Uncertainty quantification of TMS simulations considering MRI segmentation errors.
Uncertainty quantification of TMS simulations considering MRI segmentation errors.
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DOI：
10.1088/1741-2552/ac52d1
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发表时间：
2022-02-08
影响因子：
4
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经颅磁刺激（TMS）是一种非侵入性脑刺激方法，用于研究大脑功能和进行神经精神治疗。通常用于TMS的电场（E场）剂量测定的计算方法在准确度和精度方面受到限制，因为通过将医学图像分割成组织类型而在头部模型的生成中引入了可能的几何误差。本文研究了电场预测保真度作为分割精度的函数。将医学图像分割成组织类型的误差建模为组织类型之间边界形状的几何不确定性。对于每个组织边界的实现，我们然后使用内部边界元方法来执行前向传播分析，并量化组织边界的不确定性对感应皮层电场的影响。我们的研究结果表明，在大脑中诱导的电场的预测是可忽略不计的分割错误，在头皮，头骨和白色物质，车厢的敏感性。相反，电场预测对可能的CSF分割错误高度敏感。具体而言，CSF和灰质界面上的分割误差导致脑回冠部中的更高的电场不确定性，并且CSF和白色物质界面上的分割误差导致脑沟中的更高的不确定性。此外，在一个区域的平均皮层E场的不确定性表现出较低的不确定性相对于逐点估计。当前皮质E场模拟的准确性受到CSF分割准确性的准确性的限制。其他感兴趣的量，如皮层区域上的E场的平均值，可以提供对可能的分割误差鲁棒的剂量量。
Transcranial Magnetic Stimulation (TMS) is a non-invasive brain stimulation method that is used to study brain function and conduct neuropsychiatric therapy. Computational methods that are commonly used for electric field (E-field) dosimetry of TMS are limited in accuracy and precision because of possible geometric errors introduced in the generation of head models by segmenting medical images into tissue types. This paper studies E-field prediction fidelity as a function of segmentation accuracy. The errors in the segmentation of medical images into tissue types are modeled as geometric uncertainty in the shape of the boundary between tissue types. For each tissue boundary realization, we then use an in-house boundary element method to perform a forward propagation analysis and quantify the impact of tissue boundary uncertainties on the induced cortical E-field. Our results indicate that predictions of E-field induced in the brain are negligibly sensitive to segmentation errors in scalp, skull and white matter, compartments. In contrast, E-field predictions are highly sensitive to possible CSF segmentation errors. Specifically, the segmentation errors on the CSF and gray matter interface lead to higher E-field uncertainties in the gyral crowns, and the segmentation errors on CSF and white matter interface lead to higher uncertainties in the sulci. Furthermore, the uncertainty of the average cortical E-fields over a region exhibits lower uncertainty relative to point-wise estimates. The accuracy of current cortical E-field simulations is limited by the accuracy of CSF segmentation accuracy. Other quantities of interest like the average of the E-field over a cortical region could provide a dose quantity that is robust to possible segmentation errors.