Center for Psychiatric Neuroscience, Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
Hum Brain Mapp. 2020 Oct 1;41(14):4041-4061. doi: 10.1002/hbm.25108. Epub 2020 Jul 10.
The structural complexity of the thalamus, due to its mixed composition of gray and white matter, make it challenging to disjoint and quantify each tissue contribution to the thalamic anatomy. This work promotes the use of partial-volume-based over probabilistic-based tissue segmentation approaches to better capture thalamic gray matter differences between patients at different stages of psychosis (early and chronic) and healthy controls. The study was performed on a cohort of 23 patients with schizophrenia, 41 with early psychosis and 69 age and sex-matched healthy subjects. Six tissue segmentation approaches were employed to obtain the gray matter concentration/probability images. The statistical tests were applied at three different anatomical scales: whole thalamus, thalamic subregions and voxel-wise. The results suggest that the partial volume model estimation of gray matter is more sensitive to detect atrophies within the thalamus of patients with psychosis. However all the methods detected gray matter deficit in the pulvinar, particularly in early stages of psychosis. This study demonstrates also that the gray matter decrease varies nonlinearly with age and between nuclei. While a gray matter loss was found in the pulvinar of patients in both stages of psychosis, reduced gray matter in the mediodorsal was only observed in early psychosis subjects. Finally, our analyses point to alterations in a sub-region comprising the lateral posterior and ventral posterior nuclei. The obtained results reinforce the hypothesis that thalamic gray matter assessment is more reliable when the tissues segmentation method takes into account the partial volume effect.
丘脑的结构复杂性，由于其灰质和白质的混合组成，使得将每个组织的贡献与丘脑解剖结构区分开来并进行量化变得具有挑战性。这项工作促进了基于部分体积的组织分割方法的使用，以更好地捕捉处于不同精神病阶段（早期和慢性）的患者和健康对照者之间的丘脑灰质差异。该研究在一个包括 23 名精神分裂症患者、41 名早期精神病患者和 69 名年龄和性别匹配的健康受试者的队列中进行。采用了六种组织分割方法来获得灰质浓度/概率图像。统计检验在三个不同的解剖学尺度上进行：整个丘脑、丘脑亚区和体素水平。结果表明，灰质的部分体积模型估计对于检测精神病患者丘脑内的萎缩更为敏感。然而，所有方法都在丘脑的枕核中检测到灰质缺陷，尤其是在精神病的早期阶段。这项研究还表明，灰质的减少与年龄和核之间呈非线性变化。虽然在两个精神病阶段的患者中都发现了枕核的灰质损失，但仅在早期精神病患者中观察到中背核的灰质减少。最后，我们的分析指出，包含外侧后核和腹侧后核的亚区发生了改变。所得到的结果强化了这样一种假设，即当组织分割方法考虑到部分体积效应时，丘脑灰质评估更为可靠。
