Beyond white light: optical enhancement in conjunction with magnification colonoscopy for the assessment of mucosal healing in ulcerative colitis
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Background and study aim The I-SCAN optical enhancement (OE) system with magnification is a recently introduced combination of optical and digital electronic virtual chromoendoscopy, which enhances mucosal and vascular details. The aim of this pilot study was to investigate the use of I-SCAN OE in the assessment of inflammatory changes in ulcerative colitis (UC). Patients and methods A total of 41 consecutive patients with UC and 9 control patients were examined by I-SCAN OE (Pentax Medical, Tokyo, Japan). Targeted biopsies of the imaged areas were obtained. A new optical enhancement score focusing on mucosal and vascular changes was developed. The diagnostic accuracy of I-SCAN OE was calculated against histology using two UC histological scores – Robarts Histopathology Index (RHI) and ECAP (Extent, Chronicity, Activity, Plus additional findings). Results The overall I-SCAN OE score correlated with ECAP (r = 0.70; P < 0.001). The accuracy of the overall I-SCAN OE score to detect abnormalities by ECAP was 80 % (sensitivity 78 %, specificity 100 %). I-SCAN OE vascular and mucosal scores correlated with ECAP (r = 0.65 and 0.71, respectively; P < 0.001). The correlation between overall I-SCAN OE score and RHI was r = 0.61 (P < 0.01), and the accuracy to detect abnormalities by RHI was 68 % (sensitivity 78 %, specificity 50 %). The majority of patients with Mayo 0 had abnormalities on I-SCAN OE. Conclusion In UC, the new I-SCAN OE technology accurately identified mucosal inflammation, and correlated well with histological scores of chronic and acute changes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it