The Application of Diffusion Kurtosis Imaging on the Heterogeneous White Matter in Relapsing-Remitting Multiple Sclerosis

Multimodal magnetic resonance longitudinal study on the deep gray matter in multiple sclerosis patients with teriflunomide

Disease-modifying therapies (DMTs) are used in an increasing number of patients with multiple sclerosis (MS). However, whether DMTs have intrinsic effects on deep gray matter (DGM) microstructure and atrophy is still poorly understood. In this study, we described the quantitative susceptibility values (QSV) and diffusion kurtosis imaging (DKI) metrics of DGM in relapsing-remitting MS (RRMS) patients and their association with cognitive deficits. We recruited 62 patients with RRMS receiving DMTs and 30 patients with RRMS not receiving DMTs underwent MRI on a 3T scanner. Fractional anisotropy (FA), kurtosis fractional anisotropy (KFA), mean diffusivity (MD), mean kurtosis (MK), QSV and volumes of bilateral caudate nucleus (CAU), amygdala (AMYG), putamen (PUT), hippocampus (Hipp), globus pallidus (GP) and thalamus (THA) were measured. Correlation analysis was performed between those image indexes with longitudinal significant changes and clinical neurological scores, including Expanded Disability Status Scale (EDSS), Digit Span Testand (DST), Symbol Digit Modalities Test (SDMT), Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Significant longitudinal increases in FA, KFA and MK values were found in both groups in bilateral CAU, AMYG, PUT, Hipp, GP and THA (all p < 0.005). MD values of the right of CAU in the two groups were significant longitudinal increase (p = 0.009, p = 0.047); MD values of the right of GP (p = 0.042), the left of THA (p = 0.003), the right of THA (p = 0.001) in treated MS were significant longitudinal decrease; There were no significant longitudinal changes between treated and untreated groups in normalized deep gray matter volume. For QSV, longitudinal increase in the right of PUT (p = 0.022) in the treated MS group and in the left of Hipp (p = 0.045) in the untreated MS group. The QSV and DKI measures were highly correlated with cognitive and disability tests. The treated RRMS patients showed different longitudinal changes of MD value and QSV with untreated in several DGM regions, and these differences were correlated with cognitive and microstructural integrity.

Increased cortical lesion load contributed to pathological changes beyond focal lesion in cortical gray matter of multiple sclerosis: a diffusion kurtosis imaging analysis

Biomarkers specific to cortical gray matter (cGM) pathological changes of multiple sclerosis (MS) are desperately needed to better understand the disease progression. The cGM damage occurs in cortical lesion (CL) and normal-appearing cGM (NAcGM) areas. While the association between CL load and cGM damage has been reported, little is known about how different CL types, i.e. intracortical lesion (ICL) and leukocortical lesion (LCL) would be associated with cGM damage. In our study, relapsing-remitting MS patients and healthy controls were divided into 4 groups according to CL load level. NAcGM diffusion kurtosis imaging (DKI)/diffusion tensor imaging (DTI) values and cGM volume (cGMV) were used to characterize the pathological changes in cGM. Univariate general linear model was used for group comparisons and stepwise regression analysis was used to assess the effects of ICL volume and LCL volume on NAcGM damage. We found peak values in DKI/DTI values, cGMV and neuropsychological scores in high CL load group. Kurtosis fractional anisotropy (KFA) was the most sensitive in characterizing NAcGM damage, and LCL volume related more to NAcGM damage. Our findings suggested KFA could become a surrogate biomarker to cGM damage, and LCL might be the main factor in whole brain NAcGM damage.

Microstructural alterations in different types of lesions and their perilesional white matter in relapsing-remitting multiple sclerosis based on diffusion kurtosis imaging

BACKGROUND AND OBJECTIVES

In multiple sclerosis (MS), contrast enhancement lesions and chronic active lesions have been demonstrated to have different degrees of inflammation. Accordingly, they exist different degrees of tissue damage, one is short and acute, and another is slow and longstanding. This study aimed to explore whether diffusion parameters can differentiate different types of lesions, and investigate the microstructural damage between different types of MS lesions by using diffusion magnetic resonance imaging (dMRI) and its correlation with clinical biomarkers of disability and cognitive states.

METHODS

We retrospectively identified 77 contrast enhancement lesions (CELs), 384 iron rim lesions (IRLs), 393 non-iron rim lesions (NIRLs), their corresponding perilesional white matter (PLWM), and 68 normal-appearing white matter (NAWM) from 68 relapsing-remitting MS (RRMS). Additionally, 44 white matter in healthy controls (WM in HCs) were also enrolled in this study. The DTI and DKI parameters were measured in the above white matter, including kurtosis fractional anisotropy (KFA), fractional anisotropy (FA), mean kurtosis (MK), and mean diffusivity (MD). All the patients were assessed with the Digital Span Test (DST), the Symbol Digit Modalities Test (SDMT), the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), and the Expanded Disability Status Scale (EDSS).

RESULTS

The lowest KFA, FA, MK values and the highest MD values were found in CELs, followed by IRLs, NIRLs, NAWM, and WM in HCs. In KFA and FA values, there were significant differences between each type of lesion, as well as each type of PLWM (P < 0.05). The MK values of CELs and IRLs were significantly lower than NIRLs, but inversely for MD (P < 0.05). There were no differences between CELs and IRLs for MK (P = 1) and MD (P = 0.261). The results of MK and MD values in CELs-PLWM and IRLs-PLWM were similar to the CELs and IRLs. There were no significant differences between NAWM and WM in HCs in all the enrolled diffusion parameters (P >0.05) and the FA values between NIRLs-PLWM and NAWM or between NIRLs-PLWM and WM in HCs were no significant differences (P >0.05). The KFA and MD values in IRLs-PLWM (r =0.443, P =0.021; r =-0.518, P =0.006) were correlated with the DST scores and the KFA of CELs-PLWM (r =0.396, P =0.041) was correlated with SDMT scores.

CONCLUSION

Our findings demonstrate that the KFA values have the potential to distinguish different types of MS white matter tissues. Furthermore, the diffusion parameters can reflect the microstructure abnormalities in different MS lesions and might help us better understand the pathological mechanism and lesion evolution.

Application of TBSS-based machine learning models in the diagnosis of pediatric autism

Objective

To explore the microstructural changes of white matter in children with pediatric autism by using diffusion kurtosis imaging (DKI), and evaluate whether the combination of tract-based spatial statistics (TBSS) and back-propagation neural network (BPNN)/support vector machine (SVM)/logistic regression (LR) was feasible for the classification of pediatric autism.

Methods

DKI data were retrospectively collected from 32 children with autism and 27 healthy controls (HCs). Kurtosis fractional anisotropy (FAK), mean kurtosis (MK), axial kurtosis (KA), radial kurtosis (RK), fractional anisotropy (FA), axial diffusivity (DA), mean diffusivity (MD) and Radial diffusivity (DR) were generated by iQuant workstation. TBSS was used to detect the regions of parameters values abnormalities and for the comparison between these two groups. In addition, we also introduced the lateralization indices (LI) to study brain lateralization in children with pediatric autism, using TBSS for additional analysis. The parameters values of the differentiated regions from TBSS were then calculated for each participant and used as the features in SVM/BPNN/LR. All models were trained and tested with leave-one-out cross validation (LOOCV).

Results

Compared to the HCs group, the FAK, DA, and KA values of multi-fibers [such as the bilateral superior longitudinal fasciculus (SLF), corticospinal tract (CST) and anterior thalamic radiation (ATR)] were lower in pediatric autism group (p < 0.05, TFCE corrected). And we also found DA lateralization abnormality in Superior longitudinal fasciculus (SLF) (the LI in HCs group was higher than that in pediatric autism group). However, there were no significant differences in FA, MD, MK, DR, and KR values between HCs and pediatric autism group (P > 0.05, TFCE corrected). After performing LOOCV to train and test three model (SVM/BPNN/LR), we found the accuracy of BPNN (accuracy = 86.44%) was higher than that of LR (accuracy = 76.27%), but no different from SVM (RBF, accuracy = 81.36%; linear, accuracy = 84.75%).

Conclusion

Our proposed method combining TBSS findings with machine learning (LR/SVM/BPNN), was applicable in the classification of pediatric autism with high accuracy. Furthermore, the FAK, DA, and KA values and Lateralization index (LI) value could be used as neuroimaging biomarkers to discriminate the children with pediatric autism or not.

Alterations of Thalamic Nuclei Volumes and the Intrinsic Thalamic Structural Network in Patients with Multiple Sclerosis-Related Fatigue

Fatigue is a debilitating and prevalent symptom of multiple sclerosis (MS). The thalamus is atrophied at an earlier stage of MS and although the role of the thalamus in the pathophysiology of MS-related fatigue has been reported, there have been few studies on intra-thalamic changes. We investigated the alterations of thalamic nuclei volumes and the intrinsic thalamic network in people with MS presenting fatigue (F-MS). The network metrics comprised the clustering coefficient (Cp), characteristic path length (Lp), small-world index (σ), local efficiency (Eloc), global efficiency (Eglob), and nodal metrics. Volumetric analysis revealed that the right anteroventral, right central lateral, right lateral geniculate, right pulvinar anterior, left pulvinar medial, and left pulvinar inferior nuclei were atrophied only in the F-MS group. Furthermore, the F-MS group had significantly increased Lp compared to people with MS not presenting fatigue (NF-MS) (2.9674 vs. 2.4411, PAUC = 0.038). The F-MS group had significantly decreased nodal efficiency and betweenness centrality of the right mediodorsal medial magnocellular nucleus than the NF-MS group (false discovery rate corrected p < 0.05). The F-MS patients exhibited more atrophied thalamic nuclei, poorer network global functional integration, and disrupted right mediodorsal medial magnocellular nuclei interconnectivity with other nuclei. These findings might aid the elucidation of the underlying pathogenesis of MS-related fatigue.

The heterogeneity of tissue destruction between iron rim lesions and non-iron rim lesions in multiple sclerosis: A diffusion MRI study

OBJECTIVES

This study aimed to explore the microstructural heterogeneity of different white matter (WM) tissues in relapsing-remitting multiple sclerosis (RRMS) patients by diffusion magnetic resonance imaging (dMRI) and its correlation with disability and cognitive status.

MATERIALS AND METHODS

A total of 337 iron rim lesions (IRLs), 337 perilesional white matters of IRLs (IRLs-PLWMs), 330 non-iron rim lesions (non-IRLs), 330 non-IRLs-PLWMs, 42 normal-appearing white matters (NAWMs) in 42 RRMS patients, and 30 white matters in healthy controls (WMs in HCs) were enrolled in the lesion-wise analysis. Diffusion kurtosis imaging (DKI) parameters including kurtosis fractional anisotropy (KFA) and mean kurtosis (MK), and diffusion tensor imaging (DTI) parameters including fractional anisotropy (FA) and mean diffusivity (MD) were measured in the six types of tissues. Subgroup analysis was performed between non-IRLs with QSM hyperintense (non-IRLs-H) and non-IRLs with QSM isointense or hypointense (non-IRLs-I), as well as between non-IRLs-H-PLWMs and non-IRLs-I-PLWMs. Thirty-four out of forty-two patients were enrolled in patient-wise analysis. The relationships between these diffusion metrics of patients and their Kurtzke Expanded Disability Status Scale (EDSS) score and Symbol Digit Modalities Test (SDMT) score were analyzed separately by partial correlation analysis with age and disease duration (DD) as covariates.

RESULTS

The KFA, FA, MK, and MD values were significantly different among the six types of tissues. The lowest KFA, FA, and MK values and the highest MD values were revealed in IRLs. There were significant differences in all the enrolled diffusion metrics between IRLs and non-IRLs, as well as between IRLs-PLWMs and non-IRLs-PLWMs (p < 0.05). There were no significant differences between NAWMs and WMs in HCs (p = 1.000 for all enrolled diffusion metrics). For all the enrolled diffusion metrics, no significant differences were found in the subgroup analysis. The FA, MK, and MD values of total lesions (including IRLs and non-IRLs) (r = -0.420, p = 0.017; r = -0.472, p = 0.006; r = -0.475, p = 0.006) and the MK values of IRLs (r = -0.438, p = 0.012) were correlated with the EDSS scores. There was no significant correlation between the diffusion parameter values and the SDMT scores.

CONCLUSION

Our findings demonstrate that IRLs are more destructive than non-IRLs. Similarly, IRLs-PLWMs are more destructive than non-IRLs-PLWMs. Additionally, diffusion parameter values of MS lesions can reflect the disability degree. These findings contribute to a better understanding of the different evolution of MS lesions and the relationship between the disability level of patients and focal lesion damage degree.