Publications by Year: 2017

2017

Ou Y, Zöllei L, Retzepi K, Castro V, Bates S V, Pieper S, Andriole KP, Murphy SN, Gollub RL, Grant PE. Using Clinically Acquired MRI to Construct Age-specific Atlases: Quantifying Spatiotemporal ADC Changes from Birth to 6-year Old. Hum Brain Mapp. 2017;38(6):3052–68.

Diffusion imaging is critical for detecting acute brain injury. However, normal apparent diffusion coefficient (ADC) maps change rapidly in early childhood, making abnormality detection difficult. In this article, we explored clinical PACS and electronic healthcare records (EHR) to create age-specific ADC atlases for clinical radiology reference. Using the EHR and three rounds of multiexpert reviews, we found ADC maps from 201 children 0-6 years of age scanned between 2006 and 2013 who had brain MRIs with no reported abnormalities and normal clinical evaluations 2+ years later. These images were grouped in 10 age bins, densely sampling the first 1 year of life (5 bins, including neonates and 4 quarters) and representing the 1-6 year age range (an age bin per year). Unbiased group-wise registration was used to construct ADC atlases for 10 age bins. We used the atlases to quantify (a) cross-sectional normative ADC variations; (b) spatiotemporal heterogeneous ADC changes; and (c) spatiotemporal heterogeneous volumetric changes. The quantified age-specific whole-brain and region-wise ADC values were compared to those from age-matched individual subjects in our study and in multiple existing independent studies. The significance of this study is that we have shown that clinically acquired images can be used to construct normative age-specific atlases. These first of their kind age-specific normative ADC atlases quantitatively characterize changes of myelination-related water diffusion in the first 6 years of life. The quantified voxel-wise spatiotemporal ADC variations provide standard references to assist radiologists toward more objective interpretation of abnormalities in clinical images. Our atlases are available at https://www.nitrc.org/projects/mgh_adcatlases.

Diffusion MRI has been proposed as a non-invasive technique for axonal diameter mapping. However, accurate estimation of small diameters requires strong gradients, which is a challenge for the transition of the technique from preclinical to clinical MRI scanners, since these have weaker gradients. In this work, we develop a framework to estimate the lower bound for accurate diameter estimation, which we refer to as the resolution limit. We analyse only the contribution from the intra-axonal space and assume that axons can be represented by impermeable cylinders. To address the growing interest in using techniques for diffusion encoding that go beyond the conventional single diffusion encoding (SDE) sequence, we present a generalised analysis capable of predicting the resolution limit regardless of the gradient waveform. Using this framework, waveforms were optimised to minimise the resolution limit. The results show that, for parallel cylinders, the SDE experiment is optimal in terms of yielding the lowest possible resolution limit. In the presence of orientation dispersion, diffusion encoding sequences with square-wave oscillating gradients were optimal. The resolution limit for standard clinical MRI scanners (maximum gradient strength 60-80 mT/m) was found to be between 4 and 8 μm, depending on the noise levels and the level of orientation dispersion. For scanners with a maximum gradient strength of 300 mT/m, the limit was reduced to between 2 and 5 μm.

Balasubramanian M, Wells WM, Ives JR, Britz P, Mulkern RV, Orbach DB. RF Heating of Gold Cup and Conductive Plastic Electrodes during Simultaneous EEG and MRI. Neurodiagn J. 2017;57(1):69–83.

PURPOSE: To investigate the heating of EEG electrodes during magnetic resonance imaging (MRI) scans and to better understand the underlying physical mechanisms with a focus on the antenna effect. MATERIALS AND METHODS: Gold cup and conductive plastic electrodes were placed on small watermelons with fiberoptic probes used to measure electrode temperature changes during a variety of 1.5T and 3T MRI scans. A subset of these experiments was repeated on a healthy human volunteer. RESULTS: The differences between gold and plastic electrodes did not appear to be practically significant. For both electrode types, we observed heating below 4°C for straight wires whose lengths were multiples of ½ the radiofrequency (RF) wavelength and stronger heating (over 15°C) for wire lengths that were odd multiples of ¼ RF wavelength, consistent with the antenna effect. CONCLUSIONS: The antenna effect, which has received little attention so far in the context of EEG-MRI safety, can play as significant a role as the loop effect (from electromagnetic induction) in the heating of EEG electrodes, and therefore wire lengths that are odd multiples of ¼ RF wavelength should be avoided. These results have important implications for the design of EEG electrodes and MRI studies as they help to minimize the risk to patients undergoing MRI with EEG electrodes in place.

Tax CMW, Westin CF, Haije TD, Fuster A, Viergever MA, Calabrese E, Florack L, Leemans A. Quantifying the Brain’s Sheet Structure with Normalized Convolution. Med Image Anal. 2017;39:162–77.

The hypothesis that brain pathways form 2D sheet-like structures layered in 3D as "pages of a book" has been a topic of debate in the recent literature. This hypothesis was mainly supported by a qualitative evaluation of "path neighborhoods" reconstructed with diffusion MRI (dMRI) tractography. Notwithstanding the potentially important implications of the sheet structure hypothesis for our understanding of brain structure and development, it is still considered controversial by many for lack of quantitative analysis. A means to quantify sheet structure is therefore necessary to reliably investigate its occurrence in the brain. Previous work has proposed the Lie bracket as a quantitative indicator of sheet structure, which could be computed by reconstructing path neighborhoods from the peak orientations of dMRI orientation density functions. Robust estimation of the Lie bracket, however, is challenging due to high noise levels and missing peak orientations. We propose a novel method to estimate the Lie bracket that does not involve the reconstruction of path neighborhoods with tractography. This method requires the computation of derivatives of the fiber peak orientations, for which we adopt an approach called normalized convolution. With simulations and experimental data we show that the new approach is more robust with respect to missing peaks and noise. We also demonstrate that the method is able to quantify to what extent sheet structure is supported for dMRI data of different species, acquired with different scanners, diffusion weightings, dMRI sampling schemes, and spatial resolutions. The proposed method can also be used with directional data derived from other techniques than dMRI, which will facilitate further validation of the existence of sheet structure.

Essayed WI, Zhang F, Unadkat P, Cosgrove R, Golby AJ, Donnell LJO. White Matter Tractography for Neurosurgical Planning: A Topography-based Review of the Current State of the Art. Neuroimage Clin. 2017;15:659–72.

We perform a review of the literature in the field of white matter tractography for neurosurgical planning, focusing on those works where tractography was correlated with clinical information such as patient outcome, clinical functional testing, or electro-cortical stimulation. We organize the review by anatomical location in the brain and by surgical procedure, including both supratentorial and infratentorial pathologies, and excluding spinal cord applications. Where possible, we discuss implications of tractography for clinical care, as well as clinically relevant technical considerations regarding the tractography methods. We find that tractography is a valuable tool in variable situations in modern neurosurgery. Our survey of recent reports demonstrates multiple potentially successful applications of white matter tractography in neurosurgery, with progress towards overcoming clinical challenges of standardization and interpretation.

Koppelmans V, Pasternak O, Bloomberg JJ, De Dios YE, Wood SJ, Riascos R, Reuter-Lorenz PA, Kofman IS, Mulavara AP, Seidler RD. Intracranial Fluid Redistribution but No White Matter Microstructural Changes During a Spaceflight Analog. Sci Rep. 2017;7(1):3154.

The neural correlates of spaceflight-induced sensorimotor impairments are unknown. Head down-tilt bed rest (HDBR) serves as a microgravity analog because it mimics the headward fluid shift and axial body unloading of spaceflight. We investigated focal brain white matter (WM) changes and fluid shifts during 70 days of 6° HDBR in 16 subjects who were assessed pre (2x), during (3x), and post-HDBR (2x). Changes over time were compared to those in control subjects (n = 12) assessed four times over 90 days. Diffusion MRI was used to assess WM microstructure and fluid shifts. Free-Water Imaging was used to quantify distribution of intracranial extracellular free water (FW). Additionally, we tested whether WM and FW changes correlated with changes in functional mobility and balance measures. HDBR resulted in FW increases in fronto-temporal regions and decreases in posterior-parietal regions that largely recovered by two weeks post-HDBR. WM microstructure was unaffected by HDBR. FW decreases in the post-central gyrus and precuneus correlated negatively with balance changes. We previously reported that gray matter increases in these regions were associated with less HDBR-induced balance impairment, suggesting adaptive structural neuroplasticity. Future studies are warranted to determine causality and underlying mechanisms.

We present an efficient probabilistic model of anatomical variability in a linear space of initial velocities of diffeomorphic transformations and demonstrate its benefits in clinical studies of brain anatomy. To overcome the computational challenges of the high dimensional deformation-based descriptors, we develop a latent variable model for principal geodesic analysis (PGA) based on a low dimensional shape descriptor that effectively captures the intrinsic variability in a population. We define a novel shape prior that explicitly represents principal modes as a multivariate complex Gaussian distribution on the initial velocities in a bandlimited space. We demonstrate the performance of our model on a set of 3D brain MRI scans from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Our model yields a more compact representation of group variation at substantially lower computational cost than the state-of-the-art method such as tangent space PCA (TPCA) and probabilistic principal geodesic analysis (PPGA) that operate in the high dimensional image space.

Liao R, Ning L, Chen Z, Rigolo L, Gong S, Pasternak O, Golby AJ, Rathi Y, Donnell LJO. Performance of Unscented Kalman Filter Tractography in Edema: Analysis of the Two-tensor Model. Neuroimage Clin. 2017;15:819–31.

Diffusion MRI tractography is increasingly used in pre-operative neurosurgical planning to visualize critical fiber tracts. However, a major challenge for conventional tractography, especially in patients with brain tumors, is tracing fiber tracts that are affected by vasogenic edema, which increases water content in the tissue and lowers diffusion anisotropy. One strategy for improving fiber tracking is to use a tractography method that is more sensitive than the traditional single-tensor streamline tractography. We performed experiments to assess the performance of two-tensor unscented Kalman filter (UKF) tractography in edema. UKF tractography fits a diffusion model to the data during fiber tracking, taking advantage of prior information from the previous step along the fiber. We studied UKF performance in a synthetic diffusion MRI digital phantom with simulated edema and in retrospective data from two neurosurgical patients with edema affecting the arcuate fasciculus and corticospinal tracts. We compared the performance of several tractography methods including traditional streamline, UKF single-tensor, and UKF two-tensor. To provide practical guidance on how the UKF method could be employed, we evaluated the impact of using various seed regions both inside and outside the edematous regions, as well as the impact of parameter settings on the tractography sensitivity. We quantified the sensitivity of different methods by measuring the percentage of the patient-specific fMRI activation that was reached by the tractography. We expected that diffusion anisotropy threshold parameters, as well as the inclusion of a free water model, would significantly influence the reconstruction of edematous WM fiber tracts, because edema increases water content in the tissue and lowers anisotropy. Contrary to our initial expectations, varying the fractional anisotropy threshold and including a free water model did not affect the UKF two-tensor tractography output appreciably in these two patient datasets. The most effective parameter for increasing tracking sensitivity was the generalized anisotropy (GA) threshold, which increased the length of tracked fibers when reduced to 0.075. In addition, the most effective seeding strategy was seeding in the whole brain or in a large region outside of the edema. Overall, the main contribution of this study is to provide insight into how UKF tractography can work, using a two-tensor model, to begin to address the challenge of fiber tract reconstruction in edematous regions near brain tumors.

Kikinis Z, Muehlmann M, Pasternak O, Peled S, Kulkarni P, Ferris C, Bouix S, Rathi Y, Koerte IK, Pieper S, Yarmarkovich A, Porter CL, Kristal BS, Shenton ME. Diffusion Imaging of Mild Traumatic Brain Injury in the Impact Accelerated Rodent Model: A Pilot Study. Brain Inj. 2017;31(10):1376–81.

PRIMARY OBJECTIVE: There is a need to understand pathologic processes of the brain following mild traumatic brain injury (mTBI). Previous studies report axonal injury and oedema in the first week after injury in a rodent model. This study aims to investigate the processes occurring 1 week after injury at the time of regeneration and degeneration using diffusion tensor imaging (DTI) in the impact acceleration rat mTBI model. RESEARCH DESIGN: Eighteen rats were subjected to impact acceleration injury, and three rats served as sham controls. Seven days post injury, DTI was acquired from fixed rat brains using a 7T scanner. Group comparison of Fractional Anisotropy (FA) values between traumatized and sham animals was performed using Tract-Based Spatial Statistics (TBSS), a method that we adapted for rats. MAIN OUTCOMES AND RESULTS: TBSS revealed white matter regions of the brain with increased FA values in the traumatized versus sham rats, localized mainly to the contrecoup region. Regions of increased FA included the pyramidal tract, the cerebral peduncle, the superior cerebellar peduncle and to a lesser extent the fibre tracts of the corpus callosum, the anterior commissure, the fimbria of the hippocampus, the fornix, the medial forebrain bundle and the optic chiasm. CONCLUSION: Seven days post injury, during the period of tissue reparation in the impact acceleration rat model of mTBI, microstructural changes to white matter can be detected using DTI.

Ji F, Pasternak O, Liu S, Loke YM, Choo BL, Hilal S, Xu X, Ikram MK, Venketasubramanian N, Chen CLH, Zhou J. Distinct White Matter Microstructural Abnormalities and Extracellular Water Increases Relate to Cognitive Impairment in Alzheimer’s Disease with And without Cerebrovascular Disease. Alzheimers Res Ther. 2017;9(1):63.

BACKGROUND: Mixed vascular and neurodegenerative dementia, such as Alzheimer’s disease (AD) with concomitant cerebrovascular disease, has emerged as the leading cause of age-related cognitive impairment. The brain white matter (WM) microstructural changes in neurodegeneration well-documented by diffusion tensor imaging (DTI) can originate from brain tissue or extracellular free water changes. The differential microstructural and free water changes in AD with and without cerebrovascular disease, especially in normal-appearing WM, remain largely unknown. To cover these gaps, we aimed to characterize the WM free water and tissue microstructural changes in AD and mixed dementia as well as their associations with cognition using a novel free water imaging method. METHODS: We compared WM free water and free water-corrected DTI measures as well as white matter hyperintensity (WMH) in patients with AD with and without cerebrovascular disease, patients with vascular dementia, and age-matched healthy control subjects. RESULTS: The cerebrovascular disease groups had higher free water than the non-cerebrovascular disease groups. Importantly, besides the cerebrovascular disease groups, patients with AD without cerebrovascular disease also had increased free water in normal-appearing WM compared with healthy control subjects, reflecting mild vascular damage. Such free water increases in WM or normal-appearing WM (but not WMH) contributed to dementia severity. Whole-brain voxel-wise analysis revealed a close association between widespread free water increases and poorer attention, executive functioning, visual construction, and motor performance, whereas only left hemispheric free water increases were related to language deficits. Moreover, compared with the original DTI metrics, the free water-corrected DTI metric revealed tissue damage-specific (frontal and occipital) microstructural differences between the cerebrovascular disease and non-cerebrovascular disease groups. In contrast to both lobar and subcortical/brainstem free water increases, only focal lobar microstructural damage was associated with poorer cognitive performance. CONCLUSIONS: Our findings suggest that free water analysis isolates probable mild vascular damage from WM microstructural alterations and underscore the importance of normal-appearing WM changes underlying cognitive and functional impairment in AD with and without cerebrovascular disease. Further developed, the combined free water and tissue neuroimaging assays could help in differential diagnosis, treatment planning, and disease monitoring of patients with mixed dementia.