Confocal Laser Endomicroscopy for the Diagnosis of Urothelial Carcinoma in the Bladder and the Upper Urinary Tract: Protocols for Two Prospective Explorative Studies
Bibliographic record
Abstract
BACKGROUND: Visual confirmation of a suspicious lesion in the urinary tract is a major corner stone in diagnosing urothelial carcinoma. However, during cystoscopy (for bladder tumors) and ureterorenoscopy (for tumors of the upper urinary tract) no real-time histopathologic information can be obtained. Confocal laser endomicroscopy (CLE) is an optical imaging technique that allows for in vivo high-resolution imaging and may allow real-time tumor grading of urothelial lesions. OBJECTIVE: The primary objective of both studies is to develop descriptive criteria for in vivo CLE images of urothelial carcinoma (low-grade, high-grade, carcinoma in situ) and normal urothelium by comparing CLE images with corresponding histopathology. METHODS: In these two prospective clinical trials, CLE imaging will be performed of suspicious lesions and normal tissue in the urinary tract during surgery, prior to resection or biopsy. In the bladder study, CLE will be performed in 60 patients using the Cystoflex UHD-R probe. In the upper urinary tract study, CLE will be performed in 25 patients during ureterorenoscopy, who will undergo radical treatment (nephroureterectomy or segmental ureter resection) thereafter. All CLE images will be analyzed frame by frame by three independent, blinded observers. Histopathology and CLE-based diagnosis of the lesions will be evaluated. Both studies comply with the IDEAL stage 2b recommendations. RESULTS: Presently, recruitment of patients is ongoing in both studies. Results and outcomes are expected in 2018. CONCLUSIONS: For development of CLE-based diagnosis of urothelial carcinoma in the bladder and the upper urinary tract, a structured conduct of research is required. This study will provide more insight in tissue-specific CLE criteria for real-time tumor grading of urothelial carcinoma. TRIAL REGISTRATION: Confocal Laser Endomicroscopy: ClinicalTrials.gov NCT03013894; https://clinicaltrials.gov /ct2/show/NCT03013894?term=NCT03013894&rank=1 (Archived by WebCite at http://www.webcitation.org/6wiPZ378I); and Dutch Central Committee on Research Involving Human Subjects NL55537.018.15; https://www.toetsingonline.nl /to/ccmo_search.nsf/fABRpop?readform&unids=6B72AE6EB0FC3C2FC125821F001B45C6 (Archived by WebCite at http://www.webcitation.org/6wwJQvqWh). Confocal Laser Endomicroscopy in the upper urinary tract: ClinicalTrials.gov NCT03013920; https://clinicaltrials.gov/ct2/show/NCT03013920? term=NCT03013920&rank=1 (Archived by WebCite at http://www.webcitation.org/6wiPkjyt0); and Dutch Central Committee on Research Involving Human Subjects NL52989.018.16; https://www.toetsingonline.nl/to/ccmo_search.nsf/fABRpop?readform&unids=D27C9C3E5755CFECC12581690016779F (Archived by WebCite at http://www.webcitation.org/6wvy8R44C).
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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 | 0.062 | 0.014 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".