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Personalized predictions and non-invasive imaging of human brain temperature

Medicine and Health

Personalized predictions and non-invasive imaging of human brain temperature

D. Sung, P. A. Kottke, et al.

This groundbreaking research conducted by Dongsuk Sung and colleagues unveils a biophysical model that predicts personalized brain temperature distributions using MRI data, laying the foundation for enhanced recovery after brain injuries. The study successfully validates this model against experimental measurements, promising significant implications for clinical applications in brain health.

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Playback language: English
Abstract
Brain temperature is a crucial parameter for brain health and recovery after injury. This study develops a biophysical model using MRI data to predict personalized brain temperature distributions. The model, based on energy and mass conservation, is validated against experimental temperature measurements using whole-brain magnetic resonance-based thermometry. Results show strong agreement between model predictions and experimental data, highlighting the potential for personalized brain temperature predictions in clinical settings.
Publisher
Communications Physics
Published On
Apr 15, 2021
Authors
Dongsuk Sung, Peter A. Kottke, Benjamin B. Risk, Jason W. Allen, Fadi Nahab, Andrei G. Fedorov, Candace C. Fleischer
Tags
brain temperature
MRI data
biophysical model
personalized predictions
clinical settings

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