Clinical Validation of PolyDeep: an Artificial Intelligence-based Computer-aided Polyp Detection (CADe) and Characterization (CADx) System. Polydeep Advance 2.
Condition: Colorectal Cancer
MeSH terms: Colorectal Neoplasms
Study type: Interventional

Summary: 
      This study is a clinical validation of PolyDeep, a computer-aided polyp detection (CADe) and
      characterization (CADx) system. PolyDeep Advance 2 is a multicentric randomized clinical
      trial with a tandem colonoscopy design. The hypothesis of this study is that Polydeep
      assisted colonoscopy will reduce the number of missed adenomas in the first withdrawal.
    

Detailed description: 
      Colorectal cancer (CRC) is the most frequently cancer in western world. A fundamental tool
      for detection and prevention is the colonoscopy. The detection and endoscopic resection of
      colorectal polyps, the precursor lesion of CRC, can reduce CRC incidence and mortality.
      Adenoma detection rate is the most used endoscopic quality indicator. The improvement of this
      indicator is related to the reduction of postcolonoscopy CRC incidence and mortality.

      Colorectal polyp diagnosis is based on endoscopic resection and histological analysis. An
      accurate optical diagnosis could avoid histological lesion of smaller lesions, reducing the
      costs associated with histological diagnosis. The NICE (NBI International Colorectal
      Endoscopic) Classification has proposed the use of high definition endoscopes that have
      Narrow Band Imaging. However, NICE must be used by endoscopists who are sufficiently prepared
      and who have overcome the learning curve. Therefore, optical histology diagnosis with high
      accuracy independently of the center and the endoscopist is necessary.

      Computer Aid Diagnosis (CAD) systems based on Artificial Intelligence are experiencing
      exponential development in the field of medical image analysis. The development of the CAD
      system is based on the creation of large databases of endoscopic images and/or videos, on the
      training, development and validation of diagnostic algorithms in such databases and, finally,
      on prospective clinical validation in patients undergoing colonoscopy. The goal of CAD
      systems in colonoscopy is double. First, it aims to increase the detection of polyps (CADe)
      in general, and of adenomas and serrated lesions in particular. The second objective is to
      characterize (CADx) the histology of detected lesion.

      PolyDeep CAD is a functional prototype. It is capable of detecting, locating and classifying
      colorectal polyps. In vivo validation data shows that PolyDeep has high diagnostic accuracy
      for polyp identification and that this accuracy can be accommodated This clinical trial is
      part of the clinical validation of PolyDeep. We will perform a randomized clinical trial with
      a tandem colonoscopy design with adenoma miss rate as the main objective.
    

Intervention name(s): Standard technique First colonoscopy without PolyDeep; Combination technique First colonoscopy with PolyDeep
Intervention type(s): Diagnostic Test; Diagnostic Test
Intervention description(s): Standard technique First colonoscopy without PolyDeep; Combination technique First colonoscopy with PolyDeep
Allocation: Randomized
Intervention model: Crossover Assignment
Intervention model description: Patients who fulfill criteria will be randomly allocated to perform the first withdrawal with the standard technique versus PolyDeep assisted colonoscopy. All colorectal detected polyps will be resected. After a second cecal intubation, second withdrawal will be performed with the opposite technique
Masking: None (Open Label)
Primary purpose: Diagnostic
Keywords: Colorectal Adenoma; Colorectal Serrated Lesions; Colorectal Polyps; Computer-Aided polyp Detection (CAD)