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Impact of CADx on Endoscopists' Histologic Characterization of Diminutive Colorectal Polyps

Impact of CADx on Endoscopists' Histologic Characterization of Diminutive Colorectal Polyps

Status
Completed
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT07389759
Enrollment
399
Registered
2026-02-05
Start date
2026-01-03
Completion date
2026-03-31
Last updated
2026-07-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Colorectal Polyps

Brief summary

This study evaluates the impact of CADx assistance on endoscopists' histologic characterization of diminutive colorectal polyps (≤5 mm) during colonoscopy. The primary objective is to determine whether CADx assistance increases the proportion of endoscopists who meet PIVI-related performance thresholds, thereby supporting implementation of the "resect and discard" and "diagnose and leave" strategies in routine clinical practice.

Detailed description

This study evaluates the impact of CADx assistance on endoscopists' histologic characterization of diminutive colorectal polyps (≤5 mm) during colonoscopy. The primary objective is to determine whether CADx assistance increases the proportion of endoscopists who meet PIVI-related performance thresholds, thereby supporting implementation of the "resect and discard" and "diagnose and leave" strategies in routine clinical practice. In this randomized controlled trial, endoscopists will be assigned to one of three arms: no CADx assistance, CADx assistance without predicted probability, or CADx assistance with predicted probability. The CADx system provides NICE-based histology predictions (Type 1 vs Type 2), which endoscopists may use to support optical diagnosis and subsequent management decisions, including surveillance interval recommendations when applicable. Outcomes will compare endoscopist-level pass rates and diagnostic performance metrics relevant to PIVI-based adoption, with histopathology as the reference standard where applicable.

Interventions

DEVICECADx-Assisted Endoscopic Diagnosis System Without Predicted Probability Display

CADx-assisted optical diagnosis (NBI; predicted probability not displayed). Endoscopists perform optical diagnosis of diminutive colorectal polyps (≤5 mm) during colonoscopy using narrow-band imaging (NBI) with CADx-displayed NICE classification predictions for each polyp. In this arm, the CADx output is displayed without any predicted probability information.

DEVICECADx-Assisted Endoscopic Diagnosis System With Predicted Probability Display

CADx-assisted optical diagnosis (NBI; predicted probability displayed). Endoscopists perform optical diagnosis of diminutive colorectal polyps (≤5 mm) during colonoscopy using narrow-band imaging (NBI) with CADx-displayed NICE classification predictions for each polyp. In this arm, the CADx output is displayed with accompanying predicted probability information.

Sponsors

Shanghai Jiao Tong University School of Medicine
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
DIAGNOSTIC
Masking
SINGLE (Subject)

Eligibility

Sex/Gender
ALL
Age
18 Years to 65 Years
Healthy volunteers
No

Inclusion criteria

* Endoscopists with NBI experience

Exclusion criteria

-Endoscopists without colonoscopy and NBI experience

Design outcomes

Primary

MeasureTime frameDescription
Pass rate for the "resect and discard" strategy14 daysProportion of endoscopists who achieve ≥90% accuracy in correctly predicting the patient's recommended surveillance colonoscopy interval according to the 2020 U.S. Multi-Society Task Force (USMSTF) consensus recommendations.
Pass rate for the "diagnose and leave" strategy14 daysProportion of endoscopists who achieve a negative predictive value (NPV) ≥90% for neoplastic lesions among rectosigmoid polyps, when predictions are made with high diagnostic confidence

Secondary

MeasureTime frameDescription
Pass rate for the ESGE 2020-based "resect and discard" strategy14 daysThe proportion of endoscopists who achieve at least 90% accuracy in correctly predicting the patient's recommended next surveillance colonoscopy interval, using surveillance recommendations based on the ESGE 2020 guideline.
Pass rate for the APWG 2022-based "resect and discard" strategy14 daysThe proportion of endoscopists who achieve at least 90% accuracy in correctly predicting the patient's recommended next surveillance colonoscopy interval, using surveillance recommendations based on the APWG 2022 consensus.
Pass rate for the China 2023-based "resect and discard" strategy14 daysThe proportion of endoscopists who achieve at least 90% accuracy in correctly predicting the patient's recommended next surveillance colonoscopy interval, using surveillance recommendations based on the Chinese 2023 consensus.
SODA-1 achievement rate14 daysThe proportion of endoscopists who, when reporting high diagnostic confidence, meet the SODA-1 performance thresholds for diagnosing neoplastic pathology in diminutive rectosigmoid polyps, as assessed by sensitivity of at least 90% and specificity of at least 80%, with histopathology as the reference standard.
SODA-2 achievement rate14 daysThe proportion of endoscopists who, when reporting high diagnostic confidence, meet the SODA-2 performance thresholds for diagnosing neoplastic pathology in diminutive colorectal polyps, as assessed by sensitivity of at least 80% and specificity of at least 80%, with histopathology as the reference standard.
Proportion of high-confidence optical diagnoses14 daysFor each endoscopist, the percentage of polyp assessments that are labeled as high diagnostic confidence among all polyp assessments performed.
Accuracy of high-confidence optical diagnosis (neoplastic vs non-neoplastic)14 daysFor each endoscopist, the percentage of correct classifications (neoplastic vs non-neoplastic) among assessments labeled as high diagnostic confidence, using histopathology as the reference standard.

Countries

China

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Jul 8, 2026