Lung cancer is the leading cause of cancer death, accounting for over 1.6 million deaths worldwide. For initial detection of suspect peripheral tumors and central-chest lymph nodes, CT and PET imaging are used. For follow-on cancer diagnosis and staging, minimally invasive bronchoscopy and endobronchial ultrasound (EBUS) are used. A major paradigm shift, spurred by the ongoing roll-out of lung-cancer screening for early detection, is ushering in a new era focused on early-stage treatable disease. It also brings to light the major stumbling block posed by the lack of accurate, comprehensive tools for follow- on diagnosis and staging. The goal of this renewal project is to construct a multimodal image-guided bronchoscopy system for lung-cancer diagnosis and staging. As a step toward addressing this critical need, lung-cancer diagnosis has also seen a recent paradigm shift in that image-guided navigation systems have solved the task of bronchoscopic navigation. Navigation, however, is only part of the task. Upon reaching a tumor or lymph node, the physician must now perform a biopsy. Unfortunately, physician skill in using EBUS varies greatly, especially for physicians not at expert centers, resulting in poor biopsy yields. On a related note, comprehensive staging requires traversing many widely spaced nodal stations, a task rarely done because of the skill it demands. Thus, existing guidance systems suffer from two limitations: 1) they do not guide EBUS and the task of biopsy targeting; 2) they lack an efficient, systematic protocol for guiding comprehensive nodal staging, needed for reaching conclusive staging decisions. To appreciate how critical these limitations are, two national multi-center trials by the AQuIRE consortium studying state-of-the-art bronchoscopy tools for lung-cancer diagnosis and staging found a poor 47% diagnostic yield for peripheral tumor diagnosis and a 50% yield for central-chest nodal staging--- i.e., too many tumor biopsies were missed, resulting in too many uncertain diagnoses, and too few lymph- node stations were biopsied, resulting in too many uncertain staging decisions. Our objective now in this renewal is to create a new image-guided bronchoscopy/EBUS system that overcomes current limitations. To this end, the project has the following Specific Aims:
Aim 1 : Prototype an image-guided bronchoscopy system for lung-cancer disease diagnosis and staging.
Aim 2 : Perform animal (with PennVet), phantom, and human studies to optimize the system.
Aim 3 : Conduct prospective human studies to compare the optimized system to state-of-the-art practice. The final system is expected to enable accurate diagnosis/staging decisions in a single procedure, have fewer patient complications, and be easy to use independent of physician skill. In this way, inconclusive bronchoscopies decrease, ultimately leading to more timely patient treatment.

Public Health Relevance

Lung cancer is the leading cause of cancer death worldwide. A major stumbling block in the effort against lung cancer is the lack of accurate, comprehensive tools for disease diagnosis and staging. This project seeks to create a multimodal image-guided bronchoscopy system for more effective lung-cancer diagnosis and staging.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
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Biomedical Imaging Technology Study Section (BMIT)
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Tandon, Pushpa
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Pennsylvania State University
Engineering (All Types)
Biomed Engr/Col Engr/Engr Sta
University Park
United States
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