Yasheng Chen

Temporal and Spatial Development of Axonal Maturation and Myelination of White Matter in the Developing Brain

BACKGROUND AND PURPOSE: Diffusion tensor imaging (DTI) has been widely used to investigate the development of white matter (WM). However, information about this development in healthy children younger than 2 years of age is lacking, and most previous studies have only measured fractional anisotropy (FA). This study used FA and radial and axonal diffusivities in children younger than 2 years of age, aiming to determine the temporal and spatial development of axonal maturation and myelination of WM in healthy children. MATERIALS AND METHODS: A total of 60 healthy pediatric subjects were imaged by using a 3T MR imaging scanner. They were divided into 3 groups: 20 at 3 weeks, 20 at 1 year of age, and 20 at 2 years of age. All subjects were imaged asleep without sedation. FA and axial and radial diffusivities were obtained. Eight regions of interest were defined, including both central and peripheral WM for measuring diffusion parameters. RESULTS: A significant elevation in FA (P < .0001) and a reduction in axial and radial diffusivities (P < .0001) were observed from 22 days to 1 year of age, whereas only radial diffusivity showed significant changes (P = .0014) from 1 to 2 years of age. The region-of-interest analysis revealed that FA alone may not depict the underlying biologic underpinnings of WM development, whereas directional diffusivities provide more insights into the development of WM. Finally, the spatial development of WM begins from the central to the peripheral WM and from the occipital to the frontal lobes. CONCLUSIONS: With both FA and directional diffusivities, our results demonstrate the temporal and spatial development of WM in healthy children younger than 2 years of age.

Functional Connectivity MR Imaging Reveals Cortical Functional Connectivity in the Developing Brain

BACKGROUND AND PURPOSE: Unlike conventional functional MR imaging where external sensory/cognitive paradigms are needed to specifically activate different regions of the brain, resting functional connectivity MR imaging acquires images in the absence of cognitive demands (a resting condition) and detects brain regions, which are highly temporally correlated. Therefore, resting functional MR imaging is highly suited for the study of brain functional development in pediatric subjects. This study aimed to determine the temporal and spatial patterns of rfc in healthy pediatric subjects between 2 weeks and 2 years of age. MATERIALS AND METHODS: Rfc studies were performed on 85 children: 38 neonates (2–4 weeks of age), 26 one-year-olds, and 21 two-year-olds. All subjects were imaged while asleep; no sedation was used. Six regions of interest were chosen, including the primary motor, sensory, and visual cortices in each hemisphere. Mean signal intensity of each region of interest was used to perform correlation analysis pixel by pixel throughout the entire brain, identifying regions with high temporal correlation. RESULTS: Functional connectivity was observed in all subjects in the sensorimotor and visual areas. The percent brain volume exhibiting rfc and the strength of rfc continued to increase from 2 weeks to 2 years. The growth trajectories of the percent brain volume of rfc appeared to differ between the sensorimotor and visual areas, whereas the z-score was similar. The percent brain volume of rfc in the sensorimotor area was significantly larger than that in the visual area for subjects 2 weeks of age (P = .008) and 1-year-olds (P = .017) but not for the 2-year-olds. CONCLUSIONS: These findings suggest that rfc in the sensorimotor precedes that in the visual area from 2 weeks to 1 year but becomes comparable at 2 years. In contrast, the comparable z-score values between the sensorimotor and visual areas for all age groups suggest a disassociation between percent brain volume and the strength of cortical rfc.

Development trends of white matter connectivity in the first years of life

The human brain is organized into a collection of interacting networks with specialized functions to support various cognitive functions. Recent research has reached a consensus that the brain manifests small-world topology, which implicates both global and local efficiency at minimal wiring costs, and also modular organization, which indicates functional segregation and specialization. However, the important questions of how and when the small-world topology and modular organization come into existence remain largely unanswered. Taking a graph theoretic approach, we attempt to shed light on this matter by an in vivo study, using diffusion tensor imaging based fiber tractography, on 39 healthy pediatric subjects with longitudinal data collected at average ages of 2 weeks, 1 year, and 2 years. Our results indicate that the small-world architecture exists at birth with efficiency that increases in later stages of development. In addition, we found that the networks are broad scale in nature, signifying the existence of pivotal connection hubs and resilience of the brain network to random and targeted attacks. We also observed, with development, that the brain network seems to evolve progressively from a local, predominantly proximity based, connectivity pattern to a more distributed, predominantly functional based, connectivity pattern. These observations suggest that the brain in the early years of life has relatively efficient systems that may solve similar information processing problems, but in divergent ways.

White matter abnormalities revealed by diffusion tensor imaging in non-demented and demented HIV+ patients.

HIV associated dementia (HAD) is the most advanced stage of central nervous system disease caused by HIV infection. Previous studies have demonstrated that patients with HAD exhibit greater cerebral and basal ganglia atrophy than non-demented HIV+ (HND) patients. However, the extent to which white matter is affected in HAD patients compared to HND patients remains elusive. This study is designed to address the potential white matter abnormalities through the utilization of diffusion tensor imaging (DTI) in both HND and HAD patients. DTI and T1-weighted images were acquired from 18 healthy controls, 21 HND and 8 HAD patients. T1 image-based registration was performed to 1) parcellate the whole brain white matter into major white matter regions, including frontal, parietal, temporal and occipital white matter, corpus callosum and internal capsule for statistical comparisons of the mean DTI values, and 2) warp all DTI parametric images towards the common template space for voxel-based analysis. The statistical comparisons were performed with four DTI parameters including fractional anisotropy (FA), mean (MD), axial (AD), and radial (RD) diffusivities. With Whitney U tests on the mean DTI values, both HND and HAD demonstrated significant differences from the healthy control in multiple white matter regions. In addition, HAD patients exhibited significantly elevated MD and RD in the parietal white matter when compared to HND patients. In the voxel-based analysis, widespread abnormal regions were identified for both HND and HAD patients, although a much larger abnormal volume was observed in HAD patients for all four DTI parameters. Furthermore, both region of interest (ROI) based and voxel-based analyses revealed that RD was affected to a much greater extent than AD by HIV infection, which may suggest that demyelination is the prominent disease progression in white matter.

Tag surface reconstruction and tracking of myocardial beads from SPAMM-MRI with parametric B-spline surfaces

Magnetic resonance imaging (MRI) is unique in its ability to noninvasively and selectively alter tissue magnetization, and create tag planes intersecting image slices. The resulting grid of signal voids allows for tracking deformations of tissues in otherwise homogeneous-signal myocardial regions. Here, the authors propose a specific spatial modulation of magnetization (SPAMM) imaging protocol together with efficient techniques for measurement of three-dimensional (3-D) motion of material points of the human heart (referred to as myocardial beads) from images collected with the SPAMM method. The techniques make use of tagged images in orthogonal views by explicitly reconstructing 3-D B-spline surface representation of tag planes (tag planes in two orthogonal orientations intersecting the short-axis (SA) image slices and tag planes in an orientation orthogonal to the short-axis tag planes intersecting long-axis (LA) image slices). The developed methods allow for viewing deformations of 3-D tag surfaces, spatial correspondence of long-axis and short-axis image slice and tag positions, as well as nonrigld movement of myocardial beads as a function of time.

Practical consideration for 3T imaging

In the past 10 to 15 years, 1.5T has been one of the most commonly used field strengths for day-to-day clinical operations. However, recent advances in high field technology and the increased availability of high field (> 1.5T) human scanners have opened the doors for a variety of exciting improvements in clinical and research applications of MR imaging. In particular, 3T has continued to gain wide acceptance as one of the main field strengths for clinical and research studies. Therefore, in this article the authors focus on the pros and cons of 3T imaging and comparisons between results obtained at 3T and 1.5T.

Diffusion tensor imaging based network analysis detects alterations of neuroconnectivity in patients with clinically early relapsing‐remitting multiple sclerosis

Although it is inarguable that conventional MRI (cMRI) has greatly contributed to the diagnosis and assessment of multiple sclerosis (MS), cMRI does not show close correlation with clinical findings or pathologic features, and is unable to predict prognosis or stratify disease severity. To this end, diffusion tensor imaging (DTI) with tractography and neuroconnectivity analysis may assist disease assessment in MS. We, therefore, attempted this pilot study for initial assessment of early relapsing‐remitting MS (RRMS). Neuroconnectivity analysis was used for evaluation of 24 early RRMS patients within 2 years of presentation, and compared to the network measures of a group of 30 age‐and‐gender‐matched normal control subjects. To account for the situation that the connections between two adjacent regions may be disrupted by an MS lesion, a new metric, network communicability, was adopted to measure both direct and indirect connections. For each anatomical area, the brain network communicability and average path length were computed and compared to characterize the network changes in efficiencies. Statistically significant (P < 0.05) loss of communicability was revealed in our RRMS cohort, particularly in the frontal and hippocampal/parahippocampal regions as well as the motor strip and occipital lobes. Correlation with the 25‐foot Walk test with communicability measures in the left superior frontal (r = −0.71) as well as the left superior temporal gyrus (r = −0.43) and left postcentral gyrus (r = −0.41) were identified. Additionally identified were increased communicability between the deep gray matter structures (left thalamus and putamen) with the major interhemispheric and intrahemispheric white matter tracts, the corpus callosum, and cingulum, respectively. These foci of increased communicability are thought to represent compensatory changes. The proposed DTI‐based neuroconnectivity analysis demonstrated quantifiable, structurally relevant alterations of fiber tract connections in early RRMS and paves the way for longitudinal studies in larger patient groups. Hum Brain Mapp 34:3376–3391, 2013.

A MAP framework for tag line detection in SPAMM data using Markov random fields on the B-spline solid

Magnetic resonance (MR) tagging is a technique for measuring heart deformations through creation of a stripe grid pattern on cardiac images. In this paper, we present a maximum a posteriori (MAP) framework for detecting tag lines using a Markov random field (MRF) defined on the lattice generated by three-dimensional (3-D) and four-dimensional (4-D) (3-D+t) uniform sampling of B-spline models. In the 3-D case, MAP estimation is cast for detecting present tag features in the current image given an initial solid from the previous frame (the initial undeformed solid is manually positioned by clicking on corner points of a cube). The method also allows the parameters of the solid model, including the number of knots and the spline order, to be adjusted within the same framework. Fitting can start with a solid with less knots and lower spline order and proceed to one with more knots and/or higher order so as to achieve more accuracy and/or higher order of smoothness. In the 4-D case, the initial model is considered to be the linear interpolation of a sequence of optimal solids obtained from 3-D tracking. The same framework proposed for the 3-D case can once again be applied to arrive at a 4-D B-spline model with a higher temporal order.

Evaluation of MR-Derived Cerebral Oxygen Metabolic Index in Experimental Hyperoxic Hypercapnia, Hypoxia, and Ischemia

Background and Purpose— A noninvasive MRI method to measure cerebral oxygen metabolism has the potential to assess tissue viability during cerebral ischemia. The purposes of this study were to validate MR oxygenation measurements across a wide range of global cerebral oxygenation and to examine the spatiotemporal evolution of oxygen metabolism during focal middle cerebral artery occlusion in rats. Methods— A group of rats (n=28) under normal, hyperoxic hypercapnia and hypoxia were studied to compare MR-measured cerebral oxygen saturation (O2SatMRv) with blood gas oximetry measurements in the jugular vein (O2SatJV) and superior sagittal sinus (O2SatSSS). In a separate group of rats (n=31), MR-measured cerebral oxygen metabolic index (MR_COMI) was acquired at multiple time points during middle cerebral artery occlusion. Histogram analysis was performed on the normalized MR_COMI (rMR_COMI) to examine evolution of oxygen metabolism during acute ischemia. Results— Highly linear relationships were obtained between O2SatMRv and O2SatJV/O2SatSSS in rats under global cerebral oxygenation alterations. In the focal ischemia study, rMR_COMI values were significantly lower within the areas of eventual infarction than other regions. Moreover, the rMR_COMI values within the ischemic territory decreased with time, concomitant with an increase in the number of voxels with severely impaired oxygen metabolism. Conclusion— Accurate estimates of O2SatMRv can be obtained across a broad and physiologically relevant range of cerebral oxygenation. Furthermore, this method demonstrates a dynamic alteration of cerebral oxygen metabolism during acute ischemia in rats.

MR-based attenuation correction for PET/MRI neurological studies with continuous-valued attenuation coefficients for bone through a conversion from R2* to CT-Hounsfield units

AIM MR-based correction for photon attenuation in PET/MRI remains challenging, particularly for neurological applications requiring quantitation of data. Existing methods are either not sufficiently accurate or are limited by the computation time required. The goal of this study was to develop an MR-based attenuation correction method that accurately separates bone tissue from air and provides continuous-valued attenuation coefficients for bone. MATERIALS AND METHODS PET/MRI and CT datasets were obtained from 98 subjects (mean age [±SD]: 66yrs [±9.8], 57 females) using an IRB-approved protocol and with informed consent. Subjects were injected with 352±29MBq of (18)F-Florbetapir tracer, and PET acquisitions were begun either immediately or 50min after injection. CT images of the head were acquired separately using a PET/CT system. Dual echo ultrashort echo-time (UTE) images and two-point Dixon images were acquired. Regions of air were segmented via a threshold of the voxel-wise multiplicative inverse of the UTE echo 1 image. Regions of bone were segmented via a threshold of the R2* image computed from the UTE echo 1 and UTE echo 2 images. Regions of fat and soft tissue were segmented using fat and water images decomposed from the Dixon images. Air, fat, and soft tissue were assigned linear attenuation coefficients (LACs) of 0, 0.092, and 0.1cm(-1), respectively. LACs for bone were derived from a regression analysis between corresponding R2* and CT values. PET images were reconstructed using the gold standard CT method and the proposed CAR-RiDR method. RESULTS The RiDR segmentation method produces mean Dice coefficient±SD across subjects of 0.75±0.05 for bone and 0.60±0.08 for air. The CAR model for bone LACs greatly improves accuracy in estimating CT values (28.2%±3.0 mean error) compared to the use of a constant CT value (46.9%±5.8, p<10(-6)). Finally, the CAR-RiDR method provides a low whole-brain mean absolute percent-error (MAPE±SD) in PET reconstructions across subjects of 2.55%±0.86. Regional PET errors were also low and ranged from 0.88% to 3.79% in 24 brain ROIs. CONCLUSION We propose an MR-based attenuation correction method (CAR-RiDR) for quantitative PET neurological imaging. The proposed method employs UTE and Dixon images and consists of two novel components: 1) accurate segmentation of air and bone using the inverse of the UTE1 image and the R2* image, respectively and 2) estimation of continuous LAC values for bone using a regression between R2* and CT-Hounsfield units. From our analysis, we conclude that the proposed method closely approaches (<3% error) the gold standard CT-scaled method in PET reconstruction accuracy.