A Multi-robot System for Semi-automated Image-guided Vertebral Augmentation
Project Number1R01EB036341-01
Former Number1R01AR083388-01
Contact PI/Project LeaderUNBERATH, MATHIAS
Awardee OrganizationJOHNS HOPKINS UNIVERSITY
Description
Abstract Text
Project Summary
Vertebral compression fractures (VCFs) are effectively treated with vertebral augmentation (VA), which rapidly
reduces pain and restores function. The most significant opportunities to advance VA as an efficacious treatment
option for (cancer) patients in acute pain are to 1) considerably reduce radiation dose to patient and staff; 2)
improve the safety of VA; and 3) increase its efficacy by establishing superior but more complex techniques
using curved instruments. Introducing robotic systems for VA will address these three significant challenges.
However, existing robotic solutions are bulky, expensive to acquire and maintain, and disrupt workflows. These
drawbacks make current systems inadequate for VA, a quick procedure that is often performed in outpatient
settings. To capitalize on the benefits of robotics for VA – reduced radiation dose and complication rates, and increased
efficacy – novel, alternative robotic platforms and corresponding algorithms are needed that seamlessly integrate with
the VA workflow, enable robot planning from interventional X-ray images, and are more affordable.
Our long-term goal is to advance surgical robotics technology for X-ray-guided VA by developing 1) a
novel class of tool-mounted robots, 2) a suite of powerful image-based algorithms for automated intra-operative
surgical planning, verification, and closed loop control, and 3) mixed reality interfaces for remote actuation
and assurance. Because our robotic solution augments the conventional VA workflow and its tools, and is
of considerably lower cost than existing robotic solutions, our developments will contribute to unlocking the
known benefits of surgical robotics for the surgical treatment of the tens of thousands of VAs that are performed
across a wide variety of providers every year in the US. Our specific aims are: 1) Develop and test a cannula-
mounted piezo robot for image-guided VA: We will create a cannula-mounted piezo robot, supported by a passive
positioning arm, that meets the clinical requirements of VA. The robot will combine high accuracy and force
with a low-profile design to not interfere with X-ray image-guidance. 2) Develop imaging and planning algorithms,
and user feedback to guide delivery: We will develop algorithms for a camera-augmented C-arm X-ray system
to acquire and interpret X-ray and RGB-D images to achieve automated planning and guidance. Via mixed
reality, they will guide providers through the semi-automated workflow to ensure safe and accurate execution.
3) Demonstrate integrated system performance ex vivo: We will confirm the functional performance, reliability, and
overall system accuracy of our robotic approach through a series of cadaver studies.
Our multi-disciplinary team will be the first to investigate tool-mounted robots for hard-tissue surgery,
paving the way for a new family of robots that are compact and exert sufficient force for bone surgery. Combin-
ing innovative robotic actuators with powerful algorithms for automated planning and remote-actuation will
provide alternative robotic solutions that will contribute to a more widespread adoption of robotic surgery.
Public Health Relevance Statement
Project Narrative
Vertebral compression fractures, the most common fragility fractures secondary to osteoporosis, are effectively
treated with vertebral augmentation, which rapidly reduces pain and restores function. The goal of this project
is to advance surgical robotics technology for vertebral augmentation to reduce radiation dose, increase safety,
and improve efficacy. This will be accomplished by developing a novel class of tool-mounted robots and a
suite of powerful image-based algorithms for automated intra-operative planning, verification, and control,
integrated in mixed reality for remote actuation and assurance.
National Institute of Biomedical Imaging and Bioengineering
CFDA Code
286
DUNS Number
001910777
UEI
FTMTDMBR29C7
Project Start Date
10-May-2024
Project End Date
29-February-2028
Budget Start Date
10-May-2024
Budget End Date
28-February-2025
Project Funding Information for 2024
Total Funding
$546,252
Direct Costs
$354,348
Indirect Costs
$191,904
Year
Funding IC
FY Total Cost by IC
2024
National Institute of Biomedical Imaging and Bioengineering
$546,252
Year
Funding IC
FY Total Cost by IC
Sub Projects
No Sub Projects information available for 1R01EB036341-01
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Outcomes
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Clinical Studies
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