Deep learning-based classification of blue light cystoscopy imaging during transurethral resection of bladder tumors

Bladder cancer is one of the top 10 frequently occurring cancers and leads to most cancer deaths worldwide. Recently, blue light (BL) cystoscopy-based photodynamic diagnosis was introduced as a unique technology to enhance the detection of bladder cancer, particularly for the detection of flat and small lesions. Here, we aim to demonstrate a BL image-based artificial intelligence (AI) diagnostic platform using 216 BL images, that were acquired in four different urological departments and pathologically identified with respect to cancer malignancy, invasiveness, and grading. Thereafter, four pre-trained convolution neural networks were utilized to predict image malignancy, invasiveness, and grading. The results indicated that the classification sensitivity and specificity of malignant lesions are 95.77% and 87.84%, while the mean sensitivity and mean specificity of tumor invasiveness are 88% and 96.56%, respectively. This small multicenter clinical study clearly shows the potential of AI based classification of BL images allowing for better treatment decisions and potentially higher detection rates

Gender-Specific Variations in Professional and Personal Aspects among Senior Urology Physicians at German Centers: Results of a Web-Based Survey

Introduction: Senior urology physicians represent a heterogeneous group covering various clinical priorities and career objectives. No reliable data on gender-specific variations among senior urology physicians are available concerning professional and personal aspects. Methods: The objective of this study was to analyze professional perspectives, professional and personal settings, and individual career goals. A Web-based survey containing 55 items was designed which was available for senior physicians at German urologic centers between February and April 2019. Gender-specific differences were evaluated using bootstrap-adjusted multivariate logistic regression models. Results: One hundred and ninety-two surveys were evaluable including 29 female senior physicians (15.1%). Ninety-five percent would choose urology again as their field of specialization - with no significant gender-specific difference. 81.2% of participants rate the position of senior physician as a desirable career goal (comparing sexes: p = 0.220). Based on multivariate models, male participants self-assessed themselves significantly more frequently autonomously safe performing laparoscopic, open, and endourologic surgery. Male senior physicians declared 7 times more often to run for the position of head of department/full professor. Conclusion: This first study on professional and personal aspects among senior urology physicians demonstrates gender-specific variations concerning self-assessment of surgical expertise and future career goals. The creation of well-orchestrated human resources development strategies especially adapted to the needs of female urologists seems advisable

Generating panoramic images of the urinary bladder for the digital documentation of cystoscopy findings using Endorama®: Development and first clinical experience

INTRODUCTION & OBJECTIVES: In modern urology cystoscopy is essential for diagnosis of various abnormalities of the urinary bladder. Nevertheless, the documentation of suspicious findings is often observer-dependent, barely objective and not always reproducible. The aim of our work is to create panoramic images of the urinary bladder from image data of a video-cystoscopy using the Endorama software®. The achieved bladder panoramas should facilitate a comprehensive and high-quality digital documentation of the cystoscopy findings. MATERIAL & METHODS: We performed systematic cystoscopies of a bladder phantom (modified CLA 6/4, Coburg, Germany) and subsequently of human urinary bladders (n=10) before and after transurethral resection of a bladder tumour using conventional rigid endoscopes (Ch. 17 and 22, 30° optic). Applying the panorama software, distortion of the images was firstly adjusted based on a calibration reference pattern that was acquired prior to the cystoscopy. Afterwards, automatically selected video frames were registered to each other and overlaid on the basis of appropriate visual features such as vascular formations, in order to arrange them as mosaic in a common coordinate system. This allowed generating partial-panoramic images that were consequently complemented to form a comprehensive panorama of the urinary bladder. RESULTS: The data of the video-cystoscopy of the hemispheric bladder phantom was transformed digitally and in real-time to a panoramic survey, on which essential land marks of the bladde phantom were reproducible. The intraoperative video- endoscopies were analyzed using the Endorama® Software. We were able to create panoramic images of the respective human urinary bladders, on which important structures such as the orifices or bladder tumours could well be identified and scoped using zoom and translational function. The movement of the endoscope during the examination could be illustrated as an overlay track onto the panoramas. Comparing panoramic images from endoscopies before and after the resection of a bladder tumour allowed digital documentation of the outcome of the respective surgery. CONCLUSIONS: Our work proves that generating comprehensive panoramic images of the urinary bladder is technically feasible using the software Endorama®. This could help to facilitate digital documentation of cystoscopy findings and to reduce the observer-dependency of this examination, which has to be evaluated in clinical trials. In the future, a three-dimensional reconstruction of the whole bladder is meant to further improve the digital documentation

Deep Learning by Domain Transfer for Early Tumor Detection in the Urinary Bladder

Background: Bladder cancer (BCa) is the second most common genitourinary malignancy and has a mortality of 165,000 deaths p.a. The diagnosis of BCa is mostly carried out using cystoscopy - the visual examination of the urinary bladder with an endoscope. White light cystoscopy is currently considered as gold standard for the diagnosis. Nevertheless, especially flat, small or weakly textured lesions, are very difficult to detect and diagnose. Objective: With the advent of deep learning and already commercially available systems for the detection of adenomas in colonoscopy, it is investigated how such a system - for colonoscopy - performs if retrained and tested with cystoscopy images. Methods: A deep neural network with a YOLOv7-tiny architecture was pre-trained on 35,699 colonoscopy images (partially from Mannheim), yielding a precision = 0.92, sensitivity = 0.90, F1 = 0.91 on public colonoscopy data collections. Results: Testing this adenomadetection network with cystoscopy images from three sources (Ulm, Erlangen, Pforzheim), F1 scores in the range of 0.67 to 0.74 could be achieved. The network was then retrained with 12,066 cystoscopy images (from Mannheim), yielding improved F1 scores in the range of 0.78 to 0.85. Conclusion: It could be shown that a deep learning network for adenoma detection in colonoscopy is ad-hoc able to detect approximately 75% of the lesions in the urinary bladder in cystoscopy images, suggesting that these lesions have a similar appearance. After retraining the network with additional cystoscopy data, the performance for urinary lesion detection could be improved, indicating that a domain-shift with adequate additional data is feasible

Expression of the p53 Inhibitors MDM2 and MDM4 as Outcome Predictor in Muscle-invasive Bladder Cancer

Aim: To evaluate the prognostic role of the p53-upstream inhibitors MDM2, MDM4 and its splice variant MDM4-S in patients undergoing radical cystectomy (RC) for muscle-invasive bladder cancer (MIBC). Materials and Methods: mRNA Expression levels of MDM2, MDM4 and MDM4-S were assessed by quantitative real-time polymerase chain reaction (qRT-PCR) in 75 RC samples. Logistic regression analyses identified predictors of recurrence-free (RFS) and cancer-specific survival (CSS). Results: High expression was found in 42% (MDM2), 27% (MDMD4) and 91% (MDM4-S) of tumor specimens. Increased MDM2 expression was significantly associated with higher tumor stage (p=0.05) and lymphovascular invasion (LVI) (p=0.041). In the univariate analysis, low MDM4 expression (hazard ratio (HR)=5.93; p=0.002; HR=3.00; p=0.047), but not MDM2 (HR=1.63; p=0.222; HR=1.59; p=0.27), were associated with RFS and CSS. In the multivariate analysis, the combination of low MDM4 and high MDM2 was significant for RFS and CSS (HR=14.9; p=0.001; HR=5.63; p=0.019). Conclusion: The combination of MDM2 and MDM4 expression is an independent predictor in patients undergoing RC for MIBC

Multiparametric Cystoscopy for Detection of Bladder Cancer Using Real-time Multispectral Imaging

Background: Various imaging modalities can be used in addition to white light (WL) to improve detection of bladder cancer (BC). Objective: To use real-time multispectral imaging (rMSI) during urethrocystoscopy to combine different imaging modalities to achieve multiparametric cystoscopy (MPC). Design, setting, and partidpants: The rMSI system consisted of a camera with a spectral filter, a multi-LED light source, a microcontroller, and a computer for display and data acquisition. MSI with this system was achieved via temporal multiplexing. Surgical procedure: MPC was performed in ten patients with a diagnosed bladder tumor. Measurements: We gathered evidence to prove the feasibility of our approach. In addition, experienced urologists performed post-interventional evaluation of images of individual lesions. Images were independently rated in a semiquantitative manner for each modality. A statistical model was built for pairwise comparisons across modalities. Results and limitations: Overall, 31 lesions were detected using the rMSI set-up. Histopathology revealed malignancy in 27 lesions. All lesions could be visualized simultaneously in five modalities: WL, enhanced vascular contrast (EVC), blue light fluorescence, protoporphyrin IX fluorescence, and autofluorescence. EVC and photodynamic diagnosis images were merged in real time into one MP image. Using the recorded images, two observers identified all malignant lesions via MPC, whereas the single modalities did not arouse substantial suspicion for some lesions. The MP images of malignant lesions were rated significantly more suspicious than the images from single imaging modalities. Conclusions: We demonstrated for the first time the application of rMSI in endourology and we established MPC for detection of BC. This approach allows existing imaging modalities to be combined, and it may significantly improve the detection of bladder cancer

Predictive value of molecular subtyping in NMIBC by RT-qPCR of ERBB2, ESR1, PGR and MKI67 from formalin fixed TUR biopsies

Expression of ESR1, PGR, HER2 and Ki67 is important for risk stratification and therapy in breast cancer. Hormone receptor expression can also be found in MIBC, reflecting luminal and basal subtypes of breast cancer. Thus the purpose was to investigate on the mRNA expression of the aforementioned markers and their prognostic value in pT1 bladder cancer. Retrospective analysis of clinical data and Formalin-Fixed Paraffin-Embedded tissues (FFPE) of patients with stage pT1 NMIBC who underwent transurethral resection of the bladder was performed. mRNA expression was measured by single step RT-qPCR. Relative gene expression was determined by normalization to two housekeeping genes (CALM2, B2M) using the 40-Delta Delta CT method. Correlation of mRNA expression with outcome was assessed using Kaplan-Meier analysis and multivariate Cox regression analysis. From overall 302 patients, 255 samples could be analyzed with valid measurements. Subtype distribution was Luminal-A in 11.4%, Luminal-B in 38.8%, triple negative in 36.9% and ERBB2 in 12.9%, respectively. Kaplan-Meier analysis revealed molecular subtyping being statistical significant for RFS (p=0.0408) and PFS (p=0.0039). Luminal-A patients did have the best RFS and PFS. Multivariate analysis revealed molecular subtyping to be significant for PFS (L-R Chi(2) of 11.89, p=0.0078). Elevated expression of HER2 was statistically significant for PFS (p=0.0025) and discriminated among G3 tumors a high risk group (60% PFS) from a low risk risk group (90% PFS) after 5 year follow-up (p<0.001). Expression of ESR1, PGR and HER2 has predictive value in stage pT1 NMIBC and reveals potential therapeutic targets

ESR1, ERBB2, and Ki67 mRNA expression predicts stage and grade of non-muscle-invasive bladder carcinoma (NMIBC)

Pathological staging and grading are crucial for risk assessment in non-muscle-invasive bladder cancer (NMIBC). Molecular grading might support pathological evaluation and minimize interobserver variability. In this study, the well-established breast cancer markers ESR1, PGR, ERBB2, and MKI67 were evaluated as potential molecular markers to support grading and staging in NMIBC. We retrospectively analyzed clinical data and formalin-fixed paraffin-embedded tissues (FFPE) of patients with NMIBC. Messenger RNA (mRNA) expression of the aforementioned markers was measured by single-step reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) using RNA-specific TaqMan assays. Relative gene expression was determined by normalization to two reference genes (CALM2 and B2M) using the 40(-Delta Delta CT) method and correlated to histopathological stage and grade. Pathological assessment was performed by an experienced uropathologist. Statistical analysis was performed using the SAS software JMP 9.0.0 version and GraphPad Prism 5.04. Of 381 cases of NMIBC, samples of 100 pTa and 255 pT1 cases were included in the final study. Spearman rank correlation revealed significant correlations between grade and expression of MKI67 (r = 0.52, p < 0.0001), ESR1 (r = 0.25, p < 0.0001), and ERBB2 (r = 0.18, p = 0.0008). In Mann-Whitney tests, MKI67 was significantly different between all grades (p < 0.0001), while ESR1 (p = 0.0006) and ERBB2 (p = 0.027) were significantly different between G2 and G3. Higher expression of MKI67 (r = 0.49; p < 0.0001), ERBB2 (r = 0.22; p < 0.0001), and ESR1 (r = 0.18; p = 0.0009) mRNA was positively correlated with higher stage. MKI67 (p < 0.0001), ERBB2 (p = 0.0058), and PGR (p = 0.0007) were significantly different between pTa and pT1. In NMIBC expression of ESR1, ERBB2 and MKI67 are significantly different between stage and grade. This potentially provides objective parameters for pathological evaluation