Development of an Artificial Intelligence Model for the Identification and Prevention of Smoking-related Diseases.

Summary

The study is an interventional pilot study. The study is designed to be monocentric and it presents additional procedues.

Conditions

• Lung Cancer Screening Program
• Artificial Intelligence (AI)

Interventions

DIAGNOSTIC_TEST

Computed tomography (CT) scan low dose

The radiological investigation will be done with multi-detector-row (64 or more) computed tomography (CT) scanners at low-dose protocol. The low-dose spiral CT consists of a CT study of the chest, without the need for injection of contrast medium, characterized by less radio exposure than the standard CT of the chest with high sensitivity in detecting pulmonary nodules.

PROCEDURE

Blood sampling

Peripheral venous blood sampling (20 ml)

PROCEDURE

Tissue sampling (lung)

sampling of tumor and healthy tissue during surgery

OTHER

Spirometry

Spirometry measurement using spirometer

OTHER

Questionnaires

Compilation of epidemiological questionnaire, quality of life questionnaires

OTHER

Smoking cessation program

Study guarantee valid support for quitting smoking, which for a smoker is a more effective intervention to reduce the risk of developing lung cancer, myocardial infarction and other smoking-related diseases

OTHER

Carbon monoxide measurment

Measurment of Carbon monoxide (CO)

OTHER

Cardiovascular primary prevention

Intervention done in order to find the presence of coronary calcifications

Sponsors & Collaborators

• Scientific Institute San Raffaele

  lead OTHER

Study Design

Allocation

NON_RANDOMIZED

Purpose

SCREENING

Masking

NONE

Model

PARALLEL

Eligibility

Min Age

18 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2024-10-01

Primary Completion

2026-11-01

Completion

2028-11-01

Countries

• Italy

Study Locations