Benign Prostatic Lesions Research Articles

Magnetic Resonance Image Compilation Was Used in Conjunction with Prostate PI-RADS v2.1 Score Has Diagnostic Relevance for Benign and Malignant Prostate Lesions.

Objective To assess the diagnostic usefulness of magic in conjunction with PI-RADS v2.1 for prostate cancer malignant foci. Methods A total of 202 lesions (97 transitional zone lesions and 105 peripheral zone lesions) from 198 people were investigated retrospectively using traditional MRI and magic images. Each lesion has a unique pathological consequence. Lesions T1, T2, and PD values were employed as magic observation markers. The locations of the lesions were aggregated, and the paired t-test and receiver operating characteristic curve (ROC) were employed to find the indices with statistical significance in separating benign from malignant prostatic nodules (+1 point) and (−1 point) respectively. Draw a ROC curve and compare it to the PI-RADS v2.1 score using the magic positive and negative indices as well as the PI-RADS v2.1 score. By comparing the ROC curves scored separately, the diagnostic efficiency of the two scoring approaches for benign and malignant prostate lesions was investigated. Results T2 value has the highest diagnostic efficiency among the magic observation indices. T2 value of 77 ms for transitional zone lesions and T2 value of 89 ms for peripheral zone lesions are positive indices, whereas T2 value >77 ms and T2 value >89 ms are negative indexes. PI-RADS v2.1 combines one score and magic. In the transitional zone, the sensitivity, specificity, positive predictive value, and negative predictive value of the two scoring methods were 57.52, 87.70, 76.70, and 74.6 percent and 82.50, 73.68, 95.5, and 74.7 percent, respectively, and the AUC values were 0.735 and 0.846, respectively (P = 0.004); in the peripheral zone, the AUC values were 86.15 percent, 68.42 percent, 82.4. Conclusions Magic T2 value is a favorable sign for diagnosing benign and malignant prostate cancers when used in conjunction with PI-RADS v2.1. The end product exceeds PI-RADS v2.1 on its own, which is more useful in identifying benign and malignant prostate lesions, decreasing unnecessary puncture and alleviating patient pain.

Texture analysis based on PI-RADS 4/5-scored magnetic resonance images combined with machine learning to distinguish benign lesions from prostate cancer.

BackgroundThe global morbidity and mortality of prostate cancer (PCa) increase sharply every year. Early diagnosis is essential; it determines survival and outcome. So, this study extracted the texture features of apparent diffusion coefficient images in multiparametric magnetic resonance imaging (mp-MRI) and built machine learning models based on radiomics texture analysis (TA) to determine its ability to distinguish benign from PCa lesions using the Prostate Imaging Reporting and Data System (PI-RADS) 4/5 score.MethodsWe enrolled 103 patients who underwent mp-MRI examinations and transrectal ultrasound and magnetic resonance fusion imaging (TRUS-MRI) targeted prostate biopsy and obtained pathological confirmation at our hospital from August 2017 to January 2020. We used ImageJ software to obtain texture feature parameters based on apparent diffusion coefficient (ADC) images, then standardized texture feature parameters, and used LASSO regression to reduce multiple feature parameters; 70% of the cases were randomly selected from the PCa group and the benign prostate hyperplasia group as the training set. The remaining 30% was used as the test set. The machine learning classification model for identifying benign and malignant prostate lesions was constructed using the feature parameters after dimensionality reduction. The clinical indicators were statistically analyzed, and we constructed a machine learning classification model based on clinical indicators of benign and malignant prostate lesions. Finally, we compared the model’s performance based on radiomics texture features and clinical indicators to identify benign and malignant prostate lesions in PI-RADS 4/5 score.ResultsThe area under the curve (AUC) of the R-logistic model test set was 0.838, higher than the R-SVM and R-AdaBoost classification models. At this time, the corresponding R-logistic classification model formula is as follow: Y_radiomics=9.396-7.464*median ADC-0.584*kurtosis+0.627*skewness+0.576*MRI lesions volume; analysis of clinical indicators shows that the corresponding C-logistic classification model formula is as follows: Y_clinical =-2.608+0.324*PSA-3.045*Fib+4.147*LDL-C, the AUC value of the model training set was 0.860, smaller than the training set R-logistic classification model AUC value of 0.936.ConclusionsRadiomics combined with the machine learning classifier model has strong classification performance in identifying benign and PCa in PI-RADS 4/5 score. Various treatments and outcomes for PCa patients can be applied clinically.

THE ROLE OF MAGNETIC RESONANCE SPECTROSCOPY FOR PROSTATE CANCER DIAGNOSIS

Prostate cancer (PC) is the most common malignancy among men and is the fifth leading cause of cancer-related death in men worldwide. The present study aims to systematically review the ability of magnetic resonance spectroscopy (MRS) to differentiate between benign and malignant prostate lesions. According to the 06-PRISMA guideline, we searched in five English databases, including Scopus, PubMed, Web of Science, EMBASE, and Google Scholar without time limitation for publications related to the role of magnetic resonance spectroscopy for prostate cancer diagnosis. The searched words and terms were: “prostate cancer”, “prostatitis”, “magnetic resonance spectroscopy”, “benign prostate hyperplasia”, “malignant prostate hyperplasia”, “comparison”. Totally 1927 papers were identified by database searching. Out of these papers, 261 papers were discarded because of duplication. Of the remaining 1666 papers, 1604 papers were discarded because of the inadequate information and the ones in which the abstract was submitted in congresses as preceding papers, conferences, and editorials without full text. Out of the remaining 62 papers which were studied for eligibility, 52 papers were removed for a number of reasons including inconsistency between methods with results, incorrect interpretation of the results, poor methodology, etc. Finally, 10 papers were included in this present study. In general, based on the results of the review of articles, MRS has optimal sensitivity, specificity and accuracy in diagnosing prostate cancer and differentiating it from benign prostate hyperplasia in comparison with other diagnostic and pathological methods. Due to the small number of studies related to the sensitivity and specificity of MRS, further checking was not possible to confirm these results. Therefore, further studies in this regard are recommended.

Combining Magnetic Resonance Diffusion-Weighted Imaging with Prostate-Specific Antigen to Differentiate Between Malignant and Benign Prostate Lesions.

BackgroundWe aimed to develop a combined model of quantitative parameters derived from 3 different magnetic resonance imaging (MRI) diffusion models and laboratory data related to prostate-specific antigen (PSA) for differentiating between prostate cancer (PCa) and benign lesions.Material/MethodsEighty-four patients pathologically confirmed as having PCa or benign disease were enrolled. All patients underwent multiparametric MRI before biopsy, added intravoxel incoherent motion (IVIM) imaging, and diffusion kurtosis imaging (DKI). The following data were collected: quantitative parameters of diffusion-weighted imaging (DWI), IVIM, and DKI, preoperative total PSA, free/total PSA ratio, and PSA density (PSAD) values. A combined logistic regression model was established by above MRI quantitative parameters and PSA data to diagnose PCa. The Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) was used to assess the lesions for comparison.ResultsThirty-two patients had PCa and 52 patients had benign lesions. In multivariate logistic regression analysis, only apparent diffusion coefficient (ADC) and PSAD were significant variables (P<0.05) and were thus retained in the model. The area under curve value of the combined model (0.911) was higher than that of ADC, PSAD, and PI-RADS v2 (0.887, 0.861, and 0.859, respectively) in univariate analysis, but without any statistically significant differences. The combined model generated greater clinical benefit than the independent application of ADC, PSAD, and PI-RADS v2.ConclusionsADC and PSAD were the 2 most important metrics for distinguishing PCa from benign lesions. The combined model of ADC and PSAD demonstrated satisfactory discrimination and improved clinical net benefit.

Efficacy of 68Ga-PSMA-11 PET/CT with biparametric MRI in diagnosing prostate cancer and predicting risk stratification: a comparative study.

This retrospective study aimed to investigate the efficacy of the combined application of biparametric magnetic resonance imaging (bpMRI) and 68Ga-PSMA-11 positron emission computed tomography/computed tomography (bpMRI/PET) in the qualitative diagnosis of intermediate- to high-risk prostate cancer (PCa). The 105 patients with suspected PCa included in the study underwent bpMRI and PET/CT. BpMRI examinations included conventional sequences and diffusion-weighted imaging (DWI) sequences. Major lesions were qualitatively diagnosed according to the Prostate Imaging Reporting and Data System (PI-RADS). A PET/CT scan was started 60 min after intravenous 68Ga-PSMA-11 injection. The area with the highest radioactivity on PET/CT images was defined as the major lesion, and the maximum standard uptake value (SUVmax) was measured. All cases were confirmed by biopsy and pathology. Receiver operating characteristic curve (ROC) analysis was performed on the data to calculate sensitivity, specificity, and the Youden index. Of the 105 patients, 68 patients were diagnosed with PCa, and 37 patients had benign prostatic lesions. With a PI-RADS score ≥3 as the diagnostic threshold, the accuracy of bpMRI in identifying benign and malignant prostate lesions was similar to that of PET/CT (SUVmax threshold ≥10.9), and the Youden indices were 0.60 and 0.64, respectively. The sensitivity and specificity of bpMRI in the differential diagnosis of intermediate- to high-risk PCa versus low-risk PCa or benign lesions were 63% and 88%, respectively, and the Youden index was 0.51. With an SUVmax ≥12.9 as the diagnostic threshold, the sensitivity and specificity of PET/CT in the differential diagnosis of intermediate- to high-risk PCa versus low-risk PCa or benign lesions were 74% and 94%, respectively, and the Youden index was 0.68. The sensitivity and specificity of bpMRI/PET in diagnosing PCa were 94% and 81%, respectively, and the Youden index was 0.75. The sensitivity and specificity of bpMRI/PET in the differential diagnosis of intermediate- to high-risk PCa versus low-risk PCa or benign lesions were 80% and 88%, respectively, and the Youden index was 0.68. The combined application of bpMRI and PET improves the accuracy of the qualitative diagnosis of prostate lesions, and its diagnostic efficacy for risk stratification in patients with intermediate- to high-risk PCa is similar to that of PET/CT and higher than that of bpMRI alone.

Role of Multiparametric Magnetic Resonance Imaging in the Evaluation of Prostatic Pathologies on 3 Tesla Machine

Background and objectives Prostate diseases with an overall incidence of 9% are the leading cause affecting millions of males worldwide, with prostate cancer being the primary cause of death in males owing to benign prostatic hypertrophy being the primary cause of morbidity in the older age group. In light of this, we aimed to evaluate the utility of Magnetic Resonance Imaging in evaluating and characterization prostatic pathologies and grading prostatic cancer using PIRADS v2. Methods This was a study carried out on 50 patients with the age group ranging from 50 to 90 years with clinical suspicion or ultrasonographically demonstrable prostatic pathology and correlation of multiparametric MRI findings on various sequences with clinical features and histopathological findings and classification into groups of benign and malignant prostatic lesions and according to the PIRADS v2 scoring. Results Out of our study group, 4 cases were diagnosed with prostatitis and prostatic abscess, and 46 cases were categorized into PI-RADS, out of which most cases were classified into PI-RADS category V, followed by PI-RADS II and III. These were then evaluated with MR spectroscopy, of which 30 cases showed choline peak, and 16 cases showed citrate peak. The sensitivity and specificity for multiparametric MRI sequences combination detect the carcinoma of the prostate was calculated, and the Positive Predictive Value (PPV) &amp; Negative Predictive Value (NPV) was found as 76% and 92%, respectively. Conclusion Based on our findings, we found out that the multiparametric MRI approach gives a wealth of practical information that has dramatically enhanced the detection and characterization of prostatic lesions. We also found out that morphological and functional sequencing improves the sensitivity and specificity of the lesions' identification and characterization.

Lymphocyte-to-monocyte ratio is a predictor of clinically significant prostate cancer at prostate biopsy.

Inflammation plays critical roles at different stages of carcinogenesis and cancer progression. Several previous studies showed conflicting results for the predictive role of systemic inflammation markers in the detection of clinically significant prostate cancers (CSPCs). We aimed to determine the predictive roles of lymphocyte-to-monocyte (LMR) and eosinophil-to-lymphocyte ratios (ELR) in the detection of CSPC at standard 12-core transrectal ultrasound-guided prostate biopsy (12-core-TRUS-Bx) using our large-cohort database. Clinical and pathological data of a total of 1740 men, who underwent initial standard 12-core TRUS-Bx, were analyzed. LMR and ELR were calculated from the prebiopsy complete blood count. Definitions of CSPC, LMR, and ELR were "Gleason grade group ≥2," "the lymphocyte counts/the monocyte counts," and "the eosinophil counts/the lymphocyte counts," respectively. Median (interquartile range) of serum prostate-specific antigen(PSA) level and prostatic volume before TRUS-Bx were 7.59 (5.02-13.12) ng/ml and 38.2 (29.0-52.9) ml, respectively. Benign prostatic lesions, clinically insignificant prostate cancers (CIPCs), and CSPCs were detected in 1179 (67.8%), 180 (10.3%), and 381 (21.9%) patients, respectively. The patients with CSPCs had older age, a higher prevalence of diabetes mellitus or hypertension, a higher rate of digital rectal examination abnormality, higher serum PSA level, lower serum testosterone level, and lower LMR than those with benign lesions or CIPCs. However, there was no difference in ELR among the three (benign lesions, CIPCs and CSPCs). In all the patients, multivariate regression analysis showed that lower LMR was an independent predictor of CSPCs compared with ELR. In the subset of men with prostate volume ≥39.3 ml, lower LMR was an independent predictor of CSPCs compared with ELR. In the subset of men with prostate volume <39.3 ml, men with lower LMR showed the tendency of having a higher probability of CSPCs without any statistical significance on the contrary to ELR. Our data indicate that LMR can play an independent predictive role in the detection of CSPCs at initial 12-core-TRUS-Bx compared with ELR. The predictive role of the LMR appears to be significant for men with larger prostate volume rather than those with smaller prostate volume.

Biphasic GA 68-labeled prostate specific membrane antigen-11 positron emission tomography/computed tomography scans in the differential diagnosis and risk stratification of initial primary prostate cancer.

This study aimed to assess the value of biphasic GA 68-labeled prostate-specific membrane antigen-11 (68Ga-PSMA-11) positron emission tomography/computed tomography (PET/CT) scan in the differential diagnosis and risk stratification of initial primary prostate cancer (PCa). A total of 51 patients with PCa (8 low- and intermediate-risk PCa patients and 43 high-risk PCa patients) and 36 patients with benign prostate lesions, who underwent standard whole-body imaging and delayed pelvic imaging of 68Ga-PSMA-11 PET/CT, were enrolled in this prospective study. The PET parameters, such as maximum and mean standard uptake value (SUVmax and SUVmean), and maximum and mean standard retention index of PET images were calculated and compared in different prostate lesions. The diagnostic performances of the PET parameters were evaluated by receiver operating characteristic (ROC) curves. All the PET parameters of PCa participants were significantly higher than those of participants with benign prostate lesions (P<0.001). The SUVmean of delayed imaging had the best performance in the diagnosis of PCa with an area under the curve (AUC) of 0.918 (95% CI: 0.858 to 0.977), the sensitivity of 90.0%, and specificity of 83.3%. The SUVmax and SUVmean of high-risk PCa participants were significantly higher than those of low- and intermediate-risk PCa participants (P<0.005). The SUVmax of standard imaging had the best performance in predicting high-risk PCa with an AUC of 0.890 (95% CI: 0.799 to 0.980), a sensitivity of 76.7%, and a specificity of 100.0%. The biphasic 68Ga-PSMA-11 PET/CT scan had good performance in discriminating prostate cancer from benign prostate diseases. The SUVmean of the prostate lesion at delayed imaging of 68Ga-PSMA-11 PET/CT had the best value in the differential diagnosis of PCa, and the SUVmax at standard imaging was most valuable in predicting the risk stratification of PCa.

MRI-based radiomics models to assess prostate cancer, extracapsular extension and positive surgical margins

PurposeTo investigate the performance of magnetic resonance imaging (MRI)-based radiomics models for benign and malignant prostate lesion discrimination and extracapsular extension (ECE) and positive surgical margins (PSM) prediction.Methods and materialsIn total, 459 patients who underwent multiparametric MRI (mpMRI) before prostate biopsy were included. Radiomic features were extracted from both T2-weighted imaging (T2WI) and the apparent diffusion coefficient (ADC). Patients were divided into different training sets and testing sets for different targets according to a ratio of 7:3. Radiomics signatures were built using radiomic features on the training set, and integrated models were built by adding clinical characteristics. The areas under the receiver operating characteristic curves (AUCs) were calculated to assess the classification performance on the testing sets.ResultsThe radiomics signatures for benign and malignant lesion discrimination achieved AUCs of 0.775 (T2WI), 0.863 (ADC) and 0.855 (ADC + T2WI). The corresponding integrated models improved the AUC to 0.851/0.912/0.905, respectively. The radiomics signatures for ECE achieved the highest AUC of 0.625 (ADC), and the corresponding integrated model achieved the highest AUC (0.728). The radiomics signatures for PSM prediction achieved AUCs of 0.614 (T2WI) and 0.733 (ADC). The corresponding integrated models reached AUCs of 0.680 and 0.766, respectively.ConclusionsThe MRI-based radiomics models, which took advantage of radiomic features on ADC and T2WI scans, showed good performance in discriminating benign and malignant prostate lesions and predicting ECE and PSM. Combining radiomics signatures and clinical factors enhanced the performance of the models, which may contribute to clinical diagnosis and treatment.

Bi-parametric magnetic resonance imaging based radiomics for the identification of benign and malignant prostate lesions: cross-vendor validation.

The purpose of this study was to develop Bi-parametric Magnetic Resonance Imaging (BP-MRI) based radiomics models for differentiation between benign and malignant prostate lesions, and to cross-vendor validate the generalization ability of the models. The prebiopsy BP-MRI data (T2-Weighted Image [T2WI] and the Apparent Diffusion Coefficient [ADC]) of 459 patients with clinical suspicion of prostate cancer were acquired using two scanners from different vendors. The prostate biopsies are the reference standard for diagnosing benign and malignant prostate lesions. The training set was 168 patients' data from Siemens (Vendor 1), and the inner test set was 70 patients' data from the same vendor. The external test set was 221 patients' data from GE (Vendor 2). The lesion Region of Interest (ROI) was manually delineated by experienced radiologists. A total of 851 radiomics features including shape, first-order statistical, texture, and wavelet features were extracted from ROI in T2WI and ADC, respectively. Two feature-ranking methods (Minimum Redundancy Maximum Relevance [MRMR] and Wilcoxon Rank-Sum Test [WRST]) and three classifiers (Random Forest [RF], Support Vector Machine [SVM], and the Least Absolute Shrinkage and Selection Operator [LASSO] regression) were investigated for their efficacy in building single-parametric radiomics signatures. A biparametric radiomics model was built by combining the optimal single-parametric radiomics signatures. A comprehensive diagnosis model was built by combining the biparametric radiomics model with age and Prostate Specific Antigen (PSA) value using multivariable logistic regression. All models were built in the training set and independently validated in the inner and external test sets, and the performances of models in the diagnosis of benign and malignant prostate lesions were quantified by the Area Under the Receiver Operating Characteristic Curve (AUC). The mean AUCs of the inner and external test sets were calculated for each model. The non-inferiority test was used to test if the AUC of model in external test was not inferior to the AUC of model in inner test. Combining MRMR and LASSO produced the best-performing single-parametric radiomics signatures with the highest mean AUC of 0.673 for T2WI (inner test AUC = 0.729 vs. external test AUC = 0.616, p = 0.569) and the highest mean AUC of 0.810 for ADC (inner test AUC = 0.822 vs. external test AUC = 0.797, p = 0.102). The biparametric radiomics model produced a mean AUC of 0.833 (inner test AUC = 0.867 vs. external test AUC = 0.798, p = 0.051). The comprehensive diagnosis model had an improved mean AUC of 0.911 (inner test AUC = 0.935 vs. external test AUC = 0.886, p = 0.010). The comprehensive diagnosis model for differentiating benign from malignant prostate lesions was accurate and generalizable.

Optimized Application of 68Ga-Prostate-Specific Membrane Antigen-617 Whole-Body PET/CT and Pelvic PET/MR in Prostate Cancer Initial Diagnosis and Staging.

Purpose: To analyze 68Ga-PSMA-617 PET/CT or PET/MR and delayed PET/MR images in patients diagnosed with or suspicion of prostate cancer, and to explore the optimal use of PET/CT and PET/MR for initial diagnosis and staging in prostate cancer.Methods: Images from conventional scan by 68Ga-PSMA whole-body PET/CT or PET/MR followed by delayed pelvic PET/MR were retrospectively analyzed. Prostatic 68Ga-PSMA uptake was measured as SUVmax1 (conventional scan 1 h post injection) and SUVmax2 (delayed scan 3 h post injection). Age, PSA levels, and SUVmax were compared between benign and malignant cases. The correlation of SUVmax1 and SUVmax2 was analyzed. Diagnostic performance was evaluated by ROC analysis.Results: Fifty-six patients with 41 prostate cancers and 15 benign prostate lesions were enrolled. Fifty-three patients had paired conventional and delayed scans. Age, tPSA, fPSA levels, and SUVmax were significantly different between benign and malignant cases. A good correlation was found between SUVmax1 and SUVmax2. There was significant difference between SUVmax1 and SUVmax2 in the malignant group (p = 0.001). SUVmax1 had superior diagnostic performance than SUVmax2, SUVmax difference and PSA levels, with a sensitivity of 85.4%, a specificity of 100% and an AUC of 0.956. A combination of SUVmax1 with nodal and/or distant metastases and MR PI-RADS V2 score had a sensitivity and specificity of 100%. Delayed pelvic PET/MR imaging in 33 patients were found to be redundant because these patients had nodal and/or distant metastases which can be easily detected by PET/CT. PET/MR provided incremental value in 8 patients at early-stage prostate cancer based on precise anatomical localization and changes in lesion signal provided by MR.Conclusion: Combined 68Ga-PSMA whole-body PET/CT and pelvic PET/MR can accurately differentiate benign prostate diseases from prostate cancer and accurately stage prostate cancer. Whole-body PET/CT is sufficient for advanced prostate cancer. Pelvic PET/MR contributes to diagnosis and accurate staging in early prostate cancer. Imaging at about 1 h after injection is sufficient in most patients.ClinicalTrials.gov: NCT03756077. Registered 27 November 2018—Retrospectively registered, https://clinicaltrials.gov/show/NCT03756077.

Utility of p63 and AMACR in Differentiating Benign and Malignant Prostatic Lesions

Background: Prostate cancer is the sixth most common cancer in the world. Since treatment options and prognosis of prostatic adenocarcinomas and benign lesions differ significantly, so, the current study using p63and AMACR was carried out with aim to evaluate the utility of immunohistochemistry in resolving ambiguous lesions of prostate.&#x0D; Methods: The study was conducted on 130 prostatic specimens which included prostate biopsy, TURP and prostatectomy specimens. Routine hematoxylin and eosin staining and immunohistochemical staining using AMACR, p63 monoclonal antibody marker were performed.&#x0D; Results: Total of 130 cases of prostate samples were studied out of which benign lesions were seen in 102 cases (78.5%) and malignant carcinoma in 28 cases (21.5%). This study showed p63 had a sensitivity of 92.86% and specificity of 100% whereas AMACR has a sensitivity of 96.4% and specificity of 95%. BPH with prostatitis was a common finding in majority of benign lesions. All cases of LGPIN 15 cases (11.5%) were histologically associated with BPH, showing complete positivity in 12 cases (80%) and partial positivity in 3 cases (20%) with p63 immunostaining. HGPIN (1.5%) were associated with prostatic adenocarcinoma showing focal positivity whereas adenocarcinoma showed complete negativity of p63 expression (100%) and positive cytoplasmic staining with AMACR. Comparative study done between DRE, PSA, final histopathological diagnosis, expression of p63 and AMACR immunostaining gives highly significant p value of 0.001(&lt;0.05).&#x0D; Conclusion: p63 and AMACR are reliable markers which can be used in morphologically difficult cases.

DOES TRANS RECTAL ULTRASOUND (TRUS) HELPS IN DIFFERENTIAL DIAGNOSIS OF PROSTATE LESIONS? A STUDY AT TERTIARY CARE CENTER.

BACKGROUND: There are successions of investigations used in evaluation of prostatic pathology. Currently digital rectal examination &amp; serum PSA levels are used for screening of prostatic cancer. Many conventional imaging techniques like plain radiography, computed tomography, radionuclide scintigraphy and transabdominal sonography were proved to be ineffective in detection of many prostatic conditions specially cancer at an early stage. Transrectal ultrasound (TRUS) has traditionally been considered as the pivotal imaging test for the prostate, providing clinically important information regarding benign and malignant conditions. OBJECTIVES: to evaluate the TRUS and colour Doppler ndings in various benign and malignant prostatic lesions with respect to its site, echo pattern, capsular status, local invasion, vascularity and to correlate with other investigations, like digital rectal examination and serum PSA etc. and also to study the accuracy of TRUS in differentiating benign from malignant lesions. METHODOLOGY: A prospective observational study carried out over a period of 1.5 years at a tertiary care hospital. All male patient referred to department of radio diagnosis with prostate related complains referred from surgery department. Study includes clinical symptoms, family and personal history, laboratory examination like PSA, radiological examination, digital rectal examination. . Various statistical characteristics of the test such as sensitivity, specicity, positive predictive value, negative predictive value were calculated whenever applicable. Out of total 64 patients' recruited OBSERVATIONS: commonest age group was 61 – 70 years (39.1%). Commonest prostatic pathology encountered was BPH (56.2%) followed by prostatic carcinoma (31.3%), prostatitis (4.7%), prostatic abscess &amp; calculus (3.1%) prostatic cyst (1.6%). 75% patients of prostatic carcinoma and 13.9% of Benign Prostate Hypertrophy show PSA value greater than 10ng/ml. Echotexture pattern found on TRUS, in prostatic carcinoma patients was hypoechoic echotexture in 70% patients followed by mixed echotexture in 20% patients. Examination in Color Doppler found, 80 % patients of prostatic carcinoma show increased vascularity and 25 % of benign lesion also shows increased vascularity including all three cases of prostatitis and one out of two case of prostatic abscess. Any single test alone is not helpful in arriving at a diagnosis, but all the thr CONCLUSION: ee tests i.e. PSA level, digital rectal examination, and transrectal ultrasound, together give very conrmatory result, specically to differentiate benign from malignant condition of prostate. . Considering that the initial screening of patients will help in reducing the number of negative biopsies (unnecessary), without impairing the cancer detection capacity.

Interpretation of Prostatic Biopsy at a tertiary care centre

Introduction: Worldwide prostatic carcinoma is the second most frequently diagnosed cancer and the sixth leading cause of cancer death in males. Prostate-specific antigen (PSA), digital rectal examination, and transrectal ultrasound are the tools most commonly used to screen for prostate cancer. Prostatic biopsy is most often preceded by abnormalities found on digital rectal examination (DRE) or serum prostate specific antigen (S.PSA) elevation. This study was planned to know proportion of malignant and benign lesions in histopathologic examination for prostatic lesions in patient who attend OPD/IPD and to analyze the usefulness of serum PSA & ultrasound examination by histopathological confirmation. Methods: Patients visited to urology department with urinary incontinence and other complaints were evaluated which includes clinical history, signs and symptoms. Rectal examination of patients was done. Serum PSA level and prostatic biopsy were sent of those who were suspected for prostatic disease. Prostate biopsy was obtained by using any one of the following method 1.Transurethral resection biopsy 2. Transrectal biopsy Trucut biopsy. Results: Out of 300 cases of prostatic biopsy 265 (88.33%) are benign and 35 (11.66%) cases are malignant lesions. Out of 300 cases, 191 (63.66%) are pure benign prostatic hyperplasia, 48(16%) are BPH with chronic prostatitis and 11(3.66%) are BPH with severe prostatitis. Out of 35 cases of prostatic carcinoma 33 (94.28%) cases are adenocarcinoma and 2 cases (5.71%) are transitional cell carcinoma. Out of 262 cases with clinically benign lesions, 258 cases proved benign histopathologically but 4 cases (1.52%) are diagnose malignant. 151 patients have S.PSA less than 4 ng/ml, out of 151, 149 turned to be benign on histopathological examination. 52 patient have S.PSA above 10 ng/ml, out of these 52 cases, 29 have malignancy in HPE examination. Out of 278 cases diagnosed as benign isoechoic by ultra sonography 262 cases have benign lesion on histologic diagnosis and 16 have malignant lesion. Out of 22 cases diagnosed as malignant (hypoechoic asymmetrical) by ultrasonographicaly 19 proved malignant histologically. Conclusion: The results of this study indicate that transrectal ultrasound, serum prostate specific antigen and digital rectal examination were good tool to differentiate between malignant and benign lesions of prostate. Proportion of malignancies are quiet significant in prostatic lesions and increased with age. Key words: Prostae, Malignancy, Biopsy, PSA, DRE

Quantitative colour Doppler and greyscale ultrasound for evaluating prostate cancer.

Although transrectal ultrasound is routinely performed for imaging prostate lesions, colour Doppler imaging visualizing vascularity is not commonly used for diagnosis. The goal of this study was to measure vascular and echogenic differences between malignant and benign lesions of the prostate by quantitative colour Doppler and greyscale transrectal ultrasound. Greyscale and colour Doppler ultrasound images of the prostate were acquired in 16 subjects with biopsy-proven malignant or benign lesions. Echogenicity and microvascular flow velocity of each lesion were measured by quantitative image analysis. Flow velocity was measured over several cardiac cycles and the velocity-time waveform was used to determine microvascular pulsatility index and microvascular resistivity index. The Wilcoxon rank sum test was used to compare the malignant and benign groups. Median microvascular flow velocity of the malignant lesions was 1.25 cm/s compared to 0.36 cm/s for the benign lesions. Median pulsatility and resistive indices of the malignant lesions were 1.55 and 0.68, respectively versus 6.38 and 1.0 for the benign lesions. Malignant lesions were more hypoechoic relative to the surrounding tissue, with median echogenicity of 0.24 compared to 0.76 for the benign lesions. The differences between the malignant and benign groups for each measurement were significant (p < 0.01). Marked differences were observed in flow velocity, microvascular pulsatility, microvascular resistance, and echogenicity of prostate cancer measured with quantitative colour Doppler and greyscale ultrasound imaging. Vascular differences measured together with echogenicity have the combined potential to characterize malignant and benign prostate lesions.

Efectos de la toxina botulínica sobre la porción glandular de la próstata: fundamentos fisiopatológicos, mecanismo de acción y evidencias

La toxina botulínica es una potente neurotoxina que produce la inhibición de las uniones neuromusculares mediante el bloqueo de la liberación de acetilcolina y desensibilización de los nervios sensoriales. En la próstata, sus efectos no solo se limitan a la unión neuromuscular, sino que también se extienden a la unión neuroglandular. Por lo cual la inyección intraprostáticas de toxina botulínica se encuentra entre las nuevas opciones de tratamiento de la hiperplasia prostática benigna. Considerando las potencialidades que esta sustancia posee como una terapia efectiva en afecciones prostáticas, pero considerando que sus mecanismos son poco claros, el objetivo de esta revisión es organizar la evidencia actual y describir los fundamentos fisiopatológicos y mecanismo de acción conocidos hasta ahora, con la finalidad de motivar nuevas investigaciones. Luego de realizar la revisión de la evidencia se pudo concluir que la toxina botulínica puede inducir la involución prostática en ratas, perros y humanos sin causar inflamación local o efectos secundarios sistémicos significativos. Lo cual plantea la posibilidad de su aplicación en lesiones prostáticas benignas o malignas.

Effects of botulinum toxin on the glandular portion of the prostate: pathophysiologic bases, mechanism of action, and evidence

Botulinum toxin is a potent neurotoxin that inhibits neuromuscular junctions by blocking the release of acetylcholine and desensitizes sensory nerves. In the prostate, it effects are not limited to the neuromuscular junction, but also affect the neuroglandular junction, placing the intraprostatic injection of botulinum toxin among the new treatment options for benign prostatic hyperplasia. Considering its potential as an effective therapy in prostate conditions, while at the same time its mechanisms of action are not clear, the aim of the present review was to organize the current evidence and describe the currently known pathophysiologic bases and mechanism of action involved to encourage new research. After conducting the review of the evidence, it was concluded that botulinum toxin could induce involution of the prostate in rats, dogs, and humans, without causing local inflammation or significant systemic side effects, suggesting the possibility of its use in benign or malignant prostate lesions.

Multiparametric MRI for Prostate Cancer Characterization: Combined Use of Radiomics Model with PI-RADS and Clinical Parameters.

Radiomics is an emerging field of image analysis with potential applications in patient risk stratification. This study developed and evaluated machine learning models using quantitative radiomic features extracted from multiparametric magnetic resonance imaging (mpMRI) to detect and classify prostate cancer (PCa). In total, 191 patients that underwent prostatic mpMRI and combined targeted and systematic fusion biopsy were retrospectively included. Segmentations of the whole prostate glands and index lesions were performed manually in apparent diffusion coefficient (ADC) maps and T2-weighted MRI. Radiomic features were extracted from regions corresponding to the whole prostate gland and index lesion. The best performing combination of feature setup and classifier was selected to compare its predictive ability of the radiologist’s evaluation (PI-RADS), mean ADC, prostate specific antigen density (PSAD) and digital rectal examination (DRE) using receiver operating characteristic (ROC) analysis. Models were evaluated using repeated 5-fold cross-validation and a separate independent test cohort. In the test cohort, an ensemble model combining a radiomics model, with models for PI-RADS, PSAD and DRE achieved high predictive AUCs for the differentiation of (i) malignant from benign prostatic lesions (AUC = 0.889) and of (ii) clinically significant (csPCa) from clinically insignificant PCa (cisPCa) (AUC = 0.844). Our combined model was numerically superior to PI-RADS for cancer detection (AUC = 0.779; p = 0.054) as well as for clinical significance prediction (AUC = 0.688; p = 0.209) and showed a significantly better performance compared to mADC for csPCa prediction (AUC = 0.571; p = 0.022). In our study, radiomics accurately characterizes prostatic index lesions and shows performance comparable to radiologists for PCa characterization. Quantitative image data represent a potential biomarker, which, when combined with PI-RADS, PSAD and DRE, predicts csPCa more accurately than mADC. Prognostic machine learning models could assist in csPCa detection and patient selection for MRI-guided biopsy.

Diagnostic Value of Cytokeratin 34 beta E12 (Ck34βE12) and α-Methylacyl-CoA racemase (AMACR) Immunohistochemical Expression in Prostatic Lesions.

Background & Objective:Some prostatic lesions contain small suspicious foci for prostatic carcinoma in which the morphological features are equivocal. Two immunohistochemical markers namely, cytokeratin 34 beta E12 (Ck34βE12) and α-Methylacyl-CoA racemase (AMACR), were evaluated in these lesions for a definitive diagnosis and avoiding misdiagnosis or overdiagnosis of prostatic carcinoma.Methods:A total of 90 paraffin embedded blocks of prostatic tissue were selected and categorized into three groups as follows: 50 cases of benign prostatic hyperplasia (BPH), 20 cases of prostatic carcinoma, and 20 cases of benign prostatic lesions with suspicious foci labeled as ASAP (atypical small acinar proliferation) that occupy not more than 5% of the lesion. These cases were revised for histopathological diagnosis and stained with two immunohistochemical markers: Ck34βE12 and AMACR.Results:While 92.9% of BPH were positive for Ck34βE12, 96% of prostatic carcinoma were negative for this marker (P=0.0001). Regarding AMACR, 92.9% of BPH cases were negative, but 92% of prostatic carcinoma cases were positive for this marker (P=0.0001). Out of 20 cases of BPH, 15 cases containing suspicious foci showed Ck34βE12+/AMACR- (diagnosis: benign), but 5 cases were Ck34βE12-/AMACR+, for which the diagnosis changed to prostatic carcinoma (P=0.04).Conclusion:Immunohistochemical staining with Ck34βE12 and AMACR improved the diagnostic performance and increased confidence level for establishing definite diagnosis in cases with suspicious foci, in which the morphological features were equivocal. This could help to avoid misdiagnosis or overdiagnosis of prostatic carcinoma that would eventually improve the management of the patient and subsequently the prognosis.

Consortum between mast cell and prostatic lesions-An etiological factor or mere coexistence

Introduction: Prostate cancer exhibits a complex genetic and heterogeneous histological pattern reflecting its multifactorial phenotype. Mast cells mainly known for their role in allergy and anaphylaxis, now regarded as key factor cell in angiogenesis, tissue remodeling and repair, whereas their importance in tumor pathology as either cancer promoter or inhibitor is still debated. Materials and Methods: Study included 100 cases of prostatic lesions with 74 cases of benign prostatic lesions and 26 cases of adenocarcinoma prostate, received in the form of transurethral resection of prostate chips for histopathological examination. The tissues were routinely processed, the paraffin sections stained by hematoxylin and eosin and 1% toluidine blue. Histological diagnosis was made. Mast cell count was done taking a standard of 10 high power fields(x40) and mean were calculated. Distributions of mast cells were noted in stroma, perivascular, periglandular and intraglandular regions. Results: Mast cell count was significantly higher in benign prostatic hyperplasia with mean of 3.6 per high power field whereas absence or low count was found in adenocarcinoma prostate with mean of 1.7 per high power field. Mast cells were located predominantly in stromal region in both BPH and adenocarcinoma prostate; in rest of the areas the numbers were comparable. Conclusion: In this study we observed significant increase in mast cell count in stroma of BPH compared to adenocarcinoma indicating that mast cell density is inversely proportional to malignancy. This suggests high mast cell count favors the prognosis. Keywords: Mast cells, Benign Prostatic Hyperplasia, Adenocarcinoma.