Dataset of preprocessed NII- and DTI-derived metrics from patients with ME/CFS and health controls with sedentary lifestyles

We provided the dataset of preprocessed diffusion-based neuroinflammation imaging (NII) and diffusion tensor imaging (DTI) derived metrics [NII-derived hindered water ratio (NII-HR), NII-derived hindered fraction of restricted isotropic diffusion (NII-RF), NII-derived fibre fraction (NII-FF), NII-derived axial diffusivity (NII-AD), NII-derived radial diffusivity (NII-RD), NII-derived mean diffusivity (NII-MD), NII-derived fractional anisotropy (NII-FA), DTI-derived fractional anisotropy (DTI-FA), DTI-derived mean diffusivity (DTI-MD), DTI-derived axial diffusivity (DTI-AD), and DTI-derived radial diffusivity (DTI-RD)] from 67 patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), and 67 healthy controls (HCs) with sedentary lifestyles. The dataset can be used to replicate the results of the manuscript titled “Evidence of white matter neuroinflammation in myalgic encephalomyelitis/chronic fatigue syndrome: a diffusion-based neuroinflammation imaging study”. This manuscript investigated white matter neuroinflammation in ME/CFS using NII and their correlation with clinical symptoms. Details of data collection and processing can be found in the manuscript. The demographic and symptom scores were provided in the spreadsheet. Elenven subject-level datasets were determined: 1. NII_HR.nii: preprocessed NII-derived hindered water ratio; 2. NII_RF.nii: preprocessed NII-derived hindered fraction of restricted isotropic diffusion; 3. NII_FF.nii: preprocessed NII-derived fibre fraction; 4. NII_AD.nii: preprocessed NII-derived axial diffusivity; 5. NII_RD.nii: preprocessed NII-derived radial diffusivity; 6. NII_MD.nii: preprocessed NII-derived mean diffusivity; 7. NII_FA.nii: preprocessed NII-derived fractional anisotropy; 8. DTI_AD.nii.gz: preprocessed DTI-derived axial diffusivity; 9. DTI_RD.nii.gz: preprocessed DTI-derived radial diffusivity; 10. DTI_FA.nii.gz: preprocessed DTI-derived fractional anisotropy; 11. DTI_MD.nii.gz: preprocessed DTI-derived mean diffusivity.本数据集包含67例肌痛性脑脊髓炎/慢性疲劳综合征（Myalgic Encephalomyelitis/Chronic Fatigue Syndrome, ME/CFS）患者与67名具有久坐生活方式的健康对照（healthy controls, HCs）的预处理后基于扩散的神经炎症成像（diffusion-based neuroinflammation imaging, NII）衍生指标，以及扩散张量成像（diffusion tensor imaging, DTI）衍生指标，具体包括：NII衍生受阻水比例（NII-derived hindered water ratio, NII-HR）、NII衍生受限各向同性扩散受阻分数（NII-derived hindered fraction of restricted isotropic diffusion, NII-RF）、NII衍生纤维分数（NII-derived fibre fraction, NII-FF）、NII衍生轴向扩散率（NII-derived axial diffusivity, NII-AD）、NII衍生径向扩散率（NII-derived radial diffusivity, NII-RD）、NII衍生平均扩散率（NII-derived mean diffusivity, NII-MD）、NII衍生各向异性分数（NII-derived fractional anisotropy, NII-FA），以及DTI衍生各向异性分数（DTI-derived fractional anisotropy, DTI-FA）、DTI衍生平均扩散率（DTI-derived mean diffusivity, DTI-MD）、DTI衍生轴向扩散率（DTI-derived axial diffusivity, DTI-AD）、DTI衍生径向扩散率（DTI-derived radial diffusivity, DTI-RD）。 本数据集可用于复现题为《肌痛性脑脊髓炎/慢性疲劳综合征的白质神经炎症证据：一项基于扩散的神经炎症成像研究》的论文研究成果。该论文通过NII指标探究了ME/CFS患者的白质神经炎症情况，及其与临床症状的相关性。数据采集与处理的详细细节可参见该论文。人口统计学资料与症状评分已整理至电子表格中。 本数据集共包含11个受试者级数据集，详情如下： 1. NII_HR.nii：预处理后的NII衍生受阻水比例； 2. NII_RF.nii：预处理后的NII衍生受限各向同性扩散受阻分数； 3. NII_FF.nii：预处理后的NII衍生纤维分数； 4. NII_AD.nii：预处理后的NII衍生轴向扩散率； 5. NII_RD.nii：预处理后的NII衍生径向扩散率； 6. NII_MD.nii：预处理后的NII衍生平均扩散率； 7. NII_FA.nii：预处理后的NII衍生各向异性分数； 8. DTI_AD.nii.gz：预处理后的DTI衍生轴向扩散率； 9. DTI_RD.nii.gz：预处理后的DTI衍生径向扩散率； 10. DTI_FA.nii.gz：预处理后的DTI衍生各向异性分数； 11. DTI_MD.nii.gz：预处理后的DTI衍生平均扩散率。