Revealing tumor microstructure with oscillating diffusion encoding MRI in pre-surgical and post-treatment glioma patients.

PURPOSE: We hypothesized that the time-dependent diffusivity at short diffusion times, as measured by oscillating gradient spin echo (OGSE) diffusion MRI, can characterize tissue microstructures in glioma patients. THEORY AND METHODS: Five adult patients with known diffuse glioma, including two pre-surgical and three with new enhancing lesions after treatment for high-grade glioma, were scanned in an ultra-high-performance gradient 3.0T MRI system. OGSE diffusion MRI at 30-100 Hz and pulsed gradient spin echo diffusion imaging (approximated as 0 Hz) were obtained. The ADC and trace-diffusion-weighted image at each acquired frequency were calculated, that is, ADC (f) and TraceDWI (f). RESULTS: In pre-surgical patients, biopsy-confirmed solid enhancing tumor in a high-grade glioblastoma showed higher ADC ( f ) ADC ( 0 Hz ) $$ \frac{\mathrm{ADC}\ (f)}{\mathrm{ADC}\ \left(0\ \mathrm{Hz}\right)} $$ and lower TraceDWI ( f ) TraceDWI ( 0 Hz ) $$ \frac{\mathrm{TraceDWI}\ (f)}{\mathrm{TraceDWI}\ \left(0\ \mathrm{Hz}\right)} $$ , compared to that at same OGSE frequency in a low-grade astrocytoma. In post-treatment patients, the enhancing lesions of two patients who were diagnosed with tumor progression contained more voxels with high ADC ( f ) ADC ( 0 Hz ) $$ \frac{\mathrm{ADC}\ (f)}{\mathrm{ADC}\ \left(0\ \mathrm{Hz}\right)} $$ and low TraceDWI ( f ) TraceDWI ( 0 Hz ) $$ \frac{\mathrm{TraceDWI}\left(\mathrm{f}\right)}{\mathrm{TraceDWI}\left(0\ \mathrm{Hz}\right)} $$ , compared to the enhancing lesions of a patient who was diagnosed with treatment effect. Non-enhancing T2 signal abnormality lesions in both the pre-surgical high-grade glioblastoma and post-treatment tumor progressions showed regions with high ADC ( f ) ADC ( 0 Hz ) $$ \frac{\mathrm{ADC}\ (f)}{\mathrm{ADC}\ \left(0\ \mathrm{Hz}\right)} $$ and low TraceDWI ( f ) TraceDWI ( 0 Hz ) $$ \frac{\mathrm{TraceDWI}\ \left(\mathrm{f}\right)}{\mathrm{TraceDWI}\ \left(0\ \mathrm{Hz}\right)} $$ , consistent with infiltrative tumor. The solid tumor of the glioblastoma, the enhancing lesions of post-treatment tumor progressions, and the suspected infiltrative tumors showed high diffusion time-dependency from 30 to 100 Hz, consistent with high intra-tumoral volume fraction (cellular density). CONCLUSION: Different characteristics of OGSE-based time-dependent diffusivity can reveal heterogenous tissue microstructures that indicate cellular density in glioma patients.

BrainSuite BIDS App: Containerized Workflows for MRI Analysis.

There has been a concerted effort by the neuroimaging community to establish standards for computational methods for data analysis that promote reproducibility and portability. In particular, the Brain Imaging Data Structure (BIDS) specifies a standard for storing imaging data, and the related BIDS App methodology provides a standard for implementing containerized processing environments that include all necessary dependencies to process BIDS datasets using image processing workflows. We present the BrainSuite BIDS App, which encapsulates the core MRI processing functionality of BrainSuite within the BIDS App framework. Specifically, the BrainSuite BIDS App implements a participant-level workflow comprising three pipelines and a corresponding set of group-level analysis workflows for processing the participant-level outputs. The BrainSuite Anatomical Pipeline (BAP) extracts cortical surface models from a T1-weighted (T1w) MRI. It then performs surface-constrained volumetric registration to align the T1w MRI to a labeled anatomical atlas, which is used to delineate anatomical regions of interest in the MRI brain volume and on the cortical surface models. The BrainSuite Diffusion Pipeline (BDP) processes diffusion-weighted imaging (DWI) data, with steps that include coregistering the DWI data to the T1w scan, correcting for geometric image distortion, and fitting diffusion models to the DWI data. The BrainSuite Functional Pipeline (BFP) performs fMRI processing using a combination of FSL, AFNI, and BrainSuite tools. BFP coregisters the fMRI data to the T1w image, then transforms the data to the anatomical atlas space and to the Human Connectome Project's grayordinate space. Each of these outputs can then be processed during group-level analysis. The outputs of BAP and BDP are analyzed using the BrainSuite Statistics in R (bssr) toolbox, which provides functionality for hypothesis testing and statistical modeling. The outputs of BFP can be analyzed using atlas-based or atlas-free statistical methods during group-level processing. These analyses include the application of BrainSync, which synchronizes the time-series data temporally and enables comparison of resting-state or task-based fMRI data across scans. We also present the BrainSuite Dashboard quality control system, which provides a browser-based interface for reviewing the outputs of individual modules of the participant-level pipelines across a study in real-time as they are generated. BrainSuite Dashboard facilitates rapid review of intermediate results, enabling users to identify processing errors and make adjustments to processing parameters if necessary. The comprehensive functionality included in the BrainSuite BIDS App provides a mechanism for rapidly deploying the BrainSuite workflows into new environments to perform large-scale studies. We demonstrate the capabilities of the BrainSuite BIDS App using structural, diffusion, and functional MRI data from the Amsterdam Open MRI Collection's Population Imaging of Psychology dataset.

A hybrid deformable registration method to generate motion-compensated 3D virtual MRI for fusion with interventional real-time 3D ultrasound.

PURPOSE: Ultrasound is often the preferred modality for image-guided therapy or treatment in organs such as liver due to real-time imaging capabilities. However, the reduced conspicuity of tumors in ultrasound images adversely impacts the precision and accuracy of treatment delivery. This problem is compounded by deformable motion due to breathing and other physiological activity. This creates the need for a fusion method to align interventional US with pre-interventional modalities that provide superior soft-tissue contrast (e.g., MRI) to accurately target a structure-of-interest and compensate for liver motion. METHOD: In this work, we developed a hybrid deformable fusion method to align 3D pre-interventional MRI and 3D interventional US volumes to target the structures-of-interest in liver accurately in real-time. The deformable multimodal fusion method involved an offline alignment of a pre-intervention MRI with a pre-intervention US volume using a traditional registration method, followed by real-time prediction of deformation using a trained deep-learning model between interventional US volumes across different respiratory states. This framework enables motion-compensated MRI-US image fusion in real-time for image-guided treatment. RESULTS: The proposed hybrid deformable registration method was evaluated on three healthy volunteers across the pre-intervention MRI and 20 US volume pairs in the free-breathing respiratory cycle. The mean Euclidean landmark distance of three homologous targets in all three volunteers was less than 3 mm for percutaneous liver procedures. CONCLUSIONS: Preliminary results show that clinically acceptable registration accuracies for near real-time, deformable MRI-US fusion can be achieved by our proposed hybrid approach. The proposed combination of traditional and deep-learning deformable registration techniques is thus a promising approach for motion-compensated MRI-US fusion to improve targeting in image-guided liver interventions.

Calibration of concomitant field offsets using phase contrast MRI for asymmetric gradient coils.

PURPOSE: Asymmetric gradient coils introduce zeroth- and first-order concomitant field terms, in addition to higher-order terms common to both asymmetric and symmetric gradients. Salient to compensation strategies is the accurate calibration of the concomitant field spatial offset parameters for asymmetric coils. A method that allows for one-time calibration of the offset parameters is described. THEORY AND METHODS: A modified phase contrast pulse sequence with single-sided bipolar flow encoding is proposed to calibrate the offsets for asymmetric, transverse gradient coils. By fitting the measured phase offsets to different gradient amplitudes, the spatial offsets were calculated by fitting the phase variation. This was used for calibrating real-time pre-emphasis compensation of the zeroth- and first-order concomitant fields. RESULTS: Image quality improvement with the proposed corrections was demonstrated in phantom and healthy volunteers with non-Cartesian and Cartesian trajectory acquisitions. Concomitant field compensation using the calibrated offsets resulted in a residual phase error <3% at the highest gradient amplitude and demonstrated substantial reduction of image blur and slice position/selection artifacts. CONCLUSIONS: The proposed implementation provides an accurate method for calibrating spatial offsets that can be used for real-time concomitant field compensation of zeroth and first-order terms, substantially reducing artifacts without retrospective correction or sequence specific waveform modifications.

What happens to brain outside the thermal ablation zones? An assessment of needle-based therapeutic ultrasound in survival swine.

BACKGROUND: In stereotactic radiosurgery, isodose lines must be considered to determine how surrounding tissue is affected. In thermal ablative therapy, such as laser interstitial thermal therapy (LITT), transcranial MR-guided focused ultrasound (tcMRgFUS), and needle-based therapeutic ultrasound (NBTU), how the surrounding area is affected has not been well studied. OBJECTIVE: We aimed to quantify the transition zone surrounding the ablation core created by magnetic resonance-guided robotically-assisted (MRgRA) delivery of NBTU using multi-slice volumetric 2-D magnetic resonance thermal imaging (MRTI) and subsequent characterization of the resultant tissue damage using histopathologic analysis. METHODS: Four swine underwent MRgRA NBTU using varying duration and wattage for treatment delivery. Serial MRI images were obtained, and the most representative were overlaid with isodose lines and compared to brain tissue acquired postmortem which underwent histopathologic analysis. These results were also compared to predicted volumes using a finite element analysis model. Contralateral brain tissue was used for control data. RESULTS: Intraoperative MRTI thermal isodose contours were characterized and comprehensively mapped to post-operative MRI images and qualitatively compared with histological tissue sections postmortem. NBTU 360° ablations induced smaller lesion volumes (33.19 mm3; 120 s, 3 W; 30.05 mm3, 180 s, 4 W) versus 180° ablations (77.20 mm3, 120 s, 3 W; 109.29 mm3; 180 s; 4 W). MRTI/MRI overlay demonstrated the lesion within the proximal isodose lines. The ablation-zone was characterized by dense macrophage infiltration and glial/neuronal loss as demonstrated by glial fibrillary acidic protein (GFAP) and neurofilament (NF) absence and avid CD163 staining. The transition-zone between lesion and normal brain demonstrated decreased macrophage infiltration and measured ∼345 microns (n - 3). We did not detect overt hemorrhages or signs of edema in the adjacent spared tissue. CONCLUSION: We successfully performed MRgRA NBTU ablation in swine and demonstrated minimal histologic changes extended past the ablation-zone. The lesion was characterized by macrophage infiltration and glial/neuronal loss which decreased through the transition-zone.

Predicting ablation zones with multislice volumetric 2-D magnetic resonance thermal imaging.

BACKGROUND: High-intensity focused ultrasound (HIFU) serves as a noninvasive stereotactic system for the ablation of brain metastases; however, treatments are limited to simple geometries and energy delivery is limited by the high acoustic attenuation of the calvarium. Minimally-invasive magnetic resonance-guided robotically-assisted (MRgRA) needle-based therapeutic ultrasound (NBTU) using multislice volumetric 2-D magnetic resonance thermal imaging (MRTI) overcomes these limitations and has potential to produce less collateral tissue damage than current methods. OBJECTIVE: To correlate multislice volumetric 2-D MRTI volumes with histologically confirmed regions of tissue damage in MRgRA NBTU. METHODS: Seven swine underwent a total of 8 frontal MRgRA NBTU lesions. MRTI ablation volumes were compared to histologic tissue damage on brain sections stained with 2,3,5-triphenyltetrazolium chloride (TTC). Bland-Altman analyses and correlation trends were used to compare MRTI and TTC ablation volumes. RESULTS: Data from the initial and third swine's ablations were excluded due to sub-optimal tissue staining. For the remaining ablations (n = 6), the limits of agreement between the MRTI and histologic volumes ranged from -0.149 cm3 to 0.252 cm3 with a mean difference of 0.052 ± 0.042 cm3 (11.1%). There was a high correlation between the MRTI and histology volumes (r2 = 0.831) with a strong linear relationship (r = 0.868). CONCLUSION: We used a volumetric MRTI technique to accurately track thermal changes during MRgRA NBTU in preparation for human trials. Improved volumetric coverage with MRTI enhanced our delivery of therapy and has far-reaching implications for focused ultrasound in the broader clinical setting.

Modeling of Interstitial Ultrasound Ablation for Continuous Applicator Rotation With MR Validation.

The primary objective of cancer intervention is the selective removal of malignant cells while conserving surrounding healthy tissues. However, the accessibility, size and shape of the cancer can make achieving appropriate margins a challenge. One minimally invasive treatment option for these clinical cases is interstitial needle based therapeutic ultrasound (NBTU). In this work, we develop a finite element model (FEM) capable of simulating continuous rotation of a directional NBTU applicator. The developed model was used to simulate the thermal deposition for different rotation trajectories. The actual thermal deposition patterns for the simulated trajectories were then evaluated using magnetic resonance thermal imaging (MRTI) in a porcine skin gelatin phantom. An MRI-compatible robot was used to control the rotation motion profile of the physical NBTU applicator to match the simulated trajectory. The model showed agreement when compared to experimental measurements with Pearson correlation coefficients greater than 0.839 when comparing temperature fields within an area of 12.6 mm radius from the ultrasound applicator. The average temperature error along a 6.3 mm radius profile from the applicator was 1.27 °C. The model was able to compute 1 s of thermal deposition by the applicator in 0.2 s on average with a 0.1 mm spatial resolution and 0.5 s time steps. The developed simulation demonstrates performance suitable for real-time control which may enable robotically-actuated closed-loop conformal tumor ablation.

Author Correction: Noninvasive sub-organ ultrasound stimulation for targeted neuromodulation.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Oscillating diffusion-encoding with a high gradient-amplitude and high slew-rate head-only gradient for human brain imaging.

PURPOSE: We investigate the importance of high gradient-amplitude and high slew-rate on oscillating gradient spin echo (OGSE) diffusion imaging for human brain imaging and evaluate human brain imaging with OGSE on the MAGNUS head-gradient insert (200 mT/m amplitude and 500 T/m/s slew rate). METHODS: Simulations with cosine-modulated and trapezoidal-cosine OGSE at various gradient amplitudes and slew rates were performed. Six healthy subjects were imaged with the MAGNUS gradient at 3T with OGSE at frequencies up to 100 Hz and b = 450 s/mm2 . Comparisons were made against standard pulsed gradient spin echo (PGSE) diffusion in vivo and in an isotropic diffusion phantom. RESULTS: Simulations show that to achieve high frequency and b-value simultaneously for OGSE, high gradient amplitude, high slew rates, and high peripheral nerve stimulation limits are required. A strong linear trend for increased diffusivity (mean: 8-19%, radial: 9-27%, parallel: 8-15%) was observed in normal white matter with OGSE (20 Hz to 100 Hz) as compared to PGSE. Linear fitting to frequency provided excellent correlation, and using a short-range disorder model provided radial long-term diffusivities of D∞,MD = 911 ± 72 µm2 /s, D∞,PD = 1519 ± 164 µm2 /s, and D∞,RD = 640 ± 111 µm2 /s and correlation lengths of lc,MD = 0.802 ± 0.156 µm, lc,PD = 0.837 ± 0.172 µm, and lc,RD = 0.780 ± 0.174 µm. Diffusivity changes with OGSE frequency were negligible in the phantom, as expected. CONCLUSION: The high gradient amplitude, high slew rate, and high peripheral nerve stimulation thresholds of the MAGNUS head-gradient enables OGSE acquisition for in vivo human brain imaging.

Noninvasive sub-organ ultrasound stimulation for targeted neuromodulation.

Tools for noninvasively modulating neural signaling in peripheral organs will advance the study of nerves and their effect on homeostasis and disease. Herein, we demonstrate a noninvasive method to modulate specific signaling pathways within organs using ultrasound (U/S). U/S is first applied to spleen to modulate the cholinergic anti-inflammatory pathway (CAP), and US stimulation is shown to reduce cytokine response to endotoxin to the same levels as implant-based vagus nerve stimulation (VNS). Next, hepatic U/S stimulation is shown to modulate pathways that regulate blood glucose and is as effective as VNS in suppressing the hyperglycemic effect of endotoxin exposure. This response to hepatic U/S is only found when targeting specific sub-organ locations known to contain glucose sensory neurons, and both molecular (i.e. neurotransmitter concentration and cFOS expression) and neuroimaging results indicate US induced signaling to metabolism-related hypothalamic sub-nuclei. These data demonstrate that U/S stimulation within organs provides a new method for site-selective neuromodulation to regulate specific physiological functions.

Childhood Music Training Induces Change in Micro and Macroscopic Brain Structure: Results from a Longitudinal Study.

Several studies comparing adult musicians and nonmusicians have shown that music training is associated with structural brain differences. It is not been established, however, whether such differences result from pre-existing biological traits, lengthy musical training, or an interaction of the two factors, or if comparable changes can be found in children undergoing music training. As part of an ongoing longitudinal study, we investigated the effects of music training on the developmental trajectory of children's brain structure, over two years, beginning at age 6. We compared these children with children of the same socio-economic background but either involved in sports training or not involved in any systematic after school training. We established at the onset that there were no pre-existing structural differences among the groups. Two years later we observed that children in the music group showed (1) a different rate of cortical thickness maturation between the right and left posterior superior temporal gyrus, and (2) higher fractional anisotropy in the corpus callosum, specifically in the crossing pathways connecting superior frontal, sensory, and motor segments. We conclude that music training induces macro and microstructural brain changes in school-age children, and that those changes are not attributable to pre-existing biological traits.

Using the Anisotropic Laplace Equation to Compute Cortical Thickness.

Automatic computation of cortical thickness is a critical step when investigating neuroanatomical population differences and changes associated with normal development and aging, as well as in neurodegenerative diseases including Alzheimer's and Parkinson's. Limited spatial resolution and partial volume effects, in which more than one tissue type is represented in each voxel, have a significant impact on the accuracy of thickness estimates, particularly if a hard intensity threshold is used to delineate cortical boundaries. We describe a novel method based on the anisotropic heat equation that explicitly accounts for the presence of partial tissue volumes to more accurately estimate cortical thickness. The anisotropic term uses gray matter fractions to incorporate partial tissue voxels into the thickness calculation, as demonstrated through simulations and experiments. We also show that the proposed method is robust to the effects of finite voxel resolution and blurring. In comparison to methods based on hard intensity thresholds, the heat equation based method yields results with in-vivo data that are more consistent with histological findings reported in the literature. We also performed a test-retest study across scanners that indicated improved consistency and robustness to scanner differences.

Temporal Non-Local Means Filtering Reveals Real-Time Whole-Brain Cortical Interactions in Resting fMRI.

Intensity variations over time in resting BOLD fMRI exhibit spatial correlation patterns consistent with a set of large scale cortical networks. However, visualizations of this data on the brain surface, even after extensive preprocessing, are dominated by local intensity fluctuations that obscure larger scale behavior. Our novel adaptation of non-local means (NLM) filtering, which we refer to as temporal NLM or tNLM, reduces these local fluctuations without the spatial blurring that occurs when using standard linear filtering methods. We show examples of tNLM filtering that allow direct visualization of spatio-temporal behavior on the cortical surface. These results reveal patterns of activity consistent with known networks as well as more complex dynamic changes within and between these networks. This ability to directly visualize brain activity may facilitate new insights into spontaneous brain dynamics. Further, temporal NLM can also be used as a preprocessor for resting fMRI for exploration of dynamic brain networks. We demonstrate its utility through application to graph-based functional cortical parcellation. Simulations with known ground truth functional regions demonstrate that tNLM filtering prior to parcellation avoids the formation of false parcels that can arise when using linear filtering. Application to resting fMRI data from the Human Connectome Project shows significant improvement, in comparison to linear filtering, in quantitative agreement with functional regions identified independently using task-based experiments as well as in test-retest reliability.

CORRECTING INHOMOGENEITY-INDUCED DISTORTION IN FMRI USING NON-RIGID REGISTRATION.

Magnetic field inhomogeneities in echo planar images (EPI) can cause large distortion in the phase encoding dimension. In functional MRI (fMRI), this distortion can shift activation loci, increase inter subject variability, and reduce statistical power during group analysis. Distortion correction methods that make use of acquired magnetic field maps have been developed, however, field maps are not always acquired or may not be available to researchers. An alternative approach, which we pursue in this paper, is to estimate the distortion retrospectively by spatially registering the EPI to a structural MRI. We describe a constrained non-linear registration method for correcting fMRI distortion that uses T1-weighted images and does not require field maps. We compared resting state results from uncorrected fMRI, fMRI data corrected with field maps, and fMRI data corrected with our proposed method in data from 20 subjects. The results show that the estimated field maps were similar to the acquired field maps and that the proposed method reduces the overall error in independent component location.

Measuring Asymmetric Interactions in Resting State Brain Networks.

Directed graph representations of brain networks are increasingly being used to indicate the direction and level of influence among brain regions. Most of the existing techniques for directed graph representations are based on time series analysis and the concept of causality, and use time lag information in the brain signals. These time lag-based techniques can be inadequate for functional magnetic resonance imaging (fMRI) signal analysis due to the limited time resolution of fMRI as well as the low frequency hemodynamic response. The aim of this paper is to present a novel measure of necessity that uses asymmetry in the joint distribution of brain activations to infer the direction and level of interaction among brain regions. We present a mathematical formula for computing necessity and extend this measure to partial necessity, which can potentially distinguish between direct and indirect interactions. These measures do not depend on time lag for directed modeling of brain interactions and therefore are more suitable for fMRI signal analysis. The necessity measures were used to analyze resting state fMRI data to determine the presence of hierarchy and asymmetry of brain interactions during resting state. We performed ROI-wise analysis using the proposed necessity measures to study the default mode network. The empirical joint distribution of the fMRI signals was determined using kernel density estimation, and was used for computation of the necessity and partial necessity measures. The significance of these measures was determined using a one-sided Wilcoxon rank-sum test. Our results are consistent with the hypothesis that the posterior cingulate cortex plays a central role in the default mode network.

Altered Structural and Functional Connectivity in Late Preterm Preadolescence: An Anatomic Seed-Based Study of Resting State Networks Related to the Posteromedial and Lateral Parietal Cortex.

OBJECTIVE: Late preterm birth confers increased risk of developmental delay, academic difficulties and social deficits. The late third trimester may represent a critical period of development of neural networks including the default mode network (DMN), which is essential to normal cognition. Our objective is to identify functional and structural connectivity differences in the posteromedial cortex related to late preterm birth. METHODS: Thirty-eight preadolescents (ages 9-13; 19 born in the late preterm period (≥32 weeks gestational age) and 19 at term) without access to advanced neonatal care were recruited from a low socioeconomic status community in Brazil. Participants underwent neurocognitive testing, 3-dimensional T1-weighted imaging, diffusion-weighted imaging and resting state functional MRI (RS-fMRI). Seed-based probabilistic diffusion tractography and RS-fMRI analyses were performed using unilateral seeds within the posterior DMN (posterior cingulate cortex, precuneus) and lateral parietal DMN (superior marginal and angular gyri). RESULTS: Late preterm children demonstrated increased functional connectivity within the posterior default mode networks and increased anti-correlation with the central-executive network when seeded from the posteromedial cortex (PMC). Key differences were demonstrated between PMC components with increased anti-correlation with the salience network seen only with posterior cingulate cortex seeding but not with precuneus seeding. Probabilistic tractography showed increased streamlines within the right inferior longitudinal fasciculus and inferior fronto-occipital fasciculus within late preterm children while decreased intrahemispheric streamlines were also observed. No significant differences in neurocognitive testing were demonstrated between groups. CONCLUSION: Late preterm preadolescence is associated with altered functional connectivity from the PMC and lateral parietal cortex to known distributed functional cortical networks despite no significant executive neurocognitive differences. Selective increased structural connectivity was observed in the setting of decreased posterior interhemispheric connections. Future work is needed to determine if these findings represent a compensatory adaptation employing alternate neural circuitry or could reflect subtle pathology resulting in emotional processing deficits not seen with neurocognitive testing.

Co-registration and distortion correction of diffusion and anatomical images based on inverse contrast normalization.

Diffusion MRI provides quantitative information about microstructural properties which can be useful in neuroimaging studies of the human brain. Echo planar imaging (EPI) sequences, which are frequently used for acquisition of diffusion images, are sensitive to inhomogeneities in the primary magnetic (B0) field that cause localized distortions in the reconstructed images. We describe and evaluate a new method for correction of susceptibility-induced distortion in diffusion images in the absence of an accurate B0 fieldmap. In our method, the distortion field is estimated using a constrained non-rigid registration between an undistorted T1-weighted anatomical image and one of the distorted EPI images from diffusion acquisition. Our registration framework is based on a new approach, INVERSION (Inverse contrast Normalization for VERy Simple registratION), which exploits the inverted contrast relationship between T1- and T2-weighted brain images to define a simple and robust similarity measure. We also describe how INVERSION can be used for rigid alignment of diffusion images and T1-weighted anatomical images. Our approach is evaluated with multiple in vivo datasets acquired with different acquisition parameters. Compared to other methods, INVERSION shows robust and consistent performance in rigid registration and shows improved alignment of diffusion and anatomical images relative to normalized mutual information for non-rigid distortion correction.

Alterations of resting state networks and structural connectivity in relation to the prefrontal and anterior cingulate cortices in late prematurity.

Late preterm birth is increasingly recognized as a risk factor for cognitive and social deficits. The prefrontal cortex is particularly vulnerable to injury in late prematurity because of its protracted development and extensive cortical connections. Our study examined children born late preterm without access to advanced postnatal care to assess structural and functional connectivity related to the prefrontal cortex. Thirty-eight preadolescents [19 born late preterm (34-36 /7 weeks gestational age) and 19 at term] were recruited from a developing community in Brazil. Participants underwent neuropsychological testing. Individuals underwent three-dimensional T1-weighted, diffusion-weighted, and resting state functional MRI. Probabilistic tractography and functional connectivity analyses were carried out using unilateral seeds combining the medial prefrontal cortex and the anterior cingulate cortex. Late preterm children showed increased functional connectivity within regions of the default mode, salience, and central-executive networks from both right and left frontal cortex seeds. Decreased functional connectivity was observed within the right parahippocampal region from left frontal seeding. Probabilistic tractography showed a pattern of decreased streamlines in frontal white matter pathways and the corpus callosum, but also increased streamlines in the left orbitofrontal white matter and the right frontal white matter when seeded from the right. Late preterm children and term control children scored similarly on neuropsychological testing. Prefrontal cortical connectivity is altered in late prematurity, with hyperconnectivity observed in key resting state networks in the absence of neuropsychological deficits. Abnormal structural connectivity indicated by probabilistic tractography suggests subtle changes in white matter development, implying disruption of normal maturation during the late gestational period.

Improved B0 -distortion correction in diffusion MRI using interlaced q-space sampling and constrained reconstruction.

PURPOSE: To enable high-quality correction of susceptibility-induced geometric distortion artifacts in diffusion magnetic resonance imaging (MRI) images without increasing scan time. THEORY AND METHODS: A new method for distortion correction is proposed based on subsampling a generalized version of the state-of-the-art reversed-gradient distortion correction method. Rather than acquire each q-space sample multiple times with different distortions (as in the conventional reversed-gradient method), we sample each q-space point once with an interlaced sampling scheme that measures different distortions at different q-space locations. Distortion correction is achieved using a novel constrained reconstruction formulation that leverages the smoothness of diffusion data in q-space. RESULTS: The effectiveness of the proposed method is demonstrated with simulated and in vivo diffusion MRI data. The proposed method is substantially faster than the reversed-gradient method, and can also provide smaller intensity errors in the corrected images and smaller errors in derived quantitative diffusion parameters. CONCLUSION: The proposed method enables state-of-the-art distortion correction performance without increasing data acquisition time.