Melanosis of the urinary bladder, so-called melanosis vesicae, is a rare condition characterized by dark, velvety bladder mucosa observed by cystoscopy examination. Up to 20 examples have been ...reported in the English literature, and the etiology of this disease still needs to be discovered. We present an 82-year-old woman with a history of pelvic organ prolapse-associated urinary symptoms. The patient was found to have pigmented urinary bladder mucosa on cystoscopy and underwent a total hysterectomy and bladder mucosal biopsy. Histologically, pigmented granules were evident in the bladder stroma and epithelium, highlighted by Periodic Acid-Schiff (PAS) stain, suggestive of lipofuscin in nature. We outline the diagnostic features of bladder melanosis, discuss the diagnostic mimickers, and thoroughly review the literature on the subject.
Multiparametric magnetic resonance imaging (mpMRI) has become increasingly important for the clinical assessment of prostate cancer (PCa), but its interpretation is generally variable due to its ...relatively subjective nature. Radiomics and classification methods have shown potential for improving the accuracy and objectivity of mpMRI-based PCa assessment. However, these studies are limited to a small number of classification methods, evaluation using the AUC score only, and a non-rigorous assessment of all possible combinations of radiomics and classification methods. This paper presents a systematic and rigorous framework comprised of classification, cross-validation and statistical analyses that was developed to identify the best performing classifier for PCa risk stratification based on mpMRI-derived radiomic features derived from a sizeable cohort. This classifier performed well in an independent validation set, including performing better than PI-RADS v2 in some aspects, indicating the value of objectively interpreting mpMRI images using radiomics and classification methods for PCa risk assessment.
Objectives
Using a radiomics framework to quantitatively analyze tumor shape and texture features in three dimensions, we tested its ability to objectively and robustly distinguish between benign and ...malignant renal masses. We assessed the relative contributions of shape and texture metrics separately and together in the prediction model.
Materials and methods
Computed tomography (CT) images of 735 patients with 539 malignant and 196 benign masses were segmented in this retrospective study. Thirty-three shape and 760 texture metrics were calculated per tumor. Tumor classification models using shape, texture, and both metrics were built using random forest and AdaBoost with tenfold cross-validation. Sensitivity analyses on five sub-cohorts with respect to the acquisition phase were conducted. Additional sensitivity analyses after multiple imputation were also conducted. Model performance was assessed using AUC.
Results
Random forest classifier showed shape metrics featuring within the top 10% performing metrics regardless of phase, attaining the highest variable importance in the corticomedullary phase. Convex hull perimeter ratio is a consistently high-performing shape feature. Shape metrics alone achieved an AUC ranging 0.64–0.68 across multiple classifiers, compared with 0.67–0.75 and 0.68–0.75 achieved by texture-only and combined models, respectively.
Conclusion
Shape metrics alone attain high prediction performance and high variable importance in the combined model, while being independent of the acquisition phase (unlike texture). Shape analysis therefore should not be overlooked in its potential to distinguish benign from malignant tumors, and future radiomics platforms powered by machine learning should harness both shape and texture metrics.
Key Points
• Current radiomics research is heavily weighted towards texture analysis, but quantitative shape metrics should not be ignored in their potential to distinguish benign from malignant renal tumors.
• Shape metrics alone can attain high prediction performance and demonstrate high variable importance in the combined shape and texture radiomics model.
• Any future radiomics platform powered by machine learning should harness both shape and texture metrics, especially since tumor shape (unlike texture) is independent of the acquisition phase and more robust from the imaging variations.
Objectives
To evaluate the utility of CT-based radiomics signatures in discriminating low-grade (grades 1–2) clear cell renal cell carcinomas (ccRCC) from high-grade (grades 3–4) and low TNM stage ...(stages I–II) ccRCC from high TNM stage (stages III–IV).
Methods
A total of 587 subjects (mean age 60.2 years ± 12.2; range 22–88.7 years) with ccRCC were included. A total of 255 tumors were high grade and 153 were high stage. For each subject, one dominant tumor was delineated as the region of interest (ROI). Our institutional radiomics pipeline was then used to extract 2824 radiomics features across 12 texture families from the manually segmented volumes of interest. Separate iterations of the machine learning models using all extracted features (full model) as well as only a subset of previously identified robust metrics (robust model) were developed. Variable of importance (VOI) analysis was performed using the out-of-bag Gini index to identify the top 10 radiomics metrics driving each classifier. Model performance was reported using area under the receiver operating curve (AUC).
Results
The highest AUC to distinguish between low- and high-grade ccRCC was 0.70 (95% CI 0.62–0.78) and the highest AUC to distinguish between low- and high-stage ccRCC was 0.80 (95% CI 0.74–0.86). Comparable AUCs of 0.73 (95% CI 0.65–0.8) and 0.77 (95% CI 0.7–0.84) were reported using the robust model for grade and stage classification, respectively. VOI analysis revealed the importance of neighborhood operation–based methods, including GLCM, GLDM, and GLRLM, in driving the performance of the robust models for both grade and stage classification.
Conclusion
Post-validation, CT-based radiomics signatures may prove to be useful tools to assess ccRCC grade and stage and could potentially add to current prognostic models.
Summary statement
Multiphase CT-based radiomics signatures have potential to serve as a non-invasive stratification schema for distinguishing between low- and high-grade as well as low- and high-stage ccRCC.
Key Points
•
Radiomics signatures derived from clinical multiphase CT images were able to stratify low- from high-grade ccRCC, with an AUC of 0.70 (95% CI 0.62–0.78).
•
Radiomics signatures derived from multiphase CT images yielded discriminative power to stratify low from high TNM stage in ccRCC, with an AUC of 0.80 (95% CI 0.74–0.86).
•
Models created using only robust radiomics features achieved comparable AUCs of 0.73 (95% CI 0.65–0.80) and 0.77 (95% CI 0.70–0.84) to the model with all radiomics features in classifying ccRCC grade and stage, respectively
.
Juxtaglomerular cell tumor (JGCT) is a rare renal tumor with a predominantly benign clinical course. It affects young adults, who often present with hypertension, hypokalemia, and hyperaldosteronism. ...The tumor cells are round to spindle-shaped with occasional mild to moderate atypia, but mitotic figures are usually absent. Surgical resection is the treatment of choice. Typically, the blood pressure and renin levels normalize after removal of the tumor. Rare cases of metastatic and recurrent JGCT have been reported including cases with vascular invasion. These cases typically occur in older adults and present with larger tumor size (9-15 cm). We report a case of JGCT, 5.5 cm in greatest dimension, with atypical pathological features including invasion of the renal vein, lymphovascular invasion, and significant pleomorphism with rhabdoid morphology, along with a brief review of the literature.
We report an unusual intrasinusoidal growth pattern of an intraabdominal diffuse large B-cell lymphoma both clinically and histologically mimicking a metastatic adenocarcinoma. A 66-year-old woman ...presented with a high-grade distal biliary stricture with multiple enlarged abdominal lymph nodes. Frozen section at the time of pancreatoduodenectomy (“Whipple”) demonstrated cohesive nests of large atypical cells within a totally effaced lymph node presenting a diagnostic challenge. Immunohistochemistry proved this to be a diffuse large B-cell lymphoma extensively involving the sinusoids.
Summary Data on immunohistochemical expression of novel and traditional urothelial markers in the wide range of urothelial carcinoma variants have so far been very limited. In this study, whole ...tissue sections from 130 bladder urothelial carcinoma and variants were stained with a panel of novel and traditional immunomarkers supportive of urothelial lineage. The positivity rates were as follows: ( a ) urothelial carcinomas with or without divergent differentiation: GATA3 (50%), S-100P (86%), uroplakin III (20%), thrombomodulin (40%), cytokeratin 7 (CK7) (80%), CK20 (55%), p63 (87%), and high molecular weight cytokeratin (HMCK) (89%); ( b ) urothelial carcinoma variants (micropapillary, plasmacytoid, nested, clear cell, and microcystic): GATA3 (88%), S-100P (96%), uroplakin III (33%), thrombomodulin (49%), CK7 (95%), CK20 (61%), p63 (69%), and HMCK (96%); and ( c ) undifferentiated carcinomas (lymphoepithelioma-like carcinoma, small cell carcinoma, sarcomatoid carcinoma and carcinoma with rhabdoid and giant cells): GATA3 (28%), S-100P (31%), uroplakin III (0%), thrombomodulin (22%), CK7 (50%), CK20 (3%), p63 (50%), and HMCK (49%). In urothelial carcinoma with squamous differentiation, GATA3 expression was lower (20%) in contrast to p63 and S-100P. In urothelial carcinoma with glandular differentiation, GATA3 (50%) and p63 (60%) expression was lower than S-100P (100%). p63 expression was relatively lower in micropapillary (54%) and plasmacytoid (50%) variants compared with the other urothelial carcinoma variants. This study provides comprehensive data for novel and traditionally used markers to support urothelial lineage in urothelial carcinoma variants. Our findings show that GATA3, S-100P, CK7, CK20, HMCK, and p63, in the appropriate differential diagnostic setting, are useful to support urothelial lineage of variant morphologies.
Abstract
The objective of this study was to compare transperineal (TP) versus transrectal (TR) magnetic resonance imaging (MRI) and transrectal ultrasound (TRUS) fusion prostate biopsy (PBx). ...Consecutive men who underwent prostate MRI followed by a systematic biopsy. Additional target biopsies were performed from Prostate Imaging Reporting & Data System (PIRADS) 3–5 lesions. Men who underwent TP PBx were matched 1:2 with a synchronous cohort undergoing TR PBx by PSA, Prostate volume (PV) and PIRADS score. Endpoint of the study was the detection of clinically significant prostate cancer (CSPCa; Grade Group ≥ 2). Univariate and multivariable analyses were performed. Results were considered statistically significant if p < 0.05. Overall, 504 patients met the inclusion criteria. A total of 168 TP PBx were pair-matched to 336 TR PBx patients. Baseline demographics and imaging characteristics were similar between the groups. Per patient, the CSPCa detection was 2.1% vs 6.3% (p = 0.4) for PIRADS 1–2, and 59% vs 60% (p = 0.9) for PIRADS 3–5, on TP vs TR PBx, respectively. Per lesion, the CSPCa detection for PIRADS 3 (21% vs 16%; p = 0.4), PIRADS 4 (51% vs 44%; p = 0.8) and PIRADS 5 (76% vs 84%; p = 0.3) was similar for TP vs TR PBx, respectively. However, the TP PBx showed a longer maximum cancer core length (11 vs 9 mm; p = 0.02) and higher cancer core involvement (83% vs 65%; p < 0.001) than TR PBx. Independent predictors for CSPCa detection were age, PSA, PV, abnormal digital rectal examination findings, and PIRADS 3–5. Our study demonstrated transperineal MRI/TRUS fusion PBx provides similar CSPCa detection, with larger prostate cancer core length and percent of core involvement, than transrectal PBx.
The 8th Edition of the American Joint Committee on Cancer (AJCC) Staging Manual designates discontinuous involvement of spermatic cord soft tissue by testicular germ cell tumors as a metastatic ...deposit. We conducted a retrospective international multi-institutional study to validate the current recommendations. Thirty-three (72%) nonseminomatous and 13 (28%) seminomatous testicular germ cell tumors were collected from 15 institutions in America, Europe, and Asia. Testicular tumor size ranged from 1.3 to 18.0 cm (mean: 6.1). Cases were classified as discontinuous involvement of spermatic cord soft tissue (n = 26), continuous cord involvement (n = 17), or cord lymphovascular invasion (n = 3). The mean follow-up was 39 months. Clinical stage for discontinuous involvement of spermatic cord soft-tissue patients was I (local disease) in 2/24 (8%), II (regional disease) in 6/24 (25%), and III (distant disease) in 16/24 (67%) cases; 16 (67%) patients presented with distant metastasis. Clinical stage for continuous cord involvement patients was I in 9/17 (53%), II in 4/17 (23%), and III in 4/17 (23%); 4 (23%) patients presented with distant metastasis. Disease progression was seen in 4 patients with discontinuous involvement of spermatic cord soft tissue and 5 with continuous cord-involvement (p = 0.699). When comparing discontinuous and continuous cord involvement, a significant difference was found in cord margin status (p = 0.044), spermatic cord tumor size (p = 0.016), lymph-node involvement (p = 0.037), distant metastasis (p = 0.010), individual clinical stage (p = 0.003), and nonadvanced vs. advanced disease (p = 0.003) at presentation. In multivariate analysis, after adjusting for age, histology, testicular tumor size, percent of embryonal carcinoma, lymphovascular invasion, and cord margin status, discontinuous involvement of spermatic cord soft tissue was significantly associated (p = 0.011) with advanced clinical stage at presentation. Our findings support the designation of metastatic disease for discontinuous involvement of spermatic cord soft tissue, as introduced by the 8th edition of the AJCC staging.
PDF
