P436 The AI based Red Density score is correlated with the established and new histological indices for Ulcerative Colitis in an independent cohort
Bibliographic record
Abstract
Abstract Background Red Density (RD) is an automated endoscopic tool that is developed for the objective evaluation of disease activity in ulcerative colitis (UC). The initial development integrated histological disease activity based on Robarts histological index (RHI) in the machine learning algorithm. New histological scores for UC have been developed since. The aim of this study was to establish the correlation between RD and the Nancy histological index (NHI) and PICaSSO Histologic Remission Index (PHRI). Methods Patients included in 4 centers in the ongoing PROCEED-UC study (NCT04408703) had assessment with RD in the rectum and sigmoid at baseline, w52 or early termination visit. Biopsies were taken according to protocol. Biopsies were scored for the Geboes score (GBS), RHI, NHI, PHRI in a blinded way after initial scoring convention training. Correlation was tested on patient level between mean RD per segment and the different histological indices based on Spearman correlation. Results In total 96 patients from 4 centers were included representing 2634 RD images from 400 colonic segments with biopsies and corresponding RD score. Mean (± SEM) rectal RD score was 32.7 (± 4.54), 33.69 (± 5.25) and 64.86 (± 31.71) at baseline, w52 and ET respectively. Mean sigmoidal RD score was 38.13 (± 3.68), 42.82 (± 11.80) and 77.33 (± 24.65) at baseline, w52 and ET respectively. Analysis based on the segment with the highest mean RD score per patient showed significant correlation with NHI (r=0.60, p<0.0001), PHRI (r=0.62, p<0.0001). In the rectum the RD score at all time points correlated significant with NHI (r =0,53, p<0.0001) and PHRI (r=0.63, p<0.0001). Similar correlation was seen in the sigmoid for NHI (r=0.51, p<0.0001) and PHRI (r=0.22, p0.0108). A RD score of <57.5 (Likelihood Ratio (LR) 4.176; AUC 0.7820 (95CI 0.7047 - 0.8593), p<0.0001) was associated with histological remission based on NHI (<2) and a RD score of < 64.5 (LR 9.821; AUC 0.8133 (95%CI 0.7053 - 0.9212), p<0.0001) with histological remission based on PHRI (=0). The current dataset demonstrated to be stable in line with the previously established RD cut-off with GBS and RHI. 1 Conclusion In an independent cohort of patients with UC the correlation with the established and new histological indices for UC is confirmed. This underlines the value of RD as an objective endoscopic tool for the assessment of histological and endoscopic disease activity in UC. Ref 1: Bossuyt P, Nakase H, Vermeire S, De G, Eelbode T, Ferrante M, et al. Automatic, computer-aided determination of endoscopic and histological inflammation in patients with mild to moderate ulcerative colitis based on red density. Gut. 2020;69:1778–86.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".