Pancolonic Dye Spray Chromoendoscopy to Detect and Resect Ill-Defined Neoplastic Lesions in Colonic Inflammatory Bowel Disease
Bibliographic record
Abstract
Background: Pancolonic dye spray chromoendoscopy (DCE) is used as an adjunct to white light endoscopy (WLE) to enhance the detection and delineation of ill-defined neoplastic (dysplastic) lesions in persons with colonic inflammatory bowel diseases (cIBD). We evaluated the utility of DCE as follow-up to high-definition WLE (HD-WLE) to "unmask" and/or facilitate endoscopic resection of neoplastic lesions. Methods: We retrospectively studied persons with cIBD who underwent DCE as follow-up to HD-WLE between 2013 and 2020. We describe neoplastic findings and management during HD-WLE and DCE exams and report outcomes from post-DCE surveillance exams. Results: Twenty-four persons were studied (mean age 56.7 ± 13.8 years, 50.0% male, 70.8% ulcerative colitis, mean disease duration 18.0 ± 11.0 years). Overall, 32 visible neoplastic lesions were unmasked during DCE, of which 24 were endoscopically resected. DCE facilitated the diagnosis of two cancers. Among 17 persons referred for evaluation of "invisible" neoplasia (detected in non-targeted biopsies) during HD-WLE, DCE identified neoplastic lesions at the same site in eight persons and a different site in four persons. Among seven persons referred for ill-defined visible neoplasia, DCE facilitated complete endoscopic resection in four individuals, whereas two individuals required colectomy for a diagnosis of cancer. Among 19 individuals with post-DCE surveillance, five developed new visible neoplastic lesions, including one high-grade neoplasia which was completely resected. Conclusions: In our cohort, DCE aided in unmasking invisible neoplasia and facilitated endoscopic resection of ill-defined neoplasia, suggesting that it is a useful surveillance tool in selected persons with cIBD. Large prospective studies are needed to validate these findings.
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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 | 0.001 | 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) | 0.001 | 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 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".