Advancing Neurosurgical Neuronavigation Using Resting State MRI and Machine Learning

NIH RePORTER · NIH · R01 · $152,018 · view on reporter.nih.gov ↗

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
WASHINGTON UNIVERSITY
Principal Investigator
Eric CLAUDE Leuthardt
Activity code
R01
Funding institute
NIH
Fiscal year
2024
Award amount
$152,018
Award type
3
Project period
2017-01-17 → 2027-06-30