Aalto University, Department of Mathematics and Systems Analysis, PO Box 11100, FI-00076 AALTO, Finland.
Northeastern University, Department of Bioengineering, 360 Huntington Ave, Boston, MA 02115, United States of America.
Phys Med Biol. 2023 Jul 3;68(13):135019. doi: 10.1088/1361-6560/acd48c.
Diffuse optical tomography (DOT) provides a relatively convenient method for imaging haemodynamic changes related to neuronal activity on the cerebral cortex. Due to practical challenges in obtaining anatomical images of neonates, an anatomical framework is often created from an age-appropriate atlas model, which is individualized to the subject based on measurements of the head geometry. This work studies the approximation error arising from using an atlas instead of the neonate's own anatomical model.We consider numerical simulations of frequency-domain (FD) DOT using two approaches, Monte Carlo simulations and diffusion approximation via finite element method, and observe the variation in (1) the logarithm of amplitude and phase shift measurements, and (2) the corresponding inner head sensitivities (Jacobians), due to varying segmented anatomy. Varying segmentations are sampled by registering 165 atlas models from a neonatal database to the head geometry of one individual selected as the reference model. Prior to the registration, we refine the segmentation of the cerebrospinal fluid (CSF) by separating the CSF into two physiologically plausible layers.In absolute measurements, a considerable change in the grey matter or extracerebral tissue absorption coefficient was found detectable over the anatomical variation. In difference measurements, a small local 10%-increase in brain absorption was clearly detectable in the simulated measurements over the approximation error in the Jacobians, despite the wide range of brain maturation among the registered models.Individual-level atlas models could potentially be selected within several weeks in gestational age in DOT difference imaging, if an exactly age-appropriate atlas is not available. The approximation error method could potentially be implemented to improve the accuracy of atlas-based imaging. The presented CSF segmentation algorithm could be useful also in other model-based imaging modalities. The computation of FD Jacobians is now available in the widely-used Monte Carlo eXtreme software.
漫射光学断层成像(DOT)为在大脑皮层上对与神经元活动相关的血液动力学变化进行成像提供了一种相对便捷的方法。由于在获取新生儿解剖图像方面存在实际挑战,因此通常根据头部几何形状的测量值,从适合年龄的图谱模型创建解剖结构框架,并将其个性化到受试者。本工作研究了使用图谱代替新生儿自身解剖模型所产生的近似误差。我们考虑了两种方法的频域(FD)DOT 数值模拟,即蒙特卡罗模拟和通过有限元方法的扩散逼近,并观察了(1)幅度和相位偏移测量的对数以及(2)相应的头部内灵敏度(雅可比矩阵)的变化,这是由于分段解剖结构的变化。通过将来自新生儿数据库的 165 个图谱模型注册到所选个体的头部几何形状作为参考模型,可以对分段解剖结构进行采样。在注册之前,我们通过将脑脊液(CSF)分为两个生理上合理的层来细化 CSF 的分割。在绝对测量中,发现在解剖变异范围内,灰质或脑外组织的吸收系数的相当大变化是可检测的。在差分测量中,尽管在注册模型中脑成熟度范围很广,但在雅可比矩阵的近似误差上,模拟测量中大脑吸收的局部 10%增加可以明显检测到。如果没有完全适合年龄的图谱,在 DOT 差分成像中,可以在几周的时间内选择个体水平的图谱模型。近似误差方法有可能被实施以提高基于图谱的成像的准确性。所提出的 CSF 分割算法在其他基于模型的成像方式中也可能有用。FD 雅可比矩阵的计算现在可在广泛使用的蒙特卡罗极限软件中使用。