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

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

Recruiting
18 years and older
All
Phase N/A

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Overview

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

Description

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.

Eligibility

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

Study details
    Lung Cancer Screening Program
    Artificial Intelligence (AI)

NCT06626178

Scientific Institute San Raffaele

14 September 2025

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