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

Ali N, Bolenz C, Todenhöfer T, Stenzel A, Deetmar P, Kriegmair M, Knoll T, Porubsky S, Hartmann A, Popp J, Kriegmair MC, Bocklitz T (2021)

Publication Type: Journal article

Publication year: 2021

Journal

Scientific Reports Nature Publishing Group: Open Access Journals - Option B

Book Volume: 11

Article Number: 11629

Journal Issue: 1

DOI: 10.1038/s41598-021-91081-x

Abstract

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.

Authors with CRIS profile

Arndt Hartmann Lehrstuhl für Allgemeine Pathologie und Pathologische Anatomie

Involved external institutions

Friedrich-Schiller-Universität Jena DE Germany (DE) Universität Ulm DE Germany (DE) Universitätsklinikum Tübingen DE Germany (DE) Dialysezentrum München Nord DE Germany (DE) Klinikum der Universität München DE Germany (DE) Eberhard Karls Universität Tübingen DE Germany (DE) Universitätsmedizin der Johannes Gutenberg-Universität Mainz DE Germany (DE) Universitätsklinikum Mannheim DE Germany (DE)

How to cite

APA:

Ali, N., Bolenz, C., Todenhöfer, T., Stenzel, A., Deetmar, P., Kriegmair, M.,... Bocklitz, T. (2021). Deep learning-based classification of blue light cystoscopy imaging during transurethral resection of bladder tumors. Scientific Reports, 11(1). https://dx.doi.org/10.1038/s41598-021-91081-x

MLA:

Ali, Nairveen, et al. "Deep learning-based classification of blue light cystoscopy imaging during transurethral resection of bladder tumors." Scientific Reports 11.1 (2021).

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