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Trial Title:
Next Generation Chest X-Ray Tomosynthesis for Screening of Lung Cancer
NCT ID:
NCT06577883
Condition:
Lung Cancer
Conditions: Official terms:
Lung Neoplasms
Study type:
Observational
Overall status:
Recruiting
Study design:
Time perspective:
Cross-Sectional
Intervention:
Intervention type:
Diagnostic Test
Intervention name:
Chest X-ray Tomosynthesis
Description:
An imaging device that uses X-rays projected from multiple angles to reconstruct a
three-dimensional images of the chest
Arm group label:
Chest X-ray Tomosynthesis Participants
Other name:
CXRT
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.
Detailed description:
Lung cancer remains the most common cause of cancer death in the United States for which
low-dose CT has proven benefit for early detection and survival from lung cancer.
However, adoption remains low. Furthermore, >95% of nodules detected on low-dose CT,
especially those smaller than 6 mm, do not represent cancer. We have partnered to develop
a novel chest x-ray tomosynthesis (CXRT) device with the hypothesis that this device
might be an alternative to CT for detection of lung cancer. We seek to recruit a cohort
of patients to undergo CXRT, composed of patients concurrently undergoing lung cancer
screening CT and diagnostic CT for new lung cancer. We will determine the effectiveness
of CXRT for detecting lung cancer in this population, evaluating its sensitivity and
specificity for detecting cancer and lung nodules at multiple size thresholds in a
multireader study. We will additionally develop artificial intelligence algorithms and
evaluate their efficacy to further enhance cancer detection.
Criteria for eligibility:
Study pop:
Patients undergoing lung cancer screening CT or undergoing diagnostic chest CT for
incidentally detected pulmonary nodules or lung cancer.
Sampling method:
Non-Probability Sample
Criteria:
Inclusion Criteria:
- undergoing lung cancer screening
- undergoing evaluation of suspicious pulmonary nodule
- newly diagnosed lung cancer
Exclusion Criteria:
- prior history of lung cancer treatment
Gender:
All
Minimum age:
30 Years
Maximum age:
85 Years
Healthy volunteers:
Accepts Healthy Volunteers
Locations:
Facility:
Name:
University of California San Diego
Address:
City:
San Diego
Zip:
92093
Country:
United States
Status:
Recruiting
Contact:
Last name:
Alexander Cypro, MD
Phone:
858-246-2196
Email:
aidaresearch2023@gmail.com
Start date:
November 2, 2023
Completion date:
June 30, 2027
Lead sponsor:
Agency:
University of California, San Diego
Agency class:
Other
Collaborator:
Agency:
AIxSCAN, Inc.
Agency class:
Other
Source:
University of California, San Diego
Record processing date:
ClinicalTrials.gov processed this data on November 12, 2024
Source: ClinicalTrials.gov page:
https://clinicaltrials.gov/ct2/show/NCT06577883
https://www.aixscan.com
