Iterative Health Presents Award-Winning Research on the Benefits of Gastroenterological Technology at the American College of Gastroenterology Annual Scientific Meeting
Iterative Health, a pioneer in precision-medicine technologies for gastroenterology, announced today the results of new research unveiled at the American College of Gastroenterology (ACG) Annual Scientific Meeting. The five publications shared at the event capture Iterative Health's research findings, which explore the use of Computer-Aided Detection (CADe) devices and artificial intelligence (AI) in improving clinical trial recruitment for inflammatory bowel disease. This research represents strides toward enhancing the detection of precursor adenomas and streamlining clinical trial recruitment processes in gastroenterology, ultimately bringing us closer to a future of advancing patient care in the field. The publications include:
Outstanding Research Award by American College of Gastroenterology
Abstract Title: Endoscopist and procedure-level factors associated with increased adenoma detection with the use of a computer-aided detection (CADe) device
Authors: Aasma Shaukat, MD, MPH; David R Lichtenstein, MD; Daniel C Chung, MD; Yeli Wang, PhD, Emma E Navajas, BS; Daniel R Colucci, BS; Shrujal Baxi, MD; Sahin Coban, MD; and William R Brugge, MD.
Abstract Title: Artificial Intelligence (AI) in Endoscopy to Aid in Clinical Trial Recruitment in Inflammatory Bowel Disease (IBD)
Authors: William Holderman, MD; Parth Jain; Mitchell Reddan, MS; Haig Soghigian, MBA; Christopher Fourment, MD. Affiliations: Center for Crohn's and Colitis, Tacoma, WA (W.H.)., Rutgers University New Brunswick, Department of Computer Science, New Brunswick, NJ (P.J.); Iterative Health, Inc., Boston, MA (M.R., H.S., C.F.).
Abstract Title: Adenoma Prevalence with the Use of a Computer Aided Detection Device (CADe) by Patient Demographics
Authors: Sahin Coban, MD, David Lichtenstein, MD, Aasma Shaukat, MD, MPH; Yeli Wang, PhD; Daniel R Colucci, BS; Shrujal Baxi, MD; Emma Navajas, BS; William R Brugge, MD. Division of Geriatrics, Department of Medicine, School of Medicine & Health Sciences, University of North Dakota (S.C.); Division of Gastroenterology, Department of Medicine, Mount Auburn Hospital, Harvard Medical School, Boston, MA (L.B.,W.B.)
Abstract Title: Impact of Reviewers' Characteristics and Training Programs on Inter-Observer Variability of Endoscopic Scoring Systems - A Systematic Review and Meta-Analysis
Authors: Jana G. Hashash, Francis A. Farraye, Yeli Wang, Daniel R. Colucci, Shrujal Baxi, Sadaf Muneer, Faye Yu Ci Ng, Pratik Shingru, and Gil Y. Melmed.
Abstract Title: Inter- and Intra-observer variability of Endoscopic Scoring Systems in Ulcerative Colitis and Crohn's Disease - A Systematic Review and Meta-Analysis
Authors: Jana G. Hashash, Francis A. Farraye, Yeli Wang, Daniel R. Colucci, Shrujal Baxi, Sadaf Muneer, Faye Yu Ci Ng, Pratik Shingru, and Gil Y. Melmed.
The study titled "Endoscopist and procedure-level factors associated with increased adenoma detection with the use of a computer-aided detection (CADe) device," led by Dr. Aasma Shaukat, MD, MPH, Scientific Advisory Board Lead and Robert M. and Mary H. Glickman Professor of Medicine, was recognized with the "Outstanding Research Award" in the General Endoscopy Category. The pivotal research concludes that CADe devices are beneficial in increasing adenomas per colonoscopy (APC) at both community and academic centers and at all times of day. The work also suggests that existing guidelines for high-quality colonoscopy around bowel preparation and withdrawal time must be maintained with the use of CADe.1
"This research follows the groundbreaking data we published in 2022 that evaluated the clinical benefit and safety of using a CADe device during colonoscopy procedures. Just over one year later, this team continues to demonstrate the value and importance of bringing AI-assisted tools into the endoscopy suite," Dr. Shaukat said. "We are thrilled that our research was recognized at ACG this year as it validates what we already knew about CADe devices such as SKOUT®: that they have the potential to reduce variability in screenings based on provider factors, and ultimately continue to benefit both the patient and the provider."2
The five publications capture insights related to both CADe devices and the use of AI to aid in clinical trial recruitment ? both major areas of innovation for Iterative Health. The company's two primary offerings, SKOUT® and Clinical Trial Optimization (CTO), both utilize AI to help drive the GI field forward. SKOUT® is a real-time, FDA cleared polyp detection device that uses artificial intelligence to help gastroenterologists detect more adenomas during colonoscopy,3 and CTO is a suite of end-to-end services to help optimize clinical research, from site selection to patient recruitment and enrollment.
"Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the United States, and CADe tools have the tremendous capability to increase adenoma detection per colonoscopy.4 5 We're excited to present updated data that demonstrates how CADe devices can increase colonoscopy quality metrics across patient sex and age, two main demographic risk factors for CRC," said Dr. David Lichtenstein, gastroenterologist, Director of the Endoscopy Program at Boston Medical Center and investigator on the studies titled "Endoscopist and procedure-level factors associated with increased adenoma detection with the use of a computer-aided detection (CADe) device" and "Adenoma Prevalence with the Use of a Computer Aided Detection Device (CADe) by Patient Demographics."
All five abstracts are now available on the ACG website. To learn more about Iterative Health, please visit iterative.health.
About Iterative Health
Iterative Health is pioneering the use of artificial intelligence-based precision medicine in gastroenterology (GI), with the aim of helping to optimize clinical trials investigating treatment of inflammatory bowel disease (IBD) and improving the accuracy of colorectal cancer screenings. We use advanced machine learning and computer vision to interpret endoscopic images along with other types of data, helping clinicians to better assess patients with potential GI problems. This gives practitioners enhanced capabilities in the detection, annotation, disease scoring and treatment of GI related diseases.
The company is based in Cambridge, Massachusetts, with offices across the United States.
[1] Shaukat, A, Lichtenstein, D, et al. (2023) Endoscopist and procedure-level factors associated with increased adenoma detection with the use of a computer-aided detection (CADe) device. The American Journal of Gastroenterology. https://doi.org/10.14309/ajg.0000000000002479
[2] Ibid
[3] Shaukat A, Lichtenstein D, Somers S, et al. (2022). Computer-Aided Detection Improves Adenomas per Colonoscopy for Screening and Surveillance Colonoscopy: A Randomized Trial. Gastroenterology. https://doi.org/10.1053/j.gastro.2022.05.028
[4] Ibid
[5] Rebecca S, Kimberly M, Ann Godin S, Colorectal Cancer Statistics, 2020. CA Cancer J Clin 2020; 70:145-164.
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