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Challenges for biophysical modeling of microstructure.
Journal of Neuroscience Methods ( IF 2.7 ) Pub Date : 2020-07-18 , DOI: 10.1016/j.jneumeth.2020.108861
Ileana O Jelescu 1 , Marco Palombo 2 , Francesca Bagnato 3 , Kurt G Schilling 4
Affiliation  

The biophysical modeling efforts in diffusion MRI have grown considerably over the past 25 years. In this review, we dwell on the various challenges along the journey of bringing a biophysical model from initial design to clinical implementation, identifying both hurdles that have been already overcome and outstanding issues. First, we describe the critical initial task of selecting which features of tissue microstructure can be estimated using a model and which acquisition protocol needs to be implemented to make the estimation possible. The model performance should necessarily be tested in realistic numerical simulations and in experimental data – adapting the fitting strategy accordingly, and parameter estimates should be validated against complementary techniques, when/if available. Secondly, the model performance and validity should be explored in pathological conditions, and, if appropriate, dedicated models for pathology should be developed. We build on examples from tumors, ischemia and demyelinating diseases. We then discuss the challenges associated with clinical translation and added value. Finally, we single out four major unresolved challenges that are related to: the availability of a microstructural ground truth, the validation of model parameters which cannot be accessed with complementary techniques, the development of a generalized standard model for any brain region and pathology, and the seamless communication between different parties involved in the development and application of biophysical models of diffusion.



中文翻译:

微观结构生物物理建模的挑战。

在过去的 25 年中,扩散 MRI 中的生物物理建模工作有了长足的发展。在这篇综述中,我们详细讨论了将生物物理模型从初始设计引入临床实施的过程中遇到的各种挑战,确定了已经克服的障碍和悬而未决的问题。首先,我们描述了关键的初始任务,即选择可以使用模型估计组织微观结构的哪些特征,以及需要实施哪种采集协议才能使估计成为可能。模型性能必须在现实的数值模拟和实验数据中进行测试——相应地调整拟合策略,并且在/如果可用时,应根据互补技术验证参数估计。第二,应在病理条件下探索模型的性能和有效性,并且在适当的情况下,应开发专门的病理模型。我们以肿瘤、局部缺血和脱髓鞘疾病的例子为基础。然后我们讨论与临床翻译和附加值相关的挑战。最后,我们挑出了四大未解决的挑战,这些挑战与:微观结构基本事实的可用性、无法通过补充技术访问的模型参数的验证、针对任何大脑区域和病理学的通用标准模型的开发,以及参与扩散生物物理模型开发和应用的各方之间的无缝沟通。我们以肿瘤、局部缺血和脱髓鞘疾病的例子为基础。然后我们讨论与临床翻译和附加值相关的挑战。最后,我们挑出了四大未解决的挑战,这些挑战与:微观结构基本事实的可用性、无法通过补充技术访问的模型参数的验证、针对任何大脑区域和病理学的通用标准模型的开发,以及参与扩散生物物理模型开发和应用的各方之间的无缝沟通。我们以肿瘤、局部缺血和脱髓鞘疾病的例子为基础。然后我们讨论与临床翻译和附加值相关的挑战。最后,我们挑出了四大未解决的挑战,这些挑战与:微观结构基本事实的可用性、无法通过补充技术访问的模型参数的验证、针对任何大脑区域和病理学的通用标准模型的开发,以及参与扩散生物物理模型开发和应用的各方之间的无缝沟通。

更新日期:2020-07-29
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