(ISMRM 2024) Impact of Rician Bias on biophysical modeling
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Abstract #3483

Impact of Rician Bias on biophysical modeling

Guillem París1,2, Tomasz Pieciak1, Derek K Jones3, Santiago Aja-Fernández1, Antonio Tristán-Vega1, and Jelle Veraart2
1Laboratorio de Procesado de Señal (LPI), ETSI Telecomunicación, Universidad de Valladolid, Valladolid, Spain, 2Center for Biomedical Imaging (CBI), New York University Grossman School of Medicine, New York City, NY, United States, 3Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom

Synopsis

Keywords: Diffusion Modeling, Diffusion/other diffusion imaging techniques, Rician Bias, Noise, SMI

Motivation: Rician noise degrades the accuracy of biophysical modeling. Understanding this bias and defining a robust strategy for its mitigation, is important for reproducible and quantitative use of diffusion MRI.

Goal(s): To study the impact of noise biases on biophysical models and evaluate methods for more accurate estimation of diffusion metrics.

Approach: We compare various parameter estimators (via simulations and MRI data) and evaluate their impact on the accuracy of biophysical model parameters.

Results: The use of rotational-invariant spherical harmonics in biophysical modeling is a source of noise bias that can be mitigated by fitting such models directly to the diffusion-weighted signals.

Impact: With the advent of higher b-values, Rician bias pose a threat to the reproducibility in diffusion MRI studies. With this work we take a deep look at such bias and propose alternatives to avoid such counfounders from the final estimates.

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Keywords

biasdiffusionprotocolestimationnoisestrategies