Recent technological advances have enabled low-dose spiral CT to become an effective tool for lung cancer screening. The majority of pulmonary nodules detected on CT, however, are small and difficult to diagnose. While CT-guided transthoracic needle biopsy (CT-TTNB) has high diagnostic accuracy (70% to 90% depending on nodule size), the risk of complications such as pneumothorax and bleeding is high. Diagnostic confirmation by transbronchial lung biopsy using virtual bronchoscopy or electromagnetic navigation and endoscopic ultrasound is a safer alternative. However, the diagnostic yield is generally 10% to 20% lower than CT-TTNB. Current endoscopic ultrasound is limited by the size of the imaging probe, spatial resolution, and its inability to display blood vessels in the lesion. Furthermore, non-solid lung nodules are not well visualized by ultrasound. Owing to its large size, the ultrasound probe cannot be inserted through a biopsy needle or catheter. In lieu of this, a guide sheath is used to extend the working channel to allow insertion of biopsy forceps after removing the ultrasound probe to take a biopsy without-real time confirmation of the biopsy site. Therefore, there is an unmet clinical need for safe and accurate biopsy tools that can sample small pulmonary nodules under real-time image guidance. The goal of this project is to build and evaluate image-guided biopsy tools to address this knowledge gap.
In Aim 1, we will develop a small optical coherence tomography (OCT) catheter that combines Doppler OCT with autofluorescence sensitive imaging. We will integrate these AF/OCT imaging catheters with biopsy tools that will enable localization and forward sample collection from lesions perpendicular to the airway as well as with side-collecting transbronchial biopsy tools in the wall of a bronchus parallel to the biopsy probe.
Aim 2 is to evaluate, in a swine model, the feasibility and ability of the tools developed in the preceding aim to collect tissue samples with sufficient yield to enable standard and molecular pathology diagnosis and prediction of the biological behavior of malignant lesions.

Public Health Relevance

Lung cancer is the most common cause of cancer death worldwide. More than 1.3 million people die annually and the 5-year survival rates have improved only marginally in the last three decades. While population-based screening programs based on low-dose computed tomography (CT) are likely to reduce the number of deaths due to lung cancer, a significant challenge that remains is how to safely and accurately diagnose small spots (nodules) found on a screening CT. Our project is to develop small biopsy probes with integrated real-time image guidance. The biopsy probes will be inserted into the biopsy channel of a standard bronchoscope and navigated to the lung spot using virtual bronchoscopy similar to a GPS guidance system. The probe will use optical coherence tomography (OCT) to confirm the exact location of the spot to be sampled. The principle of OCT is similar to ultrasound. Instead of sound waves, near-infrared light is used to produce a high definition image similar to looking down a microscope. Our OCT probe will be much smaller than an ultrasound probe. It can detect blood vessels using the Doppler effect and analyze the chemical contents of the nodule using tissue autofluorescence imaging. The procedure will be done under local anesthesia to the throat and conscious sedation. These innovative imaging-biopsy probes will be the first of its kind to allow the accurate biopsy of small lung nodules while minimizing complications such as bleeding and lung collapse. It will advance the bronchoscopic diagnosis of small lung lesions.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
Project #
3R43CA203033-01S1
Application #
9411492
Study Section
Special Emphasis Panel (ZRG1-SBIB-T (10)B)
Program Officer
Evans, Gregory
Project Start
2017-02-05
Project End
2017-04-30
Budget Start
2017-02-05
Budget End
2017-04-30
Support Year
1
Fiscal Year
2017
Total Cost
$50,000
Indirect Cost
Name
Lx Medical Corporation
Department
Type
Domestic for-Profits
DUNS #
968636576
City
Westwood
State
MA
Country
United States
Zip Code
02090