Prostatic Lesions Research Articles

A nomogram for accurately predicting the pathological upgrading of prostate cancer, based on 68Ga‐PSMA PET/CT

To develop and validate a nomogram for preoperative predicting the pathological upgrading of prostate cancer (PCa). The prediction model was developed in a primary cohort that consisted of 208 PCa patients. All patients included in the study possessed both biopsy pathology specimens and radical prostatectomy pathology specimens, and completed the (68 Ga-prostate-specific membrane antigen [PSMA])positron emission tomography/computed tomography (PET/CT) detection. The R function "createDataPartition" was used in a 7:3 ratio to randomly divide the patients into training and validation cohorts. In the training cohort, the independent predictors of pathological upgrading of PCa were determined by univariate analysis, univariate regression analysis and multivariate regression analysis. Based on these independent predictors, a nomogram was developed, and its performance was evaluated by receiver operating characteristic (ROC) curve, area under the curve (AUC) and calibration curve of training cohort and validation cohort. The nomogram incorporated five independent predictors including prostate volume (PV), SUVmax of the 68 Ga-PSMA PET/CT examination on prostate lesions (SUVmax ), body mass index (BMI); percentage of cancer positive biopsy cores(PPC) and biopsy International Society of Urological Pathology (ISUP) grade. The nomogram showed good diagnostic accuracy for the pathological upgrading of both the training cohort and the validation cohort (AUC = 0.818 and 0.806, respectively). The calibration curves for the two cohorts both showed optimal agreement between nomogram prediction and actual observation. We developed and validated a nomogram to accurately predict the risk of pathological upgrading after radical PCa surgery, which can provide accurate basis for therapeutic schedule and prognostic data of PCa patients.

Experimental investigation of dynamic real-time rotation-including dose reconstruction during prostate tracking radiotherapy.

BackgroundHypofractionation in prostate radiotherapy is of increasing interest. Steep dose gradients and a large weight on each individual fraction emphasize the need for motion management. Real‐time motion management techniques such as multileaf collimator (MLC) tracking or couch tracking typically adjust for translational motion while rotations remain uncompensated with unknown dosimetric impact.PurposeThe purpose of this study is to demonstrate and validate dynamic real‐time rotation‐including dose reconstruction during radiotherapy experiments with and without MLC and couch tracking.MethodsReal‐time dose reconstruction was performed using the in‐house developed software DoseTracker. DoseTracker receives streamed target positions and accelerator parameters during treatment delivery and uses a pencil beam algorithm with water density assumption to reconstruct the dose in a moving target. DoseTracker's ability to reconstruct motion‐induced dose errors in a dynamically rotating and translating target was investigated during three different scenarios: (1) no motion compensation and translational motion correction with (2) MLC tracking and (3) couch tracking.In each scenario, dose reconstruction was performed online and in real time during delivery of two dual‐arc volumetric‐modulated arc therapy prostate plans with a prescribed fraction dose of 7 Gy to the prostate and simultaneous intraprostatic lesion boosts with doses of at least 8 Gy, but up to 10 Gy as long as the organs at risk dose constraints were fulfilled. The plans were delivered to a pelvis phantom that replicated three patient‐measured motion traces using a rotational insert with 21 layers of EBT3 film spaced 2.5 mm apart. DoseTracker repeatedly calculated the actual motion‐including dose increment and the planned static dose increment since the last calculation in 84 500 points in the film stack. The experiments were performed with a TrueBeam accelerator with MLC and couch tracking based on electromagnetic transponders embedded in the film stack.The motion‐induced dose error was quantified as the difference between the final cumulative dose with motion and without motion using the 2D 2%/2 mm γ‐failure rate and the difference in dose to 95% of the clinical target volume (CTV ΔD 95%) and the gross target volume (GTV ΔD 95%) as well as the difference in dose to 0.1 cm3 of the urethra, bladder, and rectum (ΔD 0.1CC). The motion‐induced errors were compared between dose reconstructions and film measurements.ResultsThe dose was reconstructed in all calculation points at a mean frequency of 4.7 Hz. The root‐mean‐square difference between real‐time reconstructed and film‐measured motion‐induced errors was 3.1%‐points (γ‐failure rate), 0.13 Gy (CTV ΔD 95%), 0.23 Gy (GTV ΔD 95%), 0.19 Gy (urethra ΔD 0.1CC), 0.09 Gy (bladder ΔD 0.1CC), and 0.07 Gy (rectum ΔD 0.1CC).ConclusionsIn a series of phantom experiments, online real‐time rotation‐including dose reconstruction was performed for the first time. The calculated motion‐induced errors agreed well with film measurements. The dose reconstruction provides a valuable tool for monitoring dose delivery and investigating the efficacy of advanced motion‐compensation techniques in the presence of translational and rotational motion.

Characterization of stage-specific tumor progression in TMPRSS2-ERG (fusion)-driven and non-fusion-driven prostate cancer in GEM models.

In the present study, we performed a comparative stage-specific pathological and molecular marker evaluation of TMPRSS2-ERG fusion and PTEN loss-driven (TMPRSS2-ERG. Ptenflox/flox ) versus non-fusion-driven prostate tumorigenesis (Hi-Myc) in mice. Anterior, ventral, and dorsolateral prostates were collected from mice at different ages (or time points post-Cre induction). Results indicated that growth and progression of prostatic intraepithelial lesions to adenocarcinoma stages occurred in both mice models albeit at different rates. In the TMPRSS2-ERG. Ptenflox/flox mice, the initiation of tumorigenesis was slow, but subsequent progression through different stages became increasingly faster. Adenocarcinoma stage was reached early on; however, no high-grade undifferentiated tumors were observed. Conversely, in the Hi-Myc+/- mice, tumorigenesis initiation was rapid; however, progression through different stages was relatively slower and it took a while to reach the more aggressive phenotype stage. Nevertheless, at the advanced stages in the Hi-Myc+/- mice, high-grade undifferentiated tumors were observed compared to the later stage tumors observed in the fusion-driven TMPRSS2-ERG. Ptenflox/flox mice. These results were corroborated by the stage specific-pattern in the molecular expression of proliferation markers (PCNA and c-Myc); androgen receptor (AR); fusion-resultant overexpression of ERG; Prostein (SLC45-A3); and angiogenesis marker (CD-31). Importantly, there was a significant increase in immune cell infiltrations, which increased with the stage of tumorigenesis, in the TMPRSS2-ERG fusion-positive tumors relative to fusion negative tumors. Together, these findings are both novel and highly significant in establishing a working preclinical model for evaluating the efficacy of interventions during different stages of tumorigenesis in TMPRSS2-ERG fusion-driven PCa.

The Detection Performance of 18 F-Prostate-Specific Membrane Antigen-1007 PET/CT in Primary Prostate Cancer : A Systemic Review and Meta-analysis.

Multiple tools are now available to determine the requirement for a biopsy to diagnose prostate cancer, and PET/CT with radiolabeled prostate-specific membrane antigen (PSMA)-targeting radiotracers has been recommended for detecting primary prostate cancer. Particularly, the radiotracer 18 F-PSMA-1007 was found to be more favorable for primary tumors compared with other PSMA-targeting radiotracers because of its low clearance via the urinary tract and better image resolution. Thus, we performed a systematic review and meta-analysis to more accurately evaluate the detection performance of 18 F-PSMA-1007 PET/CT in primary prostate cancer patients. An update on the databases of PubMed/MEDLINE, EMBASE, and Cochrane Library for comprehensive literature search was performed on September 30, 2021. The pooling detection rate was calculated on a per-patient basis. The pooling median of the SUV max was analyzed from the included studies. Furthermore, the positive predictive value of 18 F-PSMA-1007 PET/CT with pathologic lesions was analyzed using the criterion standard. Twelve studies (540 patients total) were included in the meta-analysis. The overall pooling detection rate of 18 F-PSMA-1007 per patient was 94%, and the pooling median of SUV max located at the intraprostate tumor was 16 (range, 3.7-77.7). The positive predictive value of 18 F-PSMA-1007 per lesion with histopathological validation was 0.90, detecting regional lymph node metastasis was 0.94, and detecting localized prostatic tumors was 0.84. In the current meta-analysis, we revealed the excellent performance of 18 F-PSMA-1007 to detect localized prostatic tumor lesions and regional lymph node metastasis. Moreover, the uptake of localized tumors in primary prostate cancer was nearly liver uptake and may be considered a suspicious malignancy if it was equal to or greater than the liver uptake.

SIRT1 inhibition-induced senescence as a strategy to prevent prostate cancer progression.

Emerging evidence suggests an important role for SIRT1, a nicotinamide adenine dinucleotide (NAD)-dependent deacetylase in cancer development, progression and therapeutic resistance; making it a viable therapeutic target. Here, we examined the impact of resveratrol-mediated pharmacological activation of SIRT1 on the progression of HGPIN lesions (using the Pten-/- mouse model) and on prostate tumor development (using an orthotopic model of prostate cancer cells stably silenced for SIRT1). We show that precise SIRT1 modulation could benefit both cancer prevention and treatment. Positive effect of SIRT1 activation can prevent Pten deletion-driven development of HGPIN lesions in mice if resveratrol is administered early (pre-cancer stage) with little to no benefit after the establishment of HGPIN lesions or tumor cell implantation. Mechanistically, our results show that under androgen deprivation conditions, SIRT1 inhibition induces senescence as evidenced by decreased gene signature associated with negative regulators of senescence and increased senescence-associated β-galactosidase activity. Furthermore, pharmacological inhibition of SIRT1 potentiated growth inhibitory effects of clinical androgen receptorblockade agents and radiation. Taken together, our findings provide an explanation for the discrepancy regarding the role of SIRT1 in prostate tumorigenesis. Our results reveal that the bifurcated roles for SIRT1 may occur in stage and context-dependent fashion by functioning in an antitumor role in prevention of early-stage prostate lesion development while promoting tumor development and disease progression post-lesion development. Clinically, these data highlight the importance of precise SIRT1 modulation to provide benefits for cancer prevention and treatment including sensitization to conventional therapeutic approaches.

A deep learning masked segmentation alternative to manual segmentation in biparametric MRI prostate cancer radiomics

ObjectivesTo determine the value of a deep learning masked (DLM) auto-fixed volume of interest (VOI) segmentation method as an alternative to manual segmentation for radiomics-based diagnosis of clinically significant (CS) prostate cancer (PCa) on biparametric magnetic resonance imaging (bpMRI).Materials and methodsThis study included a retrospective multi-center dataset of 524 PCa lesions (of which 204 are CS PCa) on bpMRI. All lesions were both semi-automatically segmented with a DLM auto-fixed VOI method (averaging < 10 s per lesion) and manually segmented by an expert uroradiologist (averaging 5 min per lesion). The DLM auto-fixed VOI method uses a spherical VOI (with its center at the location of the lowest apparent diffusion coefficient of the prostate lesion as indicated with a single mouse click) from which non-prostate voxels are removed using a deep learning–based prostate segmentation algorithm. Thirteen different DLM auto-fixed VOI diameters (ranging from 6 to 30 mm) were explored. Extracted radiomics data were split into training and test sets (4:1 ratio). Performance was assessed with receiver operating characteristic (ROC) analysis.ResultsIn the test set, the area under the ROC curve (AUCs) of the DLM auto-fixed VOI method with a VOI diameter of 18 mm (0.76 [95% CI: 0.66–0.85]) was significantly higher (p = 0.0198) than that of the manual segmentation method (0.62 [95% CI: 0.52–0.73]).ConclusionsA DLM auto-fixed VOI segmentation can provide a potentially more accurate radiomics diagnosis of CS PCa than expert manual segmentation while also reducing expert time investment by more than 97%.Key Points• Compared to traditional expert-based segmentation, a deep learning mask (DLM) auto-fixed VOI placement is more accurate at detecting CS PCa.• Compared to traditional expert-based segmentation, a DLM auto-fixed VOI placement is faster and can result in a 97% time reduction.• Applying deep learning to an auto-fixed VOI radiomics approach can be valuable.

Treatment response in prostatic neoplastic lesions using CyberKnife (stereotactic body radiation therapy)

Objective: To evaluate the treatment response of CyberKnife stereotactic radiotherapy in patients with prostatic neoplastic lesions.Patients and methods: This prospective observational study was conducted at Radiology and Cyberknife Robotic Radiosurgery Department of Jinnah Post Graduate Medical Centre (JPMC), Karachi from 22nd June 2019 to 21st June 2020. Males with biopsy-proven prostatic adenocarcinoma with age 55 years or more having Gleason's score of 6 to 8, clinical stage of T1 to T2C, and prostate-specific antigen (PSA) of ≤30 ng/ml were consecutively enrolled. Detailed information regarding PSA concentration, Gleason score, T stage, risk group and ADT (Androgen Deprivation Therapy) usage were noted which were given to high risk patients only for 9 months. Drop in the PSA (biochemical marker) was assessed at baseline, at 3 months and 6 months follow-up.Results: The median age of the patients was 65 years. The overall median PSA level was 2.7 (0.86-7.3) ng/ml. Majority 49 (90.7%) patients presented with T2 N0 M0 TNM status while only 5 (9.3%) patients presented with T1 N0 M0 TNM status. There were 5 (9.3%) patients with high risk, 26 (48.1%) with intermediate risk, and 23 (42.6%) with low risk. ADT was received by 5 (9.3%) patients. The median PSA at baseline was 10.1 (6.9-18.1) ng/ml which significantly drops to 1.6 (0.8-3.6) ng/ml at 3rd months, and 0.4 (0.2-1.2) at 6th months (p-value &lt;0.01).Conclusion: The findings showed an adequate treatment response of CyberKnife stereotactic radiotherapy of patients with prostatic neoplastic lesions.

ProstAttention-Net: A deep attention model for prostate cancer segmentation by aggressiveness in MRI scans

Multiparametric magnetic resonance imaging (mp-MRI) has shown excellent results in the detection of prostate cancer (PCa). However, characterizing prostate lesions aggressiveness in mp-MRI sequences is impossible in clinical practice, and biopsy remains the reference to determine the Gleason score (GS). In this work, we propose a novel end-to-end multi-class network that jointly segments the prostate gland and cancer lesions with GS group grading. After encoding the information on a latent space, the network is separated in two branches: 1) the first branch performs prostate segmentation 2) the second branch uses this zonal prior as an attention gate for the detection and grading of prostate lesions. The model was trained and validated with a 5-fold cross-validation on a heterogeneous series of 219 MRI exams acquired on three different scanners prior prostatectomy. In the free-response receiver operating characteristics (FROC) analysis for clinically significant lesions (defined as GS>6) detection, our model achieves 69.0%±14.5% sensitivity at 2.9 false positive per patient on the whole prostate and 70.8%±14.4% sensitivity at 1.5 false positive when considering the peripheral zone (PZ) only. Regarding the automatic GS group grading, Cohen's quadratic weighted kappa coefficient (κ) is 0.418±0.138, which is the best reported lesion-wise kappa for GS segmentation to our knowledge. The model has encouraging generalization capacities with κ=0.120±0.092 on the PROSTATEx-2 public dataset and achieves state-of-the-art performance for the segmentation of the whole prostate gland with a Dice of 0.875±0.013. Finally, we show that ProstAttention-Net improves performance in comparison to reference segmentation models, including U-Net, DeepLabv3+ and E-Net. The proposed attention mechanism is also shown to outperform Attention U-Net.

Target Specific Uptake of a Newly Synthesized Radiolabeled 5α-Reductase Inhibitor "Tc-99m-17-Oxo-17a-Aza-D-Homo-5-Androsten-3β-yl Phenoxyacetate (Tc-99m-17a-Aza Steroid)" in Rat Prostatic Neoplastic Lesions.

Objective:Considering the 5α-reductase (5AR) inhibitory activity of the oximes and the importance of the ester group in increasing the anti-androgenic property, we reasoned to synthesize a compound having a lactam group in ring D and an ester group at the 3 β position of the androsterone nucleus. The study aims to radiolabel 17-oxo-17a-aza-D-homo-5-androsten-3β-yl phenoxyacetate (17a-aza steroid) with Tc-99m to evaluate its targeted uptake in experimentally induced prostate carcinogenesis in rats.Materials and Methods:The prediction of the optimal interaction and binding affinity of Tc-99m-17-oxo-17a-aza-D-homo-5-androsten-3 β-ylphenoxyacetate (Tc-99m-17a-aza steroid) toward 5AR inhibitor was done using Biopredicta Vlife MDS tool. Tc-99m-17a-aza steroid was developed by direct radiolabeling protocol. The radio-pharmacological characteristics (serum stability, plasma protein-binding ability, and lipophilicity) of the complex were evaluated. Further, the bio-distribution studies of the complex were performed in rats with experimentally induced prostate carcinogenesis.Results:The in-silico analysis exhibits favorable binding of Tc-99m-17a-aza toward 5AR with D score-130.97. The radiochemical purity of Tc-99m-17a-aza was 96.79%. The radio-complex maintained stability in the rat serum for a period of 6 h (hours). Plasma protein binding and Log Po/w value were observed to be 86.23 ± 7.08% and 0.118 ± 0.045, respectively. A significantly enhanced percent-specific uptake was observed in the prostate of rats with induced prostate carcinogenesis.Conclusion:The study concludes that Tc-99m-17a-aza exhibits prostate specificity and can be explored further for its potential as a radionuclide imaging probe.

T2 mapping for the characterization of prostate lesions

PurposePurpose of this study is to evaluate the diagnostic accuracy of quantitative T2/ADC values in differentiating between PCa and lesions showing non-specific inflammatory infiltrates and atrophy, features of chronic prostatitis, as the most common histologically proven differential diagnosis.MethodsIn this retrospective, single-center cohort study, we analyzed 55 patients suspected of PCa, who underwent mpMRI (3T) including quantitative T2 maps before robot-assisted mpMRI-TRUS fusion prostate biopsy. All prostate lesions were scored according to PI-RADS v2.1. Regions of interest (ROIs) were annotated in focal lesions and normal prostate tissue. Quantitative mpMRI values from T2 mapping and ADC were compared using two-tailed t tests. Receiver operating characteristic curves (ROCs) and cutoff were calculated to differentiate between PCa and chronic prostatitis.ResultsFocal lesions showed significantly lower ADC and T2 mapping values than normal prostate tissue (p < 0.001). PCa showed significantly lower ADC and T2 values than chronic prostatitis (p < 0.001). ROC analysis revealed areas under the receiver operating characteristic curves (AUCs) of 0.85 (95% CI 0.74–0.97) for quantitative ADC values and 0.84 (95% CI 0.73–0.96) for T2 mapping. A significant correlation between ADC and T2 values was observed (r = 0.70; p < 0.001).ConclusionT2 mapping showed high diagnostic accuracy for differentiating between PCa and chronic prostatitis, comparable to the performance of ADC values.

Role of T2 Textural Analysis of Prostate Lesion: A Retrospective Study

Introduction: Prostate cancer is diagnosed in two-thirds of instances in the world's more developed regions. Prostate cancer was detected in 180,890 new cases in the United States in 2016, according to the American Cancer Society. One out of every six men is projected to develop prostate cancer at some point in their lives. The study's major purpose was to develop a textural analysis-based classifier to differentiate between benign and malignant prostate tumors using MRI-T2WI. Materials and method: The retrospective study was conducted in the department of radiology in KKUH. Total 93 lesions from prostate cases were performed in KKUH from 2015 to 2017. About 75 lesions of 48 patients were included in this study. Eleven haralick features from region of intrests (ROIs) were extracted. After matching them with traces done by consultants in Profuse software, which was utilized for image-guided biopsy, digital rectal examination (DRE), prior biopsy (Prior bx) lesions were traced using ImageJ (MRI-ultrasound fusion). Weka software used this to create a classifier that distinguishes between malignant and benign tumors. Result: The age of total 48 patients was in the interquartile range of 59.0-70.0, with an average of 64.4 years. The PSA was observed an average of 22.5 with an SD of 50.5 and an interquartile of 10.0. The mean size of the prostrate was 3.2 cm with SD 1.9. Among 48 patients Digital rectal examination (DRE) 8 (16.7%) and 40 (83.3%), Prior biopsy (PRIOR BX) 2 (4.2%) and 46 (95.8%), PI-RADS 22 (45.8%) and 26 (54.2%) were observed positive and negative respectively. In DRE, 88% sensitivity 55% specificity with PSA 9.75 (p-value 0.008) were observed. 100% of sensitivity, 41% specificity with PSA 8.19 (p-value 0.897) were found in PRIOR BX, but in MRI, 55% of sensitivity 69% specificity with PSA 10.70 (p-value 0.107) were observed. Conclusion: T2 texture analysis is good in classifying prostate lesions with acceptable sensitivity and specificity. T2W MRI-based textural analysis agreed with pathological findings from many institutions and was sensitive to underlying pathological differences between low- and intermediate/high-grade prostate cancers. Actors in the diagnostic performance, such as DWI/ADC and perfusion, histogram parameters, and other features with distinct orientations and lengths, could help doctors discriminate benign and malignant prostate nodules, allowing for more efficient and precise clinical decisions. Keywords: Prostrate lesion, MRI, textural analysis, cancer

Managing argatroban in heparin-induced thrombocytopenia: Aretrospective analysis of 729 treatment days in 32 patients with confirmed heparin-induced thrombocytopenia.

Managing argatroban in heparin-induced thrombocytopenia: Aretrospective analysis of 729 treatment days in 32 patients with confirmed heparin-induced thrombocytopenia.

CUT-OFF VALUES OF PROSTATE SPECIFIC ANTIGEN DENSITY– AN EFFECTIVE SCREENING MARKER BEFORE PROSTATE BIOPSY

OBJECTIVE: To determine cut-off values for prostate specific antigen density (PSAD) in diagnosing prostate carcinoma in symptomatic patients. METHODS: This cross sectional, observational study conducted at Department of Chemical Pathology and Endocrinology, Armed Forces Institute of Pathology, Rawalpindi, Pakistan from June 2020 to May 2021. Symptomatic patients (309) having prostatic enlargement on ultrasound were selected through consecutive sampling. All the patients underwent prostate biopsy for histopathological diagnosis. Prostate specific antigen density was calculated and compared between different age groups and different diseases. ROC curve was constructed and area under the curve was calculated to find out cut-off values value for PSAD. Sensitivity, specificity and accuracy were calculated at the cut-off values. RESULTS: Among 309 patients of median age was 68 years (IQR 43 – 75). There was a significant difference of PSAD in different age groups (p&lt;0.001) and diseases like prostate carcinoma, benign prostatic hyperplasia and other prostatic disorders. PSAD had AUC of 0.878 at cut-off value of 0.135 ng/ml where sensitivity was 100%. A higher cut-off 0.20 ng/ml was suggested in younger age group as compared to the old age group where cut-off was found 0.135. CONCLUSION: Using PSAD as part of evaluation profile for prostate lesion, number of unnecessary biopsies can be significantly decreased. PSAD cut-off to aid in decision of invasive prostate biopsy is suggested to be 0.135 ng/ml with close biochemical follow up afterwards.

Biomechanical modelling of the pelvic system: improving the accuracy of the location of neoplasms in MRI-TRUS fusion prostate biopsy

BackgroundAn accurate knowledge of the relocation of prostate neoplasms during biopsy is of great importance to reduce the number of false negative results. Prostate neoplasms are visible in magnetic resonance images (MRI) but it is difficult for the practitioner to locate them at the time of performing a transrectal ultrasound (TRUS) guided biopsy. In this study, we present a new methodology, based on simulation, that predicts both prostate deformation and lesion migration during the biopsy.MethodsA three-dimensional (3-D) anatomy model of the pelvic region, based on medical images, is constructed. A finite element (FE) numerical simulation of the organs motion and deformation as a result of the pressure exerted by the TRUS probe is carried out using the Code-Aster open-source computer software. Initial positions of potential prostate lesions prior to biopsy are taken into consideration and the final location of each lesion is targeted in the FE simulation output.ResultsOur 3-D FE simulations show that the effect of the pressure exerted by the TRUS probe is twofold as the prostate experiences both a motion and a deformation of its original shape. We targeted the relocation of five small prostate lesions when the TRUS probe exerts a force of 30 N on the rectum inner wall. The distance travelled by these lesions ranged between 5.6 and 13.9 mm.ConclusionsOur new methodology can help to predict the location of neoplasms during a prostate biopsy but further studies are needed to validate our results. Moreover, the new methodology is completely developed on open-source software, which means that its implementation would be affordable to all healthcare providers.

A prognostic hypoxia gene signature with low heterogeneity within the dominant tumour lesion in prostate cancer patients

BackgroundGene signatures measured in a biopsy have been proposed as hypoxia biomarkers in prostate cancer. We assessed a previously developed signature, and aimed to determine its relationship to hypoxia and its heterogeneity within the dominant (index) lesion of prostate cancer.MethodsThe 32-gene signature was assessed from gene expression data of 141 biopsies from the index lesion of 94 patients treated with prostatectomy. A gene score calculated from the expression levels was applied in the analyses. Hypoxic fraction from pimonidazole immunostained whole-mount and biopsy sections was used as reference standard for hypoxia.ResultsThe gene score was correlated with pimonidazole-defined hypoxic fraction in whole-mount sections, and the two parameters showed almost equal association with clinical markers of tumour aggressiveness. Based on the gene score, incorrect classification according to hypoxic fraction in whole-mount sections was seen in one third of the patients. The incorrect classifications were apparently not due to intra-tumour heterogeneity, since the score had low heterogeneity compared to pimonidazole-defined hypoxic fraction in biopsies. The score showed prognostic significance in uni-and multivariate analysis in independent cohorts.ConclusionsOur signature from the index lesion reflects tumour hypoxia and predicts prognosis in prostate cancer, independent of intra-tumour heterogeneity in pimonidazole-defined hypoxia.

The ETS Homologous Factor (EHF) Represents a Useful Immunohistochemical Marker for Predicting Prostate Cancer Metastasis.

The main aim of this study was to investigate the risk of prostate cancer metastasis formation associated with the expression of ETS homologous factor (EHF) in a cohort of bioptic samples. To this end, the expression of EHF was evaluated in a cohort of 152 prostate biopsies including primary prostate cancers that developed metastatic lesions, primary prostate cancers that did not develop metastasis, and benign lesions. Data here reported EHF as a candidate immunohistochemical prognostic biomarker for prostate cancer metastasis formation regardless of the Gleason scoring system. Indeed, our data clearly show that primary lesions with EHF positive cells ≥40% had a great risk of developing metastasis within five years from the first diagnosis. Patients with these lesions had about a 40-fold increased risk of developing metastasis as compared with patients with prostate lesions characterized by a percentage of EHF positive cells ≤30%. In conclusion, the immunohistochemical evaluation of EHF could significantly improve the management of prostate cancer patients by optimizing the diagnostic and therapeutic health procedures and, more important, ameliorating the patient’s quality of life.

Bisphenol A exposure triggers the malignant transformation of prostatic hyperplasia in beagle dogs via cfa-miR-204/KRAS axis

The prostatic toxicity of bisphenol A (BPA) exposure is mainly associated with hormonal disturbances, thus interfering with multiple signal pathways and increasing the susceptibility to prostatic lesions. This study concentrates predominantly on the potential effect and mechanisms of low-dose BPA exposure on prostates in adult beagle dogs. The dogs were orally given BPA (2, 6, 18 μg/kg/day) and vehicle for 8 weeks, followed by blood collection and dissection. The ascended organ coefficient and volume of prostates, thickened epithelium, as well as histopathological observation have manifested that BPA exposure could trigger the aberrant prostatic hyperplasia in beagle dogs. Hormone level detection revealed that the ratios of estradiol (E2) to testosterone (T) (E2/T) and prolactin (PRL) to T (PRL/T) were up-regulated in the serum from BPA group. Based on microRNA (miRNA) microarray screening and functional enrichment analysis, BPA might facilitate the progression of prostate tumorigenesis in beagle dogs via cfa-miR-204 and its downstream target KRAS oncogene. Subsequently, the overexpression of KRAS, CDKN1A, MAPK1, VEGFA, BCL2 and PTGS2 was validated. These findings provide a series of underlying targets for preventing the initiation and metastasis of BPA-induced prostatic hyperplasia and tumorigenesis, while the regulatory relationship headed with KRAS requires further investigation.

Prostate MRI using a rigid two-channel phased-array endorectal coil: comparison with phased array coil acquisition at 3\u2009T

BackgroundTo compare image quality, lesion detection and patient comfort of 3T prostate MRI using a combined rigid two-channel phased-array endorectal coil and an external phased-array coil (ERC-PAC) compared to external PAC acquisition in the same patients.MethodsThirty three men (mean age 65.3y) with suspected (n = 15) or biopsy-proven prostate cancer (PCa, n = 18) were prospectively enrolled in this exploratory study. 3T prostate MRI including T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) was performed using an ERC-PAC versus PAC alone, in random order. Image quality, lesion detection and characterization (biparametric PI-RADSv2.1) were evaluated by 2 independent observers. Estimated signal-to-noise ratio (eSNR) was measured in identified lesions and the peripheral zone (PZ). Patient comfort was assessed using a questionnaire. Data were compared between sequences and acquisitions. Inter/intra-observer agreement for PI-RADS scores was evaluated.ResultsTwenty four prostate lesions (22 PCa) were identified in 20/33 men. Superior image quality was found for ERC-PAC compared to PAC for T2WI for one observer (Obs.1, p < 0.03) and high b-value DWI for both observers (p < 0.05). The sensitivity of PI-RADS for lesion detection for ERC-PAC and PAC acquisitions was 79.2 and 75% for Obs.1, and 79.1 and 66.7%, for Obs.2, without significant difference for each observer (McNemar p-values ≥0.08). Inter−/intra-observer agreement for PI-RADS scores was moderate-to-substantial (kappa = 0.52–0.84). Higher eSNR was observed for lesions and PZ for T2WI and PZ for DWI using ERC-PAC (p < 0.013). Most patients (21/33) reported discomfort at ERC insertion.ConclusionDespite improved image quality and eSNR using the rigid ERC-PAC combination, no significant improvement in lesion detection was observed, therefore not supporting the routine use of ERC for prostate MRI.

Tumor Connectomics: Mapping the Intra-Tumoral Complex Interaction Network Using Machine Learning.

Simple SummaryUnderstanding the complex network of high-level relationships within tumors and between surrounding tissue is challenging and not fully understood. Our findings demonstrate that the tumor connectomics framework (TCF) models different networks within the tumors and surrounding tissue that are detectable on imaging. The TCF extracts a set of graph network features for each lesion and provides insight into the different types of interactions of a cancer under investigation. These TCF networks are visualized with the radiological parameters and overlaid onto the structural images for better understanding of the global and regional connections within the lesion and surrounding tissue. This information could be used for improved cancer therapeutic targeting in neoplasms and response within different organ systems.The high-level relationships that form complex networks within tumors and between surrounding tissue is challenging and not fully understood. To better understand these tumoral networks, we developed a tumor connectomics framework (TCF) based on graph theory with machine learning to model the complex interactions within and around the tumor microenvironment that are detectable on imaging. The TCF characterization model was tested with independent datasets of breast, brain, and prostate lesions with corresponding validation datasets in breast and brain cancer. The TCF network connections were modeled using graph metrics of centrality, average path length (APL), and clustering from multiparametric MRI with IsoSVM. The Matthews Correlation Coefficient (MCC), Area Under the Curve-ROC, and Precision-Recall (AUC-ROC and AUC-PR) were used for statistical analysis. The TCF classified the breast and brain tumor cohorts with an IsoSVM AUC-PR and MCC of 0.86, 0.63 and 0.85, 0.65, respectively. The TCF benign breast lesions had a significantly higher clustering coefficient and degree centrality than malignant TCFs. Grade 2 brain tumors demonstrated higher connectivity compared to Grade 4 tumors with increased degree centrality and clustering coefficients. Gleason 7 prostate lesions had increased betweenness centrality and APL compared to Gleason 6 lesions with AUC-PR and MCC ranging from 0.90 to 0.99 and 0.73 to 0.87, respectively. These TCF findings were similar in the validation breast and brain datasets. In conclusion, we present a new method for tumor characterization and visualization that results in a better understanding of the global and regional connections within the lesion and surrounding tissue.

Diagnostic significance of combined immunohistochemical panel of p63, High Molecular Weight Cytokeratin (34betaE12) and α‑Methyl Acyl Co A Racemase (AMACR) in resolving suspicious foci in prostatic lesions

Background: The assessment of small foci of atypical glands in prostatic needle biopsy specimens is a key diagnostic challenge in routine histopathology for pathologists. Due to the presence of mimickers of prostate carcinoma, at times making a definitive diagnosis becomes difficult. The use of immunomarkers like α‑Methyl Acyl Co A Racemase (AMACR), p63 and High Molecular Weight Cytokeratin (HMWCK/34betaE12) has made it easier for us to reach the diagnosis in such cases. Material and methods: All the cases which were received in the Department of Pathology, JNMCH, AMU from January 2015 to December 2018 were categorized into four histomorphologic groups on the basis of histopathology, and immunohistochemistry was applied on all the cases which were rendered ‘suspicious’ on histomorphology. Result: One hundred twenty-one prostatic specimens were received. Out of which, 13 biopsies were found to be inadequate for analysis and hence were not included in the study. Out of the rest 108 cases, (1) 52 were benign, (2) 19 were premalignant, (3) 25 were carcinoma and (4) 12 were signed as ‘suspicious’ on histopathology. These 12 suspicious cases were true cut needle biopsies which were considered appropriate for applying immunomarkers along with control cases. Out of 12 suspicious cases, 8 cases (66.7%) were negative and 3 cases (25%) were weakly positive for p63, 1 case showed moderate immunostaining. HMWCK was completely negative in 7 cases (58.33%), 3 cases (25%) showed weak positivity, 1 case showed moderate and 1 case showed strong positivity. While 5 cases (41.67%) were negative and 7 cases (58.33%) were positive for AMACR mostly showing moderate to strong positivity Conclusion: The application of immunomarkers helped us to reach a definite diagnosis in 10 out of 12 cases, which were otherwise difficult to classify. Judicious use of immunomarkers can help in differentiating mimickers of prostate carcinoma from true cancer cases and assist in reaching a definitive diagnosis.