Cancer, Lung, Lung Diseases
Conditions
Brief summary
This study investigates if a new imaging device can detect different types of lung tissue using spatial frequency domain imaging (SFDI). Specifically, this study aims to detect lung nodules within normal lung tissue and determine if lung nodules are cancerous. Patients who have confirmed or suspected lung nodules and who are undergoing resection of those nodules will be recruited for the study. Study participants will undergo standard of care lung nodule resection in the operating room, and the resected specimen will be imaged using the SFDI device immediately after removal from the surgical field. The data captured from the SFDI images will then be compared to the pathology findings to identify optical properties of normal and cancerous lung tissue. Because the intervention is conducted on resected biospecimens, this study yields minimal risk to participants.
Interventions
Resected lung tissue will be removed from the surgical field and labeled with sutures per standard of care. The specimen will then be immediately analyzed using two SFDI devices in the operating room using sterile technique. Each specimen will be recorded up to three times to ensure at least one high fidelity recording is captured. The SFDI data will be analyzed and compared to the official pathology report from the electronic medical record.
Sponsors
University of California, Irvine
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Greater than or equal to 18 years old * Suspected or confirmed lung nodule on diagnostic imaging * Undergoing lung resection using an open, endoscopic, or robotic approach * Standard of care orders placed for a pathology assessment of resected lung tissue * Adults undergoing lung resection for a lung mass
Exclusion criteria
* \<18 years old * Pregnant females and incarcerated individuals * No standard of care orders to obtain a pathology assessment * RUSH pathology order for resected lung tissue * Any condition where the principal investigator determines to impact patient safety or quality of care
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Markers of native lung parenchyma | May 7, 2023 to December 31, 2026 | Use SFDI to identify markers of lung nodule vs native lung parenchyma |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Cancer identification | May 7, 2023 to December 31, 2026 | Distinguish cancer vs non-cancer in lung nodules with SFDI |
Countries
United States
Outcome results
None listed