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

ConditionsLung Cancer Screening Program Artificial Intelligence (AI)

Trial statusRecruiting

Trial phaseNot applicable

Trial typeInterventional

Biological sexAll

Age18+

SponsorScientific Institute San Raffaele

About this trial

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

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

Age >= 50 years old

Active smokers

Former smokers (from no more than 15 years)

Pack/year >20

Disqualifiers

Previous or concurrent neoplastic disease, excluding skin cancers

Cognitive or other problems that could hinder the collection of informed consent

Severe pulmonary or extra pulmonary disease

Previous low-dose computed tomography (CT) scan in the past 12 months

Trial design

Design model

Parallel

Treatments tested in this trial

Computed tomography (CT) scan low dose
Diagnostic test
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.
Blood sampling
Procedure/Surgery
Peripheral venous blood sampling (20 ml)
Tissue sampling (lung)
Procedure/Surgery
sampling of tumor and healthy tissue during surgery
Spirometry
Other intervention
Spirometry measurement using spirometer
Questionnaires
Other intervention
Compilation of epidemiological questionnaire, quality of life questionnaires
Smoking cessation program
Other intervention
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
Carbon monoxide measurment
Other intervention
Measurment of Carbon monoxide (CO)
Cardiovascular primary prevention
Other intervention
Intervention done in order to find the presence of coronary calcifications

Treatment groups

2,840 Participants

are divided into 4 treatment groups

Group A: High-risk screening subjectsExperimental treatment 7 interventions

Group B: Previous positive high-risk screening subjectsExperimental treatment 2 interventions

Group C: Previous negative high-risk screening subjectsNo intervention 0 interventions

Group D: Lung cancer patientsExperimental treatment 2 interventions

Trial outcomes

Primary outcomes

Creation of Artificial Intelligence (AI) algorithm

To train and validate a reliable and unbiased Artificial Intelligence (AI) algorithm that detects the presence of nodules and differentiates between malignant or benign tumor types. AUC (Area Under the Curve) values, expressed as mean and standard deviation (SD), comparing the ability in detecting the presence of nodules and differentiating the malignancy or benignity of a radiologist versus an AI algorithm, both trained on the same patient group.

Time frame

from enrollment to 48 months

Secondary outcomes

Multimodal program

Develop a multimodal program to enhance the prevention and the early detection of multiple smoking-related diseases Presence and absence of lung nodules \> 4 mm with computed tomography (CT) scan

Time frame

from enrollment to 48 months

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

Scientific Institute San Raffaele

Lead sponsor

Source ClinicalTrials.gov

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