# 3D-Nanoprinted Soft Robotic Microcatheters with Integrated Microfluidic Circuitry for Cerebrovascular Surgery

> **NIH NIH R01** · UNIV OF MARYLAND, COLLEGE PARK · 2022 · $701,955

## Abstract

Project Summary:
 Cerebral aneurysms are estimated to be prevalent in 3–7% of the general population—with cases increasing
by more than 5% each year—resulting in ~500,000 deaths annually. Minimally invasive neurosurgery typically
represents the best surgical option for treating unruptured aneurysms due to benefits including reduced length
of stay and complications compared to invasive surgical clipping. Endovascular neurointerventions rely on
microcatheters to traverse cerebral anatomy safely to deliver embolic devices or stents for aneurysm treatment.
In many cases, however, tortuous vasculature and geometrically complex aneurysms pose substantial
navigation challenges for neurointerventionalists due to an inability to maneuver conventional microcatheters
safely. These difficulties in navigating such cerebrovascular anatomies contribute to longer procedural times,
unsuccessful catheterization attempts, and increased risks of complications. To address the clinical need for
neurosurgical microcatheters that overcome these maneuverability-associated barriers, we propose to engineer
and evaluate 3D-nanoprinted soft robotic microcatheters with integrated microfluidic circuitry as a means to
enable on-demand, multi-directional steering and navigation control during endovascular neurointerventions.
Our overarching hypothesis is that, by leveraging and extending recent advances at the intersection of machine
learning-based design, additive nanomanufacturing, integrated microfluidic circuitry, and soft microrobotics,
novel classes of remotely steerable neurosurgical microcatheters can be realized at unprecedented scales to
surmount current maneuverability-based deficits, and ultimately, improve catheterization efficacy, safety, and
outcomes in the treatment of cerebral aneurysms. We will investigate the clinical feasibility of this hypothesis
through four specific aims. In Aim 1, we will create machine learning-based design techniques for predicting and
informing the operational performance of the soft robotic microcatheter. In Aim 2, we will examine the manu-
facturing efficacy for 3D nanoprinting multi-actuator tips and integrated microfluidic circuits both independently
and as fully unified soft robotic microcatheters capable of on-demand, multi-directional deformations with minimal
infrastructure and external control scheme-associated requirements. In Aim 3, we will develop a handheld
controller for the neurointerventionalist and compare the maneuverability efficacy of the soft robotic micro-
catheter to that of standard clinical microcatheters using in vitro models of cerebrovascular anatomy based on
patient-specific clinical 3D angiography images. In Aim 4, we will assess the feasibility and safety of the soft
robotic microcatheter (i.e., with respect to standard clinical microcatheters) by performing minimally invasive
endovascular neurointerventions in animal models (canine, n=8). If successful, the proposed 3D-nanoprinted
soft robotic microcathe...

## Key facts

- **NIH application ID:** 10502710
- **Project number:** 1R01EB033354-01
- **Recipient organization:** UNIV OF MARYLAND, COLLEGE PARK
- **Principal Investigator:** Ryan Daniel Sochol
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $701,955
- **Award type:** 1
- **Project period:** 2022-08-01 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10502710

## Citation

> US National Institutes of Health, RePORTER application 10502710, 3D-Nanoprinted Soft Robotic Microcatheters with Integrated Microfluidic Circuitry for Cerebrovascular Surgery (1R01EB033354-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10502710. Licensed CC0.

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