Low-cost and label-free blue light cystoscopy through digital staining of white light cystoscopy videos

Shuang Chang; Greyson A Wintergerst; Camella Carlson; Haoli Yin; Kristen R Scarpato; Amy N Luckenbaugh; Sam S Chang; Soheil Kolouri; Audrey K Bowden

doi:10.1038/s43856-024-00705-6

Low-cost and label-free blue light cystoscopy through digital staining of white light cystoscopy videos

Commun Med (Lond). 2024 Dec 18;4(1):269. doi: 10.1038/s43856-024-00705-6.

Authors

Shuang Chang¹, Greyson A Wintergerst², Camella Carlson¹, Haoli Yin², Kristen R Scarpato³, Amy N Luckenbaugh³, Sam S Chang³, Soheil Kolouri², Audrey K Bowden^{4

5}

Affiliations

¹ Vanderbilt University, Department of Biomedical Engineering, Nashville, TN, 37232, USA.
² Vanderbilt University, Department of Computer Science, Nashville, TN, 37232, USA.
³ Vanderbilt University Medical Center, Department of Urology, Nashville, TN, 37232, USA.
⁴ Vanderbilt University, Department of Biomedical Engineering, Nashville, TN, 37232, USA. [email protected].
⁵ Vanderbilt University, Department of Electrical and Computer Engineering, Nashville, TN, 37232, USA. [email protected].

Abstract

Background: Bladder cancer is the 10^th most common malignancy and carries the highest treatment cost among all cancers. The elevated cost stems from its high recurrence rate, which necessitates frequent surveillance. White light cystoscopy (WLC), the standard of care surveillance tool to examine the bladder for lesions, has limited sensitivity for early-stage bladder cancer. Blue light cystoscopy (BLC) utilizes a fluorescent dye to induce contrast in cancerous regions, improving the sensitivity of detection by 43%. Nevertheless, the added equipment cost and lengthy dwell time of the dye limits the availability of BLC.

Methods: Here, we report the first demonstration of digital staining as a promising strategy to convert WLC images collected with standard-of-care clinical equipment into accurate BLC-like images, providing enhanced sensitivity for WLC without the associated labor or equipment cost.

Results: By introducing key pre-processing steps to circumvent color and brightness variations in clinical datasets needed for successful model performance, the results achieve a staining accuracy of 80.58% and show excellent qualitative and quantitative agreement of the digitally stained WLC (dsWLC) images with ground truth BLC images, including color consistency.

Conclusions: In short, dsWLC can affordably provide the fluorescent contrast needed to improve the detection sensitivity of bladder cancer, thereby increasing the accessibility of BLC contrast for bladder cancer surveillance. The broader implications of this work suggest digital staining is a cost-effective alternative to contrast-based endoscopy for other clinical scenarios outside of urology that can democratize access to better healthcare.

Plain language summary

Bladder cancer is one of the most common and costly cancers to treat. Traditional white light imaging of the bladder is not very effective at detecting early-stage cancer. Blue light imaging is better able to detect these cancers but requires administration of a dye. In this study, we use a computational process to transform white light bladder images into fluorescent, blue light versions, which improves detection of early-stage cancers. Our approach may be applicable to other clinical uses and could potentially be used to improve diagnosis of cancer.