Quantitative evaluation of age-related white matter microstructural changes on MRI by multifractal analysis

Pattern of heterogeneity in normal brain ageing: screening for mild cognitive impairment and its risk of progression with a radiomics model

PURPOSE

This study aimed to develop a normal brain ageing model based on magnetic resonance imaging and radiomics, therefore identifying radscore, an imaging indicator representing white matter heterogeneity and exploring the significance of radscore in detecting people's cognitive changes.

METHODS

Three hundred sixty cognitively normal (CN) subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database and 105 CN subjects from the Parkinson's Progression Markers Initiative database were used to develop the model. In ADNI, 230 mild cognitive impairment (MCI) subjects were matched with 230 CN old-aged subjects to evaluate their heterogeneity difference. One hundred four MCI subjects with 48 months of follow-up were divided into low and high heterogeneity groups. Kaplan-Meier survival curve analysis was used to observe the importance of heterogeneity results for predicting MCI progression.

RESULTS

The area under the receiver operating characteristic curve of the model in the training, internal test and external test sets was 0.7503, 0.7512 and 0.7514, respectively. There was a significantly positive correlation between age and radscore of CN subjects (r = 0.501; P < .001). The radscore of MCI subjects was significantly higher than that of matched CN subjects (P < .001). The median radscore ratios of MCI to CN from four age groups (66-70y, 71-75y, 76-80y and 81-85y) were 1.611, 1.760, 1.340 and 1.266, respectively. The probability to progression of low and high heterogeneity groups had a significant difference (P = .002).

CONCLUSION

When radscore is significantly higher than that of normal ageing, it is necessary to alert the possibility of cognitive impairment and deterioration.

Fractal Dimension Studies of the Brain Shape in Aging and Neurodegenerative Diseases

The fractal dimension is a morphometric measure that has been used to investigate the changes of brain shape complexity in aging and neurodegenerative diseases. This chapter reviews fractal dimension studies in aging and neurodegenerative disorders in the literature. Research has shown that the fractal dimension of the left cerebral hemisphere increases until adolescence and then decreases with aging, while the fractal dimension of the right hemisphere continues to increase until adulthood. Studies in neurodegenerative diseases demonstrated a decline in the fractal dimension of the gray matter and white matter in Alzheimer's disease, amyotrophic lateral sclerosis, and spinocerebellar ataxia. In multiple sclerosis, the white matter fractal dimension decreases, but conversely, the fractal dimension of the gray matter increases at specific stages of disease. There is also a decline in the gray matter fractal dimension in frontotemporal dementia and multiple system atrophy of the cerebellar type and in the white matter fractal dimension in epilepsy and stroke. Region-specific changes in fractal dimension have also been found in Huntington's disease and Parkinson's disease. Associations were found between the fractal dimension and clinical scores, showing the potential of the fractal dimension as a marker to monitor brain shape changes in normal or pathological processes and predict cognitive or motor function.

The fractal brain: scale-invariance in structure and dynamics

The past 40 years have witnessed extensive research on fractal structure and scale-free dynamics in the brain. Although considerable progress has been made, a comprehensive picture has yet to emerge, and needs further linking to a mechanistic account of brain function. Here, we review these concepts, connecting observations across different levels of organization, from both a structural and functional perspective. We argue that, paradoxically, the level of cortical circuits is the least understood from a structural point of view and perhaps the best studied from a dynamical one. We further link observations about scale-freeness and fractality with evidence that the environment provides constraints that may explain the usefulness of fractal structure and scale-free dynamics in the brain. Moreover, we discuss evidence that behavior exhibits scale-free properties, likely emerging from similarly organized brain dynamics, enabling an organism to thrive in an environment that shares the same organizational principles. Finally, we review the sparse evidence for and try to speculate on the functional consequences of fractality and scale-freeness for brain computation. These properties may endow the brain with computational capabilities that transcend current models of neural computation and could hold the key to unraveling how the brain constructs percepts and generates behavior.

Surface-Based Cortical Measures in Multimodal Association Brain Regions Predict Chess Expertise

The complex structure of the brain supports high-order cognition, which is crucial for mastering chess. Surface-based measures, including the fractional dimension (FD) and gyrification index (GI), may be more sensitive in detecting cortical changes relative to volumetric indexes. For this reason, structural magnetic resonance imaging data from 29 chess experts and 29 novice participants were analyzed using the CAT12 toolbox. FD and GI for each brain region were compared between the groups. A multivariate model was used to identify surface-based brain measures that can predict chess expertise. In chess experts, FD is increased in the left frontal operculum (p < 0.01), and this change correlates with the starting age of chess practice (ρ = −0.54, p < 0.01). FD is decreased in the right superior parietal lobule (p < 0.01). Chess expertise is predicted by the FD in a network of fronto-parieto-temporal regions and is associated with GI changes in the middle cingulate gyrus (p < 0.01) and the superior temporal sulcus (p < 0.01). Our findings add to the evidence that chess expertise is based on the complex properties of the brain surface of a network of transmodal association areas important for flexible high-level cognitive functions. Interestingly, these changes are associated with long-lasting practice, suggesting that neuroplastic effects develop over time.

Long-Tailed Characteristic of Spiking Pattern Alternation Induced by Log-Normal Excitatory Synaptic Distribution

Studies of structural connectivity at the synaptic level show that in synaptic connections of the cerebral cortex, the excitatory postsynaptic potential (EPSP) in most synapses exhibits sub-mV values, while a small number of synapses exhibit large EPSPs ( >~1.0 [mV]). This means that the distribution of EPSP fits a log-normal distribution. While not restricting structural connectivity, skewed and long-tailed distributions have been widely observed in neural activities, such as the occurrences of spiking rates and the size of a synchronously spiking population. Many studies have been modeled this long-tailed EPSP neural activity distribution; however, its causal factors remain controversial. This study focused on the long-tailed EPSP distributions and interlateral synaptic connections primarily observed in the cortical network structures, thereby having constructed a spiking neural network consistent with these features. Especially, we constructed two coupled modules of spiking neural networks with excitatory and inhibitory neural populations with a log-normal EPSP distribution. We evaluated the spiking activities for different input frequencies and with/without strong synaptic connections. These coupled modules exhibited intermittent intermodule-alternative behavior, given moderate input frequency and the existence of strong synaptic and intermodule connections. Moreover, the power analysis, multiscale entropy analysis, and surrogate data analysis revealed that the long-tailed EPSP distribution and intermodule connections enhanced the complexity of spiking activity at large temporal scales and induced nonlinear dynamics and neural activity that followed the long-tailed distribution.

Brain MRI radiomics analysis may predict poor psychomotor outcome in preterm neonates

OBJECTIVES

This study aimed to apply a radiomics approach to predict poor psychomotor development in preterm neonates using brain MRI.

METHODS

Prospectively enrolled preterm neonates underwent brain MRI near or at term-equivalent age and neurodevelopment was assessed at a corrected age of 12 months. Two radiologists visually assessed the degree of white matter injury. The radiomics analysis on white matter was performed using T1-weighted images (T1WI) and T2-weighted images (T2WI). A total of 1906 features were extracted from the images and the minimum redundancy maximum relevance algorithm was used to select features. A prediction model for the binary classification of the psychomotor developmental index was developed and eightfold cross-validation was performed. The diagnostic performance of the model was evaluated using the AUC with and without including significant clinical and DTI parameters.

RESULTS

A total of 46 preterm neonates (median gestational age, 29 weeks; 26 males) underwent brain MRI (median corrected gestational age, 37 weeks). Thirteen of 46 (28.3%) neonates showed poor psychomotor outcomes. There was one neonate among 46 with moderate to severe white matter injury on visual assessment. For the radiomics analysis, twenty features were selected for each analysis. The AUCs of prediction models based on T1WI, T2WI, and both T1WI and T2WI were 0.925, 0.834, and 0.902. Including gestational age or DTI parameters did not improve the prediction performance of T1WI.

CONCLUSIONS

A radiomics analysis of white matter using early T1WI or T2WI could predict poor psychomotor outcomes in preterm neonates.

KEY POINTS

• Radiomics analysis on T1-weighted images of preterm neonates showed the highest diagnostic performance (AUC, 0.925) for predicting poor psychomotor outcomes. • In spite of 45 of 46 neonates having no significant white matter injury on visual assessment, the radiomics analysis of early brain MRI showed good diagnostic performance (sensitivity, 84.6%; specificity, 78.8%) for predicting poor psychomotor outcomes. • Radiomics analysis on early brain MRI can help to predict poor neurodevelopmental outcomes in preterm neonates.

White Matter Language Pathways and Language Performance in Healthy Adults Across Ages

The goal of this study was to determine the relationship between age-related white matter changes, with a specific focus on previously identified language pathways, and language functioning in healthy aging. 228 healthy participants (126 female; 146 right-handed), ages 18 to 76, underwent 3.0 Tesla MR diffusion weighted imaging (DWI) and a battery of language assessments including the Boston Naming Test (BNT), the Peabody Picture Vocabulary Test (PPVT), the Controlled Oral Word Association Test (COWAT), Semantic Fluency Test (SFT), and a subset of the Boston Diagnostic Aphasia Examination (CI-BDAE). Using tract based spatial statistics (TBSS), we investigated measurements of fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD). TBSS was used to create a white matter skeleton that was then used to analyze white matter changes (indexed by FA, AD, RD, and MD) with age and language performance. Results focused primarily on significant relationships (p < 0.05, cluster-wise FDR corrected for multiple comparisons) in the canonical language white matter pathways. We found a diffuse linear decrease with age in global white matter FA and a significant focal increase in FA with age within the bilateral superior cerebellar peduncles (SCPs). We observed that increased BNT scores were associated with increased FA within the left SLF, and within the posterior and antero-lateral portions of the right inferior frontal-occipital fasciculus (IFOF). Increased SFT and PPVT scores were associated with increased FA within the posterior portion of the right IFOF and increased FA within the left body of the corpus callosum was associated with lower COWAT scores. We found no association between FA and BDAE. MD, RD, and AD, were found to be inversely proportional to FA within the IFOF, with AD showing a negative correlation with SFT, and RD and MD showing a negative correlation with BNT. There was no association between CI-BDAE and any of the white matter measures. Significant differences between sexes included more pronounced FA decrease with age within the right SLF in males vs. females; there were no differences in language performance scores between sexes. We also found that there was no decline in language testing scores with increasing age in our cohort. Taken together, our findings of varying relationships between DTI metrics and language function within multiple regions of the non-dominant IFOF suggest that more robust language networks with bilateral structural connectivity may contribute to better overall language functioning, regardless of age.

Analysis on Artist Neuropsychology and Art Creation

Based on Carl Gustav Jung's persona philosophy, this paper conducts theoretical analysis on the introvert and extravert personalities, distinguishes the introvert personality from the psychopathy defined from a medical perspective, and elaborates on the dominance of introvert personality in art creations, as well as the "mental conditions" among artists that the contemporary society is concerned with. This paper uses modern artists as subjects to support the conclusion through analysis of their childhood, career and life stories.

Predicting the Development of Normal-Appearing White Matter With Radiomics in the Aging Brain: A Longitudinal Clinical Study

Background: Normal-appearing white matter (NAWM) refers to the normal, yet diseased tissue around the white matter hyperintensities (WMH) on conventional MR images. Radiomics is an emerging quantitative imaging technique that provides more details than a traditional visual analysis. This study aims to explore whether WMH could be predicted during the early stages of NAWM, using a textural analysis in the general elderly population.

Methods: Imaging data were obtained from PACS between 2012 and 2017. The subjects (≥60 years) received two or more MRI exams on the same scanner with time intervals of more than 1 year. By comparing the baseline and follow-up images, patients with noted progression of WMH were included as the case group (n = 51), while age-matched subjects without WMH were included as the control group (n = 51). Segmentations of the regions of interest (ROIs) were done with the ITK software. Two ROIs of developing NAWM (dNAWM) and non-developing NAWM (non-dNAWM) were drawn separately on the FLAIR images of each patient. dNAWM appeared normal on the baseline images, yet evolved into WMH on the follow-up images. Non-dNAWM appeared normal on both the baseline and follow-up images. A third ROI of normal white matter (NWM) was extracted from the control group, which was normal on both baseline and follow-up images. Textural features were dimensionally reduced with ANOVA+MW, correlation analysis, and LASSO. Three models were built based on the optimal parameters of dimensional reduction, including Model 1 (NWM vs. dNAWM), Model 2 (non-dNAWM vs. dNAWM), and Model 3 (NWM vs. non-dNAWM). The ROC curve was adopted to evaluate the classification validity of these models.

Results: Basic characteristics of the patients and controls showed no significant differences. The AUC of Model 1 in training and test groups were 0.967 (95% CI: 0.831–0.999) and 0.954 (95% CI: 0.876–0.989), respectively. The AUC of Model 2 were 0.939 (95% CI: 0.856–0.982) and 0.846 (95% CI: 0.671–0.950). The AUC of Model 3 were 0.713 (95% CI: 0.593–0.814) and 0.667 (95% CI: 0.475–0.825).

Conclusion: Radiomics textural analysis can distinguish dNAWM from non-dNAWM on FLAIR images, which could be used for the early detection of NAWM lesions before they develop into visible WHM.

Adolescent Executive Dysfunction in Daily Life: Relationships to Risks, Brain Structure and Substance Use

During adolescence, problems reflecting cognitive, behavioral and affective dysregulation, such as inattention and emotional dyscontrol, have been observed to be associated with substance use disorder (SUD) risks and outcomes. Prior studies have typically been with small samples, and have typically not included comprehensive measurement of executive dysfunction domains. The relationships of executive dysfunction in daily life with performance based testing of cognitive skills and structural brain characteristics, thought to be the basis for executive functioning, have not been definitively determined. The aims of this study were to determine the relationships between executive dysfunction in daily life, measured by the Behavior Rating Inventory of Executive Function (BRIEF), cognitive skills and structural brain characteristics, and SUD risks, including a global SUD risk indicator, sleep quality, and risky alcohol and cannabis use. In addition to bivariate relationships, multivariate models were tested. The subjects (n = 817; ages 12 through 21) were participants in the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study. The results indicated that executive dysfunction was significantly related to SUD risks, poor sleep quality, risky alcohol use and cannabis use, and was not significantly related to cognitive skills or structural brain characteristics. In multivariate models, the relationship between poor sleep quality and risky substance use was mediated by executive dysfunction. While these cross-sectional relationships need to be further examined in longitudinal analyses, the results suggest that poor sleep quality and executive dysfunction may be viable preventive intervention targets to reduce adolescent substance use.

3D structural complexity analysis of cerebellum in Chiari malformation type I

Chiari malformation type I (CM-I), described by a descent of the cerebellar tonsils, is assumed to be a neurological developmental disorder. The aim of the present study was to investigate morphological variance in cerebellar sub-structures, including gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF), using magnetic resonance (MR) images with three-dimensional (3D) fractal dimension (FD) analysis in patients with CM-I. MRI data of 16 patients and 15 control subjects were obtained, and structural complexity analyses were performed using a box-counting FD algorithm. Results showed that patients with CM-I had significantly reduced FD values for WM and CSF in comparison with controls, and statistically significant differences in cerebellar GM and CSF volumes between patients and controls were found. Moreover, a significant difference was not found between the WM volumes. This may suggest that there are changes in structural complexity in WM even when its volume is unaffected. We conclude that the findings of this preliminary study indicate the possibility of using FD analysis to understand the pathophysiology of CM-I in patients.

Cerebral correlates of cognitive reserve

Cognitive reserve is a hypothetical concept introduced to explain discrepancies between severity of clinical dementia syndromes and the extent of dementia pathology. We examined cognitive reserve in a research programme that followed up a non-clinical sample born in 1921 or 1936 and IQ-tested age 11 years in 1932 or 1947. Structural MRI exams were acquired in about 50% of the sample from whom a subsample were recruited into an additional fMRI study. Here, we summarise findings from seven inter-related studies. These support an understanding of cognitive reserve as a balance between positive life course activity-driven experiences and the negative effects of brain pathologies including cerebrovascular disease and total and regional brain volume loss. Hypothesised structural equation models illustrate the relative causal effects of these positive and negative contributions. Cognitive reserve is considered in the context of choice of interventions to prevent dementia and the opposing effects of cerebrovascular disease and Alzheimer like brain appearances.

Fractal dimension analysis of cerebellum in Chiari Malformation type I

Chiari Malformation type I (CM-I) is a serious neurological disorder that is characterized by hindbrain herniation. Our aim was to evaluate the usefulness of fractal analysis in CM-I patients. To examine the morphological complexity features of this disorder, fractal dimension (FD) of cerebellar regions were estimated from magnetic resonance images (MRI) of 17 patients with CM-I and 16 healthy control subjects in this study. The areas of white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) were calculated and the corresponding FD values were computed using a 2D box-counting method in both groups. The results indicated that CM-I patients had significantly higher (p<0.05) FD values of GM, WM and CSF tissues compared to control group. According to the results of correlation analysis between FD values and the corresponding area values, FD and area values of GM tissues in the patients group were found to be correlated. The results of the present study suggest that FD values of cerebellar regions may be a discriminative feature and a useful marker for investigation of abnormalities in the cerebellum of CM-I patients. Further studies to explore the changes in cerebellar regions with the help of 3D FD analysis and volumetric calculations should be performed as a future work.

Relevance of magnetic resonance imaging for early detection and diagnosis of Alzheimer disease

Hippocampus volumetry currently is the best-established imaging biomarker for AD. However, the effect of multicenter acquisition on measurements of hippocampus volume needs to be explicitly considered when it is applied in large clinical trials, for example by using mixed-effects models to take the clustering of data within centers into account. The marker needs further validation in respect of the underlying neurobiological substrate and potential confounds such as vascular disease, inflammation, hydrocephalus, and alcoholism, and with regard to clinical outcomes such as cognition but also to demographic and socioeconomic outcomes such as mortality and institutionalization. The use of hippocampus volumetry for risk stratification of predementia study samples will further increase with the availability of automated measurement approaches. An important step in this respect will be the development of a standard hippocampus tracing protocol that harmonizes the large range of presently available manual protocols. In the near future, regionally differentiated automated methods will become available together with an appropriate statistical model, such as multivariate analysis of deformation fields, or techniques such as cortical-thickness measurements that yield a meaningful metrics for the detection of treatment effects. More advanced imaging protocols, including DTI, DSI, and functional MRI, are presently being used in monocenter and first multicenter studies. In the future these techniques will be relevant for the risk stratification in phase IIa type studies (small proof-of-concept trials). By contrast, the application of the broader established structural imaging biomarkers, such as hippocampus volume, for risk stratification and as surrogate end point is already today part of many clinical trial protocols. However, clinical care will also be affected by these new technologies. Radiologic expert centers already offer “dementia screening” for well-off middle-aged people who undergo an MRI scan with subsequent automated, typically VBM-based analysis, and determination of z-score deviation from a matched control cohort. Next-generation scanner software will likely include radiologic expert systems for automated segmentation, deformation-based morphometry, and multivariate analysis of anatomic MRI scans for the detection of a typical AD pattern. As these developments will start to change medical practice, first for selected subject groups that can afford this type of screening but later eventually also for other cohorts, clinicians must become aware of the potentials and limitations of these technologies. It is decidedly unclear to date how a middle-aged cognitively intact subject with a seemingly AD-positive MRI scan should be clinically advised. There is no evidence for individual risk prediction and even less for specific treatments. Thus, the development of preclinical diagnostic imaging poses not only technical but also ethical problems that must be critically discussed on the basis of profound knowledge. From a neurobiological point of view, the main determinants of cognitive impairment in AD are the density of synapses and neurons in distributed cortical and subcortical networks. MRI-based measures of regional gray matter volume and associated multivariate analysis techniques of regional interactions of gray matter densities provide insight into the onset and temporal dynamics of cortical atrophy as a close proxy for regional neuronal loss and a basis of functional impairment in specific neuronal networks. From the clinical point of view, clinicians must bear in mind that patients do not suffer from hippocampus atrophy or disconnection but from memory impairment, and that dementia screening in asymptomatic subjects should not be used outside of clinical studies.

High blood pressure accelerates gait slowing in well-functioning older adults over 18-years of follow-up

OBJECTIVES

To examine whether the association between hypertension and decline in gait speed is significant in well-functioning older adults and whether other health-related factors, such as brain, kidney, and heart function, can explain it.

DESIGN

Longitudinal cohort study.

SETTING

Cardiovascular Health Study.

PARTICIPANTS

Of 2,733 potential participants with a brain magnetic resonance imaging (MRI) scan, measures of mobility and systolic blood pressure (BP), no self-reported disability in 1992 to 1994 (baseline), and with at least 1 follow-up gait speed measurement through 1997 to 1999, 643 (aged 73.6, 57% female, 15% black) who had received a second MRI in 1997 to 1999 and an additional gait speed measure in 2005 to 2006 were included.

MEASUREMENTS

Mixed models with random slopes and intercepts were adjusted for age, race, and sex. Main explanatory factors included white matter hyperintensity progression, baseline cystatin-C, and left cardiac ventricular mass. Incidence of stroke and dementia, BP trajectories, and intake of antihypertensive medications during follow-up were tested as other potential explanatory factors.

RESULTS

Higher systolic BP was associated with faster rate of gait speed decline in this selected group of 643 participants, and results were similar in the parent cohort (N = 2,733). Participants with high BP (n = 293) had a significantly faster rate of gait speed decline than those with baseline BP less than 140/90 mmHg and no history of hypertension (n = 350). Rates were similar for those with history of hypertension who were uncontrolled (n = 110) or controlled (n = 87) at baseline and for those who were newly diagnosed (n = 96) at baseline. Adjustment for explanatory factors or for other covariates (education, prevalent cardiovascular disease, physical activity, vision, mood, cognition, muscle strength, body mass index, osteoporosis) did not change the results.

CONCLUSION

High BP accelerates gait slowing in well-functioning older adults over a long period of time, even for those who control their BP or develop hypertension later in life. Health-related measurements did not explain these associations. Future studies to investigate the mechanisms linking hypertension to slowing gait in older adults are warranted.

Fiber tracking functionally distinct components of the internal capsule

The internal capsule conveys information from primary and supplementary motor areas, frontopontine and thalamic peduncles to brain stem and cerebellar regions, and from thalamus to prefrontal cortex. Neurological accidents involving the internal capsule indicate differential functional correlates with its sectors. To examine the microstructural condition of this fiber system and to test functional correlates of its sectors in health and aging, 12 younger and 12 older adults were examined with diffusion tensor imaging (DTI) fiber tracking and neuropsychological tests. Greater age-related degradation was evident in the anterior than posterior limb and in the superior than inferior division of the internal capsule. The superior division age effect was especially notable in axial and radial diffusivity. Fractional anisotropy (FA) across the three (anterior, genu, posterior) fiber bundles of the inferior division accounted for 27-73% of the variance for each neuropsychological domain. Identification of a triple dissociation indicated selective correlations between anterior FA and set shifting, genu FA and motor skills, and posterior FA and fluency. Quantitative fiber tracking combined with assessment of cognitive and motor functions enabled the identification of selective brain structure-function relations in healthy adults without lesions that were previously observed only in patients with lesions of the internal capsule.

Longitudinal study of callosal microstructure in the normal adult aging brain using quantitative DTI fiber tracking

We present a review of neuroimaging studies of normal adult aging conducted with diffusion tensor imaging (DTI) and data from one of the first longitudinal studies using DTI to study normal aging. To date, virtually all DTI studies of normal adult aging have been cross-sectional and have identified several patterns of white matter microstructural sparing and compromise that differentiate regional effects, fiber type, and diffusivity characteristics: (1) fractional anisotropy (FA) is lower and mean diffusivity is higher in older than younger adults, (2) aging is characterized by an anterior-to-posterior gradient of greater-to-lesser compromise also seen in superior-to-inferior fiber systems, and (3) association fibers connecting cortical sites appear to be more vulnerable to aging than projection fibers. The results of this longitudinal study of the macrostructure and microstructure of the corpus callosum yielded a consistent pattern of differences between healthy, young (20s to 30s) and elderly (60s to 70s) men and women without change over 2 years. We then divided the fibers of the corpus callosum into the midsagittal strip and the lateral distal fibers in an attempt to identify the locus of the age-related differences. The results indicated that, on average, mean values of FA and longitudinal diffusivity (lambdaL) were lower in the distal than midsagittal fibers in both groups, but the age effects and the anterior-to-posterior gradients were more pronounced for the distal than midsagittal fibers and extended more posteriorly in the distal than midsagittal fibers. Despite lack of evidence for callosal aging over 2 years, ventricular enlargement occurred and was disproportionately greater in the elderly relative to the young group, being 8.2% in the elderly but only 1.2% in the young group. Thus, different brain regions can express different rates of change with aging. Our longitudinal DTI data indicate that normal aging is associated with declining FA and increasing diffusivity in both lambdaL (longitudinal diffusivity) and lambdaT (transverse diffusivity), perhaps defining the normal ontological condition rather than a pathological one, which can be marked by low FA and low diffusivity.

MR diffusion tensor imaging: a window into white matter integrity of the working brain

As Norman Geschwind asserted in 1965, syndromes resulting from white matter lesions could produce deficits in higher-order functions and "disconnexion" or the interruption of connection between gray matter regions could be as disruptive as trauma to those regions per se. The advent of in vivo diffusion tensor imaging, which allows quantitative characterization of white matter fiber integrity in health and disease, has served to strengthen Geschwind's proposal. Here we present an overview of the principles of diffusion tensor imaging (DTI) and its contribution to progress in our current understanding of normal and pathological brain function.

Application of a multifractal analysis to study brain white matter abnormalities of schizophrenia on T2-weighted magnetic resonance imaging

Multifractal analysis provides a precise quantitative description of the structural complexity of white matter (WM) on magnetic resonance imaging (MRI). To test this new technique as an aid to elucidating the pathology of schizophrenia, we examined a multifractal dimension (i.e. Deltaalpha) of WM in schizophrenia patients and their relations to clinical variables. We examined 16 patients with schizophrenia and 16 controls matched for age, sex and handedness. Delta alpha value of WM in the prefrontal and frontoparietal lobes and the corpus callosum (genu and splenium) on T2-weighted MRI was calculated. Delta alpha was not significantly different between groups in either region of interest. However, group-by-side interaction for Deltaalpha was found in the frontoparietal WM; post-hoc analysis revealed normal left dominant asymmetry in Deltaalpha for frontoparietal WM in control subjects, which was absent in schizophrenia patients. Furthermore, the patients with schizophrenia had a lower asymmetry coefficient ([R-L]/[R+L]) for Deltaalpha in frontoparietal WM. Relations to clinical symptoms from the Positive and Negative Syndrome Scale, Deltaalpha in corpus callosum, and the asymmetry coefficient in prefrontal WM were correlated with negative and general psychopathology symptom scores. Our results support the left-sided dysfunction hypothesis of schizophrenia and its relation to schizophrenic symptoms. Multifractal analysis reveals abnormal patterns of WM structures in schizophrenia that could be implicated in the disorder's etiology.

Endogenous multifractal brain dynamics are modulated by age, cholinergic blockade and cognitive performance

The intuitive notion that a healthy organism is characterised by regular, homeostatic function has been challenged by observations that a loss of complexity is, in fact, indicative of ill-health. Monofractals succinctly describe complex processes and are controlled by a single time-invariant scaling exponent, H, simply related to the fractal dimension. Previous analyses of resting fMRI time-series demonstrated that ageing and scopolamine administration were both associated with increases in H and that faster response in a prior encoding task was also associated with increased H. We revisit this experiment with a novel, multifractal approach in which fractal dynamics are assumed to be non-stationary and defined by a spectrum of local singularity exponents. Parameterisation of this spectrum was capable of refracting the effects of age, scopolamine and task performance as well as a refining a description of the associated signal changes. Using the same imaging data, we also explored turbulence as a possible mechanism underlying multifractal dynamics. Evidence is provided that Carstaing's model of turbulent information flow from high to low scales has only limited validity, and that scale invariance of energy dissipation is better explained by critical-phase phenomena, supporting the proposition that the brain maintains a state of self-organised criticality.

Quantitative fiber tracking of lateral and interhemispheric white matter systems in normal aging: relations to timed performance

The integrity of white matter, as measured in vivo with diffusion tensor imaging (DTI), is disrupted in normal aging. A current consensus is that in adults advancing age affects anterior brain regions disproportionately more than posterior regions; however, the mainstay of studies supporting this anterior-posterior gradient is based primarily on measures of the corpus callosum. Using our quantitative fiber tracking approach, we assessed fiber tract integrity of samples of major white matter cortical, subcortical, interhemispheric, and cerebellar systems (11 bilateral and 2 callosal) on DTI data collected at 1.5T magnet strength. Participants were 55 men (age 20-78 years) and 65 women (age 28-81 years), deemed healthy and cognitively intact following interview and behavioral testing. Fiber integrity was measured as orientational diffusion coherence (fractional anisotropy, FA) and magnitude of diffusion, which was quantified separately for longitudinal diffusivity (lambdaL), an index of axonal length or number, and transverse diffusivity (lambdaT), an index of myelin integrity. Aging effects were more evident in diffusivity than FA measures. Men and women, examined separately, showed similar age-related increases in longitudinal and transverse diffusivity in fibers of the internal and external capsules bilaterally and the fornix. FA was lower and diffusivity higher in anterior than posterior fibers of regional paired comparisons (genu versus splenium and frontal versus occipital forceps). Diffusivity with older age was generally greater or FA lower in the superior than inferior fiber systems (longitudinal fasciculi, cingulate bundles), with little to no evidence for age-related degradation in pontine or cerebellar systems. The most striking sex difference emerged for the corpus callosum, for which men showed significant decline in FA and increase in longitudinal and transverse diffusivity in the genu but not splenium. By contrast, in women the age effect was present in both callosal regions, albeit modestly more so in the genu than splenium. Functional meaningfulness of these age-related differences was supported by significant correlations between DTI signs of white matter degradation and poorer performance on cognitive or motor tests. This survey of multiple fiber systems throughout the brain revealed a differential pattern of age's effect on regional FA and diffusivity and suggests mechanisms of functional degradation, attributed at least in part to compromised fiber microstructure affecting myelin and axonal morphology.

Neuroradiological characterization of normal adult ageing

This paper provides a review of MRI and diffusion tensor imaging (DTI) findings in normal ageing as an essential context for evaluating imaging in dementia, and adding to the ever-growing number of such overviews. An additional extensive literature details the physics, MR acquisition, image reconstruction and mathematical computation approaches to both imaging modalities. The aim of this review is to illustrate how MR imaging modalities, spanning structural and diffusion tensor imaging, are suitable for visualizing and quantifying the macrostructural and microstructural disruptions sustained by the brain in normal ageing and to recognize the importance of normative data for identifying abnormalities characterizing neurodegenerative diseases and other conditions affecting brain tissue integrity.

Fractal dimension and white matter changes in multiple sclerosis

The brain white matter (WM) in multiple sclerosis (MS) suffers visible and non-visible (normal-appearing WM (NAWM)) changes in conventional magnetic resonance (MR) images. The fractal dimension (FD) is a quantitative parameter that characterizes the morphometric variability of a complex object. Our aim was to assess the usefulness of FD analysis in the measurement of WM abnormalities in conventional MR images in patients with MS, particularly to detect NAWM changes. First, we took on a voxel-based morphometry approach optimized for MS to obtain the segmented brain. Then, the FD of the whole grey-white matter interface (WM border) and skeletonized WM was calculated in patients with MS and healthy controls. To assess the FD of the NAWM, we focused our analysis on single sections without lesions at the centrum semiovale level. We found that patients with MS had a significant decrease in the FD of the entire brain WM compared with healthy controls. Such a decrease of the FD was detected not only on MR image sections with MS lesions but also on single sections with NAWM. Taken together, the results showed that FD identifies changes in the brain of patients with MS, including in NAWM, even at an early phase of the disease. Thus, FD might become a useful marker of diffuse damage of the central nervous system in MS.

An Interactive Test of Serial Behavior: Ageand Practice Alter Executive Function

We describe an interactive, computer-based test inspired by the Trail Making Test (TMT). In this new test, young (mean age = 20.4 years) and older participants (mean age = 74.9 years) used natural, pointing responses to order series of numbers, letters, or intermixed letters and numbers. This interactive test, which avoids several deficiencies of TMT, assesses participants' baseline speed for detecting and responding to individual items, captures the time for each response, and segregates erroneous responses from correct ones. The inter-response times with intermixed letters and numbers showed that participants did not always switch between the two different ordering tasks, but instead often recall letter-number pairs as single units. An additive factors analysis decomposed test times into functional components, including executive function, which took longer in older participants. With modest practice, both young and older participants sped up their ordering of intermixed numbers and letters, probably reflecting increased automaticity and reduced dependence upon executive function.

Multifractal analysis of deep white matter microstructural changes on MRI in relation to early-stage atherosclerosis

Multifractal analysis based on generalized concepts of fractals has been applied to evaluate biological tissues composed of complex structures. This type of analysis can provide a precise quantitative description of a broad range of heterogeneous phenomena. Previously, we applied multifractal analysis to describe heterogeneity in white matter signal fluctuation on T2-weighted MR images as a new method of texture analysis and established Deltaalpha as the most suitable index for evaluating white matter structural complexity (Takahashi et al. J. Neurol. Sci., 2004; 225: 33-37). Considerable evidence suggests that pathophysiological processes occurring in deep white matter regions may be partly responsible for cognitive deterioration and dementia in elderly subjects. We carried out a multifractal analysis in a group of 36 healthy elderly subjects who showed no evidence of atherosclerotic risk factors to examine the microstructural changes of the deep white matter on T2-weighted MR images. We also performed conventional texture analysis, i.e., determined the standard deviation of signal intensity divided by mean signal intensity (SD/MSI) for comparison with multifractal analysis. Next, we examined the association between the findings of these two types of texture analysis and the ultrasonographically measured intima-media thickness (IMT) of the carotid arteries, a reliable indicator of early carotid atherosclerosis. The severity of carotid IMT was positively associated with Deltaalpha in the deep white matter region. In addition, this association remained significant after excluding 12 subjects with visually detectable deep white matter hyperintensities on MR images. However, there was no significant association between the severity of carotid IMT and SD/MSI. These results indicate the potential usefulness of applying multifractal analysis to conventional MR images as a new approach to detect the microstructural changes of apparently normal white matter during the early stages of atherosclerosis.

A study on the computerized fractal analysis of architectural distortion in screening mammograms

Architectural distortion (AD) is a sign of malignancy often missed during mammographic interpretation. The purpose of this study was to explore the application of fractal analysis to the investigation of AD in screening mammograms. The study was performed using mammograms from the Digital Database for Screening Mammography (DDSM). The fractal dimension (FD) of mammographic regions of interest (ROIs) was calculated using the circular average power spectrum technique. Initially, the variability of the FD estimates depending on ROI location, mammographic view and breast side was studied on normal mammograms. Then, the estimated FD was evaluated using receiver operating characteristics (ROC) analysis to determine if it can discriminate ROIs depicting AD from those depicting normal breast parenchyma. The effect of several factors such as ROI size, image subsampling and breast density was studied in detail. Overall, the average FD of the normal ROIs was statistically significantly higher than that of the ROIs with AD. This result was consistent across all factors studied. For the studied set of implementation parameters, the best ROC performance achieved was 0.89 +/- 0.02. The generalizability of these conclusions across different digitizers was also demonstrated.