Properly documenting withdrawal time in colonoscopy is essential for quality assessment and cost allocation. However, reporting withdrawal time has significant interobserver variability. Additionally, current manual documentation of endoscopic findings is time-consuming and distracting for the physician. This trial examines an artificial intelligence based system to determine withdrawal time and create a structured report, including high-quality images (AI) of detected polyps and landmarks.
This study aims to compare withdrawal time precision calculated by an AI system with examiner-reported times during colonoscopy, also evaluating endoscopists' satisfaction with the images included in the AI-generated reports. The study will be single-center and endoscopist-blinded, where 138 patients are expected to be recruited, taking polyp detection rates and potential dropouts into consideration. Manual annotation of withdrawal times from examination recordings will establish gold standard annotations. The AI system performs a frame-by-frame analysis of endoscopy recordings, predicting endoscopic findings. Using a rule-based logic, the method calculates withdrawal time for the examination and automatically generates a report for the examination. The study will include consenting adult patients eligible for colonoscopy, excluding those meeting specific criteria. In this observational study, the withdrawal time for the examinations of all recruited patients is estimated by both the physician and the AI method. The study does not relate to any particular indication, and any patient that is appointed for a colonoscopy and does not meet the exclusion criteria can be recruited. The AI method operates in the background, having no influence on the examination's process, or outcome. The standard procedure requires physicians to estimate the withdrawal time and document it in the examination report. Simultaneously, the proposed AI method also computes the withdrawal time for all patients in the background, without affecting the physician, the examination, or the outcomes of the examination. Importantly, the physician remains blinded to the AI model's output. To establish the gold standard withdrawal time, manual calculations will be performed using the recorded examination data for all patients. This gold standard is used for evaluating errors in withdrawal time estimation made by both the physician and the AI method. Subsequently, a comparative analysis is conducted to assess the disparities between the physician's estimations and those of the AI method. Furthermore, the AI method captures characteristic images of anatomical landmarks and notable events, such as polyp resections, during the examination. A panel of certified endoscopists will rigorously evaluate the quality and relevance of these selected images.
Study Type
OBSERVATIONAL
Enrollment
147
Withdrawal time is calculated and an image report is generated using the EndoMind system.
Universitätsklinikum Würzburg
Würzburg, Bavaria, Germany
Withdrawal time error comparison for colonoscopies using the proposed AI system versus physician estimation
The error between gold standard withdrawal time and the withdrawal time estimated from the proposed AI system and the physician are compared for the same examination.
Time frame: Through study completion, an average of 5 months
Image quality satisfaction
A board of endoscopy experts receives the reports generated by the proposed system and evaluate the quality and satisfaction for the images included in the report. Evaluation will be performed on a Likert scale from 1 to 5.
Time frame: Through study completion, an average of 5 months
Subgroup analysis for withdrawal time calculation error based on the presence or absence of resections in the examination.
Interventions will be split into two categories, those containing at least one resection and those without any resections.The error between gold standard withdrawal time and the withdrawal time estimated from the proposed AI system and the physician are compared for each subgroups of examinations separately.
Time frame: Through study completion, an average of 5 months
Number of examination where withdrawal time could not be determined
Evaluation of the number of examinations where the withdrawal time could not be calculated and the causes.
Time frame: Through study completion, an average of 5 months
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