Application of Hyperspectral Imaging Analysis Technology in the Diagnosis of Colorectal Cancer Based on Colonoscopic Biopsy

NCT05576506 | Completed DMC

• 1 other identifier: 2022-SDU-QILU-G003
• Study Type: observational
• Target: 86
• Locations: 1 country
• Sites: 1

Brief Summary

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

Colorectal Neoplasms; Colorectal Polyp; Colorectal Adenoma; Colorectal SSA

Keywords

Hyperspectral imaging; Artifitial intelligence; colorectal cancer

Outcome Measures

Primary Outcomes (5)

• Accuracy of HSI artificial intelligence model to identify colorectal adenoma and cancer

  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%

  1 year

• Sensitivity

  Sensitivity of HSI artificial intelligence model Sensitivity = number of true positives / (number of true positives + number of false negatives) \* 100%.

  1 year

• Specificity

  Specificity of HSI Artificial Intelligence Model Specificity = number of true negatives / (number of true negatives + number of false positives))\*100%

  1 year

• Negative predictive values(NPV)

  Negative predictive values for HSI artificial intelligence model = number of true negatives / (number of true negatives + number of false negatives)\*100%

  1 year

• AUC (95% CI)

  area under the receiver operating characteristic curve (AUC)

  1 year

Secondary Outcomes (1)

• To record and evaluate any unknown risks and adverse events of hyperspectral imaging in specimen image acquisition

  1 year

Study Arms (1)

Deep learning algorithm group

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.

Eligibility Criteria

• Age: 18 Years - 75 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

patients aged 18-75 years who undergo the colonoscopy examination and biopsy;

You may qualify if:

• patients aged 18-75 years who undergo the colonoscopy examination and biopsy

You may not qualify if:

• 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

Sponsors & Collaborators

• Shandong University: lead

Study Sites (1)

Qilu hosipital

Jinan, Shandong, 250012, China

Location

Biospecimen

Retention: SAMPLES WITH DNA

Biopsies from the colonic or rectal polyps will be prospectively collected hyperspectral images and conducted for histology examination and model validation.

MeSH Terms

Conditions

Colorectal Neoplasms

Condition Hierarchy (Ancestors)

Intestinal Neoplasms; Gastrointestinal Neoplasms; Digestive System Neoplasms; Neoplasms by Site; Neoplasms; Digestive System Diseases; Gastrointestinal Diseases; Colonic Diseases; Intestinal Diseases; Rectal Diseases

Study Officials

• Xiuli Zuo, MD,PhD

  Study Principal investigator

  STUDY CHAIR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Director of Qilu Hospital gastroenterology department

Study Record Dates

• First Submitted: October 8, 2022
• First Posted: October 12, 2022
• Study Start: October 8, 2022
• Primary Completion: December 31, 2022
• Study Completion: December 31, 2022
• Last Updated: July 31, 2024

Record last verified: 2024-07

Locations

CN (1)