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Abstract #3402

Predicting Quantitative Myelin Images from Clinical Scans and DTI using Linear and Neural Network Models

Kayla Bohlke1, Francesca Bagnato2, Ashley Stokes1, and Richard Dortch1
1Barrow Neurological Institute, Phoenix, AZ, United States, 2Vanderbilt University Medical Center, Nashville, TN, United States

Synopsis

Keywords: Diagnosis/Prediction, Magnetization transfer, Quantitative myelin imaging

Motivation: Quantitative myelin imaging methods are usually not included in clinical MRI scans for persons with multiple sclerosis.

Goal(s): Predict macromolecular pool-size-ratio maps from standard clinical scans.

Approach: Compare PSR map prediction results from linear model and neural network model.

Results: Most of the relationship between clinical scans plus DTI and PSR maps is captured by a simple linear model and the more complex nonlinear model offers minimal improvements.

Impact: Leveraging typical clinical scans to predict PSR maps using a simple linear model can improve diagnostic capabilities for multiple.

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Keywords