Cutting-edge IMAGING Technologies to Improve the SAFEty and the Sustainability of LUNG Cancer Screening and the Accuracy of Non-invasive Lung Nodules Characterization

NCT06963515 | Not Yet Recruiting

• 1 other identifier: IMAGING-SAFE-LUNG
• Study Type: observational
• Target: 250
• Locations: 0 countries
• Sites: N/A

Brief Summary

Low-dose computed tomography (LDCT) is used in individuals at high risk of developing lung cancer (smokers over 50 years of age), as it allows for the identification of pulmonary nodules, which, in a small percentage of cases, may represent early-stage lung cancer. However, according to LUNG-RADS guidelines, individuals undergoing screening must repeat multiple LDCT scans, as the comparison between successive LDCT scans enables the assessment of existing nodules' progression and the identification of newly developed pulmonary nodules. This results in cumulative exposure to ionizing radiation, increasing the risk of radiation-induced cancers. This study addresses, through the implementation of new imaging techniques utilizing the latest and most advanced technological innovation (high-field 3T Magnetic Resonance Imaging (MRI) with artificial intelligence), the critical challenge of reducing radiation exposure in current LDCT-based screening programs, proposing the use of MRI as an alternative screening method to LDCT.

Conditions

Lung Cancer

Keywords

Magnetic Resonance Imaging; Low Dose Computed Tomography

Outcome Measures

Primary Outcomes (1)

• the sensitivity and specificity for lung nodule detection of a Single Breath- Hold Lung non-contrast MRI scan (SBH-Lung-MRI), lasting less than 20 seconds, in comparison to LDCT

  3 years

Secondary Outcomes (1)

• the sensitivity and specificity for lung nodule detection of SBH-Lung-MRI, lasting less than 20 seconds, in comparison to two of the most accurate available sequences for MRI lung nodule detection, namely: 2D-UTE and spiral 3D- UTE MRI sequences.

  3 years

Other Outcomes (2)

• The health impact of implementing a radiation-free MRI-based lung cancer screening program using the SBH-Lung-MRI approach compared to conventional LDCT screening.

  3 years

• The cost-effectiveness of implementing a radiation-free MRI-based lung cancer screening program using the SBH-Lung-MRI approach tested in specific aim 1 compared to conventional LDCT screening.

  3 years

Interventions

Magnetic Resonance Imaging PROCEDURE

3T Magnetic Resonance Imaging

Eligibility Criteria

• Age: 18 Years - 100 Years
• Sex: all
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The population will include 250 participants at high risk of lung cancer (smokers over 50 years old) already enrolled in screening programmes undergoing baseline or repeated CT scans.

You may qualify if:

• Age ≥ 18 years
• Indication to first lung cancer screening with LDCT according to international guidelines
• Indication to repeated lung cancer screening with LDCT according to international guidelines

You may not qualify if:

• Age \< 18 years
• contraindication to MRI
• presence of metallic implants likely to hamper MRI image quality
• inability to hold breath for 15-20 seconds
• claustrophobia
• refusal to participate in the study

Sponsors & Collaborators

• IRCCS San Raffaele: lead

Related Publications (9)

• National Lung Screening Trial Research Team; Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, Fagerstrom RM, Gareen IF, Gatsonis C, Marcus PM, Sicks JD. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011 Aug 4;365(5):395-409. doi: 10.1056/NEJMoa1102873. Epub 2011 Jun 29.

  PMID: 21714641 BACKGROUND

• de Koning HJ, van der Aalst CM, de Jong PA, Scholten ET, Nackaerts K, Heuvelmans MA, Lammers JJ, Weenink C, Yousaf-Khan U, Horeweg N, van 't Westeinde S, Prokop M, Mali WP, Mohamed Hoesein FAA, van Ooijen PMA, Aerts JGJV, den Bakker MA, Thunnissen E, Verschakelen J, Vliegenthart R, Walter JE, Ten Haaf K, Groen HJM, Oudkerk M. Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial. N Engl J Med. 2020 Feb 6;382(6):503-513. doi: 10.1056/NEJMoa1911793. Epub 2020 Jan 29.

  PMID: 31995683 BACKGROUND

• Potter AL, Rosenstein AL, Kiang MV, Shah SA, Gaissert HA, Chang DC, Fintelmann FJ, Yang CJ. Association of computed tomography screening with lung cancer stage shift and survival in the United States: quasi-experimental study. BMJ. 2022 Mar 30;376:e069008. doi: 10.1136/bmj-2021-069008.

  PMID: 35354556 BACKGROUND

• Christensen J, Prosper AE, Wu CC, Chung J, Lee E, Elicker B, Hunsaker AR, Petranovic M, Sandler KL, Stiles B, Mazzone P, Yankelevitz D, Aberle D, Chiles C, Kazerooni E. ACR Lung-RADS v2022: Assessment Categories and Management Recommendations. J Am Coll Radiol. 2024 Mar;21(3):473-488. doi: 10.1016/j.jacr.2023.09.009. Epub 2023 Oct 10.

  PMID: 37820837 BACKGROUND

• McCunney RJ, Li J. Radiation risks in lung cancer screening programs: a comparison with nuclear industry workers and atomic bomb survivors. Chest. 2014 Mar 1;145(3):618-24. doi: 10.1378/chest.13-1420.

  PMID: 24590022 BACKGROUND

• Ohno Y, Takenaka D, Yoshikawa T, Yui M, Koyama H, Yamamoto K, Hamabuchi N, Shigemura C, Watanabe A, Ueda T, Ikeda H, Hattori H, Murayama K, Toyama H. Efficacy of Ultrashort Echo Time Pulmonary MRI for Lung Nodule Detection and Lung-RADS Classification. Radiology. 2022 Mar;302(3):697-706. doi: 10.1148/radiol.211254. Epub 2021 Nov 30.

  PMID: 34846203 BACKGROUND

• Sommer G, Tremper J, Koenigkam-Santos M, Delorme S, Becker N, Biederer J, Kauczor HU, Heussel CP, Schlemmer HP, Puderbach M. Lung nodule detection in a high-risk population: comparison of magnetic resonance imaging and low-dose computed tomography. Eur J Radiol. 2014 Mar;83(3):600-5. doi: 10.1016/j.ejrad.2013.11.012. Epub 2013 Dec 4.

  PMID: 24364923 BACKGROUND

• Heuvelmans MA, Walter JE, Peters RB, Bock GH, Yousaf-Khan U, Aalst CMV, Groen HJM, Nackaerts K, Ooijen PMV, Koning HJ, Oudkerk M, Vliegenthart R. Relationship between nodule count and lung cancer probability in baseline CT lung cancer screening: The NELSON study. Lung Cancer. 2017 Nov;113:45-50. doi: 10.1016/j.lungcan.2017.08.023. Epub 2017 Sep 1.

  PMID: 29110848 BACKGROUND

• McWilliams A, Tammemagi MC, Mayo JR, Roberts H, Liu G, Soghrati K, Yasufuku K, Martel S, Laberge F, Gingras M, Atkar-Khattra S, Berg CD, Evans K, Finley R, Yee J, English J, Nasute P, Goffin J, Puksa S, Stewart L, Tsai S, Johnston MR, Manos D, Nicholas G, Goss GD, Seely JM, Amjadi K, Tremblay A, Burrowes P, MacEachern P, Bhatia R, Tsao MS, Lam S. Probability of cancer in pulmonary nodules detected on first screening CT. N Engl J Med. 2013 Sep 5;369(10):910-9. doi: 10.1056/NEJMoa1214726.

  PMID: 24004118 BACKGROUND

MeSH Terms

Conditions

Lung Neoplasms

Interventions

Magnetic Resonance Spectroscopy

Condition Hierarchy (Ancestors)

Respiratory Tract Neoplasms; Thoracic Neoplasms; Neoplasms by Site; Neoplasms; Lung Diseases; Respiratory Tract Diseases

Intervention Hierarchy (Ancestors)

Spectrum Analysis; Chemistry Techniques, Analytical; Investigative Techniques

Central Study Contacts

Antonio A Esposito, MD

CONTACT

0226436102; esposito.antonio@hsr.it

Davide Vignale, MD

CONTACT

vignale.davide@hsr.it

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: February 19, 2025
• First Posted: May 9, 2025
• Study Start: June 20, 2025
• Primary Completion (Estimated): June 20, 2027
• Study Completion (Estimated): June 20, 2028
• Last Updated: May 9, 2025

Record last verified: 2025-04

Data Sharing

• IPD Sharing: Will not share