Clinical Validation of PolyDeep: an Artificial Intelligence-based Computer-aided Polyp Detection (CADe) and Characterization (CADx) System. Polydeep Advance 3

PolyDeep Advance 3: Randomized Clinical Trial Comparing High Definition Colonoscopy With PolyDeep Assisted High Definition Colonoscopy.

This study is a clinical validation of PolyDeep, a computer-aided polyp detection (CADe) and characterization (CADx) system. PolyDeep Advance 3 is a multicentric randomized clinical trial comparing high definition colonoscopy with PolyDeep assisted high definition colonoscopy. The hypothesis of the study is that the PolyDeep assisted colonoscopy increases the Adenoma Detection Rate (ADR).

Study Overview

• Status: Recruiting
• Conditions: Colorectal Cancer
• Intervention / Treatment: Diagnostic test: High definition colonoscopy (standard colonoscopy) in Adenoma Detection Rate; Diagnostic test: PolyDeep assisted high definition colonoscopy (CAD system) in Adenoma Detection Rate

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 use high definition endoscopes that have Narrow Band Imaging (NBI). 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, the CAD system 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. This CAD system 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 3 is to compare Adenoma Detection Rate differences in a randomized clinical trial. The investigators will compare the Adenoma Detection Rate between high definition colonoscopy and PolyDeep assisted high definition colonoscopy, both in CRC screening and surveillance.

• Study Type: Interventional
• Enrollment (Estimated): 854
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Joaquín Cubiella Fernandez, MD PhD; Phone Number: 0034988385824; Email: joaquin.cubiella.fernandez@sergas.es
• Study Contact Backup: Name: Miguel Reboiro Jato, PhD

Study Locations

• Spain
  • Ourense, Spain, 32003.
    • Recruiting
    • Complexo Hospitalario Universitario de Ourense
    • Principal Investigator: Joaquín Cubiella, MD, PhD
    • Sub-Investigator: Pedro Davila, Masters degree
  • Pontevedra, Spain
    • Recruiting
    • Hospital de Montecelo
  • Pontevedra
    • Vigo, Pontevedra, Spain
      • Recruiting
      • Hospital Álvaro Cunqueiro (Vigo)

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 informed consent.

Exclusion Criteria:

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

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Diagnostic
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Other: Control arm: High definition colonoscopy; Diagnostic test: Standard colonoscopy	Diagnostic test: High definition colonoscopy (standard colonoscopy) in Adenoma Detection Rate; In the intervention of this arm the investigators will apply the standard colonoscopy without computer-aided colonoscopy (polyDeep)
Experimental: PolyDeep assisted high definition colonoscopy; Diagnostic test: PolyDeep	Diagnostic test: PolyDeep assisted high definition colonoscopy (CAD system) in Adenoma Detection Rate; In the intervention of this arm the investigators will apply polyDeep assisted high definition colonoscopy (CAD system).

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Adenoma Detection Rate (ADR)	Number of colonoscopies with adenomas/total number of colonoscopies. The investigators will evaluate if there are differences between both arms.	1.5 years

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Polyp detection rate	Number of colonoscopies with polyps/total number of colonoscopies. The investigators will evaluate if there are differences between both arms.	1.5 years
Serrated lesion detection rate	Number of colonoscopies with serrated lesions/total number of colonoscopies. The investigators will evaluate if there are differences between both arms.	1.5 years
Advanced lesion detection rate	Number of colonoscopies with advanced lesions (adenomas≥10mm, villous histology or high grade dysplasia; serrated lesions with dysplasia or ≥10mm) /total number of colonoscopies. The investigators will evaluate if there are differences between both arms.	1.5 years
Withdrawal time:	Withdrawal time between the two arms will be calculated and compared by the investigators	1.5 years
Characterization of the detected lesions.	The investigators will evaluate the optical diagnosis accuracy of Polydeep for the final histological diagnosis (sensitivity, specificity, positive and negative predictive values).	1.5 years

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.
• Liu A, Wang H, Lin Y, Fu L, Liu Y, Yan S, Chen H. Gastrointestinal endoscopy nurse assistance during colonoscopy and polyp detection: A PRISMA-compliant meta-analysis of randomized control trials. Medicine (Baltimore). 2020 Aug 21;99(34):e21278. doi: 10.1097/MD.0000000000021278.

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): November 17, 2023
• Primary Completion (Actual): March 15, 2024
• Study Completion (Estimated): May 31, 2024

Study Registration Dates

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

Study Record Updates

• Last Update Posted (Actual): April 3, 2024
• Last Update Submitted That Met QC Criteria: April 2, 2024
• Last Verified: November 1, 2023

More Information

Terms related to this study

• Keywords: Colorectal polyps; Serrated lesions; Colorectal adenomas; Polydeep; computer-aided System
• 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 3.0

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: There are not a plan to make Individual Participant Data (IPD)

Drug and device information, study documents

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