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Amy Brodtmann

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11 papers

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YNICL Journal 2023 Journal Article

Neural correlates of verbal fluency revealed by longitudinal T1, T2 and FLAIR imaging in stroke

Yanyu Xiong
Mohamed Salah Khlif
Natalia Egorova-Brumley
Amy Brodtmann
Brielle C. Stark

Diffusion-weighted imaging has been widely used in the research on post-stroke verbal fluency but acquiring diffusion data is not always clinically feasible. Achieving comparable reliability for detecting brain variables associated with verbal fluency impairments, based on more readily available anatomical, non-diffusion images (T1, T2 and FLAIR), enables clinical practitioners to have complementary neurophysiological information at hand to facilitate diagnosis and treatment of language impairment. Meanwhile, although the predominant focus in the stroke recovery literature has been on cortical contributions to verbal fluency, it remains unclear how subcortical regions and white matter disconnection are related to verbal fluency. Our study thus utilized anatomical scans of ischaemic stroke survivors (n = 121) to identify longitudinal relationships between subcortical volume, white matter tract disconnection, and verbal fluency performance at 3- and 12-months post-stroke. Subcortical grey matter volume was derived from FreeSurfer. We used an indirect probabilistic approach to quantify white matter disconnection in terms of disconnection severity, the proportion of lesioned voxel volume to the total volume of a tract, and disconnection probability, the probability of the overlap between the stroke lesion and a tract. These disconnection variables of each subject were identified based on the disconnectome map of the BCBToolkit. Using a linear mixed multiple regression method with 5-fold cross-validations, we correlated the semantic and phonemic fluency scores with longitudinal measurements of subcortical grey matter volume and 22 bilateral white matter tracts, while controlling for demographic variables (age, sex, handedness and education), total brain volume, lesion volume, and cortical thickness. The results showed that the right subcortical grey matter volume was positively correlated with phonemic fluency averaged over 3 months and 12 months. The finding generalized well on the test data. The disconnection probability of left superior longitudinal fasciculus II and left posterior arcuate fasciculus was negatively associated with semantic fluency only on the training data, but the result aligned with our previous study using diffusion scans in the same clinical population. In sum, our results presented evidence that routinely acquired anatomical scans can serve as a reliable source for deriving neural variables of post-stroke verbal fluency performance. The use of this method might provide an ecologically valid and more readily implementable analysis tool.

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YNICL Journal 2022 Journal Article

Cortical thinning 3 years after ischaemic stroke is associated with cognitive impairment and APOE ε4

Mohamed Salah Khlif
Natalia Egorova-Brumley
Laura J. Bird
Emilio Werden
Amy Brodtmann

Cortical thinning has been described in many neurodegenerative diseases and used for both diagnosis and disease monitoring. The imaging signatures of post-stroke vascular cognitive impairment have not been well described. We investigated the trajectory of cortical thickness over 3 years following ischaemic stroke compared to healthy stroke-free age- and sex-matched controls. We also compared cortical thickness between cognitively normal and impaired stroke survivors, and between APOE ɛ4 carriers and non-carriers. T1-weighted MRI and cognitive data for 90 stroke survivors and 36 controls from the Cognition And Neocortical Volume After Stroke (CANVAS) study were used. Cortical thickness was estimated using FreeSurfer volumetric reconstruction according to the Desikan-Killiany parcellation atlas. Segmentation inaccuracies were manually corrected and infarcted ipsilesional vertices in cortical thickness maps were identified and excluded using stroke lesion masks traced a-priori. Mixed-effects regression was used to compare cortical thickness cross-sectionally between groups and longitudinally between timepoints. Healthy control and stroke groups did not differ on demographics and most clinical characteristics, though controls were less likely to have atrial fibrillation. Age was negatively associated with global mean cortical thickness independent of sex or group, with women in both groups having significantly thicker cortex. Three months post-stroke, cortical thinning was limited and focal. From 3 months to 3 years, the rate of cortical thinning in stroke was faster compared to that in healthy controls. However, this difference in cortical thinning rate could not survive family-wise correction for multiple comparisons. Yet, cortical thinning at 3 years was found more spread especially in ipsilesional hemispheres in regions implicated in motor, sensory, and memory processing and recovery. The cognitively impaired stroke survivors showed greater cortical thinning, compared to controls, than those who were cognitively normal at 3 years. Also, carriers of the APOE ɛ4 allele in stroke exhibited greater cortical thinning independent of cognitive status. The temporal changes of cortical thickness in both healthy and stroke cohorts followed previously reported patterns of cortical thickness asymmetry loss across the human adult life. However, this loss of thickness asymmetry was amplified in stroke. The post-stroke trajectories of cortical thickness reported in this study may contribute to our understanding of imaging signatures of vascular cognitive impairment.

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YNIMG Journal 2021 Journal Article

Investigating the microstructural properties of normal-appearing white matter (NAWM) preceding conversion to white matter hyperintensities (WMHs) in stroke survivors

Wasim Khan
Mohamed Salah Khlif
Remika Mito
Thijs Dhollander
Amy Brodtmann

Using advanced diffusion MRI, we aimed to assess the microstructural properties of normal-appearing white matter (NAWM) preceding conversion to white matter hyperintensities (WMHs) using 3-tissue diffusion signal compositions in ischemic stroke. Data were obtained from the Cognition and Neocortical Volume After Stroke (CANVAS) study. Diffusion-weighted MR and high-resolution structural brain images were acquired 3- (baseline) and 12-months (follow-up) post-stroke. WMHs were automatically segmented and longitudinal assessment at 12-months was used to retrospectively delineate NAWM voxels at baseline converting to WMHs. NAWM voxels converting to WMHs were further dichotomized into either: “growing” WMHs if NAWM adhered to existing WMH voxels, or “isolated de-novo" WMHs if NAWM was unconnected to WMH voxels identified at baseline. Microstructural properties were assessed using 3-tissue diffusion signal compositions consisting of white matter-like (WM-like: TW), gray matter-like (GM-like: TG), and cerebrospinal fluid-like (CSF-like: TC) signal fractions. Our findings showed that NAWM converting to WMHs already exhibited similar changes in tissue compositions at baseline to WMHs with lower TW and increased TC (fluid-like, i. e. free-water) and TG compared to persistent NAWM. We also found that microstructural properties of persistent NAWM were related to overall WMH burden with greater free-water content in patients with high WMH load. These findings suggest that NAWM preceding conversion to WMHs are accompanied by greater fluid-like properties indicating increased tissue water content. Increased GM-like properties may indicate a more isotropic microstructure of tissue reflecting a degree of hindered diffusion in NAWM regions vulnerable to WMH development. These results support the usefulness of microstructural compositions as a sensitive marker of NAWM vulnerability to WMH pathogenesis.

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YNIMG Journal 2021 Journal Article

QSMART: Quantitative susceptibility mapping artifact reduction technique

Negin Yaghmaie
Warda T. Syeda
Chengchuan Wu
Yicheng Zhang
Tracy D. Zhang
Emma L. Burrows
Amy Brodtmann
Bradford A. Moffat

PURPOSE: Quantitative susceptibility mapping (QSM) is a novel MR technique that allows mapping of tissue susceptibility values from MR phase images. QSM is an ill-conditioned inverse problem, and although several methods have been proposed in the field, in the presence of a wide range of susceptibility sources, streaking artifacts appear around high susceptibility regions and contaminate the whole QSM map. QSMART is a post-processing pipeline that uses two-stage parallel inversion to reduce the streaking artifacts and remove banding artifact at the cortical surface and around the vasculature. METHOD: Tissue and vein susceptibility values were separately estimated by generating a mask of vasculature driven from the magnitude data using a Frangi filter. Spatially dependent filtering was used for the background field removal step and the two susceptibility estimates were combined in the final QSM map. QSMART was compared to RESHARP/iLSQR and V-SHARP/iLSQR inversion in a numerical phantom, 7T in vivo single and multiple-orientation scans, 9.4T ex vivo mouse data, and 4.7T in vivo rat brain with induced focal ischemia. RESULTS: Spatially dependent filtering showed better suppression of phase artifacts near cortex compared to RESHARP and V-SHARP, while preserving voxels located within regions of interest without brain edge erosion. QSMART showed successful reduction of streaking artifacts as well as improved contrast between different brain tissues compared to the QSM maps obtained by RESHARP/iLSQR and V-SHARP/iLSQR. CONCLUSION: QSMART can reduce QSM artifacts to enable more robust estimation of susceptibility values in vivo and ex vivo.

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YNICL Journal 2020 Journal Article

In vivo microstructural heterogeneity of white matter lesions in healthy elderly and Alzheimer's disease participants using tissue compositional analysis of diffusion MRI data

Remika Mito
Thijs Dhollander
Ying Xia
David Raffelt
Olivier Salvado
Leonid Churilov
Christopher C. Rowe
Amy Brodtmann

White matter hyperintensities (WMH) are regions of high signal intensity typically identified on fluid attenuated inversion recovery (FLAIR). Although commonly observed in elderly individuals, they are more prevalent in Alzheimer's disease (AD) patients. Given that WMH appear relatively homogeneous on FLAIR, they are commonly partitioned into location- or distance-based classes when investigating their relevance to disease. Since pathology indicates that such lesions are often heterogeneous, probing their microstructure in vivo may provide greater insight than relying on such arbitrary classification schemes. In this study, we investigated WMH in vivo using an advanced diffusion MRI method known as single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD), which models white matter microstructure while accounting for grey matter and CSF compartments. Diffusion MRI data and FLAIR images were obtained from AD (n = 48) and healthy elderly control (n = 94) subjects. WMH were automatically segmented, and classified: (1) as either periventricular or deep; or (2) into three distance-based contours from the ventricles. The 3-tissue profile of WMH enabled their characterisation in terms of white matter-, grey matter-, and fluid-like characteristics of the diffusion signal. Our SS3T-CSD findings revealed substantial heterogeneity in the 3-tissue profile of WMH, both within lesions and across the various classes. Moreover, this heterogeneity information indicated that the use of different commonly used WMH classification schemes can result in different disease-based conclusions. We conclude that future studies of WMH in AD would benefit from inclusion of microstructural information when characterising lesions, which we demonstrate can be performed in vivo using SS3T-CSD.

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YNIMG Journal 2020 Journal Article

Three-tissue compositional analysis reveals in-vivo microstructural heterogeneity of white matter hyperintensities following stroke

Wasim Khan
Natalia Egorova
Mohamed Salah Khlif
Remika Mito
Thijs Dhollander
Amy Brodtmann

White matter hyperintensities (WMHs) are frequently observed on brain scans of older individuals and are associated with cognitive impairment and vascular brain burden. Recent studies have shown that WMHs may only represent an extreme end of a diffuse pathological spectrum of white matter (WM) degeneration. The present study investigated the microstructural characteristics of WMHs using an advanced diffusion MRI modelling approach known as Single-Shell 3-Tissue Constrained Spherical Deconvolution (SS3T-CSD), which provides information on different tissue compartments within each voxel. The SS3T-CSD method may provide complementary information in the interpretation of pathological tissue through the tissue-specific microstructural compositions of WMHs. Data were obtained from stroke patients enrolled in the Cognition and Neocortical Volume After Stroke (CANVAS) study, a study examining brain volume and cognition after stroke. WMHs were segmented using an automated method, based on fluid attenuated inversion recovery (FLAIR) images. Automated tissue segmentation was used to identify normal-appearing white matter (NAWM). WMHs were classified into juxtaventricular, periventricular and deep lesions, based on their distance from the ventricles (3–10 mm). We aimed to compare in stroke participants the microstructural composition of the different lesion classes of WMHs and compositions of NAWM to assess the in-vivo heterogeneity of these lesions. Results showed that the 3-tissue composition significantly differed between WMHs classes and NAWM. Specifically, the 3-tissue compositions for juxtaventricular and periventricular WMHs both exhibited a relatively greater fluid-like (free water) content, which is compatible with a presence of interstitial fluid accumulation, when compared to deep WMHs. These findings provide evidence of microstructural heterogeneity of WMHs in-vivo and may support new insights for understanding the role of WMH development in vascular neurodegeneration.

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YNICL Journal 2019 Journal Article

A comparison of automated segmentation and manual tracing in estimating hippocampal volume in ischemic stroke and healthy control participants

Mohamed Salah Khlif
Natalia Egorova
Emilio Werden
Alberto Redolfi
Marina Boccardi
Charles S. DeCarli
Evan Fletcher
Baljeet Singh

Manual quantification of the hippocampal atrophy state and rate is time consuming and prone to poor reproducibility, even when performed by neuroanatomical experts. The automation of hippocampal segmentation has been investigated in normal aging, epilepsy, and in Alzheimer's disease. Our first goal was to compare manual and automated hippocampal segmentation in ischemic stroke and to, secondly, study the impact of stroke lesion presence on hippocampal volume estimation. We used eight automated methods to segment T1-weighted MR images from 105 ischemic stroke patients and 39 age-matched controls sampled from the Cognition And Neocortical Volume After Stroke (CANVAS) study. The methods were: AdaBoost, Atlas-based Hippocampal Segmentation (ABHS) from the IDeALab, Computational Anatomy Toolbox (CAT) using 3 atlas variants (Hammers, LPBA40 and Neuromorphometics), FIRST, FreeSurfer v5.3, and FreeSurfer v6.0-Subfields. A number of these methods were employed to re-segment the T1 images for the stroke group after the stroke lesions were masked (i.e., removed). The automated methods were assessed on eight measures: process yield (i.e. segmentation success rate), correlation (Pearson's R and Shrout's ICC), concordance (Lin's RC and Kandall's W), slope 'a' of best-fit line from correlation plots, percentage of outliers from Bland-Altman plots, and significance of control-stroke difference. We eliminated the redundant measures after analysing between-measure correlations using Spearman's rank correlation. We ranked the automated methods based on the sum of the remaining non-redundant measures where each measure ranged between 0 and 1. Subfields attained an overall score of 96.3%, followed by AdaBoost (95.0%) and FIRST (94.7%). CAT using the LPBA40 atlas inflated hippocampal volumes the most, while the Hammers atlas returned the smallest volumes overall. FIRST (p = 0.014), FreeSurfer v5.3 (p = 0.007), manual tracing (p = 0.049), and CAT using the Neuromorphometics atlas (p = 0.017) all showed a significantly reduced hippocampal volume mean for the stroke group compared to control at three months. Moreover, masking of the stroke lesions prior to segmentation resulted in hippocampal volumes which agreed less with manual tracing. These findings recommend an automated segmentation without lesion masking as a more reliable procedure for the estimation of hippocampal volume in ischemic stroke.

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YNICL Journal 2019 Journal Article

Assessment of longitudinal hippocampal atrophy in the first year after ischemic stroke using automatic segmentation techniques

Mohamed Salah Khlif
Emilio Werden
Natalia Egorova
Marina Boccardi
Alberto Redolfi
Laura Bird
Amy Brodtmann

We assessed first-year hippocampal atrophy in stroke patients and healthy controls using manual and automated segmentations: AdaBoost, FIRST (fsl/v5.0.8), FreeSurfer/v5.3 and v6.0, and Subfields (in FreeSurfer/v6.0). We estimated hippocampal volumes in 39 healthy controls and 124 stroke participants at three months, and 38 controls and 113 stroke participants at one year. We used intra-class correlation, concordance, and reduced major axis regression to assess agreement between automated and 'Manual' estimations. A linear mixed-effect model was used to characterize hippocampal atrophy. Overall, hippocampal volumes were reduced by 3.9% in first-ever stroke and 9.2% in recurrent stroke at three months post-stroke, with comparable ipsi-and contra-lesional reductions in first-ever stroke. Mean atrophy rates between time points were 0.5% for controls and 1.0% for stroke patients (0.6% contra-lesionally, 1.4% ipsi-lesionally). Atrophy rates in left and right-hemisphere strokes were comparable. All methods revealed significant volume change in first-ever and ipsi-lesional stroke (p < 0.001). Hippocampal volume estimation was not impacted by hemisphere, study group, or scan time point, but rather, by the interaction between the automated segmentation method and hippocampal size. Compared to Manual, Subfields and FIRST recorded the lowest bias. FreeSurfer/v5.3 overestimated volumes the most for large hippocampi, while FIRST was the most accurate in estimating small volumes. AdaBoost performance was average. Our findings suggest that first-year ipsi-lesional hippocampal atrophy rate especially in first-ever stroke, is greater than atrophy rates in healthy controls and contra-lesional stroke. Subfields and FIRST can complementarily be effective in characterizing the hippocampal atrophy in healthy and stroke cohorts.

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YNICL Journal 2017 Journal Article

Fractional amplitude of low-frequency fluctuations (fALFF) in post-stroke depression

Natalia Egorova
Michele Veldsman
Toby Cumming
Amy Brodtmann

Depression is a common outcome following stroke, associated with reduced quality of life and poorer recovery. Despite attempts to associate depression symptoms with specific lesion sites, the neural basis of post-stroke depression remains poorly understood. Resting state fMRI has provided new insights into the neural underpinnings of post-stroke depression, but has been limited to connectivity analyses exploring interregional correlations in the time-course of activity. Other aspects of resting state BOLD signal remain unexamined. Measuring the amplitude of low frequency fluctuations allows the detection of spontaneous neural activity across the whole brain. It provides complementary information about frequency-specific local neural activity. We calculated the fractional amplitude of low frequency fluctuations (fALFF) in a group of 64 participants scanned 3 months post-stroke. Twenty showed depression symptoms when assessed with the Patient Health Questionnaire (PHQ-9). We performed analyses in both the typical 0.01-0.08 Hz range, as well as separately in the slow-5 (0.01-0.027 Hz) and slow-4 (0.027-0.073 Hz) ranges. We found significantly higher fALFF in the depressed compared to non-depressed participants in the left dorsolateral prefrontal cortex (DLPFC) and the right precentral gyrus, and a significant association between higher depression scores and higher fALFF in the left insula. The group differences were detected in the slow-5 fluctuations, while the association with depression severity was observed in the slow-4 range. We conclude that post-stroke depression can be characterised by aberrant spontaneous local neural activity, which in small samples could be a more sensitive measure than lesion volume and location.

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YNICL Journal 2015 Journal Article

Cortical thickness estimation in longitudinal stroke studies: A comparison of 3 measurement methods

Qi Li
Heath Pardoe
Renee Lichter
Emilio Werden
Audrey Raffelt
Toby Cumming
Amy Brodtmann

There is considerable controversy about the causes of cognitive decline after stroke, with evidence for both the absence and coexistence of Alzheimer pathology. A reduction in cortical thickness has been shown to be an important biomarker for the progression of many neurodegenerative diseases, including Alzheimer's disease (AD). However, brain volume changes following stroke are not well described. Cortical thickness estimation presents an ideal way to detect regional and global post-stroke brain atrophy. In this study, we imaged a group of patients in the first month after stroke and at 3 months. We compared three methods of estimating cortical thickness on unmasked images: one surface-based (FreeSurfer) and two voxel-based methods (a Laplacian method and a registration method, DiRecT). We used three benchmarks for our analyses: accuracy of segmentation (especially peri-lesional performance), reproducibility, and biological validity. We found important differences between these methods in cortical thickness values and performance in high curvature areas and peri-lesional regions, but similar reproducibility metrics. FreeSurfer had less reliance on manual boundary correction than the other two methods, while reproducibility was highest in the Laplacian method. A discussion of the caveats for each method and recommendations for use in a stroke population is included. We conclude that both surface- and voxel-based methods are valid for estimating cortical thickness in stroke populations.

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YNIMG Journal 2003 Journal Article

The functional magnetic resonance imaging hemodynamic response to faces remains stable until the ninth decade

Amy Brodtmann
Aina Puce
Ari Syngeniotis
David Darby
Geoffrey Donnan

The effects of aging on blood oxygen level dependent signal changes and the hemodynamic response (HDR) remain controversial. Using functional magnetic resonance (MR) imaging, we examined the HDR properties and activated voxel counts in striate and extrastriate cortex in 18 healthy elderly subjects in response to a simple visual paradigm. Subjects of equal number and gender were prospectively separated into groups from the seventh, eighth, and ninth decades. Activation data were compared with those of 6 healthy subjects aged 30–39 under the same conditions. We found no systematic difference in HDR amplitude, shape, or latency across these groups. However, increasing age over 60 was associated with a significant decline in activated voxel counts, relative to the young controls. The results are discussed in comparison with previously published studies and in the context of the effects of aging on MR signal change. While robust activation can be produced in the striate and extrastriate cortices until the end of the ninth decade, caution should be exercised when comparing data from subjects in different decades. As functional magnetic resonance imaging is increasingly being used to examine patients with stroke and dementia, these results emphasize the importance of careful selection and age matching of control subjects when comparing with a patient population affected by disease processes associated with aging.

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