# Extending Reach, Accuracy, and Therapeutic Capabilities: A Soft Robot for Peripheral Early-Stage Lung Cancer

> **NIH NIH R01** · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · 2024 · $297,000

## Abstract

PROJECT SUMMARY
This proposal focuses on the design, development, and validation of a novel soft surgical robot to address critical
unmet needs within the world of lung cancer. Lung cancer is the leading cause of death from cancer in the
United States and worldwide with an estimated 1.8 million deaths a year, more than breast cancer, prostate
cancer, and colon cancer combined. Early diagnosis and therapy are essential to increase the survival rate of
lung cancer. Because approximately 70% of lung nodules reside in the deeper peripheral region of the lung,
adequate sampling of the tissue is challenging. Traditional manual bronchoscopes are limited in their ability to
access small bronchi because of large diameters. Robotic bronchoscopes available on the market are easier
and more intuitive to maneuver. However, they still present distal dexterity limitations and deep exploration is still
performed without visualization by using semi-flexible needles that are pushed manually by the clinician. This
affects biopsy accuracy and precision and ultimately diagnostic yield, causing delays in diagnosis and treatment
and increasing the risk for tumor growth and spread. In this proposal, we will leverage our prior pioneering work
on the design, fabrication, and preliminary validation of a miniaturized soft robotic bronchoscope for early-stage
lung cancer diagnosis and treatment. This air-powered, image-guided robot is the smallest and most flexible
and dexterous robotic bronchoscope, allowing navigation in branches deeper in the lung and visual feedback
throughout the procedure. The system features two separate working channels to facilitate, for the first time,
simultaneous (i.e., within the same bronchoscopy procedure) diagnostic and therapeutic capabilities and hasten
early-stage lung cancer treatment. We will optimize the soft robotic bronchoscope navigation and stabilization
control based on computer vision algorithms. We will merge pre-operative planning and intra-operative data and
evaluate accuracy and precision in registration. We will develop a mechanical stabilization system at the robot
tip, that will anchor to the surrounding anatomy and work in concert with software stabilization. This will enhance
robot lesion tracking abilities during breathing and other involuntary or accidental movements and counteract
tissue reaction forces during biopsy to improve surgical tasks’ accuracy and precision. We will enable robotic
actuation control for needle tool deployment and steering via multi-DOF soft robotic micro actuators at the robot
tip. Sharp bending angles and large strokes will enable access to hard-to-reach lesions without losing visualization.
We will validate the robot in-vitro and ex-vivo and compare metrics with standard bronchoscopy. We anticipate
our technology to have better navigational abilities, more accurate instrument placement, reduced procedure
times, less tissue trauma, better diagnostic yield, shortened learning curve, and an over...

## Key facts

- **NIH application ID:** 10895281
- **Project number:** 5R01EB034286-02
- **Recipient organization:** BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
- **Principal Investigator:** Sheila Russo
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $297,000
- **Award type:** 5
- **Project period:** 2023-08-01 → 2027-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10895281

## Citation

> US National Institutes of Health, RePORTER application 10895281, Extending Reach, Accuracy, and Therapeutic Capabilities: A Soft Robot for Peripheral Early-Stage Lung Cancer (5R01EB034286-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10895281. Licensed CC0.

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