Preliminary study of diffusion-weighted MRI in the preoperative diagnosis of cystitis glandularis

Anti-Inflammatory Action and Molecular Mechanism of Fucoidan Against Cystitis Glandularis

Cystitis glandularis (CG), known as a pre-gradual lesion in the bladder, is the pathological changes in the vesical mucosa characterized by inflammatory invasion and chronic obstruction. Clinically, effective treatment against CG is prescribed only when using drug therapy. Fucoidan, the naturally extractive polysaccharide, is well-reported bioactive compound with anti-inflammatory and immunoregulatory properties. In this research, an emerging computational approach was applied to explicate anti-CG actions and pharmacological targets exhibited by fucoidan in detail. Current network pharmacology data showed that 16 intersection genes of fucoidan and CG were identified, whereas all 6 core targets, including interleukin-6 (IL-6), tumor necrosis factor (TNF), interleukin-1B (IL-1B), matrix metalloproteinase-9 (MMP-9), interleukin-10 (IL-10), matrix metalloproteinase-2 (MMP-2), biological processes, and signaling pathways of fucoidan against CG were characterized, respectively. As revealed in the underlying mechanism, the anti-CG actions achieved by fucoidan were chiefly implicated in the reduction of inflammatory reactions and enhancement of immunoregulation. Taken together, these network bioinformatics findings may be used to reveal anti-CG effects and the pharmacological mechanism of fucoidan before further experimental validation. Furthermore, those core genes identified may be therapeutic targets for research and development of fucoidan-anti-CG.

Florid cystitis glandularis (intestinal type) with mucus extravasation: Two case reports and literature review

Background

Cystitis glandularis is a common bladder epithelial lesion characterized by hyperplasia and metaplasia of the bladder mucosa epithelium. The pathogenesis of cystitis glandularis of the intestinal type is unknown and less common. When cystitis glandularis (intestinal type) is extremely severely differentiated, it is called florid cystitis glandularis (the occurrence is extremely rare).

Case summary

Both patients were middle-aged men. In patient 1, the lesion was also seen in the posterior wall and was diagnosed more than 1 year ago as cystitis glandularis with urethral stricture. Patient 2 was examined for symptoms such as hematuria and was found to have an occupied bladder; both were treated surgically, and the postoperative pathology was diagnosed as florid cystitis glandularis (intestinal type), with mucus extravasation.

Conclusion

The pathogenesis of cystitis glandularis (intestinal type) is unknown and less common. When cystitis glandularis of the intestinal type is extremely severely differentiated, we call it florid cystitis glandularis. It is more common in the bladder neck and trigone. The clinical manifestations are mainly symptoms of bladder irritation, or hematuria as the main complaint, which rarely leads to hydronephrosis. Imaging is nonspecific and the diagnosis depends on pathology. Surgical excision of the lesion is possible. Due to the malignant potential of cystitis glandularis of intestinal type, postoperative follow-up is required.

Feasibility Study on Predicting Recurrence Risk of Bladder Cancer Based on Radiomics Features of Multiphase CT Images

Background

Predicting the recurrence risk of bladder cancer is crucial for the individualized clinical treatment of patients with bladder cancer.

Objective

To explore the radiomics based on multiphase CT images combined with clinical risk factors, and to further construct a radiomics-clinical model to predict the recurrence risk of bladder cancer within 2 years after surgery.

Methods

Patients with bladder cancer who underwent surgical treatment at the First Affiliated Hospital of Soochow University from January 2016 to December 2019 were retrospectively included and followed up to record the disease recurrence. A total of 183 patients were included in the study, and they were randomly divided into training group and validation group in a ratio of 7: 3. The three basic models which are plain scan, corticomedullary phase, and nephrographic phase as well as two combination models, namely, corticomedullary phase + nephrographic phase and plain scan + corticomedullary phase + nephrographic phase, were built with the logistic regression algorithm, and we selected the model with higher performance and calculated the Rad-score (radiomics score) of each patient. The clinical risk factors and Rad-score were screened by Cox univariate and multivariate proportional hazard models in turn to obtain the independent risk factors, then the radiomics-clinical model was constructed, and their performance was evaluated.

Results

Of the 183 patients included, 128 patients constituted the training group and 55 patients constituted the validation group. In terms of the radiomics-clinical model constructed by three independent risk factors—number of tumors, tumor grade, and Rad-score—the AUCs of the training group and validation group were 0.813 (95% CI 0.740–0.886) and 0.838 (95% CI 0.733–0.943), respectively. In the validation group, the diagnostic accuracy, sensitivity, and specificity were 0.727, 0.739, and 0.719, respectively.

Conclusion

Combining with radiomics based on multiphase CT images and clinical risk factors, the radiomics-clinical model constructed to predict the recurrence risk of bladder cancer within 2 years after surgery had a good performance.

Cystitis glandularis- rare cause of urinary bladder mass: case report and literature review

Background

Cystitis glandularis a rare benign proliferative disease of the urinary bladder mucosa is usually a microscopic finding and manifests rarely as a large visible macroscopic lesion of urinary bladder. Only few cases of cystitis glandularis presenting as urinary bladder mass in female patients have been reported in the literature. We are reporting a case of cystitis glandularis presenting as a urinary bladder mass in a very young female patient.

Case presentation.

Our patient, a young female 25 years of age presented in the Urology OPD with complaints of irritative lower urinary tract symptoms for two years and intermittent hematuria for one year. On evaluation, she was found to have a urinary bladder mass. Transurethral resection of her urinary bladder mass was done and on histopathological examination, it came out to be cystitis glandularis.

Conclusion

Clinical presentation of cystitis glandularis is variable. It may remain asymptomatic or could present as irritative lower urinary tract symptoms, hematuria, or mucus in the urine. It is normally a microscopic finding but could also present as an overt urinary bladder mass however this has been reported rarely in the literature.

Bioinformatics and experimental findings reveal the therapeutic actions and targets of pachymic acid against cystitis glandularis

Pachymic acid (PA), a bioactive ingredient isolated from Poria cocos Wolf, is reported with potential benefits of anti-inflammatory, anti-oxidative actions. It is reasoned that PA may play the potential benefits against cystitis glandularis (CG), an inflammation of the bladder tissue. In this study, we aimed to apply the network pharmacology and molecular docking analyses to reveal concrete anti-CG targets and mechanisms of PA, and then the bioinformatic findings were verified by using clinical and animal samples. The methodological data from network pharmacology approach showed that 303 and 243 reporting targets of CG and PA, and other 31 shared targets of CG and PA were identified. Subsequently, all top targets of PA against CG were screened out, including cyclooxygenase-2, epidermal growth factor receptor, tumor antigen p53 (TP53), tumor necrosis factor-alpha (TNF), interleukin-1 (IL-1) beta, proto-oncogene c-jun. Molecular docking data demonstrated that PA exerted potent bonding capacities with TNF, TP53 proteins in CG. In human study, the findings suggested that overactivated TNF-α expression and suppressed TP53 activation were detected in CG samples. In animal study, PA-treated mice showed reduced intravesical IL-1, IL-6 levels, and lactate dehydrogenase content, downregulated TNF-α and upregulated TP53 proteins in bladder samples. Taken together, our bioinformatics and experimental findings identify the key anti-CG biotargets and mechanisms of PA. More markedly, these pivotal pharmacological targets of PA against CG have been screened out and verified by using computational and experimental analyses.

A nomogram combined with radiomics features, albuminuria, and metabolic syndrome to predict the risk of myometrial invasion of bladder cancer

Background

To establish a preoperative prediction model of myometrial invasion of bladder cancer (BC) based on the radiomics characteristics of multi-parameter thin-slice enhanced computed tomography (CT) imaging.

Methods

Data from 100 patients with BC were analyzed retrospectively. The patients were divided into two groups: muscular invasive BC and non-muscular invasive BC. The tumor region was segmented from enhanced CT images (arterial- and venous-phase calibration maps) of all patients using Slicer-3D software. We extracted 1,223 texture features from tumor image data based on the shape and gray-level co-occurrence matrix, gray size region matrix, gray run-length matrix, adjacent gray difference matrix, and gray correlation matrix. The patients were randomly divided into a training group (n=70) and a verification group (n=30) in a 7:3 ratio. Interclass correlation coefficients >0.75, least absolute shrinkage, and selection operator regression were used for feature selection. The prediction model was established by combining Rad-score, independent clinical factors, and support vector machine (SVM), and a radiomics nomogram was constructed. The nomogram was tested using the consistency index, calibration curve, time-dependent receiver operating characteristic curve, and clinical decision curve to predict the myometrial invasion of the bladder preoperatively.

Results

Six radiomics features that were significantly related to myometrial invasion of BC were selected to construct a predictive model. The area under the curve (AUC) values of training group and verification group based on SVM were 0.898 (95% CI: 0.820–0.976) and 0.702 (95% CI: 0.495–0.909), respectively. Single factor and multiple factor analysis showed that albuminuria (95% CI: 0.243–2.206, P=0.0014) and metabolic syndrome (95% CI: 0.850–2.935, P<0.001) were independent influencing factors of BC myometrial invasion. Clinical factors and 11 radiomics features were used to construct a comprehensive model for predicting the pathological grade of BC (radiomics + clinical). After a comprehensive comparison, we found that the overall effectiveness of the model (radiomics + clinical) was the highest (AUC =0.8457).

Conclusions

Based on the multi-parameter thin-layer enhanced CT radiomics feature can be used as a potential independent predictor of BC myometrial invasion, the model based on parameters can initially quantitatively characterize the risk of myometrial invasion, and has excellent potential for predicting myometrial invasion of BC.

Quantitative Analysis of Enhanced Computed Tomography in Differentiating Cystitis Glandularis and Bladder Cancer

Objective

This study was performed to assess the value of quantitative analysis of enhanced computed tomography (CT) values in the differential diagnosis of bladder cancer and cystitis glandularis (CG).

Methods

Eighty patients with bladder masses (39 with CG and 41 with bladder cancer) who underwent enhanced CT were retrospectively reviewed. The CT enhancement values of the lesion and normal bladder wall in the arterial phase, venous phase, and delayed phase were measured. The relative enhancement CT values (relative enhancement CT value = enhancement CT value of lesion - enhancement CT value of normal bladder) in the arterial phase, venous phase, and delayed phase were also calculated. The pathological results were used as the gold standard, and the area under the curve (AUC), sensitivity, and specificity were calculated for the six groups of quantitative indicators (enhanced CT values and relative enhanced CT values of CG and bladder cancer in the arterial, venous, and delayed phases). We performed the leave-group-out cross-validation method to validate the accuracy, AUC, sensitivity, and specificity. The differences in accuracy, AUC, sensitivity, and specificity among the six groups of quantitative indicators were compared by the t-test.

Results

In a combined analysis of the AUC, sensitivity, and specificity performance, the best indicator was the arterial-phase relative enhancement CT value with a cut-off of 25.85 HU (AUC, 0.966; sensitivity, 95.1%; specificity, 92.3%). We used the 100-times leave-group-out cross-validation method to validate the accuracy, AUC, sensitivity, and specificity. Arterial-phase relative enhancement CT values showed the highest AUC and accuracy among the six groups, with statistical significance (P < 0.05).

Conclusion

Quantitative analysis of enhanced CT is of great clinical value in the differential diagnosis of CG and bladder cancer.