Subcortical contributions to salience network functioning during negative emotional processing.

Core regions of the salience network (SN), including the anterior insula (aINS) and dorsal anterior cingulate cortex (dACC), coordinate rapid adaptive changes in attentional and autonomic processes in response to negative emotional events. In doing so, the SN incorporates bottom-up signals from subcortical brain regions, such as the amygdala and periaqueductal gray (PAG). However, the precise influence of these subcortical regions is not well understood. Using ultra-high field 7-Tesla functional magnetic resonance imaging, this study investigated the bottom-up interactions of the amygdala and PAG with the SN during negative emotional salience processing. Thirty-seven healthy participants completed an emotional oddball paradigm designed to elicit a salient negative emotional response via the presentation of random, task-irrelevant negative emotional images. Negative emotional processing was associated with prominent activation in the SN, spanning the amygdala, PAG, aINS, and dACC. Consistent with previous research, analysis using dynamic causal modelling revealed an excitatory influence from the amygdala to the aINS, dACC, and PAG. In contrast, the PAG showed an inhibitory influence on amygdala, aINS and dACC activity. Our findings suggest that the amygdala may amplify the processing of negative emotional stimuli in the SN to enable upstream access to attentional resources. In comparison, the inhibitory influence of the PAG possibly reflects its involvement in modulating sympathetic-parasympathetic autonomic arousal mediated by the SN. This PAG-mediated effect may be driven by amygdala input and facilitate bottom-up processing of negative emotional stimuli. Overall, our results show that the amygdala and PAG modulate divergent functions of the SN during negative emotional processing.

Delineation and agreement of FET PET biological volumes in glioblastoma: results of the nuclear medicine credentialing program from the prospective, multi-centre trial evaluating FET PET In Glioblastoma (FIG) study-TROG 18.06.

PURPOSE: The O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) PET in Glioblastoma (FIG) trial is an Australian prospective, multi-centre study evaluating FET PET for glioblastoma patient management. FET PET imaging timepoints are pre-chemoradiotherapy (FET1), 1-month post-chemoradiotherapy (FET2), and at suspected progression (FET3). Before participant recruitment, site nuclear medicine physicians (NMPs) underwent credentialing of FET PET delineation and image interpretation. METHODS: Sites were required to complete contouring and dynamic analysis by ≥ 2 NMPs on benchmarking cases (n = 6) assessing biological tumour volume (BTV) delineation (3 × FET1) and image interpretation (3 × FET3). Data was reviewed by experts and violations noted. BTV definition includes tumour-to-background ratio (TBR) threshold of 1.6 with crescent-shaped background contour in the contralateral normal brain. Recurrence/pseudoprogression interpretation (FET3) required assessment of maximum TBR (TBRmax), dynamic analysis (time activity curve [TAC] type, time to peak), and qualitative assessment. Intraclass correlation coefficient (ICC) assessed volume agreement, coefficient of variation (CoV) compared maximum/mean TBR (TBRmax/TBRmean) across cases, and pairwise analysis assessed spatial (Dice similarity coefficient [DSC]) and boundary agreement (Hausdorff distance [HD], mean absolute surface distance [MASD]). RESULTS: Data was accrued from 21 NMPs (10 centres, n ≥ 2 each) and 20 underwent review. The initial pass rate was 93/119 (78.2%) and 27/30 requested resubmissions were completed. Violations were found in 25/72 (34.7%; 13/12 minor/major) of FET1 and 22/74 (29.7%; 14/8 minor/major) of FET3 reports. The primary reasons for resubmission were as follows: BTV over-contour (15/30, 50.0%), background placement (8/30, 26.7%), TAC classification (9/30, 30.0%), and image interpretation (7/30, 23.3%). CoV median and range for BTV, TBRmax, and TBRmean were 21.53% (12.00-30.10%), 5.89% (5.01-6.68%), and 5.01% (3.37-6.34%), respectively. BTV agreement was moderate to excellent (ICC = 0.82; 95% CI, 0.63-0.97) with good spatial (DSC = 0.84 ± 0.09) and boundary (HD = 15.78 ± 8.30 mm; MASD = 1.47 ± 1.36 mm) agreement. CONCLUSION: The FIG study credentialing program has increased expertise across study sites. TBRmax and TBRmean were robust, with considerable variability in BTV delineation and image interpretation observed.

A thalamo-centric neural signature for restructuring negative self-beliefs.

Negative self-beliefs are a core feature of psychopathology. Despite this, we have a limited understanding of the brain mechanisms by which negative self-beliefs are cognitively restructured. Using a novel paradigm, we had participants use Socratic questioning techniques to restructure negative beliefs during ultra-high resolution 7-Tesla functional magnetic resonance imaging (UHF 7 T fMRI) scanning. Cognitive restructuring elicited prominent activation in a fronto-striato-thalamic circuit, including the mediodorsal thalamus (MD), a group of deep subcortical nuclei believed to synchronize and integrate prefrontal cortex activity, but which has seldom been directly examined with fMRI due to its small size. Increased activity was also identified in the medial prefrontal cortex (MPFC), a region consistently activated by internally focused mental processing, as well as in lateral prefrontal regions associated with regulating emotional reactivity. Using Dynamic Causal Modelling (DCM), evidence was found to support the MD as having a strong excitatory effect on the activity of regions within the broader network mediating cognitive restructuring. Moreover, the degree to which participants modulated MPFC-to-MD effective connectivity during cognitive restructuring predicted their individual tendency to engage in repetitive negative thinking. Our findings represent a major shift from a cortico-centric framework of cognition and provide important mechanistic insights into how the MD facilitates key processes in cognitive interventions for common psychiatric disorders. In addition to relaying integrative information across basal ganglia and the cortex, we propose a multifaceted role for the MD whose broad excitatory pathways act to increase synchrony between cortical regions to sustain complex mental representations, including the self.

Dynamic subcortical modulators of human default mode network function.

The brain's "default mode network" (DMN) enables flexible switching between internally and externally focused cognition. Precisely how this modulation occurs is not well understood, although it may involve key subcortical mechanisms, including hypothesized influences from the basal forebrain (BF) and mediodorsal thalamus (MD). Here, we used ultra-high field (7 T) functional magnetic resonance imaging to examine the involvement of the BF and MD across states of task-induced DMN activity modulation. Specifically, we mapped DMN activity suppression ("deactivation") when participants transitioned between rest and externally focused task performance, as well as DMN activity engagement ("activation") when task performance was internally (i.e., self) focused. Consistent with recent rodent studies, the BF showed overall activity suppression with DMN cortical regions when comparing the rest to external task conditions. Further analyses, including dynamic causal modeling, confirmed that the BF drove changes in DMN cortical activity during these rest-to-task transitions. The MD, by comparison, was specifically engaged during internally focused cognition and demonstrated a broad excitatory influence on DMN cortical activation. These results provide the first direct evidence in humans of distinct BF and thalamic circuit influences on the control of DMN function and suggest novel mechanistic avenues for ongoing translational research.

Neural mediators of subjective and autonomic responding during threat learning and regulation.

Threat learning elicits robust changes across multiple affective domains, including changes in autonomic indices and subjective reports of fear and anxiety. It has been argued that the underlying causes of such changes may be dissociable at a neural level, but there is currently limited evidence to support this notion. To address this, we examined the neural mediators of trial-by-trial skin conductance responses (SCR), and subjective reports of anxious arousal and valence in participants (n = 27; 17 females) performing a threat reversal task during ultra-high field functional magnetic resonance imaging. This allowed us to identify brain mediators during initial threat learning and subsequent threat reversal. Significant neural mediators of anxious arousal during threat learning included the dorsal anterior cingulate, anterior insula cortex (AIC), and ventromedial prefrontal cortex (vmPFC), subcortical regions including the amygdala, ventral striatum, caudate and putamen, and brain-stem regions including the pons and midbrain. By comparison, autonomic changes (SCR) were mediated by a subset of regions embedded within this broader circuitry that included the caudate, putamen and thalamus, and two distinct clusters within the vmPFC. The neural mediators of subjective negative valence showed prominent effects in posterior cortical regions and, with the exception of the AIC, did not overlap with threat learning task effects. During threat reversal, positive mediators of both subjective anxious arousal and valence mapped to the default mode network; this included the vmPFC, posterior cingulate, temporoparietal junction, and angular gyrus. Decreased SCR during threat reversal was positively mediated by regions including the mid cingulate, AIC, two sub-regions of vmPFC, the thalamus, and the hippocampus. Our findings add novel evidence to support distinct underlying neural processes facilitating autonomic and subjective responding during threat learning and threat reversal. The results suggest that the brain systems engaged in threat learning mostly capture the subjective (anxious arousal) nature of the learning process, and that appropriate responding during threat reversal is facilitated by participants engaging self- and valence-based processes. Autonomic changes (SCR) appear to involve distinct facilitatory and regulatory contributions of vmPFC sub-regions.

QSMART: Quantitative susceptibility mapping artifact reduction technique.

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.

xQSM: quantitative susceptibility mapping with octave convolutional and noise-regularized neural networks.

Quantitative susceptibility mapping (QSM) provides a valuable MRI contrast mechanism that has demonstrated broad clinical applications. However, the image reconstruction of QSM is challenging due to its ill-posed dipole inversion process. In this study, a new deep learning method for QSM reconstruction, namely xQSM, was designed by introducing noise regularization and modified octave convolutional layers into a U-net backbone and trained with synthetic and in vivo datasets, respectively. The xQSM method was compared with two recent deep learning (QSMnet+ and DeepQSM) and two conventional dipole inversion (MEDI and iLSQR) methods, using both digital simulations and in vivo experiments. Reconstruction error metrics, including peak signal-to-noise ratio, structural similarity, normalized root mean squared error and deep gray matter susceptibility measurements, were evaluated for comparison of the different methods. The results showed that the proposed xQSM network trained with in vivo datasets achieved the best reconstructions of all the deep learning methods. In particular, it led to, on average, 32.3%, 25.4% and 11.7% improvement in the accuracy of globus pallidus susceptibility estimation for digital simulations and 39.3%, 21.8% and 6.3% improvements for in vivo acquisitions compared with DeepQSM, QSMnet+ and iLSQR, respectively. It also exhibited the highest linearity against different susceptibility intensity scales and demonstrated the most robust generalization capability to various spatial resolutions of all the deep learning methods. In addition, the xQSM method also substantially shortened the reconstruction time from minutes using MEDI to only a few seconds.

Compressed sensing effects on quantitative analysis of undersampled human brain sodium MRI.

PURPOSE: The clinical application of sodium MRI is hampered due to relatively low image quality and associated long acquisition times. Compressed sensing (CS) aims at a reduction of measurement time, but has been found to encompass quantitative estimation bias when used in low SNR x-Nuclei imaging. This work analyses CS in quantitative human brain sodium MRI from undersampled acquisitions and provides recommendations for tissue sodium concentration (TSC) estimation. METHODS: CS reconstructions from 3D radial acquisitions of 5 healthy volunteers were investigated over varying undersampling factors (USFs) and CS penalty weights on different sparsity domains, Wavelet, Discrete Cosine Transform (DCT), and Identity. Resulting images were compared with highly sampled and undersampled NUFFT-based images and evaluated for image quality (i.e. structural similarity), image intensity bias, and its effect on TSC estimates in gray and white matter. RESULTS: Wavelet-based CS reconstructions show highest image quality with stable TSC estimates for most USFs. Up to an USF of 4, images showed good structural detail. DCT and Identity-based CS enable good image quality, however show a bias in TSC with a reduction in estimates across USFs. CONCLUSIONS: The image intensity bias is lowest in Wavelet-based reconstructions and enables an up to fourfold acquisition speed up while maintaining good structural detail. The associated acquisition time reduction can facilitate a translation of sodium MRI into clinical routine.

Extracting more for less: multi-echo MP2RAGE for simultaneous T1 -weighted imaging, T1 mapping, R2∗ mapping, SWI, and QSM from a single acquisition.

PURPOSE: To demonstrate simultaneous T1 -weighted imaging, T1 mapping, R2∗ mapping, SWI, and QSM from a single multi-echo (ME) MP2RAGE acquisition. METHODS: A single-echo (SE) MP2RAGE sequence at 7 tesla was extended to ME with 4 bipolar gradient echo readouts. T1 -weighted images and T1 maps calculated from individual echoes were combined using sum of squares and averaged, respectively. ME-combined SWI and associated minimum intensity projection images were generated with TE-adjusted homodyne filters. A QSM reconstruction pipeline was used, including a phase-offsets correction and coil combination method to properly combine the phase images from the 32 receiver channels. Measurements of susceptibility, R2∗ , and T1 of brain tissue from ME-MP2RAGE were compared with those from standard ME-gradient echo and SE-MP2RAGE. RESULTS: The ME combined T1 -weighted, T1 map, SWI, and minimum intensity projection images showed increased SNRs compared to the SE results. The proposed coil combination method led to QSM results free of phase-singularity artifacts, which were present in the standard adaptive combination method. T1 -weighted, T1 , and susceptibility maps from ME-MP2RAGE were comparable to those obtained from SE-MP2RAGE and ME-gradient echo, whereas R2∗ maps showed increased blurring and reduced SNR. T1 , R2∗ , and susceptibility values of brain tissue from ME-MP2RAGE were consistent with those from SE-MP2RAGE and ME-gradient echo. CONCLUSION: High-resolution structural T1 weighted imaging, T1 mapping, R2∗ mapping, SWI, and QSM can be extracted from a single 8.5-min ME-MP2RAGE acquisition using a customized reconstruction pipeline. This method can be applied to replace separate SE-MP2RAGE and ME-gradient echo acquisitions to significantly shorten total scan time.

Functional neuroplasticity in response to cerebello-thalamic injury underpins the clinical presentation of tremor in multiple sclerosis.

BACKGROUND: Tremor is present in almost half of multiple sclerosis (MS) patients. The lack of understanding of its pathophysiology is hampering progress in development of treatments. OBJECTIVES: To clarify the structural and functional brain changes associated with the clinical phenotype of upper limb tremor in people with MS. METHODS: Fifteen healthy controls (46.1 ± 15.4 years), 27 MS participants without tremor (46.7 ± 11.6 years) and 42 with tremor (46.6 ± 11.5 years) were included. Tremor was quantified using the Bain score (0-10) for overall severity, handwriting and Archimedes spiral drawing. Functional magnetic resonance imaging activations were compared between participants groups during performance of a joystick task designed to isolate tremulous movement. Inflammation and atrophy of cerebello-thalamo-cortical brain structures were quantified. RESULTS: Tremor participants were found to have atrophy of the cerebellum and thalamus, and higher ipsilateral cerebellar lesion load compared to participants without tremor (p < 0.020). We found higher ipsilateral activation in the inferior parietal lobule, the premotor cortex and supplementary motor area in MS tremor participants compared to MS participants without tremor during the joystick task. Finally, stronger activation in those areas was associated with lower tremor severity. CONCLUSION: Subcortical neurodegeneration and inflammation along the cerebello-thalamo-cortical and cortical functional neuroplasticity contribute to the severity of tremor in MS.

Seven-tesla quantitative magnetic resonance spectroscopy of glutamate, γ-aminobutyric acid, and glutathione in the posterior cingulate cortex/precuneus in patients with epilepsy.

OBJECTIVE: The posterior cingulate cortex (PCC)/precuneus is a key hub of the default mode network, whose function is known to be altered in epilepsy. Glutamate and γ-aminobutyric acid (GABA) are the main excitatory and inhibitory neurotransmitters in the central nervous system, respectively. Glutathione (GSH) is the most important free radical scavenging compound in the brain. Quantification of these molecules by magnetic resonance spectroscopy (MRS) up to 4 T is limited by overlapping resonances from other molecules. In this study, we used ultra-high-field (7 T) MRS to quantify their concentrations in patients with different epilepsy syndromes. METHODS: Nineteen patients with temporal lobe epilepsy (TLE) and 16 with idiopathic generalized epilepsy (IGE) underwent magnetic resonance imaging scans using a 7-T research scanner. Single-voxel (8 cm3 ) MRS, located in the PCC/precuneus, was acquired via stimulated echo acquisition mode. Their results were compared to 10 healthy volunteers. RESULTS: Mean concentrations of glutamate, GABA, and the glutamate/GABA ratio did not differ between the IGE, TLE, and healthy volunteer groups. The mean ± SD concentration of GSH was 1.9 ± 0.3 mmol·L-1 in healthy controls, 2.0 ± 0.2 mmol·L-1 in patients with TLE, and 2.2 ± 0.4 mmol·L-1 in patients with IGE. One-way analysis of variance with post hoc Tukey-Kramer test revealed a significant difference in the concentration of GSH between patients with IGE and controls (P = .03). Short-term seizure freedom in patients with epilepsy was predicted by an elevated concentration of glutamate in the PCC/precuneus (P = .01). In patients with TLE, the concentration of GABA declined with age (P = .03). SIGNIFICANCE: Patients with IGE have higher concentrations of GSH in the PCC/precuneus than healthy controls. There is no difference in the concentrations of glutamate and GABA, or their ratio, in the PCC/precuneus between patients with IGE, patients with TLE, and healthy controls. Measuring the concentration of glutamate in the PCC/precuneus may assist with predicting drug response.

Zero-gradient-excitation ramped hybrid encoding (zGRF -RHE) sodium MRI.

PURPOSE: Fast bi-exponential transverse signal decay compounds sodium image quality. This work aims at enhancing image characteristics using a special case of ramped hybrid encoding (RHE). Zero-gradient-excitation (zGRF )-RHE provides (1) gradient-free excitation for high flip angle, artifact-free excitation profiles and (2) gradient ramping during dead-time for the optimization of encoding time (tenc ) to reduce T2* signal decay influence during acquisition. METHODS: Radial zGRF -RHE and standard radial UTE were investigated over a range of receiver bandwidths in simulations, phantom and in vivo brain experiments. Central k-space in zGRF -RHE was acquired through single point measurements at the minimum achievable TE. T2* blurring artifacts and image SNR and CNR were assessed. RESULTS: zGRF -RHE enabled 90° flip angle artifact-free excitation, whereas gradient pre-ramping provided greater tenc efficiency for any readout bandwidths. Experiments confirmed simulation results, revealing sharper edge characteristics particularly at short readout durations (TRO ). Significant SNR improvements of up to 4.8% were observed for longer TRO . CONCLUSION: zGRF -RHE allows for artifact-free high flip angle excitation with time-efficient encoding improving on image characteristics. This hybrid encoding concept with gradient pre-ramping is trajectory independent and can be introduced in any center-out UTE trajectory design.

7T-fMRI: Faster temporal resolution yields optimal BOLD sensitivity for functional network imaging specifically at high spatial resolution.

Recent developments in accelerated imaging methods allow faster acquisition of high spatial resolution images. This could improve the applications of functional magnetic resonance imaging at 7 Tesla (7T-fMRI), such as neurosurgical planning and Brain Computer Interfaces (BCIs). However, increasing the spatial and temporal resolution will both lead to signal-to-noise ratio (SNR) losses due to decreased net magnetization per voxel and T1-relaxation effect, respectively. This could potentially offset the SNR efficiency gains made with increasing temporal resolution. We investigated the effects of varying spatial and temporal resolution on fMRI sensitivity measures and their implications on fMRI-based BCI simulations. We compared temporal signal-to-noise ratio (tSNR), observed percent signal change (%∆S), volumes of significant activation, Z-scores and decoding performance of linear classifiers commonly used in BCIs across a range of spatial and temporal resolution images acquired during an ankle-tapping task. Our results revealed an average increase of 22% in %∆S (p=0.006) and 9% in decoding performance (p=0.015) with temporal resolution only at the highest spatial resolution of 1.5×1.5×1.5mm3, despite a 29% decrease in tSNR (p<0.001) and plateaued Z-scores. Further, the volume of significant activation was indifferent (p>0.05) across spatial resolution specifically at the highest temporal resolution of 500ms. These results demonstrate that the overall BOLD sensitivity can be increased significantly with temporal resolution, granted an adequately high spatial resolution with minimal physiological noise level. This shows the feasibility of diffuse motor-network imaging at high spatial and temporal resolution with robust BOLD sensitivity with 7T-fMRI. Importantly, we show that this sensitivity improvement could be extended to an fMRI application such as BCIs.

Spatially dynamic recurrent information flow across long-range dorsal motor network encodes selective motor goals.

Performing voluntary movements involves many regions of the brain, but it is unknown how they work together to plan and execute specific movements. We recorded high-resolution ultra-high-field blood-oxygen-level-dependent signal during a cued ankle-dorsiflexion task. The spatiotemporal dynamics and the patterns of task-relevant information flow across the dorsal motor network were investigated. We show that task-relevant information appears and decays earlier in the higher order areas of the dorsal motor network then in the primary motor cortex. Furthermore, the results show that task-relevant information is encoded in general initially, and then selective goals are subsequently encoded in specifics subregions across the network. Importantly, the patterns of recurrent information flow across the network vary across different subregions depending on the goal. Recurrent information flow was observed across all higher order areas of the dorsal motor network in the subregions encoding for the current goal. In contrast, only the top-down information flow from the supplementary motor cortex to the frontoparietal regions, with weakened recurrent information flow between the frontoparietal regions and bottom-up information flow from the frontoparietal regions to the supplementary cortex were observed in the subregions encoding for the opposing goal. We conclude that selective motor goal encoding and execution rely on goal-dependent differences in subregional recurrent information flow patterns across the long-range dorsal motor network areas that exhibit graded functional specialization.

3D-multi-echo radial imaging of 23 Na (3D-MERINA) for time-efficient multi-parameter tissue compartment mapping.

PURPOSE: This work demonstrates a 3D radial multi-echo acquisition scheme for time-efficient sodium (23 Na) MR-signal acquisition and analysis. Echo reconstructions were used to produce signal-to-noise ratio (SNR)-enhanced 23 Na-images and parameter maps of the biexponential observed transverse relaxation time ( T2*) decay. METHODS: A custom-built sequence for radial multi-echo acquisition was proposed for acquisition of a series of 3D volumetric 23 Na-images. Measurements acquired in a phantom and in vivo human brains were analyzed for SNR enhancement and multi-component T2* estimation. RESULTS: Rapid gradient refocused imaging acquired 38 echoes within a repetition time of 160 ms. Signal averaging of multi-echo time (TE) measurements showed an average brain tissue SNR enhancement of 34% compared to single-TE images across subjects. Phantom and in vivo measurements detected distinguishable signal decay characteristics for fluid and solid media. Mapping results were investigated in phantom and in vivo experiments for sequence timing optimization and signal decay analysis. The T2* mapping results were consistent with previously reported values and facilitated fluid-signal discrimination. CONCLUSION: The proposed method offers an efficient 23 Na-imaging scheme that extends existing 23 Na-MRI sequences by acquiring signal decay information with no increase in time or specific absorption rate. The resultant SNR-enhanced 23 Na-images and estimated T2* signal decay characteristics offer great potential for detailed investigation of tissue compartment characterization and clinical application. Magn Reson Med 79:1950-1961, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Optimized partial-coverage functional analysis pipeline (OPFAP): a semi-automated pipeline for skull stripping and co-registration of partial-coverage, ultra-high-field functional images.

OBJECTIVE: Ultra-high-field functional MRI (UHF-fMRI) allows for higher spatiotemporal resolution imaging. However, higher-resolution imaging entails coverage limitations. Processing partial-coverage images using standard pipelines leads to sub-optimal results. We aimed to develop a simple, semi-automated pipeline for processing partial-coverage UHF-fMRI data using widely used image processing algorithms. MATERIALS AND METHODS: We developed automated pipelines for optimized skull stripping and co-registration of partial-coverage UHF functional images, using built-in functions of the Centre for Functional Magnetic Resonance Imaging of the Brain's (FMRIB's) Software library (FSL) and advanced normalization tools. We incorporated the pipelines into the FSL's functional analysis pipeline and provide a semi-automated optimized partial-coverage functional analysis pipeline (OPFAP). RESULTS: Compared to the standard pipeline, the OPFAP yielded images with 15 and 30% greater volume of non-zero voxels after skull stripping the functional and anatomical images, respectively (all p = 0.0004), which reflected the conservation of cortical voxels lost when the standard pipeline was used. The OPFAP yielded the greatest Dice and Jaccard coefficients (87 and 80%, respectively; all p < 0.0001) between the co-registered participant gyri maps and the template gyri maps, demonstrating the goodness of the co-registration results. Furthermore, the greatest volume of group-level activation in the most number of functionally relevant regions was observed when the OPFAP was used. Importantly, group-level activations were not observed when using the standard pipeline. CONCLUSION: These results suggest that the OPFAP should be used for processing partial-coverage UHF-fMRI data for detecting high-resolution macroscopic blood oxygenation level-dependent activations.

An Objective Measurement of Lacunar Infarct Location from the Middle Cerebral Artery Stem.

BACKGROUND: There is emerging interest in the relationship between neuroimaging location of lacunar infarcts and underlying stroke risk factors. Recent methods used for localization of lacunar infarcts are affected by high inter-rater variability. We used a novel algorithm-driven method that provided quantitative assessment of the distance of the lacunar infarct from the origins of the lenticulostriate arteries. METHODS: We conducted a retrospective analysis of patients who presented with lacunar infarcts between 2007 and 2011. Diffusion-weighted imaging and magnetic resonance angiography were used to manually mark the infarct lesion and the ipsilateral origins of lenticulostriate arteries. A 3-dimensional distance formula computed the distance between the infarct and the arterial region of interest. All distances were adjusted for brain volumes. Agreement testing using 2 blinded assessors was used to determine reproducibility of this method. RESULTS: One hundred and ten patients were included in our study, with a median age of 72 years (interquartile range 58-81); 67 (61%) were male and 33 (30%) had hypertension and other vascular risk factors including hypercholesterolemia 45 (41%), smoking 33 (30%), diabetes 24 (22%), ischemic heart disease 18 (16%), and atrial fibrillation 9 (8%). The agreement test for 33 patients demonstrated an intraclass correlation of .89 and Lin's correlation coefficient of .89 (95% confidence interval .816-.963). The median distance for the study cohort was 24.5 mm, with shorter median distances of 13.7 mm observed in patients with atrial fibrillation (P value < .005). CONCLUSION: Our study used a novel method to calculate a distance measurement, which has high inter-rater correlation.

Early perfusion MRI predicts survival outcome in patients with recurrent glioblastoma treated with bevacizumab and carboplatin.

Bevacizumab, an anti-angiogenic agent, is FDA-approved for use in patients with recurrent glioblastoma multiforme (rGBM). The radiologic evaluation of tumor response to bevacizumab is complex and there is no validated method of monitoring tumor vascularity during therapy. We evaluated perfusion-weighted MR imaging (PWI) in our cohort of patients enrolled in the CABARET trial, which examined the effectiveness of bevacizumab with or without carboplatin in patients with rGBM. Pre-treatment and early follow-up (4- and 8-week) PWI were used to calculate relative cerebral blood volume (rCBV) histogram statistics of the contrast-enhancing and FLAIR hyperintense tumor volumes. A novel rCBV measurement (load) was developed to estimate the total volume of perfused tumor blood vessels. Changes in all rCBV measures were examined for correlations with progression-free (PFS) and overall survival (OS). All of our 15 patients enrolled in the CABARET trial were included. Median PFS and OS were 23 and 45 weeks respectively. Kaplan-Meier analysis of pre-treatment PWI revealed an 18 week reduction in median OS in patients with high tumor rCBV (p = 0.031). Changes in rCBV measures, especially load, correlated significantly with PFS and OS at both follow-up time-points. Patients with the greatest reduction in rCBVload by 8-weeks of therapy had a significantly increased median OS (30 weeks; p = 0.013). PWI may be of significant clinical utility in managing patients with rGBM, particularly those treated with anti-angiogenic agents such as bevacizumab. These findings need to be confirmed prospectively in larger studies.

Association between baseline peri-infarct magnetic resonance spectroscopy and regional white matter atrophy after stroke.

INTRODUCTION: Cerebral atrophy after stroke is associated with poor functional outcome. The prediction and prevention of post-stroke brain atrophy could therefore represent a target for neurorestorative therapies. We investigated the associations between peri-infarct metabolite concentrations measured by quantitative MRS and brain volume change in the infarct hemisphere after stroke. METHODS: Twenty patients with ischemic stroke were enrolled. Patients underwent 3T-MRI within 1 week of onset, and at 1 and 3 months. At the baseline scan, an MRS voxel was placed manually in the peri-infarct area and another in the corresponding contralateral region. Volumetric analysis of T1 images was performed using two automated processing packages. Changes in gray and white matter volume were assessed as percentage change between 1 and 3 months. RESULTS: Mean concentrations (institutional units) of N-acetylaspartic acid (NAA) (6.1 vs 7.0, p = 0.039), total creatine (Cr+PCr) (5.4 vs 5.8, p = 0.043), and inositol (4.5 vs 5.0, p = 0.014), were significantly lower in the peri-infarct region compared with the contralateral hemisphere. There was a significant correlation between baseline peri-infarct NAA and white matter volume change in the infarct hemisphere between 1 and 3 months, with lower NAA being associated with subsequent white matter atrophy (Spearman's rho = 0.66, p = 0.010). The baseline concentration of Cr+PCr was also significantly correlated with white matter atrophy in the infarct hemisphere (Spearman's rho = 0.59, p = 0.027). Both of these associations were significant after adjustment for the false discovery rate and were validated using the secondary volumetric method. CONCLUSION: MRS may be useful in the prediction of white matter atrophy post-stroke and in the testing of novel neurorestorative therapies.

Semi-automated hippocampal segmentation in people with cognitive impairment using an age appropriate template for registration.

BACKGROUND: To evaluate a new semi-automated segmentation method for calculating hippocampal volumes and to compare results with standard software tools in a cohort of people with subjective memory complaints (SMC) and mild cognitive impairment (MCI). METHODS: Data from 58 participants, 39 with SMC (17 male, 22 female, mean age 72.6) and 19 with MCI (6 male, 13 female, mean age 74.3), were analyzed. For each participant, T1-weighted images were acquired using an MPRAGE sequence on a 3 Tesla MRI system. Hippocampal volumes (left, right, and total) were calculated with a new, age appropriate registration template, based on older people and using the advanced software tool ANTs (Advanced Normalization Tools). The results were compared with manual tracing (seen as the reference standard) and two widely accepted automated software tools (FSL, FreeSurfer). RESULTS: The hippocampal volumes, calculated by using the age appropriate registration template were significantly (P < 0.05) more accurate (mean volume accuracy more than 90%) than those obtained with FreeSurfer and FSL (both less than 70%). Dice coefficients for the hippocampal segmentations with the new template method (75.3%) were slightly, but significantly (P < 0.05) higher than those from FreeSurfer (72.4%). CONCLUSION: These results suggest that an age appropriate registration template might be a more accurate alternative to calculate hippocampal volumes when manual segmentation is not feasible.