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Acoustic Radiation Force Impulse imaging for aneurysms
2009
2009 IEEE International Ultrasonics Symposium
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A method for reliable, noninvasive estimation of Abdominal Aortic Aneurysms (AAA) wall mechanics may be a useful clinical tool for rupture prediction. An in vitro AAA model was developed from an excised porcine aorta, with elastase treatment. The AAA model behaviour was analysed using Acoustic Radiation Force Impulse (ARFI) imaging techniques to generate displacements in both aneurysmal and normal aortic tissue. The incremental modulus of the arteries was indicative of early collagen
doi:10.1109/ultsym.2009.5441927
fatcat:q2ixljdmzze6jomrmx2xaxwjbm
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... , typical in aneurysms due to elastin degradation. Opening angle measurement showed a four fold decrease from healthy aorta to AAA model. The mechanical changes that occur during aneurysm formation were found to be detectable using ARFI imaging. An in vivo aorta was imaged to demonstrate the viability of excitation of abdominal aorta using ARFI imaging. B-mode and ARFI images were acquired for one diseased aorta in a female volunteer. Cardiac motion was minimized using ECG-triggered beam sequences, and ARFI images were acquired during diastole. Residual motion was treated with a linear motion filter. Diseased aortic images revealed greater displacement in the intraluminal thrombus than the wall of the aorta.
Is Bonferroni correction more sensitive than Random Field Theory for most fMRI studies?
[article]
2016
arXiv
pre-print
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Random Field Theory has been used in the fMRI literature to address the multiple comparisons problem. The method provides an analytical solution for the computation of precise p-values when its assumptions are met. When its assumptions are not met the thresholds generated by Random Field Theory can be more conservative than Bonferroni corrections, which are arguably too stringent for use in fMRI. As this has been well documented theoretically it is surprising that a majority of current studies
arXiv:1607.08205v1
fatcat:3wwqshu45vdcjg2xz5soomj42u
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... ~80%) would not meet the assumptions of Random Field Theory and therefore would have reduced sensitivity. Specifically most data is not smooth enough to meet the good lattice assumption. Current studies smooth data on average by twice the voxel size which is rarely sufficient to meet the good lattice assumption. The amount of smoothing required for Random Field Theory to produce accurate p-values increases with image resolution and decreases with degrees of freedom. There is no rule of thumb that is valid for all study designs but for typical data (3mm resolution, and greater than 20 subjects) residual smoothness with FWHM = 4 times voxel size should produce valid results. However, it should be stressed that for higher spatial resolution and lower degrees of freedom the critical smoothness required will increase sharply. This implies that researchers should carefully choose appropriate smoothing kernels. This can be facilitated by the simulations we provide that identify the critical smoothness at which the application of RFT becomes appropriate. For some applications such as presurgical mapping or, imaging of small structures, probing the laminar/columnar structure of the cortex these smoothness requirements may be too great to preserve spatial structure. As such, this study suggests developments are needed in Random Field Theory to fully exploit the resolution of modern neuroimaging.
Testing covariance models for MEG source reconstruction of hippocampal activity
[article]
2021
biorxiv/medrxiv
pre-print
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Beamforming is one of the most commonly used source reconstruction methods for magneto- and electroencephalography (M/EEG). One underlying assumption, however, is that distant sources are uncorrelated and here we tested whether this is an appropriate model for the human hippocampal data. We revised the Empirical Bayesian Beamfomer (EBB) to accommodate specific a-priori correlated source models. We showed in simulation that we could use model evidence (as approximated by Free Energy) to
doi:10.1101/2021.04.29.441929
fatcat:xqoooddkezezljjhu3o4sydmbi
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... sh between different correlated and uncorrelated source scenarios. Using group MEG data in which the participants performed a hippocampal-dependent task, we explored the possibility that the hippocampus or the cortex or both were correlated in their activity across hemispheres. We found that incorporating a correlated hippocampal source model significantly improved model evidence. Our findings help to explain why, up until now, the majority of MEG-reported hippocampal activity (typically making use of beamformers) has been estimated as unilateral.
Spherical harmonic based noise rejection and neuronal sampling with multi-axis OPMs
[article]
2021
bioRxiv
pre-print
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., 2021; Tierney et al., 2020; Vrba & Robinson, 2002) . ...
The sensor placement algorithm is described elsewhere (Tierney et al., 2020) . ...
doi:10.1101/2021.12.22.473837
fatcat:26ykujms2jbqtnqinddub3gcoa
Using OPMs to measure neural activity in standing, mobile participants
[article]
2021
bioRxiv
pre-print
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Interference was also modelled as a mean-field and removed from the data (Tierney et al., 2020) . ...
It is Vivekananda, U., Mellor, S., Tierney, T. M., Holmes, N., Boto, E., Leggett, J., Roberts, G., Hill, R. M., Litvak, V., & Brookes, M. J. (2020) . ...
doi:10.1101/2021.05.26.445793
fatcat:lelgxoq7yrgwjfiebk66psaliy
Optically Pumped Magnetoencephalography in Epilepsy
[article]
2019
medRxiv
pre-print
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AbstractOur aim was to demonstrate the first use of Optically Pumped Magnetoencephalography (OP-MEG) in an epilepsy patient with unrestricted head movement. Current clinical MEG uses a traditional SQUID system for recording MEG signal, where sensors are cryogenically cooled and housed in a helmet in which the patient's head is fixed. Here we use a different type of sensor (OPM), which operates at room temperature and can be placed directly on the patient's scalp, permitting free head movement.
doi:10.1101/2019.12.10.19014423
fatcat:icaovqlqqnctvkexetn4vau3w4
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... e performed two 30 minute OP-MEG recording sessions in a patient with refractory focal epilepsy and compared these with clinical scalp EEG performed earlier. OP-MEG was able to identify analogous interictal activity to scalp EEG, and source localise this activity to an appropriate brain region. This is the first application of OP-MEG in human epilepsy. Future directions include simultaneous EEG/OP-MEG recording and prolonged OP-MEG telemetry.
Modelling optically pumped magnetometer interference as a mean (magnetic) field
[article]
2020
bioRxiv
pre-print
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., 2019; Tierney et al., , 2020 . ...
doi:10.1101/2020.11.25.397778
fatcat:vdldpmholvcftaxd4ugx3whtna
Pragmatic spatial sampling for wearable MEG arrays
[article]
2019
biorxiv/medrxiv
pre-print
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Several new technologies have recently emerged promising new MEG systems in which the sensors can be placed close to the scalp. One such technology, Optically Pumped Magnetometry MEG (OP-MEG) allows for a scalp mounted flexible system that provides field measurements within mm of the scalp surface. A question that arises in developing on-scalp systems, such as OP-MEG scanners, is: how many sensors are necessary to achieve adequate performance/spatial discrimination? There are many factors to
doi:10.1101/2019.12.29.890426
fatcat:5jw4k7zjezdu7jcbyrhtqoeviy
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... sider in answering this question such as the signal to noise ratio (SNR), the locations and depths of the sources of interest, the density of spatial sampling, sensor gain errors (due to interference, subject movement, cross-talk, etc.) and, of course, the desired spatial discrimination. In this paper, we provide simulations which show the impact these factors have on designing sensor arrays for wearable MEG. While OP-MEG has the potential to provide high information content at dense spatial samplings, we find that adequate spatial discrimination of sources (<1cm) can be achieved with relatively few sensors (<100) at coarse spatial samplings (~30mm) at high SNR. Comparable discrimination for traditional cryogenic systems require far more channels by these same metrics. Finally we show that sensor gain errors have the greatest impact on discrimination between deep sources at high SNR.
Interference suppression techniques for OPM-based MEG: Opportunities and challenges
2021
NeuroImage
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As shown by Tierney et al. (2021a) , SSP is also a useful technique for OPM interference suppression. ...
Holmes et al., 2021 ) and/or signal processing techniques tailored for OPM data Tierney et al., 2021a ). ...
doi:10.1016/j.neuroimage.2021.118834
pmid:34933122
pmcid:PMC8803550
fatcat:cgoknj6zv5gblmhv7pcd3wvlve
Using OPMs to measure neural activity in standing, mobile participants
2021
NeuroImage
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The next pre-processing step involved modelling external interference as a homogenous field and removing this from the data ( Tierney et al., 2021b ) . ...
A new generation of wearable MEG sensors called optically pumped magnetometers (OPMs) have been developed , that measure small magnetic fields (see Tierney et al., 2019 for a review) and have a similar ...
doi:10.1016/j.neuroimage.2021.118604
pmid:34555493
pmcid:PMC8591613
fatcat:6z4mhfahozcvzlkrq56sngqgyu
Imaging the human hippocampus with optically-pumped magnetoencephalography
2019
NeuroImage
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The scanner-casts were constructed from high bandwidth, low echo time T1-weighted MRI images that allowed accurate reconstruction of the scalp surface (Tierney et al., 2018) . ...
OP-MEG The OP-MEG acquisition system used here was identical to that reported in a previous OP-MEG study which examined neocortical responses during language processing (Tierney et al., 2018) . ...
doi:10.1016/j.neuroimage.2019.116192
pmid:31521823
pmcid:PMC6854457
fatcat:ohfklaxza5eipplhm4b5242dhm
Using optically-pumped magnetometers to measure magnetoencephalographic signals in the human cerebellum
[article]
2018
bioRxiv
pre-print
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., 2018; Tierney et al., 2018) . ...
This 3D mesh was used in 3D printing to shape 14 the inner surface of a nylon head-cast, as described in (Boto et al., 2017; Meyer et al., 2017; 15 Tierney et al., 2018) , with sockets around the outer ...
doi:10.1101/425447
fatcat:dr76jig3ubcuvca7tdt2trdjvy
Flexible proton density (PD) mapping using multi-contrast variable flip angle (VFA) data
2019
NeuroImage
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Quantitative proton density (PD) maps measure the amount of free water, which is important for non-invasive tissue characterization in pathology and across lifespan. PD mapping requires the estimation and subsequent removal of factors influencing the signal intensity other than PD. These factors include the T1, T2* relaxation effects, transmit field inhomogeneities, receiver coil sensitivity profile (RP) and the spatially invariant factor that is required to scale the data. While the transmit
doi:10.1016/j.neuroimage.2018.11.023
pmid:30465865
pmcid:PMC7611405
fatcat:t3vdexztkfhujmrp6akieqrneq
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... eld can be reliably measured, the RP estimation is usually based on image post-processing techniques due to limitations of its measurement at magnetic fields higher than 1.5 T. The post-processing methods are based on unified bias-field/tissue segmentation, fitting the sensitivity profile from images obtained with different coils, or on the linear relationship between T1 and PD. The scaling factor is derived from the signal within a specific tissue compartment or reference object. However, these approaches for calculating the RP and scaling factor have limitations particularly in severe pathology or over a wide age range, restricting their application. We propose a new approach for PD mapping based on a multi-contrast variable flip angle acquisition protocol and a data-driven estimation method for the RP correction and map scaling. By combining all the multi-contrast data acquired at different echo times, we are able to fully correct the MRI signal for T2* relaxation effects and to decrease the variance and the entropy of PD values within tissue class of the final map. The RP is determined from the corrected data applying a non-parametric bias estimation, and the scaling factor is based on the median intensity of an external calibration object. Finally, we compare the signal intensity and homogeneity of the multi-contrast PD map with the well-established effective PD (PD*) mapping, for which the RP is based on concurrent bias field estimation and tissue classification, and the scaling factor is estimated from the mean white matter signal. The multi-contrast PD values homogeneity and accuracy within the cerebrospinal fluid (CSF) and deep brain structures are increased beyond that obtained using PD* maps. We demonstrate that the multi-contrast RP approach is insensitive to anatomical or a priori tissue information by applying it in a patient with extensive brain abnormalities and for whole body PD mapping in post-mortem foetal imaging.
First experiences of whole-head OP-MEG recordings from a patient with Epilepsy
[article]
2021
medRxiv
pre-print
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Environmental noise was then reduced by modelling the background 119 magnetic field as a homogeneous field at each timepoint (Tierney et al., 2021) . ...
studied and could provide this necessary ground
224
truth.
225
Here we have
226
modelled the background field as a homogeneous field across the sensors and corrected for the model
227
predictions (Tierney ...
doi:10.1101/2021.09.28.21264047
fatcat:ns6mecdyebdolkhur4accl4qpm
FIACH: A biophysical model for automatic retrospective noise control in fMRI
2016
NeuroImage
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Different noise sources in fMRI acquisition can lead to spurious false positives and reduced sensitivity. We have developed a biophysically-based model (named FIACH: Functional Image Artefact Correction Heuristic) which extends current retrospective noise control methods in fMRI. FIACH can be applied to both General Linear Model (GLM) and resting state functional connectivity MRI (rs-fcMRI) studies. FIACH is a two-step procedure involving the identification and correction of non-physiological
doi:10.1016/j.neuroimage.2015.09.034
pmid:26416652
fatcat:afh7loxyxfbajdgasopxy6npuy
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... rge amplitude temporal signal changes and spatial regions of high temporal instability. We have demonstrated its efficacy in a sample of 42 healthy children while performing language tasks that include overt speech with known activations. We demonstrate large improvements in sensitivity when FIACH is compared with current methods of retrospective correction. FIACH reduces the confounding effects of noise and increases the study's power by explaining significant variance that is not contained within the commonly used motion parameters. The method is particularly useful in detecting activations in inferior temporal regions which have proven problematic for fMRI. We have shown greater reproducibility and robustness of fMRI responses using FIACH in the context of task induced motion. In a clinical setting this will translate to increasing the reliability and sensitivity of fMRI used for the identification of language lateralisation and eloquent cortex. FIACH can benefit studies of cognitive development in young children, patient populations and older adults.
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