate has been identified as a test that could mitigate these diagnostic errors. The performance of mpMRI can vary depending on the population being studied, the execution of the MRI itself, the experience of the radiologist, whether additional biomarkers are considered and whether mpMRI-targeted biopsy is carried out alone or in addition to systematic biopsy. A number of challenges to implementation remain, such as ensuring high-quality execution and reporting of mpMRI and ensuring that this diagnostic pathway is cost-effective. Nevertheless, emerging clinical trial data support the adoption of this technology as part of the standard of care for the diagnosis of prostate cancer.

The Evolution of MRI of the Prostate: The Past, the Present, and the Future

OBJECTIVE. The purpose of this article is to discuss the evolution of MRI in prostate cancer from the early 1980s to the current day, providing analysis of the key studies on this topic. CONCLUSION. The rapid diffusion of MRI technology has meant that residual variability remains between centers regarding the quality of acquisition and the quality and standardization of reporting.

Comparison of PIRADS 3 lesions with histopathological findings after MRI-fusion targeted biopsy of the prostate in a real world-setting

INTRODUCTION

We aimed to evaluate whether PIRADS 3 lesions in multiparametric MRI (mpMRI) represent a significant risk of prostate cancer (PCa) in a real-world setting of different referring radiologic institutes.

MATERIALS AND METHODS

Between May 2015 and October 2017, a total of 408 patients were referred to our clinic for MRI-ultrasound fusion targeted biopsy of the prostate (FusPbx) due to suspected prostate cancer. In all patients, preoperatively an mpMRI of the prostate was performed by altogether 62 different radiologic institutes. Prostate lesions were classified according to the PIRADS system. A PIRADS 3 lesion was diagnosed in 41 patients. FusPbx was performed transrectally using a Philips EPIQ 7 (Philips Medical Systems, Bothell, WA) scanner with plane wise fusion of ultrasound and MRI image data. In addition to FusPbx in each patient a randomized 12-core transrectal ultrasound guided biopsy (USPbx) was performed.

RESULTS

Mean PSA Level was 9.5 ng/ml (range: 1- 26 ng/ml), mean patients age was 66.1 years (48.6- 80.4). In 11/41 patients (26.8%) prostate cancer was diagnosed by FusPbx of the PIRADS 3 lesion. In the target lesion PCa was classified as Gleason Score 3+3 in 5 patients, as 3+4 in 3, 4+3 in 1, 4+4 in 1 and 4+5 in 1 patient. In patients with negative FusPbx USPbx revealed PCa in another 7 patients (17.1%). In 5 of these GS 3+3 PCa was found, in another 2 patients GS 3+4 PCa.

CONCLUSIONS

PIRADS 3 lesion indicates an equivocal likelihood of significant prostate cancer. In our series the overall PCa detection rate was 26.8% and 14.6% for clinically significant cancer in PIRADS 3 lesions. This evokes the question, if PIRADS 3 lesions could be surveilled only. The findings should be confirmed in a larger series.

Image quality and diagnostic accuracy of complex-averaged high b value images in diffusion-weighted MRI of prostate cancer

PURPOSE

To evaluate the impact of complex-averaging on image quality (IQ) and diagnostic accuracy of acquired and calculated high b value (aHBV, cHBV) images in diffusion-weighted prostate MRI.

MATERIALS AND METHODS

This retrospective study included 84 patients who underwent multiparametric prostate MRI at 3 Tesla without endorectal coil. DWIs were acquired at three different b values which included two lower b values (b = 50,900 s/mm²) and one higher b value (aHBV at 2000 s/mm²). The acquired data were postprocessed to generate two different types of trace-weighted images-using conventional magnitude-averaging and complex-averaging. Using lower b values (b = 50,900 s/mm²) from both conventional and complex-averaged image sets, cHBV images (b = 2000 s/mm²) and ADC maps were derived. All image sets were reviewed by two radiologists in different reading sessions to assess image quality and PIRADS. The diagnostic accuracy of different image sets for the detection of prostate lesions was performed by correlating PIRADS and Gleason scores.

RESULTS

Complex-averaging did not impact ADC values of the prostate lesions compared to magnitude-averaging (P = 0.08). Complex-averaging improved image quality of acquired high b value and calculated high b value images (P < 0.0001). Complex-averaging also improved the level of confidence (LOC) of the acquired high b value for both readers (P < 0.0001, P < 0.05), but only for reader A in calculated high b value (P < 0.0001). The image quality of calculated high b value images was not significantly different than acquired high b value images. The dataset combining complex-averaging and calculated high b value provided the highest diagnostic accuracy (but not statistically significant) for detection of the significant prostate lesion compared to the magnitude-averaged acquired high b value (79.55% vs. 72.73%; P = 0.317). The mean acquisition time for b = 2000 s/mm² sequence (aHBV) was 6 min 30 s (± 1 min 16 s) out of a total of 28 min 31 s (± 4 min 26 s) for the entire mp-MRI protocol (approximately 25% of total scan time).

CONCLUSION

Complex-averaging provides better image quality and level of confidence without significant impact on ADC values and diagnostic accuracy for detection of the significant prostate lesions . The calculated high b value images are also comparable to (and can substitute) the acquired high b value images which can help in reducing the imaging time.

False positives in PIRADS (V2) 3, 4, and 5 lesions: relationship with reader experience and zonal location

PURPOSE

To investigate the effect of reader experience and zonal location on the occurrence of false positives (FPs) in PIRADS (V2) 3, 4, and 5 lesions on multiparametric (MP)-MRI of the prostate.

MATERIALS AND METHODS

This retrospective study included 139 patients who had consecutively undergone an MP-MRI of the prostate in combination with a transrectal ultrasound MRI fusion-guided biopsy between 2014 and 2017. MRI exams were prospectively read by a group of inexperienced radiologists (cohort 1; 54 patients) and an experienced radiologist (cohort 2; 85 patients). Multivariable logistic regression analysis was performed to determine the association of experience of the radiologist and zonal location with a FP reading. FP rates were compared between readings by inexperienced and experienced radiologists according to zonal location, using Chi-square (χ²) tests.

RESULTS

A total of 168 lesions in 139 patients were detected. Median patient age was 68 years (Interquartile range (IQR) 62.5-73), and median PSA was 10.9 ng/mL (IQR 7.6-15.9) for the entire patient cohort. According to multivariable logistic regression, inexperience of the radiologist was significantly (P = 0.044, odds ratio 1.927, 95% confidence interval [CI] 1.017-3.651) and independently associated with a FP reading, while zonal location was not (P = 0.202, odds ratio 1.444, 95% CI 0.820-2.539). In the transition zone (TZ), the FP rate of the inexperienced radiologists 59% (17/29) was significantly higher (χ²P = 0.033) than that of the experienced radiologist 33% (13/40).

CONCLUSION

Inexperience of the radiologist is significantly and independently associated with a FP reading, while zonal location is not. Inexperienced radiologists have a significantly higher FP rate in the TZ.

Contrast- vs. non-contrast enhanced MR data sets for characterization of perianal fistulas

PURPOSE

To evaluate the diagnostic efficacy between pre- and post-contrast MRI sequences in perianal fistulas using intra-operative findings as the gold standard.

MATERIALS AND METHODS

Retrospective analysis of 50 patients with a history of perianal fistula and MRI performed between January 2006 and January 2018 was performed. The inclusion criteria were patients who underwent MRI prior to surgery and had a detailed surgical report available. Pre- and post-contrast MR data sets were evaluated by two radiologists at two-week-intervals, assessed fistula type, internal/external opening, presence of abscess/secondary tracts, and confidence scores. The area under the curve (AUC) was used for comparison the diagnostic ability. The sensitivity and specificity were compared using the McNemar's test.

RESULTS

The confidence scores in detecting perianal fistulas were significantly higher in the post-contrast MR data set (p < 0.003). The post-contrast MR data set had similar ability to classify perianal fistulas as combined T2-DWI and isolated T2 data sets in 49/50 cases. For internal/external opening, the post-contrast MR, combined T2-DWI, and isolated T2 data sets had 100% concordance with intra-operative reports. For perianal abscess, there was no significant difference in sensitivity or AUC value between the isolated T2 or combined T2-DWI data sets and post-contrast MR data set (p > 0.05). All MR data sets correctly identified secondary tracts in all 50 cases.

CONCLUSIONS

Although contrast-enhanced MR studies can improve a radiologist's confidence, non-contrast MR studies had similar diagnostic efficacy in identifying perianal fistulas and their complications. Therefore, a non-contrast study may suffice in selected patients such as those with renal impairment.

Diagnostic Performance and Interobserver Consistency of the Prostate Imaging Reporting and Data System Version 2: A Study on Six Prostate Radiologists with Different Experiences from Half a Year to 17 Years

Background:

One of the main aims of the updated Prostate Imaging Reporting and Data System Version 2 (PI-RADS v2) is to diminish variation in the interpretation and reporting of prostate imaging, especially among readers with varied experience levels. This study aimed to retrospectively analyze diagnostic consistency and accuracy for prostate disease among six radiologists with different experience levels from a single center and to evaluate the diagnostic performance of PI-RADS v2 scores in the detection of clinically significant prostate cancer (PCa).

Methods:

From December 2014 to March 2016, 84 PCa patients and 99 benign prostatic shyperplasia patients who underwent 3.0T multiparametric magnetic resonance imaging before biopsy were included in our study. All patients received evaluation according to the PI-RADS v2 scale (1–5 scores) from six blinded readers (with 6 months and 2, 3, 4, 5, or 17 years of experience, respectively, the last reader was a reviewer/contributor for the PI-RADS v2). The correlation among the readers' scores and the Gleason score (GS) was determined with the Kendall test. Intra-/inter-observer agreement was evaluated using κ statistics, while receiver operating characteristic curve and area under the curve analyses were performed to evaluate the diagnostic performance of the scores.

Results:

Based on the PI-RADS v2, the median κ score and standard error among all possible pairs of readers were 0.506 and 0.043, respectively; the average correlation between the six readers' scores and the GS was positive, exhibiting weak-to-moderate strength (r = 0.391, P = 0.006). The AUC values of the six radiologists were 0.883, 0.924, 0.927, 0.932, 0.929, and 0.947, respectively.

Conclusion:

The inter-reader agreement for the PI-RADS v2 among the six readers with different experience is weak to moderate. Different experience levels affect the interpretation of MRI images.

Accuracy and Variability of Prostate Multiparametric Magnetic Resonance Imaging Interpretation Using the Prostate Imaging Reporting and Data System: A Blinded Comparison of Radiologists

BACKGROUND

Multiparametric (mp) magnetic resonance imaging (MRI) has become an important tool for the detection of clinically significant prostate cancer. However, diagnostic accuracy is affected by variability between radiologists.

OBJECTIVE

To determine the accuracy and variability in prostate mpMRI interpretation among radiologists, both individually and in teams, in a blinded fashion.

DESIGN, SETTING, AND PARTICIPANTS

A study cohort (n=32) was created from our prospective registry of patients who received prostate mpMRI with subsequent biopsy. The cohort was then independently reviewed by four radiologists of varying levels of experience, who assigned a Prostate Imaging Reporting and Data System (PI-RADS) classification, blinded to all clinical information. Consensus interpretation by teams of two radiologists was evaluated after a 12-wk wash-out period. Interpretive accuracy was calculated with various cutoffs for PI-RADS classification and Gleason score. Variability among individual radiologists and teams was calculated using the Fleiss kappa and intraclass correlation coefficient (ICC).

RESULTS AND LIMITATIONS

Using PI-RADS 3+/Gleason 7+ (p<0.01) and PI-RADS 4+/Gleason 6+ (p=0.02) as cutoffs, significant differences in accuracy among the four radiologists were noted. At no cutoff for PI-RADS classification or Gleason score did a team read achieve higher accuracy than the most accurate radiologist. The kappa and ICC ranged from 0.22 to 0.29 for the individuals and from 0.16 to 0.21 for the teams (poor agreement). A larger sample size may be needed to adequately power differences in accuracy among individual radiologists.

CONCLUSIONS

At various cutoffs for PI-RADS classification and Gleason score, we find significant differences in individual radiologist accuracy, as well as a poor agreement among individual radiologists. Consensus interpretations-as teams of two radiologists-did not improve accuracy or reduce variability.

PATIENT SUMMARY

This study investigated radiologist variability and differences in accuracy using multiparametric magnetic resonance imaging for the diagnosis of prostate cancer. Despite attempts to standardize interpretation within the field, we found substantial variability and significant differences in accuracy among individual radiologists.

Computer-aided diagnosis prior to conventional interpretation of prostate mpMRI: an international multi-reader study

OBJECTIVES

To evaluate if computer-aided diagnosis (CAD) prior to prostate multi-parametric MRI (mpMRI) can improve sensitivity and agreement between radiologists.

METHODS

Nine radiologists (three each high, intermediate, low experience) from eight institutions participated. A total of 163 patients with 3-T mpMRI from 4/2012 to 6/2015 were included: 110 cancer patients with prostatectomy after mpMRI, 53 patients with no lesions on mpMRI and negative TRUS-guided biopsy. Readers were blinded to all outcomes and detected lesions per PI-RADSv2 on mpMRI. After 5 weeks, readers re-evaluated patients using CAD to detect lesions. Prostatectomy specimens registered to MRI were ground truth with index lesions defined on pathology. Sensitivity, specificity and agreement were calculated per patient, lesion level and zone-peripheral (PZ) and transition (TZ).

RESULTS

Index lesion sensitivity was 78.2% for mpMRI alone and 86.3% for CAD-assisted mpMRI (p = 0.013). Sensitivity was comparable for TZ lesions (78.7% vs 78.1%; p = 0.929); CAD improved PZ lesion sensitivity (84% vs 94%; p = 0.003). Improved sensitivity came from lesions scored PI-RADS < 3 as index lesion sensitivity was comparable at PI-RADS ≥ 3 (77.6% vs 78.1%; p = 0.859). Per patient specificity was 57.1% for CAD and 70.4% for mpMRI (p = 0.003). CAD improved agreement between all readers (56.9% vs 71.8%; p < 0.001).

CONCLUSIONS

CAD-assisted mpMRI improved sensitivity and agreement, but decreased specificity, between radiologists of varying experience.

KEY POINTS

• Computer-aided diagnosis (CAD) assists clinicians in detecting prostate cancer on MRI. • CAD assistance improves agreement between radiologists in detecting prostate cancer lesions. • However, this CAD system induces more false positives, particularly for less-experienced clinicians and in the transition zone. • CAD assists radiologists in detecting cancer missed on MRI, suggesting a path for improved diagnostic confidence.

Long-distance longitudinal prostate MRI quality assurance: from startup to 12 months

PURPOSE

To evaluate a 12-month long-distance prostate MRI quality assurance (QA) program.

METHODS

The need for IRB approval was waived for this prospective longitudinal QA effort. One academic institution experienced with prostate MRI [~ 1000 examinations/year (Site 2)] partnered with a private institution 240 miles away that was starting a new prostate MRI program (Site 1). Site 1 performed all examinations (N = 249). Four radiologists at Site 1 created finalized reports, then sent images and reports to Site 2 for review on a rolling basis. One radiologist at Site 2 reviewed findings and exam quality and discussed results by phone (~ 2-10 minutes/MRI). In months 1-6 all examinations were reviewed. In months 7-12 only PI-RADS ≤ 2 and 'difficult' cases were reviewed. Repeatability was assessed with intra-class correlation (ICC). 'Clinically significant cancer' was Gleason ≥ 7.

RESULTS

Image quality significantly (p < 0.001) improved after the first three months. Inter-rater agreement also improved in months 3-4 [ICC: 0.849 (95% CI 0.744-0.913)] and 5-6 [ICC: 0.768 (95% CI 0.619-0.864)] compared to months 1-2 [ICC: 0.621 (95% CI 0.436-0.756)]. PI-RADS ≤ 2 examinations were reclassified PI-RADS ≥ 3 in 19% (30/162); of these, 23 had post-MRI histology and 57% (13/23) had clinically significant cancer (5.2% of 249). False-negative examinations [N = 18 (PI-RADS ≤ 2 and Gleason ≥ 7)] were more common at Site 1 during months 1-6 [9% (14/160) vs. 4% (4/89)]. Positive predictive values for PI-RADS ≥ 3 were similar.

CONCLUSION

Remote quality assurance of prostate MRI is feasible and useful, enabling new programs to gain durable skills with minimal risk to patients.

Can Apparent Diffusion Coefficient Values Assist PI-RADS Version 2 DWI Scoring? A Correlation Study Using the PI-RADSv2 and International Society of Urological Pathology Systems

OBJECTIVE

The purposes of this study were to assess correlation of apparent diffusion coefficient (ADC) and normalized ADC (ratio of tumor to nontumor tissue) with the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) and updated International Society of Urological Pathology (ISUP) categories and to determine how to optimally use ADC metrics for objective assistance in categorizing lesions within PI-RADSv2 guidelines.

MATERIALS AND METHODS

In this retrospective study, 100 patients (median age, 62 years; range, 44-75 years; prostate-specific antigen level, 7.18 ng/mL; range, 1.70-84.56 ng/mL) underwent 3-T multiparametric MRI of the prostate with an endorectal coil. Mean ADC was extracted from ROIs based on subsequent prostatectomy specimens. Histopathologic analysis revealed 172 lesions (113 peripheral, 59 transition zone). Two radiologists blinded to histopathologic outcome assigned PI-RADSv2 categories. Kendall tau was used to correlate ADC metrics with PI-RADSv2 and ISUP categories. ROC curves were used to assess the utility of ADC metrics in differentiating each reader's PI-RADSv2 DWI category 4 or 5 assessment in the whole prostate and by zone.

RESULTS

ADC metrics negatively correlated with ISUP category in the whole prostate (ADC, τ = -0.21, p = 0.0002; normalized ADC, τ = -0.21, p = 0.0001). Moderate negative correlation was found in expert PI-RADSv2 DWI categories (ADC, τ = -0.34; normalized ADC, τ = -0.31; each p < 0.0001) maintained across zones. In the whole prostate, AUCs of ADC and normalized ADC were 87% and 82% for predicting expert PI-RADSv2 DWI category 4 or 5. A derived optimal cutoff ADC less than 1061 and normalized ADC less than 0.65 achieved positive predictive values of 83% and 84% for correct classification of PI-RADSv2 DWI category 4 or 5 by an expert reader. Consistent relations and predictive values were found by an independent novice reader.

CONCLUSION

ADC and normalized ADC inversely correlate with PI-RADSv2 and ISUP categories and can serve as quantitative metrics to assist with assigning PI-RADSv2 DWI category 4 or 5.

National implementation of multi-parametric magnetic resonance imaging for prostate cancer detection - recommendations from a UK consensus meeting

OBJECTIVES

To identify areas of agreement and disagreement in the implementation of multi-parametric magnetic resonance imaging (mpMRI) of the prostate in the diagnostic pathway.

MATERIALS AND METHODS

Fifteen UK experts in prostate mpMRI and/or prostate cancer management across the UK (involving nine NHS centres to provide for geographical spread) participated in a consensus meeting following the Research and Development Corporation and University of California-Los Angeles (UCLA-RAND) Appropriateness Method, and were moderated by an independent chair. The experts considered 354 items pertaining to who can request an mpMRI, prostate mpMRI protocol, reporting guidelines, training, quality assurance (QA) and patient management based on mpMRI levels of suspicion for cancer. Each item was rated for agreement on a 9-point scale. A panel median score of ≥7 constituted 'agreement' for an item; for an item to reach 'consensus', a panel majority scoring was required.

RESULTS

Consensus was reached on 59% of items (208/354); these were used to provide recommendations for the implementation of prostate mpMRI in the UK. Key findings include prostate mpMRI requests should be made in consultation with the urological team; mpMRI scanners should undergo QA checks to guarantee consistently high diagnostic quality scans; scans should only be reported by trained and experienced radiologists to ensure that men with unsuspicious prostate mpMRI might consider avoiding an immediate biopsy.

CONCLUSIONS

Our consensus statements demonstrate a set of criteria that are required for the practical dissemination of consistently high-quality prostate mpMRI as a diagnostic test before biopsy in men at risk.

Detection of prostate cancer with multiparametric MRI utilizing the anatomic structure of the prostate

Multiparametric magnetic resonance imaging (mpMRI), which combines traditional anatomic and newer quantitative MRI methods, has been shown to result in improved voxel-wise classification of prostate cancer as compared with any single MRI parameter. While these results are promising, substantial heterogeneity in the mpMRI parameter values and voxel-wise prostate cancer risk has been observed both between and within regions of the prostate. This suggests that classification of prostate cancer can potentially be improved by incorporating structural information into the classifier. In this paper, we propose a novel voxel-wise classifier of prostate cancer that accounts for the anatomic structure of the prostate by Bayesian hierarchical modeling, which can be combined with post hoc spatial Gaussian kernel smoothing to account for residual spatial correlation. Our proposed classifier results in significantly improved area under the ROC curve (0.822 vs 0.729, P < .001) and sensitivity corresponding to 90% specificity (0.599 vs 0.429, P < .001), compared with a baseline model that does not account for the anatomic structure of the prostate. Furthermore, the classifier can also be applied on voxels with missing mpMRI parameters, resulting in similar performance, which is an important practical consideration that cannot be easily accommodated using regression-based classifiers. In addition, our classifier achieved high computational efficiency with a closed-form solution for the posterior predictive cancer probability.

Assessment of Needle Tip Deflection During Transrectal Guided Prostate Biopsy: Implications for Targeted Biopsies

OBJECTIVES

To measure needle tip deflection during transrectal ultrasound (TRUS) prostate biopsy and evaluate predictors for needle tip deflection.

MATERIALS AND METHODS

Analysis of 568 prostate biopsies obtained from 51 consecutive patients who underwent a standard 12-core TRUS guided prostate biopsy. TRUS guided prostate biopsies were performed using BK flex500, with a side-fire biplane probe. Each biopsy core image was captured and clinical data were recorded prospectively. The angle between the expected trajectory of the needle and actual needle course was measured using the longitudinal view of the captured image. The distance between expected and actual needle tip was calculated. We measured median and interquartile needle tip deflection rate stratified by side and location (apex, midgland, base). Univariable and multivariable linear regressions analysis were performed.

RESULTS

The overall median needle tip deflection was 1.77 mm (IQR 1.35-2.47). Location did not significantly alter needle deflection measurements. On multivariable linear regression analysis, higher prostate volume (B = 0.007 95%, CI 0.004, 0.011; p < 0.001) and the right sided biopsy (B = 0.191 95%, CI 0.047, 0.336; p = 0.010) emerged as predictors of higher needle tip deflection.

CONCLUSIONS

To the best of our knowledge this is the first study to measure needle tip deflection during TRUS guided prostate biopsies. We demonstrated that larger prostate size and biopsy side may affect the accuracy of biopsies. These results may have clinical implication to those performing targeted biopsies.

Online Interactive Case-Based Instruction in Prostate Magnetic Resonance Imaging Interpretation Using Prostate Imaging and Reporting Data System Version 2: Effect for Novice Readers

PURPOSE

To assess the effect on reader performance of an interactive case-based online tutorial for prostate magnetic resonance imaging (MRI) interpretation using Prostate Imaging and Reporting Data System (PI-RADS).

METHODS

An educational website was developed incorporating scrollable multiparametric prostate MRI examinations with annotated solutions based on PI-RADS version 2. Three second-year radiology residents evaluated a separate set of 60 prostate MRI examinations both before and after review of the online case material, identifying and scoring dominant lesions. These 60 examinations included 30 benign cases and 30 cases with a dominant lesion demonstrating Gleason score ≥3 + 4 tumor on fusion-targeted biopsy. The readers' pooled performance was compared between the 2 sessions using logistic regression and Wilcoxon signed rank tests.

RESULTS

All readers completed the online material within four-hours. Review of the online material significantly improved sensitivity (from 57.8%-73.3%, P = 0.003) and negative predictive value (from 69.2%-78.2%, P = 0.049), but not specificity (from 70.0%-67.8%, P = 0.692) or positive predictive value (from 59.6%-64.7%, P = 0.389). Reader confidence (1-10 scale; 10 = maximal confidence) also improved significantly (from 5.6 ± 2.7 to 6.3 ± 2.6, P = 0.026). However, accuracy of assigned PI-RADS scores did not improve significantly (from 45.5%-53.3%, P = 0.149).

CONCLUSION

An online interactive case-based website in prostate MRI interpretation improved novice readers' sensitivity and negative predictive value for tumor detection, as well as readers' confidence. This online material may serve as a resource complementing existing traditional methods of instruction by providing a more flexible educational experience among a larger volume of learners. However, further more targeted educational initiatives regarding the proper application of PI-RADS remain warranted.