Clinical trial · Observational
Application of Hyperspectral Imaging Analysis Technology in the Diagnosis of Colorectal Cancer Based on Colonoscopic Biopsy
NCT05576506CI-TRIAL-00079341completedClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
The purpose of this study is to develop and validate a deep learning algorithm for the diagnosis of colorectal cancer other colorectal disease by marking and analyzing the characteristics of hyperspectral images based on the pathological results of colonoscopic biopsy, so as to improve the objectiveness and intelligence of early colorectal cancer diagnosis.
Conditions
Conditions (4)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Colorectal Adenoma | Colorectal Adenoma | ONTOLOGY_EXACT | 0.98 |
| Colorectal Neoplasms | Colorectal Neoplasm | ONTOLOGY_EXACT | 0.98 |
| Colorectal Polyp | — | UNRESOLVED | — |
| Colorectal SSA | — | UNRESOLVED | — |
Interventions
Interventions (0)
Data not yet available
No intervention recorded.
Design
Arms and outcomes
Arms (1)
- label
- Deep learning algorithm group
- description
- After the patient has passed the screening, a routine colonoscopy will be performed, and the target tissue with suspected inflammation or neoplasia will be biopsied. The clinical investigators use the hyperspectral microscope to collect image information of the biopsy tissue in the endoscopy room. After collecting information, biopsy specimens will be routinely processed and sent for pathological diagnosis.
Primary outcomes (5)
- measure
- Accuracy of HSI artificial intelligence model to identify colorectal adenoma and cancer
- timeFrame
- 1 year
- description
- Accuracy of hyperspectral imaging (HSI) artificial intelligence model to identify colorectal hyperplastic polyp, adenoma, SSL and colorectal cancer. Accuracy of artificial intelligence models Accuracy = (true positives + true negatives) / total number of subjects \* 100%
- measure
- Sensitivity
- timeFrame
- 1 year
- description
- Sensitivity of HSI artificial intelligence model Sensitivity = number of true positives / (number of true positives + number of false negatives) \* 100%.
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
- Maximum age
- 75 Years
Show eligibility criteria text
Inclusion Criteria: * patients aged 18-75 years who undergo the colonoscopy examination and biopsy Exclusion Criteria: * patients with severe cardiac, cerebral, pulmonary or renal dysfunction or psychiatric disorders who cannot participate in colonoscopy * patients with previous surgical procedures on the gastrointestinal tract. * patients with contraindications to biopsy * patients who refuse to sign the informed consent form
References
Publications (0)
Data not yet available
No reference posted for this study.