Methods.
- Methods. | 1 | 2 | 3 | 4 | 5 |
- Sixteen CFS patients (aged 24‐46 years; average age 34.0 years; 10 men and 6 women) and 49 age-matched healthy control subjects (aged 21‐47 years; average age 34.4 years; 27 men and 22 women) were enrolled in the study. They were recruited from the outpatient fatigue clinic in Osaka University Hospital (HK's special clinic) where more than 430 CFS patients, who met the diagnostic criteria of CFS [4], are being followed. The protocol was approved by the ethical committee of the National Institute for Physiological Sciences, Japan, and all subjects gave their written informed consent for the study. The periods of CFS lasted between 10 and 244 months, and the mean duration was 69.8 months (Table 1). All CFS patients were unable to carry out normal activities or actively work for several days a week because of severe general fatigue at the time of diagnosis. The severity of fatigue was measured using self-reported ratings based on daily activities (performance status; Table 2). A detailed neurological examination, the time course of the patients' signs and symptoms, and additional MRI (for 7 out of 16 patients) made the diagnosis of multiple sclerosis (MS) unlikely. The characteristics of the patients are shown in Table 1. To compare brain volumes, high-resolution anatomical images were acquired using a 3 Tesla MR scanner (Allegra, Siemens, Erlangen, Germany). A three-dimensional structural MRI was acquired for each subject using a T1-weighted magnetization-prepared rapid-gradient echo sequence (repetition time, 1970 ms; echo time, 4.3 ms; inversion time, 990 ms; number of excitation, 1; flip angle, 8°; matrix size, 256 × 256; field of view, 210 × 210 mm) yielding 160 sagittal slices with a slice thickness of 1.2 mm and an in-plane resolution of 0.82 mm.
- Voxel-based morphometry (VBM) [12] was performed using SPM2 for image processing and was analyzed with SnPM99 [13] implemented in MATLAB 6.1 (MathWorks, Natick, MA, USA). VBM is a fully-automated whole-brain morphometric technique that detects regional structural differences between groups on a voxel-by-voxel basis. Briefly, images were segmented into gray matter, white matter, cerebrospinal fluid and skull/scalp compartments, then normalized to standard space and re-segmented. Any volume changes induced by normalization were adjusted [10,11]. The spatially normalized segments of gray and white matter were smoothed using a 12-mm full-width half-maximum isotropic Gaussian kernel. Statistical analysis of regional differences between groups was performed using a permutation test for decreased probability of a particular voxel containing gray or white matter. Potential confounding effects of age, sex and whole segment (gray or white matter) volume differences were modeled, and the variances attributable to them were excluded from the analysis [11,14,15]. The significance levels for statistics estimated by 500 nonparametric randomization and permutation tests were set at P = 0.05, corrected for multiple comparisons. Within the areas showing a significant volume reduction in patients, linear correlates between volume reduction and the degree of fatigue were examined under the threshold of P < 0.005.
