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Abstract #0183

Subject-specific head gradient PNS prediction using only demographics and head dimensions

Koray Ertan1, Samantha J Ma2, Erica Walker3, Alexander J S Beckett3, Nicolas Boulant4,5, David A Feinberg3,6, and Brian Keith Rutt1
1Radiology, Stanford University, Stanford, CA, United States, 2Siemens Medical Solutions, Malvern, PA, United States, 3UC Berkeley, Berkeley, CA, United States, 4University of Paris-Saclay, Gif sur Yvette, France, 5CEA Paris, Gif sur Yvette, France, 6Advanced MRI Technologies, Sebastopol, CA, United States

Synopsis

Keywords: Gradients, Gradients, Peripheral Nerve Stimulation / Safety / Bioeffects & Magnetic Fields

Motivation: Given the ~3-fold population variability in PNS thresholds, rapid and accurate prediction of PNS thresholds for individual subjects would be valuable.

Goal(s): To test the hypothesis that individual PNS thresholds can be predicted using only demographics and head dimensions.

Approach: PNS thresholds and localizer images were measured for 30 participants in a head gradient. Demographic (age, sex, BMI) and anatomical (head dimensions and offset from isocenter) variables were used as explanatory variables in multivariate models to predict subject-specific PNS thresholds for each of the three Impulse gradient axes.

Results: Subject-specific models succeeded in explaining a majority of the population variance in PNS thresholds.

Impact: Multivariate linear models using only select demographics and head dimensions as explanatory variables can estimate subject-specific PNS parameters with reasonable accuracy, explaining ~50-80% of the population variance and permitting the tailoring and tightening of on-scanner PNS limits to the individual.

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Keywords