Accuracy and Precision of Random Walk with Barrier Model Fitting: Simulations and Applications in Head and Neck Cancers
Jiaren Zou, Yue Cao

TL;DR
This study evaluates the accuracy and precision of Random Walk with Barrier Model fitting in diffusion MRI for head and neck cancers, providing insights to optimize data acquisition and improve biophysical parameter estimation.
Contribution
It offers a comprehensive analysis of RWBM fitting performance, highlighting how data acquisition parameters affect estimation accuracy and precision in clinical applications.
Findings
Free diffusivity estimates are accurate across parameters.
Optimal diffusion time is around 200 ms for membrane permeability.
Short-time limit fitting reduces variance and improves accuracy.
Abstract
Promising results have been reported in quantifying microstructural parameters (free diffusivity, cell size, and membrane permeability) in head and neck cancers (HNCs) using time-dependent diffusion MRI fitted to Random Walk with Barrier Model (RWBM). However, model fitting remains challenging due to limited number of measurements, low signal-to-noise ratio and complex nonlinear biophysical model. In this work, we comprehensively investigated and elucidated the dependence of RWBM fitting performance on tissue property, data acquisition and processing, and provided insights on improving data acquisition and model fitting. We numerically evaluated the accuracy and precision of RWBM fitting using non-linear least squares as a function of model parameters, noise levels, and maximum effective diffusion times over a wide range of microstructural parameter values. We then elucidated these…
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Taxonomy
TopicsHead and Neck Cancer Studies · Gene expression and cancer classification · Brain Tumor Detection and Classification
