Colonoscopy is the cornerstone for colorectal cancer screening, diagnosis, and post-treatment surveillance. Procedural quality is influenced by patient anatomy, particularly variations in colonic configuration such as sigmoid redundancy, looping, and low-lying transverse colon. These features prolong insertion time, increase patient discomfort, and elevate physician workload.

Evidence suggests that prior CT imaging can provide objective and individualized information on colonic anatomy-such as redundancy, angulation, and tortuosity-potentially predicting procedural difficulty. However, existing studies are mainly retrospective or descriptive, lacking prospective randomized evidence on clinical utility.

This single-blind, randomized controlled trial evaluates whether image-assisted colonoscope insertion, based on pre-existing abdominal/pelvic CT scans, can improve cecal intubation time, enhance patient experience, reduce operator workload, and improve overall examination quality compared with standard colonoscopy.

Colonoscopy performance varies widely among patients, with anatomical factors being major contributors to insertion difficulty. Prior CT colonography studies demonstrate high interindividual variability in colon length, flexures, and tortuosity, and up to 73% of patients experience looping during colonoscopy. Fluoroscopy-guided maneuvers have been shown to resolve looping in >95% of cases, highlighting the potential value of anatomical prediction.

This study investigates the feasibility and effectiveness of using information extracted from a patient's previous abdominal/pelvic CT scan (≤5 years) to guide insertion strategy during colonoscopy. Image-assisted guidance may help endoscopists anticipate looping patterns, identify redundant segments, and plan insertion maneuvers more effectively.

A total of 140 participants will be randomized 1:1 into an image-assisted group or standard group. The primary endpoint is cecal intubation time. Secondary endpoints include patient-reported pain (VAS), willingness for future colonoscopy, operator workload (NASA-TLX), looping events, total procedure time, and polyp detection rate. Consistency between CT-based predictions and actual procedural findings will also be assessed.

This trial will provide foundational evidence for individualized, anatomy-informed colonoscopy strategies and support future large-scale studies or AI-assisted implementation.

Inclusion Criteria:

• Age 18-80 years, or expected natural survival >3 years
• Undergoing colonoscopy at Peking Union Medical College Hospital
• Presence of an abdominal/pelvic CT scan performed within ≤5 years and no - - - major abdominal surgery afterward
• Patient or legal guardian able to understand the study and provide written consent

Exclusion Criteria:

• No available CT or CT quality insufficient for anatomical evaluation
• Prior colonic surgery affecting anatomy (e.g., right hemicolectomy, transverse colectomy)
• Severe cardiopulmonary dysfunction or coagulopathy
• Pregnancy
• Refusal to participate or inability to complete questionnaires
• Patient or guardian unable to understand study requirements

The individual participant data (IPD) will not be shared. Only aggregated results will be published.