2_use_case_name: Computer Aided Detection (CADe) of Neoplasia during Colonoscopy - “GI Genius”
3_agency: Department of Veterans Affairs
3_abr: VA
4_bureau: VHA: Veterans Health Administration
8_topic_area: Health & Medical
10_commercial_ai: None of the above.
11_purpose_benefits: GI Genius™, a commercial product distributed by Medtronic, Inc., is a computer-aided detection module, powered by artificial intelligence, designed to aid endoscopists in detecting colonic mucosal lesions (such as polyps and adenomas) during colonoscopy. The FDA cleared this commercial product in April 2021.
The device physically connects to existing endoscopes, video processors, and display monitors, but does not connect to the VA network.
During endoscopy, the CADe device automatically detects, and highlights suspected neoplastic lesions / polyps in real time. The module was trained and validated with white-light endoscopy videos and continues to be refined with growing datasets. Information about the indications, safety and warnings can be found here: GI Genius™ Intelligent Endoscopy Module - Indications, Safety, and Warnings | Medtronic (https://www.medtronic.com/covidien/en-us/products/gastrointestinal-artificial-intelligence/gi-genius-intelligent-endoscopy/indications-safety-warnings.html)
Multiple studies and meta-analyses have found these devices increase adenoma detection rates, a well-established metric for colonoscopy quality that is related to colon cancer incidence and death. Initial randomized implementation of the devices across VA facilities allowed for a pragmatic evaluation of the impact of these devices on adenoma detection. The evaluation demonstrated that the provision of colonoscopy CADe devices resulted in a statistically significant 21% increase in the odds of adenoma detection and an absolute increase in ADR of approximately 4% compared to colonoscopy without CADe. These devices will improve ADR, which should decrease colorectal cancer incidence and mortality amongst Veterans over time.

12_outputs: The device physically connects to existing endoscopes, video processors, and display monitors, but does not connect to the VA network.  During endoscopy, the CADe device automatically detects, and highlights suspected neoplastic lesions / polyps in real time on the display monitor.
16_dev_stage: Operation and Maintenance
17_impact_type: Both
18_date_initiated: 6/1/2022
19_date_acq_dev_began: 6/30/2022
20_date_implemented: 10/12/2023
22_dev_method: Developed with contracting resources.
23_contract_piids: 36C10X22X0045
24_hisp_support: Yes
25_hisp_name: Veterans Health Administration
27_public_info: No
28_iqa_compliance: Not Applicable. This device does not disseminate information to the public; nor does it store or disseminate any information at all.
29_contains_pii: No
30_saop_review: No
31_data_catalog: Other
31_question_type: Not applicable. No data catalog or repository required.
33_agency_data: No agency-owned data have been, nor are being, used to train the device. However, initial output/outcome evaluations of the device were conducted. The impact of CADe on adenoma detection rate (ADR) was not moderated by patient race, ethnicity, gender, or rurality (p>.05 for each); however, it was moderated by patient age (OR 1.02, 95% CI 1.00-1.03, p=.02), indicating that improvement in ADR after CADe availability was greater for older patients. The impact of CADe on ADR was moderated by the number of years since an endoscopist’s medical degree (OR 1.02; 95% CI 1.00-1.04, p =.04), indicating that ADR improvement with CADe availability was greater for endoscopists with more years since their medical degree. The impact of CADe on ADR was not moderated by endoscopist specialty or sex (p >.05 for both).
34_data_docs: Documentation has been partially completed: Some documentation exists (detailing the composition and any statistical bias or measurement skew for training and evaluation purposes), but documentation took place within this use case’s development.
35_demo_features: Other
35_question_type: None. It does not have access to, nor use, any demographic variables.
37_custom_code: No
38_code_access: No – agency does not have access to source code.
40_has_ato: No
43_infra_provisioned: No
45_compute_request: Other
45_question_type: Not Applicable. This AI is a commercial, off the shelf, FDA cleared device.
47_timely_resources: Yes
49_existing_reuse: None: This use case does not re-use any internally developed tooling or managed infrastructure from any other AI development efforts within the agency.
50_internal_review: Limited documentation for review: Some information regarding the model’s performance on specific benchmarks are available or have been shared with specific stakeholders within the agency.
51_extension_request: No – Agency did not request an extension for this use case.
52_impact_assessment: Yes
53_real_world_testing: Impact evaluation in operational environment: The AI use case has been tested in an operational environment before being fully implemented as a solution and has utilized randomized experiments with a control group or other counterfactual, social systems analysis, or other rigorous research methodologies to evaluate impact and identify potential harm to users as well as broader groups of people.
54_key_risks: Possible risk of increased false positive detection of colorectal lesions leading to unnecessary biopsies or polypectomy. This could result in increased costs and potential complications. Risk of over-reliance on detection by the physician (i.e., automation bias) Risk to education / training of fellows who may become reliant on the technology.
55_independent_eval: TRUE
56_monitor_postdeploy: Intermittent and Manually Updated: A plan for monitoring the AI use case is in place, and requires data science teams to work with DevOps engineers to manually update models at scheduled intervals, and create metrics to detect data distribution shifts between the operational environment and the training data for the model. 
57_autonomous_impact: No - Some individual decisions or actions require direct human oversight.
59_ai_notice: Other
61_adverse_impact: No
62_disparity_mitigation: This FDA cleared AI device was formally evaluated by VA specifically looking for evidence of disparities in performance. The AI device was equally beneficial for all demographic groups evaluated, including by sex, race, and ethnicity. There was a modest increase in benefit with increasing patient age, which may be related to the increased prevalence of precancerous polyps with age.
63_stakeholder_consult: Direct user testing, Post-transaction customer feedback collections
65_appeal_process: No – it is not operationally practical to offer this.
66_no_appeal_reason: This FDA cleared device is designed to assist the endoscopist in recognizing potential colorectal pathology; it does not make a diagnosis. It is ultimately the physician’s decision whether to act upon the findings highlighted by the AI device. The physician has full discretion in these actions. The physician can also turn off the device. There is no mandate to use this device.
67_opt_out: Yes