BettyAnn Chodkowski

RETINAL NERVE FIBER LAYER IS ASSOCIATED WITH BRAIN ATROPHY IN MULTIPLE SCLEROSIS

Objective: Optical coherence tomography (OCT) noninvasively quantifies retinal nerve fiber layer (RNFL) thickness. Studies show RNFL thinning in multiple sclerosis (MS), and we assessed its association with brain atrophy. Methods: RNFL thickness was measured in 40 patients with MS and 15 controls. Brain parenchymal fraction (BPF) and partial brain volumes were estimated from cranial MRI scans using SIENA-X. Multiple linear regression modeling assessed the association between OCT and MRI measures of atrophy. Results: Minimum RNFL thickness and subject age together predict 21% (p = 0.005) of the variance in BPF in all patients with MS and 43% (p = 0.003) of the variance in BPF in the subgroup with relapsing remitting MS (RRMS; n = 20). The partial correlation coefficient between BPF and minimum RNFL thickness, controlling for age, is 0.46 (p = 0.003) in all patients with MS and 0.69 (p = 0.001) in patients with RRMS. These associations are driven by CSF volume but not by gray or white matter volume. There is no significant association of these variables among controls. Conclusions: In multiple sclerosis (MS), retinal nerve fiber layer thickness is associated with brain parenchymal fraction and CSF volume. These data suggest that quantification of axonal thickness in the retina by optical coherence tomography (OCT) provides concurrent information about MRI brain abnormality in MS. OCT should be examined in longitudinal studies to determine if it could be used as an outcome measure in clinical trials of neuroprotective drugs. GLOSSARY: BPF = brain parenchymal fraction; EDSS = Expanded Disability Status Scale; KKI = Kennedy Krieger Institute; MNI = Montreal Neurological Institute; MPRAGE = magnetization-prepared rapid gradient echo; MS = multiple sclerosis; OCT = optical coherence tomography; PPMS = primary progressive MS; RNFL = retinal nerve fiber layer; RRMS = relapsing remitting MS; SPMS = secondary progressive MS; TMV = total macular volume.

Sensorimotor dysfunction in multiple sclerosis and column-specific magnetization transfer-imaging abnormalities in the spinal cord

The human spinal cord contains segregated sensory and motor pathways that have been difficult to quantify using conventional magnetic resonance imaging (MRI) techniques. Multiple sclerosis is characterized by both focal and spatially diffuse spinal cord lesions with heterogeneous pathologies that have limited attempts at linking MRI and behaviour. We used a novel magnetization-transfer-weighted imaging approach to quantify damage to spinal white matter columns and tested its association with sensorimotor impairment. We studied 42 participants with multiple sclerosis who each underwent MRI at 3 Tesla and quantitative tests of sensorimotor function. We measured cerebrospinal-fluid-normalized magnetization-transfer signals in the dorsal and lateral columns and grey matter of the cervical cord. We also measured brain lesion volume, cervical spinal cord lesion number and cross-sectional area, vibration sensation, strength, walking velocity and standing balance. We used linear regression to assess the relationship between sensorimotor impairment and MRI abnormalities. We found that the dorsal column cerebrospinal-fluid-normalized magnetization-transfer signal specifically correlated with vibration sensation (R = 0.58, P < 0.001) and the lateral column signal with strength (R = -0.45, P = 0.003). Spinal cord signal measures also correlated with walking and balance dysfunction. A stepwise multiple regression showed that the dorsal column signal and diagnosis subtype alone explained a significant portion of the variance in sensation (R(2) = 0.54, P < 0.001), whereas the lateral column signal and diagnosis subtype explained a significant portion of the variance in strength (R(2) = 0.30, P < 0.001). These results help to understand the anatomic basis of sensorimotor disability in multiple sclerosis and have implications for testing the effects of neuroprotective and reparative interventions.

Precision and accuracy of regional radioactivity quantitation using the maximum likelihood EM reconstruction algorithm

The imaging characteristics of maximum likelihood (ML) reconstruction using the EM algorithm for emission tomography have been extensively evaluated. There has been less study of the precision and accuracy of ML estimates of regional radioactivity concentration. The authors developed a realistic brain slice simulation by segmenting a normal subjects MRI scan into gray matter, white matter, and CSF and produced PET sinogram data with a model that included detector resolution and efficiencies, attenuation, scatter, and randoms. Noisy realizations at different count levels were created, and ML and filtered backprojection (FBP) reconstructions were performed. The bias and variability of ROI values were determined. In addition, the effects of ML pixel size, image smoothing and region size reduction were assessed. Hit estimates at 3,000 iterations (0.6 sec per iteration on a parallel computer) for 1-cm(2) gray matter ROIs showed negative biases of 6%+/-2% which can be reduced to 0%+/-3% by removing the outer 1-mm rim of each ROI. FBP applied to the full-size ROIs had 15%+/-4% negative bias with 50% less noise than hit. Shrinking the FBP regions provided partial bias compensation with noise increases to levels similar to ML. Smoothing of ML images produced biases comparable to FBP with slightly less noise. Because of its heavy computational requirements, the ML algorithm will be most useful for applications in which achieving minimum bias is important.

Reproducibility of tract-specific magnetization transfer and diffusion tensor imaging in the cervical spinal cord at 3 tesla.

Damage to specific white matter tracts within the spinal cord can often result in the particular neurological syndromes that characterize myelopathies such as traumatic spinal cord injury. Noninvasive visualization of these tracts with imaging techniques that are sensitive to microstructural integrity is an important clinical goal. Diffusion tensor imaging (DTI)‐ and magnetization transfer (MT)‐derived quantities have shown promise in assessing tissue health in the central nervous system. In this paper, we demonstrate that DTI of the cervical spinal cord can reliably discriminate sensory (dorsal) and motor (lateral) columns. From data derived from nine healthy volunteers, two raters quantified column‐specific parallel (λ||) and perpendicular (λ⟂) diffusivity, fractional anisotropy (FA), mean diffusivity (MD), and MT‐weighted signal intensity relative to cerebrospinal fluid (MTCSF) over two time‐points separated by more than 1 week. Cross‐sectional means and standard deviations of these measures in the lateral and dorsal columns were as follows: λ||: 2.13 ± 0.14 and 2.14 ± 0.11 μm2/ms; λ⟂: 0.67 ± 0.16 and 0.61 ± 0.09 μm2/ms; MD: 1.15 ± 0.15 and 1.12 ± 0.08 μm2/ms; FA: 0.68 ± 0.06 and 0.68 ± 0.05; MTCSF: 0.52 ± 0.05 and 0.50 ± 0.05. We examined the variability and interrater and test‐retest reliability for each metric. These column‐specific MR measurements are expected to enhance understanding of the intimate structure‐function relationship in the cervical spinal cord and may be useful for the assessment of disease progression. Copyright

Corticospinal Tract Abnormalities Are Associated with Weakness in Multiple Sclerosis

BACKGROUND AND PURPOSE: The association of MR imaging abnormalities with clinical disability in multiple sclerosis (MS) has been disappointing. This association might be improved by imaging specific functional systems in the central nervous system—for example, the motor system in a patient with weakness. Our aim was to assess the relationship between muscle strength in MS and corticospinal tract (CST) abnormalities detected with multimodality MR imaging of the brain. MATERIALS AND METHODS: In 47 individuals with MS, diffusion tensor imaging (DTI) at 3T was used to reconstruct the intracranial CSTs. Tract profiles depicted the variation in T2 relaxation time, magnetization transfer ratio (MTR), and DTI-derived indices (fractional anisotropy and diffusivity) as a function of normalized position along the tract. Brain parenchymal fraction was calculated as a normalized measure of brain volume. Stepwise linear regression modeling was used to determine the MR imaging indices most closely related to ankle dorsiflexion and hip flexion strength assessed with quantitative dynamometry. RESULTS: Individuals with MS were significantly weak: Average ankle strength fell 1.7 SDs below the age-, handedness-, and sex-corrected healthy mean. Brain parenchymal fraction was not associated with weakness. A parsimonious model that includes MTR in the brain stem and MS clinical subtype explained 30%–45% of the variance in ankle and hip strength. The model was successfully applied to scans and strength data from the same individuals at an earlier time point. CONCLUSION: MR imaging abnormalities specific to the motor tract are associated with clinical dysfunction related to that tract. The relevant abnormalities are found in the brain stem, distant from the periventricular inflammatory lesions that are common in MS. This suggests that neurodegeneration, rather than primary inflammation, at least partially explains the findings.

Reliability and reproducibility of perfusion MRI in cognitively normal subjects

Arterial spin labeling (ASL) magnetic resonance imaging (MRI) is becoming a popular method for measuring perfusion due to its ability of generating perfusion maps noninvasively. This allows for frequent repeat scanning, which is especially useful for follow-up studies. However, limited information is available regarding the reliability and reproducibility of ASL perfusion measurements. Here, the reliability and reproducibility of pulsed ASL was investigated in an elderly population to determine the variation in perfusion among cognitively normal individuals in different brain structures. Intraclass correlation coefficients (ICC) and within-subject variation coefficients (wsCV) were used to estimate reliability and reproducibility over a period of 1 year. Twelve cognitively normal subjects (75.5 ± 5.3 years old, six male and six female) were scanned four times (at 0, 3, 6 and 12 months). No significant difference in cerebral blood flow (CBF) was found over this period. CBF values ranged from 46 to 53 ml/100 g per minute in the medial frontal gyrus (MFG) and from 40 to 44 ml/100 g per minute over all gray matter regions in the superior part of the brain. Data obtained from the first two scans were processed by two readers and showed high reliability (ICC >0.97) and reproducibility (wsCV <6%). However, over the total period of 1 year, reliability reduced to a moderate level (ICC=0.63-0.74) with wsCVs of gray matter, left MFG, right MFG of 13.5%, 12.3%, and 15.4%, respectively. In conclusion, measurement of CBF with pulsed ASL provided good agreement between inter-raters. A moderate level of reliability was obtained over a 1-year period, which was attributed to variance in slice positioning and coregistration. As such pulsed ASL has the potential to be used for CBF comparison in longitudinal studies.

Spatial and temporal reproducibility-based ranking of the independent components of BOLD fMRI data.

Independent component analysis (ICA) decomposes fMRI data into spatially independent maps and their corresponding time courses. However, distinguishing the neurobiologically and biophysically reasonable components from those representing noise and artifacts is not trivial. We present a simple method for the ranking of independent components, by assessing the resemblance between components estimated from all the data, and components estimated from only the odd- (or even-) numbered time points. We show that the meaningful independent components of fMRI data resemble independent components estimated from downsampled data, and thus tend to be highly ranked by the method.

Sex differences in psychophysical and neurophysiological responses to pain in older adults: a cross-sectional study

BackgroundNeuroimaging studies in younger adults have demonstrated sex differences in brain processing of painful experimental stimuli. Such differences may contribute to findings that women suffer disproportionately from pain. It is not known whether sex-related differences in pain processing extend to older adults.MethodsThis cross-sectional study investigated sex differences in pain reports and brain response to pain in 12 cognitively healthy older female adults and 12 cognitively healthy age-matched older male adults (age range 65–81, median = 67). Participants underwent psychophysical assessments of thermal pain responses, functional MRI, and psychosocial assessment.ResultsWhen compared to older males, older females reported experiencing mild and moderate pain at lower stimulus intensities (i.e., exhibited greater pain sensitivity; Cohen’s d = 0.92 and 0.99, respectively, p < 0.01) yet did not report greater pain-associated unpleasantness. Imaging results indicated that, despite the lower stimulus intensities required to elicit mild pain detection in females, they exhibited less deactivations than males in regions associated with the default mode network (DMN) and in regions associated with pain affect (bilateral dorsolateral prefrontal cortex, somatomotor area, rostral anterior cingulate cortex (rACC), and dorsal ACC). Conversely, at moderate pain detection levels, males exhibited greater activation than females in several ipsilateral regions typically associated with pain sensation (e.g., primary (SI) and secondary somatosensory cortices (SII) and posterior insula). Sex differences were found in the association of brain activation in the left rACC with pain unpleasantness. In the combined sample of males and females, brain activation in the right secondary somatosensory cortex was associated with pain unpleasantness.ConclusionsCognitively healthy older adults in the sixth and seventh decades of life exhibit similar sex differences in pain sensitivity compared to those reported in younger individuals. However, older females did not find pain to be more unpleasant. Notably, increased sensitivity to mild pain in older females was reflected via less brain deactivation in regions associated with both the DMN and in pain affect. Current findings elevate the rACC as a key region associated with sex differences in reports of pain unpleasantness and brain deactivation in older adults. Also, pain affect may be encoded in SII in both older males and females.

Imbalance in resting state functional connectivity is associated with eating behaviors and adiposity in children

Background and Hypothesis Over the past 30 years, childhood obesity in the US has nearly doubled, while obesity has tripled among adolescents. Non-homeostatic eating, influenced by impulsivity and inhibition, may undermine successful long-term weight loss. We hypothesized that unhealthy eating habits and adiposity among children are associated with functional connectivity between brain regions associated with impulsivity, response inhibition, and reward. Methods We analyzed resting state functional magnetic resonance images from 38 children, ages 8–13. Using seed-based resting state functional connectivity, we quantified connectivity between brain regions associated with response inhibition (inferior parietal lobe [IPL]), impulsivity (frontal pole), and reward (nucleus accumbens [NAc]). We assessed the relationship of resting state functional connectivity with adiposity, quantified by BMI z-score, and eating behaviors, as measured by the Child Eating Behaviour Questionnaire (CEBQ). We computed an imbalance measure—the difference between [frontal pole:NAC] and [ipl:nac] functional connectivity—and investigated the relationship of this imbalance with eating behaviors and adiposity. Results As functional connectivity imbalance is increasingly biased toward impulsivity, adiposity increases. Similarly, as impulsivity-biased imbalance increases, food approach behaviors increase and food avoidance behaviors decrease. Increased adiposity is associated with increased food approach behaviors and decreased food avoidance behaviors. Conclusions In the absence of any explicit eating-related stimuli, the developing brain is primed toward food approach and away from food avoidance behavior with increasing adiposity. Imbalance in resting state functional connectivity that is associated with non-homeostatic eating develops during childhood, as early as 8–13 years of age. Our results indicate the importance of identifying children at risk for obesity for earlier intervention. In addition to changing eating habits and physical activity, strategies that normalize neural functional connectivity imbalance are needed to maintain healthy weight. Mindfulness may be one such approach as it is associated with increased response inhibition and decreased impulsivity.