Zhang Junhao, Treyer Valerie, Sun Junfeng, Zhang Chencheng, Gietl Anton, Hock Christoph, Razansky Daniel, Nitsch Roger M, Ni Ruiqing
Institute for Regenerative Medicine, University of Zurich, 8952 Zurich, Switzerland.
Institute for Biomedical Engineering, ETH Zurich & University of Zurich, 8093 Zurich, Switzerland.
bioRxiv. 2023 Jan 25:2023.01.19.524484. doi: 10.1101/2023.01.19.524484.
Personalized neurostimulation has been a potential treatment for many brain diseases, which requires insights into brain/skull geometry. Here, we developed an open source efficient pipeline BrainCalculator for automatically computing the skull thickness map, scalp-to-cortex distance (SCD), and brain volume based on T -weighted magnetic resonance imaging (MRI) data. We examined the influence of age and sex cross-sectionally in 407 cognitively normal older adults (71.9±8.0 years, 60.2% female) from the ADNI. We demonstrated the compatibility of our pipeline with commonly used preprocessing packages and found that BrainSuite Skullfinder was better suited for such automatic analysis compared to FSL Brain Extraction Tool 2 and SPM12- based unified segmentation using ground truth. We found that the sphenoid bone and temporal bone were thinnest among the skull regions in both females and males. There was no increase in regional minimum skull thickness with age except in the female sphenoid bone. No sex difference in minimum skull thickness or SCD was observed. Positive correlations between age and SCD were observed, faster in females (0.307%/y) than males (0.216%/y) in temporal SCD. A negative correlation was observed between age and whole brain volume computed based on brain surface (females -1.031%/y, males -0.998%/y). In conclusion, we developed an automatic pipeline for MR-based skull thickness map, SCD, and brain volume analysis and demonstrated the sex-dependent association between minimum regional skull thickness, SCD and brain volume with age. This pipeline might be useful for personalized neurostimulation planning.
个性化神经刺激一直是许多脑部疾病的潜在治疗方法，这需要深入了解脑/颅骨几何结构。在此，我们开发了一个开源高效管道BrainCalculator，用于基于T加权磁共振成像（MRI）数据自动计算颅骨厚度图、头皮到皮质距离（SCD）和脑容量。我们对来自阿尔茨海默病神经成像计划（ADNI）的407名认知正常的老年人（71.9±8.0岁，60.2%为女性）进行了年龄和性别的横断面研究。我们证明了我们的管道与常用预处理软件包的兼容性，并发现与基于FSL脑提取工具2和SPM12的统一分割相比，BrainSuite Skullfinder更适合这种自动分析。我们发现，在男性和女性的颅骨区域中，蝶骨和颞骨最薄。除女性蝶骨外，区域最小颅骨厚度没有随年龄增加。未观察到最小颅骨厚度或SCD的性别差异。观察到年龄与SCD之间存在正相关，颞部SCD中女性（0.307%/年）比男性（0.216%/年）增加得更快。观察到年龄与基于脑表面计算的全脑容量之间存在负相关（女性-1.031%/年，男性-0.998%/年）。总之，我们开发了一种基于磁共振成像的颅骨厚度图、SCD和脑容量分析的自动管道，并证明了最小区域颅骨厚度、SCD和脑容量与年龄之间存在性别依赖性关联。该管道可能有助于个性化神经刺激计划。
