Self-supervised multicontrast super-resolution for diffusion-weighted prostate MRI.

PURPOSE: This study addresses the challenge of low resolution and signal-to-noise ratio (SNR) in diffusion-weighted images (DWI), which are pivotal for cancer detection. Traditional methods increase SNR at high b-values through multiple acquisitions, but this results in diminished image resolution due to motion-induced variations. Our research aims to enhance spatial resolution by exploiting the global structure within multicontrast DWI scans and millimetric motion between acquisitions. METHODS: We introduce a novel approach employing a "Perturbation Network" to learn subvoxel-size motions between scans, trained jointly with an implicit neural representation (INR) network. INR encodes the DWI as a continuous volumetric function, treating voxel intensities of low-resolution acquisitions as discrete samples. By evaluating this function with a finer grid, our model predicts higher-resolution signal intensities for intermediate voxel locations. The Perturbation Network's motion-correction efficacy was validated through experiments on biological phantoms and in vivo prostate scans. RESULTS: Quantitative analyses revealed significantly higher structural similarity measures of super-resolution images to ground truth high-resolution images compared to high-order interpolation (p < $$ < $$ 0.005). In blind qualitative experiments, 96 . 1 % $$ 96.1\% $$ of super-resolution images were assessed to have superior diagnostic quality compared to interpolated images. CONCLUSION: High-resolution details in DWI can be obtained without the need for high-resolution training data. One notable advantage of the proposed method is that it does not require a super-resolution training set. This is important in clinical practice because the proposed method can easily be adapted to images with different scanner settings or body parts, whereas the supervised methods do not offer such an option.

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.

Clinical and economic impact of the introduction of pre-biopsy MRI-based assessment on a large prostate cancer centre diagnostic population and activity: 10 years on.

INTRODUCTION: Prostate mpMRI was introduced in 2011 as a secondary test and subsequently integrated into a prostate cancer (PCa) diagnostics unit representing a population of approximately 550,000 people. The following represents an audit of its step-wise introduction between 2 index years, 2009 and 2018, focusing on the activity, patient outcomes and economic benefits. PATIENTS AND METHODS: The 2 distinct years were selected for relying on a transrectal ultrasound biopsy pathway in 2009 to an mpMRI-based pathway in 2018. All referrals were retrospectively screened and compared for age, PSA levels, DRE findings, biopsy history, biopsy and mpMRI allocation data. Cost analysis was determined using local unit procedure costs. RESULTS: Patients referred included 648 in 2009 and 714 in 2018. mpMRI seldomly informed decision to biopsy in 2009 (9.8%), while in 2018 it was performed in the pre-biopsy setting in 87.9% cases and enabled biopsy avoidance in 137 patients. In 2018, there was a 31.8% decrease in the number of biopsies in patients without previous PCa diagnosis, coupled with an increase in diagnostic rates of csPCa, from 28.6 to 49.0% (p < 0.0001) and a reduction in negative biopsy rates from 52.3 to 33.8%. mpMRI had a positive impact on the system with reduced patient morbidity and post-procedural complications. The estimated overall cost savings amount to approximately £75,000/year for PCa diagnosis and £11,000/year due to reduced complications. CONCLUSION: Our evaluation shows the mpMRI-based pathway has improved early detection of csPCa and reduction of repeat biopsies, resulting in significant financial benefits for the local healthcare system.

PI-RADS Version 2.0 Versus Version 2.1: Comparison of Prostate Cancer Gleason Grade Upgrade and Downgrade Rates From MRI-Targeted Biopsy to Radical Prostatectomy.

BACKGROUND. Precise risk stratification through MRI/ultrasound (US) fusion-guided targeted biopsy (TBx) can guide optimal prostate cancer (PCa) management. OBJECTIVE. The purpose of this study was to compare PI-RADS version 2.0 (v2.0) and PI-RADS version 2.1 (v2.1) in terms of the rates of International Society of Urological Pathology (ISUP) grade group (GG) upgrade and downgrade from TBx to radical prostatectomy (RP). METHODS. This study entailed a retrospective post hoc analysis of patients who underwent 3-T prostate MRI at a single institution from May 2015 to March 2023 as part of three prospective clinical trials. Trial participants who underwent MRI followed by MRI/US fusion-guided TBx and RP within a 1-year interval were identified. A single genitourinary radiologist performed clinical interpretations of the MRI examinations using PI-RADS v2.0 from May 2015 to March 2019 and PI-RADS v2.1 from April 2019 to March 2023. Upgrade and downgrade rates from TBx to RP were compared using chi-square tests. Clinically significant cancer was defined as ISUP GG2 or greater. RESULTS. The final analysis included 308 patients (median age, 65 years; median PSA density, 0.16 ng/mL2). The v2.0 group (n = 177) and v2.1 group (n = 131) showed no significant difference in terms of upgrade rate (29% vs 22%, respectively; p = .15), downgrade rate (19% vs 21%, p = .76), clinically significant upgrade rate (14% vs 10%, p = .27), or clinically significant downgrade rate (1% vs 1%, p > .99). The upgrade rate and downgrade rate were also not significantly different between the v2.0 and v2.1 groups when stratifying by index lesion PI-RADS category or index lesion zone, as well as when assessed only in patients without a prior PCa diagnosis (all p > .01). Among patients with GG2 or GG3 at RP (n = 121 for v2.0; n = 103 for v2.1), the concordance rate between TBx and RP was not significantly different between the v2.0 and v2.1 groups (53% vs 57%, p = .51). CONCLUSION. Upgrade and downgrade rates from TBx to RP were not significantly different between patients whose MRI examinations were clinically interpreted using v2.0 or v2.1. CLINICAL IMPACT. Implementation of the most recent PI-RADS update did not improve the incongruence in PCa grade assessment between TBx and surgery.

Association between mpMRI detected tumor apparent diffusion coefficient and 5-year biochemical recurrence risk after radical prostatectomy.

PURPOSE: To assess the ability of tumor apparent diffusion coefficient (ADC) values obtained from multiparametric magnetic resonance imaging (mpMRI) to predict the risk of 5-year biochemical recurrence (BCR) after radical prostatectomy (RP). MATERIALS AND METHODS: This retrospective analysis included 1207 peripheral and 232 non-peripheral zone prostate cancer (PCa) patients who underwent mpMRI before RP (2012-2015), with the outcome of interest being 5-year BCR. ADC was evaluated as a continuous variable and as categories: low (< 850 µm2/s), intermediate (850-1100 µm2/s), and high (> 1100 µm2/s). Kaplan-Meier curves with log-rank testing of BCR-free survival, multivariable Cox proportional hazard regression models were formed to estimate the risk of BCR. RESULTS: Among the 1439 males with median age 63 (± 7) years, the median follow-up was 59 months, and 306 (25%) patients experienced BCR. Peripheral zone PCa patients with BCR had lower tumor ADC values than those without BCR (874 versus 1025 µm2/s, p < 0.001). Five-year BCR-free survival rates were 52.3%, 74.4%, and 87% for patients in the low, intermediate, and high ADC value categories, respectively (p < 0.0001). Lower ADC was associated with BCR, both as continuously coded variable (HR: 5.35; p < 0.001) and as ADC categories (intermediate versus high ADC-HR: 1.56, p = 0.017; low vs. high ADC-HR; 2.36, p < 0.001). In the non-peripheral zone PCa patients, no association between ADC and BCR was observed. CONCLUSION: Tumor ADC values and categories were found to be predictive of the 5-year BCR risk after RP in patients with peripheral zone PCa and may serve as a prognostic biomarker.

Impact of the bladder detrusor muscular ring on lower urinary tract symptoms due to benign prostatic hyperplasia: A quantitative MRI analysis.

BACKGROUND: The etiology of lower urinary tract symptoms secondary to benign prostatic hyperplasia (LUTS/BPH) remains uncertain. OBJECTIVE: The purpose of our study was to quantitatively analyze anatomic characteristics on magnetic resonance imaging (MRI) to assess novel independent factors for symptoms. METHODS: This retrospective single-institution study evaluated treatment-naïve men who underwent prostate MRI within 3 months of international prostate symptom score (IPSS) scoring from June 2021 to February 2022. Factors measured on MRI included: size of the detrusor muscular ring (DMR) surrounding the bladder outlet, central gland (CG) mean apparent diffusion coefficient (ADC), levator hiatus (LH) volume, intrapelvic volume, intravesicular prostate protrusion (IPP) volume, CG volume, peripheral zone (PZ) volume, prostate urethra angle (PUA), and PZ background ordinal score. Multivariable logistic regression and receiver operating characteristic analysis were used to analyze factors for moderate/severe (IPSS ≥ 8) and severe LUTS/BPH (IPSS ≥ 20). RESULTS: A total of 303 men (mean age: 66.1 [SD: 8.1]) were included: 154 demonstrated moderate or severe symptoms with 28 severe and 149 with asymptomatic/mild symptoms. Increasing age [p = 0.02; odds ratio (OR): 1.05 (1.01-1.08)], PUA [p = 0.02; OR: 1.05 (1.01-1.09)], LH volume [p = 0.04; OR: 1.02 (1.00-1.05)], and DMR size measured as diameter [p < 0.001; OR: 5.0 (3.01-8.38)] or area [p < 0.001; OR: 1.92 (1.47-2.49)] were significantly independently associated with moderate/severe symptoms, with BMI [p = 0.02; OR: 0.93 (0.88-0.99)] inversely related. For every one cm increase in DMR diameter, patients had approximately five times the odds for moderate/severe symptoms. Increasing DMR size [diameter p < 0.001; OR: 2.74 (1.76-4.27) or area p < 0.001; OR: 1.37 (1.18-1.58)] was independently associated with severe symptoms. Optimal criterion cutoff of DMR diameter for moderate/severe symptoms was 1.2 cm [sensitivity: 77.3; specificity: 71.8; AUC: 0.80 (0.75-0.84)]. Inter-reader reliability was excellent for DMR diameter [ICC = 0.92 (0.90-0.94)]. CONCLUSION: Expansion of the DMR surrounding the bladder outlet is a novel anatomic factor independently associated with moderate and severe LUTS/BPH, taking into account prostate volumes, including quantified IPP volume, which were unrelated. Detrusor ring diameter, easily and reliably measured on routine prostate MRI, may relate to detrusor dysfunction from chronic stretching of this histologically distinct smooth muscle around the bladder neck.

Model-based image reconstruction with wavelet sparsity regularization for through-plane resolution restoration in T2 -weighted spin-echo prostate MRI.

PURPOSE: The purpose is to develop a model-based image-reconstruction method using wavelet sparsity regularization for maintaining restoration of through-plane resolution but with improved retention of SNR versus linear reconstruction using Tikhonov (TK) regularization in high through-plane resolution (1 mm) T2 -weighted spin-echo (T2SE) images of the prostate. METHODS: A wavelet sparsity (WS)-regularized image reconstruction was developed that takes as input a set of ≈80 overlapped 3-mm-thick slices acquired using a T2SE multislice scan and typically 30 coil elements. After testing in contrast and resolution phantoms and calibration in 6 subjects, the WS reconstruction was evaluated in 16 consecutive prostate T2SE MRI exams. Results reconstructed with nominal 1-mm thickness were compared with those from the TK reconstruction with the same raw data. Results were evaluated radiologically. The ratio of magnitude of prostate signal to periprostatic muscle signal was used to assess the presence of noise reduction. Technical performance was also compared with a commercial 3D-T2SE sequence. RESULTS: The new WS reconstruction was assessed as superior statistically to TK for overall SNR, contrast, and multiple evaluation criteria related to sharpness while retaining the high (1 mm) through-plane resolution. Wavelet sparsity tended to provide improved overall diagnostic quality versus TK, but not significantly so. In all 16 studies, the prostate-to-muscle signal ratio increased. CONCLUSIONS: Model-based WS-regularized reconstruction consistently provides improved SNR in high (1 mm) through-plane resolution images of prostate T2SE MRI versus linear reconstruction using TK regularization.

Comparison of a Deep Learning-Accelerated vs. Conventional T2-Weighted Sequence in Biparametric MRI of the Prostate.

BACKGROUND: Demand for prostate MRI is increasing, but scan times remain long even in abbreviated biparametric MRIs (bpMRI). Deep learning can be leveraged to accelerate T2-weighted imaging (T2WI). PURPOSE: To compare conventional bpMRIs (CL-bpMRI) with bpMRIs including a deep learning-accelerated T2WI (DL-bpMRI) in diagnosing prostate cancer. STUDY TYPE: Retrospective. POPULATION: Eighty consecutive men, mean age 66 years (47-84) with suspected prostate cancer or prostate cancer on active surveillance who had a prostate MRI from December 28, 2020 to April 28, 2021 were included. Follow-up included prostate biopsy or stability of prostate-specific antigen (PSA) for 1 year. FIELD STRENGTH AND SEQUENCES: A 3 T MRI. Conventional axial and coronal T2 turbo spin echo (CL-T2), 3-fold deep learning-accelerated axial and coronal T2-weighted sequence (DL-T2), diffusion weighted imaging (DWI) with b = 50 sec/mm2 , 1000 sec/mm2 , calculated b = 1500 sec/mm2 . ASSESSMENT: CL-bpMRI and DL-bpMRI including the same conventional diffusion-weighted imaging (DWI) were presented to three radiologists (blinded to acquisition method) and to a deep learning computer-assisted detection algorithm (DL-CAD). The readers evaluated image quality using a 4-point Likert scale (1 = nondiagnostic, 4 = excellent) and graded lesions using Prostate Imaging Reporting and Data System (PI-RADS) v2.1. DL-CAD identified and assigned lesions of PI-RADS 3 or greater. STATISTICAL TESTS: Quality metrics were compared using Wilcoxon signed rank test, and area under the receiver operating characteristic curve (AUC) were compared using Delong's test. SIGNIFICANCE: P = 0.05. RESULTS: Eighty men were included (age: 66 ± 9 years; 17/80 clinically significant prostate cancer). Overall image quality results by the three readers (CL-T2, DL-T2) are reader 1: 3.72 ± 0.53, 3.89 ± 0.39 (P = 0.99); reader 2: 3.33 ± 0.82, 3.31 ± 0.74 (P = 0.49); reader 3: 3.67 ± 0.63, 3.51 ± 0.62. In the patient-based analysis, the reader results of AUC are (CL-bpMRI, DL-bpMRI): reader 1: 0.77, 0.78 (P = 0.98), reader 2: 0.65, 0.66 (P = 0.99), reader 3: 0.57, 0.60 (P = 0.52). Diagnostic statistics from DL-CAD (CL-bpMRI, DL-bpMRI) are sensitivity (0.71, 0.71, P = 1.00), specificity (0.59, 0.44, P = 0.05), positive predictive value (0.23, 0.24, P = 0.25), negative predictive value (0.88, 0.88, P = 0.48). CONCLUSION: Deep learning-accelerated T2-weighted imaging may potentially be used to decrease acquisition time for bpMRI. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

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.

The impact of a second MRI and re-biopsy in patients with initial negative mpMRI-targeted and systematic biopsy for PIRADS ≥ 3 lesions.

OBJECTIVE: To evaluate the proportions of detected prostate cancer (PCa) and clinically significant PCa (csPCa), as well as identify clinical predictors of PCa, in patients with PI-RADS > = 3 lesion at mpMRI and initial negative targeted and systematic biopsy (initial biopsy) who underwent a second MRI and a re-biopsy. METHODS: A total of 290 patients from 10 tertiary referral centers were included. The primary outcome measures were the presence of PCa and csPCa at re-biopsy. Logistic regression analyses were performed to evaluate predictors of PCa and csPCa, adjusting for relevant covariates. RESULTS: Forty-two percentage of patients exhibited the presence of a new lesion. Furthermore, at the second MRI, patients showed stable, upgrading, and downgrading PI-RADS lesions in 42%, 39%, and 19%, respectively. The interval from the initial to repeated mpMRI and from the initial to repeated biopsy was 16 mo (IQR 12-20) and 18 mo (IQR 12-21), respectively. One hundred and eight patients (37.2%) were diagnosed with PCa and 74 (25.5%) with csPCa at re-biopsy. The presence of ASAP on the initial biopsy strongly predicted the presence of PCa and csPCa at re-biopsy. Furthermore, PI-RADS scores at the first and second MRI and a higher number of systematic biopsy cores at first and second biopsy were independent predictors of the presence of PCa and csPCa. Selection bias cannot be ruled out. CONCLUSIONS: Persistent PI-RADS ≥ 3 at the second MRI is suggestive of the presence of a not negligible proportion of csPca. These findings contribute to the refinement of risk stratification for men with initial negative MRI-TBx.

The PRECISE Recommendations for Prostate MRI in Patients on Active Surveillance for Prostate Cancer: A Critical Review.

The Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) recommendations were published in 2016 to standardize the reporting of MRI examinations performed to assess for disease progression in patients on active surveillance for prostate cancer. Although a limited number of studies have reported outcomes from use of PRECISE in clinical practice, the available studies have demonstrated PRECISE to have high pooled NPV but low pooled PPV for predicting progression. Our experience in using PRECISE in clinical practice at two teaching hospitals has highlighted issues with its application and areas requiring clarification. This Clinical Perspective critically appraises PRECISE on the basis of this experience, focusing on the system's key advantages and disadvantages and exploring potential changes to improve the system's utility. These changes include consideration of image quality when applying PRECISE scoring, incorporation of quantitative thresholds for disease progression, adoption of a PRECISE 3F sub-category for progression not qualifying as substantial, and comparisons with both the baseline and most recent prior examinations. Items requiring clarification include derivation of a patient-level score in patients with multiple lesions, intended application of PRECISE score 5 (i.e., if requiring development of disease that is no longer organ-confined), and categorization of new lesions in patients with prior MRI-invisible disease.

Is Active Surveillance Too Active?

PURPOSE OF REVIEW: Many prostate cancer active surveillance protocols mandate serial monitoring at defined intervals, including but certainly not limited to serum PSA (often every 6 months), clinic visits, prostate multiparametric MRI, and repeat prostate biopsies. The purpose of this article is to evaluate whether current protocols result in excessive testing of patients on active surveillance. RECENT FINDINGS: Multiple studies have been published in the past several years evaluating the utility of multiparametric MRI, serum biomarkers, and serial prostate biopsy for men on active surveillance. While MRI and serum biomarkers have promise with risk stratification, no studies have demonstrated that periodic prostate biopsy can be safely omitted in active surveillance. Active surveillance for prostate cancer is too active for some men with seemingly low-risk cancer. The use of multiple prostate MRIs or additional biomarkers do not always add to the prediction of higher-grade disease on surveillance biopsy.

Deep Learning Reconstruction Enables Highly Accelerated Biparametric MR Imaging of the Prostate.

BACKGROUND: Early diagnosis and treatment of prostate cancer (PCa) can be curative; however, prostate-specific antigen is a suboptimal screening test for clinically significant PCa. While prostate magnetic resonance imaging (MRI) has demonstrated value for the diagnosis of PCa, the acquisition time is too long for a first-line screening modality. PURPOSE: To accelerate prostate MRI exams, utilizing a variational network (VN) for image reconstruction. STUDY TYPE: Retrospective. SUBJECTS: One hundred and thirteen subjects (train/val/test: 70/13/30) undergoing prostate MRI. FIELD STRENGTH/SEQUENCE: 3.0 T; a T2 turbo spin echo (TSE) T2-weighted image (T2WI) sequence in axial and coronal planes, and axial echo-planar diffusion-weighted imaging (DWI). ASSESSMENT: Four abdominal radiologists evaluated the image quality of VN reconstructions of retrospectively under-sampled biparametric MRIs (bp-MRI), and standard bp-MRI reconstructions for 20 test subjects (studies). The studies included axial and coronal T2WI, DWI B50 seconds/mm2 and B1000 seconds/mm (4-fold T2WI, 3-fold DWI), all of which were evaluated separately for image quality on a Likert scale (1: non-diagnostic to 5: excellent quality). In another 10 test subjects, three readers graded lesions on bp-MRI-which additionally included calculated B1500 seconds/mm2 , and apparent diffusion coefficient map-according to the Prostate Imaging Reporting and Data System (PI-RADS v2.1), for both VN and standard reconstructions. Accuracy of PI-RADS ≥3 for clinically significant cancer was computed. Projected scan time of the retrospectively under-sampled biparametric exam was also computed. STATISTICAL TESTS: One-sided Wilcoxon signed-rank test was used for comparison of image quality. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated for lesion detection and grading. Generalized estimating equation with cluster effect was used to compare differences between standard and VN bp-MRI. A P-value of <0.05 was considered statistically significant. RESULTS: Three of four readers rated no significant difference for overall quality between the standard and VN axial T2WI (Reader 1: 4.00 ± 0.56 (Standard), 3.90 ± 0.64 (VN) P = 0.33; Reader 2: 4.35 ± 0.74 (Standard), 3.80 ± 0.89 (VN) P = 0.003; Reader 3: 4.60 ± 0.50 (Standard), 4.55 ± 0.60 (VN) P = 0.39; Reader 4: 3.65 ± 0.99 (Standard), 3.60 ± 1.00 (VN) P = 0.38). All four readers rated no significant difference for overall quality between standard and VN DWI B1000 seconds/mm2 (Reader 1: 2.25 ± 0.62 (Standard), 2.45 ± 0.75 (VN) P = 0.96; Reader 2: 3.60 ± 0.92 (Standard), 3.55 ± 0.82 (VN) P = 0.40; Reader 3: 3.85 ± 0.72 (Standard), 3.55 ± 0.89 (VN) P = 0.07; Reader 4: 4.70 ± 0.76 (Standard); 4.60 ± 0.73 (VN) P = 0.17) and three of four readers rated no significant difference for overall quality between standard and VN DWI B50 seconds/mm2 (Reader 1: 3.20 ± 0.70 (Standard), 3.40 ± 0.75 (VN) P = 0.98; Reader 2: 2.85 ± 0.81 (Standard), 3.00 ± 0.79 (VN) P = 0.93; Reader 3: 4.45 ± 0.72 (Standard), 4.05 ± 0.69 (VN) P = 0.02; Reader 4: 4.50 ± 0.69 (Standard), 4.45 ± 0.76 (VN) P = 0.50). In the lesion evaluation study, there was no significant difference in the number of PI-RADS ≥3 lesions identified on standard vs. VN bp-MRI (P = 0.92, 0.59, 0.87) with similar sensitivity and specificity for clinically significant cancer. The average scan time of the standard clinical biparametric exam was 11.8 minutes, and this was projected to be 3.2 minutes for the accelerated exam. DATA CONCLUSION: Diagnostic accelerated biparametric prostate MRI exams can be performed using deep learning methods in <4 minutes, potentially enabling rapid screening prostate MRI. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 5.

Effect of Prostate MRI Interpretation Experience on PPV Using PI-RADS Version 2: A 6-Year Assessment Among Eight Fellowship-Trained Radiologists.

BACKGROUND. Understanding the effect of specific experience in prostate MRI interpretation on diagnostic performance would help inform the minimum interpretation volume to establish proficiency. OBJECTIVE. The purpose of this article is to assess for an association between increasing experience in prostate MRI interpretation and change in radiologist-level PPVs for PI-RADS version 2 (v2) categories 3, 4, and 5. METHODS. This retrospective study included prostate MRI examinations performed between July 1, 2015, and August 13, 2021, that were assigned a PI-RADS v2 category of 3, 4, or 5 and with an MRI-ultrasound fusion biopsy available as the reference standard. All examinations were among the first 100-200 prostate MRI examinations interpreted using PI-RADS v2 by fellowship-trained abdominal radiologists. Radiologists received feedback through a quality assurance program. Radiologists' experience levels were classified using progressive subsets of 50 interpreted examinations. Change with increasing experience in distribution of individual radiologists' whole-gland PPVs for Gleason sum score 7 or greater prostate cancer, stratified by PI-RADS category, was assessed by hierarchic linear mixed models. RESULTS. The study included 1300 prostate MRI examinations in 1037 patients (mean age, 66 ± 7 [SD] years), interpreted by eight radiologists (median, 13 years of postfellow-ship experience; range, 5-22 years). Aggregate PPVs were 20% (68/340) for PI-RADS category 3, 49% (318/652) for category 4, and 71% (220/308) for category 5. Interquartile ranges (IQRs) of PPVs overlapped for category 4 (51%; IQR, 42-60%) and category 5 (70%; IQR, 54-75%) for radiologists' first 50 examinations. IQRs of PPVs did not overlap between categories of greater experience; for example, at the 101-150 examination level, PPV for category 3 was 24% (IQR, 20-29%), category 4 was 55% (IQR, 54-63%), and category 5 was 81% (IQR, 77-82%). Hierarchic modeling showed no change in radiologists' absolute PPV with increasing experience (category 3, p = .27; category 4, p = .71; category 5, p = .38). CONCLUSION. Absolute PPVs at specific PI-RADS categories did not change during radiologists' first 200 included examinations. However, resolution of initial overlap in IQRs indicates improved precision of PPVs after the first 50 examinations. CLINICAL IMPACT. If implementing a minimum training threshold for fellowship-trained abdominal radiologists, 50 prostate MRI examinations may be sufficient in the context of a quality assurance program with feedback.

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. The purposes of this study were to compare the frequency of csPCa after negative prebiopsy bpMRI and mpMRI and to evaluate factors predictive of 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 and 193 men (mean age, 69.0 years) with negative mpMRI from January 2018 to December 2018. PI-RADS category 1 or 2 was defined as negative. The study institution offered 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 of 3 + 4 or greater. Multivariable regression analyses were performed to identify independent predictors of csPCa. The AUC of PSA density (PSAD) for csPCA was computed, and the diagnostic performance of PSAD was assessed at a clinically established threshold of 0.15 ng/mL2. RESULTS. Systematic biopsy was performed after negative bpMRI for 41.4% (96/232) of patients and after negative mpMRI for 30.5% (59/193) (p = .02). Among those undergoing biopsy, csPCa was present in 15.6% (15/96) in the bpMRI cohort versus 13.6% (8/59) in the mpMRI cohort (p = .69). The 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) was not independently predictive of csPCa (p > .05). PSAD had an AUC for csPCa of 0.71 (95% CI, 0.56-0.87) in the bpMRI cohort versus 0.68 (95% CI, 0.42-0.93) in the mpMRI cohort. For detecting csPCa, a 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 frequencies of csPCa were not significantly different at systematic biopsy performed after negative bpMRI and mpMRI examinations. PSAD had similar diagnostic utility for csPCa in the two cohorts. CLINICAL IMPACT. Either bpMRI or mpMRI, in combination with PSAD measurement, can help avoid negative prostate biopsies.

COMPARISON OF GRADING ACCURACY OF PROSTATE CANCER IN SAMPLES ACQUIRED BY A TARGETED AND SYSTEMIC PROSTATE BIOPSY.

Introduction: All malignancies, including prostate cancer, require accurate diagnosing and staging before making a treatment decision. The introduction of targeted biopsies based on prostate MRI findings has raised prostate biopsy accuracy. Guided biopsies target the tumor itself during the biopsy instead of the most common tumor sites as is the case with a systemic biopsy. Some studies report that targeted biopsies should lower prostate cancer biopsy undergrading and overgrading. Goals: To determine the incidence of prostate cancer biopsy undergrading in patients who underwent a classic systemic biopsy compared to patients who underwent a mpMRI cognitive targeted biopsy. Materials and methods: We identified the patients from our database who underwent a radical prostatectomy at our institution from January 1st, 2021, to June 30th, 2021.There were 112 patients identified. Patients were stratified into two groups based on the type of biopsy that confirmed prostate cancer. The mpMRI (N=50) group had a mpMRI cognitive guided transrectal ultrasound (TRUS) prostate biopsy performed, and the non-mpMRI group (N=62) received a classic, systemic TRUS biopsy. We compared the biopsy results with the final pathological results, and searched for undergrading or overgrading in the biopsies compared to the final histological report. Results: The undergrading was found in 17,7% (N=11) cases in the non-mpMRI group and in 12,0% (N=6) of cases in the mpMRI group (p=0,02, Mann-Whitney U test). No overgrading was found in our cohort. All cases of undergrading had Grade Group 1 in the biopsy report and Grade Group 2 in the final specimen report. The charasteristics of patients are listed in Table 1. Discussion and conclusion: In our cohort, the patients who underwent a mpMRI targeted biopsy had a lower undergrading incidence. During a systemic TRUS biopsy, the urologist targets the areas of the prostate where cancer is most commonly located, which is usually the peripheral zone of the prostate. Since different areas of the tumor have different areas of differentiation, only a low-grade part of the tumor is sometimes biopsied, which results in a sampling error. Once the prostate is removed, the whole tumor is analyzed, so the obtained pathological results related to the removed prostate are far more accurate than the analysis of prostate cores obtained by biopsy.

Cross correlation-based misregistration correction for super resolution T2 -weighted spin-echo images: application to prostate.

PURPOSE: The purpose is to develop a retrospective correction for subtle slice-to-slice positional inconsistencies that can occur when overlapped slices are acquired for super resolution in T2 -weighted spin-echo multislice imaging. METHODS: Spin-echo acquisition of overlapped slices is typically done using multiple passes. After the passes are assembled into the final slice set, consecutive slices are correlated due to their overlap. Cross correlation was used to measure slice-to-slice displacement. After Z-dependent filtering to preserve true object shape, the displacements were used to correct slice position. The method was tested in a phantom moved slowly (0.16-0.63 mm/pass) under computer control and in vivo in 16 patients having prostate MRI. RESULTS: Over the motion range, the correlation method had an accuracy within 0.03 mm/pass and precision ± 0.20 mm (ie, subpixel). Corrected images visually resemble the true object. Over the patient studies, the mean range of motion in the anterior-posterior direction was 1.63 mm. Motion-corrected axial images and the sagittal reformats were evaluated as significantly superior over those formed without motion correction. CONCLUSION: The retrospective correlation-based motion-correction method provides significant improvement in the slice-to-slice registration necessary for effective super resolution using overlapped slices.

Magnetic Resonance Imaging Radiomics-Based Machine Learning Prediction of Clinically Significant Prostate Cancer in Equivocal PI-RADS 3 Lesions.

BACKGROUND: While Prostate Imaging Reporting and Data System (PI-RADS) 4 and 5 lesions typically warrant prostate biopsy and PI-RADS 1 and 2 lesions may be safely observed, PI-RADS 3 lesions are equivocal. PURPOSE: To construct and cross-validate a machine learning model based on radiomics features from T2 -weighted imaging (T2 WI) of PI-RADS 3 lesions to identify clinically significant prostate cancer (csPCa), that is, pathological Grade Group ≥ 2. STUDY TYPE: Single-center retrospective study. POPULATION: A total of 240 patients were included (training cohort, n = 188, age range 43-82 years; test cohort, n = 52, age range 41-79 years). Eligibility criteria were 1) magnetic resonance imaging (MRI)-targeted biopsy between 2015 and 2020; 2) PI-RADS 3 index lesion identified on multiparametric MRI; (3) biopsy performed within 1 year of MRI. The percentages of csPCa lesions were 10.6% and 15.4% in the training and test cohorts, respectively. FIELD STRENGTH/SEQUENCE: A 3 T; T2 WI turbo-spin echo, diffusion-weighted spin-echo echo planar imaging, dynamic contrast-enhanced MRI with time-resolved T1-weighted imaging. ASSESSMENT: Multislice volumes-of-interest (VOIs) were drawn in the PI-RADS 3 index lesions on T2 WI. A total of 107 radiomics features (first-order histogram and second-order texture) were extracted from the segmented lesions. STATISTICAL TESTS: A random forest classifier using the radiomics features as input was trained and validated for prediction of csPCa. The performance of the machine learning classifier, prostate specific antigen (PSA) density, and prostate volume for csPCa prediction was evaluated using receiver operating characteristic (ROC) analysis. RESULTS: The trained random forest classifier constructed from the T2 WI radiomics features good and statistically significant area-under-the-curves (AUCs) of 0.76 (P = 0.022) for prediction of csPCa in the test set. Prostate volume and PSA density showed moderate and nonsignificant performance (AUC 0.62, P = 0.275 and 0.61, P = 0.348, respectively) for csPCa prediction in the test set. CONCLUSION: The machine learning classifier based on T2 WI radiomic features demonstrated good performance for prediction of csPCa in PI-RADS 3 lesions. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: 2.

Innovative standardized reporting template for prostate mpMRI improves clarity and confidence in the report.

PURPOSE: The goal of the current study was to evaluate the effect of a standardized prostate mpMRI reporting template on urologists' understanding and confidence in counselling a patient on the results of the MRI. To do this we performed a survey study to assess the understanding and confidence of urologists reviewing reports prior to (pre) and after (post) adoption of a standardized mpMRI template. METHODS: Six urologists reviewed ten pre- and post- mpMRI templated reports and completed a survey to assess the clarity of key elements and the confidence in counseling the patient. The urologists were blinded to the study objective. Nonparametric constrained permutation test for significance was performed to compare the results prior to and after implementation of the template. RESULTS: 29 pre- and 30 post-template mpMRI reports were reviewed. The average score for the post-template reports was significantly higher (10.7 ± 0.6 vs 7.5 ± 2.7 [ p< 0.001]) regardless of the reviewer. Urologists were also overall more confident in counselling patients when the standardized mpMRI reporting template had been used. CONCLUSION: Implementation of a standardized template for reporting of prostate mpMRI findings resulted in improved clarity and confidence in counselling patients. Radiologists should consider implementing a standardized reporting template to improve clinicians' understanding and confidence of the report.

Comparison of risk-calculator and MRI and consecutive pathways as upfront stratification for prostate biopsy.

PURPOSE: In biopsy naïve men suspected for prostate cancer (PCa), it is uncertain how a risk-calculator and bi-parametric (bp) MRI should be combined to decide on prostate biopsy, balancing cancer detection rates and diagnostic burden. METHODS: Prospective, single centre cohort study (August 2018-April 2019). All patients referred with serum PSA ≥ 3 ng/ml or abnormal digital rectal examination received bpMRI and risk for PCa was calculated using the ERSPC risk-calculator. Men with either PI-RADS ≥ 3 or calculator risk-score > 20% were recommended to undergo systematic biopsy (SB) and targeted biopsy (TB) of any visible lesion (reference pathway). Eight different derived diagnostic pathways were compared to the reference pathway regarding cancer detection, number of biopsies and bpMRIs performed. RESULTS: Of 496 patients; 233 (47%) had a risk-calculator score of > 20%; 201 (41%) had PI-RADS score ≥ 3. The reference pathway detected PCa in 32.1%, clinically significant (cs) PCa in 19.4%, with 41% avoided biopsies, but 0% avoided bpMRI. Stratification with only risk-calculator: 76% csPCa diagnosed, 53% avoided biopsies and 100% avoided bpMRI. Stratification with only bpMRI: 97% csPCa diagnosed, 59% avoided biopsies, but 0% avoided bpMRI. A pathway with risk-calculator first, followed only with bpMRI when high-risk: 81% csPCa diagnosed, 72% avoided biopsies and 53% avoided bpMRI. CONCLUSION: Upfront bpMRI as a risk stratification tool outperforms risk-calculator in detecting significant disease. Applying the risk-calculator first to decide on performing an MRI, avoids 1 out of 2 MRIs, but up to 1 out of 5 significant cancers are missed.