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| Format: | Preprint |
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2025
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| Online Access: | https://arxiv.org/abs/2506.12228 |
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| _version_ | 1866909649002823680 |
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| author | Zou, Jiaren Cao, Yue |
| author_facet | Zou, Jiaren Cao, Yue |
| contents | 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 results by examining the model's degeneracy and fitting landscape. In vivo fitting results on patients with HNCs were analyzed and were interpreted using the numerical results. We observed that free diffusivity estimates were accurate and precise over a wide range of microstructural parameters, whereas the accuracy and precision of surface-to-volume ratio and membrane permeability depended on the values of the parameters. In addition, a maximum effective diffusion time of 200 ms provided the lowest bias and variance in membrane permeability estimations. By fitting to the short-time limit expression, we observed that the variance of parameter estimation was reduced, and that a more accurate and precise estimation of membrane permeability was achieved. In vivo fitting results were consistent with the numerical findings. In conclusion, this work provides a comprehensive analysis of RWBM fitting in clinical settings and has the potential to guide further optimizations of data acquisition and model fitting methods. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_12228 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Accuracy and Precision of Random Walk with Barrier Model Fitting: Simulations and Applications in Head and Neck Cancers Zou, Jiaren Cao, Yue Medical Physics 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 results by examining the model's degeneracy and fitting landscape. In vivo fitting results on patients with HNCs were analyzed and were interpreted using the numerical results. We observed that free diffusivity estimates were accurate and precise over a wide range of microstructural parameters, whereas the accuracy and precision of surface-to-volume ratio and membrane permeability depended on the values of the parameters. In addition, a maximum effective diffusion time of 200 ms provided the lowest bias and variance in membrane permeability estimations. By fitting to the short-time limit expression, we observed that the variance of parameter estimation was reduced, and that a more accurate and precise estimation of membrane permeability was achieved. In vivo fitting results were consistent with the numerical findings. In conclusion, this work provides a comprehensive analysis of RWBM fitting in clinical settings and has the potential to guide further optimizations of data acquisition and model fitting methods. |
| title | Accuracy and Precision of Random Walk with Barrier Model Fitting: Simulations and Applications in Head and Neck Cancers |
| topic | Medical Physics |
| url | https://arxiv.org/abs/2506.12228 |