Fractal Analysis of MRI Data at 7 T: How Much Complex Is the Cerebral Cortex?

The human brain is a highly complex structure, which can be only partially described by conventional metrics derived from magnetic resonance imaging (MRI), such as volume, cortical thickness, and gyrification index. In the last years, the fractal dimension (FD) - a useful quantitative index of fractal geometry - has proven to well express the morphological complexity of the cerebral cortex. However, this complexity is likely higher than that we can observe using MRI scanners with 1.5 T or 3 T field strength. Ultrahigh-field MRI (UHF-MRI) improves imaging of smaller anatomical brain structures by exploring down to a submillimetric spatial resolution with higher signal-to-noise and contrast-to-noise ratios. Accordingly, we hypothesized that UHF-MRI might reveal a higher level of the structural complexity of the cerebral cortex. In this study, using an improved box-counting algorithm, we estimated the FD of the cerebral cortex in six public or private T1-weighted MRI datasets of young healthy subjects (for a total of 87 subjects), acquired at different field strengths (1.5 T, 3 T, and 7 T). Our results showed, for the first time, that MRI-derived FD values of the cerebral cortex imaged at 7 T were significantly higher than those observed at lower field strengths. UHF-MRI provides an anatomical definition not achievable at lower field strengths and can improve unveiling the real structural complexity of the human brain

Prevalence of comorbidities according to predominant phenotype and severity of chronic obstructive pulmonary disease

BACKGROUND: In addition to lung involvement, several other diseases and syndromes coexist in patients with chronic obstructive pulmonary disease (COPD). Our purpose was to investigate the prevalence of idiopathic arterial hypertension (IAH), ischemic heart disease, heart failure, peripheral vascular disease (PVD), diabetes, osteoporosis, and anxious depressive syndrome in a clinical setting of COPD outpatients whose phenotypes (predominant airway disease and predominant emphysema) and severity (mild and severe diseases) were determined by clinical and functional parameters. METHODS: A total of 412 outpatients with COPD were assigned either a predominant airway disease or a predominant emphysema phenotype of mild or severe degree according to predictive models based on pulmonary functions (forced expiratory volume in 1 second/vital capacity; total lung capacity %; functional residual capacity %; and diffusing capacity of lung for carbon monoxide %) and sputum characteristics. Comorbidities were assessed by objective medical records. RESULTS: Eighty-four percent of patients suffered from at least one comorbidity and 75% from at least one cardiovascular comorbidity, with IAH and PVD being the most prevalent ones (62% and 28%, respectively). IAH prevailed significantly in predominant airway disease, osteoporosis prevailed significantly in predominant emphysema, and ischemic heart disease and PVD prevailed in mild COPD. All cardiovascular comorbidities prevailed significantly in predominant airway phenotype of COPD and mild COPD severity. CONCLUSION: Specific comorbidities prevail in different phenotypes of COPD; this fact may be relevant to identify patients at risk for specific, phenotype-related comorbidities. The highest prevalence of comorbidities in patients with mild disease indicates that these patients should be investigated for coexisting diseases or syndromes even in the less severe, pauci-symptomatic stages of COPD. The simple method employed to phenotype and score COPD allows these results to be translated easily into daily clinical practice

Regional Distribution and Clinical Correlates of White Matter Structural Damage in Huntington Disease: A Tract-Based Spatial Statistics Study

BACKGROUND AND PURPOSE: HD entails damage of the WM. Our aim was to explore in vivo the regional volume and microstructure of the brain WM in HD and to correlate such findings with clinical status of the patients. MATERIALS AND METHODS: Fifteen HD gene carriers in different clinical stages of the disease and 15 healthy controls were studied with T1-weighted images for VBM and DTI for TBSS. Maps of FA, MD, and λ∥ and λ⊥ were reconstructed. RESULTS: Compared with controls, in addition to neostriatum and cortical GM volume loss, individuals with HD showed volume loss in the genu of the internal capsule and subcortical frontal WM bilaterally, the right splenium of the corpus callosum, and the left corona radiata. TBSS revealed symmetrically decreased FA in the corpus callosum, fornix, external/extreme capsule, inferior fronto-occipital fasciculus, and inferior longitudinal fasciculus. Areas of increased MD were more extensive and included arciform fibers of the cerebral hemispheres and cerebral peduncles. Increase of the λ∥ and a comparatively more pronounced increase of the λ⊥ underlay the decreased FA of the WM in HD. Areas of WM atrophy, decreased FA, and increased MD correlated with the severity of the motor and cognitive dysfunction, whereas only the areas with increased MD correlated with disease duration. CONCLUSIONS: Microstructural damage accompanies volume decrease of the WM in HD and is correlated with the clinical deficits and disease duration. MR imaging−based measures could be considered as a biomarker of neurodegeneration in HD gene carriers

Fractal dimension of cerebral white matter : A consistent feature for prediction of the cognitive performance in patients with small vessel disease and mild cognitive impairment

Patients with cerebral small vessel disease (SVD) frequently show decline in cognitive performance. However, neuroimaging in SVD patients discloses a wide range of brain lesions and alterations so that it is often difficult to understand which of these changes are the most relevant for cognitive decline. It has also become evident that visually-rated alterations do not fully explain the neuroimaging correlates of cognitive decline in SVD. Fractal dimension (FD), a unitless feature of structural complexity that can be computed from high-resolution T1-weighted images, has been recently applied to the neuroimaging evaluation of the human brain. Indeed, white matter (WM) and cortical gray matter (GM) exhibit an inherent structural complexity that can be measured through the FD. In our study, we included 64 patients (mean age \ub1 standard deviation, 74.6 \ub1 6.9, education 7.9 \ub1 4.2 years, 53% males) with SVD and mild cognitive impairment (MCI), and a control group of 24 healthy subjects (mean age \ub1 standard deviation, 72.3 \ub1 4.4 years, 50% males). With the aim of assessing whether the FD values of cerebral WM (WM FD) and cortical GM (GM FD) could be valuable structural predictors of cognitive performance in patients with SVD and MCI, we employed a machine learning strategy based on LASSO (least absolute shrinkage and selection operator) regression applied on a set of standard and advanced neuroimaging features in a nested cross-validation (CV) loop. This approach was aimed at 1) choosing the best predictive models, able to reliably predict the individual neuropsychological scores sensitive to attention and executive dysfunctions (prominent features of subcortical vascular cognitive impairment) and 2) identifying a features ranking according to their importance in the model through the assessment of the out-of-sample error. For each neuropsychological test, using 1000 repetitions of LASSO regression and 5000 random permutations, we found that the statistically significant models were those for the Montreal Cognitive Assessment scores (p-value =.039), Symbol Digit Modalities Test scores (p-value =.039), and Trail Making Test Part A scores (p-value =.025). Significant prediction of these scores was obtained using different sets of neuroimaging features in which the WM FD was the most frequently selected feature. In conclusion, we showed that a machine learning approach could be useful in SVD research field using standard and advanced neuroimaging features. Our study results raise the possibility that FD may represent a consistent feature in predicting cognitive decline in SVD that can complement standard imaging

Brain structural damage in Friedreich's ataxia.

ABSTRACT Objective: Neuropathological descriptions of the brain in Friedreich’s ataxia (FRDA) were obtained before avail- ability of the current molecular genetic tests for this disease. Voxel-based morphometry (VBM) enables an unbiased whole-brain quantitative analysis of differences in gray matter (GM) and white matter (WM) volume. Methods: Using VBM, we assessed the brain structural damage in 22 patients with genetically confirmed FRDA and 25 healthy controls. The results were correlated with the disease duration and the severity of the patients’ clinical deficits—evaluated using the International Cerebellar Ataxia Rating Scale and Inherited Ataxia Clinical Rating Scale. Results: In patients with FRDA, VBM showed a symmetrical volume loss in dorsal medulla, infero-medial portions of the cerebellar hemispheres, the rostral vermis and in the dentate region. No volume loss in cerebral hemispheres was observed. The atrophy of the cerebel- lum and medulla correlated with the severity of the clinical deficit and disease duration. Conclusions: In patients with FRDA, significant GM and WM loss was observed only in the cerebellum and dorsal medulla. These structural changes correlate with the severity of the clinical deficit and disease duration

Regional Analysis of the Magnetization Transfer Ratio of the Brain in Mild Alzheimer Disease and Amnestic Mild Cognitive Impairment

BACKGROUND AND PURPOSE: Manually drawn VOI-based analysis shows a decrease in magnetization transfer ratio in the hippocampus of patients with Alzheimer disease. We investigated with whole-brain voxelwise analysis the regional changes of the magnetization transfer ratio in patients with mild Alzheimer disease and patients with amnestic mild cognitive impairment. MATERIALS AND METHODS: Twenty patients with mild Alzheimer disease, 27 patients with amnestic mild cognitive impairment, and 30 healthy elderly control subjects were examined with high-resolution T1WI and 3-mm-thick magnetization transfer images. Whole-brain voxelwise analysis of magnetization transfer ratio maps was performed by use of Statistical Parametric Mapping 8 software and was supplemented by the analysis of the magnetization transfer ratio in FreeSurfer parcellation-derived VOIs. RESULTS: Voxelwise analysis showed 2 clusters of significantly decreased magnetization transfer ratio in the left hippocampus and amygdala and in the left posterior mesial temporal cortex (fusiform gyrus) of patients with Alzheimer disease as compared with control subjects but no difference between patients with amnestic mild cognitive impairment and either patients with Alzheimer disease or control subjects. VOI analysis showed that the magnetization transfer ratio in the hippocampus and amygdala was significantly lower (bilaterally) in patients with Alzheimer disease when compared with control subjects (ANOVA with Bonferroni correction, at P < .05). Mean magnetization transfer ratio values in the hippocampus and amygdala in patients with amnestic mild cognitive impairment were between those of healthy control subjects and those of patients with mild Alzheimer disease. Support vector machine-based classification demonstrated improved classification performance after inclusion of magnetization transfer ratio-related features, especially between patients with Alzheimer disease versus healthy subjects. CONCLUSIONS: Bilateral but asymmetric decrease of magnetization transfer ratio reflecting microstructural changes of the residual GM is present not only in the hippocampus but also in the amygdala in patients with mild Alzheimer disease

Magnetization transfer MR imaging demonstrates degeneration of the subcortical and cortical gray matter in Huntington disease.

BACKGROUND AND PURPOSE: GM is typically affected in HD since the presymptomatic stage. Our aim was to investigate with MT MR imaging the microstructural changes of the residual brain subcortical and cortical GM in carriers of the HD gene and to preliminarily assess their correlation with the clinical features. MATERIALS AND METHODS: Fifteen HD gene carriers with a range of clinical severity and 15 age- and sex-matched healthy controls underwent MT MR imaging on a 1.5T scanner. The MT ratio was measured automatically in several subcortical and cortical GM regions (striatal nuclei; thalami; and the neocortex of the frontal, temporal, parietal, and occipital lobes) by using FLS tools. RESULTS: The MT ratio was significantly ( P < .05 with Bonferroni correction for multiple comparison) decreased in all subcortical structures except the putamen and decreased diffusely in the cerebral cortex of HD carriers compared with controls. Close correlation was observed between the subcortical and cortical regional MT ratios and several clinical variables, including disease duration, motor disability, and scores in timed neuropsychological tests. CONCLUSIONS: MT imaging demonstrates degeneration of the subcortical and cortical GM in HD carriers and might serve, along with volumetric assessment, as a surrogate marker in future clinical trials of HD. CAG : cytosine-adenine-guanine FIRST : FMRIB's Integrated Registration and Segmentation Tool FMRIB : Functional MR Imaging of the Brain FSL : FMRIB's Software Library GM : gray matter HD : Huntington disease MNI : Montreal Neurological Institute MT : magnetization transfer NGMV : normalized GM volume NS : not significant NWMV : normalized WM volume UHDRS : Unified Huntington's Disease Rating Scale WM : white matte

Whole-brain histogram and voxel-based analyses of apparent diffusion coefficient and magnetization transfer ratio in celiac disease, epilepsy, and cerebral calcifications syndrome

BACKGROUND AND PURPOSE: Diffusion and magnetization transfer (MT) techniques have been applied to the investigation with MR of epilepsy and have revealed changes in patients with or without abnormalities on MR imaging. We hypothesized that also in the coeliac disease (CD), epilepsy and cerebral calcifications (CEC) syndrome diffusion and MT techniques could reveal brain abnormalities undetected by MR imaging and tentatively correlated to epilepsy. MATERIALS AND METHODS: Diffusion and MT weighted images were obtained in 10 patients with CEC, 8 patients with CD without epilepsy and 17 healthy volunteers. The whole brain apparent diffusion coefficient (ADC) and MT ratio (MTR) maps were analyzed with histograms and the Statistical Parametric Mapping 2 (SPM2) software. We employed the non-parametric Mann-Whitney U test to assess differences for ADC and MTR histogram metrics. Voxel by voxel comparison of the ADC and MTR maps was performed with 2 tails t-test corrected for multiple comparison. RESULTS: A significantly higher whole brain ADC value as compared to healthy controls was observed in CEC (P = 0.006) and CD (P = 0.01) patients. SPM2 showed bilateral areas of significantly decreased MTR in the parietal and temporal subcortical white matter (WM) in the CEC patients. CONCLUSION: Our study indicates that diffusion and MT techniques are also capable of revealing abnormalities undetected by MR imaging. In particular patients with CEC syndrome show an increase of the whole brain ADC histogram which is more pronounced than in patients with gluten intolerance. IN CEC patients, voxel-based analysis demonstrates a localized decrease of the MTR in the parieto-temporal subcortical WM