Hongjian He

Simulation of changes in diffusion related to different pathologies at cellular level after traumatic brain injury.

The goal of the current study was to investigate tissue pathology at the cellular level in traumatic brain injury (TBI) as revealed by Monte Carlo simulation of diffusion tensor imaging (DTI)‐derived parameters and elucidate the possible sources of conflicting findings of DTI abnormalities as reported in the TBI literature.

Efficient parallel reconstruction for high resolution multishot spiral diffusion data with low rank constraint.

To propose a novel reconstruction method using parallel imaging with low rank constraint to accelerate high resolution multishot spiral diffusion imaging.

Robust sliding-window reconstruction for Accelerating the acquisition of MR fingerprinting.

To develop a method for accelerated and robust MR fingerprinting (MRF) with improved image reconstruction and parameter matching processes.

Effect of myelin water exchange on DTI‐derived parameters in diffusion MRI: Elucidation of TE dependence

Water exchange exists between different neuronal compartments of brain tissue but is often ignored in most diffusion models. The goal of the current study was to demonstrate the dependence of diffusion measurements on echo time (TE) in the human brain and to investigate the underlying effects of myelin water exchange.

High resolution myelin water imaging incorporating local tissue susceptibility analysis

Quantitative myelin water imaging (MWI) from signal T2* decay acquired with multiple Gradient-Recalled Echo (mGRE) sequence has been widely used since its first report. A recent study showed that with low resolution data (2mm isotropic voxels), direct application of complex fitting to a three-pool WM model with frequency shift terms could produce more stable parameter estimation for myelin water fraction mapping. MWI maps of higher spatial resolution resulting in more detailed tissue structures and reduced partial volume effects around white matter/gray matter (WM/GM) interface, however, is more desirable. Furthermore, as signal-to-noise ratio (SNR) of original images decreases due to reduced voxel size, the direct complex fitting procedure of myelin water imaging becomes more prone to systematic errors which severely compromised stability and reliability of the result. Instead of using the original part of T2* decay, this work presents a new method based on the WM-induced phase from tissue susceptibility calculated with the same mGRE dataset, in a three-pool WM model (water of myelin, axonal and extracellular water), to improve high resolution MWI. Compared with direct complex fitting for the higher spatial resolution case, the proposed method is shown to provide a more stable and accurate estimation of MWI parameters, and finer details near WM/GM boundaries with greatly reduced partial volume effects.

Detection of Lesions in Mesial Temporal Lobe Epilepsy by Using MR Fingerprinting

Purpose To improve diagnosis of hippocampal sclerosis (HS) in patients with mesial temporal lobe epilepsy (MTLE) by using MR fingerprinting and compare with visual assessment of T1- and T2-weighted MR images. Materials and Methods For this prospective study performed between April and November 2016, T1 and T2 maps were obtained and tissue segmentation performed in consecutive patients with drug-resistant MTLE with unilateral or bilateral HS. T1 and T2 maps were compared between 33 patients with MTLE (23 women and 10 men; mean age, 32.6 years; age range, 16-60 years) and 30 healthy participants (20 women and 10 men; mean age, 28.8 years; age range, 18-40 years). Differences in individual bilateral hippocampi were compared by using a Wilcoxon signed rank test, whereas the Wilcoxon rank-sum test was used for difference analysis between healthy control participants and patients with MTLE. Results The diagnosis rate (ie, ratio of HS diagnosed on the basis of a 2.5-minute MR fingerprinting examination compared with standard methods: MRI, electroencephalography, and PET) was 32 of 33 (96.9%; 95% confidence interval: 84.9%, 100%), reflecting improved accuracy of diagnosis (P = 1.92 × 10-12) over routine MR examinations that had a diagnostic rate of 23 of 33 (69.7%; 95% confidence interval: 51.5%, 81.6%). The comparison between atrophic and normal-appearing hippocampus in 33 patients with MTLE and healthy control participants demonstrated that both T1 and T2 values in HS lesions were higher than those of normal hippocampal tissue of healthy participants (T1: 1361 msec ± 85 vs 1249 msec ± 59, respectively; T2: 135 msec ± 15 vs 104 msec ± 9, respectively; P < .0001). Conclusion MR fingerprinting allowed for multiparametric mapping of temporal lobe within 2.5 minutes and helped to identify lesions suspicious for HS in patients with MTLE with improved accuracy.

Intra- and Inter-scanner Reliability of Scaled Subprofile Model of Principal Component Analysis on ALFF in Resting-State fMRI Under Eyes Open and Closed Conditions

Scaled Subprofile Model of Principal Component Analysis (SSM-PCA) is a multivariate statistical method and has been widely used in Positron Emission Tomography (PET). Recently, SSM-PCA has been applied to discriminate patients with Parkinsons disease and healthy controls with Amplitude of Low Frequency Fluctuation (ALFF) from Resting-State Functional Magnetic Resonance Imaging (RS-fMRI). As RS-fMRI scans are more readily available than PET scans, it is important to investigate the intra- and inter-scanner reliability of SSM-PCA in RS-fMRI. A RS-fMRI dataset with Eyes Open (EO) and Eyes Closed (EC) conditions was obtained in 21 healthy subjects (21.8 ± 1.8 years old, 11 females) on 3 visits (V1, V2, and V3), with V1 and V2 (mean interval of 14 days apart) on one scanner and V3 (about 8 months from V2) on a different scanner. To simulate between-group analysis in conventional SSM-PCA studies, 21 subjects were randomly divided into two groups, i.e., EC-EO group (EC ALFF map minus EO ALFF map, n = 11) and EO-EC group (n = 10). A series of covariance patterns and their expressions were derived for each visit. Only the expression of the first pattern showed significant differences between the two groups for all the visits (p = 0.012, 0.0044, and 0.00062 for V1, V2, and V3, respectively). This pattern, referred to as EOEC-pattern, mainly involved the sensorimotor cortex, superior temporal gyrus, frontal pole, and visual cortex. EOEC-patterns expression showed fair intra-scanner reliability (ICC = 0.49) and good inter-scanner reliability (ICC = 0.65 for V1 vs. V2 and ICC = 0.66 for V2 vs. V3). While the EOEC-pattern was similar with the pattern of conventional unpaired T-test map, the two patterns also showed method-specific regions, indicating that SSM-PCA and conventional T-test are complementary for neuroimaging studies.

Intra- and Inter-Scanner Reliability of Voxel-Wise Whole-Brain Analytic Metrics for Resting State fMRI

As the multi-center studies with resting-state functional magnetic resonance imaging (RS-fMRI) have been more and more applied to neuropsychiatric studies, both intra- and inter-scanner reliability of RS-fMRI are becoming increasingly important. The amplitude of low frequency fluctuation (ALFF), regional homogeneity (ReHo), and degree centrality (DC) are 3 main RS-fMRI metrics in a way of voxel-wise whole-brain (VWWB) analysis. Although the intra-scanner reliability (i.e., test-retest reliability) of these metrics has been widely investigated, few studies has investigated their inter-scanner reliability. In the current study, 21 healthy young subjects were enrolled and scanned with blood oxygenation level dependent (BOLD) RS-fMRI in 3 visits (V1 – V3), with V1 and V2 scanned on a GE MR750 scanner and V3 on a Siemens Prisma. RS-fMRI data were collected under two conditions, eyes open (EO) and eyes closed (EC), each lasting 8 minutes. We firstly evaluated the intra- and inter-scanner reliability of ALFF, ReHo, and DC. Secondly, we measured systematic difference between two scanning visits of the same scanner as well as between two scanners. Thirdly, to account for the potential difference of intra- and inter-scanner local magnetic field inhomogeneity, we measured the difference of relative BOLD signal intensity to the mean BOLD signal intensity of the whole brain between each pair of visits. Last, we used percent amplitude of fluctuation (PerAF) to correct the difference induced by relative BOLD signal intensity. The inter-scanner reliability was much worse than intra-scanner reliability; Among the VWWB metrics, DC showed the worst (both for intra-scanner and inter-scanner comparisons). PerAF showed similar intra-scanner reliability with ALFF and the best reliability among all the 4 metrics. PerAF reduced the influence of BOLD signal intensity and hence increase the inter-scanner reliability of ALFF. For multi-center studies, inter-scanner reliability should be taken into account.

Evaluating the Influence of Spatial Resampling for Motion Correction in Resting-State Functional MRI

Head motion is one of major concerns in current resting-state functional MRI studies. Image realignment including motion estimation and spatial resampling is often applied to achieve rigid-body motion correction. While the accurate estimation of motion parameters has been addressed in most studies, spatial resampling could also produce spurious variance, and lead to unexpected errors on the amplitude of BOLD signal. In this study, two simulation experiments were designed to characterize these variance related with spatial resampling. The fluctuation amplitude of spurious variance was first investigated using a set of simulated images with estimated motion parameters from a real dataset, and regions more likely to be affected by spatial resampling were found around the peripheral regions of the cortex. The other simulation was designed with three typical types of motion parameters to represent different extents of motion. It was found that areas with significant correlation between spurious variance and head motion scattered all over the brain and varied greatly from one motion type to another. In the last part of this study, four popular motion regression approaches were applied respectively and their performance in reducing spurious variance was compared. Among them, Friston 24 and Voxel-specific 12 model (Friston et al., 1996), were found to have the best outcomes. By separating related effects during fMRI analysis, this study provides a better understanding of the characteristics of spatial resampling and the interpretation of motion-BOLD relationship.