On the importance of modeling fMRI transients when estimating effective connectivity: A dynamic causal modeling study using ASL data.

Effective connectivity is commonly assessed using blood oxygenation level-dependent (BOLD) signals. In (Havlicek et al., 2015), we presented a novel, physiologically informed dynamic causal model (P-DCM) that extends current generative models. We demonstrated the improvements afforded by P-DCM in terms of the ability to model commonly observed neuronal and vascular transients in single regions. Here, we assess the ability of the novel and previous DCM variants to estimate effective connectivity among a network of five ROIs driven by a visuo-motor task. We demonstrate that connectivity estimates depend sensitively on the DCM used, due to differences in the modeling of hemodynamic response transients; such as the post-stimulus undershoot or adaptation during stimulation. In addition, using a novel DCM for arterial spin labeling (ASL) fMRI that measures BOLD and CBF signals simultaneously, we confirmed our findings (by using the BOLD data alone and in conjunction with CBF). We show that P-DCM provides better estimates of effective connectivity, regardless of whether it is applied to BOLD data alone or to ASL time-series, and that all new aspects of P-DCM (i.e. neuronal, neurovascular, hemodynamic components) constitute an improvement compared to those in the previous DCM variants. In summary, (i) accurate modeling of fMRI response transients is crucial to obtain valid effective connectivity estimates and (ii) any additional hemodynamic data, such as provided by ASL, increases the ability to disambiguate neuronal and vascular effects present in the BOLD signal.

Comparison of 3T and 7T ASL techniques for concurrent functional perfusion and BOLD studies.

Arterial spin labeling (ASL) is the primary non-invasive MRI approach to measure baseline cerebral blood flow (CBF) in healthy subjects and patients. ASL also allows concurrent functional BOLD signal and CBF measurements, but the latter typically suffer from low contrast-to-noise (CNR) ratio. Ultra-high-field imaging significantly boosts BOLD signal CNR. However, it is contested whether also CBF CNR benefits from increasing magnetic field strength, especially given that technical challenges related to field inhomogeneities and power deposition constraints exist. Recently, we presented an optimized PASL technique that utilizes tr-FOCI inversion pulses and dielectric pads to overcome the temporal resolution limitations of previous 7T ASL implementations (Ivanov et al., in press; 2017). The primary goal of this study was to compare its performance to that of 3T ASL approaches - both pulsed ASL (PASL) and pseudo-continuous (pCASL) - concerning functional studies using simultaneous CBF and BOLD signal acquisition. To this aim, we investigated a wide range of parameters that can influence CBF and BOLD signal sensitivities: spatial resolution, labeling scheme, parallel imaging and echo time. We found that 7T ASL is superior in terms of CBF and BOLD temporal signal-to-noise ratio (SNR) and activation volume compared to all 3T ASL variants, in particular at high spatial resolution. Our results show that the advantages of 7T for ASL stem from increased image SNR, especially when parallel imaging is used. The gray matter baseline CBF was in good agreement for all 3T ASL variants, but a significantly lower value was obtained at 7T. The labeling scheme utilized was also found to significantly influence the measured perfusion territories CBF. In conclusion, a single-echo accelerated 7T PASL is recommended for high spatial and temporal resolution CBF and BOLD imaging, while a 3T dual-echo pCASL approach without parallel imaging may be preferred for low (i.e., 3mm isotropic and lower) resolution functional perfusion and BOLD 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 38:1140-1154, 2017. © 2016 Wiley Periodicals, Inc.

The effect of spatial resolution on decoding accuracy in fMRI multivariate pattern analysis.

Multivariate pattern analysis (MVPA) in fMRI has been used to extract information from distributed cortical activation patterns, which may go undetected in conventional univariate analysis. However, little is known about the physical and physiological underpinnings of MVPA in fMRI as well as about the effect of spatial smoothing on its performance. Several studies have addressed these issues, but their investigation was limited to the visual cortex at 3T with conflicting results. Here, we used ultra-high field (7T) fMRI to investigate the effect of spatial resolution and smoothing on decoding of speech content (vowels) and speaker identity from auditory cortical responses. To that end, we acquired high-resolution (1.1mm isotropic) fMRI data and additionally reconstructed them at 2.2 and 3.3mm in-plane spatial resolutions from the original k-space data. Furthermore, the data at each resolution were spatially smoothed with different 3D Gaussian kernel sizes (i.e. no smoothing or 1.1, 2.2, 3.3, 4.4, or 8.8mm kernels). For all spatial resolutions and smoothing kernels, we demonstrate the feasibility of decoding speech content (vowel) and speaker identity at 7T using support vector machine (SVM) MVPA. In addition, we found that high spatial frequencies are informative for vowel decoding and that the relative contribution of high and low spatial frequencies is different across the two decoding tasks. Moderate smoothing (up to 2.2mm) improved the accuracies for both decoding of vowels and speakers, possibly due to reduction of noise (e.g. residual motion artifacts or instrument noise) while still preserving information at high spatial frequency. In summary, our results show that - even with the same stimuli and within the same brain areas - the optimal spatial resolution for MVPA in fMRI depends on the specific decoding task of interest.

Physiologically informed dynamic causal modeling of fMRI data.

The functional MRI (fMRI) signal is an indirect measure of neuronal activity. In order to deconvolve the neuronal activity from the experimental fMRI data, biophysical generative models have been proposed describing the link between neuronal activity and the cerebral blood flow (the neurovascular coupling), and further the hemodynamic response and the BOLD signal equation. These generative models have been employed both for single brain area deconvolution and to infer effective connectivity in networks of multiple brain areas. In the current paper, we introduce a new fMRI model inspired by experimental observations about the physiological underpinnings of the BOLD signal and compare it with the generative models currently used in dynamic causal modeling (DCM), a widely used framework to study effective connectivity in the brain. We consider three fundamental aspects of such generative models for fMRI: (i) an adaptive two-state neuronal model that accounts for a wide repertoire of neuronal responses during and after stimulation; (ii) feedforward neurovascular coupling that links neuronal activity to blood flow; and (iii) a balloon model that can account for vascular uncoupling between the blood flow and the blood volume. Finally, we adjust the parameterization of the BOLD signal equation for different magnetic field strengths. This paper focuses on the form, motivation and phenomenology of DCMs for fMRI and the characteristics of the various models are demonstrated using simulations. These simulations emphasize a more accurate modeling of the transient BOLD responses - such as adaptive decreases to sustained inputs during stimulation and the post-stimulus undershoot. In addition, we demonstrate using experimental data that it is necessary to take into account both neuronal and vascular transients to accurately model the signal dynamics of fMRI data. By refining the models of the transient responses, we provide a more informed perspective on the underlying neuronal process and offer new ways of inferring changes in local neuronal activity and effective connectivity from fMRI.

Creation of ORNL NURBS-based phantoms: evaluation of the voxel effect on absorbed doses from radiopharmaceuticals.

Doses from radiopharmaceuticals absorbed by organs can be assessed using Monte Carlo simulations and computational phantoms. Patient-based voxel phantoms improve the realism of organ topology but present unrealistic stair-stepped surfaces. The goal of this research was to study the voxel effect on the basis of creation and voxelisation of a series of non-uniform rational B-spline (NURBS) reference phantoms issued from the publication of the Oak Ridge National Laboratory (ORNL). Absorbed doses from various radiopharmaceuticals were calculated and compared with the values obtained for the corresponding analytical phantoms for models of an adult male and a 5-y-old child. Dose differences lower than 12.5 % were observed when the critical structure of the skin was excluded. Moreover, the highest differences were noted for small organs and walls. Finally, all NURBS phantoms of the ORNL series, their voxelised version and the corresponding Monte Carlo N-Particle eXtended input files were programmed and are available for further simulations.

Evaluation of absorbed and effective doses to patients from radiopharmaceuticals using the ICRP 110 reference computational phantoms and ICRP 103 formulation.

In diagnostic nuclear medicine, mean absorbed doses to patients' organs and effective doses are published for standard stylised anatomic models. To provide more realistic and detailed geometries of the human morphology, the International Commission on Radiological Protection (ICRP) has recently adopted male and female voxel phantoms to represent the reference adult. This work investigates the impact of the use of these new computational phantoms. The absorbed doses were calculated for 11 different radiopharmaceuticals currently used in diagnostic nuclear medicine. They were calculated for the ICRP 110 reference computational phantoms using the OEDIPE software and the MCNP extended Monte Carlo code. The biokinetic models were issued from ICRP Publications 53, 80 and 106. The results were then compared with published values given in these ICRP Publications. To discriminate the effect of anatomical differences on organ doses from the effect of the calculation method, the Monte Carlo calculations were repeated for the reference adult stylised phantom. The voxel effect, the influence of the use of different densities and nuclear decay data were also investigated. Effective doses were determined for the ICRP 110 adult reference computational phantom with the tissue weighting factor of ICRP Publication 60 and the tissue weighting factors of ICRP Publication 103. The calculation method and, in particular, the simulation of the electron transport have a significant influence on the calculated doses, especially, for small and walled organs. Overestimates of >200 % were observed for the urinary bladder wall of the stylised phantom compared with the computational phantoms. The unrealistic organ topology of the stylised phantom leads to important dose differences, sometimes by an order of magnitude. The effective doses calculated using the new computational phantoms and the new tissue weighting factors are globally lower than the published ones, except for some radiopharmaceuticals, where the differences can reach 60 % higher than the published values. This study analyses the first set of absorbed and effective doses with the new ICRP male and female reference computational phantoms for different radiopharmaceuticals. It highlights the importance of taking into account the electron transport and the realism of the shape and inter-organ distances of the anthropomorphic model used.