# Advancing Neurosurgical Neuronavigation Using Resting State MRI and Machine Learning

> **NIH NIH R01** · WASHINGTON UNIVERSITY · 2024 · $152,018

## Abstract

PROJECT SUMMARY
Our team has developed a machine learning (ML) algorithm that provides highly accurate prognostic
information neurosurgeons can use to advise brain tumor removal. While this algorithm holds great promise
with regard to surgical decision-making and patient outcomes, it also raises significant ethical issues and risk
factors. Proactively identifying relevant ethical issues and exploring possible solutions can improve the
effectiveness, benefits, and uptake of this technology, while also mitigating potential harm to patients and
suboptimal surgical decision-making.
We propose a 12-month bioethics research supplement that will collect original data on stakeholder
perspectives about research and clinical practice involving this novel ML algorithm. Data can inform ethical and
responsible implementation of this technology and will begin to lay the groundwork for developing ethical
solutions and guidance to maximize patient wellbeing and support surgeon decision-making as they balance
patient and caregiver needs, their professional judgment, and ML-generated surgical insights. The research
team has experience in brain mapping, neuroethics, stakeholder engagement, and the responsible conduct of
research and clinical practice. We propose the following aims:
Aim 1. Explore the perspectives of patients (N = 15) with malignant brain tumors about perceived benefits,
drawbacks, concerns, and risk factors in utilizing a ML algorithm for predicting prognosis and surgical decisions
for severe brain tumors.
Aim 2. Explore the perspectives of caregivers of patients (N = 15) with malignant brain tumors about perceived
benefits, drawbacks, concerns, and risk factors in utilizing an ML algorithm for predicting prognosis and
surgical decisions for severe brain tumors.
Aim 3. Explore the perspectives of neurosurgeons (N = 15) who treat patients with malignant brain tumors
about perceived benefits, drawbacks, concerns, and risk factors in utilizing an ML algorithm for predicting
prognosis and surgical decisions for severe brain tumors.

## Key facts

- **NIH application ID:** 11063640
- **Project number:** 3R01CA203861-08S1
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Eric CLAUDE Leuthardt
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $152,018
- **Award type:** 3
- **Project period:** 2017-01-17 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11063640

## Citation

> US National Institutes of Health, RePORTER application 11063640, Advancing Neurosurgical Neuronavigation Using Resting State MRI and Machine Learning (3R01CA203861-08S1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/11063640. Licensed CC0.

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