An Efficient Framework for Video Documentation of Bladder Lesions for Cystoscopy: A Proof-of-Concept Study

Abstract

The identification of relevant frame sequences in an endoscopy video is labor-intensive and complicated by the poor data integrity of endoscopic information. We designed a surgeon-guided framework to efficiently manage the visual data from commonly performed bladder endoscopy (cystoscopy) videos. Screenshots of bladder lesions were captured during cystoscopy during transurethral resection of bladder tumor, then manually labeled according to case identification, date, lesion location, imaging modality, and pathology. The framework used the screenshot to search for and extract a corresponding 10-second video clip. Each video clip included a one-second space holder with a QR barcode informing the video content. The success of the framework was measured by the secondary use of these short clips and the reduction of storage volume required for video materials. From 86 cases, the framework successfully generated 249 video clips from 230 screenshots, with 14 erroneous video clips from 8 screenshots excluded. The HIPPA-compliant barcodes provided information of video contents with a 100% data completeness. A web-based educational gallery was curated with various diagnostic categories and annotated frame sequences. Compared with the unedited videos, the informative short video clips reduced the storage volume by 99.5%. In conclusion, our framework expedites the generation of visual contents with surgeon’s instruction for cystoscopy and potential incorporation of video data towards applications including clinical documentation, education, and research.