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NCT Number: NCT06626178

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

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

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Key information

Conditions

Lung Cancer Screening Program Artificial Intelligence (AI) Lung Diseases Lung Neoplasms Neoplasms Neoplasms by Site Respiratory Tract Diseases Respiratory Tract Neoplasms Thoracic Neoplasms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Scientific Institute Ospedale San Raffaele

Milan, 20132, Italy

Location status: Recruiting

Location contact

Piergiorgio Muriana, MD

CONTACT

[email protected]

0226437232 ext. +39

Piergiorgio Muriana, MD

PRINCIPAL_INVESTIGATOR

About this study

Interventional pilot study, single-center with additional procedures, such as completion of EORTC-QLQ-LC29, EORTC-QLQ-C30 questionnaires, motivational test, Fagestrom test, anamnestic questionnaire, spirometry, measurement of carbon monoxide, Low-dose spiral computed tomography without contrast medium, peripheral venous blood sampling for a volume of 20 ml.

The study has the main objective of traininig and validate a reliable and unbiased Artificial Intelligence (AI) algorithm that detects the presence of nodules and differentiates between malignant or benign tumor types.

The study considers patients with suspected diagnosis or with a dignosis of lung cancer, smokers and former smokers over 50 years of age at high risk of lung cancer and subjects enrolled in previous screening cohorts at this Institute.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

High-risk screening subjects

Inclusion criteria

  • Age >= 50 years old
  • Active smokers
  • Former smokers (from no more than 15 years)
  • Pack/year >20
  • Risk-prediction model from Prostate, Lung, Colorectal, and Ovarian study (PLCOm2012) >1.2%
  • Provision and signature of informed consent

Exclusion criteria

  • 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

Previous high-risk positive screening subjects

Inclusion criteria

  • Subjects enrolled in previous lung cancer screening with the presence of lung nodules >4 mm and candidate to additional computed tomography (CT)
  • Signed informed consent

Exclusion criteria

  • None

Previous high-risk negative screening subjects

Inclusion criteria

  • Subjects enrolled in previous lung cancer screening in this Institute with negative computed tomography (CT)
  • Signed informed consent

Exclusion criteria

  • None

Lung Cancer patients

Inclusion criteria

  • Patients with diagnosis or suspicious diagnosis of lung cancer candidate to surgical treatment or already submitted to it
  • Patients with diagnosis of lung cancer treated with surgical resection
  • Signed informed consent

Exclusion criteria

  • computed tomography (CT) scans not available at San Raffaele Hospital
  • Previous neoadjuvant treatment

Treatment and study plan

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

Peripheral venous blood sampling (20 ml)

Tissue sampling (lung)

Procedure

sampling of tumor and healthy tissue during surgery

Spirometry

Other

Spirometry measurement using spirometer

questionnaires

Other

Compilation of epidemiological questionnaire, quality of life questionnaires

Smoking cessation program

Other

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

Measurment of Carbon monoxide (CO)

Cardiovascular primary prevention

Other

Intervention done in order to find the presence of coronary calcifications

Primary outcomes

  1. Creation of Artificial Intelligence (AI) algorithm

    Time frame: from enrollment to 48 months

    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.

Secondary outcomes

  1. Multimodal program

    Time frame: from enrollment to 48 months

    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

Study contacts

Contact information is provided by the study sponsor or research team.

Piergiorgio Muriana, MD

CONTACT

[email protected]

0226437232 ext. +39

Sponsors and collaborators

Lead sponsor

Scientific Institute San Raffaele

Other

Registry information

Official study title

ARtificial Intelligence for heAlth and Prevention of Smoking-related Diseases

Acronym: ARIA

Important dates

Study start
2024
Primary completion
2026
Study completion
2028
First posted
Oct 3, 2024
Registry last updated
Oct 3, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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