Search

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.

BackgroundMen with grade group 2 or 3 prostate cancer are often considered ineligible for active surveillance; some patients with grade group 2 prostate cancer who are managed with active surveillance will have early disease progression requiring radical therapy. This study aimed to investigate whether MRI-guided focused ultrasound focal therapy can safely reduce treatment burden for patients with localised grade group 2 or 3 intermediate-risk prostate cancer.MethodsIn this single-arm, multicentre, phase 2b study conducted at eight health-care centres in the USA, we recruited men aged 50 years and older with unilateral, MRI-visible, primary, intermediate-risk, previously untreated prostate adenocarcinoma (prostate-specific antigen ≤20 ng/mL, grade group 2 or 3; tumour classification ≤T2) confirmed on combined biopsy (combining MRI-targeted and systematic biopsies). MRI-guided focused ultrasound energy, sequentially titrated to temperatures sufficient for tissue ablation (about 60-70°C), was delivered to the index lesion and a planned margin of 5 mm or more of normal tissue, using real-time magnetic resonance thermometry for intraoperative monitoring. Co-primary outcomes were oncological outcomes (absence of grade group 2 and higher cancer in the treated area at 6-month and 24-month combined biopsy; when 24-month biopsy data were not available and grade group 2 or higher cancer had occurred in the treated area at 6 months, the 6-month biopsy results were included in the final analysis) and safety (adverse events up to 24 months) in all patients enrolled in the study. This study is registered with ClinicalTrials.gov, NCT01657942, and is no longer recruiting.FindingsBetween May 4, 2017, and Dec 21, 2018, we assessed 194 patients for eligibility and treated 101 patients with MRI-guided focused ultrasound. Median age was 63 years (IQR 58-67) and median concentration of prostate-specific antigen was 5·7 ng/mL (IQR 4·2-7·5). Most cancers were grade group 2 (79 [78%] of 101). At 24 months, 78 (88% [95% CI 79-94]) of 89 men had no evidence of grade group 2 or higher prostate cancer in the treated area. No grade 4 or grade 5 treatment-related adverse events were reported, and only one grade 3 adverse event (urinary tract infection) was reported. There were no treatment-related deaths.Interpretation24-month biopsy outcomes show that MRI-guided focused ultrasound focal therapy is safe and effectively treats grade group 2 or 3 prostate cancer. These results support focal therapy for select patients and its use in comparative trials to determine if a tissue-preserving approach is effective in delaying or eliminating the need for radical whole-gland treatment in the long term.FundingInsightec and the National Cancer Institute.

To evaluate the performance of computed high b value diffusion-weighted images (DWI) in prostate cancer detection. 97 consecutive patients who had undergone multiparametric MRI of the prostate followed by biopsy were reviewed. Five radiologists independently scored 138 lesions on native high b-value images (b = 1200 s/mm2), apparent diffusion coefficient (ADC) maps, and computed high b-value images (contrast equivalent to b = 2000 s/mm2) to compare their diagnostic accuracy. Receiver operating characteristic (ROC) analysis and McNemar's test were performed to assess the relative performance of computed high b value DWI, native high b-value DWI and ADC maps. No significant difference existed in the area under the curve (AUC) for ROCs comparing B1200 (b = 1200 s/mm2) to computed B2000 (c-B2000) in 5 readers. In 4 of 5 readers c-B2000 had significantly increased sensitivity and/or decreased specificity compared to B1200 (McNemar's p

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Prostate Cancer Early Detection provide recommendations for prostate cancer screening in healthy men who have elected to participate in an early detection program. The NCCN Guidelines focus on minimizing unnecessary procedures and limiting the detection of indolent disease. These NCCN Guidelines Insights summarize the NCCN Prostate Cancer Early Detection Panel's most significant discussions for the 2016 guideline update, which included issues surrounding screening in high-risk populations (ie, African Americans, BRCA1/2 mutation carriers), approaches to refine patient selection for initial and repeat biopsies, and approaches to improve biopsy specificity.

PurposeGleason 6 (3+3) is the most commonly diagnosed prostate cancer among men with prostate specific antigen screening, the most histologically well differentiated and is associated with the most favorable prognosis. Despite its prevalence, considerable debate exists regarding the genetic features, clinical significance, natural history, metastatic potential and optimal management.Materials and methodsMembers of the Young Urologic Oncologists in the Society of Urologic Oncology cooperated in a comprehensive search of the peer reviewed English medical literature on Gleason 6 prostate cancer, specifically focusing on the history of the Gleason scoring system, histological features, clinical characteristics, practice patterns and outcomes.ResultsThe Gleason scoring system was devised in the early 1960s, widely adopted by 1987 and revised in 2005 with a more restrictive definition of Gleason 6 disease. There is near consensus that Gleason 6 meets pathological definitions of cancer, but controversy about whether it meets commonly accepted molecular and genetic criteria of cancer. Multiple clinical series suggest that the metastatic potential of contemporary Gleason 6 disease is negligible but not zero. Population based studies in the U.S. suggest that more than 90% of men newly diagnosed with prostate cancer undergo treatment and are exposed to the risk of morbidity for a cancer unlikely to cause symptoms or decrease life expectancy. Efforts have been proposed to minimize the number of men diagnosed with or treated for Gleason 6 prostate cancer. These include modifications to prostate specific antigen based screening strategies such as targeting high risk populations, decreasing the frequency of screening, recommending screening cessation, incorporating remaining life expectancy estimates, using shared decision making and novel biomarkers, and eliminating prostate specific antigen screening entirely. Large nonrandomized and randomized studies have shown that active surveillance is an effective management strategy for men with Gleason 6 disease. Active surveillance dramatically reduces the number of men undergoing treatment without apparent compromise of cancer related outcomes.ConclusionsThe definition and clinical relevance of Gleason 6 prostate cancer have changed substantially since its introduction nearly 50 years ago. A high proportion of screen detected cancers are Gleason 6 and the metastatic potential is negligible. Dramatically reducing the diagnosis and treatment of Gleason 6 disease is likely to have a favorable impact on the net benefit of prostate cancer screening.

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

Recent advances in multiparametric magnetic resonance imaging (MRI) have enabled image-guided detection of prostate cancer. Fusion of MRI with real-time ultrasound (US) allows the information from MRI to be used to direct biopsy needles under US guidance in an office-based procedure. Fusion can be performed either cognitively or electronically, using a fusion device. Fusion devices allow superimposition (coregistration) of stored MRI images on real-time US images; areas of suspicion found on MRI can then serve as targets during US-guided biopsy. Currently available fusion devices use a variety of technologies to perform coregistration: robotic tracking via a mechanical arm with built-in encoders (Artemis/Eigen, BioJet/Geoscan); electromagnetic tracking (UroNav/Philips-Invivo, Hi-RVS/Hitachi); or tracking with a 3D US probe (Urostation/Koelis). Targeted fusion biopsy has been shown to identify more clinically significant cancers and fewer insignificant cancers than conventional biopsy. Fusion biopsy appears to be a major advancement over conventional biopsy because it allows (1) direct targeting of suspicious areas not seen on US and (2) follow-up biopsy of specific cancerous sites in men undergoing active surveillance.

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

• When considering high intensity focused ultrasound (HIFU) ablation therapies, patients marginally prioritized urinary incontinence (UI) over prostate biopsy outcomes, and erectile dysfunction (ED) was the least important outcome. • Patients are willing to accept increased risk of ED or UI to obtain an increased chance of favorable biopsy outcome. • Results from this study may help inform development and evaluation of future HIFU ablation therapies. Food and Drug Administration must make decisions about emerging high intensity focused ultrasound (HIFU) devices that may lack relevant clinical oncologic data but present with known side effects. This study aims to capture patients' perspective by quantifying their preferences regarding the available benefit and important side effects associated with HIFU for localized prostate cancer. Preferences for HIFU outcomes were examined using a discrete choice experiment survey. Participants were asked to choose a preferred treatment option in 9 choice questions. Each included a pair of hypothetical treatment profiles that have similar attributes/outcomes with varying levels. Outcomes included prostate biopsy outcome and treatment-related risks of erectile dysfunction (ED) and urinary incontinence (UI). We calculated the maximum risk of side effect patients were willing to tolerate in exchange for increased benefit. Preferences were further explored via clinical and demographic data. About 223 subjects with a mean age of 64.8 years completed the survey. Respondents were willing to accept a 1.51%-point increase in new ED risk for a 1%-point increase in favorable biopsy outcome. They were also willing to accept a 0.93%-point increase in new UI risk for a 1%-point increase in biopsy outcome. Subjects who perceived their cancer to be more aggressive had higher risk tolerance for UI. Younger men were willing to tolerate less ED risk than older men. Respondents with greater than college level of education had a lower risk tolerance for ED or UI. Results may inform development and regulatory evaluation for future HIFU ablation devices by providing supplemental information from the patient perspective. Emerging high intensity focused ultrasound devices may lack relevant clinical oncologic data but present with known side effects. A discrete choice experiment showed that patients with localized prostate cancer were willing to accept increased treatment-related risk of erectile dysfunction or urinary incontinence to obtain increased chance of favorable biopsy outcome. Results may inform development and evaluation of future HIFU therapies. [ABSTRACT FROM AUTHOR]

Purpose: While multi‐parametric magnetic resonance imaging (MRI) shows great promise in assisting with prostate cancer diagnosis and localization, subtle differences in appearance between cancer and normal tissue lead to many false positive and false negative interpretations by radiologists. We sought to automatically detect aggressive cancer (Gleason pattern ≥ 4) and indolent cancer (Gleason pattern 3) on a per‐pixel basis on MRI to facilitate the targeting of aggressive cancer during biopsy. Methods: We created the Stanford Prostate Cancer Network (SPCNet), a convolutional neural network model, trained to distinguish between aggressive cancer, indolent cancer, and normal tissue on MRI. Ground truth cancer labels were obtained by registering MRI with whole‐mount digital histopathology images from patients who underwent radical prostatectomy. Before registration, these histopathology images were automatically annotated to show Gleason patterns on a per‐pixel basis. The model was trained on data from 78 patients who underwent radical prostatectomy and 24 patients without prostate cancer. The model was evaluated on a pixel and lesion level in 322 patients, including six patients with normal MRI and no cancer, 23 patients who underwent radical prostatectomy, and 293 patients who underwent biopsy. Moreover, we assessed the ability of our model to detect clinically significant cancer (lesions with an aggressive component) and compared it to the performance of radiologists. Results: Our model detected clinically significant lesions with an area under the receiver operator characteristics curve of 0.75 for radical prostatectomy patients and 0.80 for biopsy patients. Moreover, the model detected up to 18% of lesions missed by radiologists, and overall had a sensitivity and specificity that approached that of radiologists in detecting clinically significant cancer. Conclusions: Our SPCNet model accurately detected aggressive prostate cancer. Its performance approached that of radiologists, and it helped identify lesions otherwise missed by radiologists. Our model has the potential to assist physicians in specifically targeting the aggressive component of prostate cancers during biopsy or focal treatment. [ABSTRACT FROM AUTHOR]

Purpose: Magnetic resonance imaging (MRI) has great potential to improve prostate cancer diagnosis; however, subtle differences between cancer and confounding conditions render prostate MRI interpretation challenging. The tissue collected from patients who undergo radical prostatectomy provides a unique opportunity to correlate histopathology images of the prostate with preoperative MRI to accurately map the extent of cancer from histopathology images onto MRI. We seek to develop an open‐source, easy‐to‐use platform to align presurgical MRI and histopathology images of resected prostates in patients who underwent radical prostatectomy to create accurate cancer labels on MRI. Methods: Here, we introduce RAdiology Pathology Spatial Open‐Source multi‐Dimensional Integration (RAPSODI), the first open‐source framework for the registration of radiology and pathology images. RAPSODI relies on three steps. First, it creates a three‐dimensional (3D) reconstruction of the histopathology specimen as a digital representation of the tissue before gross sectioning. Second, RAPSODI registers corresponding histopathology and MRI slices. Third, the optimized transforms are applied to the cancer regions outlined on the histopathology images to project those labels onto the preoperative MRI. Results: We tested RAPSODI in a phantom study where we simulated various conditions, for example, tissue shrinkage during fixation. Our experiments showed that RAPSODI can reliably correct multiple artifacts. We also evaluated RAPSODI in 157 patients from three institutions that underwent radical prostatectomy and have very different pathology processing and scanning. RAPSODI was evaluated in 907 corresponding histpathology‐MRI slices and achieved a Dice coefficient of 0.97 ± 0.01 for the prostate, a Hausdorff distance of 1.99 ± 0.70 mm for the prostate boundary, a urethra deviation of 3.09 ± 1.45 mm, and a landmark deviation of 2.80 ± 0.59 mm between registered histopathology images and MRI. Conclusion: Our robust framework successfully mapped the extent of cancer from histopathology slices onto MRI providing labels from training machine learning methods to detect cancer on MRI. [ABSTRACT FROM AUTHOR]

Purpose After an initial negative biopsy there is an ongoing need for strategies to improve patient selection for repeat biopsy as well as the diagnostic yield from repeat biopsies. Materials and Methods As a collaborative initiative of the AUA (American Urological Association) and SAR (Society of Abdominal Radiology) Prostate Cancer Disease Focused Panel, an expert panel of urologists and radiologists conducted a literature review and formed consensus statements regarding the role of prostate magnetic resonance imaging and magnetic resonance imaging targeted biopsy in patients with a negative biopsy, which are summarized in this review. Results The panel recognizes that many options exist for men with a previously negative biopsy. If a biopsy is recommended, prostate magnetic resonance imaging and subsequent magnetic resonance imaging targeted cores appear to facilitate the detection of clinically significant disease over standardized repeat biopsy. Thus, when high quality prostate magnetic resonance imaging is available, it should be strongly considered for any patient with a prior negative biopsy who has persistent clinical suspicion for prostate cancer and who is under evaluation for a possible repeat biopsy. The decision of whether to perform magnetic resonance imaging in this setting must also take into account the results of any other biomarkers and the cost of the examination, as well as the availability of high quality prostate magnetic resonance imaging interpretation. If magnetic resonance imaging is done, it should be performed, interpreted and reported in accordance with PI-RADS version 2 (v2) guidelines. Experience of the reporting radiologist and biopsy operator are required to achieve optimal results and practices integrating prostate magnetic resonance imaging into patient care are advised to implement quality assurance programs to monitor targeted biopsy results. Conclusions Patients receiving a PI-RADS assessment category of 3 to 5 warrant repeat biopsy with image guided targeting. While transrectal ultrasound guided magnetic resonance imaging fusion or in-bore magnetic resonance imaging targeting may be valuable for more reliable targeting, especially for lesions that are small or in difficult locations, in the absence of such targeting technologies cognitive (visual) targeting remains a reasonable approach in skilled hands. At least 2 targeted cores should be obtained from each magnetic resonance imaging defined target. Given the number of studies showing a proportion of missed clinically significant cancers by magnetic resonance imaging targeted cores, a case specific decision must be made whether to also perform concurrent systematic sampling. However, performing solely targeted biopsy should only be considered once quality assurance efforts have validated the performance of prostate magnetic resonance imaging interpretations with results consistent with the published literature. In patients with negative or low suspicion magnetic resonance imaging (PI-RADS assessment category of 1 or 2, respectively), other ancillary markers (ie PSA, PSAD, PSAV, PCA3, PHI, 4K) may be of value in identifying patients warranting repeat systematic biopsy, although further data are needed on this topic. If a repeat biopsy is deferred on the basis of magnetic resonance imaging findings, then continued clinical and laboratory followup is advised and consideration should be given to incorporating repeat magnetic resonance imaging in this diagnostic surveillance regimen. [ABSTRACT FROM AUTHOR]

Utilization of pre-biopsy multiparametric MRI (mpMRI) is increasing. To optimize the usefulness of mpMRI, physicians should accurately quote patients a numerical risk of cancer based on their MRI. The Prostate Imaging Reporting and Data System (PIRADS) standardizes interpretation of mpMRI; however, reported rates of clinically significant prostate cancer (CSC) stratified by PIRADS score vary widely. While some publications use radical prostatectomy (RP) specimens as gold standard, others use biopsy. We hypothesized that much of the variation in CSC stems from differences in cancer prevalence in RP cohorts (100% prevalence) vs biopsy cohorts. To quantify the impact of this selection bias on cancer yield according to PIRADS score, we analyzed data from 614 men with 854 lesions who underwent targeted biopsy from 2014 to 2018. Of these, 125 men underwent RP. We compared the PIRADS detection rates of CSC (Gleason ≥7) on targeted biopsy between the biopsy-only and RP cohorts. For all PIRADS scores, CSC yield was much greater in patients who underwent RP. For example, CSC was found in 30% of PIRADS 3 lesions in men who underwent RP vs 7.6% in men who underwent biopsy. Our results show that mpMRI performance appears to be better in men who undergo RP compared with those who only receive biopsy. Physicians should understand the effect of this selection bias and its magnitude when discussing mpMRI results with patients considering biopsy, and take great caution in quoting CSC yields from publications using RP as gold standard. [ABSTRACT FROM AUTHOR]

Abstract: Background: Conventional biopsy fails to detect the presence of some prostate cancers (PCas). Men with a prior negative biopsy but persistently elevated prostate-specific antigen (PSA) pose a diagnostic dilemma, as some harbor elusive cancer. Objective: To determine whether use of magnetic resonance–ultrasound (MR-US) fusion biopsy results in improved detection of PCa compared to repeat conventional biopsy. Design, setting, and participants: In a consecutive-case series, 105 subjects with prior negative biopsy and elevated PSA values underwent multiparametric magnetic resonance imaging (MRI) and fusion biopsy in an outpatient setting. Intervention: Suspicious areas on multiparametric MRI were delineated and graded by a radiologist; MR–US fusion biopsy was performed by a urologist using the Artemis device; targeted and systematic biopsies were obtained regardless of MRI result. Outcome measurements and statistical analysis: Detection rates of all PCa and clinically significant PCa (Gleason ≥3+4 or Gleason 6 with maximal cancer core length ≥4mm) were determined. The yield of targeted biopsy was compared to systematic biopsy. The ability of an MRI grading system to predict clinically significant cancer was investigated. Stepwise multivariate logistic regression analysis was performed to determine predictors of significant cancer on biopsy. Results and limitations: Fusion biopsy revealed PCa in 36 of 105 men (34%; 95% confidence interval [CI], 25–45). Seventy-two percent of men with PCa had clinically significant disease; 21 of 23 men (91%) with PCa on targeted biopsy had significant cancer compared to 15 of 28 (54%) with systematic biopsy. Degree of suspicion on MRI was the most powerful predictor of significant cancer on multivariate analysis. Twelve of 14 (86%) subjects with a highly suspicious MRI target were diagnosed with clinically significant cancer. Conclusions: MR–US fusion biopsy provides improved detection of PCa in men with prior negative biopsies and elevated PSA values. Most cancers found were clinically significant. [Copyright &y& Elsevier]

Purpose: Targeted biopsy of lesions identified on magnetic resonance imaging may enhance the detection of clinically relevant prostate cancers. We evaluated prostate cancer detection rates in 171 consecutive men using magnetic resonance ultrasound fusion prostate biopsy. Materials and Methods: Subjects underwent targeted biopsy for active surveillance (106) or persistently increased prostate specific antigen but negative prior conventional biopsy (65). Before biopsy, each man underwent multiparametric magnetic resonance imaging at 3.0 Tesla. Lesions on magnetic resonance imaging were outlined in 3 dimensions and assigned increasing cancer suspicion levels (image grade 1 to 5) by a uroradiologist. A biopsy tracking system was used to fuse the stored magnetic resonance imaging with real-time ultrasound, generating a 3-dimensional prostate model on the fly. Working from the 3-dimensional model, transrectal biopsy of target lesions and 12 systematic biopsies were performed with the patient under local anesthesia in the clinic. Results: A total of 171 subjects (median age 65 years) underwent targeted biopsy. At biopsy, median prostate specific antigen was 4.9 ng/ml and prostate volume was 48 cc. A targeted biopsy was 3 times more likely to identify cancer than a systematic biopsy (21% vs 7%). Prostate cancer was found in 53% of men, 38% of whom had Gleason grade 7 or greater cancer. Of the men with Gleason 7 or greater cancer 38% had disease detected only on targeted biopsies. Targeted biopsy findings correlated with level of suspicion on magnetic resonance imaging. Of 16 men 15 (94%) with an image grade 5 target (highest suspicion) had prostate cancer, including 7 with Gleason 7 or greater cancer. Conclusions: Prostate lesions identified on magnetic resonance imaging can be accurately targeted using magnetic resonance ultrasound fusion biopsy by a urologist in clinic. Biopsy findings correlate with level of suspicion on magnetic resonance imaging. [ABSTRACT FROM AUTHOR]

Spirituality is interdependent with the biological, psychological, and interpersonal aspects of life. Although spirituality has been studied in breast cancer survivors, little work has been done in men with prostate cancer. We sought to determine whether lower spirituality in men with early stage prostate cancer is associated with worse general health-related quality of life (HRQOL), disease-specific HRQOL, or psychosocial health. Two hundred and twenty-two subjects were drawn from a state-funded program providing free prostate cancer treatment to indigent men. Validated instruments captured spirituality, general and disease-specific HRQOL, anxiety, symptom distress, and emotional well-being. We found a consistent relationship between spirituality and the outcomes assessed. Low spirituality was associated with significantly worse physical and mental health, sexual function and more urinary bother after controlling for covariates. All of the psychosocial variables studied reflected worse adjustment in the men with low spirituality. Because the likelihood of prostate cancer survivorship is high, interventions targeting spirituality could impact the physical and psychosocial health of many men. Copyright © 2005 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Objectives Materials and Methods Results Conclusion To externally validate the performance of the DeepDx Prostate artificial intelligence (AI) algorithm (Deep Bio Inc., Seoul, South Korea) for Gleason grading on whole‐mount prostate histopathology, considering potential variations observed when applying AI models trained on biopsy samples to radical prostatectomy (RP) specimens due to inherent differences in tissue representation and sample size.The commercially available DeepDx Prostate AI algorithm is an automated Gleason grading system that was previously trained using 1133 prostate core biopsy images and validated on 700 biopsy images from two institutions. We assessed the AI algorithm's performance, which outputs Gleason patterns (3, 4, or 5), on 500 1‐mm2 tiles created from 150 whole‐mount RP specimens from a third institution. These patterns were then grouped into grade groups (GGs) for comparison with expert pathologist assessments. The reference standard was the International Society of Urological Pathology GG as established by two experienced uropathologists with a third expert to adjudicate discordant cases. We defined the main metric as the agreement with the reference standard, using Cohen's kappa.The agreement between the two experienced pathologists in determining GGs at the tile level had a quadratically weighted Cohen's kappa of 0.94. The agreement between the AI algorithm and the reference standard in differentiating cancerous vs non‐cancerous tissue had an unweighted Cohen's kappa of 0.91. Additionally, the AI algorithm's agreement with the reference standard in classifying tiles into GGs had a quadratically weighted Cohen's kappa of 0.89. In distinguishing cancerous vs non‐cancerous tissue, the AI algorithm achieved a sensitivity of 0.997 and specificity of 0.88; in classifying GG ≥2 vs GG 1 and non‐cancerous tissue, it demonstrated a sensitivity of 0.98 and specificity of 0.85.The DeepDx Prostate AI algorithm had excellent agreement with expert uropathologists and performance in cancer identification and grading on RP specimens, despite being trained on biopsy specimens from an entirely different patient population. [ABSTRACT FROM AUTHOR]

The article presents a study on the effects of a magnetic resonance imaging (MRI)-ultrasound fusion technique on prostate cancer detection in men with prior negative biopsies but with an increased prostate specific antigen (PSA). It compares targeted and systematic biopsies in relation to detecting cancer in the patients. The efficacy of the MRI-US fusion targeted biopsy is also discussed.

Objectives: To determine whether PSA density (PSAD), can sub-stratify risk of biopsy upgrade among men on active surveillance (AS) with normal baseline MRI.Methods: We identified a cohort of patients with low and favorable intermediate-risk prostate cancer on AS at two large academic centers from February 2013 - December 2017. Analysis was restricted to patients with GG1 cancer on initial biopsy and a negative baseline or surveillance mpMRI, defined by the absence of PI-RADS 2 or greater lesions. We assessed ability of PSA, prostate volume and PSAD to predict upgrading on confirmatory biopsy.Results: We identified 98 patients on AS with negative baseline or surveillance mpMRI. Median PSA at diagnosis was 5.8 ng/mL and median PSAD was 0.08 ng/mL/mL. Fourteen men (14.3%) experienced Gleason upgrade at confirmatory biopsy. Patients who were upgraded had higher PSA (7.9 vs 5.4 ng/mL, P = .04), PSAD (0.20 vs 0.07 ng/mL/mL, P < .001), and lower prostate volumes (42.5 vs 65.8 mL, P = .01). On multivariate analysis, PSAD was associated with pathologic upgrade (OR 2.23 per 0.1-increase, P = .007). A PSAD cutoff at 0.08 generated a NPV of 98% for detection of pathologic upgrade.Conclusion: PSAD reliably discriminated the risk of Gleason upgrade at confirmatory biopsy among men with low-grade prostate cancer with negative MRI. PSAD could be clinically implemented to reduce the intensity of surveillance for a subset of patients. [ABSTRACT FROM AUTHOR]

Objectives: We sought to identify clinical and magnetic resonance imaging (MRI) characteristics in men with the Prostate Imaging - Reporting and Data System (PI-RADS) category 3 index lesions that predict clinically significant prostate cancer (CaP) on MRI targeted biopsy.Materials and Methods: Multicenter study of prospectively collected data for biopsy-naive men (n = 247) who underwent MRI-targeted and systematic biopsies for PI-RADS 3 index lesions. The primary endpoint was diagnosis of clinically significant CaP (Grade Group ≥2). Multivariable logistic regression models assessed for factors associated with clinically significant CaP. The probability distributions of clinically significant CaP based on different levels of predictors of multivariable models were plotted in a heatmap.Results: Men with clinically significant CaP had smaller prostate volume (39.20 vs. 55.10 ml, P < 0.001) and lower apparent diffusion coefficient (ADC) values (973 vs. 1068 μm2/s, P = 0.013), but higher prostate-specific antigen (PSA) density (0.21 vs. 0.13 ng/ml2, P = 0.027). On multivariable analyses, lower prostate volume (odds ratio [OR]: 0.95, 95% confidence interval [CI]: 0.92-0.97), lower ADC value (OR: 0.99, 95% CI: 0.99-1.00), and Prostate-specific antigen density >0.15 ng/ml2 (OR: 3.51, 95% CI 1.61-7.68) were independently associated with significant CaP.Conclusion: Higher PSA density, lower prostate volume and ADC values are associated with clinically significant CaP in biopsy-naïve men with PI-RADS 3 lesions. We present regression-derived probabilities of detecting clinically significant CaP based on various clinical and imaging values that can be used in decision-making. Our findings demonstrate an opportunity for MRI refinement or biomarker discovery to improve risk stratification for PI-RADS 3 lesions. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the performance of multiparametric magnetic resonance imaging (mpMRI) and PSA testing in follow-up after high intensity focused ultrasound (HIFU) focal therapy for localized prostate cancer.Methods: A total of 73 men with localized prostate cancer were prospectively enrolled and underwent focal HIFU followed by per-protocol PSA and mpMRI with systematic plus targeted biopsies at 12 months after treatment. We evaluated the association between post-treatment mpMRI and PSA with disease persistence on the post-ablation biopsy. We also assessed post-treatment functional and oncological outcomes.Results: Median age was 69 years (Interquartile Range (IQR): 66-74) and median PSA was 6.9 ng/dL (IQR: 5.3-9.9). Of 19 men with persistent GG ≥ 2 disease, 58% (11 men) had no visible lesions on MRI. In the 14 men with PIRADS 4 or 5 lesions, 7 (50%) had either no cancer or GG 1 cancer at biopsy. Men with false negative mpMRI findings had higher PSA density (0.16 vs. 0.07 ng/mL2, P = 0.01). No change occurred in the mean Sexual Health Inventory for Men (SHIM) survey scores (17.0 at baseline vs. 17.7 post-treatment, P = 0.75) or International Prostate Symptom Score (IPSS) (8.1 at baseline vs. 7.7 at 24 months, P = 0.81) after treatment.Conclusions: Persistent GG ≥ 2 cancer may occur after focal HIFU. mpMRI alone without confirmatory biopsy may be insufficient to rule out residual cancer, especially in patients with higher PSA density. Our study also validates previously published studies demonstrating preservation of urinary and sexual function after HIFU treatment. [ABSTRACT FROM AUTHOR]

• Distinguishing indolent from aggressive prostate cancer on MRI is a clinical need • An automated method for distinguishing indolent from aggressive cancer is presented • Correlated feature learning is used to capture pathology characteristics on MRI • Deep learning is used for cancer detection and characterization of aggressiveness • Our method can improve prostate cancer care by guiding treatment planning [Display omitted] Automated methods for detecting prostate cancer and distinguishing indolent from aggressive disease on Magnetic Resonance Imaging (MRI) could assist in early diagnosis and treatment planning. Existing automated methods of prostate cancer detection mostly rely on ground truth labels with limited accuracy, ignore disease pathology characteristics observed on resected tissue, and cannot selectively identify aggressive (Gleason Pattern ≥ 4) and indolent (Gleason Pattern=3) cancers when they co-exist in mixed lesions. In this paper, we present a radiology-pathology fusion approach, CorrSigNIA, for the selective identification and localization of indolent and aggressive prostate cancer on MRI. CorrSigNIA uses registered MRI and whole-mount histopathology images from radical prostatectomy patients to derive accurate ground truth labels and learn correlated features between radiology and pathology images. These correlated features are then used in a convolutional neural network architecture to detect and localize normal tissue, indolent cancer, and aggressive cancer on prostate MRI. CorrSigNIA was trained and validated on a dataset of 98 men, including 74 men that underwent radical prostatectomy and 24 men with normal prostate MRI. CorrSigNIA was tested on three independent test sets including 55 men that underwent radical prostatectomy, 275 men that underwent targeted biopsies, and 15 men with normal prostate MRI. CorrSigNIA achieved an accuracy of 80% in distinguishing between men with and without cancer, a lesion-level ROC-AUC of 0.81 ± 0.31 in detecting cancers in both radical prostatectomy and biopsy cohort patients, and lesion-levels ROC-AUCs of 0.82 ± 0.31 and 0.86 ± 0.26 in detecting clinically significant cancers in radical prostatectomy and biopsy cohort patients respectively. CorrSigNIA consistently outperformed other methods across different evaluation metrics and cohorts. In clinical settings, CorrSigNIA may be used in prostate cancer detection as well as in selective identification of indolent and aggressive components of prostate cancer, thereby improving prostate cancer care by helping guide targeted biopsies, reducing unnecessary biopsies, and selecting and planning treatment. [ABSTRACT FROM AUTHOR]

Background: While multiparametric MRI (mpMRI) has high sensitivity for detection of clinically significant prostate cancer (CSC), false positives and negatives remain common. Calculators that combine mpMRI with clinical variables can improve cancer risk assessment, while providing more accurate predictions for individual patients. We sought to create and externally validate nomograms incorporating Prostate Imaging Reporting and Data System (PIRADS) scores and clinical data to predict the presence of CSC in men of all biopsy backgrounds.Methods: Data from 2125 men undergoing mpMRI and MR fusion biopsy from 2014 to 2018 at Stanford, Yale, and UAB were prospectively collected. Clinical data included age, race, PSA, biopsy status, PIRADS scores, and prostate volume. A nomogram predicting detection of CSC on targeted or systematic biopsy was created.Results: Biopsy history, Prostate Specific Antigen (PSA) density, PIRADS score of 4 or 5, Caucasian race, and age were significant independent predictors. Our nomogram-the Stanford Prostate Cancer Calculator (SPCC)-combined these factors in a logistic regression to provide stronger predictive accuracy than PSA density or PIRADS alone. Validation of the SPCC using data from Yale and UAB yielded robust AUC values.Conclusions: The SPCC combines pre-biopsy mpMRI with clinical data to more accurately predict the probability of CSC in men of all biopsy backgrounds. The SPCC demonstrates strong external generalizability with successful validation in two separate institutions. The calculator is available as a free web-based tool that can direct real-time clinical decision-making. [ABSTRACT FROM AUTHOR]

• For the first time, deep learning is used for MRI-histopathology image registration. • Our registration network avoids the shortcomings of multi-modal similarity measures. • Our registration network allows mapping of the ground truth cancer labels onto MRI. • This important advance will facilitate the detection of prostate cancer on MRI. • Our code is freely available at https://github.com/pimed//ProsRegNet. Magnetic resonance imaging (MRI) is an increasingly important tool for the diagnosis and treatment of prostate cancer. However, interpretation of MRI suffers from high inter-observer variability across radiologists, thereby contributing to missed clinically significant cancers, overdiagnosed low-risk cancers, and frequent false positives. Interpretation of MRI could be greatly improved by providing radiologists with an answer key that clearly shows cancer locations on MRI. Registration of histopathology images from patients who had radical prostatectomy to pre-operative MRI allows such mapping of ground truth cancer labels onto MRI. However, traditional MRI-histopathology registration approaches are computationally expensive and require careful choices of the cost function and registration hyperparameters. This paper presents ProsRegNet, a deep learning-based pipeline to accelerate and simplify MRI-histopathology image registration in prostate cancer. Our pipeline consists of image preprocessing, estimation of affine and deformable transformations by deep neural networks, and mapping cancer labels from histopathology images onto MRI using estimated transformations. We trained our neural network using MR and histopathology images of 99 patients from our internal cohort (Cohort 1) and evaluated its performance using 53 patients from three different cohorts (an additional 12 from Cohort 1 and 41 from two public cohorts). Results show that our deep learning pipeline has achieved more accurate registration results and is at least 20 times faster than a state-of-the-art registration algorithm. This important advance will provide radiologists with highly accurate prostate MRI answer keys, thereby facilitating improvements in the detection of prostate cancer on MRI. Our code is freely available at https://github.com/pimed//ProsRegNet. Image, graphical abstract [ABSTRACT FROM AUTHOR]