BACKGROUND: Corpora amylacea (CAM), in benign prostatic acini, contain acute-phase proteins. Do CAM coincide with carcinoma? METHODS: Within 270 biopsies, 83 prostatectomies, and 33 transurethral resections (TURs), CAM absence was designated CAM 0; corpora in less than 5% of benign acini: CAM 1; in 5% to 25%: CAM 2; in more than 25%: CAM 3. CAM were compared against carcinoma presence, clinicopathologic findings, and grade groups (GG) 1 to 2 vs 3 to 5. The frequency of CAM according to anatomic zone was counted. A pilot study was conducted using paired initial benign and repeat biopsies (33 benign, 24 carcinoma). RESULTS: A total of 68.9% of biopsies, 96.4% of prostatectomies, and 66.7% of TURs disclosed CAM. CAM ≥1 was common at an older age (P = .019). In biopsies, 204 cases (75%) had carcinoma; and CAM of 2 to 3 (compared to 0-1) were recorded in 25.0% of carcinomas but only 7.4% of benign biopsies (P = .005; odds ratio [OR] = 5.1). CAM correlated with high percent Gleason pattern 3, low GG (P = .035), and chronic inflammation (CI). CI correlated inversely with carcinoma (P = .003). CAM disclosed no association with race, body mass index, serum prostate specific antigen (PSA), acute inflammation (in biopsies), atrophy, or carcinoma volume. With CAM 1, the odds of GG 3 to 5 carcinoma, by comparison to CAM 0, decreased more than 2× (OR = 0.48; P = .032), with CAM 2, more than 3× (OR = 0.33; P = .005), and with CAM 3, almost 3× (OR = 0.39, P = .086). For men aged less than 65, carcinoma predictive model was: Score = (2 × age) + (5 × PSA) - (20 × degree of CAM); using our data, area under the ROC curve was 78.17%. When the transition zone was involved by cancer, it showed more CAM than in cases where it was uninvolved (P = .012); otherwise zonal distributions were similar. In the pilot study, CAM ≥1 predicted carcinoma on repeat biopsy (P < .05; OR = 8), as did CAM 2 to 3 (P < .0001; OR = 30). CI was not significant, and CAM retained significance after adjusting for CI. CONCLUSION: CAM correlate with carcinoma. Whether abundant CAM in benign biopsies adds value amidst high clinical suspicion, warrants further study.

There is a need to develop a novel analgesic for pain associated with interstitial cystitis/painful bladder syndrome (IC/PBS). The use of the conventional μ-opioid receptor agonists to manage IC/PBS pain is controversial due to adverse CNS effects. These effects are attenuated in benzylideneoxymorphone (BOM), a low-efficacy μ-opioid receptor agonist/δ-opioid receptor antagonist that attenuates thermal pain and is devoid of reinforcing effects. We hypothesize that BOM will inhibit bladder pain by attenuating responses of urinary bladder distension (UBD)-sensitive afferent fibers. Therefore, the effect of BOM was tested on responses of UBD-sensitive afferent fibers in L6 dorsal root from inflamed and non-inflamed bladder of rats. Immunohistochemical (IHC) examination reveals that following the induction of inflammation there were significant high expressions of μ, δ, and μ-δ heteromer receptors in DRG. BOM dose-dependently (1-10 mg/kg, i.v) attenuated mechanotransduction properties of these afferent fibers from inflamed but not from non-inflamed rats. In behavioral model of bladder pain, BOM significantly attenuated visceromotor responses (VMRs) to UBD only in inflamed group of rats when injected either systemically (10 mg/kg, i.v.) or locally into the bladder (0.1 ml of 10 mg/ml). Furthermore, oxymorphone (OXM), a high-efficacy μ-opioid receptor agonist, attenuated responses of mechanosensitive bladder afferent fibers and VMRs to UBD. Naloxone (10 mg/kg, i.v.) significantly reversed the inhibitory effects of BOM and OXM on responses of bladder afferent fibers and VMRs suggesting μ-opioid receptor-related analgesic effects of these compounds. The results reveal that a low-efficacy, bifunctional opioid-based compound can produce analgesia by attenuating mechanotransduction functions of afferent fibers innervating the urinary bladder.

Growth and differentiation factor 15 (GDF-15), also known as macrophage inhibitory cytokine 1 (MIC-1), may act as both a tumor suppressor and promotor and, by regulating NF-κB and macrophage signaling, promote early prostate carcinogenesis. To determine whether expression of these two inflammation-related proteins affect prostate cancer susceptibility, dual immunostaining of benign prostate biopsies for GDF-15 and NF-κB was done in a study of 503 case-control pairs matched on date, age, and race, nested within a historical cohort of 10,478 men. GDF-15 and NF-κB expression levels were positively correlated (r = 0.39; p < 0.0001), and both were significantly lower in African American (AA) compared with White men. In adjusted models that included both markers, the odds ratio (OR) for NF-κB expression was statistically significant, OR =0.87; p = 0.03; 95% confidence interval (CI) =0.77-0.99, while GDF-15 expression was associated with a nominally increased risk, OR =1.06; p = 0.27; 95% CI =0.96-1.17. When modeling expression levels by quartiles, the highest quartile of NF-κB expression was associated with almost a fifty percent reduction in prostate cancer risk (OR =0.51; p = 0.03; 95% CI =0.29-0.92). In stratified models, NF-κB had the strongest negative association with prostate cancer in non-aggressive cases (p = 0.03), older men (p = 0.03), and in case-control pairs with longer follow-up (p = 0.02). Risk associated with GDF-15 expression was best fit using nonlinear regression modeling where both first (p = 0.02) and second (p = 0.03) order GDF-15 risk terms were associated with significantly increased risk. This modeling approach also revealed significantly increased risk associated with GDF-15 expression for subsamples defined by AA race, aggressive disease, younger age, and in case-control pairs with longer follow-up. Therefore, although positively correlated in benign prostatic biopsies, NF-κB and GDF-15 expression appear to exert opposite effects on risk of prostate tumor development.

Purpose: Our study predictively maps epithelium density in magnetic resonance imaging (MRI) space while varying the ground truth labels provided by five pathologists to quantify the downstream effects of interobserver variability. Approach: Clinical imaging and postsurgical tissue from 48 recruited prospective patients were used in our study. Tissue was sliced to match the MRI orientation and whole-mount slides were stained and digitized. Data from 28 patients ( n = 33 slides) were sent to five pathologists to be annotated. Slides from the remaining 20 patients ( n = 123 slides) were annotated by one of the five pathologists. Interpathologist variability was measured using Krippendorffs alpha. Pathologist-specific radiopathomic mapping models were trained using a partial least-squares regression using MRI values to predict epithelium density, a known marker for disease severity. An analysis of variance characterized intermodel means difference in epithelium density. A consensus model was created and evaluated using a receiver operator characteristic classifying high grade versus low grade and benign, and was statistically compared to apparent diffusion coefficient (ADC). Results: Interobserver variability ranged from low to acceptable agreement (0.31 to 0.69). There was a statistically significant difference in mean predicted epithelium density values ( p < 0.001 ) between the five models. The consensus model outperformed ADC (areas under the curve = 0.80 and 0.71, respectively, p < 0.05 ). Conclusion: We demonstrate that radiopathomic maps of epithelium density are sensitive to the pathologist annotating the dataset; however, it is unclear if these differences are clinically significant. The consensus model produced the best maps, matched the performance of the best individual model, and outperformed ADC.

BACKGROUND: Diffusion-weighted imaging (DWI) is commonly used to detect prostate cancer, and a major clinical challenge is differentiating aggressive from indolent disease. PURPOSE: To compare 14 site-specific parametric fitting implementations applied to the same dataset of whole-mount pathologically validated DWI to test the hypothesis that cancer differentiation varies with different fitting algorithms. STUDY TYPE: Prospective. POPULATION: Thirty-three patients prospectively imaged prior to prostatectomy. FIELD STRENGTH/SEQUENCE: 3 T, field-of-view optimized and constrained undistorted single-shot DWI sequence. ASSESSMENT: Datasets, including a noise-free digital reference object (DRO), were distributed to the 14 teams, where locally implemented DWI parameter maps were calculated, including mono-exponential apparent diffusion coefficient (MEADC), kurtosis (K), diffusion kurtosis (DK), bi-exponential diffusion (BID), pseudo-diffusion (BID*), and perfusion fraction (F). The resulting parametric maps were centrally analyzed, where differentiation of benign from cancerous tissue was compared between DWI parameters and the fitting algorithms with a receiver operating characteristic area under the curve (ROC AUC). STATISTICAL TEST: Levenes test, P < 0.05 corrected for multiple comparisons was considered statistically significant. RESULTS: The DRO results indicated minimal discordance between sites. Comparison across sites indicated that K, DK, and MEADC had significantly higher prostate cancer detection capability (AUC range = 0.72-0.76, 0.76-0.81, and 0.76-0.80 respectively) as compared to bi-exponential parameters (BID, BID*, F) which had lower AUC and greater between site variation (AUC range = 0.53-0.80, 0.51-0.81, and 0.52-0.80 respectively). Post-processing parameters also affected the resulting AUC, moving from, for example, 0.75 to 0.87 for MEADC varying cluster size. DATA CONCLUSION: We found that conventional diffusion models had consistent performance at differentiating prostate cancer from benign tissue. Our results also indicated that post-processing decisions on DWI data can affect sensitivity and specificity when applied to radiological-pathological studies in prostate cancer. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 3.