Subject motion is known to produce spurious covariance among time-series in functional connectivity that has been reported to induce distance-dependent spurious correlations. To present a feasibility study for applying the extended Kalman filter (EKF) framework for high temporal resolution motion correction of resting state functional MRI (rs-fMRI) series using each simultaneous multi-slice (SMS) echo planar imaging (EPI) shot as its own navigator. Prospective feasibility study. Three human volunteers. 3T GE DISCOVERY MR750 scanner using a 32-channel head coil. Simultaneous multi-slice rs-fMRI sequence with repetition time (TR)/echo time (TE) = 800/30 ms, and SMS factor 6. Motion estimates were computed using two techniques: a conventional rigid-body volume-wise registration; and a high-temporal resolution motion estimation rigid-body approach. The reference image was resampled using the estimates obtained from both approaches and the difference between these predicted volumes and the original moving series was summarized using the normalized mean squared error (NMSE). Direct comparison of NMSE values. High-temporal motion estimation was always superior to volume-wise motion estimation for the sample presented. For staged continuous rotations, the NMSE using high-temporal resolution motion estimates ranged between [0.130, 0.150] for the first volunteer (in-plane rotations), between [0.060, 0.068] for the second volunteer (in-plane rotations), and between [0.063, 0.080] for the third volunteer (through-plane rotations). These values went up to [0.384, 0.464]; [0.136, 0.179]; and [0.080, 0.096], respectively, when using volume-wise motion estimates. Accurate high-temporal rigid-body motion estimates can be obtained for rs-fMRI taking advantage of simultaneous multi-slice EPI sub-TR shots. 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018.

Sensitivity to global visual motion has been proposed as a signature of brain development, related to the dorsal rather than ventral cortical stream. Thresholds for global motion have been found to be elevated more than for global static form in many developmental disorders, leading to the idea of "dorsal stream vulnerability." Here we explore the association of global motion thresholds with individual differences in children's brain development, in a group of typically developing 5- to 12-year-olds. Good performance was associated with a relative increase in parietal lobe surface area, most strongly around the intraparietal sulcus and decrease in occipital area. In line with the involvement of intraparietal sulcus, areas in visuospatial and numerical cognition, we also found that global motion performance was correlated with tests of visuomotor integration and numerical skills. Individual differences in global form detection showed none of these anatomical or cognitive correlations. This suggests that the correlations with motion sensitivity are unlikely to reflect general perceptual or attentional abilities required for both form and motion. We conclude that individual developmental variations in global motion processing are not linked to greater area in the extrastriate visual areas, which initially process such motion, but in the parietal systems that make decisions based on this information. The overlap with visuospatial and numerical abilities may indicate the anatomical substrate of the "dorsal stream vulnerability" proposed as characterizing neurodevelopmental disorders.

Importance

The very early postnatal period witnesses extraordinary rates of growth, but structural brain development in this period has largely not been explored longitudinally. Such assessment may be key in detecting and treating the earliest signs of neurodevelopmental disorders.

Objective

To assess structural growth trajectories and rates of change in the whole brain and regions of interest in infants during the first 3 months after birth.

Design, setting, and participants

Serial structural T1-weighted and/or T2-weighted magnetic resonance images were obtained for 211 time points from 87 healthy term-born or term-equivalent preterm-born infants, aged 2 to 90 days, between October 5, 2007, and June 12, 2013.

Main outcomes and measures

We segmented whole-brain and multiple subcortical regions of interest using a novel application of Bayesian-based methods. We modeled growth and rate of growth trajectories nonparametrically and assessed left-right asymmetries and sexual dimorphisms.

Results

Whole-brain volume at birth was approximately one-third of healthy elderly brain volume, and did not differ significantly between male and female infants (347 388 mm3 and 335 509 mm3, respectively, P = .12). The growth rate was approximately 1%/d, slowing to 0.4%/d by the end of the first 3 months, when the brain reached just more than half of elderly adult brain volume. Overall growth in the first 90 days was 64%. There was a significant age-by-sex effect leading to widening separation in brain sizes with age between male and female infants (with male infants growing faster than females by 200.4 mm3/d, SE = 67.2, P = .003). Longer gestation was associated with larger brain size (2215 mm3/d, SE = 284, P = 4×10-13). The expected brain size of an infant born one week earlier than average was 5% smaller than average; at 90 days it will not have caught up, being 2% smaller than average. The cerebellum grew at the highest rate, more than doubling in 90 days, and the hippocampus grew at the slowest rate, increasing by 47% in 90 days. There was left-right asymmetry in multiple regions of interest, particularly the lateral ventricles where the left was larger than the right by 462 mm3 on average (approximately 5% of lateral ventricular volume at 2 months). We calculated volume-by-age percentile plots for assessing individual development.

Conclusions and relevance

Normative trajectories for early postnatal brain structural development can be determined from magnetic resonance imaging and could be used to improve the detection of deviant maturational patterns indicative of neurodevelopmental disorders.

Williams Syndrome (WS) is a rare genetic disorder with unique behavioral features. Yet the rareness of WS has limited the number and type of studies that can be conducted in which inferences are made about how neuroanatomical abnormalities mediate behaviors. In this study, we extracted a WS-specific neuroanatomical profile from structural magnetic resonance imaging (MRI) measurements and tested its association with behavioral features of WS. Using a WS adult cohort (22 WS, 16 healthy controls), we modeled a sparse representation of a WS-specific neuroanatomical profile. The predictive performances are robust within the training cohort (10-fold cross-validation, AUC = 1.0) and accurately identify all WS individuals in an independent child WS cohort (seven WS, 59 children with diverse developmental status, AUC = 1.0). The WS-specific neuroanatomical profile includes measurements in the orbitofrontal cortex, superior parietal cortex, Sylvian fissures, and basal ganglia, and variability within these areas related to the underlying size of hemizygous deletion in patients with partial deletions. The profile intensity mediated the overall cognitive impairment as well as personality features related to hypersociability. Our results imply that the unique behaviors in WS were mediated through the constellation of abnormalities in cortical-subcortical circuitry consistent in child WS and adult WS. The robustness of the derived WS-specific neuroanatomical profile also demonstrates the potential utility of our approach in both clinical and research applications.

A subset of patients with high-grade glioma and brain metastases who are treated with bevacizumab develop regions of marked and persistent restricted diffusion that do not reflect recurrent tumor. Here, we quantify the degree of restricted diffusion and the relative cerebral blood volume (rCBV) within these regions of bevacizumab-related imaging abnormality (BRIA) in order to facilitate differentiation of these lesions from recurrent tumor. Six patients with high-grade glioma and two patients with brain metastases who developed regions of restricted diffusion after initiation of bevacizumab were included. Six pre-treatment GBM controls were also included. Restriction spectrum imaging (RSI) was used to create diffusion maps which were co-registered with rCBV maps. Within regions of restricted diffusion, mean RSI values and mean rCBV values were calculated for patients with BRIA and for the GBM controls. These values were also calculated for normal-appearing white matter (NAWM). RSI values in regions of restricted diffusion were higher for both BRIA and tumor when compared to NAWM; furthermore RSI values in BRIA were slightly higher than in tumor. Conversely, rCBV values were very low in BRIA-lower than both tumor and NAWM. However, there was only a trend for rCBV values to be higher in tumor than in NAWM. When evaluating areas of restricted diffusion in patients with high-grade glioma or brain metastases treated with bevacizumab, RSI is better able to detect the presence of pathology whereas rCBV is better able to differentiate BRIA from tumor. Thus, combining these tools may help to differentiate necrotic tissue related to bevacizumab treatment from recurrent tumor.

Improved characterization of the microstructural brain changes occurring in the early stages of Alzheimer's disease may permit more timely disease detection. This study examined how longitudinal change in brain microstructure relates to cognitive decline in aging and prodromal Alzheimer's disease. At baseline and two-year follow-up, 29 healthy controls and 21 individuals with mild cognitive impairment or mild Alzheimer's disease underwent neuropsychological evaluation and restriction spectrum imaging (RSI). Microstructural change in the hippocampus, entorhinal cortex, and white matter tracts previously shown to be vulnerable to Alzheimer's disease, was compared between healthy controls and impaired participants. Partial correlations and stepwise linear regressions examined whether baseline RSI metrics predicted subsequent cognitive decline, or change in RSI metrics correlated with cognitive change. In medial temporal gray and white matter, restricted isotropic diffusion and crossing fibers were lower, and free water diffusion was higher, in impaired participants. Restricted isotropic diffusion in the hippocampus declined more rapidly for cognitively impaired participants. Baseline hippocampal restricted isotropic diffusion predicted cognitive decline, and change in hippocampal and entorhinal restricted isotropic diffusion correlated with cognitive decline. Within controls, changes in white matter restricted oriented diffusion and crossing fibers correlated with memory decline. In contrast, there were no correlations between rates of cortical atrophy and cognitive decline in the full sample or within controls. Changes in medial temporal lobe microarchitecture were associated with cognitive decline in prodromal Alzheimer's disease, and these changes were distinct from microstructural changes in normal cognitive aging. RSI metrics of brain microstructure may hold value for predicting cognitive decline in aging and for monitoring the course of Alzheimer's disease.

Background

Diffusion imaging has demonstrated sensitivity to structural brain changes in Alzheimer's disease (AD). However, there remains a need for a more complete characterization of microstructural alterations occurring at the earliest disease stages, and how these changes relate to underlying neuropathology. This study evaluated the sensitivity of restriction spectrum imaging (RSI), an advanced diffusion magnetic resonance imaging (MRI) technique, to microstructural brain changes in mild cognitive impairment (MCI) and AD.

Methods

MRI and neuropsychological test data were acquired from 31 healthy controls, 12 individuals with MCI, and 13 individuals with mild AD, aged 63-93 years. Cerebrospinal fluid amyloid-β levels were measured in a subset (n = 38) of participants. RSI measures of neurite density (ND) and isotropic free water (IF) were computed in fiber tracts and in hippocampal and entorhinal cortex gray matter, respectively. Analyses evaluated whether these measures predicted memory performance, correlated with amyloid-β levels, and distinguished impaired individuals from controls. For comparison, analyses were repeated with standard diffusion tensor imaging (DTI) metrics of fractional anisotropy (FA) and mean diffusivity.

Results

Both RSI and DTI measures correlated with episodic memory and disease severity. RSI, but not DTI, measures correlated with amyloid-β42 levels. ND and FA in the arcuate fasciculus and entorhinal cortex IF most strongly predicted recall performance. RSI measures of arcuate fasciculus ND and entorhinal cortex IF best discriminated memory impaired participants from healthy participants.

Conclusions

RSI is highly sensitive to microstructural changes in the early stages of AD, and is associated with biochemical markers of AD pathology. Reduced ND in cortical association fibers and increased medial temporal lobe free-water diffusion predicted episodic memory, distinguished cognitively impaired from healthy individuals, and correlated with amyloid-β. Although further research is needed to assess the sensitivity of RSI to preclinical AD and disease progression, these results suggest that RSI may be a promising tool to better understand neuroanatomical changes in AD and their association with neuropathology.

Knowing how the human brain is shaped by migration and admixture is a critical step in studying human evolution [1, 2], as well as in preventing the bias of hidden population structure in brain research [3, 4]. Yet, the neuroanatomical differences engendered by population history are still poorly understood. Most of the inference relies on craniometric measurements, because morphology of the brain is presumed to be the neurocranium's main shaping force before bones are fused and ossified [5]. Although studies have shown that the shape variations of cranial bones are consistent with population history [6-8], it is unknown how much human ancestry information is retained by the human cortical surface. In our group's previous study, we found that area measures of cortical surface and total brain volumes of individuals of European descent in the United States correlate significantly with their ancestral geographic locations in Europe [9]. Here, we demonstrate that the three-dimensional geometry of cortical surface is highly predictive of individuals' genetic ancestry in West Africa, Europe, East Asia, and America, even though their genetic background has been shaped by multiple waves of migratory and admixture events. The geometry of the cortical surface contains richer information about ancestry than the areal variability of the cortical surface, independent of total brain volumes. Besides explaining more ancestry variance than other brain imaging measurements, the 3D geometry of the cortical surface further characterizes distinct regional patterns in the folding and gyrification of the human brain associated with each ancestral lineage.

Background

Although amyloid-β (Aβ) and microstructural brain changes are both effective biomarkers of Alzheimer's disease, their independent or synergistic effects on cognitive decline are unclear.

Objective

To examine associations of Aβ and brain microstructure with cognitive decline in amnestic mild cognitive impairment and dementia.

Methods

Restriction spectrum imaging, cerebrospinal fluid Aβ, and longitudinal cognitive data were collected on 23 healthy controls and 13 individuals with mild cognitive impairment or mild to moderate Alzheimer's disease. Neurite density (ND) and isotropic free water diffusion (IF) were computed in fiber tracts and cortical regions of interest. We examined associations of Aβ with regional and whole-brain microstructure, and assessed whether microstructure mediates effects of Aβ on cognitive decline.

Results

Lower ND in limbic and association fibers and higher medial temporal lobe IF predicted baseline impairment and longitudinal decline across multiple cognitive domains. ND and IF predicted cognitive outcomes after adjustment for Aβ or whole-brain microstructure. Correlations between microstructure and cognition were present for both amyloid-positive and amyloid-negative individuals. Aβ correlated with whole-brain, rather than regional, ND and IF.

Conclusion

Aβ correlates with widespread microstructural brain changes, whereas regional microstructure correlates with cognitive decline. Microstructural abnormalities predict cognitive decline regardless of amyloid, and may inform about neural injury leading to cognitive decline beyond that attributable to amyloid.

Purpose To develop a multicompartmental signal model for whole-body diffusion-weighted imaging (DWI) and apply it to study the diffusion properties of normal tissue and metastatic prostate cancer bone lesions in vivo. Materials and Methods This prospective study (ClinicalTrials.gov: NCT03440554) included 139 men with prostate cancer (mean age, 70 years ± 9 [SD]). Multicompartmental models with two to four tissue compartments were fit to DWI data from whole-body scans to determine optimal compartmental diffusion coefficients. Bayesian information criterion (BIC) and model-fitting residuals were calculated to quantify model complexity and goodness of fit. Diffusion coefficients for the optimal model (having lowest BIC) were used to compute compartmental signal-contribution maps. The signal intensity ratio (SIR) of bone lesions to normal-appearing bone was measured on these signal-contribution maps and on conventional DWI scans and compared using paired t tests (α = .05). Two-sample t tests (α = .05) were used to compare compartmental signal fractions between lesions and normal-appearing bone. Results Lowest BIC was observed from the four-compartment model, with optimal compartmental diffusion coefficients of 0, 1.1 × 10^-3, 2.8 × 10^-3, and >3.0 ×10^-2 mm²/sec. Fitting residuals from this model were significantly lower than from conventional apparent diffusion coefficient mapping (P < .001). Bone lesion SIR was significantly higher on signal-contribution maps of model compartments 1 and 2 than on conventional DWI scans (P < .008). The fraction of signal from compartments 2, 3, and 4 was also significantly different between metastatic bone lesions and normal-appearing bone tissue (P ≤ .02). Conclusion The four-compartment model best described whole-body diffusion properties. Compartmental signal contributions from this model can be used to examine prostate cancer bone involvement. Keywords: Whole-Body MRI, Diffusion-weighted Imaging, Restriction Spectrum Imaging, Diffusion Signal Model, Bone Metastases, Prostate Cancer Clinical trial registration no. NCT03440554 Supplemental material is available for this article. © RSNA, 2023 See also commentary by Margolis in this issue.