Clinical trial NCT06577883: Next Generation Chest X-Ray Tomosynthesis for Screening of Lung Cancer
Official title: Chest X-ray Tomosynthesis for Detection of Lung Cancer and Lung Disease
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Lung Cancer
Lead sponsor: University of California, San Diego
Sponsor class: OTHER
Collaborators: name: AIxSCAN, Inc.
First posted: 2024-08-29
Enrollment: 1000
Sex: ALL
Minimum age (years): 30
Maximum age (years): 85
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: CROSS_SECTIONAL
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.

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.

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.

Eligibility 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

Primary outcomes:
measure: Chest X-ray tomosynthesis detection of lung cancer
timeFrame: through 12/31/2026
Secondary outcomes:
measure: Chest X-ray tomosynthesis detection of suspicious nodules
timeFrame: through 12/31/2026
Other outcomes:
Locations:
city: San Diego
country: United States
facility: University of California San Diego
state: California
Study officials:
affiliation: UC San Diego, Department of Radiology
name: Albert Hsiao, MD PhD
role: PRINCIPAL_INVESTIGATOR
References: