Diffusion Tensor Imaging, White Matter lesions, the Corpus Callosum and Gait in the Elderly

Abstract

Background and Purpose

Gait impairment is common in the elderly, especially those with stroke and white matter hyperintensities (WMH) on conventional brain MRI. Diffusion Tensor Imaging (DTI) is more sensitive to white matter damage than conventional MRI. The relationship between DTI measures and gait has not been previously evaluated. Our purpose was to investigate the relationship between the integrity of white matter in the corpus callosum as determined by DTI and quantitative measures of gait in the elderly.

Methods

One hundred seventy-three participants of a community-dwelling elderly cohort had neurological and neuropsychological examinations and brain MRI. Gait function was measured by Tinetti gait (0-12), balance (0-16) and total (0-28) scores. DTI assessed Fractional Anisotropy in the genu and splenium of the corpus callosum. Conventional MRI was used to evaluate for brain infarcts and WMH volume.

Results

Participants with abnormal gait had low fractional anisotropy in the genu of the corpus callosum but not the splenium. Multiple regressions analyses showed an independent association between these genu abnormalities and all three Tinetti scores (p <0.001). This association remained significant after adding MRI infarcts and WMH volume to the analysis.

Conclusions

The independent association between quantitative measures of gait function and DTI findings shows that white matter integrity in the genu of corpus callosum is an important marker of gait in the elderly. DTI analyses of white matter tracts in brain and spinal cord may improve knowledge about the pathophysiology of gait impairment and help target clinical interventions.

Introduction

Maintaining safe walking and balance throughout life is important. Gait impairment is very common in the frail and homebound elderly and its prevalence increases with age^{1, 2}. Falls related to gait impairment are a major cause of morbidity, and fall-related injuries are the sixth leading cause of death in the elderly^3-5. Given the growth of an elderly population in the US and the world, fall-related injuries are likely to become increasingly common. Therefore, understanding mechanisms of gait impairment in the elderly has become an important public health issue.

The measurable properties of postural stability/balance and gait, that are requisite for safe and dependable mobility rely on complex interactions between the central and peripheral nervous systems⁶. White matter degeneration has been critically implicated as a major element in the process of aging of the nervous system⁷. Strokes, especially due to penetrating artery disease are the most important cause of white matter gliosis and tissue loss in the elderly. Patients with Binswanger disease often have abnormal gait as well as cognitive and behavioral abnormalities⁸. Previous imaging studies using conventional MRI have shown that patients with abnormal gait have significantly more white matter hyperintensities (WHI), brain infarcts, and larger ventricular size on conventional MRI compared to those without gait impairment^{2, 9-11}.

Diffusion tensor imaging (DTI) has been shown to be a reliable method for evaluation of white matter integrity, and can detect abnormalities in the white matter that appear normal on conventional MR imaging^{12, 13}. An additional advantage of DTI over conventional MRI is its ability to study individual white matter tracts¹⁴. The relationship between quantitative measures of DTI and gait in an aging population has not been previously evaluated.

We posited that DTI of tracts within the corpus callosum could yield additional information to that gleaned only from analysis of white matter hyperintensities (WMH), and would reflect the underlying neural integrity necessary for normal gait, stance and balance and would correlate with quantitative measures of mobility in the elderly. We explored the corpus callosum because it has been linked to gait function¹⁵, and is a highly organized coherent bundle of axons that travel in a single direction and as such is ideal for study of white matter integrity through DTI.

Methods

Subjects

The study sample consists of 173 of the 366 participants in the Nutrition, Aging, and Memory in Elders (NAME) study that underwent MRI. The NAME study investigated whether micronutrient status contributed to cognitive impairment and central nervous system abnormalities in elderly subjects ¹⁶. The study design including the inclusion-exclusion criteria were published in detail¹⁶. A subset of 366 subjects among the total of 1246 subjects were thoroughly evaluated with psychiatric, neurological examinations and MRI scans in addition to the nutritional, neuropsychological, medical-historical and blood chemistry evaluations in which all NAME trial subjects participated. The Institutional Review Board approved the NAME study, and all participants signed an informed consent. After year one, a DTI sequence was added to the MRI protocol. This report is based on the first consecutive 187 subjects in whom DTI data analysis was completed. Fourteen subjects were excluded: 8 were missing Tinetti scale values, and 5 were excluded due to book keeping errors and one was excluded due to an amputated leg. The final sample contained 173 subjects.

Imaging Protocol

All subjects were imaged on a 1.5 Tesla scanner (Siemens Symphony). T1, intermediate and T2-weighted axial images were used to determine WMH volume and brain infarcts. DTI was performed using a single-shot, spin echo, echo-planar sequence. DTI data was acquired along six independent axes.

Image Analysis

WMH and intracranial volumes were determined by quantitative segmentation using histogram analysis method described by DeCarli et al¹⁷. WMH volumes were reported in liters. A board-certified neuroradiologist determined the presence or absence of MRI infarcts using the method described by the cardiovascular Health Study¹⁸.

DTI images were processed on a Siemens Numaris 4 satellite console (Leonardo workstation) using DTI TASK CARD developed at Massachusetts General Hospital. The region of Interest (ROI) function on this program can be used to determine quantitative DTI information including Fractional Anisotropy (FA). Fractional anisotropy (FA) values for the genu and splenium of corpus callosum were determined by placing elliptical Regions of Interests (ROIs) in the genu and splenium of corpus callosum (Figure 1). All ROIs were placed by a Radiology resident and verified by an experienced board-certified neuroradiologist.

Figure 1.

Fractional Anisotropy image showing regions of interest in the genu and splenium of corpus callosum

Health and Neuropsycological Examination

Extensive demographic, laboratory and neuropsychological data were collected from NAME participants¹⁶. Participants identified their own abnormalities from a list of chronic conditions and health events. Diabetes was defined as the use of anti-diabetic medication or fasting glucose ≥126mg/dl. Hypertension was defined by self-report, systolic pressure ≥ 140 mm Hg or diastolic pressure ≥90 Hg or use of anti-hypertension medication. Arthritis was defined as a report of a physician's diagnosis of arthritis.

Neurological and Psychiatric Examinations

A Board certified psychiatrist evaluated the participants to record the Hamilton Rating Scale for depression¹⁹, the Clinical Dementia Rating Scale²⁰, and the MINI Mental Status Exam²¹ scores.

A neurological evaluation was performed by a board-certified neurologist. All subjects were scored on the national Institute of Health Stroke Scale (NIHHS)²². The neurologist judged whether the subject had clinical evidence of symptomatic stroke(s), peripheral neuropathy or another neurological syndrome. Strokes were classified according to the TOAST criteria²³.

Gait Assessment

Each participant's gait, balance and stance were assessed by the neurologist as part of the overall examination using the Performance-Oriented Mobility Assessment scale developed by Tinett²⁴. The total Tinetti scale (0-28) consists of gait (0-12) and balance (0-16) scales, and is based on a variety of items scored as 2- or 3-points per item. The gait scale scores ignition, step mechanics, arm swing, turning and gait coordination. The balance scale scores the components of static stance and balance as well as transfers between the seated and standing. Intact natural gait and balance receive the highest scores

Statistical Analysis

Mean and standard deviation were determined for continuous variables. Frequency and percentage of subjects showing a characteristic were determined for categorical variables. The values for Fractional Anisotropy (FA) in the genu and spenium of the corpus callosum and WMH volume were evaluated as tertiles. Univariate linear regression analysis was used to determine the association between independent variables (demographic, clinical characteristics, and DTI measures), and the dependent variables (Tinetti gait, balance and total scores). Stepwise regression analyses were performed to determine which demographic, clinical and DTI variables independently were associated with Tinetti scores. Variables with univariate p-values<0.05 were considered as candidate variables in the stepwise algorithm. A p value of <0.05 was considered significant. All statistical analyses were performed using SAS 9.1 (Cary, NC).

Results

Demographic, Clinical and Imaging Characteristics of Subjects

The demographic, clinical and imaging characteristics of the subjects are shown in Table 1.

Table 1.

Demographic, Clinical and Imaging Characteristics of Subjects

Variable	Total Subjects	Value
Age, y	173	72.83 ± 7.72
Women, n (%)	173	129 (74.57)
Hypertension, n (%)	172	145 (84.30 %)
Diabetes, n (%)	167	51 (30.54%)
MMSE Score, (0-30)	173	25.66+ 3.28
Depression Scale (CES-D), (1-60)	168	11.82 ± 9.78
Stroke-Diagnosis by a Neurologist, n (%)	173	30 (17.34%)
History of Arthritis, n (%)	171	127 (74.27 %)
Neuropathy- Diagnosis by a Neurologist, n (%)	173	87 (50.29%)
Vision (no visual loss), n (%)	173	169 (97.7%)
Nystagmus	173	2 (1.16%)
Parkinsons Disease (%)	165	2 (1.2)
MRI Infarcts (%)	171	49 (28.7)
Tinetti Scale
Gait (0-12)	173	10.21 ± 2.41
Balance (0-16)		13.69 ± 2.97
Total (0-28)		23.90 ± 5.12
FA-GCC H	173	857.49 ± 35.01
FA-GCC M		776.56 ± 25.79
FA-GCC L		659.83 ± 67.38
FA-SCC H	173	946.53 ± 22.66
FA-SCC M		885.83 ± 14.41
FA-SCC L		810.07 ± 47.80
WMHV H	164	0.01 ± 0.007
WMHV M		0.003 ± 0.0007
WMHV L		0.0009 ± 0.0004

Data are presented as mean ± standard deviation for continuous variables.

Data presented as number of subjects affected (percent) for categorical variables

FA-GCC H, M, L= Highest, Middle and Lowest tertiles of FA-GCC.

FA-SCC H, M, L = Highest, Middle and Lowest tertiles of FA-SCC.

WMHV H, M, L = Highest, Middle and Lowest tertiles of WMH volume.

Univariate Analyses of Subject Characteristics, FA-GCC, FA-SCC and Tinetti Scores

The results of Univariate analyses between subject characteristics, FA-GCC, FA-SCC and Tinetti scores are shown in Table 2. Gait scores showed a significant association with MMSE, stroke, MRI infarcts, WMH volume, MRI infarcts, and FA-GCC. There was no association between gait scores and other characteristics such as age, sex, arthritis, neuropathy or depression. There was no association between FA-SCC and gait scores.

Table 2.

Univariate Analyses of Clinical and Imaging Characteristics with Tinetti Scores

Variable	Tinetti Gait	Tinetti Balance	Tinetti Total
	β ± SE	β ± SE	β ± SE
Age	-0.04 ± 0.02	-0.05 ± 0.03	-0.10 ± 0.05
Female	0.31 ± 0.42	0.47 ± 0.52	0.78 ± 0.89
MMSE Score	0.19 ± 0.05 ***	0.19 ± 0.07**	0.38 ± 0.12 **
Depression Scale (CES-D)	-0.02 ± 0.02	-0.04 ± 0.02	-0.07 ± 0.04
History of Arthritis	0.25 ± 0.41	0.63 ± 0.51	0.88 ± 0.87
Stroke- Diagnosis by a Neurologist	-1.58 ± 0.47***	-1.65 ± 0.59**	-3.23 ± 1.00 **
Neuropathy- Diagnosis by a Neurologist	-0.51 ± 0.37	-1.12 ± 0.45*	-1.63 ± 0.77*
MRI Infarct	-1.55 ± 0.39***	-1.41 ± 0.49**	-2.96 ± 0.83***
FA-GCC L (compared to FA-GCC H)	-1.77 ± 0.43***	-1.85 ± 0.54***	-3.62 ± 0.91***
FA-GCC M (compared to FA-GCC H)	0.03 ± 0.43	-0.005 ± 0.54	0.03 ± 0.91
FA-SCC L (compared to FA-SCC H)	-0.55 ± 0.45	-0.32 ± 0.56	-0.87 ± 0.97
FA-SCC M (compared to FA-SCC H)	0.03 ± 0.45	0.10 ± 0.56	0.14 ± 0.96
WMHV H (compared to WMHV L)	-1.85 ± 0.44***	-1.76 ± 0.56**	-3.62 ± 0.95***
WMHV M (compared to WMHV L)	-0.43 ± 0.45	0.00 ± 0.56	-0.43 ± 0.96

^*p<.05;

^**p<.01;

^***p<.001

β ± SE = Beta ± Std. Error

Balance scores were significantly associated with MMSE, Stroke, neuropathy, MRI infarcts, WMH volume and FA-GCC. There was no association observed between balance scores and FA-SCC. Tinetti total scores were significantly associated with MMSE, stroke, neuropathy, MRI infarcts, WMH volume and FA-GCC. There was no association between Tinetti total scores and FA-SCC.

Multiple Stepwise Regression Analyses of Subjects Characteristics and FA-GCC with Tinetti Scores

Multiple forward regression analyses were performed using FA-GCC and WMH volume as tertiles. The results are shown in Table 3. Two models were created. In model-I, FA-GCC was the only imaging variable included as candidate variables. However, in model-II, WMH volume and MRI infarcts were also included as additional candidate imaging variables to examine the independent association between FA-GCC and gait function.

Table 3.

Multiple Forward Regression Analyses of Clinical and Imaging Characteristics with Tinetti Scores

Variable	Tinetti Gait	Tinetti Balance	Tinetti Total
	β ± SE	β ± SE	β ± SE
Model I
FA-GCC L (compared to FA-GCC H)	-1.52 ± 0.41***	-1.60 ± 0.53**	-3.11± 0.89***
FA-GCC M (compared to FA-GCC H)	-0.007 ± 0.41	0.05 ± 0.52	-0.05 ± 0.88
MMSE	0.13 ± 0.05*	NA	0.26 ± 0.11*
Stroke-diagnosis by a neurologist	-1.18 ± 0.45**	-1.33 ± 0.56*	-2.42± 0.96*
Neuropathy	NA	-0.90± 0.43*	NA
Model II
WMHV H (compared to WMHV L)	-1.46 ± 0.44**	-1.33 ± 0.57*	-2.40 ± 0.98*
FA-GCC L (compared to FA-GCC H)	-1.17 ± 0.45**	-1.41 ± 0.57*	-2.62 ± 0.96**
MMSE	0.15 ± 0.05**	NA	NA
Stroke-diagnosis by a neurologist	NA	NA	-1.98 ± 0.99*
Neuropathy	NA	NA	NA

p<.05;

^**p<.01;

^***p<.001

β ± SE = Beta ± Std. Error

Model I – Candidate variables for stepwise regression analyses were age, female sex, depression scale, arthritis, neuropathy, stroke, MMSE, and tertiles of FA-GCC

Model II- Candidate variables for stepwise regression analyses were age, female sex, depression scale, arthritis, neuropathy, stroke, MMSE, MRI infarcts, tertiles of FA-GCC and WMHV

NA – did not enter forward regression model

In model-I, gait scores were independently associated with lowest tertile of FA-GCC, stroke and MMSE. Subjects in lowest tertile of FA-GCC had, on average, a 1.52 point lower gait score compared to those in the highest tertile of FA-GCC. Balance scores were independently associated with stroke, neuropathy and lowest tertile of FA-GCC. Presence of stroke and lowest tertile of FA-GCC independently contributed to more than 1 point decline each, on average, in the balance score. Finally, Tinetti total scores were independently associated with lowest tertile of FA-GCC, stroke and MMSE. Both the lowest tertile of FA-GCC and stroke independently contributed to more than a 2-point decline in Tinetti total scores, on average, compared to participants without these characteristics.

In model-II, gait scores were independently associated with MMSE, lowest tertile of FA-GCC and highest tertile of WMH volume. Balance scores were independently associated only with lowest tertile of FA-GCC and highest tertile of WMH volume. Finally, Tinetti total scores were independently associated with stroke, lowest tertile of FA-GCC and highest tertile of WMH volume. Both the lowest tertile of FA-GCC and highest tertile WMH volume independently contributed to more than a 2-point decline in Tinetti total scores compared to participants without these imaging findings.

Discussion

The results of this prospective cross-sectional study show that white matter integrity in the genu of the corpus callosum determined by DTI is associated with quantitative measures of gait. This relationship was independent of other factors that affect gait and balance such as age, MMSE, depression, neuropathy, and stroke. This relationship persisted after WMH volume, a well known imaging characteristics for gait impairment was added in the analyses ^9-11. If confirmed by further studies, white matter integrity in the genu of corpus callosum may prove to be an important marker of walking ability. We also observed that white matter integrity in the splenium of corpus callosum had no association with measures of gait.

Modulation of gait and balance needed for successful walking is largely an automatic task, but increasing attention has recently been given to the integrity of the neural network that manages mobility through the correct equilibrium of motor control and sensory inputs⁶. Subcortical white matter disease has been shown to disrupt neural connections likely leading to impaired gait and balance²⁵.

Previous studies have consistently shown that white matter disease depicted by WMH on conventional MRI is associated with gait impairment^9-11. We used DTI to determine the status of white matter integrity and assessed its relationship to gait function in the elderly. It has been shown that FA measurements from DTI can demonstrate age-related decline in white matter and correlate with cognitive decline in the elderly (our data not presented here also showed these relationships)²⁶. Unlike conventional MRI, DTI can be used to assess individual projection, commissural and association white matter tracts¹⁴. Since most modern scanners have the ability to perform DTI and the analysis software is freely available on the internet, this technique has the potential to be used in routine clinical practice to detect early white matter disease amenable to intervention.

Results of our DTI study in a community based sample of elderly homebound individuals confirm previous observations of an association between white matter disease and gait impairment in the elderly. Our results also agree with the observations that atrophy of the corpus callosum is associated with gait impairment¹⁵. Using the more refined white matter technique of DTI, we were further able to localize this particular white matter derangement to commissural tracts in the genu of the corpus callosum but not in the splenium. Connections between the left and right frontal lobe especially the pre-frontal and anterior frontal cortices are dominant in the genu while fibers interconnecting the occipital and parahippocampal cortices are found in the splenium.²⁷ This clinico-anatomical correlation is consistent with the concept of the importance of integrated frontal executive function for the maintenance of gait and balance²⁸. Effective safe walking requires coordination between various levels of the nervous system and frontal coordination of the executive and cognitive functions. Our results are consistent with the concept that the white matter tracts carried in the genu of corpus callosum are necessary for successful and safe gait, balance and mobility. Our finding that white matter abnormalities in the genu lead to disturbance of gait and balance might also be expected to implicate frontal circuitry involved in executive function, language and motor planning and would imply the need for clinical strategies to support for loss of these functions in patients with gait disorders.

It is important to address three limitations of our study. First, we were able to sample only six directions for DTI due to limitations of MRI hardware available. Second, according to the NAME study inclusion criteria only those subjects living independently at home were included; consequently, our study population may have a selection bias toward healthier subjects with low prevalence of mobility impairment reducing the strength of relationship observed by us. Finally, findings reported do not characterize the components of gait affected by asymmetric processes such as hemiplegia. Given the exchange of information between hemispheres, it would be expected that the FA would be abnormal regardless of a symmetric or asymmetric mechanism. Such a mechanistic analysis is important and will be a focus of further experiments.

Since gait is a complex function requiring coordination between various levels of nervous system, future prospective studies with analyses of white matter tracts in brain and spinal cord in addition to corpus callosum, may help in improving our understanding of the pathophysiology of gait impairment, and to assess if DTI measurements such as fractional anisotropy are able to predict falls in the elderly individuals.