No support for structural brain differences in adults with developmental coordination disorder: a fixel-based analysis.

Comparison of panic disorder with and without comorbid major depression by using brain structural magnetic resonance imaging

Obsessive-compulsive disorder (OCD) is one of the most debilitating psychiatric disorders, with some speculating that a reason for difficulty in its treatment might be its coexistence with autism spectrum. We investigated the tendency for autistic spectrum disorders (ASD) in patients with OCD from a neuroimaging point of view using voxel-based morphometry. We acquired T1-weighted images from 20 patients with OCD and 30 healthy controls and investigated the difference in regional volume between the groups as well as the correlation between Autism-Spectrum Quotient (AQ) scores and regional cerebral volumes of patients with OCD. Volumes in the bilateral middle frontal gyri were significantly decreased in patients with OCD compared to controls. Correlational analysis showed significant positive correlations between AQ scores and regional gray matter (GM) volumes in the left dorsolateral prefrontal cortex (DLPFC) and left amygdala. Furthermore, GM volumes of these regions were positively correlated with each other. The positive correlation of ASD traits in patients with OCD with regional GM volumes in the left DLPFC and amygdala could reflect the heterogeneity of patient symptoms. Our results suggest that differences in GM volume might allow classification of patients with OCD for appropriate therapy based on their particular traits.

Currently, there is still a lack of valuable neuroimaging markers to assess the clinical severity of stroke patients with small artery occlusion (SAO). Quantitative susceptibility mapping (QSM) is a quantitative processing method for neuroradiological diagnostics. Gray matter (GM) volume changes in stroke patients are also proved to be associated with neurological deficits. This study aims to explore the predictive value of QSM and GM volume in neurological deficits of patients with SAO. As neurological deficits, the National Institutes of Health Stroke Scale (NIHSS) was used. Sixty-six SAO participants within 24h of first onset were enrolled and divided into mild and moderate groups based on NIHSS. QSM values of infarct area and GM volume were calculated from magnetic resonance imaging (MRI) data. Two-sample t-tests were used to compare differences in QSM value and GM volume between the two groups, and the diagnostic efficacy of the combination of QSM value and GM volume was evaluated. The results revealed both the QSM value and GM volume within the infarct area of the moderate group were lower compared to the mild group. Moderate group exhibited lower GM volume in some specific gyrus compared with mild group in the case of voxel-wise GM volume on whole-brain voxel level. The support vector machine (SVM) classifier's analysis showed a high power for the combination of QSM value, GM volume within the infarct area, and voxel-wise GM volume. Our research first reported the combination of QSM value, GM volume within the infarct area, and voxel-wise GM volume could be used to predict neurological impairment of patients with SAO, which provides new insights for further understanding the SAO stroke.

Larger gray matter (GM) volume in healthy children is correlated with higher IQ. Children with neurofibromatosis type 1 (NF1) have larger brains, their magnetic resonance images frequently show T2-weighted hyperintensities, and their IQs are lower. To confirm the hypotheses that (1) children with NF1 have larger GM and white matter volumes, (2) the greatest volume differences are in the frontal and parietal regions and in children with NF1 with hyperintensities, and (3) GM volume is inversely related to IQ in children with NF1. Wechsler Intelligence Scale for Children-Third Edition IQ testing and measurement of cerebral volumes and hyperintensities in brain magnetic resonance images were performed on 36 children with NF1 and on 36 matched relatives who served as control subjects. Gray matter and white matter volumes were significantly larger in children with NF1. The greatest difference was observed in cerebral white matter volume, predominantly in the frontal lobes, whereas the greatest difference in GM volume was in the temporal, parietal, and occipital regions. In controls, IQ was significantly related to GM volume, but in children with NF1, IQ was not inversely associated with GM volume, although IQs of children with NF1 were significantly lower. Children with NF1 do not have the normal relationship between GM volume and IQ. Larger GM volume in the posterior brain regions and larger white matter volumes in the frontal brain regions contribute to the larger brain volume in children with NF1.

Type 1 diabetes mellitus (T1DM) affects the development of cognitive function in children, which may be due to deficits in brain structures or functions. It is unclear whether children with T1DM experience alterations in the gray matter (GM) structure at the initial stages of the disease. This study investigated GM structure alterations in children with newly diagnosed T1DM. Based on 3D T1-weighted MR images, we investigated the gray matter volume (GMV) of 35 newly diagnosed T1DM children and 35 age- and sex-matched healthy controls using voxel-based morphometry. The brain regions with significant differences in GMV between the newly diagnosed T1DM children and the controls were extracted and the correlation with clinical data was assessed. Compared with the control group, children with newly diagnosed T1DM had a lower GMV in the right inferior and middle temporal gyri, right lingual gyrus, and left superior frontal gyrus. In T1DM subjects, the GMV of the right middle temporal gyrus was positively correlated with IQ but was negatively correlated with HbA1c. Our findings provide compelling evidence that GM abnormalities occur during early disease stages in T1DM children, which may be a potential neurobiological mechanism underlying cognitive deficits. Using an efficient method to analyze gray matter changes in T1DM is very important. The anterior, posterior, and temporal brain regions are susceptible to T1DM in children. Recent glucose variability may affect regional gray matter volume in children with newly diagnosed T1DM. Structural changes were documented in the gray matter of the brain even at the early stages of the disease in children with T1DM.

Introduction: Adolescent-onset cannabis use is rising in the era of marijuana legalization. Recent imaging studies have identified neuroanatomical differences between adult cannabis users and controls that are more prominent in early-onset users. Other studies point to sex-dependent effects of cannabis. Methods: A systematic review following PRISMA guidelines and subsequent effect-size seed-based d mapping (SDM) meta-analyses were conducted to investigate relationships between age (across the 12-to-21-year-old developmental window), sex, and gray matter volume (GMV) differences between cannabis using (CU) and typically developing (TD) youth. Results: Our search identified 1326 citations, 24 of which were included in a qualitative analysis. A total of 6 whole-brain voxel-based morphometry (VBM) studies comparing regional GMV between 357 CU (mean [SD] age = 16.68 [1.28]; 71% male) and 404 TD (mean [SD] age = 16.77 [1.36]; 63% male) youth were included in the SDM-meta-analysis. Meta-analysis of whole-brain VBM studies identified no regions showing significant GMV difference between CU and TD youth. Meta-regressions showed divergent effects of age and sex on cortical GMV differences in CU vs. TD youth. Age effects were seen in the superior temporal gyrus (STG), with older-aged CU youth showing decreased and younger-aged CU youth showing increased STG GMV compared to age-matched TD youth. Parallel findings in the STG were also observed in relation to duration of CU (years) in supplemental meta-regressions. Regarding sex effects, a higher proportion of females in studies was associated with increased GMV in the middle occipital gyrus in CU vs. TD youth. Conclusions: These findings suggest that GMV differences between CU and TD youth, if present, are subtle, and may vary as a function of age, cumulative cannabis exposure, and sex in young people. Whether age- and sex-related GMV differences are attributable to common predispositional factors, cannabis-induced neuroadaptive changes, or both warrant further investigation.

Hallucinations are considered one of the primary symptoms of psychosis; however, their neural basis remains unclear. Voxel-based morphometry (VBM)1 studies have associated hallucinations with gray matter (GM) volume reduction in the superior temporal gyrus in schizophrenia.2 Although hallucinations are associated with brain connectivity,3 few studies have investigated their relationship with white matter (WM) volume. Moreover, these studies have shown inconsistent results.4, 5 The chronicity of illness and long-term medications for schizophrenia may limit the interpretation of previous findings.2 Thus, hallucination studies in clinical high risk for psychosis (CHR) and first-episode psychosis (FEP) are required, with minimal effects of chronicity of illness and medication. However, no VBM study has examined the relationship between hallucinations and WM volume in CHR and FEP. Therefore, we aimed to investigate the regional GM and WM volumes associated with hallucinations in CHR and FEP. We enrolled 57 individuals with CHR, 50 individuals with FEP, and 33 healthy controls (HCs). The Comprehensive Assessment of At-Risk Mental States-Japanese version6 was used to confirm whether ultra-high risk criteria7 were met. Table S1 summarizes the demographic and clinical data of the patients. Hallucination severity was assessed using the Positive and Negative Syndrome Scale (PANSS)8 P3 score. Fig. S1 shows the distribution of the severity of hallucinations. Some of those with a PANSS P3 score of 3 or higher were classified as having CHR because of the low frequency and duration of hallucinations. Magnetic resonance imaging (MRI) data were acquired with a 1.5-T Philips scanner. We examined the association of GM and WM volume with hallucination severity in the group that combined patients with CHR and FEP (CHR/FEP combined group) and performed group comparisons of GM and WM volume between the CHR/FEP combined and HC groups. Age, sex, and intracranial volume were entered as nuisance covariates for each analysis. VBM analysis was conducted using DARTEL9 in SPM12 (https://www.fil.ion.ucl.ac.uk/spm/software/spm12/) with standard smoothing of 8-mm full width at half maximum (FWHM). The initial statistical threshold was set at P < 0.001, uncorrected at the voxel level. The extent threshold for cluster size was set based on the expected number of voxels per cluster provided by SPM. Familywise error (FWE) correction at the cluster level (P < 0.05) was applied to identify significant clusters. Appendix S1 provides detailed information on these methods. This study was performed in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of Tohoku University Graduate School of Medicine and Tohoku University Hospital. Written informed consent was obtained from participants aged 18 years or older and from the parents of those under 18 years of age, with written assent from the participants. The anonymity of participants was preserved. WM volume was not significantly correlated with hallucination severity in the CHR/FEP combined group after FWE correction at the cluster level. Reanalysis with 15-mm or 20-mm FWHM filtering did not show significant associations. Additionally, there was no significant difference in the GM and WM volumes between the CHR/FEP combined and HC groups. No regional GM volume abnormalities were significantly correlated with hallucination severity in the CHR/FEP combined group. Appendix S1, Figs. S2–S5, and Tables S2–S5 provide uncorrected results and detailed information regarding these results. To the best of our knowledge, this is the first VBM study to investigate WM volume related to hallucinations in CHR and FEP. We found no significant correlation between WM volume and hallucination severity. In contrast to previous studies in schizophrenia,2, 4, 5 this study examined the brain volume association of hallucinations in CHR and FEP. CHR and FEP are heterogeneous groups in the early stages of mental illness and do not necessarily convert to schizophrenia. Our results indicate that brain disturbances involved in hallucinations in CHR and FEP may be more subtle and/or inconsistent with those in schizophrenia. Diffusion tensor imaging, a neuroimaging method applied to CHR,10 may be suitable for examining structural abnormalities in the development of hallucinations. This study has some limitations. First, information regarding hallucinations is not detailed. Second, the cross-sectional design limited the interpretation of our findings. Third, we used an MRI scanner with a lower field strength than that of recent studies.4 Fourth, there were significant age differences between the groups. Fifth, automatic quality assurance for MRI scans was not performed. In conclusion, advanced neuroimaging studies are needed to reveal the mechanism of hallucinations. This work was supported by JSPS KAKENHI (grant number 18K07586). We thank the participants, staff of the SAFE clinic, and radiological technologists. The authors declare no conflicts of interest. Appendix S1. Supporting information Figure S1. Distribution of hallucination severity. CHR, clinical high risk for psychosis; FEP, first-episode psychosis; PANSS, Positive and Negative Syndrome Scale. Figure S2. Brain regions with lower gray matter volume in the CHR/FEP group compared to the HC group. Statistical threshold was set at P < 0.001, uncorrected at the voxel level. The threshold extent for cluster size was set to k = 117 based on the expected number of voxels per cluster provided by SPM. The full width at half maximum was set to 8-mm. CHR, clinical high risk for psychosis; FEP, first-episode psychosis; HC, healthy controls; SPM, Statistical Parametric Mapping Figure S3. Brain regions with lower white matter volume in the CHR/FEP group compared to the HC group. Statistical threshold was set at P < 0.001, uncorrected at the voxel level. The threshold extent for cluster size was set to k = 129 based on the expected number of voxels per cluster provided by SPM. The full width at half maximum was set to 8-mm. CHR, clinical high risk for psychosis; FEP, first-episode psychosis; HC, healthy controls; SPM, Statistical Parametric Mapping Figure S4. Positive correlation between gray matter volume and hallucination severity in the patients at clinical high risk for psychosis. Statistical threshold was set at P < 0.001, uncorrected at the voxel level. The threshold extent for cluster size was set to k = 101 based on the expected number of voxels per cluster provided by the SPM. The full width at half maximum was set to 8-mm. SPM, Statistical Parametric Mapping Figure S5. Negative correlation between white matter volume and hallucination severity in the patients at clinical high risk for psychosis. Statistical threshold was set at P < 0.001, uncorrected at the voxel level. The threshold extent for cluster size was set to k = 121 based on the expected number of voxels per cluster provided by the SPM. The full width at half maximum was set to 8-mm. SPM, Statistical Parametric Mapping Table S1. Demographic and clinical characteristics of the participants. †Educational level, CP-equivalent dose on MRI scan, PANSS positive, PANSS negative, PANSS general, PANSS total, PANSS P3: hallucinatory behavior, and days from enrollment to MRI scan were analyzed using the t-test. Age and intracranial volume were analyzed using one-way analysis of variance. Sex and antipsychotic use were analyzed using the chi-squared test. Significant results are shown in bold. CHR, clinical high risk for psychosis; CP-equivalent, chlorpromazine equivalent; FEP, first-episode psychosis; HC, healthy controls; PANSS, Positive and Negative Syndrome Scale. Table S2. Between-group comparison of regional gray matter volume. CHR/FEP < HC (extent threshold: 117 voxels). † Uncorrected p-value at voxel level. ‡ familywise error-corrected p-value at the cluster level. k, cluster size at P < 0.001 (uncorrected); CHR, clinical high risk for psychosis; FEP, first-episode psychosis; HC, healthy controls; L/R, left/right hemisphere; MNI, Montreal Neurological Institute. The extent threshold for cluster size was set based on the expected number of voxels per cluster provided by the SPM. The full width at half maximum was set to 8-mm. Table S3. Between group comparison of regional white matter volume. CHR/FEP < HC (extent threshold: 129 voxels). † Uncorrected P-value at voxel level. ‡ familywise error-corrected p-value at the cluster level. k, cluster size at P < 0.001 (uncorrected); CHR, clinical high risk for psychosis; FEP, first-episode psychosis; HC, healthy controls; L/R, left/right hemisphere; MNI, Montreal Neurological Institute. The extent threshold for cluster size was set based on the expected number of voxels per cluster provided by the SPM. The full width at half maximum was set to 8-mm. Table S4. Correlation between gray matter volume and hallucination severity in the patients with CHR. Positive correlation (extent threshold: 101 voxels). † Uncorrected p-value at voxel level. ‡ familywise error-corrected p-value at the cluster level. k, cluster size at P < 0.001 (uncorrected); CHR, clinical high risk for psychosis; L/R, left/right hemisphere; MNI, Montreal Neurological Institute. The extent threshold for cluster size was set based on the expected number of voxels per cluster provided by the SPM. The full width at half maximum was set to 8-mm. Table S5. Correlation between white matter volume and hallucination severity in the patients with CHR. Negative correlation (extent threshold: 121 voxels). † Uncorrected p-value at voxel level. ‡ familywise error-corrected p-value at the cluster level. k, cluster size at P < 0.001 (uncorrected); CHR, clinical high risk for psychosis; L/R, left/right hemisphere; MNI, Montreal Neurological Institute. The extent threshold for cluster size was set based on the expected number of voxels per cluster provided by the SPM. The full width at half maximum was set to 8-mm. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Structural brain abnormalities correlate with clinical features in patients with drug-naïve OCD: A DARTEL-enhanced voxel-based morphometry study

PurposeTo investigate the concurrent brain structural and functional alterations related to cognition in patients with cerebral small vessel disease (CSVD).MethodsThirty normal controls and 65 CSVD patients, including 33 patients with mild cognitive impairment and 32 patients with no cognitive impairment were included. Structural and resting-state functional MRI measures, including gray matter volume (GMV) and white matter volume (WMV) using voxel-based morphometry (VBM) analysis and amplitude of low-frequency fluctuation (ALFF), were obtained and compared among the three groups. Associations between cognitive scores and ALFF/VBM coupling in the co-altered regions were investigated in CSVD groups.ResultsMultiple brain regions showed significant differences in GMV and WMV among the three groups (P < 0.01). Abnormal ALFF among the three groups was identified in the left putamen, Rolandic operculum, fusiform gyrus, caudate, parahippocampal gyrus, insula, middle cingulum, bilateral lingual gyrus, and right frontal lobe (P < 0.01). Importantly, a decrease in VBM and increase in ALFF in the left parahippocampal gyrus, caudate and Rolandic operculum, a reduction of the WMV and ALFF in the right superior frontal lobe, and a united rise of GMV and ALFF in the left caudate were detected in CSVD groups. In addition, abnormal ALFF/VBM coupling was significantly related to multiple cognitive assessments.ConclusionThe study indicated a reversed pattern of the brain structural deficits and functional activation in the left parahippocampal gyrus, caudate, and Rolandic operculum, suggesting structure–function decoupling in CSVD groups. These might help further understand the pathophysiological mechanism of CSVD.

Gray matter volume differences and the effects of smoking on gray matter in schizophrenia

Very-late-onset schizophrenia-like psychosis (VLOSLP) is associated with significant burden. Its clinical importance is increasing as the global population of older adults rises, yet owing to limited research in this population, the neurobiological underpinnings of VLOSP remain insufficiently clarified. Here we address this knowledge gap using novel morphometry techniques to investigate grey matter volume (GMV) differences between VLOSLP and healthy older adults, and their correlations with neuropsychological scores. In this cross-sectional study, we investigated whole-brain GMV differences between 35 individuals with VLOSLP (mean age 76.7, 26 female) and 36 healthy controls (mean age 75.7, 27 female) using whole-brain voxel-based morphometry (VBM) and supplementary source-based morphometry (SBM) on high resolution 3D T1-weighted MRI images. Additionally, we investigated relationships between GMV differences and cognitive function assessed with an extensive neuropsychological battery. VBM showed lower GMV in the thalamus, left inferior frontal gyrus and left insula in patients with VLOSLP compared to healthy controls. SBM revealed lower thalamo-temporal GMV in patients with VLOSLP. Processing speed, selective attention, mental flexibility, working memory, verbal memory, semantic fluency and confrontation naming were impaired in patients with VLOSLP. Correlations between thalamic volumes and memory function were significant within the group of individuals with VLOSLP, whereas no significant associations remained in the healthy controls. Lower GMV in the thalamus and fronto-temporal regions may be part of the underlying neurobiology of VLOSLP, with lower thalamic GMV contributing to memory impairment in the disorder.

This thesis aimed to investigate the feasibility of two diffusion imaging techniques, Diffusion Tensor Imaging (DTI) and Diffusion Kurtosis Imaging (DKI), on detecting subtle physiological or pathological microstructural changes in normal-appearing neural tissues of human central nervous system. &#13;\n At first, ten patients with neuromyelitis optica (NMO) and twelve age- and gender-matched healthy subjects were recruited. DTI-derived indices including fractional anisotropy (FA), mean diffusivity (MD), axial and radial diffusivities were quantified in the lateral and dorsal columns of cervical spinal cord. Based on the regions of interest (ROIs) measurement, NMO patients showed reduced FA, increased MD and radial diffusivity compared to control subjects, while axial diffusivity did not show any significant difference. The three former DTI metrics also showed significant correlations with disability scores, and especially FA was found to be sensitive to mild NMO. Our results show that DTI-derived indices can quantitatively assess the white matter (WM) abnormalities with seemingly normal appearance in conventional MRI, and are associated with the level of clinical disability, suggesting that DTI may have great potential as a useful diagnostic tool in the clinical setting.&#13;\n DKI is an extension of conventional DTI to probe the non-Gaussian diffusion property in biological tissues. Besides the four conventional DTI-derived metrics, DKI also provide three additional kurtosis metrics (mean kurtosis (MK), axial and radial kurtosis). In the second study, ROI-based analysis was used to characterize age-related microstructural changes in WM, cortical and subcortical gray matter (GM) of 27 healthy adults (21~59 yrs). Though the volumes of GM and WM were still preserved, DTI-derived metrics can detect the subtle changes in WM and GM. Meanwhile, MK and radial kurtosis significantly increased in both caudate nucleus and putamen while Thalamus showed little aging effect in the diffusivity and kurtosis metrics but significantly decreased only in FA. Our results demonstrated that DKI is sensitive to detect the age-related alterations in neural microstructures at the stage of early aging.&#13;\n In addition, DKI has been applied to detect the pathological changes in the normal-appearing neural tissues of 18 patients with multiple sclerosis (MS), compared to 22 healthy controls. Diffuse WM abnormalities have been observed extensively in the brain, revealed by DKI-derived metrics. Though the volumetric and voxel-wise analysis revealed no significant changes in the volume of cortical GM, decreased FA and kurtoses with increased diffusivities in MS group were sensitive to disclose the subtle alterations in global and regional cortical GM tissues. Significant correlations have been found between FA in the global, frontal and temporal cortical GM in relapsing-remitting MS patients and their disability scores, suggesting FA as an important biomarker to monitor the disease progress in cortical GM. Moreover, elevated kurtosis indices in MS patients did not correlate with diffusivities in caudate nucleus, putamen and thalamus, suggesting these metrics may be vulnerable to different pathologic aspects of the disease.&#13;\n In conclusion, DKI is sensitive to neural alterations during normal aging and in MS pathologies, and can provide complementary information to conventional MRI and DTI.

Esophageal cancer (EC), a highly prevalent malignant cancer, is frequently accompanied by cancer-related cognitive impairment (CRCI), yet its underlying neural mechanisms remain poorly understood. This study integrated inflammatory biomarkers and nutritional index with structural magnetic resonance imaging (MRI) to investigate the characteristics of brain structural alterations in EC patients and their association with systemic inflammation and nutritional metabolism. A total of 49 treatment-naive EC patients and 31 healthy controls (HC) were enrolled. High-resolution T1-weighted MRI scans and peripheral blood indices (including platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR)) were collected. Voxel-based morphometry (VBM) was employed to assess gray matter (GM) volume differences, and correlations between GM volume, inflammatory markers and nutritional index were analyzed. Results demonstrated that the EC group exhibited significantly elevated monocyte counts and PLR, alongside reduced lymphocytes, albumin levels, and prognostic nutritional index compared to HC (p < 0.05). Structural MRI revealed significantly increased GM volume in bilateral occipital lobes, basal ganglia, pre-/postcentral gyri, and the right temporal lobe in EC patients, and decreased GM volume in bilateral parahippocampa gyri, amygdala, and cerebellum Posterior Lobe (FDR correction, p < 0.05). Partial correlation analysis indicated a negative association between GM volume in the right basal ganglia and PLR (r = - 0.464, p = 0.005). These findings suggest that brain structural alterations in EC patients may be driven by systemic inflammation and nutritional imbalance, reflecting a dynamic equilibrium between neuroplastic compensation and neuroinflammatory injury. The negative correlation between GM volume and PLR provides neuroimaging evidence for inflammation-mediated CRCI mechanisms, offering novel targets for the development of early intervention strategies.

Secondary changes in the volume of motor-related cortical regions and the relationship with functional recovery during the acute stage after cerebral infarction have not been determined. In the present study, we quantified changes in gray matter (GM) volume in motor-related cortical regions and analyzed their correlations to clinical scores in patients with focal cerebral infarct. Fifteen patients with acute subcortical infarct underwent longitudinal high-resolution structural MRI and clinical assessment 3 times during a 12-week period (weeks 1, 4, and 12). Fourteen age- and sex-matched controls underwent MRI examination. Voxel-based morphometry was used to quantify changes in global GM volume; in addition, relationships between GM volume changes in volumes of interest and clinical scores were analyzed. In patients with cerebral infarction, GM volumes detected by voxel-based morphometry both decreased and increased significantly in diffuse cortical regions during the observation period (P<0.001). GM volumes within volumes of interest decreased significantly in the ipsilateral supplementary motor area and contralateral insula, but they increased in the contralateral supplementary motor area over time (all P<0.017). The changes of GM volumes in the ipsilesional and contralesional supplementary motor area correlated with the changes in the Fugl-Meyer scale scores (ipsilesional, rs=0.52; P=0.048; contralesional, rs=0.74; P=0.002) and Barthel Index (ipsilesional, rs=0.56; P=0.030; contralesional, rs=0.65; P=0.009). These results suggest that secondary GM changes occur in diffuse areas and structural changes in some specific motor-related cortex may inhibit or promote functional recovery after an acute subcortical cerebral infarct.

To investigate the possible covariation of grey matter volume (GMV) and white matter fractional anisotropy in infants with spastic cerebral palsy (CP) and periventricular white matter injury. Thirty-nine infants with spastic CP and 25 typically developing controls underwent structural magnetic resonance imaging and diffusion tensor imaging. Multimodal canonical correlation analysis with joint independent component analysis were used to capture differences in GMV and fractional anisotropy between groups. Correlation analysis was performed between imaging findings and clinical features. Infants with spastic CP showed one joint group-discriminating component (i.e. GMV-fractional anisotropy) associated with regions in the cortico-basal ganglia-thalamo-cortical loop and in the corpus callosum compared to typically developing controls and one modality-specific group-discriminating component (i.e. GMV). Significant negative correlations were found between loadings in certain regions and the motor function score in spastic CP. In infants with spastic CP, covarying GMV-fractional anisotropy and altered GMV in specific regions were implicated in motor dysfunction, which confirmed that simultaneous GMV and fractional anisotropy changes underly motor deficits, but might also extend to sensory, cognitive, or visual dysfunction. These findings also suggest that multimodal fusion analysis allows for a more comprehensive understanding of the relevance between grey and white matter structures and its crucial role in the neuropathological mechanisms of spastic CP.