Living with prostate cancer: a mixed-method evaluation of group therapy intervention to alleviate psychological distress in a Canadian setting.

PURPOSE: To assess the effects of group therapy focused on the experience of living with prostate cancer (PC) on depression and mental well-being among men with the disease and to explore participant experiences of a guided opportunity to 'speak the unspeakable' as it pertains to living with PC. METHODS: We used a mixed-method convergent design. Participants completed four validated self-report questionnaires at baseline, immediately after the final session, and at three, six, and 12 months follow-up. A repeated measures mixed-effect model examined the effects of the program on depression, mental well-being, and masculinity. Seven focus groups (n = 37) and 39 semi-structured individual interviews explored participant reactions at follow-up. RESULTS: Thirty-nine (93%) participants completed the questionnaires at all follow-ups. Responses indicated improved mental well-being up to three months (p < 0.01) and a decrease in depressive symptoms to 12 months (p < 0.05). Qualitative analysis revealed how the cohesive group environment alleviated psychological stress, enabled participants to identify significant issues and concerns in their lives, and improved communication and relationship skills that were of value in the group as well as with family and friends. The facilitation was essential to guiding participants to 'speak the unspeakable.' CONCLUSION: Men with PC who speak of their experience in a group setting with a guided process incorporating features of a life review appear to gain insight into the impact of PC in their lives, experience diminished features of depression and isolation, and enhance their communication skills within the groups as well as with family members and friends.

Multi-Frequency 3D Shear Wave Absolute Vibro-Elastography (S-WAVE) System for the Prostate.

This article describes a novel system for quantitative and volumetric measurement of tissue elasticity in the prostate using simultaneous multi-frequency tissue excitation. Elasticity is computed by using a local frequency estimator to measure the three-dimensional local wavelengths of steady-state shear waves within the prostate gland. The shear wave is created using a mechanical voice coil shaker which transmits simultaneous multi-frequency vibrations transperineally. Radio frequency data is streamed directly from a BK Medical 8848 transrectal ultrasound transducer to an external computer where tissue displacement due to the excitation is measured using a speckle tracking algorithm. Bandpass sampling is used that eliminates the need for an ultra-fast frame rate to track the tissue motion and allows for accurate reconstruction at a sampling frequency that is below the Nyquist rate. A roll motor with computer control is used to rotate the transducer and obtain 3D data. Two commercially available phantoms were used to validate both the accuracy of the elasticity measurements as well as the functional feasibility of using the system for in vivo prostate imaging. The phantom measurements were compared with 3D Magnetic Resonance Elastography (MRE), where a high correlation of 96% was achieved. In addition, the system has been used in two separate clinical studies as a method for cancer identification. Qualitative and quantitative results of 11 patients from these clinical studies are presented here. Furthermore, an AUC of 0.87±0.12 was achieved for malignant vs. benign classification using a binary support vector machine classifier trained with data from the latest clinical study with leave one patient out cross-validation.

The "Ins and Outs" of Prostate Specific Membrane Antigen (PSMA) as Specific Target in Prostate Cancer Therapy.

Prostate-specific membrane antigen (PSMA) is expressed in epithelial cells of the prostate gland and is strongly upregulated in prostatic adenocarcinoma, with elevated expression correlating with metastasis, progression, and androgen independence. Because of its specificity, PSMA is a major target of prostate cancer therapy; however, detectable levels of PSMA are also found in other tissues, especially in salivary glands and kidney, generating bystander damage of these tissues. Antibody target therapy has been used with relative success in reducing tumor growth and prostate specific antigen (PSA) levels. However, since antibodies are highly stable in plasma, they have prolonged time in circulation and accumulate in organs with an affinity for antibodies such as bone marrow. For that reason, a second generation of PSMA targeted therapeutic agents has been developed. Small molecules and minibodies have had promising clinical trial results, but concerns about their specificity had arisen with side effects due to accumulation in salivary glands and kidneys. Herein we study the specificity of small molecules and minibodies that are currently being clinically tested. We observed a high affinity of these molecules for PSMA in prostate, kidney and salivary gland, suggesting that their effect is not prostate specific. The search for specific prostate target agents must continue so as to optimally treat patients with prostate cancer, while minimizing deleterious effects in other PSMA expressing tissues.

Aquablation therapy in large prostates (80-150 cc) for lower urinary tract symptoms due to benign prostatic hyperplasia: WATER II 3-year trial results.

Objective: The objective of this study is to determine if Aquablation therapy can maintain its effectiveness in treating men with lower urinary tract symptoms (LUTS) due to benign prostatic hyperplasia (BPH) with large-volume (80-150 cc) prostates at 3 years. Subjects and Methods: One hundred one men with moderate-to-severe BPH symptoms and prostate volumes between 80 and 150 cc were enrolled in a prospective, nonrandomized, multicenter, international clinical trial in late 2017. Baseline, procedural, and follow-up parameters were recorded at baseline and scheduled postoperative visits. IPSS, Qmax, and treatment failure are reported at 3 years. Results: The mean prostate volume was 107 cc (range 80-150). Mean IPSS improved from 23.2 at baseline to 6.5 at 3 years (16.3-point improvement, p < 0.0001). Mean IPSS quality of life improved from 4.6 at baseline to 1.1 at 3 years (improvement of 3.4 points, p < 0.0001). Maximum urinary flow increased from 8.7 to 18.5 cc/s. At 3 year follow-up, 6% of treated patients needed BPH medication and an additional 3% required surgical retreatment for LUTS. Conclusions: Three-year follow-up demonstrates a sustained symptom reduction response along with low irreversible complications to Aquablation in men with LUTS due to BPH and prostates of 80-150 cc. Current treatment options available for men with prostates of this size have similar efficacy outcomes but are burdened with high rates of irreversible complications. There are now numerous clinical studies with Aquablation used in various prostates sizes, and it should be offered as an option to men with LUTS due to BPH.

Genetic Factors Associated with Prostate Cancer Conversion from Active Surveillance to Treatment.

Men diagnosed with low-risk prostate cancer (PC) are increasingly electing active surveillance (AS) as their initial management strategy. While this may reduce the side effects of treatment for prostate cancer, many men on AS eventually convert to active treatment. PC is one of the most heritable cancers, and genetic factors that predispose to aggressive tumors may help distinguish men who are more likely to discontinue AS. To investigate this, we undertook a multi-institutional genome-wide association study (GWAS) of 5,222 PC patients and 1,139 other patients from replication cohorts, all of whom initially elected AS and were followed over time for the potential outcome of conversion from AS to active treatment. In the GWAS we detected 18 variants associated with conversion, 15 of which were not previously associated with PC risk. With a transcriptome-wide association study (TWAS), we found two genes associated with conversion (MAST3, p = 6.9×10-7 and GAB2, p = 2.0×10-6). Moreover, increasing values of a previously validated 269-variant genetic risk score (GRS) for PC was positively associated with conversion (e.g., comparing the highest to the two middle deciles gave a hazard ratio [HR] = 1.13; 95% Confidence Interval [CI]= 0.94-1.36); whereas, decreasing values of a 36-variant GRS for prostate-specific antigen (PSA) levels were positively associated with conversion (e.g., comparing the lowest to the two middle deciles gave a HR = 1.25; 95% CI, 1.04-1.50). These results suggest that germline genetics may help inform and individualize the decision of AS-or the intensity of monitoring on AS-versus treatment for the initial management of patients with low-risk PC.

Taking Advantage of the Teachable Moment at Initial Diagnosis of Prostate Cancer-Results of a Pilot Randomized Controlled Trial of Supervised Exercise Training.

BACKGROUND: Increased physical activity (PA) levels are associated with improved prostate cancer (PCa) outcomes. Sustainable PA has been linked to improved health-related quality of life (QoL) in cancer patients. The time of diagnosis of PCa may offer a critical time point when patients might be more likely to consider lifestyle changes. This, in turn, may contribute to sustainable PA and its likely benefits. OBJECTIVE: The aims of this study were to determine if a structured PA intervention introduced at the time of diagnosis can (1) lead to sustainable PA and (2) help improve psychosocial and QoL outcomes as compared with usual PA. INTERVENTIONS/METHODS: This was a pilot randomized controlled trial enrolling patients with intermediate-risk PCa into either arm A (supervised 8- to 12-week physical exercise program; n = 10) or control arm B (usual PA; n = 10). Primary outcome was PA at 6 months. Secondary outcomes were QoL, psychological well-being, physical fitness, and functional outcomes postintervention. Change over time was compared using a nonparametric Wilcoxon test. RESULTS: Demographic variables were the same between arms. Comparing parameters at the start and 6 months post-radical prostatectomy, PA significantly improved in arm A (self-reported Godin score 24.7 vs 42.8 units, P < .01, objective number of chair stands [14-19, P < .01]), but not in arm B. There were no significant differences between arms in QoL and psychosocial outcomes. CONCLUSIONS: A preoperative supervised exercise training program increases long-term PA. IMPLICATIONS FOR PRACTICE: Future trials should evaluate PA sustainability beyond 6 months and if this leads to improved psychosocial and QoL outcomes.

Factors Associated with Time to Conversion from Active Surveillance to Treatment for Prostate Cancer in a Multi-Institutional Cohort.

PURPOSE: We examined the demographic and clinicopathological parameters associated with the time to convert from active surveillance to treatment among men with prostate cancer. MATERIALS AND METHODS: A multi-institutional cohort of 7,279 patients managed with active surveillance had data and biospecimens collected for germline genetic analyses. RESULTS: Of 6,775 men included in the analysis, 2,260 (33.4%) converted to treatment at a median followup of 6.7 years. Earlier conversion was associated with higher Gleason grade groups (GG2 vs GG1 adjusted hazard ratio [aHR] 1.57, 95% CI 1.36-1.82; ≥GG3 vs GG1 aHR 1.77, 95% CI 1.29-2.43), serum prostate specific antigen concentrations (aHR per 5 ng/ml increment 1.18, 95% CI 1.11-1.25), tumor stages (cT2 vs cT1 aHR 1.58, 95% CI 1.41-1.77; ≥cT3 vs cT1 aHR 4.36, 95% CI 3.19-5.96) and number of cancerous biopsy cores (3 vs 1-2 cores aHR 1.59, 95% CI 1.37-1.84; ≥4 vs 1-2 cores aHR 3.29, 95% CI 2.94-3.69), and younger age (age continuous per 5-year increase aHR 0.96, 95% CI 0.93-0.99). Patients with high-volume GG1 tumors had a shorter interval to conversion than those with low-volume GG1 tumors and behaved like the higher-risk patients. We found no significant association between the time to conversion and self-reported race or genetic ancestry. CONCLUSIONS: A shorter time to conversion from active surveillance to treatment was associated with higher-risk clinicopathological tumor features. Furthermore, patients with high-volume GG1 tumors behaved similarly to those with intermediate and high-risk tumors. An exploratory analysis of self-reported race and genetic ancestry revealed no association with the time to conversion.

The Association Between Statin Use and Outcomes in Patients Initiating Androgen Deprivation Therapy.

BACKGROUND: Studies have conflicting results regarding the association between statin use and biochemical recurrence for prostate cancer (PCa). A limited number of studies examining statins in advanced stages report positive results, with a few specifically examining statins and androgen deprivation therapy (ADT). OBJECTIVE: To perform a post hoc secondary analysis of a randomised controlled trial (RCT) of men initiating ADT to examine the association between statin use and outcomes. DESIGN, SETTING, AND PARTICIPANTS: Patients with prostate-specific antigen (PSA) >3 ng/ml >1 yr following primary/salvage radiotherapy were enrolled in an RCT of intermittent androgen deprivation (IAD) versus continuous ADT (NCT00003653). Baseline and on-study statin use was modelled as a time-dependent covariate. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary endpoint was overall survival. Models were adjusted for age, time from radiotherapy to ADT, baseline PSA, and prior ADT. RESULTS AND LIMITATIONS: Of 1364 patients, statin users (585; 43%) were younger (72.7 vs 73.8 yr, p = 0.001) and less likely to have PSA >15 ng/ml (20% vs 25%, p = 0.04). After a median follow-up of 6.9 yr, statin use was associated with reduced overall (hazard ratio [HR]: 0.64; 95% confidence interval [CI] 0.53-0.78, p < 0.001) and PCa-specific (HR: 0.65, 95% CI 0.48-0.87, p = 0.004) mortality. Statin users had 13% longer time to castration resistance, but this did not reach statistical significance (p = 0.15). As an exploratory endpoint, in the IAD arm, statin users had longer time off treatment (median: 0.85 vs 0.64 yr, p = 0.06). Limitations include potential for residual confounding between statin users and nonusers, and confounding by indication. CONCLUSIONS: In men treated with ADT following primary or salvage radiotherapy, statin use was associated with improved overall and PCa-specific survival. In patients treated with IAD, statin use was associated with a trend towards longer time off treatment. A prospective trial of statins in men commencing ADT is warranted. PATIENT SUMMARY: We found a favourable association between statin use and survival outcomes in patients initiating androgen deprivation therapy.

Mapping Canadian Men's Recent and Intended Health Behavior Changes Through the Don't Change Much Electronic Health Program.

BACKGROUND: Although evaluation studies confirm the strong potential of men's electronic health (eHealth) programs, there have been calls to more fully understand acceptability, engagement, and behavior change to guide future work. Relatedly, mapping of behavior changes using health promotion theories including the transtheoretical model (or stages of change) has been recommended to build a translatable empirical base to advance design and evaluation considerations for men's eHealth programs. OBJECTIVE: This study aimed to use a benchmark sample as a reference group to map the recent and intended health behavior changes in Canadian men who use the Don't Change Much (DCM) eHealth program. The hypothesis being tested was that increased exposure to DCM would be positively associated with men's recent and intended health behavior changes. METHODS: DCM users (n=863) were sampled for demographic data and self-reported recent and intended health behavior changes. Respondents also reported their usage (frequency and duration) for each of the 3 DCM components (web, newsletter, and social media) and were allocated to limited exposure (257/863, 29.8%), low exposure (431/863, 49.9%), and high exposure (175/863, 20.3%) subgroups. A benchmark sample (n=2000), comprising respondents who had not accessed DCM provided a reference group. Bivariate analysis of recent and intended health behavior changes and DCM exposure levels were used to compute the strength of association between the independent variables (exposure levels) and the 10 categorical dependent variables (recent and intended health behavior changes). Binary logistic regression models were computed for each of the 10 recent and intended health behavior changes. Linear regression was used to model the association between the number of recent and intended changes and the level of exposure to DCM. RESULTS: Compared with the benchmark reference group, DCM high-exposure respondents had significantly increased odds for 9 of the 10 health behavior changes, with the largest effect size observed for Changed diet or Improved eating habits (odds ratio [OR] 5.628, 95% CI 3.932-8.055). High-exposure respondents also had significantly increased odds for 9 intended health changes, with the largest effect sizes observed for Reduce stress level (OR 4.282, 95% CI 3.086-5.941). Moderate effect size (goodness of fit) was observed for increased total number of recent (F12,2850=25.52; P.001; adjusted R2=.093) and intended health behavior changes (F12,2850=36.30; P.001; adjusted R2=.129) among high-exposure respondents. CONCLUSIONS: DCM respondents contrasted the predominately precontemplative benchmark sample mapping across the contemplative, preparation, and action stages of the transtheoretical health behavior change model. Almost 10% of variation in the recent and 13% of variation in the intended health behavior changes can be explained by DCM exposure and demographic factors, indicating the acceptability of this men's eHealth resource.

MRI of the Prostate With and Without Endorectal Coil at 3 T: Correlation With Whole-Mount Histopathologic Gleason Score.

OBJECTIVE. The purpose of this article is to prospectively compare image quality and diagnostic accuracy of clinically significant prostate cancer with and without endorectal coil (ERC) at 3 T using a combination of T2-weighted and diffusion-weighted MRI. SUBJECTS AND METHODS. Twenty-three patients with biopsy-proven prostate cancer underwent MRI with and without ERC at the same visit. Patients subsequently underwent radical prostatectomy. Specimens were assessed by whole-mount histopathologic examination. Two radiologists reviewed MR images for image quality (5-point scale) and disease using Prostate Imaging Reporting and Data Systems version 2 (PI-RADSv2). Sensitivity, specificity, and area under the ROC curve (AUC) were calculated with and without ERC. Additionally, apparent diffusion coefficient (ADC) was correlated with Gleason score and ADC values of each lesion were compared with and without ERC. RESULTS. Image quality was comparable with and without ERC (3.8 vs 3.5). Twenty-nine cancer foci larger than 0.5 cm in diameter were found in 23 patients on histopathologic examination; 18 tumors had a Gleason score of 7 or greater. Two radiologists recorded AUC for tumors with a Gleason score of 7 or greater as 0.96 and 0.96 with ERC and 0.88 and 0.91 without ERC. All 13 tumors with a Gleason score of 3 + 4 were detected with ERC, but only 9 were detected without ERC. One of five tumors with Gleason scores less than 3 + 4 was missed with and without ERC. ADC significantly correlated with Gleason score. There was no significant difference in the ADC of a lesion on MRI with and without an ERC. CONCLUSION. MRI with and without ERC was equally accurate at showing prostate cancers with Gleason scores of 4 + 3 or greater. However, MRI with ERC was superior at showing cancer with a Gleason score of 3 + 4. There was no significant difference in ADC values between scores acquired with or without an ERC.

Canadian men's health stigma, masculine role norms and lifestyle behaviors.

Men are at high risk for both morbidity and premature mortality from several of the most common serious diseases. Although numerous factors have been identified to explain men's risk, this study focused on the relationship between lifestyle behaviors, health-related self-stigma and masculine role norms. An age and location stratified sample of 2000 Canadian men completed measures assessing five lifestyle behaviors (smoking, alcohol use, sleep, diet and exercise), a screen for depression, and measures of self-stigma and masculine role norms. The results showed that elements of both health-related self-stigma and masculine role norms were associated with increased risk for being above the clinical threshold for four of the lifestyle behaviors and depression. The most frequent and largest relationships were associated with exercise and depression. The total number of lifestyle behaviors for which participants were above the clinical cut-points was also associated with self-stigma and masculine role norms. These findings demonstrate the importance of health-related self-stigma and masculine role norms as potential barriers to men's health and well-being.

A partial augmented reality system with live ultrasound and registered preoperative MRI for guiding robot-assisted radical prostatectomy.

We propose an image guidance system for robot assisted laparoscopic radical prostatectomy (RALRP). A virtual 3D reconstruction of the surgery scene is displayed underneath the endoscope's feed on the surgeon's console. This scene consists of an annotated preoperative Magnetic Resonance Image (MRI) registered to intraoperative 3D Trans-rectal Ultrasound (TRUS) as well as real-time sagittal 2D TRUS images of the prostate, 3D models of the prostate, the surgical instrument and the TRUS transducer. We display these components with accurate real-time coordinates with respect to the robot system. Since the scene is rendered from the viewpoint of the endoscope, given correct parameters of the camera, an augmented scene can be overlaid on the video output. The surgeon can rotate the ultrasound transducer and determine the position of the projected axial plane in the MRI using one of the registered da Vinci instruments. This system was tested in the laboratory on custom-made agar prostate phantoms. We achieved an average total registration accuracy of 3.2 â€¯±â€¯ 1.3 mm. We also report on the successful application of this system in the operating room in 12 patients. The average registration error between the TRUS and the da Vinci system for the last 8 patients was 1.4 â€¯±â€¯ 0.3 mm and average target registration error of 2.1 â€¯±â€¯ 0.8 mm, resulting in an in vivo overall robot system to MRI mean registration error of 3.5 mm or less, which is consistent with our laboratory studies.

A new era: artificial intelligence and machine learning in prostate cancer.

Artificial intelligence (AI) - the ability of a machine to perform cognitive tasks to achieve a particular goal based on provided data - is revolutionizing and reshaping our health-care systems. The current availability of ever-increasing computational power, highly developed pattern recognition algorithms and advanced image processing software working at very high speeds has led to the emergence of computer-based systems that are trained to perform complex tasks in bioinformatics, medical imaging and medical robotics. Accessibility to 'big data' enables the 'cognitive' computer to scan billions of bits of unstructured information, extract the relevant information and recognize complex patterns with increasing confidence. Computer-based decision-support systems based on machine learning (ML) have the potential to revolutionize medicine by performing complex tasks that are currently assigned to specialists to improve diagnostic accuracy, increase efficiency of throughputs, improve clinical workflow, decrease human resource costs and improve treatment choices. These characteristics could be especially helpful in the management of prostate cancer, with growing applications in diagnostic imaging, surgical interventions, skills training and assessment, digital pathology and genomics. Medicine must adapt to this changing world, and urologists, oncologists, radiologists and pathologists, as high-volume users of imaging and pathology, need to understand this burgeoning science and acknowledge that the development of highly accurate AI-based decision-support applications of ML will require collaboration between data scientists, computer researchers and engineers.

A Prospective Study on 18F-DCFPyL PSMA PET/CT Imaging in Biochemical Recurrence of Prostate Cancer.

18F-DCFPyL (2-(3-{1-carboxy-5-[(6-18F-fluoro-pyridine-3-carbonyl)-amino]-pentyl}-ureido)-pentanedioic acid), a prostate-specific membrane antigen-targeting radiotracer, has shown promise as a prostate cancer imaging radiotracer. We evaluated the safety, sensitivity, and impact on patient management of 18F-DCFPyL in the setting of biochemical recurrence of prostate cancer. Methods: Subjects with prostate cancer and biochemical recurrence after radical prostatectomy or curative-intent radiotherapy were included in this prospective study. The subjects underwent 18F-DCFPyL PET/CT imaging. The localization and number of lesions were recorded. The uptake characteristics of the 5 most active lesions were measured. A pre- and posttest questionnaire was sent to treating physicians to assess the impact on management. Results: One hundred thirty subjects were evaluated. 18F-DCFPyL PET/CT localized recurrent prostate cancer in 60% of cases with a prostate-specific antigen (PSA) level of ≥0.4 to <0.5, 78% with a level of ≥0.5 to <1.0, 72% with a level of ≥1.0 to <2.0, and 92% with a level of ≥2.0. Many subjects had few lesions (1 lesion in 40.8%, 2 in 8.5%, and 3 in 4.6%). The number of lesions was significantly related to PSA by ANOVA, but there was a large overlap in the PSA values for number of lesion categories. Total lesion uptake was also significantly related to PSA level. A change in treatment intent occurred in 65.5% of subjects, disease stage changed in 65.5%, and management plans changed in 87.3%. Twenty-two subjects reported mild adverse events after the scan; all resolved completely. Conclusion:18F-DCFPyL PET/CT is safe and sensitive for the localization of biochemical recurrence of prostate cancer. This test improved decision making for referring oncologists and changed management for most subjects.

Comparison of Artificial Intelligence Techniques to Evaluate Performance of a Classifier for Automatic Grading of Prostate Cancer From Digitized Histopathologic Images.

Importance: Proper evaluation of the performance of artificial intelligence techniques in the analysis of digitized medical images is paramount for the adoption of such techniques by the medical community and regulatory agencies. Objectives: To compare several cross-validation (CV) approaches to evaluate the performance of a classifier for automatic grading of prostate cancer in digitized histopathologic images and compare the performance of the classifier when trained using data from 1 expert and multiple experts. Design, Setting, and Participants: This quality improvement study used tissue microarray data (333 cores) from 231 patients who underwent radical prostatectomy at the Vancouver General Hospital between June 27, 1997, and June 7, 2011. Digitized images of tissue cores were annotated by 6 pathologists for 4 classes (benign and Gleason grades 3, 4, and 5) between December 12, 2016, and October 5, 2017. Patches of 192 µm2 were extracted from these images. There was no overlap between patches. A deep learning classifier based on convolutional neural networks was trained to predict a class label from among the 4 classes (benign and Gleason grades 3, 4, and 5) for each image patch. The classification performance was evaluated in leave-patches-out CV, leave-cores-out CV, and leave-patients-out 20-fold CV. The analysis was performed between November 15, 2018, and January 1, 2019. Main Outcomes and Measures: The classifier performance was evaluated by its accuracy, sensitivity, and specificity in detection of cancer (benign vs cancer) and in low-grade vs high-grade differentiation (Gleason grade 3 vs grades 4-5). The statistical significance analysis was performed using the McNemar test. The agreement level between pathologists and the classifier was quantified using a quadratic-weighted κ statistic. Results: On 333 tissue microarray cores from 231 participants with prostate cancer (mean [SD] age, 63.2 [6.3] years), 20-fold leave-patches-out CV resulted in mean (SD) accuracy of 97.8% (1.2%), sensitivity of 98.5% (1.0%), and specificity of 97.5% (1.2%) for classifying benign patches vs cancerous patches. By contrast, 20-fold leave-patients-out CV resulted in mean (SD) accuracy of 85.8% (4.3%), sensitivity of 86.3% (4.1%), and specificity of 85.5% (7.2%). Similarly, 20-fold leave-cores-out CV resulted in mean (SD) accuracy of 86.7% (3.7%), sensitivity of 87.2% (4.0%), and specificity of 87.7% (5.5%). Results of McNemar tests showed that the leave-patches-out CV accuracy, sensitivity, and specificity were significantly higher than those for both leave-patients-out CV and leave-cores-out CV. Similar results were observed for classifying low-grade cancer vs high-grade cancer. When trained on a single expert, the overall agreement in grading between pathologists and the classifier ranged from 0.38 to 0.58; when trained using the majority vote among all experts, it was 0.60. Conclusions and Relevance: Results of this study suggest that in prostate cancer classification from histopathologic images, patch-wise CV and single-expert training and evaluation may lead to a biased estimation of classifier's performance. To allow reproducibility and facilitate comparison between automatic classification methods, studies in the field should evaluate their performance using patient-based CV and multiexpert data. Some of these conclusions may be generalizable to other histopathologic applications and to other applications of machine learning in medicine.

Comparing diagnostic accuracy of luminal water imaging with diffusion-weighted and dynamic contrast-enhanced MRI in prostate cancer: A quantitative MRI study.

Luminal water imaging (LWI) is a new MRI T2 mapping technique that has been developed with the aim of diagnosis of prostate carcinoma (PCa). This technique measures the fractional amount of luminal water in prostate tissue, and has shown promising preliminary results in detection of PCa. To include LWI in clinical settings, further investigation on the accuracy of this technique is required. In this study, we compare the diagnostic accuracy of LWI with those of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) MRI in detection and grading of PCa. Fifteen patients with biopsy-proven PCa consented to participate in this ethics-board-approved prospective study. Patients were examined with LWI, DWI, and DCE sequences at 3 T prior to radical prostatectomy. Maps of MRI parameters were generated and registered to whole-mount histology. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic accuracy of individual and combined MR parameters. Correlation with Gleason score (GS) was evaluated using Spearman's rank correlation test. The results show that area under the ROC curve (AUC) obtained from LWI was equal to or higher than the AUC obtained from DWI, DCE, or their combination, in peripheral zone (0.98 versus 0.90, 0.89, and 0.91 respectively), transition zone (0.99 versus 0.98, n/a, and 0.98), and the entire prostate (0.85 versus 0.81, 0.75, and 0.84). The strongest correlation with GS was achieved from LWI (ρ = -0.81 ± 0.09, P < 0.001). Results of this pilot study show that LWI performs equally well as, or better than, DWI and DCE in detection of PCa. LWI provides significantly higher correlation with GS than DWI and DCE. This technique can potentially be included in clinical MRI protocols to improve characterization of tumors. However, considering the small size of the patient population in this study, a further study with a larger cohort of patients and broader range of GS is required to confirm the findings and draw a firm conclusion on the applicability of LWI in clinical settings.

Automatic grading of prostate cancer in digitized histopathology images: Learning from multiple experts.

Prostate cancer (PCa) is a heterogeneous disease that is manifested in a diverse range of histologic patterns and its grading is therefore associated with an inter-observer variability among pathologists, which may lead to an under- or over-treatment of patients. In this work, we develop a computer aided diagnosis system for automatic grading of PCa in digitized histopathology images using supervised learning methods. Our pipeline comprises extraction of multi-scale features that include glandular, cellular, and image-based features. A number of novel features are proposed based on intra- and inter-nuclei properties; these features are shown to be among the most important ones for classification. We train our classifiers on 333 tissue microarray (TMA) cores that were sampled from 231 radical prostatectomy patients and annotated in detail by six pathologists for different Gleason grades. We also demonstrate the TMA-trained classifier's performance on additional 230 whole-mount slides of 56 patients, independent of the training dataset, by examining the automatic grading on manually marked lesions and randomly sampled 10% of the benign tissue. For the first time, we incorporate a probabilistic approach for supervised learning by multiple experts to account for the inter-observer grading variability. Through cross-validation experiments, the overall grading agreement of the classifier with the pathologists was found to be an unweighted kappa of 0.51, while the overall agreements between each pathologist and the others ranged from 0.45 to 0.62. These results suggest that our classifier's performance is within the inter-observer grading variability levels across the pathologists in our study, which are also consistent with those reported in the literature.

Unhealthy Behaviors Among Canadian Men Are Predictors of Comorbidities: Implications for Clinical Practice.

Men's poor health behaviors are an increasingly prevalent issue with long-term consequences. This study broadly samples Canadian men to obtain information regarding health behaviors as a predictor of downstream medical comorbidities. A survey of Canadian men included questions regarding demographics, comorbidities, and health behaviors (smoking and alcohol consumption, sleep and exercise behaviors, and dietary habits). Health behaviors were classified as either healthy or unhealthy based upon previous studies and questionnaire thresholds. Multivariate regression was performed to determine predictors for medical comorbidities. The 2,000 participants were aged 19-94 (median 48, interquartile range 34-60). Approximately half (47.4%) were regular smokers, 38.7% overused alcohol, 53.9% reported unhealthy sleep, 48.9% had low levels of exercise, and 61.8% had unhealthy diets. On multivariate analysis, regular smoking predicted heart disease (OR 2.08, p < .01), elevated cholesterol (OR 1.35, p = .02), type 2 diabetes (OR 1.57, p = .02), osteoarthritis (OR 1.43, p = .04), and depression (OR 1.62, p < .01). Alcohol overuse predicted hypertension (OR 1.40, p < .01) and protected against type 2 diabetes (OR 0.61, p < .01). Unhealthy sleep predicted hypertension (OR 1.46, p < .01), erectile dysfunction (OR 1.50, p = .04), and depression (OR 1.87, p < .01). Low levels of exercise predicted hypertension (OR 1.30, p = .03) and elevated cholesterol (OR 1.27, p = .05). Finally, unhealthy diet predicted depression (OR 1.65, p < .01). This study confirms the association of poor health behaviors and comorbidities common to middle-aged and older men. The results emphasize the potential scope of targeted gender-sensitized public awareness campaigns and interventions to reduce common male disease, morbidity, and mortality.

Assessment of the need for DCE MRI in the detection of dominant lesions in the whole gland: Correlation between histology and MRI of prostate cancer.

The purpose of this study was to evaluate the utility of dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) in the detection of dominant prostate tumors with multi-parametric MRI of the whole gland. Combined diffusion tensor imaging (DTI) and DCE MRI from 16 patients with biopsy-proven prostate cancer and no previous treatment were acquired with a 3.0-T MRI scanner prior to radical prostatectomy, and used to identify dominant tumors. MRI results were validated by whole-mount histology. Paired t-test and Wilcoxon test, logistic generalized linear mixed effect models and receiver operating characteristic (ROC) analyses were used for the estimation of the statistical significance of the results. In the peripheral zone (PZ), the areas under the ROC curve (ROC-AUC) were 0.98 (sensitivity, 96%; specificity, 98%) for DTI, 0.96 (sensitivity, 92%; specificity, 97%) for DCE and 0.99 (sensitivity, 98%; specificity, 98%) for DTI + DCE. In the entire prostate, the ROC-AUC values were 0.96 (sensitivity, 84%; specificity, 95%) for DTI, 0.87 (sensitivity, 45%; specificity, 94%) for DCE and 0.96 (sensitivity, 88%; specificity, 98%) for DTI + DCE. The increase in ROC-AUC by the addition of DCE was not statistically significant in either PZ or the entire prostate. The results of this study have shown that DTI identified dominant tumors with high accuracy in both PZ and the entire prostate, whereas the inclusion of DCE MRI had no significant impact on the identification of either PZ or entire prostate dominant lesions. Our results suggest that the inclusion of DCE MRI may not increase the accuracy of dominant lesion detection, allowing for faster, better tolerated imaging studies.