# Multimodal Image-Guided Intervention System for Lung-Cancer Diagnosis and Staging

> **NIH NIH R01** · PENNSYLVANIA STATE UNIVERSITY, THE · 2021 · $403,859

## Abstract

Project Summary/Abstract
 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.

## Key facts

- **NIH application ID:** 10069303
- **Project number:** 5R01CA151433-09
- **Recipient organization:** PENNSYLVANIA STATE UNIVERSITY, THE
- **Principal Investigator:** William Evan Higgins
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $403,859
- **Award type:** 5
- **Project period:** 2010-08-24 → 2022-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10069303

## Citation

> US National Institutes of Health, RePORTER application 10069303, Multimodal Image-Guided Intervention System for Lung-Cancer Diagnosis and Staging (5R01CA151433-09). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10069303. Licensed CC0.

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