Next Generation Chest X-Ray Tomosynthesis for Screening of Lung Cancer

NCT06577883 | Recruiting

• 1 other identifier: 805210
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this observational clinical trial is to learn if chest tomosynthesis is a potential alternative to computed tomography for the detection of lung cancer. It will also develop artificial intelligence tools to aid in the diagnosis of lung cancer on chest tomosynthesis images. The main questions it aims to answer are:

• What is the accuracy of chest X-ray tomosynthesis in diagnosing lung cancer in a population of individuals undergoing lung cancer screening or evaluation of a suspicious lung nodule?
• Can artificial intelligence help us detect lung cancer on chest tomosynthesis images? Researchers will compare chest tomosynthesis images to computed tomography scans for each participant to see how they compare in diagnosing lung cancer. Participants will a chest tomosynthesis scan in addition to their routine clinical computed tomography scan.

Conditions

Lung Cancer

Outcome Measures

Primary Outcomes (1)

• Chest X-ray tomosynthesis detection of lung cancer

  Diagnostic accuracy of chest tomosynthesis in identifying biopsy-proven lung cancer

  through 12/31/2026

Secondary Outcomes (1)

• Chest X-ray tomosynthesis detection of suspicious nodules

  through 12/31/2026

Study Arms (1)

Chest X-ray Tomosynthesis Participants

Participants who had a recent, routine clinical chest computed tomography scan for lung cancer screening or evaluation of nodule suspicious for lung cancer will undergo an additional chest X-ray tomosynthesis scan.

Diagnostic Test: Chest X-ray Tomosynthesis

Interventions

Chest X-ray Tomosynthesis DIAGNOSTIC_TEST

An imaging device that uses X-rays projected from multiple angles to reconstruct a three-dimensional images of the chest

Also known as: CXRT

Chest X-ray Tomosynthesis Participants

Eligibility Criteria

• Age: 30 Years - 85 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients undergoing lung cancer screening CT or undergoing diagnostic chest CT for incidentally detected pulmonary nodules or lung cancer.

You may qualify if:

• undergoing lung cancer screening
• undergoing evaluation of suspicious pulmonary nodule
• newly diagnosed lung cancer

You may not qualify if:

• prior history of lung cancer treatment

Sponsors & Collaborators

• University of California, San Diego: lead
• AIxSCAN, Inc.: collaborator

Study Sites (1)

University of California San Diego

San Diego, California, 92093, United States

RECRUITING

Related Links

• AIxScan, Inc

MeSH Terms

Conditions

Lung Neoplasms

Condition Hierarchy (Ancestors)

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

Study Officials

• Albert Hsiao, MD PhD

  UC San Diego, Department of Radiology

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Alexander Cypro, MD

CONTACT

858-2462196; aidaresearch2023@gmail.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor in Residence, Department of Radiology

Study Record Dates

• First Submitted: August 27, 2024
• First Posted: August 29, 2024
• Study Start: November 2, 2023
• Primary Completion (Estimated): December 31, 2026
• Study Completion (Estimated): June 30, 2027
• Last Updated: August 29, 2024

Record last verified: 2024-08

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)