Artificial Intelligence to Solve the MissINg of Gastric Cancer (AIMING) (GAIN)

Istituto Clinico Humanitas

Status: Begins enrollment this month

Conditions: Gastric Cancer

Treatments: Device: Integration of Artificial Intelligence (AI) assistance to screening gastroscopy

Study type: Interventional

Funder types: Other

Identifiers

NCT06971471

AIMING

Details and patient eligibility

About

Our AIMING project comprises four core work packages (WPs): WP1. Nation-level randomized controlled trial; WP2. Development of an innovative AI tool; WP3. Novel microsimulation modelling; WP4. Patient inclusion.

The nation-level multi-center tandem randomized controlled trial (WP1) will contribute to a better understanding of how the real-time AI algorithm can reduce miss rate of early gastric cancer and dysplasia during gastroscopy. Moreover, the innovation project will contribute to development of a novel AI tool (WP2) that can stratify the risk of gastric cancer by identifying in vivo precancerous conditions. Furthermore, a microsimulation modelling will allow us to predict how the use of AI can prevent gastric cancer and affect cost and patients' burdens. The assessment of the balance between benefits and harms is quite crucial especially for this type of medical device because the value of innovative tools is sometimes overestimated due to stakeholders' enthusiasm (WP3). Finally, we will take care of patients' perspective throughout the study project by including patient organization in both WP1, 2, and 3 (WP4).

Enrollment: 6,600 estimated patients

Sex: All

Ages: 60+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• All >60 years-old patients undergoing upper-gastrointestinal (GI) endoscopy for selected indications at high-risk of gastric cancer..

Exclusion criteria

• contraindications to upper-GI endoscopy.
• contraindications to biopsy.
• active upper-GI bleeding or urgent upper-GI endoscopy.
• patients with previous upper-GI surgery involving the stomach.
• patients who were not able or refused to give informed written consent.

Trial design

Primary purpose: Prevention

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: None (Open label)

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6,600 participants in 4 patient groups

Parallel arm 1

No Intervention group

Description:

patients will undergo standard high-definition and high-quality upper-GI endoscopy for the detection of gastric lesions with histological mapping according to Sydney system

Parallel arm 2

Active Comparator group

Description:

patients will undergo high-definition and high quality upper-GI endoscopy with real-time assistance by real-time artificial intelligence for the detection of early gastric cancer and gastric dysplasia.

Treatment:

Device: Integration of Artificial Intelligence (AI) assistance to screening gastroscopy

Cross-over arm 1 (control)

Other group

Description:

patients will undergo two standard high-definition and high-quality upper-GI endoscopies in tandem: the first will be without Artificial Intelligence assistance, and the second with Artificial Intelligence in order to define the miss rate for standard unassisted upper-GI endoscopy.

Treatment:

Device: Integration of Artificial Intelligence (AI) assistance to screening gastroscopy

Cross-over arm 2

Active Comparator group

Description:

patients will undergo two standard high-definition and high-quality upper-GI endoscopies in tandem: the first will be with Artificial Intelligence assistance, and the second without Artificial Intelligence in order to define the decrease of miss rate when assistance by Artificial Intelligence is implemented.

Treatment:

Device: Integration of Artificial Intelligence (AI) assistance to screening gastroscopy