Subjects and clinical evaluation
Twenty-five patients (13 nIHH patients and 12 KS patients) with an average age of 17.88±1.51 years, ranging from 15 to 21 years of age, were recruited from the Department of Endocrinology and were assessed. All patients were males. A complete laboratory endocrine examination was obtained for each patient. The Smell Identification Test was performed to evaluate olfactory function (14). Clinical symptoms and signs of hypogonadism, as well as data from clinical reports indicating normal or defective olfactory function, were used as the diagnostic criteria for KS or nIHH.
A total of 25 age-matched healthy male controls were recruited from the community. MRI scans and laboratory tests were performed. Exclusion criteria for all participants in our control group included the following: (1) any history of prematurity and other endocrine diseases, (2) any psychiatric diseases or neurological disorders, (3) a history of neurosurgery or head trauma with a loss of consciousness ≥ 5 min, (4) medication history that may affect the central nervous system, and (5) any MRI contraindications. This study was approved by the medical research ethics committee and was in accordance with the Declaration of Helsinki. All participants provided written informed consent.
We performed MRI scans by using a GE Signa HDX 3.0T MR scanner. Thin-section (1 mm) coronal three-dimensional time of flight spoiled gradient recalled acquisition (3D T1 SPGR) and three-dimensional fast imaging employing steady-state acquisition (3D FIESTA) were acquired for rhinencephalon evaluation. At least 2 radiologists separately evaluated the olfactory sulci and bulbs of the 25 patients and 25 healthy controls. Functional magnetic resonance imaging (fMRI) scans were obtained using a spin-echo planar imaging sequence aligned to the anterior and posterior commissure plane (AC-PC plane) with the following scan parameters: echo time (TE) = 30 ms, repetition time (TR) = 2000 ms, matrix = 64 × 64, flip angle = 90°, field of view (FOV) = 240 × 240 mm, 35 slices of 3 mm, and no gap. DTI was performed in alignment with the AC-PC plane using a spin-echo planar imaging sequence. We applied diffusion sensitizing gradients along 25 non-collinear directions (b value = 1000 s/mm2), together with a non-diffusion weighted acquisition. The scan parameters were as follows: TE = 85.4 ms, TR = 17000 ms, matrix = 120 × 120, FOV = 240 × 240 mm, slice thickness = 2 mm, no gap, and 65 slices. The subjects were to close their eyes but remain awake throughout the scan.
MRI data processing and analysis
FMRI data processing
Resting-state fMRI data pre-processing included disposing the first 10 time points, slice timing, head motion correction, and normalization to the Montreal Neurological Institute (MNI) template (resampling voxel size = 3 × 3 × 3 mm3), followed by spatial smoothing (full width at half-maximum = 6 mm). Subjects with excessive motion (head motion > 3 mm or head rotation > 3°) were excluded. Pre-processing of REST involves filtering the time series of each voxel (bandpass filtering, 0.01- 0.08 Hz) to reduce the effects of low-frequency drifts and high-frequency physiological noise. Linear regression was performed for the head motion parameters, white matter signal, cerebrospinal fluid signal, and global mean signal to eliminate the influence of the nuisance covariates.
Definition of Regions of Interest (ROIs)
We selected the bilateral olfactory cortex as the seed ROI based on the definition of the automated anatomical labelling (AAL) template contained in DPABI (resampling voxel size = 3 × 3 × 3 mm3) (15). The olfactory cortex ROIs were defined as bilateral regions placed on Brodmann’s areas 21 and 22 in MNI coordinates using the WFU_PickAtlas (https://www.nitrc.org/frs/?group_id=46). The detailed olfactory cortex ROIs are provided in the Supplementary results (Fig. S1). A reference time series was extracted by averaging the fMRI time series of all of the voxels within the ROI in each participant. The correlations between the seed ROI and the rest of the brain were calculated in a voxel-wise manner by DPABI. The correlation coefficients were transformed to z-values using Fisher’s r-to-z transformation.
DTI data processing
PANDA software was used to process the DTI Images (16) (Pipeline for Analysing braiN Diffusion imAges 1.2.3 http://www.nitrc.org/projects/panda/), which synthesizes procedures in FSL (http://fsl.fmrib.ox.ac.uk/fsl), MRIcron (http://www.mccauslandcenter.sc.edu/mricro/mricron), and Diffusion Toolkit (http://www.nmr.mgh.harvard.edu/~rpwang/dtk). The following steps were used to pre-process images: converting DICOM files into NIfTI images, estimating the brain mask, cropping images, correcting for the eddy-current effect, averaging acquisitions, calculating DTI metrics, and generating diffusion metrics for statistical analysis. The individual images of the diffusion metrics were transformed from native space to standard MNI space by spatial normalization (voxel size = 1 × 1 × 1 mm3).
The rsFC and fractional anisotropy (FA) results in the three groups were analysed by ANOVA using DPABI software. Multiple comparisons were performed by Gaussian random field (GRF) correction, and the significance threshold was set at p < 0.05 at the cluster level and p < 0.01 at the voxel level. Then, we performed post hoc pair-wise comparisons of olfactory cortex FC strength among groups (KS v. HC, nIHH v.HC and KS v. HC) in significant regions with Bonferroni tests (p < 0.05). The fine anatomical localization of statistical results was acquired based on the AAL template.
We performed Pearson’s correlation analyses to investigate the correlations between the FA value and FC strength, showing significant differences among the three groups separately. Statistical Package for the Social Sciences (SPSS) software, version 20.0 (SPSS Inc., Chicago, IL, USA), was used to perform statistical analysis of clinical and demographical variables. All statistical thresholds were set at p < 0.05.