Diagnosis of transition zone prostate cancer by multiparametric MRI: added value of MR spectroscopic imaging with sLASER volume selection.

BACKGROUND: Current multiparametric MRI (mp-MRI) in routine clinical practice has poor-to-moderate diagnostic performance for transition zone prostate cancer. The aim of this study was to evaluate the potential diagnostic performance of novel 1H magnetic resonance spectroscopic imaging (MRSI) using a semi-localized adiabatic selective refocusing (sLASER) sequence with gradient offset independent adiabaticity (GOIA) pulses in addition to the routine mp-MRI, including T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI) and quantitative dynamic contrast enhancement (DCE) for transition zone prostate cancer detection, localization and grading. METHODS: Forty-one transition zone prostate cancer patients underwent mp-MRI with an external phased-array coil. Normal and cancer regions were delineated by two radiologists and divided into low-risk, intermediate-risk, and high-risk categories based on TRUS guided biopsy results. Support vector machine models were built using different clinically applicable combinations of T2WI, DWI, DCE, and MRSI. The diagnostic performance of each model in cancer detection was evaluated using the area under curve (AUC) of the receiver operating characteristic diagram. Then accuracy, sensitivity and specificity of each model were calculated. Furthermore, the correlation of mp-MRI parameters with low-risk, intermediate-risk and high-risk cancers were calculated using the Spearman correlation coefficient. RESULTS: The addition of MRSI to T2WI + DWI and T2WI + DWI + DCE improved the accuracy, sensitivity and specificity for cancer detection. The best performance was achieved with T2WI + DWI + MRSI where the addition of MRSI improved the AUC, accuracy, sensitivity and specificity from 0.86 to 0.99, 0.83 to 0.96, 0.80 to 0.95, and 0.85 to 0.97 respectively. The (choline + spermine + creatine)/citrate ratio of MRSI showed the highest correlation with cancer risk groups (r = 0.64, p < 0.01). CONCLUSION: The inclusion of GOIA-sLASER MRSI into conventional mp-MRI significantly improves the diagnostic accuracy of the detection and aggressiveness assessment of transition zone prostate cancer.

Synergistic multi-contrast cardiac magnetic resonance image reconstruction.

Cardiac magnetic resonance imaging (CMR) is an important tool for the non-invasive diagnosis of a variety of cardiovascular diseases. Parametric mapping with multi-contrast CMR is able to quantify tissue alterations in myocardial disease and promises to improve patient care. However, magnetic resonance imaging is an inherently slow imaging modality, resulting in long acquisition times for parametric mapping which acquires a series of cardiac images with different contrasts for signal fitting or dictionary matching. Furthermore, extra efforts to deal with respiratory and cardiac motion by triggering and gating further increase the scan time. Several techniques have been developed to speed up CMR acquisitions, which usually acquire less data than that required by the Nyquist-Shannon sampling theorem, followed by regularized reconstruction to mitigate undersampling artefacts. Recent advances in CMR parametric mapping speed up CMR by synergistically exploiting spatial-temporal and contrast redundancies. In this article, we will review the recent developments in multi-contrast CMR image reconstruction for parametric mapping with special focus on low-rank and model-based reconstructions. Deep learning-based multi-contrast reconstruction has recently been proposed in other magnetic resonance applications. These developments will be covered to introduce the general methodology. Current technical limitations and potential future directions are discussed. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'.

Clinical characteristics and oncological outcomes in negative multiparametric MRI patients undergoing robot-assisted radical prostatectomy.

BACKGROUND: Efforts are ongoing to try and find ways to reduce the number of unnecessary prostate biopsies without missing clinically significant prostate cancers (csPCa). The utility of multiparametric magnetic resonance imaging (mpMRI) in detecting prostate cancer (PCa) shows promise to be used as triage test for systematic prostate biopsy. Our aim is to Study clinical parameters and oncological outcomes in men with negative mpMRI (nMRI; PI-RADS v2 scores of ≤ 2) who underwent robot-assisted radical prostatectomy (RARP) to evaluate nMRI's practicality as a biopsy triage test. METHODS: Retrospective analysis of 331 men with nMRI who underwent RARP between 2014 and 2020 compared with men with positive mpMRI (pMRI; PI-RADS v2 scores ≥ 3, N = 1770). csPCa was defined as Gleason score ≥ 3 + 4 and biochemical recurrence (BCR) was defined as PSA > 0.2 ng/ml on two occasions. Biopsies were graded with the International Society of Urologic Pathology [ISUP] grade. Descriptive statistics for nMRI and pMRI were performed. Mann-Whitney U test was used for continuous variables and χ 2 for categorical variables. Univariable and multivariable regression analyses were performed. RESULTS: Univariable analysis shows statistically significant difference (p < .05) between median age (nMRI-61 years vs. pMRI 63 years), race (higher incidence of nMRI in African American men), use of 5-alpha reductase inhibitors (higher rate in nMRI). While incidence rates of family history of PCa, suspicious digital rectal examination (DRE) findings, median PSA levels and 4Kscore, were lower in nMRI versus pMRI. Rates of positive surgical margins and BCR were comparable in nMRI versus pMRI. Biopsy ISUP Grades I and II upgraded by 51% and 12%, respectively in final pathology. African American race and no history of the prior negative biopsy were significant predictors for upgrading. CONCLUSION: Men with nMRI pose diagnostic challenges as they tend to be younger patients with lower rates of suspicious DRE findings and lower 4K scores, yet comparable oncological outcomes in csPCa rates, positive surgical margins, and BCR rates.

Optimizing Spatial Biopsy Sampling for the Detection of Prostate Cancer.

PURPOSE: The appropriate number of systematic biopsy cores to retrieve during magnetic resonance imaging (MRI)-targeted prostate biopsy is not well defined. We aimed to demonstrate a biopsy sampling approach that reduces required core count while maintaining diagnostic performance. MATERIALS AND METHODS: We collected data from a cohort of 971 men who underwent MRI-ultrasound fusion targeted biopsy for suspected prostate cancer. A regional targeted biopsy (RTB) was evaluated retrospectively; only cores within 2 cm of the margin of a radiologist-defined region of interest were considered part of the RTB. We compared detection rates for clinically significant prostate cancer (csPCa) and cancer upgrading rate on final whole mount pathology after prostatectomy between RTB, combined, MRI-targeted, and systematic biopsy. RESULTS: A total of 16,459 total cores from 971 men were included in the study data sets, of which 1,535 (9%) contained csPCa. The csPCa detection rates for systematic, MRI-targeted, combined, and RTB were 27.0% (262/971), 38.3% (372/971), 44.8% (435/971), and 44.0% (427/971), respectively. Combined biopsy detected significantly more csPCa than systematic and MRI-targeted biopsy (p <0.001 and p=0.004, respectively) but was similar to RTB (p=0.71), which used on average 3.8 (22%) fewer cores per patient. In 102 patients who underwent prostatectomy, there was no significant difference in upgrading rates between RTB and combined biopsy (p=0.84). CONCLUSIONS: A RTB approach can maintain state-of-the-art detection rates while requiring fewer retrieved cores. This result informs decision making about biopsy site selection and total retrieved core count.

Diagnosis of Prostate Cancer in Patients with Prostate-Specific Antigen (PSA) in the Gray Area: Construction of 2 Predictive Models.

BACKGROUND Two diagnostic models of prostate cancer (PCa) and clinically significant prostate cancer (CS-PCa) were established using clinical data of among patients whose prostate-specific antigen (PSA) levels are in the gray area (4.0-10.0 ng/ml). MATERIAL AND METHODS Data from 181 patients whose PSA levels were in the gray area were retrospectively analyzed, and the following data were collected: age, digital rectal examination, total PSA, PSA density (PSAD), free/total PSA (f/t PSA), transrectal ultrasound, multiparametric magnetic resonance imaging (mpMRI), and pathological reports. Patients were diagnosed with benign prostatic hyperplasia (BPH) and PCa by pathology reports, and PCa patients were separated into non-clinically significant PCa (NCS-PCa) and CS-PCa by Gleason score. Afterward, predictor models constructed by above parameters were researched to diagnose PCa and CS-PCa, respectively. RESULTS According to the analysis of included clinical data, there were 109 patients with BPH, 44 patients with NCS-PCa, and 28 patients with CS-PCa. Regression analysis showed PCa was correlated with f/t PSA, PSAD, and mpMRI (P<0.01), and CS-PCa was correlated with PSAD and mpMRI (P<0.01). The area under the receiver operating characteristic curves of 2 models for PCa (sensitivity=73.64%, specificity=64.23%) and for CS-PCa (sensitivity=71.41%, specificity=81.82%) were 0.79 and 0.87, respectively. CONCLUSIONS The prediction models had satisfactory diagnostic value for PCa and CS-PCa among patients with PSA in the gray area, and use of these models may help reduce overdiagnosis.

Spatiotemporal Heterogeneity in Multiparametric Physiologic MRI Is Associated with Patient Outcomes in IDH-Wildtype Glioblastoma.

PURPOSE: Heterogeneity in glioblastomas is associated with poorer outcomes, and physiologic heterogeneity can be quantified with noninvasive imaging. We developed spatial habitats based on multiparametric physiologic MRI and evaluated associations between temporal changes in these habitats and progression-free survival (PFS) after concurrent chemoradiotherapy (CCRT) in patients with glioblastoma. EXPERIMENTAL DESIGN: Ninety-seven patients with isocitrate dehydrogenase (IDH)-wildtype glioblastoma were enrolled and two serial MRI examinations after CCRT were analyzed. Cerebral blood volumes and apparent diffusion coefficients were grouped using k-means clustering into three spatial habitats. Associations between temporal changes in spatial habitats and PFS were investigated using Cox proportional hazard modeling. The performance of significant predictors for PFS and overall survival (OS) was measured using a discrete increase of habitat (habitat risk score) in a temporal validation set from a prospective registry (n = 53, ClinicalTrials.gov NCT02619890). The site of progression was matched with the spatiotemporal habitats. RESULTS: Three spatial habitats of hypervascular cellular, hypovascular cellular, and nonviable tissue were identified. A short-term increase in the hypervascular cellular habitat (HR, 40.0; P = 0.001) and hypovascular cellular habitat was significantly associated with shorter PFS (HR, 3.78; P < 0.001) after CCRT. Combined with clinical predictors, the habitat risk score showed a C-index of 0.79 for PFS and 0.74 for OS and stratified patients with short, intermediate, and long PFS (P = 0.016). An increase in the hypovascular cellular habitat predicted tumor progression sites. CONCLUSIONS: Hypovascular cellular habitats derived from multiparametric physiologic MRIs may be useful predictors of clinical outcomes in patients with posttreatment glioblastoma.

The Impact of Histopathological Features of Prostate Cancerous Lesions on Multiparametric Magnetic Resonance Imaging Findings using PI-RADS Version 2.

OBJECTIVES: To determine the square measure threshold of prostate cancer lesions in pathological specimens showing PI-RADS categories 3 to 5, and to identify the pathological characteristics of cancerous lesions over the threshold. METHODS: Cancer foci detected in horizontal sections of specimens were defined as pathological cancerous lesions, in which square measure, lesion location (peripheral or transition zone), Gleason pattern (GP), GP4-5 component percentages, and GP 4 subtypes were assessed. A receiver operating characteristic curve was used to determine the threshold of the square measure of pathological specimens that distinguishes between lesions of PI-RADS categories 1 and 2 and those of 3 to 5. Univariable and multivariable analyses were performed to determine the histopathological features associated with PI-RADS categories 3 to 5. RESULTS: A total of 100 consecutive patients underwent multiparametric magnetic resonance imaging before robotic-assisted laparoscopic prostatectomy. A total of 1366 pathological cancerous lesions were detected, 217 of which were classified as PI-RADS categories 3 to 5. A square measure of 40 mm2 on pathological specimens was the threshold for PI-RADS categories 3 to 5. Of the 415 lesions that were over 40 mm2, 211 lesions exhibited PI-RADS categories 1, 2 and 204 lesions exhibited PI-RADS categories 3 to 5. Multiple logistic regression analysis showed that square measure, fused glands, and cribriform glands were independently associated with PI-RADS categories 3 to 5. CONCLUSION: Cancerous lesions over 40 mm2 showing PI-RADS categories 3 to 5 are associated with square measure, fused glands, and cribriform glands.

Evaluation of Multimodal Algorithms for the Segmentation of Multiparametric MRI Prostate Images.

Prostate segmentation in multiparametric magnetic resonance imaging (mpMRI) can help to support prostate cancer diagnosis and therapy treatment. However, manual segmentation of the prostate is subjective and time-consuming. Many deep learning monomodal networks have been developed for automatic whole prostate segmentation from T2-weighted MR images. We aimed to investigate the added value of multimodal networks in segmenting the prostate into the peripheral zone (PZ) and central gland (CG). We optimized and evaluated monomodal DenseVNet, multimodal ScaleNet, and monomodal and multimodal HighRes3DNet, which yielded dice score coefficients (DSC) of 0.875, 0.848, 0.858, and 0.890 in WG, respectively. Multimodal HighRes3DNet and ScaleNet yielded higher DSC with statistical differences in PZ and CG only compared to monomodal DenseVNet, indicating that multimodal networks added value by generating better segmentation between PZ and CG regions but did not improve the WG segmentation. No significant difference was observed in the apex and base of WG segmentation between monomodal and multimodal networks, indicating that the segmentations at the apex and base were more affected by the general network architecture. The number of training data was also varied for DenseVNet and HighRes3DNet, from 20 to 120 in steps of 20. DenseVNet was able to yield DSC of higher than 0.65 even for special cases, such as TURP or abnormal prostate, whereas HighRes3DNet's performance fluctuated with no trend despite being the best network overall. Multimodal networks did not add value in segmenting special cases but generally reduced variations in segmentation compared to the same matched monomodal network.

Performance of Multiparametric MRI of the Prostate in Biopsy Naïve Men: A Meta-analysis of Prospective Studies.

OBJECTIVE: To assess the outcomes through systematic review and meta-analysis of multi-parametric magnetic resonance imaging (mpMRI) of the prostate in biopsy naïve men. METHODS: Systemic review and meta-analysis was performed to assess the performance of mpMRI on prostate cancer (PCa) detection at the time of biopsy. We used standard methods for performing a meta-analysis evaluating a diagnostic test and reported the pooled sensitivity and specificity, and the positive and negative likelihood ratios (LR) for mpMRI in the detection of any and clinically significant prostate cancer (csPCa). RESULTS: A total of 10 studies comprising 2486 patients were analyzed. Overall, if biopsies would have been performed only in men with an mpMRI suspicious for malignancy between 7.4% and 58.5% of the biopsies could have been avoided, but 2.3%-36% of any PCa and 0%-30.8% of csPCa would have been missed. The sensitivity, specificity, positive LR, and negative LR of mpMRI for any PCa detection were 0.86 (95% confidence interval [CI], 0.78-0.91), 0.67 (95% CI, 0.40-0.86), 2.6 (95% CI, 1.2-5.5), and 0.2 (95% CI, 0.12-0.32), respectively. The AUC for any PCa detection was 0.84 (95% CI, 0.75-0.90). The pooled sensitivity, specificity, positive LR, and negative LR of mpMRI for csPCa detection was 0.94 (95% CI, 0.83-0.98), 0.54 (95% CI, 0.42-0.65), 2 (95% CI, 1.5-2.7), and 0.1 (95% CI, 0.02-0.35), respectively. The AUC for csPCa detection was 0.94 (95% CI, 0.65-1). CONCLUSION: This study provides summary estimates indicating that mpMRI can accurately detect prostate cancer and help avoid unnecessary biopsies in this population.

Multimodal principal component analysis to identify major features of white matter structure and links to reading.

The role of white matter in reading has been established by diffusion tensor imaging (DTI), but DTI cannot identify specific microstructural features driving these relationships. Neurite orientation dispersion and density imaging (NODDI), inhomogeneous magnetization transfer (ihMT) and multicomponent driven equilibrium single-pulse observation of T1/T2 (mcDESPOT) can be used to link more specific aspects of white matter microstructure and reading due to their sensitivity to axonal packing and fiber coherence (NODDI) and myelin (ihMT and mcDESPOT). We applied principal component analysis (PCA) to combine DTI, NODDI, ihMT and mcDESPOT measures (10 in total), identify major features of white matter structure, and link these features to both reading and age. Analysis was performed for nine reading-related tracts in 46 neurotypical 6-16 year olds. We identified three principal components (PCs) which explained 79.5% of variance in our dataset. PC1 probed tissue complexity, PC2 described myelin and axonal packing, while PC3 was related to axonal diameter. Mixed effects regression models did not identify any significant relationships between principal components and reading skill. Bayes factor analysis revealed that the absence of relationships was not due to low power. Increasing PC1 in the left arcuate fasciculus with age suggest increases in tissue complexity, while increases of PC2 in the bilateral arcuate, inferior longitudinal, inferior fronto-occipital fasciculi, and splenium suggest increases in myelin and axonal packing with age. Multimodal white matter imaging and PCA provide microstructurally informative, powerful principal components which can be used by future studies of development and cognition. Our findings suggest major features of white matter undergo development during childhood and adolescence, but changes are not linked to reading during this period in our typically-developing sample.

Comparison of 68Ga-PSMA-617 PET/CT with mpMRI for the detection of PCa in patients with a PSA level of 4-20 ng/ml before the initial biopsy.

The study was aimed at assessing the diagnostic performance of 68Ga-PSMA-617 PET/CT in the detection of prostate cancer (PCa) in patients with a prostate-specific antigen (PSA) level of 4-20 ng/ml and to compare its efficacy with that of multiparametric MRI (mpMRI). We analyzed the data of 67 consecutive patients with PSA levels of 4-20 ng/ml who almost simultaneously underwent 68Ga-PSMA-617 PET/CT and mpMRI. 68Ga-PSMA-617 PET/CT and mpMRI diagnostic performances were compared via receiver operating characteristic (ROC) curve analysis. Of the 67 suspected PCa cases, 33 had pathologically confirmed PCa. 68Ga-PSMA-617 PET/CT showed a patient-based sensitivity, specificity, and positive and negative predictive values (PPVs and NPVs) of 87.88%, 88.24%, 87.88%, and 88.24%, respectively. The corresponding values for mpMRI were 84.85%, 52.94%, 63.64%, and 78.26%. The area under the curve values for 68Ga-PSMA-617 PET/CT and mpMRI were 0.881 and 0.689, respectively. 68Ga-PSMA-617 PET/CT showed a better diagnostic performance than mpMRI in the detection of PCa in patients with PSA levels of 4-20 ng/ml.

Multimodal MRI Brain Tumor Image Segmentation Using Sparse Subspace Clustering Algorithm.

Brain tumors are one of the most deadly diseases with a high mortality rate. The shape and size of the tumor are random during the growth process. Brain tumor segmentation is a brain tumor assisted diagnosis technology that separates different brain tumor structures such as edema and active and tumor necrosis tissues from normal brain tissue. Magnetic resonance imaging (MRI) technology has the advantages of no radiation impact on the human body, good imaging effect on structural tissues, and an ability to realize tomographic imaging of any orientation. Therefore, doctors often use MRI brain tumor images to analyze and process brain tumors. In these images, the tumor structure is only characterized by grayscale changes, and the developed images obtained by different equipment and different conditions may also be different. This makes it difficult for traditional image segmentation methods to deal well with the segmentation of brain tumor images. Considering that the traditional single-mode MRI brain tumor images contain incomplete brain tumor information, it is difficult to segment the single-mode brain tumor images to meet clinical needs. In this paper, a sparse subspace clustering (SSC) algorithm is introduced to process the diagnosis of multimodal MRI brain tumor images. In the absence of added noise, the proposed algorithm has better advantages than traditional methods. Compared with the top 15 in the Brats 2015 competition, the accuracy is not much different, being basically stable between 10 and 15. In order to verify the noise resistance of the proposed algorithm, this paper adds 5%, 10%, 15%, and 20% Gaussian noise to the test image. Experimental results show that the proposed algorithm has better noise immunity than a comparable algorithm.

PI-RADS® Category as a Predictor of Progression to Unfavorable Risk Prostate Cancer in Men on Active Surveillance.

PURPOSE: We identified baseline imaging and clinical characteristics of patients that may improve risk stratification among patients being evaluated for active surveillance. MATERIALS AND METHODS: From July 2007 to January 2020 patients referred to our institution for prostate cancer were evaluated and those who remained on active surveillance were identified. Men underwent multiparametric magnetic resonance imaging upon entry into our active surveillance protocol during which baseline demographic and imaging data were documented. Patients were then followed and outcomes, specifically progression to Gleason Grade Group (GG)3 or greater disease, were recorded. RESULTS: Of the men placed on active surveillance 344 had at least 1 PI-RADS score documented. For those with an index lesion PI-RADS category of 5, 33% (17/51) had progression to GG3 or greater on active surveillance with a median time to progression of 31 months. When comparing the progression-free survival times and progression rates in each category, PI-RADS category was found to be associated with progression to GG3 or greater on active surveillance (p <0.01). On univariable analysis factors associated with progression included an index lesion PI-RADS category of 5, prostate specific antigen density and the size of the largest lesion. On multivariable analysis only PI-RADS category of 5 and prostate specific antigen density were associated with progression on active surveillance. CONCLUSIONS: PI-RADS lesion categories at baseline multiparametric magnetic resonance imaging during active surveillance enrollment can be used to predict cancer progression to GG3 or greater on active surveillance. This information, along with other clinical data, can better assist urologists in identifying and managing patients appropriate for active surveillance.

Does the Visibility of Grade Group 1 Prostate Cancer on Baseline Multiparametric Magnetic Resonance Imaging Impact Clinical Outcomes?

PURPOSE: We assessed whether the visibility of Grade Group (GG) 1 prostate cancer on baseline multiparametric magnetic resonance imaging affects clinical outcomes. MATERIALS AND METHODS: We evaluated 454 men who underwent multiparametric magnetic resonance imaging between 2006 and 2018 with maximum GG1 prostate cancer inclusive of magnetic resonance imaging targeted biopsy. Multiparametric magnetic resonance imaging was graded as negative, equivocal or positive. Assessed outcomes were treatment-free survival, biopsy upgrade-free survival and unfavorable disease at radical prostatectomy (pT 3 or greater and/or GG3 or greater). Kaplan-Meier and multivariable Cox proportional hazard analyses were used to estimate the impact of multiparametric magnetic resonance imaging and clinicopathological variables (age, year, prostate specific antigen density and measures of tumor volume on biopsy) on outcomes. RESULTS: During followup (median 45.2 months) 61 men had disease upgraded on followup biopsy and 139 underwent definitive treatment. In men with negative, equivocal and positive baseline multiparametric magnetic resonance imaging at 5 years, treatment-free survival was 79%, 73% and 49% (p <0.0001), treatment-free survival was 89%, 82% and 70% (p=0.002), and survival without unfavorable disease at radical prostatectomy was 98%, 98% and 86% (p=0.007), respectively. At multivariable analysis positive (HR 1.93, 95% CI 1.21-3.09, p=0.006) and equivocal multiparametric magnetic resonance imaging (HR 2.02, 95% CI 1.11-3.68, p=0.02) were associated with shorter treatment-free survival, and positive multiparametric magnetic resonance imaging was a significant prognostic factor for upgrade-free survival (HR 2.03, 95% CI 1.06-3.86, p=0.03) and unfavorable disease at radical prostatectomy (HR 4.45, 95% CI 1.39-18.17, p=0.01). CONCLUSIONS: Men with positive multiparametric magnetic resonance imaging and GG1 prostate cancer on magnetic resonance imaging targeted biopsy are at increased risk for intervention, upgrading and unfavorable disease at radical prostatectomy compared to those with multiparametric magnetic resonance imaging invisible GG1 prostate cancer.

Effects of "real life" prostate MRI inter-observer variability on total needle samples and indication for biopsy.

PURPOSE: Prostate multiparametric magnetic resonance imaging (mpMRI) improves diagnosis of clinically significant cancer and reduces over-detection of nonsignificant cancer. Disagreement in the interpretation of mpMRI readings is well-known, with a reported discrepancy rate of 10% to 42%. We report the clinical repercussions of this variability on prostate biopsy candidates. MATERIALS AND METHODS: Medical records of patients referred from 11 medical centers for MR-guided prostate biopsy (MRGpB) between October, 2017 and January, 2019 were retrospectively analyzed. Patients with at least one prostate imaging reporting and data system (PI-RADS) 3 or greater prostate lesion were selected, and the mpMRI studies (all read by others) were reviewed by our prostate mpMRI reader. Outcomes included changes in PI-RADS score and the subsequent effect on total needle samples and indication for biopsy. RESULTS: Eighty-two patients with 128 lesions were suitable for analysis (mean age 66.5 ± 7.1 years, mean PSA 6.8 ± 8.5 ng/ml). Nine (11%) patients had suspicious rectal exams (T2a). Following our prostate mpMRI reader's imaging revisions, the PI-RADS score was downgraded in 66 (52%) lesions, upgraded in 15 (12%), and unchanged in 47 (37%), leaving a total of 84 suspected lesions (kappa = 0.17). Biopsy was deferred in 22 (27%) patients, and an estimated 136.4 (34.4%) samples were avoided (P = 0.0001 for both). There was a trend toward prostate size to correlate with imaging revision and abortion of biopsy (P = 0.06) while enrollment in active surveillance correlated with proof from such outcome (P = 0.007). CONCLUSION: These data suggest that high interobserver disagreement in prostate mpMRIs from diverse institutes significantly affects prostate biopsy practice. The clinical consequences of this discord are significant.

Racial disparity in the utilization of multiparametric MRI-ultrasound fusion biopsy for the detection of prostate cancer.

BACKGROUND: Black men have significantly higher incidence and are up to three times more likely to die of prostate cancer (PCa) than White men. Multiparametric magnetic resonance imaging-ultrasound fusion biopsy (FBx) has emerged as a promising modality for the detection of PCa. The goal of our study is to identify differences in utilization of FBx between Black and White men presenting with suspicion of PCa. METHODS: We performed a retrospective review of Black and White men who presented with suspicion of PCa and required biopsy from January 2014 to December 2018. Multivariate logistic regression analysis was done to study the influence of race on the utilization of FBx. RESULTS: Six hundred nineteen (Black: 182, White: 437) men were included in the study. Forty-one out of 182 (22.5%) Black men underwent FBx compared with 225/437 (51.5%) of White men (P < 0.001). After adjusting for age, race, prostate-specific antigen level, digital rectal exam, family history of PCa and health insurance provider, Black race was found to be a significant negative predictor of obtaining FBx (OR:0.32, 95% CI: 0.21-0.51, P < 0.001). Black race stayed an independent negative predictor (OR: 0.36, 95% CI: 0.20-0.64, P < 0.001) in the cohort of patients who were biopsy naïve; however, although reduced, there was no significant difference in the cohort with a prior negative biopsy (OR: 0.51, 95% CI: 0.19-1.36, P = 0.179). CONCLUSIONS: Although FBx is a superior modality for early detection of PCa, we found that Black men were less likely to undergo FBx when presenting with PCa suspicion. Further investigation is needed to evaluate if this difference is patient preference or if there are underlying socioeconomic, cultural or provider biases influencing this disparity.

Comparing the interobserver reproducibility of different regions of interest on multi-parametric renal magnetic resonance imaging in healthy volunteers, patients with heart failure and renal transplant recipients.

OBJECTIVE: To assess interobserver reproducibility of different regions of interest (ROIs) on multi-parametric renal MRI using commercially available software. MATERIALS AND METHODS: Healthy volunteers (HV), patients with heart failure (HF) and renal transplant recipients (Tx) were recruited. Localiser scans, T1 mapping and pseudo-continuous arterial spin labelling (pCASL) were performed. HV and Tx also underwent diffusion-weighted imaging to allow calculation of apparent diffusion coefficient (ADC). For T1, pCASL and ADC, ROIs were drawn for whole kidney (WK), cortex (Cx), user-defined representative cortex (rep-Cx) and medulla. Intraclass correlation coefficient (ICC) and coefficient of variation (CoV) were assessed. RESULTS: Forty participants were included (10 HV, 10 HF and 20 Tx). The ICC for renal volume was 0.97 and CoV 6.5%. For T1 and ADC, WK, Cx, and rep-Cx were highly reproducible with ICC ≥ 0.76 and CoV < 5%. However, cortical pCASL results were more variable (ICC > 0.86, but CoV up to 14.2%). While reproducible, WK values were derived from a wide spread of data (ROI standard deviation 17% to 55% of the mean value for ADC and pCASL, respectively). Renal volume differed between groups (p < 0.001), while mean cortical T1 values were greater in Tx compared to HV (p = 0.009) and HF (p = 0.02). Medullary T1 values were also higher in Tx than HV (p = 0.03), while medullary pCASL values were significantly lower in Tx compared to HV and HF (p = 0.03 for both). DISCUSSION: Kidney volume calculated by manually contouring a localiser scan was highly reproducible between observers and detected significant differences across patient groups. For T1, pCASL and ADC, Cx and rep-Cx ROIs are generally reproducible with advantages over WK values.

The Magnetic Resonance Imaging in Active Surveillance (MRIAS) Trial: Use of Baseline Multiparametric Magnetic Resonance Imaging and Saturation Biopsy to Reduce the Frequency of Surveillance Prostate Biopsies.

PURPOSE: Prospective studies are lacking in assessing the diagnostic utility of serial multiparametric magnetic resonance imaging to predict biopsy proven progression to clinically significant prostate cancer in men on active surveillance, as well as the oncologic safety of baseline magnetic resonance imaging and saturation diagnostic biopsy in replacing early confirmatory biopsy during active surveillance. MATERIALS AND METHODS: A total of 172 men were enrolled in this single arm prospective trial. Men with cT2 or lower histologically proven prostate cancer (Gleason 3+3=6 or Gleason 3+4=7 with 10% or less Gleason pattern 4 overall and less than 2 cores Gleason pattern 4) eligible for surveillance were included in the study. Men underwent baseline multiparametric magnetic resonance imaging and saturation biopsy followed by serial annual multiparametric magnetic resonance imaging until a 3-year end point per protocol saturation biopsy. The standardized 1-year confirmatory biopsy was omitted and biopsies during the protocol were triggered based on new abnormalities on multiparametric magnetic resonance imaging and prostate specific antigen density. RESULTS: We report the prespecified interim analysis of the first 100 men at 3 years. At baseline the median age was 64.5 (IQR 57.25-69) years, prostate specific antigen was 4.7 ng/ml (IQR 3.4-6.6), 91% had Gleason 3+3=6 prostate cancer and multiparametric magnetic resonance imaging was negative (Prostate Imaging Reporting and Data System 1/2/3) in 87% of men. Within 3 years 21% experienced pathological progression. The positive predictive value, negative predictive value, sensitivity and specificity for detection of clinically significant prostate cancer by surveillance multiparametric magnetic resonance imaging was 45%, 89%, 61% and 80%, respectively. Positive surveillance magnetic resonance imaging (p=0.002) and prostate specific antigen density greater than 0.2 ng/ml (p=0.042) had significant predictive value for clinically significant prostate cancer. CONCLUSIONS: Our novel active surveillance protocol incorporating multiparametric magnetic resonance imaging detected most cases of disease progression and may enable confirmatory biopsy to be deferred, but should not replace 3-year surveillance biopsy altogether due to occasional magnetic resonance imaging invisible tumors.