Diagnostic accuracy of optical coherence tomography in bladder cancer patients: A systematic review and meta-analysis

Huang, Juan; Ma, Xuelei; Zhang, Lei; Jia, Hongjie; Wang, Feng

doi:10.3892/mco.2018.1566

Cited by 12 publications

(10 citation statements)

References 37 publications

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“…OCT is a biomedical optical imaging technique that can provide real-time and cross-sectional images of tissue morphology. In a meta-analysis published in 2018, an excellent diagnostic accuracy of OCT in detection of bladder cancer was shown, where the pooled sensitivity and specificity were 0.96 (95% CI: 0.94–0.98) and 0.82 (95% CI: 0.80–0.85), respectively, on a per-patient level [26]. In the present study, the specificity of CLE was a little disappointing.…”

Section: Discussionmentioning

confidence: 50%

Diagnostic Performance of Confocal Laser Endomicroscopy for the Detection of Bladder Cancer: Systematic Review and Meta-Analysis

Wang

Luo

et al. 2020

Urol Int

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Objective: To systematically evaluate the diagnostic efficacy of confocal laser endomicroscopy (CLE) in detection of bladder cancer. Methods: A systematic literature search on CLE in diagnosing bladder cancer in PubMed, Embase, and the Cochrane Library databases was performed. A bivariate meta-regression model was used for meta-analysis to evaluate the pooled diagnostic value of CLE. Results: A total of 5 eligible studies involving 302 lesions were available for this meta-analysis. In a per-lesion analysis, pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and summary receiver-operating curve (SROC) area under the curve (AUC) of CLE for malignant lesions were 0.90 (95% confidence interval [

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Section: Discussionmentioning

confidence: 50%

Diagnostic Performance of Confocal Laser Endomicroscopy for the Detection of Bladder Cancer: Systematic Review and Meta-Analysis

Wang

Luo

et al. 2020

Urol Int

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“…Huang et al recently performed a meta-analysis to evaluate the diagnostic accuracy of OCT. The sensitivity and specificity of the included publications ranged from 76 to 100% and 62% and 97%, resulting in a pooled sensitivity and specificity of 0.96 and 0.82, respectively [21]. OCT is limited by a small area of analysis, making the examination of the entire bladder impractical; therefore, its use with other ancillary methods is encouraged.…”

Section: State Of the Art Of Urological Endoscopymentioning

confidence: 99%

Application of artificial neural networks for automated analysis of cystoscopic images: a review of the current status and future prospects

et al. 2020

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Background Optimal detection and surveillance of bladder cancer (BCa) rely primarily on the cystoscopic visualization of bladder lesions. AI-assisted cystoscopy may improve image recognition and accelerate data acquisition. Objective To provide a comprehensive review of machine learning (ML), deep learning (DL) and convolutional neural network (CNN) applications in cystoscopic image recognition. Evidence acquisition A detailed search of original articles was performed using the PubMed-MEDLINE database to identify recent English literature relevant to ML, DL and CNN applications in cystoscopic image recognition. Evidence synthesis In total, two articles and one conference abstract were identified addressing the application of AI methods in cystoscopic image recognition. These investigations showed accuracies exceeding 90% for tumor detection; however, future work is necessary to incorporate these methods into AI-aided cystoscopy and compared to other tumor visualization tools. Furthermore, we present results from the RaVeNNA-4pi consortium initiative which has extracted 4200 frames from 62 videos, analyzed them with the U-Net network and achieved an average dice score of 0.67. Improvements in its precision can be achieved by augmenting the video/frame database. Conclusion AI-aided cystoscopy has the potential to outperform urologists at recognizing and classifying bladder lesions. To ensure their real-life implementation, however, these algorithms require external validation to generalize their results across other data sets.

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“…Umsetzbar im Rahmen der Zystoskopie ist das Einbringen einer Sonde und die Darstellung und Abschätzung der Ausdehnung von spezifischen Befunden. Mehrere klinische Studien belegen die prinzipielle Durchführbarkeit und die korrekte Einstufung von auffälligen Arealen (100 % Sensitivität), wobei die Spezifität zwischen 65 -89 % schwankt [14].…”

Section: Experimentelle Verfahren Zur Verbesserten Diagnostikunclassified

Verbesserungspotenziale durch neue Resektions- und Bildgebungstechniken bei der TUR-B

Hennig¹,

Kramer²

2020

Aktuelle Urol

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ZusammenfassungDie transurethrale Resektion von Harnblasentumoren (TURB) ist ein Grundpfeiler in der urologischen Versorgung von Harnblasenkarzinompatienten. Seit der initialen Einführung von Resektoskopen vor knapp 100 Jahren hat sich an der grundlegenden Resektionstechnik wenig geändert. Erst mit der Verbreitung der sog. En-Bloc-Resektion (ERBT), welche im Gegensatz zur fragmentierten Abtragung die Tumorintegrität erhält, findet eine zögerliche Neujustierung der Technik statt. Vorteile, die der ERBT zugeschrieben werden, sind die bessere histopathologische Beurteilbarkeit und die höhere Detrusormuskulaturrate. Zudem sind Tendenzen für eine geringere Rate an sog. „in-field“ Rezidiven sowie eine verminderte Komplikationsrate beschrieben worden. Randomisierte, kontrollierte Studien mit geeigneter Fallzahl und Methodik stehen allerdings aus. Nur wenige Neuerungen hinsichtlich verbesserter endoskopischer Tumordiagnostik sind in den letzten Jahren hinzugekommen. Erwähnenswert ist die multiparametrische Magnetresonanztomografie der Blase, welche die Genauigkeit der lokalen Tumorausbreitung im Vergleich zur alleinigen konventionellen Bildgebung verbessern soll, sowie Verfahren aus dem Bereich der künstlichen Intelligenz. Die Intention dieses Artikels ist es einen aktuellen Stand über die ERBT sowie die lokale Diagnostik bei Harnblasentumoren zu geben.

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Diagnostic accuracy of optical coherence tomography in bladder cancer patients: A systematic review and meta-analysis

Cited by 12 publications

References 37 publications

Diagnostic Performance of Confocal Laser Endomicroscopy for the Detection of Bladder Cancer: Systematic Review and Meta-Analysis

Diagnostic Performance of Confocal Laser Endomicroscopy for the Detection of Bladder Cancer: Systematic Review and Meta-Analysis

Application of artificial neural networks for automated analysis of cystoscopic images: a review of the current status and future prospects

Verbesserungspotenziale durch neue Resektions- und Bildgebungstechniken bei der TUR-B

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