David Brennan

Potential use of oxygen as a metabolic biosensor in combination with T2*-weighted MRI to define the ischemic penumbra

We describe a novel magnetic resonance imaging technique for detecting metabolism indirectly through changes in oxyhemoglobin:deoxyhemoglobin ratios and T2* signal change during ‘oxygen challenge’ (OC, 5 mins 100% O2). During OC, T2* increase reflects O2 binding to deoxyhemoglobin, which is formed when metabolizing tissues take up oxygen. Here OC has been applied to identify tissue metabolism within the ischemic brain. Permanent middle cerebral artery occlusion was induced in rats. In series 1 scanning (n = 5), diffusion-weighted imaging (DWI) was performed, followed by echo-planar T2* acquired during OC and perfusion-weighted imaging (PWI, arterial spin labeling). Oxygen challenge induced a T2* signal increase of 1.8%, 3.7%, and 0.24% in the contralateral cortex, ipsilateral cortex within the PWI/DWI mismatch zone, and ischemic core, respectively. T2* and apparent diffusion coefficient (ADC) map coregistration revealed that the T2* signal increase extended into the ADC lesion (3.4%). In series 2 (n = 5), FLASH T2* and ADC maps coregistered with histology revealed a T2* signal increase of 4.9% in the histologically defined border zone (55% normal neuronal morphology, located within the ADC lesion boundary) compared with a 0.7% increase in the cortical ischemic core (92% neuronal ischemic cell change, core ADC lesion). Oxygen challenge has potential clinical utility and, by distinguishing metabolically active and inactive tissues within hypoperfused regions, could provide a more precise assessment of penumbra.

T2*-weighted magnetic resonance imaging with hyperoxia in acute ischemic stroke

We describe the first clinical application of transient hyperoxia (“oxygen challenge”) during T2*‐weighted magnetic resonance imaging (MRI), to detect differences in vascular deoxyhemoglobin between tissue compartments following stroke.

Prospective multi-centre Voxel Based Morphometry study employing scanner specific segmentations: procedure development using CaliBrain structural MRI data.

BackgroundStructural Magnetic Resonance Imaging (sMRI) of the brain is employed in the assessment of a wide range of neuropsychiatric disorders. In order to improve statistical power in such studies it is desirable to pool scanning resources from multiple centres. The CaliBrain project was designed to provide for an assessment of scanner differences at three centres in Scotland, and to assess the practicality of pooling scans from multiple-centres.MethodsWe scanned healthy subjects twice on each of the 3 scanners in the CaliBrain project with T1-weighted sequences. The tissue classifier supplied within the Statistical Parametric Mapping (SPM5) application was used to map the grey and white tissue for each scan. We were thus able to assess within scanner variability and between scanner differences. We have sought to correct for between scanner differences by adjusting the probability mappings of tissue occupancy (tissue priors) used in SPM5 for tissue classification. The adjustment procedure resulted in separate sets of tissue priors being developed for each scanner and we refer to these as scanner specific priors.ResultsVoxel Based Morphometry (VBM) analyses and metric tests indicated that the use of scanner specific priors reduced tissue classification differences between scanners. However, the metric results also demonstrated that the between scanner differences were not reduced to the level of within scanner variability, the ideal for scanner harmonisation.ConclusionOur results indicate the development of scanner specific priors for SPM can assist in pooling of scan resources from different research centres. This can facilitate improvements in the statistical power of quantitative brain imaging studies.

The Neuro/PsyGRID Calibration Experiment: Identifying Sources of Variance and Bias in Multicenter MRI Studies

Calibration experiments precede multicenter trials to identify potential sources of variance and bias. In support of future imaging studies of mental health disorders and their treatment, the Neuro/PsyGRID consortium commissioned a calibration experiment to acquire functional and structural MRI from twelve healthy volunteers attending five centers on two occasions. Measures were derived of task activation from a working memory paradigm, fractal scaling (Hurst exponent) from resting fMRI, and grey matter distributions from T1‐weighted sequences. At each intracerebral voxel a fixed‐effects analysis of variance estimated components of variance corresponding to factors of center, subject, occasion, and within‐occasion order, and interactions of center‐by‐occasion, subject‐by‐occasion, and center‐by‐subject, the latter (since there is no intervention) a surrogate of the expected variance of the treatment effect standard error across centers. A rank order test of between‐center differences was indicative of crossover or noncrossover subject‐by‐center interactions. In general, factors of center, subject and error variance constituted >90% of the total variance, whereas occasion, order, and all interactions were generally <5%. Subject was the primary source of variance (70%–80%) for grey‐matter, with error variance the dominant component for fMRI‐derived measures. Spatially, variance was broadly homogenous with the exception of fractal scaling measures which delineated white matter, related to the flip angle of the EPI sequence. Maps of P values for the associated F‐tests were also derived. Rank tests were highly significant indicating the order of measures across centers was preserved. In summary, center effects should be modeled at the voxel‐level using existing and long‐standing statistical recommendations. Hum Brain Mapp, 2012.

Between- and within-scanner variability in the CaliBrain study n-back cognitive task.

Psychiatric neuroimaging techniques are likely to improve understanding of the brain in health and disease, but studies tend to be small, based in one imaging centre and of unclear generalisability. Multicentre studies have great appeal but face problems if functional magnetic resonance imaging (fMRI) data from different centres are to be combined. Fourteen healthy volunteers had two brain scans on different days at three scanners. Considerable effort was first made to use similar scanning sequences and standardise task implementation across centres. The n-back cognitive task was used to investigate between- and within-scanner reproducibility and reliability. Both the functional imaging and behavioural results were in good accord with the existing literature. We found no significant differences in the activation/deactivation maps between scanners, or between repeat visits to the same scanners. Between- and within-scanner reproducibility and reliability was very similar. However, the smoothness of images from the scanners differed, suggesting that smoothness equalization might further reduce inter-scanner variability. Our results for the n-back task suggest it is possible to acquire fMRI data from different scanners which allows pooling across centres, when the same field strength scanners are used and scanning sequences and paradigm implementations are standardised.

Classification images reveal the information sensitivity of brain voxels in fMRI

Reverse correlation methods have been widely used in neuroscience for many years and have recently been applied to study the sensitivity of human brain signals (EEG, MEG) to complex visual stimuli. Here we employ one such method, Bubbles (Gosselin, F., Schyns, P.G., 2001. Bubbles: A technique to reveal the use of information in recognition tasks. Vis. Res. 41, 2261-2271), in conjunction with fMRI in the context of a 3AFC facial expression categorization task. We highlight the regions of the brain showing significant sensitivity with respect to the critical visual information required to perform the categorization judgments. Moreover, we reveal the actual subset of visual information which modulates BOLD sensitivity within each such brain region. Finally, we show the potential which lies within analyzing brain function in terms of the information states of different brain regions. Thus, we can now analyse human brain function in terms of the specific visual information different brain regions process.

Localisation of regions of intense pleasure response evoked by soccer goals

Localisation of regions of intense pleasure responses will lead to a better understanding of the reward mechanisms in the brain. Here we present a novel fMRI video paradigm designed to evoke high levels of pleasure in a specific test group and to distinguish regions of pleasure from anticipation. It exploits the intense commitment of soccer supporters and thus captures the intense euphoric feeling experienced when a soccer goal is scored. Nine healthy male subjects were imaged. Statistically significant activation clusters were determined for four contrasts: (i) goals vs. open play; (ii) missed chances vs. open play; (iii) goals vs. missed chances; and (iv) goals and missed chances vs. open play. Superior temporal, inferior frontal and amygdala were activated by all contrasts. Anterior cingulate cortex (ACC) was activated in contrasts (i) and (iii), suggesting that the ACC is involved in processing pleasure. The putamen was activated in contrasts (i), (ii) and (iv) implicating involvement of this region in the anticipation of pleasure. This paradigm activates brain regions known to be involved in pleasure-processing networks. The structure of the paradigm allows the separation of anticipation from the pleasure stimulus and provides a paradigm devoid of decision-making.

Assessment of the impact of the scanner-related factors on brain morphometry analysis with Brainvisa

BackgroundBrain morphometry is extensively used in cross-sectional studies. However, the difference in the estimated values of the morphometric measures between patients and healthy subjects may be small and hence overshadowed by the scanner-related variability, especially with multicentre and longitudinal studies. It is important therefore to investigate the variability and reliability of morphometric measurements between different scanners and different sessions of the same scanner.MethodsWe assessed the variability and reliability for the grey matter, white matter, cerebrospinal fluid and cerebral hemisphere volumes as well as the global sulcal index, sulcal surface and mean geodesic depth using Brainvisa. We used datasets obtained across multiple MR scanners at 1.5 T and 3 T from the same groups of 13 and 11 healthy volunteers, respectively. For each morphometric measure, we conducted ANOVA analysis and verified whether the estimated values were significantly different across different scanners or different sessions of the same scanner. The between-centre and between-visit reliabilities were estimated from their contribution to the total variance, using a random-effects ANOVA model. To estimate the main processes responsible for low reliability, the results of brain segmentation were compared to those obtained using FAST within FSL.ResultsIn a considerable number of cases, the main effects of both centre and visit factors were found to be significant. Moreover, both between-centre and between-visit reliabilities ranged from poor to excellent for most morphometric measures. A comparison between segmentation using Brainvisa and FAST revealed that FAST improved the reliabilities for most cases, suggesting that morphometry could benefit from improving the bias correction. However, the results were still significantly different across different scanners or different visits.ConclusionsOur results confirm that for morphometry analysis with the current version of Brainvisa using data from multicentre or longitudinal studies, the scanner-related variability must be taken into account and where possible should be corrected for. We also suggest providing some flexibility to Brainvisa for a step-by-step analysis of the robustness of this package in terms of reproducibility of the results by allowing the bias corrected images to be imported from other packages and bias correction step be skipped, for example.

Perfluorocarbons Enhance a T2*-Based MRI Technique for Identifying the Penumbra in a Rat Model of Acute Ischemic Stroke

Accurate imaging of ischemic penumbra is crucial for improving the management of acute stroke patients. T2* magnetic resonance imaging (MRI) combined with a T2*oxygen challenge (T2*OC) is being developed to detect penumbra based on changes in blood deoxyhemoglobin. Using 100% O2, T2*OC-defined penumbra exhibits ongoing glucose metabolism and tissue recovery on reperfusion. However, potential limitations in translating this technique include a sinus artefact in human scans with delivery of 100% OC and relatively small signal changes. Here we investigate whether an oxygen-carrying perfluorocarbon (PFC) emulsion can enhance the sensitivity of the technique, enabling penumbra detection with lower levels of inspired oxygen. Stroke was induced in male Sprague-Dawley rats (n =17) with ischemic injury and perfusion deficit determined by diffusion and perfusion MRI, respectively. T2* signal change was measured in regions of interest (ROIs) located within ischemic core, T2*OC-defined penumbra and equivalent contralateral areas during 40% O2± prior PFC injection. Region of interest analyses between groups showed that PFC significantly enhanced the T2* response to 40% O2 in T2*-defined penumbra (mean increase of 10.6 ± 2.3% compared to 5.6 ± 1.5% with 40% O2, P<0.001). This enhancement was specific to the penumbra ROI. Perfluorocarbon emulsions therefore enhances the translational potential of the T2*OC technique for identifying penumbra in acute stroke patients.

Crossed Cerebellar Diaschisis: Insights into Oxygen Challenge MRI

Hyperoxia during T2∗-weighted magnetic resonance imaging (oxygen challenge imaging (OCI)) causes T2∗-weighted signal change that is dependent on cerebral blood volume (CBV) and oxygen extraction fraction (OEF). Crossed cerebellar diaschisis (CCD), where CBV is reduced but OEF is maintained, may be used to understand the relative contributions of OEF and CBV to OCI results. In subjects with large hemispheric strokes, OCI showed reduced signal change in the contralesional cerebellum (P = 0.027, n = 12). This was associated with reduced CBV in contralesional cerebellum (P = 0.039, n = 9). CCD may be a useful model to determine the relative contribution of CBV to signal change measured by OCI.