Dataset Information

Relationship between the frequency of electrocautery of Hunner lesions and changes in bladder capacity in patients with Hunner type interstitial cystitis.

ABSTRACT: Electrocautery is a promising treatment option for patients with Hunner type interstitial cystitis (HIC), but frequently requires multiple sessions due to recurrence of the lesions. In the present study, we assessed the relationship between the frequency of electrocautery of Hunner lesions and changes in maximum bladder capacity (MBC) at hydrodistension in a large cohort of 118 HIC patients. Three mixed-effect linear regression analyses were conducted for MBC against (1) the number of sessions; (2) the number of sessions and the time between each session and the first session; and (3) other relevant clinical parameters in addition to the Model (2). The mean number of sessions was 2.8 times. MBC decreased approximately 50 mL for each additional electrocautery session, but this loss was offset by 10 mL for each year the subsequent session was postponed. MBC of < 400 mL at the first session was a significant risk factor for MBC loss with further sessions. No other clinical parameters were associated with MBC over time. This study demonstrates a significant relationship between the frequency of electrocautery of Hunner lesions and MBC changes in HIC patients. Low MBC at the first session is a poor prognostic marker for MBC loss over multiple sessions.

SUBMITTER: Akiyama Y

PROVIDER: S-EPMC7794499 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Relationship between the frequency of electrocautery of Hunner lesions and changes in bladder capacity in patients with Hunner type interstitial cystitis.

Akiyama Yoshiyuki Y Zaitsu Masayoshi M Watanabe Daiji D Yoshimura Itsuki I Niimi Aya A Nomiya Akira A Yamada Yuta Y Sato Yusuke Y Nakamura Masaki M Kawai Taketo T Yamada Daisuke D Suzuki Motofumi M Kume Haruki H Homma Yukio Y

Scientific reports 20210108 1

Electrocautery is a promising treatment option for patients with Hunner type interstitial cystitis (HIC), but frequently requires multiple sessions due to recurrence of the lesions. In the present study, we assessed the relationship between the frequency of electrocautery of Hunner lesions and changes in maximum bladder capacity (MBC) at hydrodistension in a large cohort of 118 HIC patients. Three mixed-effect linear regression analyses were conducted for MBC against (1) the number of sessions; ...[more]

PMID: 33420263

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Project description:BackgroundThe aim of this study was to identify novel genetic features of Hunner's lesion interstitial cystitis (HIC) via comprehensive analysis of the Gene Expression Omnibus (GEO) database.MethodsThe GSE11783 and GSE28242 datasets were downloaded from GEO for further analysis. Differentially expressed genes (DEGs) were identified and analyzed for functional annotation. The diagnostic markers for HIC were screened and validated using the least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine recursive feature elimination (SVM-RFE) algorithms. Finally, the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was adopted to investigate the correlation between immune cell infiltration and diagnostic markers in HIC.ResultsA total of 7837 DEGs were identified in GSE11783 and 1583 DEGs in GSE28242. Venn diagrams were used to obtain 16 overlapping upregulated and 67 overlapping downregulated DEGs separately. The LASSO logistic model and SVM-RFE algorithm were used to identify 6 genes including KRT20, SLFN11, CD86, ITGA4, PLAC8, and BTN3A3 from DEGs as diagnostic markers for HIC. Their diagnostic potential in HIC and bladder pain syndrome/interstitial cystitis (BPS/IC) were acceptable. PLAC8 exhibited the best diagnostic performance in BPS/IC with an area under the curve of 0.916. The results of immune infiltration involving GSE11783 revealed that the plasma cell ratio (p = 0.017), activated memory CD4+ T cells (p = 0.009), activated dendritic cells (p = 0.01), eosinophils (p = 0.004), and neutrophils (p = 0.03) were significantly higher in HIC than in normal samples, in contrast to resting mast cells (p = 0.022). A positive correlation existed between diagnostic markers and infiltrating immune cells.ConclusionKRT20, SLFN11, CD86, ITGA4, PLAC8, and BTN3A3 represent novel and potent diagnostic markers for HIC. They also exhibit certain diagnostic potential in BPS/IC. Immune cell infiltration might play a key role in the pathogenesis and progression of BPS/IC.

Project description:BackgroundAccurate cystoscopic recognition of Hunner lesions (HLs) is indispensable for better treatment prognosis in managing patients with Hunner-type interstitial cystitis (HIC), but frequently challenging due to its varying appearance.ObjectiveTo develop a deep learning (DL) system for cystoscopic recognition of a HL using artificial intelligence (AI).Design setting and participantsA total of 626 cystoscopic images collected from January 8, 2019 to December 24, 2020, consisting of 360 images of HLs from 41 patients with HIC and 266 images of flat reddish mucosal lesions resembling HLs from 41 control patients including those with bladder cancer and other chronic cystitis, were used to create a dataset with an 8:2 ratio of training images and test images for transfer learning and external validation, respectively. AI-based five DL models were constructed, using a pretrained convolutional neural network model that was retrained to output 1 for a HL and 0 for control. A five-fold cross-validation method was applied for internal validation.Outcome measurements and statistical analysisTrue- and false-positive rates were plotted as a receiver operating curve when the threshold changed from 0 to 1. Accuracy, sensitivity, and specificity were evaluated at a threshold of 0.5. Diagnostic performance of the models was compared with that of urologists as a reader study.Results and limitationsThe mean area under the curve of the models reached 0.919, with mean sensitivity of 81.9% and specificity of 85.2% in the test dataset. In the reader study, the mean accuracy, sensitivity, and specificity were, respectively, 83.0%, 80.4%, and 85.6% for the models, and 62.4%, 79.6%, and 45.2% for expert urologists. Limitations include the diagnostic nature of a HL as warranted assertibility.ConclusionsWe constructed the first DL system that recognizes HLs with accuracy exceeding that of humans. This AI-driven system assists physicians with proper cystoscopic recognition of a HL.Patient summaryIn this diagnostic study, we developed a deep learning system for cystoscopic recognition of Hunner lesions in patients with interstitial cystitis. The mean area under the curve of the constructed system reached 0.919 with mean sensitivity of 81.9% and specificity of 85.2%, demonstrating diagnostic accuracy exceeding that of human expert urologists in detecting Hunner lesions. This deep learning system assists physicians with proper diagnosis of a Hunner lesion.

Dataset Information

Relationship between the frequency of electrocautery of Hunner lesions and changes in bladder capacity in patients with Hunner type interstitial cystitis.

Publications

Relationship between the frequency of electrocautery of Hunner lesions and changes in bladder capacity in patients with Hunner type interstitial cystitis.

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