Clinical Validation of Polydeep: an Artificial Intelligence-based Computer-aided Polyp Detection (CADe) and Characterization (CADx) System

Polydeep Advance I: Prospective Diagnostic Tests Trial With a Paired Study Design

This study is a clinical validation of Polydeep, a computer-aided polyp detection (CADe) and characterization (CADx) system. Polydeep Advance 1 is an unicentric prospective diagnostic tests trial with a paired study design. The hypothesis of the study is that Polydeep, a CAD system, is more sensitive than a blinded endoscopists for the detection of colorectal polyps in a high definition colonoscopy.

Study Overview

• Status: Completed
• Conditions: Colorectal Cancer
• Intervention / Treatment: Diagnostic test: Sensitivity of Polydeep vs high experienced endoscopists for colorectal polyp detection

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 international 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. The aim of Polydeep advance 1 is to perform the clinical validation within a diagnostic test trial with a paired study design. We will compare the sensitivity of Polydeep to endoscopists blinded to Polydeep in high definition colonoscopy.

• Study Type: Interventional
• Enrollment (Actual): 205
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Spain
  • Ourense, Spain, 32002
    • Complexo Hospitalario Universitario de Ourense

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 40 years to 79 years (Adult, Older Adult)
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• First diagnostic colonoscopy performed after a positive fecal immunochemical test performed within the CRC screening program.
• Surveillance after resection of colorectal adenomas.
• Acceptance after reading the information sheet and signing the informed consent

Exclusion Criteria:

• Colonoscopies with insufficient intestinal cleansing (Boston Bowel Preparation Scale <6 or <2 in any of the evaluated segments).
• Detected lesions without histologic diagnosis.
• Previous CRC
• Previous colonic resection
• Hereditary CRC syndromes
• Serrated polyposis syndrome
• Incomplete colonoscopy without cecal intubation.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Diagnostic
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Sensitivity of Polydeep vs high experienced endoscopists for colorectal polyp detection; Both diagnostic interventions will be performed in all patients: High definition colonoscopy and Polydeep system.	Diagnostic test: Sensitivity of Polydeep vs high experienced endoscopists for colorectal polyp detection; Both diagnostic interventions will be performed in all patients; High definition colonoscopy performed by high experienced endoscopists blinded to Polydeep.; Polydeep: a CADe and CADx system. The gold standard will be the histological diagnosis of the lesion.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Sensitivity of polydeep vs high experienced endoscopist blinded to polydeep	To compare the sensitivity of Polydeep to a high experienced endoscopist for colorectal polyp detection (adenoma or serrated lesion histologically confirmed)	1 year

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Sensitivity for serrated lesions detection.	To compare the sensitivity of Polydeep to a high experienced endoscopist for serrated lesions detection	1 year
Sensitivity for adenoma detection.	To compare the sensitivity of Polydeep to a high experienced endoscopist for adenoma detection	1 year
Sensitivity for advanced colonic lesions	To compare the sensitivity of Polydeep to a high experienced endoscopist for advanced colonic lesions (serrated lesions ≥10mm and/or dysplasia, adenoma ≥10mm and/or villous histology and/or high grade dysplasia) detection	1 year
Sensitivity for diminute lesions (≤5mm)	To compare the sensitivity of Polydeep to a high experienced endoscopist for diminute lesions (≤5mm) detection	1 year
To compare the diagnostic yield of the optical diagnosis	To compare diagnostic yield of optic diagnostic of polydeep to high experienced endoscopists.	1 year

Collaborators and Investigators

• Sponsor: Fundacin Biomedica Galicia Sur

Publications and helpful links

General Publications

• Hassan C, Spadaccini M, Iannone A, Maselli R, Jovani M, Chandrasekar VT, Antonelli G, Yu H, Areia M, Dinis-Ribeiro M, Bhandari P, Sharma P, Rex DK, Rosch T, Wallace M, Repici A. Performance of artificial intelligence in colonoscopy for adenoma and polyp detection: a systematic review and meta-analysis. Gastrointest Endosc. 2021 Jan;93(1):77-85.e6. doi: 10.1016/j.gie.2020.06.059. Epub 2020 Jun 26.
• Corley DA, Jensen CD, Marks AR, Zhao WK, Lee JK, Doubeni CA, Zauber AG, de Boer J, Fireman BH, Schottinger JE, Quinn VP, Ghai NR, Levin TR, Quesenberry CP. Adenoma detection rate and risk of colorectal cancer and death. N Engl J Med. 2014 Apr 3;370(14):1298-306. doi: 10.1056/NEJMoa1309086.
• Cubiella J, Marzo-Castillejo M, Mascort-Roca JJ, Amador-Romero FJ, Bellas-Beceiro B, Clofent-Vilaplana J, Carballal S, Ferrandiz-Santos J, Gimeno-Garcia AZ, Jover R, Mangas-Sanjuan C, Moreira L, Pellise M, Quintero E, Rodriguez-Camacho E, Vega-Villaamil P; Sociedad Espanola de Medicina de Familia y Comunitaria y Asociacion Espanola de Gastroenterologia. Clinical practice guideline. Diagnosis and prevention of colorectal cancer. 2018 Update. Gastroenterol Hepatol. 2018 Nov;41(9):585-596. doi: 10.1016/j.gastrohep.2018.07.012. Epub 2018 Sep 20. English, Spanish.
• Zhao S, Wang S, Pan P, Xia T, Chang X, Yang X, Guo L, Meng Q, Yang F, Qian W, Xu Z, Wang Y, Wang Z, Gu L, Wang R, Jia F, Yao J, Li Z, Bai Y. Magnitude, Risk Factors, and Factors Associated With Adenoma Miss Rate of Tandem Colonoscopy: A Systematic Review and Meta-analysis. Gastroenterology. 2019 May;156(6):1661-1674.e11. doi: 10.1053/j.gastro.2019.01.260. Epub 2019 Feb 6.
• Puig I, Lopez-Ceron M, Arnau A, Rosinol O, Cuatrecasas M, Herreros-de-Tejada A, Ferrandez A, Serra-Burriel M, Nogales O, Vida F, de Castro L, Lopez-Vicente J, Vega P, Alvarez-Gonzalez MA, Gonzalez-Santiago J, Hernandez-Conde M, Diez-Redondo P, Rivero-Sanchez L, Gimeno-Garcia AZ, Burgos A, Garcia-Alonso FJ, Bustamante-Balen M, Martinez-Bauer E, Penas B, Pellise M; EndoCAR group, Spanish Gastroenterological Association and the Spanish Digestive Endoscopy Society. Accuracy of the Narrow-Band Imaging International Colorectal Endoscopic Classification System in Identification of Deep Invasion in Colorectal Polyps. Gastroenterology. 2019 Jan;156(1):75-87. doi: 10.1053/j.gastro.2018.10.004. Epub 2018 Oct 6.
• Jin EH, Lee D, Bae JH, Kang HY, Kwak MS, Seo JY, Yang JI, Yang SY, Lim SH, Yim JY, Lim JH, Chung GE, Chung SJ, Choi JM, Han YM, Kang SJ, Lee J, Chan Kim H, Kim JS. Improved Accuracy in Optical Diagnosis of Colorectal Polyps Using Convolutional Neural Networks with Visual Explanations. Gastroenterology. 2020 Jun;158(8):2169-2179.e8. doi: 10.1053/j.gastro.2020.02.036. Epub 2020 Feb 29.
• Parmar R, Martel M, Rostom A, Barkun AN. Validated Scales for Colon Cleansing: A Systematic Review. Am J Gastroenterol. 2016 Feb;111(2):197-204; quiz 205. doi: 10.1038/ajg.2015.417. Epub 2016 Jan 19.
• Parsa N, Rex DK, Byrne MF. Colorectal polyp characterization with standard endoscopy: Will Artificial Intelligence succeed where human eyes failed? Best Pract Res Clin Gastroenterol. 2021 Jun-Aug;52-53:101736. doi: 10.1016/j.bpg.2021.101736. Epub 2021 Feb 22.
• Wani S, Rastogi A. Narrow-band imaging in the prediction of submucosal invasive colon cancer: how "NICE" is it? Gastrointest Endosc. 2013 Oct;78(4):633-6. doi: 10.1016/j.gie.2013.06.015. No abstract available.
• Mangas-Sanjuan C, Santana E, Cubiella J, Rodriguez-Camacho E, Seoane A, Alvarez-Gonzalez MA, Suarez A, Alvarez-Garcia V, Gonzalez N, Lue A, Cid-Gomez L, Ponce M, Bujanda L, Portillo I, Pellise M, Diez-Redondo P, Herraiz M, Ono A, Pizarro A, Zapater P, Jover R; QUALISCOPIA Study Investigators. Variation in Colonoscopy Performance Measures According to Procedure Indication. Clin Gastroenterol Hepatol. 2020 May;18(5):1216-1223.e2. doi: 10.1016/j.cgh.2019.08.035. Epub 2019 Aug 22.
• ASGE Technology Committee; Abu Dayyeh BK, Thosani N, Konda V, Wallace MB, Rex DK, Chauhan SS, Hwang JH, Komanduri S, Manfredi M, Maple JT, Murad FM, Siddiqui UD, Banerjee S. ASGE Technology Committee systematic review and meta-analysis assessing the ASGE PIVI thresholds for adopting real-time endoscopic assessment of the histology of diminutive colorectal polyps. Gastrointest Endosc. 2015 Mar;81(3):502.e1-502.e16. doi: 10.1016/j.gie.2014.12.022. Epub 2015 Jan 16.

Helpful Links

• Polydeep website
• Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study.
• 43th congress of digestive endoscopy spanish society

Study record dates

Study Major Dates

• Study Start (Actual): January 30, 2023
• Primary Completion (Actual): March 15, 2023
• Study Completion (Actual): April 11, 2023

Study Registration Dates

• First Submitted: August 22, 2022
• First Submitted That Met QC Criteria: August 23, 2022
• First Posted (Actual): August 24, 2022

Study Record Updates

• Last Update Posted (Actual): April 18, 2023
• Last Update Submitted That Met QC Criteria: April 17, 2023
• Last Verified: May 1, 2022

More Information

Terms related to this study

• Keywords: Colorectal polyps; Serrated lesions; Colorectal adenomas; Computer-Aided detection System (CAD)
• Additional Relevant MeSH Terms: Digestive System Diseases; Neoplasms; Neoplasms by Site; Gastrointestinal Neoplasms; Digestive System Neoplasms; Gastrointestinal Diseases; Colonic Diseases; Intestinal Diseases; Intestinal Neoplasms; Rectal Diseases; Colorectal Neoplasms
• Other Study ID Numbers: PolyDeep Advance 1.0

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No