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PURPOSE: Defining prostate cancer contours is a complex task, undermining the efficacy of interventions such as focal therapy. A multireader multicase study compared physicians' performance using artificial intelligence (AI) vs standard-of-care methods for tumor delineation. MATERIALS AND METHODS: Cases were interpreted by 7 urologists and 3 radiologists from 5 institutions with 2 to 23 years of experience. Each reader evaluated 50 prostatectomy cases retrospectively eligible for focal therapy. Each case included a T2-weighted MRI, contours of the prostate and region(s) of interest suspicious for cancer, and a biopsy report. First, readers defined cancer contours cognitively, manually delineating tumor boundaries to encapsulate all clinically significant disease. Then, after ≥ 4 weeks, readers contoured the same cases using AI software. Using tumor boundaries on whole-mount histopathology slides as ground truth, AI-assisted, cognitively-defined, and hemigland cancer contours were evaluated. Primary outcome measures were the accuracy and negative margin rate of cancer contours. All statistical analyses were performed using generalized estimating equations. RESULTS: The balanced accuracy (mean of voxel-wise sensitivity and specificity) of AI-assisted cancer contours (84.7%) was superior to cognitively-defined (67.2%) and hemigland contours (75.9%; P < .0001). Cognitively-defined cancer contours systematically underestimated cancer extent, with a negative margin rate of 1.6% compared to 72.8% for AI-assisted cancer contours (P < .0001). CONCLUSIONS: AI-assisted cancer contours reduce underestimation of prostate cancer extent, significantly improving contouring accuracy and negative margin rate achieved by physicians. This technology can potentially improve outcomes, as accurate contouring informs patient management strategy and underpins the oncologic efficacy of treatment.

Prostate biopsy and image-guided treatment procedures are often performed under the guidance of ultrasound fused with magnetic resonance images (MRI). Accurate image fusion relies on accurate segmentation of the prostate on ultrasound images. Yet, the reduced signal-to-noise ratio and artifacts (e.g., speckle and shadowing) in ultrasound images limit the performance of automated prostate segmentation techniques and generalizing these methods to new image domains is inherently difficult. In this study, we address these challenges by introducing a novel 2.5D deep neural network for prostate segmentation on ultrasound images. Our approach addresses the limitations of transfer learning and finetuning methods (i.e., drop in performance on the original training data when the model weights are updated) by combining a supervised domain adaptation technique and a knowledge distillation loss. The knowledge distillation loss allows the preservation of previously learned knowledge and reduces the performance drop after model finetuning on new datasets. Furthermore, our approach relies on an attention module that considers model feature positioning information to improve the segmentation accuracy. We trained our model on 764 subjects from one institution and finetuned our model using only ten subjects from subsequent institutions. We analyzed the performance of our method on three large datasets encompassing 2067 subjects from three different institutions. Our method achieved an average Dice Similarity Coefficient (Dice) of 94.0±0.03 and Hausdorff Distance (HD95) of 2.28 mm in an independent set of subjects from the first institution. Moreover, our model generalized well in the studies from the other two institutions (Dice: 91.0±0.03; HD95: 3.7 mm and Dice: 82.0±0.03; HD95: 7.1 mm). We introduced an approach that successfully segmented the prostate on ultrasound images in a multi-center study, suggesting its clinical potential to facilitate the accurate fusion of ultrasound and MRI images to drive biopsy and image-guided treatments.

ObjectivesTo create reliable predictive metrics of unilateral disease using spatial tracking from a fusion device, thereby improving patient selection for hemi-gland ablation of prostate cancer.Patients and methodsWe identified patients who received magnetic resonance imaging (MRI)/ultrasound-guided biopsy and radical prostatectomy at a single institution between 2011 and 2018. In addition to standard clinical features, we extracted quantitative features related to biopsy core and MRI target locations predictive of tumour unilaterality. Classification and Regression Tree (CART) analysis was used to create a decision tree (DT) for identifying cancer laterality. We evaluated concordance of model-determined laterality with final surgical pathology.ResultsA total of 173 patients were identified with biopsy coordinates and surgical pathology available. Based on CART analysis, in addition to biopsy- and MRI-confirmed disease unilaterality, patients should be further screened for cancer detected within 7 mm of midline in a 40 mL prostate, which equates to the central third of any-sized prostate by radius. The area under the curve for this DT was 0.82. Standard diagnostics and the DT correctly identified disease laterality in 73% and 80% of patients, respectively (P = 0.13). Of the patients identified as unilateral by standard diagnostics, 47% had undetected contralateral disease or were otherwise incorrectly identified. This error rate was reduced to 17% (P = 0.01) with the DT.ConclusionUsing spatial tracking from fusion devices, a DT was more reliable for identifying laterality of prostate cancer compared to standard diagnostics. Patients with cancer detected within the central third of the prostate by radius are poor hemi-gland ablation candidates due to the risk of midline extension of tumour.

ObjectiveThis investigation was performed to evaluate the registration accuracy between magnetic resonance imaging (MRI) and pathology using three-dimensional (3-D) printed molds.MethodsTissue-mimicking prostate phantoms were manufactured with embedded fiducials. The fiducials were used to measure and compare target registration error (TRE) between phantoms that were sliced by hand versus phantoms that were sliced within 3-D-printed molds. Subsequently, ten radical prostatectomy specimens were placed inside molds, scanned with MRI, and then sliced. The ex vivo scan was used to assess the true location of whole mount (WM) slides relative to in vivo MRI. The TRE between WM and in vivo MRI was measured using anatomic landmarks.ResultsManually sliced phantoms had a 4.1-mm mean TRE, whereas mold-sliced phantoms had a 1.9-mm mean TRE. Similarly, mold-assisted slicing reduced mean angular misalignment around the left-right (LR) anatomic axis from 10.7° to 4.5°. However, ex vivo MRI revealed that excised prostates were misaligned within molds, including a mean 14° rotation about the LR axis. The mean in-plane TRE was 3.3 mm using molds alone and 2.2 mm after registration was corrected with ex vivo MRI.ConclusionPatient-specific molds improved accuracy relative to manual slicing techniques in a phantom model. However, the registration accuracy of surgically resected specimens was limited by their imperfect fit within molds. This limitation can be overcome with the addition of ex vivo imaging.SignificanceThe accuracy of 3-D-printed molds was characterized, quantifying their utility for facilitating MRI-pathology registration.

PurposeWe assessed focal therapy eligibility in men who underwent multiparametric magnetic resonance imaging and targeted biopsy with correlation to whole mount histology after radical prostatectomy.Materials and methodsSubjects were selected from among the 454 men in whom targeted biopsy proven prostate cancer was derived from regions of interest on multiparametric magnetic resonance imaging from 2010 to 2016. Focal therapy eligibility was limited to a maximum Gleason score of 4 + 3 in regions of interest with or without other foci of low risk prostate cancer (Gleason score 3 + 3 and less than 4 mm). Men who did not meet NCCN® intermediate risk criteria were classified as ineligible for focal therapy. Of the 454 men 64 underwent radical prostatectomy and biopsy findings were compared to final pathology findings.ResultsOf the 454 men with a biopsy proven region of interest 175 (38.5%) were eligible for focal therapy. Fusion biopsy, which combined targeted and template biopsy, had 80.0% sensitivity (12 of 15 cases), 73.5% specificity (36 of 49) and 75.0% accuracy (48 of 64) for focal therapy eligibility. Targeted cores alone yielded 73.3% sensitivity (11 of 15 cases), 47.9% specificity (23 of 48) and 54.7% accuracy (35 of 64). Gleason score and extension across the midline differed in 4 and 9, respectively, of the 13 cases that showed discordant biopsy and whole mount histology.ConclusionsUsing intermediate risk eligibility criteria more than a third of men with a targeted biopsy proven lesion identified on multiparametric magnetic resonance imaging would have been eligible for focal therapy. Eligibility determined by fusion biopsy was concordant with whole mount histology in 75% of cases. Improved selection criteria are needed to reliably determine focal therapy eligibility.

PurposeWe compared the upgrading rate obtained by resampling precise spots of prostate cancer (tracking biopsy) vs conventional systematic resampling during followup of men on active surveillance.Materials and methodsFrom 2009 to 2017 in 352 men prostate cancer was Gleason 3 + 3 in 268 and Gleason 3 + 4 in 84 at initial magnetic resonance imaging-ultrasound fusion biopsy. These men subsequently underwent a second fusion biopsy. At the first biopsy session all men underwent 12-core systematic biopsies and, when magnetic resonance imaging visible lesions were present, targeted biopsies. All cancerous sites were recorded electronically. During active surveillance at a second fusion biopsy session 6 to 18 months later tracking and systematic nontracking samples were obtained. The primary outcome measure was an increase in Gleason score (upgrading) at followup sampling, which was stratified by biopsy method.ResultsOverall 91 of the 352 men (25.9%) experienced upgrading at the second biopsy during a median 11-month interval. The upgrade rate in the Gleason 3 + 3 and 3 + 4 groups was 26.9% and 22.6%, respectively. The mean number of cores taken at second biopsy was 12.2 ± 3.3 in men with upgrading and 12.4 ± 4.1 in those who remained stable (p not significant). Men with grade 0 to 4 magnetic resonance imaging targets were all upgraded at approximately the same rate of 20% to 30% (p not significant). However, 58.8% of the men with grade 5 magnetic resonance imaging targets were upgraded. Of the 91 upgrades 48 (53%) were detected only by tracking.ConclusionsThe tracking function of magnetic resonance imaging-ultrasound fusion biopsy warrants further study. When specific sites are resampled in men undergoing active surveillance of prostate cancer, upgrading is detected more often than by nontracking biopsy.

ObjectiveThe objective of our study was to determine the clinical and MRI characteristics of clinically significant prostate cancer (PCA) (Gleason score ≥ 3 + 4) in men with Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) category 3 transition zone (TZ) lesions.Materials and methodsFrom 2014 to 2016, 865 men underwent prostate MRI and MRI/ultrasound (US) fusion biopsy (FB). A subset of 90 FB-naïve men with 96 PI-RADSv2 category 3 TZ lesions was identified. Patients were imaged at 3 T using a body coil. Images were assigned a PI-RADSv2 category by an experienced radiologist. Using clinical data and imaging features, we performed univariate and multivariate analyses to identify predictors of clinically significant PCA.ResultsThe mean patient age was 66 years, and the mean prostate-specific antigen density (PSAD) was 0.13 ng/mL2. PCA was detected in 34 of 96 (35%) lesions, 14 of which (15%) harbored clinically significant PCA. In univariate analysis, DWI score, prostate volume, and PSAD were significant predictors (p < 0.05) of clinically significant PCA with a suggested significance for apparent diffusion coefficient (ADC) and prostate-specific antigen value (p < 0.10). On multivariate analysis, PSAD and lesion ADC were the most important covariates. The combination of both PSAD of 0.15 ng/mL2 or greater and an ADC value of less than 1000 mm2/s yielded an AUC of 0.91 for clinically significant PCA (p < 0.001). If FB had been restricted to these criteria, only 10 of 90 men would have undergone biopsy, resulting in diagnosis of clinically significant PCA in 60% with eight men (9%) misdiagnosed (false-negative).ConclusionThe yield of FB in men with PI-RADSv2 category 3 TZ lesions for clinically significant PCA is 15% but significantly improves to 60% (AUC > 0.9) among men with PSAD of 0.15 ng/mL2 or greater and lesion ADC value of less than 1000 mm2/s.

Prostate specific membrane antigen (PSMA) scanning is a sensitive method of prostate cancer detection. In a 71 y.o. man with a PSA of 49 (6%F), 4 negative MRI studies and 6 negative biopsies over an 8 year interval, a 68Ga-PSMA PET/CT scan showed a PSMA-avid spot in the prostate. Using image fusion technology, the lesion was target-biopsied and Gleason 3 + 4 = 7 (cancer core length of 12 mm) was identified. This case may herald a new application for PSMA scanning and prostate cancer imaging.

PurposeWe sought to determine the rate of upgrading to Gleason score 4 + 3 or greater using targeted biopsy for diagnosis and monitoring in men undergoing active surveillance of prostate cancer.Materials and methodsStudy subjects comprised all 259 men, including 196 with Gleason score 3 + 3 and 63 with Gleason score 3 + 4, who were diagnosed by magnetic resonance imaging/ultrasound fusion guided biopsy from 2009 to 2015 and underwent subsequent fusion biopsy for as long as 4 years of active surveillance. The primary end point was the discovery of Gleason score 4 + 3 or greater prostate cancer. Followup biopsies included targeting of positive sites, which were tracked in an Artemis™ device. Kaplan-Meier curves were generated to determine upgrading rates, stratified by initial Gleason score and prostate specific antigen density.ResultsBased on a Cox proportional hazard model, men with Gleason score 3 + 4 were 4.65 times more likely to have upgrading than men with an initial Gleason score of 3 + 3 at 3 years (p

Purpose: To determine whether MRI/ultrasound (MRI/US) fusion biopsy facilitates longitudinal resampling of the same clonal focus of prostate cancer and to determine whether high-grade cancers can evolve from low-grade clones.Experimental Design: All men on active surveillance who underwent tracking MRI/US fusion biopsy of Gleason 6 prostate cancer, on at least two distinct occasions, between 2012 and 2014 were enrolled. MRI/US fusion was used to track and resample specific cancer foci. IHC for ERG and targeted RNA/DNA next-generation sequencing (NGS) were performed on formalin-fixed paraffin-embedded prostate biopsy specimens to assess clonality.Results: Thirty-one men with median age and PSA of 65 years and 4.6 ng/mL, respectively, were analyzed. The median sampling interval was 12 months (range, 5-35). Of the 26 evaluable men, ERG IHC concordance was found between initial and repeat biopsies in 25 (96%), indicating resampling of the same clonal focus over time. Targeted NGS supported ERG IHC results and identified unique and shared driving mutations, such as IDH1 and SPOP, in paired specimens. Of the nine men (34.6%) who were found to have Gleason ≥7 on repeat biopsy, all displayed temporal ERG concordance. Prioritized genetic alterations were detected in 50% (13/26) of paired samples. Oncogenic mutations were detected in 22% (2/9) of Gleason 6 cancers prior to progression and 44% (4/9) of Gleason ≥7 cancers when progression occurred.Conclusions: Precise tracking of prostate cancer foci via MRI/US fusion biopsy allowed subsequent resampling of the same clonal focus of cancer over time. Further research is needed to clarify the grade progression potential of Gleason 6 prostate cancer. Clin Cancer Res; 23(4); 985-91. ©2016 AACR.

PurposeWe evaluated the accuracy of magnetic resonance imaging in determining the size and shape of localized prostate cancer.Materials and methodsThe subjects were 114 men who underwent multiparametric magnetic resonance imaging before radical prostatectomy with patient specific mold processing of the specimen from 2013 to 2015. T2-weighted images were used to contour the prostate capsule and cancer suspicious regions of interest. The contours were used to design and print 3-dimensional custom molds, which permitted alignment of excised prostates with magnetic resonance imaging scans. Tumors were reconstructed in 3 dimensions from digitized whole mount sections. Tumors were then matched with regions of interest and the relative geometries were compared.ResultsOf the 222 tumors evident on whole mount sections 118 had been identified on magnetic resonance imaging. For the 118 regions of interest mean volume was 0.8 cc and the longest 3-dimensional diameter was 17 mm. However, for matched pathological tumors, of which most were Gleason score 3 + 4 or greater, mean volume was 2.5 cc and the longest 3-dimensional diameter was 28 mm. The median tumor had a 13.5 mm maximal extent beyond the magnetic resonance imaging contour and 80% of cancer volume from matched tumors was outside region of interest boundaries. Size estimation was most accurate in the axial plane and least accurate along the base-apex axis.ConclusionsMagnetic resonance imaging consistently underestimates the size and extent of prostate tumors. Prostate cancer foci had an average diameter 11 mm longer and a volume 3 times greater than T2-weighted magnetic resonance imaging segmentations. These results may have important implications for the assessment and treatment of prostate cancer.

PurposeWe assessed whether changes in serial multiparametric magnetic resonance imaging can help predict the pathological progression of prostate cancer in men on active surveillance.Materials and methodsA retrospective cohort study was conducted of 49 consecutive men with Gleason 6 prostate cancer who underwent multiparametric magnetic resonance imaging at baseline and again more than 6 months later, each followed by a targeted prostate biopsy, between January 2011 and May 2015. We evaluated whether progression on multiparametric magnetic resonance imaging (an increase in index lesion suspicion score, increase in index lesion volume or decrease in index lesion apparent diffusion coefficient) could predict pathological progression (Gleason 3 + 4 or greater on subsequent biopsy, in systematic or targeted cores). Diagnostic performance of multiparametric magnetic resonance imaging was determined with and without clinical data using a binary logistic regression model.ResultsThe mean interval between baseline and followup multiparametric magnetic resonance imaging was 28.3 months (range 11 to 43). Pathological progression occurred in 19 patients (39%). The sensitivity, specificity, positive predictive value and negative predictive value of multiparametric magnetic resonance imaging was 37%, 90%, 69% and 70%, respectively. Area under the receiver operating characteristic curve was 0.63. A logistic regression model using clinical information (maximum cancer core length greater than 3 mm on baseline biopsy or a prostate specific antigen density greater than 0.15 ng/ml(2) at followup biopsy) had an AUC of 0.87 for predicting pathological progression. The addition of serial multiparametric magnetic resonance imaging data significantly improved the AUC to 0.91 (p=0.044).ConclusionsSerial multiparametric magnetic resonance imaging adds incremental value to prostate specific antigen density and baseline cancer core length for predicting Gleason 6 upgrading in men on active surveillance.

BackgroundThe current study was conducted to evaluate the performance of magnetic resonance (MR)-ultrasound-guided fusion biopsy in diagnosing clinically significant prostate cancer (csCaP).MethodsA total of 1042 men underwent multiparametric MR imaging (mpMRI) and fusion biopsy consecutively in a prospective trial (2009-2014). An expert reader graded mpMRI regions of interest (ROIs) as 1 to 5 using published protocols. The fusion biopsy device was used to obtain targeted cores from ROIs (when present) followed by a fusion image-guided, 12-core systematic biopsy in all men, even if no suspicious ROI was noted. The primary endpoint of the study was the detection of csCaP (ie, Gleason score ≥ 7).ResultsAmong 825 men with ≥ 1 suspicious ROI of ≥ grade 3, 289 (35%) were found to have csCaP. Powerful predictors of csCaP were ROI grade (grade 5 vs grade 3: odds ratio, 6.5 [P

Lessons learned during a 6-year experience with more than 1200 patients undergoing targeted prostate biopsy via MRI/ultrasound fusion are reported: (1) the procedure is safe and efficient, requiring some 15-20 minutes in an office setting; (2) MRI is best performed by a radiologist with specialized training, using a transabdominal multiparametric approach and preferably a 3T magnet; (3) grade of MRI suspicion is the most powerful predictor of biopsy results, eg, Grade 5 usually represents cancer; (4) some potentially important cancers (15%-30%) are MRI-invisible; (5) Targeted biopsies provide >80% concordance with whole-organ pathology. Early enthusiasm notwithstanding, cost-effectiveness is yet to be resolved, and the technologies remain in evolution.

PurposeWe explored the impact of magnetic resonance imaging-ultrasound fusion prostate biopsy on the prediction of final surgical pathology.Materials and methodsA total of 54 consecutive men undergoing radical prostatectomy at UCLA after fusion biopsy were included in this prospective, institutional review board approved pilot study. Using magnetic resonance imaging-ultrasound fusion, tissue was obtained from a 12-point systematic grid (mapping biopsy) and from regions of interest detected by multiparametric magnetic resonance imaging (targeted biopsy). A single radiologist read all magnetic resonance imaging, and a single pathologist independently rereviewed all biopsy and whole mount pathology, blinded to prior interpretation and matched specimen. Gleason score concordance between biopsy and prostatectomy was the primary end point.ResultsMean patient age was 62 years and median prostate specific antigen was 6.2 ng/ml. Final Gleason score at prostatectomy was 6 (13%), 7 (70%) and 8-9 (17%). A tertiary pattern was detected in 17 (31%) men. Of 45 high suspicion (image grade 4-5) magnetic resonance imaging targets 32 (71%) contained prostate cancer. The per core cancer detection rate was 20% by systematic mapping biopsy and 42% by targeted biopsy. The highest Gleason pattern at prostatectomy was detected by systematic mapping biopsy in 54%, targeted biopsy in 54% and a combination in 81% of cases. Overall 17% of cases were upgraded from fusion biopsy to final pathology and 1 (2%) was downgraded. The combination of targeted biopsy and systematic mapping biopsy was needed to obtain the best predictive accuracy.ConclusionsIn this pilot study magnetic resonance imaging-ultrasound fusion biopsy allowed for the prediction of final prostate pathology with greater accuracy than that reported previously using conventional methods (81% vs 40% to 65%). If confirmed, these results will have important clinical implications.

ObjectivesTargeted biopsy, using magnetic resonance (MR)-ultrasound (US) fusion, may allow tracking of specific cancer sites in the prostate. We aimed to evaluate the initial use of the technique to follow tumor sites in men on active surveillance of prostate cancer.Methods and materialsA total of 53 men with prostate cancer (all T1c category) underwent rebiopsy of 74 positive biopsy sites, which were tracked and targeted using the Artemis MR-US fusion device (Eigen, Grass Valley, CA) from March 2010 through January 2013. The initial biopsy included 12 cores from a standard template (mapped by software) and directed biopsies from regions of interest seen on MR imaging (MRI). In the repeat biopsy, samples were taken from sites containing cancer at the initial biopsy. Outcomes of interest at second MR-US biopsy included (a) presence of any cancer and (b) presence of clinically significant cancer.ResultsAll cancers on initial biopsy had either Gleason score 3+3 = 6 (n = 63) or 3+4 = 7 (n = 11). At initial biopsy, 23 cancers were within an MRI target, and 51 were found on systematic biopsy. Cancer detection rate on repeat biopsy (29/74, 39%) was independent of Gleason score on initial biopsy (P = not significant) but directly related to initial cancer core length (P

Purpose: Established in 1994, the Epstein histological criteria (Gleason score 6 or less, 2 or fewer cores positive and 50% or less of any core) have been widely used to select men for active surveillance. However, with the advent of targeted biopsy, which may be more accurate than conventional biopsy, we reevaluated the likelihood of reclassification upon confirmatory rebiopsy using multiparametric magnetic resonance imaging-ultrasound fusion. Materials and Methods: We identified 113 men enrolled in active surveillance at our institution who met Epstein criteria and subsequently underwent confirmatory targeted biopsy via multiparametric magnetic resonance imaging-ultrasound fusion. Median patient age was 64 years, median prostate specific antigen was 4.2 ng/ml and median prostate volume was 46.8 cc. Targets or regions of interest on multiparametric magnetic resonance imaging-ultrasound fusion were graded by suspicion level and biopsied at 3 mm intervals along the longest axis (median 10.5 mm). Also, 12 systematic cores were obtained during confirmatory rebiopsy. Our reporting is consistent with START (Standards of Reporting for MRI-targeted Biopsy Studies) criteria. Results: Confirmatory fusion biopsy resulted in reclassification in 41 men (36%), including 26 (23%) due to Gleason grade 6 or greater and 15 (13%) due to high volume Gleason 6 disease. When stratified by suspicion on multiparametric magnetic resonance imaging-ultrasound fusion, the likelihood of reclassification was 24% to 29% for target grade 0 to 3, 45% for grade 4 and 100% for grade 5 (p = 0.001). Men with grade 4 and 5 vs lower grade targets were greater than 3 times more likely to be reclassified (OR 3.2, 95% CI 1.4-7.1, p = 0.006). Conclusions: Upon confirmatory rebiopsy using multiparametric magnetic resonance imaging-ultrasound fusion men with high suspicion targets on imaging were reclassified 45% to 100% of the time. Criteria for active surveillance should be reevaluated when multiparametric magnetic resonance imaging-ultrasound fusion guided prostate biopsy is used. © 2014 American Urological Association Education and Research, Inc.

ObjectiveTo determine whether multiparametric magnetic resonance imaging might improve the identification of patients with higher risk disease at diagnosis and thereby reduce the incidence of undergrading or understaging.MethodsWe retrospectively reviewed the clinical records of 115 patients who underwent multiparametric magnetic resonance imaging before radical prostatectomy. We used Epstein's criteria of insignificant disease with and without a magnetic resonance imaging (MRI) parameter (apparent diffusion coefficient) to calculate sensitivity, specificity, as well as negative and positive predictive values [NPV and PPV] across varying definitions of clinically significant cancer based on Gleason grade and tumor volume (0.2 mL, 0.5 mL, and 1.3 mL) on whole-mount prostate specimens. Logistic regression analysis was performed to determine the incremental benefit of MRI in delineating significant cancer.ResultsThe majority had a prostate-specific antigen from 4.1-10.0 (67%), normal rectal examinations (90%), biopsy Gleason score ≤ 6 (68%), and ≤ 2 cores positive (55%). Of the 58 patients pathologically staged with Gleason 7 or pT3 disease at prostatectomy, Epstein's criteria alone missed 12 patients (sensitivity of 79% and NPV of 68%). Addition of apparent diffusion coefficient improved the sensitivity and NPV for predicting significant disease at prostatectomy to 93% and 84%, respectively. MRI improved detection of large Gleason 6 (≥ 1.3 mL, P = .006) or Gleason ≥ 7 lesions of any size (P

We have developed a system for evaluating magnetic resonance imaging of prostate cancer, using patient-specific 3D printed molds to facilitate MR-histology correlation. Prior to radical prostatectomy a patient receives a multiparametric MRI, which an expert genitourinary radiologist uses to identify and contour regions suspicious for disease. The same MR series is used to generate a prostate contour, which is the basis for design of a patient-specific mold. The 3D printed mold contains a series of evenly spaced parallel slits, each of which corresponds to a known MRI slice. After surgery, the patient's specimen is enclosed within the mold, and all whole-mount levels are obtained simultaneously through use of a multi-bladed slicing device. The levels are then formalin fixed, processed, and delivered to an expert pathologist, who identifies and grades all lesions within the slides. Finally, the lesion contours are loaded into custom software, which elastically warps them to fit the MR prostate contour. The suspicious regions on MR can then be directly compared to lesions on histology. Furthermore, the false-negative and false-positive regions on MR can be retrospectively examined, with the ultimate goal of developing methods for improving the predictive accuracy of MRI. This work presents the details of our analysis method, following a patient from diagnosis through the MR-histology correlation process. For this patient MRI successfully predicted the presence of cancer, but true lesion volume and extent were underestimated. Most cancer-positive regions missed on MR were observed to have patterns of low T2 signal, suggesting that there is potential to improve sensitivity.

OBJECTIVES: Robot-assisted radical prostatectomy (RARP) has now become the most common surgical treatment option for prostate cancer (CaP). Clinicopathologic data (i.e., biopsy, digital rectal exam, prostate specific antigen level) and patient-specific factors (e.g., age, erectile function, co-morbidities) are the primary sources of information that urologists use for counseling and treatment decision making. Magnetic resonance imaging (MRI) has evolved along a similar temporal arc to RARP, with increased utilization and precision over the past decade. MRI prior to RARP provides multifaceted adjunctive information, including enhancement of locoregional staging, delineation of spatial anatomic information, and identification of aberrant anatomy, all of which aid in patient treatment counseling and operative planning. This article is designed for urologic surgeons who perform RARP, with the aim of providing a review of prostate MRI imaging and highlighting findings which may specifically alter the operation. METHODS AND MATERIALS: A review of the literature was performed, focusing on the most recent publications. RESULTS: MRI imaging of the prostate has become increasing accurate for the identification, localization, and characterization of CaP lesions. In addition to tumor-specific information, a number of intra- and extra-prostatic findings are consistently identified on MRI which may impact RARP. CONCLUSIONS: MRI provides important information which may alter RARP.

Robots ultrasound (RUS) can be defined as the combination of ultrasound imaging with a robotic system in medical interventions. With their potential for high precision, dexterity, and repeatability, robots are often uniquely suited for ultrasound integration. Although the field is relatively young, it has already generated a multitude of robotic systems for application in dozens of medical procedures. This paper reviews the robotic ultrasound systems that have been developed over the past two decades and describes their potential impact on modern medicine. The RUS projects reviewed include extracorporeal devices, needle guidance systems, and intraoperative systems. [ABSTRACT FROM AUTHOR]