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Completed

NCT Number: NCT06444373

Artificial Intelligence in Lung Cancer Screening

Single-center, non-profit, observational, retrospective study of collection of clinical and amnestic data and images to create, implement and develop a pilot model of an integrated virtual platform.

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Key information

Conditions

Lung Cancer Screening Asbestos

Age range

50 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

IRCCS San Raffaele Scientific Institute

Milan, 20132, Italy

About this study

The project we propose is a study whose objective was to develop an artificial intelligence program integrated into a web-based platform for the optimization of the performance of lung cancer screening for the diagnosis of lung nodules and risk stratification in subjects exposed to environmental carcinogens and/or cigarette smoke.

Inclusion criteria

Age > 50; smokers for at least 20 pack-years (20 cigarillos a day for 20 years) or former heavy smokers if they quit less than 15 years ago; and/or previous professional exposure to asbestos; absence of lung cancer symptoms; who performed lung cancer screening after the year 2000 upon approval of the study by the relevant EC.

Who can participate

Healthy volunteers accepted: Yes

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

Inclusion criteria

  • Age > 50 years;
  • smokers for at least 20 pack-years (20 cigarettes a day for 20 years) or former heavy smokers if they quit less than 15 years ago;
  • and/or previous professional exposure to asbestos;
  • absence of lung cancer symptoms;
  • who performed lung cancer screening after the year 2000 upon approval of the study by the relevant Etical Committee

Exclusion criteria

  • Age < 50 years
  • never smokers
  • lung cancer symptoms

Treatment and study plan

Primary outcomes

  1. AIM 1 Pilot deep learning model

    Time frame: from enrollment to the end of treatment at 2 years

    Development and fine-tuning of a pilot deep learning model for automatic detection and diagnosis of screen-detected nodules for risk stratification in subjects with asbestos exposure as part of a lung cancer screening program in high-risk subjects for exposure to asbestos and smoking on retrospective data.

Secondary outcomes

  1. AIM 2 Clinical database

    Time frame: from enrollment to the end of treatment at 2 years

    Development of an integrated system between the clinical database and several existing imaging volumetric software and risk models for the creation of a pilot platform in order to optimize the organizational management of lung cancer screening.

Sponsors and collaborators

Lead sponsor

Scientific Institute San Raffaele

Other

Registry information

Official study title

Development of an Artificial Intelligence Model in Lung Cancer Screening for the Diagnosis of Lung Nodules and Risk Stratification in Subjects With Occupational and/or Smoking Exposure

Acronym: INAIL BRIC

Important dates

Study start
2022
Primary completion
2024
Study completion
2024
First posted
Jun 5, 2024
Registry last updated
Jun 5, 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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