Feasibility of high-resolution perfusion imaging using arterial spin labeling MRI at 3 Tesla

Cerebral blood flow (CBF) is a critical physiological parameter of brain health, and it can be non-invasively measured with arterial spin labeling (ASL) MRI. In this study, we evaluated and optimized whole-brain, high-resolution ASL as an alternative to the low-resolution ASL employed in the routine assessment of CBF in both healthy participants and patients. Two high-resolution protocols (i.e., pCASL and FAIR-Q2TIPS (PASL) with 2 mm isotropic voxels) were compared to a default clinical pCASL protocol (3.4 × 3.4 × 4 mm3), all of whom had an acquisition time of ≈ 5 min. We assessed the impact of high-resolution acquisition on reducing partial voluming and improving sensitivity to the perfusion signal, and evaluated the effectiveness of z-deblurring on the ASL data. We compared the quality of whole-brain ASL acquired using three available head coils with differing number of receive channels (i.e., 20, 32, and 64ch). We found that using higher coil counts (32 and 64ch coils as compared to 20ch) offers improved signal-to-noise ratio (SNR) and acceleration capabilities that are beneficial for ASL imaging at 3 Tesla (3 T). The inherent reduction in partial voluming effects with higher resolution acquisitions improves the resolving power of perfusion without impacting the sensitivity. In conclusion, our results suggest that high-resolution ASL (2 to 2.5 mm isotropic voxels) has the potential to become a new standard for perfusion imaging at 3 T and increase its adoption into clinical research and cognitive neuroscience applications

Tonotopic maps in human auditory cortex using arterial spin labeling

A tonotopic organization of the human auditory cortex (AC) has been reliably found by neuroimaging studies. However, a full characterization and parcellation of the AC is still lacking. In this study, we employed pseudo-continuous arterial spin labeling (pCASL) to map tonotopy and voice selective regions using, for the first time, cerebral blood flow (CBF). We demonstrated the feasibility of CBF-based tonotopy and found a good agreement with BOLD signal-based tonotopy, despite the lower contrast-to-noise ratio of CBF. Quantitative perfusion mapping of baseline CBF showed a region of high perfusion centered on Heschl's gyrus and corresponding to the main high-low-high frequency gradients, co-located to the presumed primary auditory core and suggesting baseline CBF as a novel marker for AC parcellation. Furthermore, susceptibility weighted imaging was employed to investigate the tissue specificity of CBF and BOLD signal and the possible venous bias of BOLD-based tonotopy. For BOLD only active voxels, we found a higher percentage of vein contamination than for CBF only active voxels. Taken together, we demonstrated that both baseline and stimulus-induced CBF is an alternative fMRI approach to the standard BOLD signal to study auditory processing and delineate the functional organization of the auditory cortex. Hum Brain Mapp, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc

Effects of MP2RAGE B\u3csub\u3e1\u3c/sub\u3e\u3csup\u3e+\u3c/sup\u3e sensitivity on inter-site T\u3csub\u3e1\u3c/sub\u3e reproducibility and hippocampal morphometry at 7T

Most neuroanatomical studies are based on T -weighted MR images, whose intensity profiles are not solely determined by the tissue\u27s longitudinal relaxation times (T ), but also affected by varying non-T contributions, hampering data reproducibility. In contrast, quantitative imaging using the MP2RAGE sequence, for example, allows direct characterization of the brain based on the tissue property of interest. Combined with 7 Tesla (7T) MRI, this offers unique opportunities to obtain robust high-resolution brain data characterized by a high reproducibility, sensitivity and specificity. However, specific MP2RAGE parameter choices – e.g., to emphasize intracortical myelin-dependent contrast variations – can substantially impact image quality and cortical analyses through remnants of B -related intensity variations, as illustrated in our previous work. To follow up on this: we (1) validate this protocol effect using a dataset acquired with a particularly B insensitive set of MP2RAGE parameters combined with parallel transmission excitation; and (2) extend our analyses to evaluate the effects on hippocampal morphometry. The latter remained unexplored initially, but can provide important insights related to generalizability and reproducibility of neurodegenerative research using 7T MRI. We confirm that B inhomogeneities have a considerably variable effect on cortical T estimates, as well as on hippocampal morphometry depending on the MP2RAGE setup. While T differed substantially across datasets initially, we show the inter-site T comparability improves after correcting for the spatially varying B field using a separately acquired Sa2RAGE B map. Finally, removal of B residuals affects hippocampal volumetry and boundary definitions, particularly near structures characterized by strong intensity changes (e.g. cerebral spinal fluid). Taken together, we show that the choice of MP2RAGE parameters can impact T comparability across sites and present evidence that hippocampal segmentation results are modulated by B inhomogeneities. This calls for careful (1) consideration of sequence parameters when setting acquisition protocols, as well as (2) acquisition of a B map to correct MP2RAGE data for potential B variations to allow comparison across datasets. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 + + + + + + + +

Anatomic & metabolic brain markers of the m.3243A>G mutation: A multi-parametric 7T MRI study

One of the most common mitochondrial DNA (mtDNA) mutations, the A to G transition at base pair 3243, has been linked to changes in the brain, in addition to commonly observed hearing problems, diabetes and myopathy. However, a detailed quantitative description of m.3243A>G patients' brains has not been provided so far. In this study, ultra-high field MRI at 7T and volume- and surface-based data analyses approaches were used to highlight morphology (i.e. atrophy)-, microstructure (i.e. myelin and iron concentration)- and metabolism (i.e. cerebral blood flow)-related differences between patients (N = 22) and healthy controls (N = 15). The use of quantitative MRI at 7T allowed us to detect subtle changes of biophysical processes in the brain with high accuracy and sensitivity, in addition to typically assessed lesions and atrophy. Furthermore, the effect of m.3243A>G mutation load in blood and urine epithelial cells on these MRI measures was assessed within the patient population and revealed that blood levels were most indicative of the brain's state and disease severity, based on MRI as well as on neuropsychological data. Morphometry MRI data showed a wide-spread reduction of cortical, subcortical and cerebellar gray matter volume, in addition to significantly enlarged ventricles. Moreover, surface-based analyses revealed brain area-specific changes in cortical thickness (e.g. of the auditory cortex), and in T1, T2* and cerebral blood flow as a function of mutation load, which can be linked to typically m.3243A>G-related clinical symptoms (e.g. hearing impairment). In addition, several regions linked to attentional control (e.g. middle frontal gyrus), the sensorimotor network (e.g. banks of central sulcus) and the default mode network (e.g. precuneus) were characterized by alterations in cortical thickness, T1, T2* and/or cerebral blood flow, which has not been described in previous MRI studies. Finally, several hypotheses, based either on vascular, metabolic or astroglial implications of the m.3243A>G mutation, are discussed that potentially explain the underlying pathobiology. To conclude, this is the first 7T and also the largest MRI study on this patient population that provides macroscopic brain correlates of the m.3243A>G mutation indicating potential MRI biomarkers of mitochondrial diseases and might guide future (longitudinal) studies to extensively track neuropathological and clinical changes

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

Physiological modeling of the BOLD signal and implications for effective connectivity: A primer

In this primer, I provide an overview of the physiological processes that contribute to the observed BOLD signal (i.e., the generative biophysical model), including their time course properties within the framework of the physiologically-informed dynamic causal modeling (P-DCM). The BOLD signal is primarily determined by the change in paramagnetic deoxygenated hemoglobin, which results from combination of changes in oxygen metabolism, and cerebral blood flow and volume. Specifically, the physiological origin of the so-called BOLD signal “transients” will be discussed, including the initial overshoot, steady-state activation and the post-stimulus undershoot. I argue that incorrect physiological assumptions in the generative model of the BOLD signal can lead to incorrect inferences pertaining to both local neuronal activity and effective connectivity between brain regions. In addition, I introduce the recent laminar BOLD signal model, which extends P-DCM to cortical depths-resolved BOLD signals, allowing for laminar neuronal activity to be determined using high-resolution fMRI data

To dip or not to dip: Reconciling optical imaging and fMRI data

Several optical studies have reported a brief initial increase of deoxyhemoglobin (1), which is consistent with an initial dip observed in the functional MRI (fMRI) signal, evoked by local neuronal activity. This effect is small and not always present (2), but it has stirred great interest because it may reflect a rapid increase of oxidative metabolism before increases in blood flow and, thus, may have a narrower spatial spread than the main positive hemodynamic response. In a recent elegant and comprehensive study, Sirotin et al. (3) investigated the spatiotemporal specificity of intrinsic optical imaging signals at different wavelengths and for different chromophores

Linking brain vascular physiology to hemodynamic response in ultra-high field MRI

Functional MRI using blood oxygenation level-dependent (BOLD) contrast indirectly probes neuronal activity via evoked cerebral blood volume (CBV) and oxygenation changes. Thus, its spatio-temporal characteristics are determined by vascular physiology and MRI parameters. In this paper, we focus on the spatial distribution and time course of the fMRI signal and their magnetic field strength dependence. Even though much is still unknown, the following consistent picture is emerging: a) For high spatial resolution imaging, fMRI contrast-to-noise increases supra-linearly with field strength. b) The location and spacing of penetrating arteries and ascending veins in the cortical tissue are not correlated to cortical columns, imposing limitations on achievable point-spread function (PSF) in fMRI. c) Baseline CBV distribution may vary over cortical layers biasing fMRI signal to layers with high CBV values. d) The largest CBV change is in the tissue microvasculature, less in surface arteries and even less in pial veins. e) Venous CBV changes are only relevant for longer stimuli, and oxygenation changes are largest in post-capillary blood vessels. f) The balloon effect (i.e. slow recovery of CBV to baseline) is located in the tissue, consistent with the fact that the post-stimulus undershoot has narrower spatial PSF than the positive BOLD response. g) The onset time following stimulation has been found to be shortest in middle/lower layers, both in optical imaging and high-resolution fMRI, but we argue and demonstrate with simulations that varying signal latencies can also be caused by vascular properties and, therefore, may potentially not be interpreted as neural latencies. With simulations, we illustrate the field strength dependency of fMRI signal transients, such as the adaptation during stimulation, initial dip and the post-stimulus undershoot. In sum, vascular structure and function impose limitations on the achievable PSF of fMRI and give rise to complex fMRI transients, which contain time-varying amount of excitatory and inhibitory neuronal information. Nevertheless, non-invasive fMRI at ultra-high magnetic fields not only provides high contrast-to-noise but also an unprecedented detailed view on cognitive processes in the human brain