Fractional Anisotropy Kurtosis Research Articles

Diffusion kurtosis imaging of brain white matter alteration in patients with coronary artery disease based on the TBSS method.

The aim of our study was to examine the alterations in microstructure in patients with coronary artery disease (CAD) and cognitive impairment (CI) using diffusion kurtosis imaging (DKI). Additionally, we aimed to investigate the potential correlation between DKI parameters and cognitive function. A total of 28 CAD patients and 30 healthy controls (HC) were prospectively enrolled in our study. All participants underwent routine and diffusion sequences of head imaging. DKE software was utilized to generate various diffusion kurtosis imaging parameters (DKI), including kurtosis fractional anisotropy (KFA), mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), fractional anisotropy (FA), and mean diffusivity (MD). Nonparametric tests were conducted using tract-based spatial statistics (TBSS) to compare the parameter values between the two groups. The parameter values of the significantly different fiber tracts were extracted and correlated with the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. Compared to the HC group, patients with coronary artery disease exhibited significant reductions in FA values in the bilateral Superior corona radiata, bilateral Anterior corona radiata, bilateral Posterior corona radiata, corpus callosum, left Posterior thalamic radiation, right Posterior limb of internal capsule, Anterior limb of internal capsule, and Cerebral peduncle, as well as in the left Superior longitudinal fasciculus. Additionally, KFA values decreased in the bilateral Anterior corona radiata, bilateral Anterior limb of internal capsule, and Genu of the corpus callosum. The MK values decreased in the right Posterior corona radiata, Retrolenticular part of the internal capsule, Posterior thalamic radiation (including optic radiation), Superior longitudinal fasciculus, and left Posterior thalamic radiation (including optic radiation). Moreover, the RK values decreased in the bilateral Retrolenticular part of the internal capsule, right Posterior thalamic radiation (including optic radiation), and Superior longitudinal fasciculus, as well as in the left Superior longitudinal fasciculus and Posterior thalamic radiation (including optic radiation) (p < 0.01, TFCE corrected), while no significant differences were observed in other parameter values (p > 0.01, TFCE corrected). The FA values of the right posterior limb of the internal capsule (r = 0.610, p = 0.001) and the right cerebral peduncle (r = 0.622, p < 0.001) were positively correlated with MMSE scores. Additionally, a significant correlation between kurtosis and diffusion coefficient parameters (FA and KFA) was observed. CAD patients showed radial shrinkage and complexity of brain white matter microstructure. Whole-brain white matter analysis based on TBSS DKI can objectively reflect the characteristics of white matter damage in CAD patients, providing a basis for the auxiliary diagnosis of CAD with CI.

Diagnosis of dysthyroid optic neuropathy: combined value of orbital MRI and intracranial visual pathway diffusion kurtosis imaging.

To evaluate the combined performance of orbital MRI and intracranial visual pathway diffusion kurtosis imaging (DKI) in diagnosing dysthyroid optic neuropathy (DON). We retrospectively enrolled 61 thyroid-associated ophthalmopathy (TAO) patients, including 25 with DON (40 eyes) and 36 without DON (72 eyes). Orbital MRI-based apical muscle index (MI), diameter index (DI) of the optic nerve (ON), area index (AI) of the ON, apparent diffusion coefficient (ADC) and signal intensity ratio (SIR) of the ON, DKI-based kurtosis fractional anisotropy (KFA) and mean kurtosis (MK) of the optic tract (OT), optic radiation (OR), and Brodmann areas (BAs) 17, 18, and 19 were measured and compared between groups. The diagnostic performances of models were evaluated using receiver operating characteristic curve analyses and compared using the DeLong test. TAO patients with DON had significantly higher apical MI, apical AI, and SIR of the ON, but significantly lower ADC of the ON than those without DON (p < 0.05). Meanwhile, the DON group exhibited significantly lower KFA across the OT, OR, BA17, BA18, and BA19 and lower MK at the OT and OR than the non-DON group (p < 0.05). The model integrating orbital MRI and intracranial visual pathway DKI parameters performed the best in diagnosing DON (AUC = 0.926), with optimal diagnostic sensitivity (80%) and specificity (94.4%), followed by orbital MRI combination (AUC = 0.890), and then intracranial visual pathway DKI combination (AUC = 0.832). Orbital MRI and intracranial visual pathway DKI can both assist in diagnosing DON. Combining orbital and intracranial imaging parameters could further optimize diagnostic efficiency. The novel finding could bring novel insights into the precise diagnosis and treatment of dysthyroid optic neuropathy, accordingly, contributing to the improvement of the patients' prognosis and quality of life in the future. • Orbital MRI and intracranial visual pathway diffusion kurtosis imaging can both assist in diagnosing dysthyroid optic neuropathy. • Combining orbital MRI and intracranial visual pathway diffusion kurtosis imaging optimized the diagnostic efficiency of dysthyroid optic neuropathy.

Microstructural white matter abnormalities in overactive bladder syndrome evaluation with diffusion kurtosis imaging tract-based spatial statistics analysis.

This prospective study aimed to explore the microstructural alterations of the white matter in overactive bladder syndrome (OAB) using the Tract-based Spatial Statistics (TBSS) method of diffusion kurtosis imaging (DKI). A total of 30 patients were enrolled and compared with 30 controls. White matter (WM) status was assessed using tract-based spatial statistics for DKI. The differences in DKI-derived parameters, including kurtosis fractional anisotropy (KFA), fractional anisotropy (FA), mean kurtosis (MK), mean diffusivity (MD), radial kurtosis (RK), axial kurtosis (AK), axial diffusivity (AD), and radial diffusivity (RD), were compared between the two groups using the TBSS method. The correlation between the altered DKI-derived parameters and the (OABSS) scores was analyzed. A receiver operating characteristic curve (ROC) was used to evaluate the diagnostic performance of different white matter parameters. As a result, compared with the HC group, the KFA, and FA values decreased significantly in the OAB group. Compared with the HC group, the MK and MD values increased significantly in the OAB group. The KFA values of the genu of corpus callosum (GCC) were significantly correlated with the OABSS scores (r = -0.509; p = 0.004). The FA values of anterior corona radiata (ACR) were significantly correlated with OABSS scores (r = -0.447; p = 0.013). The area under the ROC curve (AUC) for the genu of corpus callosum KFA values was higher than FA for the diagnosis of OAB patients. DKI is a promising approach to the investigation of the pathophysiology of OAB and a potential biomarker for clinical diagnosis of OAB.

Telomeres are associated with markers and regions sensitive to aging and not Alzheimer’s disease in cognitively unimpaired older adults

AbstractBackgroundTelomeres (protective chromosomal ends) gradually shorten over the lifespan and have been associated with the development of age‐related diseases such as Alzheimer’s disease (AD). Most studies use median telomere length as a biomarker of cellular aging, but their dysfunction is rather reflected by the load of short telomere. No study to date has assessed the links between the percentage of short telomeres (ST) and blood, neuroimaging markers of aging, neurodegeneration, amyloid and tau pathologies in healthy elderly.MethodBaseline data from 125 cognitively unimpaired older adults (65 to 83 years old; mean ± SD: 68.9 ± 2.8) from the Age‐Well trial (NCT02977819), who completed multimodal neuroimaging and blood sampling, were analyzed. Neuroimaging data included structural T1‐weighted MRI, T2‐weighted high‐resolution scan of the hippocampus, DKI, FDG‐PET and AV45‐PET (perfusion and amyloid load). ST, as well as neurodegeneration, amyloid, and tau biomarkers (NFL, GFAP, Aß42/40 ratio and pTau181) were measured in blood samples. Multiple linear regressions between ST and each marker were conducted corrected for age, sex, education and body mass index. Additional adjustments for APOE and amyloid status were made. Statistical significance was set to p&lt;0.05, except for voxelwise analyses (puncorrected&lt;0.005, kuncorrected = 500 voxels).ResultST was associated with lower white matter integrity (measured by kurtosis fractional anisotropy (kFA)) in prefrontal and temporal regions (Fig.1), and with the hippocampal subiculum volume, but not with total gray matter volume, mean kurtosis, glucose metabolism, brain perfusion or amyloid load; nor with blood markers of neurodegeneration, amyloid, or tau. Additional adjustments for APOE/amyloid status gave similar results.ConclusionTelomere dysfunctions were associated with lower white matter integrity in regions vulnerable to aging, but not to AD, nor with neurodegeneration, amyloid or tau biomarkers, and neither with AD risk factors (APOE or amyloid status). When we focused on the hippocampus, a specific link was found with the subiculum volume, an hippocampal subfield known to be the most sensitive to aging, which is not the case in AD. These results give further evidence for the tight connection between cellular and cerebral aging, but not with AD in cognitively unimpaired older adults.

Telomeres are associated with markers and regions sensitive to aging and not Alzheimer’s disease in cognitively unimpaired older adults

AbstractBackgroundTelomeres (protective chromosomal ends) gradually shorten over the lifespan and have been associated with the development of age‐related diseases such as Alzheimer’s disease (AD). Most studies use median telomere length as a biomarker of cellular aging, but their dysfunction is rather reflected by the load of short telomere. No study to date has assessed the links between the percentage of short telomeres (ST) and blood, neuroimaging markers of aging, neurodegeneration, amyloid and tau pathologies in healthy elderly.MethodBaseline data from 125 cognitively unimpaired older adults (65 to 83 years old; mean ± SD: 68.9 ± 2.8) from the Age‐Well trial (NCT02977819), who completed multimodal neuroimaging and blood sampling, were analyzed. Neuroimaging data included structural T1‐weighted MRI, T2‐weighted high‐resolution scan of the hippocampus, DKI, FDG‐PET and AV45‐PET (perfusion and amyloid load). ST, as well as neurodegeneration, amyloid, and tau biomarkers (NFL, GFAP, Aβ42/40 ratio and pTau181) were measured in blood samples. Multiple linear regressions between ST and each marker were conducted corrected for age, sex, education and body mass index. Additional adjustments for APOE and amyloid status were made. Statistical significance was set to p&lt;0.05, except for voxelwise analyses (puncorrected&lt;0.005, kuncorrected = 500 voxels).ResultST was associated with lower white matter integrity (measured by kurtosis fractional anisotropy (kFA)) in prefrontal and temporal regions (Fig.1), and with the hippocampal subiculum volume, but not with total gray matter volume, mean kurtosis, glucose metabolism, brain perfusion or amyloid load; nor with blood markers of neurodegeneration, amyloid, or tau. Additional adjustments for APOE/amyloid status gave similar results.ConclusionTelomere dysfunctions were associated with lower white matter integrity in regions vulnerable to aging, but not to AD, nor with neurodegeneration, amyloid or tau biomarkers, and neither with AD risk factors (APOE or amyloid status). When we focused on the hippocampus, a specific link was found with the subiculum volume, an hippocampal subfield known to be the most sensitive to aging, which is not the case in AD. These results give further evidence for the tight connection between cellular and cerebral aging, but not with AD in cognitively unimpaired older adults.

Diffusion kurtosis imaging tractography reveals disrupted white matter structural networks in children with obstructive sleep apnea syndrome.

To assess the disruptions of brain white matter (WM) structural network in children with obstructive sleep apnea (OSA) using diffusion kurtosis imaging (DKI). We use DKI tractography to construct individual whole-brain, region-level WM networks in 40 OSA and 28 healthy children. Then, we apply graph theory approaches to analyze whether OSA children would show altered global and regional network topological properties and whether these alterations would significantly correlate with the clinical characteristics of OSA. We found that both OSA and healthy children showed an efficient small-world organization and highly similar hub distributions in WM networks. However, characterized by kurtosis fractional anisotropy (KFA) weighted networks, OSA children exhibited decreased global and local efficiency, increased shortest path length compared with healthy children. For regional topology, OSA children exhibited significant decreased nodal betweenness centrality (BC) in the bilateral medial orbital superior frontal gyrus (ORBsupmed), right orbital part superior frontal gyrus (ORBsup), insula, postcentral gyrus, left middle temporal gyrus (MTG), and increased nodal BC in the superior parietal gyrus, pallidum. Intriguingly, the altered nodal BC of multiple regions (right ORBsupmed, ORBsup and left MTG) within default mode network showed significant correlations with sleep parameters for OSA patients. Our results suggest that children with OSA showed decreased global integration and local specialization in WM networks, typically characterized by DKI tractography and KFA metric. This study may advance our current understanding of the pathophysiological mechanisms of impaired cognition underlying OSA.

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.

U-fiber diffusion kurtosis and susceptibility characteristics in relapsing-remitting multiple sclerosis may be related to cognitive deficits and neurodegeneration.

To evaluate the diffusion kurtosis and susceptibility change in the U-fiber region of patients with relapsing-remitting multiple sclerosis (pwRRMS) and their correlations with cognitive status and degeneration. Mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), kurtosis fractional anisotropy (KFA), and the mean relative quantitative susceptibility mapping (mrQSM) values in the U-fiber region were compared between 49 pwRRMS and 48 healthy controls (HCs). The U-fiber were divided into upper and deeper groups based on the location. The whole brain volume, gray and white matter volume, and cortical thickness were obtained. The correlations between the mrQSM values, DKI-derived metrics in the U-fiber region and clinical scale scores, brain morphologic parameters were further investigated. The decreased MK, AK, RK, KFA, and increased mrQSM values in U-fiber lesions (p < 0.001, FDR corrected), decreased RK, KFA, and increased mrQSM values in U-fiber non-lesions (p = 0.034, p < 0.001, p < 0.001, FDR corrected) were found in pwRRMS. There were differences in DKI-derived metrics and susceptibility values between the upper U-fiber region and the deeper one for U-fiber non-lesion areas of pwRRMS and HCs (p < 0.05), but not for U-fiber lesions in DKI-derived metrics. The DKI-derived metrics and susceptibility values were widely related with cognitive tests and brain atrophy. RRMS patients show abnormal diffusion kurtosis and susceptibility characteristics in the U-fiber region, and these underlying tissue abnormalities are correlated with cognitive deficits and degeneration. The macroscopic and microscopic tissue damages of U-fiber help to identify cognitive impairment and brain atrophy in multiple sclerosis and provide underlying pathophysiological mechanism. • Diffusion kurtosis and susceptibility changes are present in the U-fiber region of multiple sclerosis. • There are gradients in diffusion kurtosis and susceptibility characteristics in the U-fiber region. • Tissue damages in the U-fiber region are correlated with cognitive impairment and brain atrophy.

Quantitative microglia morphological features correlate with diffusion MRI in 2-month-old 3xTg-AD mice

Microglia (MØ) morphologies are closely related to their functional state and have a central role in the maintenance of brain homeostasis. It is well known that inflammation contributes to neurodegeneration at later stages of Alzheimer's Disease, but it is not clear which role MØ-mediated inflammation may play earlier in the disease pathogenesis. We have previously reported that diffusion MRI (dMRI) is able to detect early myelin abnormalities present in 2-month-old 3xTg-AD (TG) mice; since MØ actively participate in regulating myelination, the goal of this study was to assess quantitatively MØ morphological characteristics and its association with dMRI metrics patterns in 2-month-old 3xTg-AD mice. Our results show that, even at this young age (2-month-old), TG mice have statistically significantly more MØ cells, which are overall smaller and more complex, compared with age-matched normal control mice (NC). Our results also confirm that myelin basic protein is reduced in TG mice, particularly in fimbria (Fi) and cortex. Additionally, MØ morphological characteristics, in both groups, correlate with several dMRI metrics, depending on the brain region examined. For example, the increase in MØ number correlated with higher radial diffusivityD⊥ (r = 0.59, p = 0.008), lower fractional anisotropy (FA) (r = −0.47, p = 0.03), and lower kurtosis fractional anisotropy (KFA) (r = −0.55, p = 0.01) in the CC. Furthermore, smaller MØ cells correlate with higher axial diffusivity(D∥) in the HV (r = 0.49, p = 0.03) and Sub (r = 0.57, p = 0.01). Our findings demonstrate, for the first time, that MØ proliferation/activation are a common and widespread feature in 2-month-old 3xTg-AD mice and suggest that dMRI measures are sensitive to these MØ alterations, which are associated in this model with myelin dysfunction and microstructural integrity abnormalities.

The effects of cytomegalovirus on brain structure following sport-related concussion.

The neurotrophic herpes virus cytomegalovirus is a known cause of neuropathology in utero and in immunocompromised populations. Cytomegalovirus is reactivated by stress and inflammation, possibly explaining the emerging evidence linking it to subtle brain changes in the context of more minor disturbances of immune function. Even mild forms of traumatic brain injury, including sport-related concussion, are major physiological stressors that produce neuroinflammation. In theory, concussion could predispose to the reactivation of cytomegalovirus and amplify the effects of physical injury on brain structure. However, to our knowledge this hypothesis remains untested. This study evaluated the effect of cytomegalovirus serostatus on white and grey matter structure in a prospective study of athletes with concussion and matched contact-sport controls. Athletes who sustained concussion (n = 88) completed MRI at 1, 8, 15 and 45 days post-injury; matched uninjured athletes (n = 73) completed similar visits. Cytomegalovirus serostatus was determined by measuring serum IgG antibodies (n = 30 concussed athletes and n = 21 controls were seropositive). Inverse probability of treatment weighting was used to adjust for confounding factors between athletes with and without cytomegalovirus. White matter microstructure was assessed using diffusion kurtosis imaging metrics in regions previously shown to be sensitive to concussion. T1-weighted images were used to quantify mean cortical thickness and total surface area. Concussion-related symptoms, psychological distress, and serum concentration of C-reactive protein at 1 day post-injury were included as exploratory outcomes. Planned contrasts compared the effects of cytomegalovirus seropositivity in athletes with concussion and controls, separately. There was a significant effect of cytomegalovirus on axial and radial kurtosis in athletes with concussion but not controls. Cytomegalovirus positive athletes with concussion showed greater axial (P = 0.007, d = 0.44) and radial (P = 0.010, d = 0.41) kurtosis than cytomegalovirus negative athletes with concussion. Similarly, there was a significant association of cytomegalovirus with cortical thickness in athletes with concussion but not controls. Cytomegalovirus positive athletes with concussion had reduced mean cortical thickness of the right hemisphere (P = 0.009, d = 0.42) compared with cytomegalovirus negative athletes with concussion and showed a similar trend for the left hemisphere (P = 0.036, d = 0.33). There was no significant effect of cytomegalovirus on kurtosis fractional anisotropy, surface area, symptoms and C-reactive protein. The results raise the possibility that cytomegalovirus infection contributes to structural brain abnormalities in the aftermath of concussion perhaps via an amplification of concussion-associated neuroinflammation. More work is needed to identify the biological pathways underlying this process and to clarify the clinical relevance of this putative viral effect.

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

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. 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). 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. 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.

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. 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). 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%). 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.

Diffusion kurtosis imaging and diffusion tensor imaging parameters applied to white matter and gray matter of patients with anti-N-methyl-D-aspartate receptor encephalitis.

To compare parameters of diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) to evaluate which can better describe the microstructural changes of anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis patients and to characterize the non-Gaussian diffusion patterns of the whole brain and their correlation with neuropsychological impairments in these patients. DTI and DKI parameters were measured in 57 patients with anti-NMDAR encephalitis and 42 healthy controls. Voxel-based analysis was used to evaluate group differences between white matter and gray matter separately. The modified Rankin Scale (mRS) was used to evaluate the severity of the neurofunctional recovery of patients, the Montreal Cognitive Assessment (MoCA) was used to assess global cognitive performance, and the Hamilton Depression Scale (HAMD) and fatigue severity scale (FSS) were used to evaluate depressive and fatigue states. Patients with anti-NMDAR encephalitis showed significantly decreased radial kurtosis (RK) in the right extranucleus in white matter (P < 0.001) and notably decreased kurtosis fractional anisotropy (KFA) in the right precuneus, the right superior parietal gyrus (SPG), the left precuneus, left middle occipital gyrus, and left superior occipital gyrus in gray matter (P < 0.001). Gray matter regions with decreased KFA overlapped with those with decreased RK in the left middle temporal gyrus, superior temporal gyrus (STG), supramarginal gyrus (SMG), postcentral gyrus (POCG), inferior parietal but supramarginal gyrus, angular gyrus (IPL) and angular gyrus (ANG) (P < 0.001). The KFA and RK in the left ANG, IPL and POCG correlated positively with MoCA scores. KFA and RK in the left ANG, IPL, POCG and SMG correlated negatively with mRS scores. KFA in the left precuneus and right SPG as well as RK in the left STG correlated negatively with mRS scores. No significant correlation between KFA and RK in the abnormal brain regions and HAMD and FSS scores was found. The microstructural changes in gray matter were much more extensive than those in white matter in patients with anti-NMDAR encephalitis. The brain damage reflected by DKI parameters, which have higher sensitivity than parameters of DTI, correlated with cognitive impairment and the severity of the neurofunctional recovery.

Characterisation of brain microstructural alterations in children with obstructive sleep apnea syndrome using diffusion kurtosis imaging.

Obstructive sleep apnea (OSA) is a common chronic sleep-related breathing disorder in children. Previous studies showed widespread alterations in white matter (WM) in children with OSA mainly by using diffusion tensor imaging (DTI), while diffusional kurtosis imaging (DKI) extended DTI and exhibited improved sensitivity in detecting developmental and pathological changes in neural tissues. Therefore, we conducted whole-brain DTI and DKI analyses and compared the differences in kurtosis and diffusion parameters within the skeleton between 41 children with OSA and 32 healthy children. Between-group differences were evaluated by tract-based spatial statistics (TBSS) analysis (p < 0.05, TFCE corrected), and partial correlations between DKI metrics and sleep parameters were assessed considering age and gender as covariates. Compared with the controls, children with OSA showed significantly decreased kurtosis fractional anisotropy (KFA) mainly in white matter regions with a complex fibre arrangement including the posterior corona radiate (PCR), superior longitudinal fasciculus (SLF), and inferior fronto-occipital fasciculus (IFOF), while decreased FA in white matter regions with a coherent fibre arrangement including the posterior limb of internal capsule (PLIC), anterior thalamic radiation (ATR), and corpus callosum (CC). Notably, the receiver operating characteristic (ROC) curve analysis demonstrated the KFA value in complex tissue regions significantly (p < 0.001) differentiated children with OSA from the controls. In addition, the KFA value in the left PCR, SLF, and IFOF showed significant partial correlations to the sleep parameters for children with OSA. Combining DKI derived kurtosis and diffusion parameters can provide complementary neuroimaging biomarkers for assessing white matter alterations, and reveal pathological changes and monitor disease progression in paediatric OSA.

The microstructural abnormalities of cingulum was related to patients with mild cognitive impairment: a diffusion kurtosis imaging study

ObjectiveOur study aimed to investigate the correlations between microstructural changes of cingulum and patients with mild cognitive impairment (MCI) by diffusion kurtosis imaging (DKI) technique.MethodA total of 104 patients with cerebral small vessel diseases (cSVD) were retrospectively enrolled in this study. According to Montreal Cognitive Assessment Scale (MoCA) scores, these patients were divided into MCI group (n = 59) and non-MCI group (n = 45). The general clinical data was collected and analyzed. The regions of interests (ROIs) were selected for investigation in cingulum. The values of DKI parameters were measured in each ROI and compared between the two groups, the correlations between DKI parameters and MoCA scores were examined.ResultsCompared to non-MCI group, MCI patients had more severe white matter hyperintensities (WMHs) (P = 0.038) and lower MoCA scores (P < 0.01). MCI patients showed significantly decreased fractional anisotropy (FA), axial kurtosis (AK), mean kurtosis (MK), radial kurtosis (RK), and kurtosis fractional anisotropy (KFA) in the left cingulum in the cingulated cortex (CgC) region (all P < 0.0125). In the left CgC region, FA, AK, MK, RK, and KFA were positively correlated with MoCA scores (r = 0.348, 0.409, 0.310, 0.441, 0.422, all P < 0.001). Meanwhile, FA, AK, MK, RK, and KFA were also positively correlated with MoCA scores (r = 0.338, 0.352, 0.289, 0.380, 0.370, all P < 0.001) in the right CgC region.ConclusionDKI technique could be used to explore the microstructural changes of cingulum in MCI patients and DKI-derived parameters might be feasible to evaluate MCI patients.

Classification of cognitively normal controls, mild cognitive impairment and Alzheimer’s disease using transfer learning approach

Automated classification of dementia stage using imaging will be useful for clinical diagnosis and the classification accuracy will be biased for highly imbalanced samples in each class. Hence, we propose a novel approach using transfer learning-based structural significance (TLSS) for the classification of cognitively normal controls (CN), mild cognitive impairment (MCI) and Alzheimer’s disease (AD) patients based on white matter Gaussian diffusion (tensor) indices and non-Gaussian diffusion (kurtosis) indices. The structural T1-weighted magnetic resonance imaging and diffusion images were taken from ADNI dataset with 44 CN, 84 MCI and 22 AD patients. We estimate the regional Gaussian diffusion indices such as tensor fractional anisotropy (TFA) and mean diffusivity (TMD) as well as non-Gaussian diffusion indices such as kurtosis fractional anisotropy (KFA) and kurtosis mean diffusivity (KMD) in white matter regions. Further, we build transfer learning model using various balanced classifiers with structural expansion reduction (SER) and structure transfer using threshold (STT) and ensemble of majority voting of both SER and STT algorithms. We build two models by training the source model using kurtosis indices, refine the model on target tensor indices and vice versa. Transfer learning model using balanced random forest classifier was able to classify and predict all the groups with an overall accuracy about 0.79 using ensemble of SER and STT forests rather than individual algorithms (SER and STT). Our results conclude that the proposed model using kurtosis indices as source model classified and predicted with accuracies of 0.96, 0.72 and 0.7 in classifying CN vs AD, CN vs MCI and AD vs MCI respectively. To conclude, the proposed approach has improved the classification accuracy and its potential applicability for imbalanced data sample datasets.

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

ObjectivesThis 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 MethodsA 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. ResultsThe 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. ConclusionOur 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.

Cross-sectional analysis of whole-brain microstructural changes in adult patients with bipolar and unipolar depression by diffusion kurtosis imaging.

More than half of the bipolar depression (BD) subjects are misdiagnosed as unipolar depression (UD) due to lack of objective diagnostic criteria. We aimed to identify microstructural neuronal changes differentiating BD from UD groups using diffusion kurtosis imaging (DKI). The objective of the study is to identify an objective neuro-imaging marker to differentiate BD from UD. A prospective, cross-sectional study included total of 62 subjects with diagnosis of bipolar depression (n = 21), unipolar depression (n = 21), and healthy controls (n = 20). All subjects underwent diffusion-weighted imaging (b = 0,1000,2000) of the whole brain on 3-Tesla MR scanner. DKI data was analyzed using 189 region whole-brain atlas. Eight diffusion and kurtosis metrics including mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), fractional anisotropy (FA), mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), and kurtosis fractional anisotropy (FKA) were measured against these 189 regions. Principle component analysis (PCA) was utilized to identify the most significant regions of the brain. ANOVA with post hoc tests was used for analyzing these regions. BD group showed increased MD, RD, decreased AK at the left amygdala and decreased MK and RK at the right hemi-cerebellum. UD group showed increased MK and RK at the right external capsule; and increased AK, MK, and RK at the right amygdala. The right and left amygdala, right external capsule, and right hemi-cerebellum showed microstructural abnormalities capable of differentiating BD and UD groups. Diffusion imaging especially DKI can aid in management of depression patients.

Evaluation of White Matter Microstructural Alterations in Patients with Post-Stroke Cognitive Impairment at the Sub-Acute Stage.

PurposeTo investigate white matter alterations in post-stroke cognitive impairment (PSCI) patients at the subacute stage employing diffusion kurtosis and tensor imaging.MethodsThirty PSCI patients at the subacute phase and 30 healthy controls (HC) underwent diffusion kurtosis imaging (DKI) scans and neuropsychological assessments. Based on the tract-based spatial statistics and atlas-based ROI analysis, fractional anisotropy (FA), mean diffusivity (MD), mean kurtosis (MK), kurtosis fractional anisotropy (KFA), axial kurtosis (AK), and radial kurtosis (RK) were compared in specific white matter fiber bundles between the groups (with family-wise error correction). Adjusting for age and gender, a partial correlation was conducted between neurocognitive assessments and DKI metrics in the PSCI group.ResultsIn comparison with the HC, PSCI patients significantly showed decreased MK, RK, and FA and increased MD values in the genu of corpus callosum, anterior limb internal capsule, and left superior corona radiata. In addition, DKI detected more white matter region changes in MK (31/48), KFA (40/48), and RK (25/48) than DTI with FA (28/48) and MD (21/48), which primarily consisted of the right cingulum, right superior longitudinal fasciculus, and left posterior limb of internal capsule. In the left anterior limb of internal capsule, MK and RK values were significantly negatively correlated with TMT-B (r = −0.435 and −0.414, P < 0.05), and KFA values (r = −0.385, P < 0.05) of corpus callosum negatively associated with TMT-B.ConclusionCombing DTI, DKI, and neuropsychological tests, we found extensive damaged white matter microstructure and poor execution performance in subacute PSCI patients. DKI could detect more subtle white matter changes than DTI metrics. Our findings provide added information for exploring the mechanisms of PSCI and conducting cognitive rehabilitation in the subacute stage.

White Matter Changes Following Chronic Restraint Stress and Neuromodulation: A Diffusion Magnetic Resonance Imaging Study in Young Male Rats

BackgroundRepetitive transcranial magnetic stimulation (rTMS), a noninvasive neuromodulation technique, is an effective treatment for depression. However, few studies have used diffusion magnetic resonance imaging to investigate the longitudinal effects of rTMS on the abnormal brain white matter (WM) described in depression. MethodsIn this study, we acquired diffusion magnetic resonance imaging from young adult male Sprague Dawley rats to investigate 1) the longitudinal effects of 10- and 1-Hz low-intensity rTMS (LI-rTMS) in healthy animals; 2) the effect of chronic restraint stress (CRS), an animal model of depression; and 3) the effect of 10 Hz LI-rTMS in CRS animals. Diffusion magnetic resonance imaging data were analyzed using tract-based spatial statistics and fixel-based analysis. ResultsSimilar changes in diffusion and kurtosis fractional anisotropy were induced by 10- and 1-Hz stimulation in healthy animals, although changes induced by 10-Hz stimulation were detected earlier than those following 1-Hz stimulation. Additionally, 10-Hz stimulation increased axial and mean kurtosis within the external capsule, suggesting that the two protocols may act via different underlying mechanisms. Brain maturation–related changes in WM, such as increased corpus callosum, fimbria, and external and internal capsule fiber cross-section, were compromised in CRS animals compared with healthy control animals and were rescued by 10-Hz LI-rTMS. Immunohistochemistry revealed increased myelination within the corpus callosum in LI-rTMS–treated CRS animals compared with those that received sham or no stimulation. ConclusionsOverall, decreased WM connectivity and integrity in the CRS model corroborate findings in patients experiencing depression with high anxiety, and the observed LI-rTMS–induced effects on WM structure suggest that LI-rTMS might rescue abnormal WM by increasing myelination.