Three-dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe

Multi-atlas based segmentation of brain images: atlas selection and its effect on accuracy

Quantitative research in neuroimaging often relies on anatomical segmentation of human brain MR images. Recent multi-atlas based approaches provide highly accurate structural segmentations of the brain by propagating manual delineations from multiple atlases in a database to a query subject and combining them. The atlas databases which can be used for these purposes are growing steadily. We present a framework to address the consequent problems of scale in multi-atlas segmentation. We show that selecting a custom subset of atlases for each query subject provides more accurate subcortical segmentations than those given by non-selective combination of random atlas subsets. Using a database of 275 atlases, we tested an image-based similarity criterion as well as a demographic criterion (age) in a leave-one-out cross-validation study. Using a custom ranking of the database for each subject, we combined a varying number n of atlases from the top of the ranked list. The resulting segmentations were compared with manual reference segmentations using Dice overlap. Image-based selection provided better segmentations than random subsets (mean Dice overlap 0.854 vs. 0.811 for the estimated optimal subset size, n=20). Age-based selection resulted in a similar marked improvement. We conclude that selecting atlases from large databases for atlas-based brain image segmentation improves the accuracy of the segmentations achieved. We show that image similarity is a suitable selection criterion and give results based on selecting atlases by age that demonstrate the value of meta-information for selection.

Functional prefrontal reorganization accompanies learning-associated refinements in surgery: a manifold embedding approach

The prefrontal cortex (PFC) is known to be vital for acquisition of visuomotor skills, but its role in the attainment of complex technical skills which comprise both perceptual and motor components, such as those associated with surgery, remains poorly understood. We hypothesized that the prefrontal response to a surgical knot-tying task would be highly dependent on technical expertise, and that activation would wane in the context of learning success following extended practice. The present series of experiments investigated this issue, using functional Near Infrared Spectroscopy (fNIRS) and dexterity analysis to compare the PFC responses and technical skill of expert and novice surgeons performing a surgical knot-tying task in a block design experiment. Applying a data-embedding technique known as Isomap and Earth Mover's Distance (EMD) analysis, marked differences in cortical hemodynamic responses between expert and novice surgeons have been found. To determine whether refinement in technical skill was associated with reduced PFC demands, a second experiment assessed the impact of pre- and post-training on the PFC responses in novices. Significant improvements (p < 0.01) were observed in all performance parameters following training. Smaller EMD distances were observed between expert surgeons and novices following training, suggesting an evolving pattern of cortical responses. A random effect model demonstrated a statistically significant decrease in relative changes of total hemoglobin (Delta HbT) [coefficient = -3.825, standard error (s.e.) = 0.8353, z = -4.58, p < 0.001] and oxygenated hemoglobin (Delta HbO(2)) [coefficient = -4.6815, s.e = 0.6781, z = -6.90, p < 0.001] and a significant increase in deoxygenated hemoglobin (Delta HHb) [coefficient = 0.8192, s.e = 0.3034, z = 2.66, p < 0.01] across training. The results indicate that learning-related refinements in technical performance are mediated by temporal reductions in prefrontal activation.

Functional and structural synergy for resolution recovery and partial volume correction in brain PET

PURPOSE

Positron Emission Tomography (PET) has the unique capability of measuring brain function but its clinical potential is affected by low resolution and lack of morphological detail. Here we propose and evaluate a wavelet synergistic approach that combines functional and structural information from a number of sources (CT, MRI and anatomical probabilistic atlases) for the accurate quantitative recovery of radioactivity concentration in PET images. When the method is combined with anatomical probabilistic atlases, the outcome is a functional volume corrected for partial volume effects.

METHODS

The proposed method is based on the multiresolution property of the wavelet transform. First, the target PET image and the corresponding anatomical image (CT/MRI/atlas-based segmented MRI) are decomposed into several resolution elements. Secondly, high-resolution components of the PET image are replaced, in part, with those of the anatomical image after appropriate scaling. The amount of structural input is weighted by the relative high frequency signal content of the two modalities. The method was validated on a digital Zubal phantom and clinical data to evaluate its quantitative potential.

RESULTS

Simulation studies showed the expected relationship between functional recovery and the amount of correct structural detail provided, with perfect recovery achieved when true images were used as anatomical reference. The use of T1-MRI images brought significant improvements in PET image resolution. However improvements were maximized when atlas-based segmented images as anatomical references were used; these results were replicated in clinical data sets.

CONCLUSION

The synergistic use of functional and structural data, and the incorporation of anatomical probabilistic information in particular, generates morphologically corrected PET images of exquisite quality.

A survey of approaches for direct parametric image reconstruction in emission tomography

The quantitative data obtained by emission tomography are decoded using a number of techniques and methods in sequence to provide physiological information. Conventionally, the data are reconstructed to produce a series of static images. Then, pharmacokinetic modeling techniques are applied, and kinetic parameters that have physiological or functional significance are derived. Although it is possible to optimize each estimation step in this process, many simplifying assumptions have to be introduced to make the methods that are used practicable. Published research has shown that if the kinetic parameters are estimated directly from the measured data, the parametric images will have higher quality and lower mean-squared error than if this was done indirectly. This review highlights some aspects of the methods that have been proposed for such direct estimation of pharmacokinetic information from raw emission data.

Effect of BDNF val66met polymorphism on age-related amygdala volume changes in healthy subjects

Brain-derived neurotrophic factor (BDNF) has been implicated in the mechanism of age-related regional brain volumetric changes. Healthy volunteers with the valine to methionine polymorphism at codon 66 of the BDNF gene (val66met) exhibit decreased volume of a number of brain structures, including hippocampus, temporal and occipital lobar gray matter volumes, and a negative correlation between age and the volume of bilateral dorsolateral prefrontal cortices. We sought to characterize the relationship between age, BDNF and amygdala volumes among healthy volunteers. We measured amygdala volumes in 55 healthy, right-handed volunteers who underwent structural magnetic resonance imaging (MRI) and were also characterized demographically and genotyped with respect to BDNF. Using an ANCOVA model, we found that amygdala volumes were inversely correlated with age in BDNF val66met carriers but not in non-carriers. This is the first report of age-related BDNF val66met polymorphism effects on amygdala volume.

Microglia, amyloid, and cognition in Alzheimer's disease: An [11C](R)PK11195-PET and [11C]PIB-PET study

[11C](R)PK11195-PET is a marker of activated microglia while [11C]PIB-PET detects raised amyloid load. Here we studied in vivo the distributions of amyloid load and microglial activation in Alzheimer's disease (AD) and their relationship with cognitive status. Thirteen AD subjects had [11C](R)PK11195-PET and [11C]PIB-PET scans. Ten healthy controls had [11C](R)PK11195-PET and 14 controls had [11C]PIB-PET scans. Region-of-interest analysis of [11C](R)PK11195-PET detected significant 20-35% increases in microglial activation in frontal, temporal, parietal, occipital and cingulate cortices (p<0.05) of the AD subjects. [11C]PIB-PET revealed significant two-fold increases in amyloid load in these same cortical areas (p<0.0001) and SPM (statistical parametric mapping) analysis confirmed the localisation of these increases to association areas. MMSE scores in AD subjects correlated with levels of cortical microglial activation but not with amyloid load. The inverse correlation between MMSE and microglial activation is compatible with a role of microglia in neuronal damage.

Appearance modeling of 11C PiB PET images: characterizing amyloid deposition in Alzheimer's disease, mild cognitive impairment and healthy aging

Beta-amyloid (Abeta) deposition is one of the neuropathological hallmarks of Alzheimer's disease (AD), Abeta burden can be quantified using (11)C PiB PET. Neuropathological studies have shown that the initial plaques are located in the temporal and orbitofrontal cortices, extending later to the cingulate, frontal and parietal cortices (Braak and Braak, 1997). Previous studies have shown an overlap in (11)C PiB PET retention between AD, mild cognitive impairment (MCI) patients and normal elderly control (NC) participants. It has also been shown that there is a relationship between Abeta deposition and memory impairment in MCI patients. In this paper we explored the variability seen in 15 AD, 15 MCI and 18 NC by modeling the voxel data from spatially and uptake normalized PiB images using principal component analysis. The first two principal components accounted for 80% of the variability seen in the data, providing a clear separation between AD and NC, and allowing subsequent classification. The MCI cases were distributed along an apparent axis between the AD and NC group, closely aligned with the first principal component axis. The NC cases that were PiB(+) formed a distinct cluster that was between, but separated from the AD and PiB(-) NC clusters. The PiB(+) MCI were found to cluster with the AD cases, and exhibited a similar deposition pattern. The primary principal component score was found to correlate with episodic memory scores and mini mental status examination and it was observed that by varying the first principal component, a change in amyloid deposition could be derived that is similar to the expected progression of amyloid deposition observed from post mortem studies.

Effects of citalopram infusion on the serotonin transporter binding of [11C]DASB in healthy controls

The positron emission tomography (PET) ligand [(11)C]DASB is currently the most widely used imaging agent for quantitative studies of the serotonin transporter (SERT) in human brain. The aim of this work was to assess the effects of an intravenous infusion of 10 mg citalopram, a selective serotonin reuptake inhibitor (SSRI), before the PET scan on the kinetics of [(11)C]DASB in arterial plasma and in selected brain regions. Four healthy male volunteers underwent two PET scans with a mean of 523 MBq injected activity after either placebo or citalopram infusion in a randomised design. The citalopram infusion led to a substantial increase of the area under the curve of the metabolite-corrected arterial plasma input function. Total volumes of distribution V(T) were estimated applying the Logan plot to regional time-activity curves or by generating parametric maps with spectral analysis. A mean reduction of the cerebellar V(T) of 19% with Logan analysis and of 24% with spectral analysis was observed after citalopram infusion, which confirms previous findings of displaceable SERT ligand binding in cerebellar grey matter. The SERT occupancy for six target regions with moderate to high binding was 60% derived from BP(ND) and 69% derived from BP(P).

Novel reference region model reveals increased microglial and reduced vascular binding of 11C-(R)-PK11195 in patients with Alzheimer's disease

11C-(R)-PK11195 is a PET radiotracer for the quantification of peripheral benzodiazepine binding sites (PBBSs). The PBBS is a consistent marker of activated microglia, and 11C-(R)-PK11195 has been used to image microglial activity in the diseased brain and in neoplasia. However, the PBBS is also expressed in the brain vasculature (endothelium and smooth muscles), and no evidence, to our knowledge, exists of a change in the vascular PBBS in pathologic brains or of such a change having an effect on the quantification of 11C-(R)-PK11195 binding. To investigate this issue, we have used a modified reference-tissue model (SRTMV) that accounts for tracer vascular activity both in reference and target tissues and applied it for the estimation of binding potential (BP) in a cohort of patients with Alzheimer's disease (AD).

METHODS

A total of 10 patients with AD and 10 age-matched healthy subjects who underwent a 11C-(R)-PK11195 scan were considered in the analysis. The time-activity curves of 11 regions of interest were extracted using the Hammersmith maximum probability atlas. BPs were first estimated using the standard simplified reference-tissue model (SRTM) with the reference tissue computed with a supervised selection algorithm. Subsequently, we applied an SRTMV that models PBBS vascular activity using an additional linear term for both target (VbT) and reference (VbR) regions accounting for vascular tracer activity (C(B)), whereas C(B) was extracted directly from the images. VbR was fixed to 5%, and R1, k2, BP, and VbT were estimated. PBBS density in the vasculature was also assessed by immunocytochemistry on a separate cohort of young and elderly controls and 3 AD postmortem brains.

RESULTS

The inclusion of a vascular component in the SRTM increased BPs in all subjects, but the amount of the increase was different (about 11.9% in controls and 16.8% in patients with AD). In addition, average VbT values derived using the SRTMV were 4.22% for controls but only 2.87% in patients with AD. Immunochemistry showed reduced PBBS expression in AD due to vascular fibrosis.

CONCLUSION

The reduction of VbT in AD can be interpreted as a consequence of 2 independent but concurring phenomena. The vascular fibrosis in the AD brain causes the well-documented decrease of the size of lumens and the reduction of blood volume. At the same time, the fibrotic process determines the loss of vascular PBBS, particularly in smooth muscles, as here documented by immunochemistry. The inclusion of the additional vascular component in the SRTM effectively models these 2 concurrent processes and amplifies the BP in AD more than in controls because of the decrease in tracer binding to the vasculature in the disease cohort.

Joint penalized-likelihood reconstruction of time-activity curves and regions-of-interest from projection data in brain PET

This paper presents a novel statistical approach for joint estimation of regions-of-interest (ROIs) and the corresponding time-activity curves (TACs) from dynamic positron emission tomography (PET) brain projection data. It is based on optimizing the joint objective function that consists of a data log-likelihood term and two penalty terms reflecting the available a priori information about the human brain anatomy. The developed local optimization strategy iteratively updates both the ROI and TAC parameters and is guaranteed to monotonically increase the objective function. The quantitative evaluation of the algorithm is performed with numerically and Monte Carlo-simulated dynamic PET brain data of the 11C-Raclopride and 18F-FDG tracers. The results demonstrate that the method outperforms the existing sequential ROI quantification approaches in terms of accuracy, and can noticeably reduce the errors in TACs arising due to the finite spatial resolution and ROI delineation.

Automatic volumetry on MR brain images can support diagnostic decision making

Background

Diagnostic decisions in clinical imaging currently rely almost exclusively on visual image interpretation. This can lead to uncertainty, for example in dementia disease, where some of the changes resemble those of normal ageing. We hypothesized that extracting volumetric data from patients' MR brain images, relating them to reference data and presenting the results as a colour overlay on the grey scale data would aid diagnostic readers in classifying dementia disease versus normal ageing.

Methods

A proof-of-concept forced-choice reader study was designed using MR brain images from 36 subjects. Images were segmented into 43 regions using an automatic atlas registration-based label propagation procedure. Seven subjects had clinically probable AD, the remaining 29 of a similar age range were used as controls. Seven of the control subject data sets were selected at random to be presented along with the seven AD datasets to two readers, who were blinded to all clinical and demographic information except age and gender. Readers were asked to review the grey scale MR images and to record their choice of diagnosis (AD or non-AD) along with their confidence in this decision. Afterwards, readers were given the option to switch on a false-colour overlay representing the relative size of the segmented structures. Colorization was based on the size rank of the test subject when compared with a reference group consisting of the 22 control subjects who were not used as review subjects. The readers were then asked to record whether and how the additional information had an impact on their diagnostic confidence.

Results

The size rank colour overlays were useful in 18 of 28 diagnoses, as determined by their impact on readers' diagnostic confidence. A not useful result was found in 6 of 28 cases. The impact of the additional information on diagnostic confidence was significant (p < 0.02).

Conclusion

Volumetric anatomical information extracted from brain images using automatic segmentation and presented as colour overlays can support diagnostic decision making.

In Vivo 3D Digital Atlas Database of the Adult C57BL/6J Mouse Brain by Magnetic Resonance Microscopy

In this study, a 3D digital atlas of the live mouse brain based on magnetic resonance microscopy (MRM) is presented. C57BL/6J adult mouse brains were imaged in vivo on a 9.4 Tesla MR instrument at an isotropic spatial resolution of 100 μm. With sufficient signal-to-noise (SNR) and contrast-to-noise ratio (CNR), 20 brain regions were identified. Several atlases were constructed including 12 individual brain atlases, an average atlas, a probabilistic atlas and average geometrical deformation maps. We also investigated the feasibility of using lower spatial resolution images to improve time efficiency for future morphological phenotyping. All of the new in vivo data were compared to previous published in vitro C57BL/6J mouse brain atlases and the morphological differences were characterized. Our analyses revealed significant volumetric as well as unexpected geometrical differences between the in vivo and in vitro brain groups which in some instances were predictable (e.g. collapsed and smaller ventricles in vitro) but not in other instances. Based on these findings we conclude that although in vitro datasets, compared to in vivo images, offer higher spatial resolutions, superior SNR and CNR, leading to improved image segmentation, in vivo atlases are likely to be an overall better geometric match for in vivo studies, which are necessary for longitudinal examinations of the same animals and for functional brain activation studies. Thus the new in vivo mouse brain atlas dataset presented here is a valuable complement to the current mouse brain atlas collection and will be accessible to the neuroscience community on our public domain mouse brain atlas website.

FreeSurfer-initiated fully-automated subcortical brain segmentation in MRI using Large Deformation Diffeomorphic Metric Mapping

Fully-automated brain segmentation methods have not been widely adopted for clinical use because of issues related to reliability, accuracy, and limitations of delineation protocol. By combining the probabilistic-based FreeSurfer (FS) method with the Large Deformation Diffeomorphic Metric Mapping (LDDMM)-based label-propagation method, we are able to increase reliability and accuracy, and allow for flexibility in template choice. Our method uses the automated FreeSurfer subcortical labeling to provide a coarse-to-fine introduction of information in the LDDMM template-based segmentation resulting in a fully-automated subcortical brain segmentation method (FS+LDDMM). One major advantage of the FS+LDDMM-based approach is that the automatically generated segmentations generated are inherently smooth, thus subsequent steps in shape analysis can directly follow without manual post-processing or loss of detail. We have evaluated our new FS+LDDMM method on several databases containing a total of 50 subjects with different pathologies, scan sequences and manual delineation protocols for labeling the basal ganglia, thalamus, and hippocampus. In healthy controls we report Dice overlap measures of 0.81, 0.83, 0.74, 0.86 and 0.75 for the right caudate nucleus, putamen, pallidum, thalamus and hippocampus respectively. We also find statistically significant improvement of accuracy in FS+LDDMM over FreeSurfer for the caudate nucleus and putamen of Huntington's disease and Tourette's syndrome subjects, and the right hippocampus of Schizophrenia subjects.

Construction of a 3D probabilistic atlas of human cortical structures

We describe the construction of a digital brain atlas composed of data from manually delineated MRI data. A total of 56 structures were labeled in MRI of 40 healthy, normal volunteers. This labeling was performed according to a set of protocols developed for this project. Pairs of raters were assigned to each structure and trained on the protocol for that structure. Each rater pair was tested for concordance on 6 of the 40 brains; once they had achieved reliability standards, they divided the task of delineating the remaining 34 brains. The data were then spatially normalized to well-known templates using 3 popular algorithms: AIR5.2.5's nonlinear warp (Woods et al., 1998) paired with the ICBM452 Warp 5 atlas (Rex et al., 2003), FSL's FLIRT (Smith et al., 2004) was paired with its own template, a skull-stripped version of the ICBM152 T1 average; and SPM5's unified segmentation method (Ashburner and Friston, 2005) was paired with its canonical brain, the whole head ICBM152 T1 average. We thus produced 3 variants of our atlas, where each was constructed from 40 representative samples of a data processing stream that one might use for analysis. For each normalization algorithm, the individual structure delineations were then resampled according to the computed transformations. We next computed averages at each voxel location to estimate the probability of that voxel belonging to each of the 56 structures. Each version of the atlas contains, for every voxel, probability densities for each region, thus providing a resource for automated probabilistic labeling of external data types registered into standard spaces; we also computed average intensity images and tissue density maps based on the three methods and target spaces. These atlases will serve as a resource for diverse applications including meta-analysis of functional and structural imaging data and other bioinformatics applications where display of arbitrary labels in probabilistically defined anatomic space will facilitate both knowledge-based development and visualization of findings from multiple disciplines.

Tyrosine depletion alters cortical and limbic blood flow but does not modulate spatial working memory performance or task-related blood flow in humans

Dopamine appears critical in regulating spatial working memory (SWM) within the PFC of non-human primates; however findings in humans are less clear. Recent studies of the effects of global depletion of dopamine via acute tyrosine/phenylalanine depletion (TPD) on SWM task performance have yielded inconsistent results, which may be partly related to task differences. These previous studies do not address whether TPD can directly impair PFC functioning. The current study investigated the effects of TPD on (1) regional cerebral blood flow (rCBF) during a SWM n-back task using H(2) (15)O Positron Emission Tomography (PET), and (2) behavioural performance on three different SWM tasks. Ten healthy males were scanned twice: once following a placebo (balanced) amino acid mixture and once following an equivalent mixture deficient in tyrosine/phenylalanine (TPD condition). Participants completed two additional delayed-response tasks to examine whether differences in response demands influenced TPD effects on performance. TPD resulted in widespread increases in rCBF, with maximum increases in the region of the parahippocampal gyrus bilaterally, left inferior frontal gyrus, and the putamen. TPD related rCBF reductions were observed in the medial frontal gyrus bilaterally, right inferior temporal gyrus and the pons. Despite widespread changes in blood flow following TPD, no specific effects on SWM neural networks or task performance were observed. The use of three different SWM tasks suggests that task differences are unlikely to account for the lack of effects observed. These findings question the capacity of TPD to consistently modulate dopamine function and SWM neural networks in humans.

Similarity metrics for groupwise non-rigid registration

The use of groupwise registration techniques for average atlas construction has been a growing area of research in recent years. One particularly challenging component of groupwise registration is finding scalable and effective groupwise similarity metrics; these do not always extend easily from pairwise metrics. This paper investigates possible choices of similarity metrics and additionally proposes a novel metric based on Normalised Mutual Information. The described groupwise metrics are quantitatively evaluated on simulated and 3D MR datasets, and their performance compared to equivalent pairwise registration.

[11C]Flumazenil PET in temporal lobe epilepsy: do we need an arterial input function or kinetic modeling?

Reduced signal on [(11)C]]flumazenil (FMZ) positron emission tomography (PET) is associated with epileptogenic foci. Linear correlations within individuals between parametric and nonparametric images of FMZ binding have been shown, and various methods have been used, without comparison of diagnostic usefulness. Using hippocampal sclerosis (HS) as a test case, we formally compare the diagnostic yield of parametric images obtained either with a parent tracer arterial plasma input function and spectral analysis (yielding volume-of-distribution (VD) images), or with an image-based input function and the simplified reference tissue model (binding potential images, BP-SRTM) with the diagnostic yield of semiquantitative-integrated (ADD) images from 10 to 20 or 20 to 40 mins (ADD1020 and ADD2040). Dynamic 90-min [(11)C]FMZ PET datasets and arterial plasma input functions were available for 15 patients with medically refractory medial temporal lobe epilepsy (TLE) and histologically verified unilateral HS and for 13 control subjects. SPM2 was used for analysis. ADD1020 and ADD2040 images showed decreased FMZ uptake ipsilateral to the epileptogenic hippocampus in 13/15 cases; 6/13 had bilateral decreases in the ADD1020 analysis and 5/13 in the ADD2040 analysis. BP-SRTM images detected ipsilateral decreases in 12/15 cases, with bilateral decreases in three. In contrast, VD images showed ipsilateral hippocampal decreases in all 15 patients, with bilateral decreases in three patients. Bilateral decreases in the ADD images tended to be more symmetrical and in one case were more marked contralaterally. Full quantification with an image-independent input should ideally be used in the evaluation of FMZ PET; at least in TLE, intrasubject correlations do not predict equivalent clinical usefulness.

In Vivo 3D Digital Atlas Database of the Adult C57BL/6J Mouse Brain by Magnetic Resonance Microscopy

In this study, a 3D digital atlas of the live mouse brain based on magnetic resonance microscopy (MRM) is presented. C57BL/6J adult mouse brains were imaged in vivo on a 9.4 Tesla MR instrument at an isotropic spatial resolution of 100 mum. With sufficient signal-to-noise (SNR) and contrast-to-noise ratio (CNR), 20 brain regions were identified. Several atlases were constructed including 12 individual brain atlases, an average atlas, a probabilistic atlas and average geometrical deformation maps. We also investigated the feasibility of using lower spatial resolution images to improve time efficiency for future morphological phenotyping. All of the new in vivo data were compared to previous published in vitro C57BL/6J mouse brain atlases and the morphological differences were characterized. Our analyses revealed significant volumetric as well as unexpected geometrical differences between the in vivo and in vitro brain groups which in some instances were predictable (e.g. collapsed and smaller ventricles in vitro) but not in other instances. Based on these findings we conclude that although in vitro datasets, compared to in vivo images, offer higher spatial resolutions, superior SNR and CNR, leading to improved image segmentation, in vivo atlases are likely to be an overall better geometric match for in vivo studies, which are necessary for longitudinal examinations of the same animals and for functional brain activation studies. Thus the new in vivo mouse brain atlas dataset presented here is a valuable complement to the current mouse brain atlas collection and will be accessible to the neuroscience community on our public domain mouse brain atlas website.

Towards construction of an ideal stereotactic brain atlas

BACKGROUND

The role of the brain atlas is changing in many aspects with the advancements in stereotactic and functional neurosurgery. Therefore, there is a critical need to construct a new atlas. This paper addresses the definition and construction of an atlas, ideal (in our opinion) for stereotactic and functional neurosurgery. The essence of the new atlas is not only its population-based structural and functional content, but also its continuous "self-updatability" with the new clinical results obtained.

METHOD

The ideal atlas defined here contains four major components: brain models, knowledge database, tools, and clinical results. Towards its creation, a multi-atlas is proposed. The construction of the initial version of the multi-atlas is detailed with the probabilistic functional atlas (PFA), interpolated Talairach-Tournoux atlas, and enhanced Schaltenbrand-Wahren atlas. These atlases are put in a spatial register by matching their AC-PC distances and heights of the thalamus; the Schaltenbrand coronal and sagittal microseries are scaled laterally to match the target structure centroids with the locations of the best targets of the PFA.

FINDINGS

Construction of an initial version of the ideal stereotactic atlas is feasible at present from the available resources. To achieve that, our three atlases (PFA, Talairach and Schaltenbrand) are enhanced and combined together. A single lateral scaling factor per target structure is feasible to co-register the Schaltenbrand atlas with PFA in four situations (compensated against the third ventricle, non-compensated, bilateral, and non-bilateral). The STN has to be stretched by 18% more than the VIM on the Schaltenbrand coronal microseries, and the VIM has to be compressed by 13% less than the STN on the Schaltenbrand sagittal microseries.

CONCLUSION

The new multi-atlas can potentially be more useful than the currently employed atlases and will facilitate further development of the ideal atlas for stereotactic and functional neurosurgery.

Voxel-based morphometry of temporal lobe epilepsy: an introduction and review of the literature

We review the applications and results of voxel-based morphometry (VBM) studies that have reported brain changes associated with temporal lobe epilepsy (TLE). A PubMed search yielded 18 applications of VBM to study brain abnormalities in patients with TLE up to May 2007. Across studies, 26 brain regions were found to be significantly reduced in volume relative to healthy controls. There was a strong asymmetrical distribution of temporal lobe abnormalities preferentially observed ipsilateral to the seizure focus, particularly of the hippocampus (82.35% of all studies), parahippocampal gyrus (47.06%), and entorhinal (23.52%) cortex. The contralateral hippocampus was reported as abnormal in 17.65% of studies. There was a much more bilateral distribution of extratemporal lobe atrophy, preferentially affecting the thalamus (ipsilateral = 61.11%, contralateral = 50%) and parietal lobe (ipsilateral = 47.06%, contralateral = 52.94%). VBM generally reveals a distribution of brain abnormalities in patients with TLE consistent with the region-of-interest neuroimaging and postmortem literature. It is unlikely that VBM has any clinical utility given the lack of robustness for individual comparisons. However, VBM may help elucidate some unresolved important research questions such as how recurrent temporal lobe seizures affect hippocampal and extrahippocampal morphology using serial imaging acquisitions.

Classifier selection strategies for label fusion using large atlas databases

Structural segmentations of brain MRI can be generated by propagating manually labelled atlas images from a repository to a query subject and combining them. This method has been shown to be robust, consistent and increasingly accurate with increasing numbers of classifiers. It outperforms standard atlas-based segmentation but suffers, however, from problems of scale when the number of atlases is large. For a large repository and a particular query subject, using a selection strategy to identify good classifiers is one way to address problems of scale. This work presents and compares different classifier selection strategies which are applied to a group of 275 subjects with manually labelled brain MR images. We approximate an upper limit for the accuracy or overlap that can be achieved for a particular structure in a given subject and compare this with the accuracy obtained using classifier selection. The accuracy of different classifier selection strategies are also rated against the distribution of overlaps generated by random groups of classifiers.

A common system for the comprehension and production of narrative speech

Humans devote much time to the exchange of memories within the context of shared general and personal semantic knowledge. Our hypothesis was that functional imaging in normal subjects would demonstrate the convergence of speech comprehension and production on high-order heteromodal and amodal cortical areas implicated in declarative memory functions. Activity independent of speech phase (that is, comprehension and production) was most evident in the left and right lateral anterior temporal cortex. Significant activity was also observed in the posterior cortex, ventral to the angular gyri. The left and right hippocampus and adjacent inferior temporal cortex were active during speech comprehension, compatible with mnemonic encoding of narrative information, but activity was significantly less during the overt memory retrieval associated with speech production. Therefore, although clinical studies suggest that hippocampal function is necessary for the retrieval as well as the encoding of memories, the former appears to depend on much less net synaptic activity. In contrast, the retrosplenial/posterior cingulate cortex and the parahippocampal area, which are closely associated anatomically with the hippocampus, were equally active during both speech comprehension and production. The results demonstrate why a severe and persistent inability both to understand and produce meaningful speech in the absence of an impairment to process linguistic forms is usually only observed after bilateral, and particularly anterior, destruction of the temporal lobes, and emphasize the importance of retrosplenial/posterior cingulate cortex, an area known to be affected early in the course of Alzheimer's disease, in the processing of memories during communication.

In praise of tedious anatomy

Functional neuroimaging is fundamentally a tool for mapping function to structure, and its success consequently requires neuroanatomical precision and accuracy. Here we review the various means by which functional activation can be localised to neuroanatomy and suggest that the gold standard should be localisation to the individual's or group's own anatomy through the use of neuroanatomical knowledge and atlases of neuroanatomy. While automated means of localisation may be useful, they cannot provide the necessary accuracy, given variability between individuals. We also suggest that the field of functional neuroimaging needs to converge on a common set of methods for reporting functional localisation including a common "standard" space and criteria for what constitutes sufficient evidence to report activation in terms of Brodmann's areas.

Human 5-HT transporter availability predicts amygdala reactivity in vivo

The amygdala plays a central role in fear conditioning, emotional processing, and memory modulation. A postulated key component of the neurochemical regulation of amygdala function is the neurotransmitter 5-hydroxytryptamine (5-HT), and synaptic levels of 5-HT in the amygdala and elsewhere are critically regulated by the 5-HT transporter (5-HTT). The aim of this study was to directly examine the relationship between 5-HTT availability and amygdala activity using multimodal [positron emission tomography (PET) and functional magnetic resonance imaging (fMRI)] imaging measures in the same individuals. Healthy male volunteers who had previously undergone an [11C]-3-amino-4-(2-dimethylaminomethylphenylsulfanyl)-benzonitrile ([11C]-DASB) PET scan to determine 5-HTT availability completed an fMRI emotion recognition task. [11C]-DASB binding potential values were calculated for the amygdala using arterial input function and linear graphical (Logan) analysis. fMRI was performed on a 3T Philips Intera scanner, and data were analyzed using SPM2 (Wellcome Department Imaging Neuroscience, University College London). Percentage signal change during the task was extracted from the amygdala using MarsBaR (Brett et al., 2002). fMRI analysis revealed significant amygdala activation during the emotion recognition task. Region of interest analyses demonstrated a significant negative correlation between fMRI signal change in the left amygdala and 5-HTT availability in the left amygdala, with 5-HTT availability accounting for approximately 42% of the variability in left amygdala activity. Our novel in vivo data highlight the central importance of the serotonergic system in the responsiveness of the human amygdala during emotional processing.

Sulcal variability, stereological measurement and asymmetry of Broca's area on MR images

Leftward volume asymmetry of the pars opercularis and pars triangularis may exist in the human brain, frequently referred to as Broca's area, given the functional asymmetries observed in this region with regard to language expression. However, post-mortem and magnetic resonance imaging (MRI) studies have failed to consistently identify such a volumetric asymmetry. In the present study, an analysis of the asymmetry of sulco-gyral anatomy and volume of this anterior speech region was performed in combination with an analysis of the morphology and volume asymmetry of the planum temporale, located within the posterior speech region, in 50 healthy subjects using MRI. Variations in sulcal anatomy were documented according to strict classification schemes and volume estimation of the grey matter within the brain structures was performed using the Cavalieri method of stereology. Results indicated great variation in the morphology of and connectivity between the inferior frontal, inferior precentral and diagonal sulci. There were significant inter-hemispheric differences in the presence of (1) the diagonal sulcus within the pars opercularis, and (2) horizontal termination of the posterior Sylvian fissure (relative to upward oblique termination), both with an increased leftward incidence. Double parallel inferior precentral sulci and absent anterior rami of the Sylvian fissure prevented stereological measurements in five subjects. Therefore volumes were obtained from 45 subjects. There was a significant leftward volume asymmetry of the pars opercularis (P = 0.02), which was significantly related to the asymmetrical presence of the diagonal sulcus (P < 0.01). Group-wise pars opercularis volume asymmetry did not exist when a diagonal sulcus was present in both or neither hemispheres. There was no significant volume asymmetry of the pars triangularis. There was a significant leftward volume asymmetry of the planum temporale (P < 0.001), which was significantly associated with the shape of the posterior Sylvian fissure as a unilateral right or left upward oblique termination was always associated with leftward or rightward volume asymmetry respectively (P < 0.01). There was no relationship between volume asymmetries of the anterior and posterior speech regions. Our findings illustrate the extent of morphological variability of the anterior speech region and demonstrate the difficulties encountered when determining volumetric asymmetries of the inferior frontal gyrus, particularly when sulci are discontinuous, absent or bifid. When the intrasulcal grey matter of this region is exhaustively sampled according to strict anatomical landmarks, the volume of the pars opercularis is leftward asymmetrical. This manuscript illustrates the importance of simultaneous consideration of brain morphology and morphometry in studies of cerebral asymmetry.

Balancing bias, reliability, noise properties and the need for parametric maps in quantitative ligand PET: [(11)C]diprenorphine test-retest data

[(11)C]diprenorphine (DPN) is a non-subtype selective opioid receptor PET ligand with slow kinetics and no region devoid of specific binding. Parametric maps are desirable but have to overcome high noise at the voxel level. We obtained parameter values, parametric map image quality, test-retest reproducibility and reliability (using intraclass correlation coefficients (ICCs)) for conventional spectral analysis and a derived method (rank shaping), compared them with values obtained through sampling of volumes of interest (VOIs) on the dynamic data sets and tested whether smaller amounts of radioactivity injected maintained reliability. Ten subjects were injected twice with either approximately 185 MBq or approximately 135 MBq of [(11)C]DPN, followed by dynamic PET for 90 min. Data were movement corrected with a frame-to-frame co-registration method. Arterial plasma input functions corrected for radiolabelled metabolites were created. There was no overall effect of movement correction except for one subject with substantial movement whose test-retest differences decreased by approximately 50%. Actual parametric values depended heavily on the cutoff for slow frequencies (between 0.0008 s(-1) and 0.00063 s(-1)). Image quality was satisfactory for restricted base ranges when using conventional spectral analysis. The rank shaping method allowed maximising of this range but had similar bias. VOI-based methods had the widest dynamic range between regions. Average percentage test-retest differences were smallest for the parametric maps with restricted base ranges; similarly ICCs were highest for these (up to 0.86) but unacceptably low for VOI-derived VD estimates at the low doses of injected radioactivity (0.24/0.04). Our data can inform the choice of methodology for a given biological problem.

[Neurobiological early diagnosis of Alzheimer's disease]

In order to improve diagnosis of Alzheimer's disease (AD), candidate biological markers in CSF as well as structural and functional imaging were investigated. Biomarkers are clearly needed to support detection of incipient AD in subjects with mild cognitive impairment (MCI). To date the most promising core candidate markers are total and hyperphosphorylated tau protein and amyloid beta peptides in the CSF, as well as hippocampus and whole brain volumetry using MRI. None of the candidates has been finally validated and established for clinical routine so far. International controlled multicenter cooperative studies are ongoing to further develop these core diagnostic marker candidates (phase III). The core markers are reviewed in detail. Promising novel approaches are discussed.

Brain opioid receptor binding in early abstinence from opioid dependence: positron emission tomography study

BACKGROUND

Although opioid receptor function in humans is clearly reduced during opioid dependence, what happens to the receptor in early abstinence is not understood.

AIMS

This study sought to examine changes in opioid receptor availability in early abstinence from opioid dependence.

METHOD

Ten people with opioid dependence who had completed in-patient detoxification and 20 healthy controls underwent [11C]-diprenorphine positron emission tomography. Clinical variables were assessed with structured questionnaires. Opioid receptor binding was characterised as the volume of distribution of [11C]-diprenorphine using a template of predefined brain volumes and an exploratory voxel-by-voxel analysis.

RESULTS

Compared with controls, participants with opioid dependence had increased [11C]-diprenorphine binding in the whole brain and in 15 of the 21 a priori regions studied.

CONCLUSIONS

This study suggests that opioid receptor binding is increased throughout the brain in early abstinence from dependent opioid use. These data complement the findings in cocaine and alcohol dependence.

Exploring the physiological effects of double-cone coil TMS over the medial frontal cortex on the anterior cingulate cortex: an H2(15)O PET study

Transcranial magnetic stimulation (TMS) using a double-cone coil over the medial frontal cortex has the potential to clarify the function of the anterior cingulate cortex (ACC) in cognition, emotion and mood disorders. Following demonstration of disruption of performance on psychological tasks closely linked to cingulate function using this TMS technique, the current study aimed to directly measure the regional distribution of physiological effects of stimulation in the brain with H2(15)O PET. Experiment 1 assessed the effect of increasing numbers of pulse trains of TMS on regional cerebral blood flow (rCBF). Experiment 2 assessed the capacity of medial frontal TMS to modulate brain activity associated with the Stroop task using medial parietal TMS as a control site of stimulation. SPM99 analyses, using the ACC as a region of interest, revealed clusters of increased rCBF during medial frontal TMS in Brodmann area 24 and reduced rCBF in more ventral ACC, the latter occurring in both experiments. In a whole-brain analysis, striking changes in rCBF were observed distal to the ACC following medial frontal TMS. Although TMS reliably affected Stroop task performance in early trials, there was no interaction between TMS and Stroop condition in rCBF. Our results suggest that medial frontal TMS using the double-cone coil can affect ACC activity. However, a number of more distal cortical areas were also affected in these experiments. These additional changes may reflect either 'downstream' effects of altered cingulate cortex activity or direct effects of the coil.

Pharmacoresistance in epilepsy: a pilot PET study with the P-glycoprotein substrate R-[(11)C]verapamil

PURPOSE AND METHODS

Regional overexpression of the multidrug transporter P-glycoprotein (P-gp) in epileptic brain tissue may lower target site concentrations of antiepileptic drugs and thus contribute to pharmacoresistance in epilepsy. We used the P-gp substrate R-[(11)C]verapamil and positron emission tomography (PET) to test for differences in P-gp activity between epileptogenic and nonepileptogenic brain regions of patients with drug-resistant unilateral temporal lobe epilepsy (n = 7). We compared R-[(11)C]verapamil kinetics in homologous brain volumes of interest (VOIs) located ipsilateral and contralateral to the seizure focus.

RESULTS

Among different VOIs, radioactivity was highest in the choroid plexus. The hippocampal VOI could not be used for data analysis because it was contaminated by spill-in of radioactivity from the adjacent choroid plexus. In several other temporal lobe regions that are known to be involved in seizure generation and propagation ipsilateral influx rate constants K(1) and efflux rate constants k(2) of R-[(11)C]verapamil were descriptively increased as compared to the contralateral side. Parameter asymmetries were most prominent in parahippocampal and ambient gyrus (K(1), range: -3.8% to +22.3%; k(2), range: -2.3% to +43.9%), amygdala (K(1), range: -20.6% to +31.3%; k(2), range: -18.0% to +38.9%), medial anterior temporal lobe (K(1), range: -8.3% to +14.5%; k(2), range: -14.5% to +31.0%) and lateral anterior temporal lobe (K(1), range: -20.7% to +16.8%; k(2), range: -24.4% to +22.6%). In contrast to temporal lobe VOIs, asymmetries were minimal in a region presumably not involved in epileptogenesis located outside the temporal lobe (superior parietal gyrus, K(1), range: -3.7% to +4.5%; k(2), range: -4.2% to +5.8%). In 5 of 7 patients, ipsilateral efflux (k(2)) increases were more pronounced than ipsilateral influx (K(1)) increases, which resulted in ipsilateral reductions (10%-26%) of R-[(11)C]verapamil distribution volumes (DV). However, for none of the examined brain regions, any of the differences in K(1), k(2) and DV between the epileptogenic and the nonepileptogenic hemisphere reached statistical significance (p > 0.05, Wilcoxon matched pairs test).

CONCLUSIONS

Even though we failed to detect statistically significant differences in R-[(11)C]verapamil model parameters between epileptogenic and nonepileptogenic brain regions, it cannot be excluded from our pilot data in a small sample size of patients that regionally enhanced P-gp activity might contribute to drug resistance in some patients with temporal lobe epilepsy.

Multiclassifier fusion in human brain MR segmentation: modelling convergence

Segmentations of MR images of the human brain can be generated by propagating an existing atlas label volume to the target image. By fusing multiple propagated label volumes, the segmentation can be improved. We developed a model that predicts the improvement of labelling accuracy and precision based on the number of segmentations used as input. Using a cross-validation study on brain image data as well as numerical simulations, we verified the model. Fit parameters of this model are potential indicators of the quality of a given label propagation method or the consistency of the input segmentations used.

Brain functional localization: a survey of image registration techniques

Functional localization is a concept which involves the application of a sequence of geometrical and statistical image processing operations in order to define the location of brain activity or to produce functional/parametric maps with respect to the brain structure or anatomy. Considering that functional brain images do not normally convey detailed structural information and, thus, do not present an anatomically specific localization of functional activity, various image registration techniques are introduced in the literature for the purpose of mapping functional activity into an anatomical image or a brain atlas. The problems addressed by these techniques differ depending on the application and the type of analysis, i.e., single-subject versus group analysis. Functional to anatomical brain image registration is the core part of functional localization in most applications and is accompanied by intersubject and subject-to-atlas registration for group analysis studies. Cortical surface registration and automatic brain labeling are some of the other tools towards establishing a fully automatic functional localization procedure. While several previous survey papers have reviewed and classified general-purpose medical image registration techniques, this paper provides an overview of brain functional localization along with a survey and classification of the image registration techniques related to this problem.

Automatic detection and quantification of hippocampal atrophy on MRI in temporal lobe epilepsy: a proof-of-principle study

In temporal lobe epilepsy (TLE), hippocampal atrophy (HA) is a marker of poor prognosis regarding seizure remission, but predicts success of anterior temporal lobe resection. Manual quantification of HA on MRI is time-consuming and limited by investigator availability. Normal ranges of hippocampal volumes, both in absolute terms and relative to intracranial volume, and of hippocampal asymmetry were defined using an automatic label propagation and decision fusion technique based on thirty manually derived atlases of healthy controls. Manual test-retest reliability and overlaps of automatically and manually determined hippocampal volumes were quantified with similarity indices (SIs). Correct clinical identification of ipsilateral HA, and contralaterally normal hippocampal volumes, was determined in nine patients with histologically confirmed hippocampal sclerosis in terms of volumes and asymmetry indices (AIs) for standard statistical thresholds and with receiver operating characteristic (ROC) analysis. Manual test-retest reliability was very high, with SIs between 0.87 and 0.90. Manual and automatic hippocampus labels overlapped with a SI of 0.83 on the unaffected but with 0.76 on the atrophic side. Accuracy was higher for less atrophic hippocampi. The automatic method correctly identified 6/9 HAs in terms of absolute volume, 7/9 in terms of relative volume at a standard 2 SD threshold, and 9/9 for AIs. ROC-determined thresholds allowed clinically desirable correct identification of all HAs (100% sensitivity) with 85-100% specificity for volumes, and 100% specificity for AIs. The method has the potential to automatically detect unilateral HA, but further work is needed to determine its performance in detecting clinically important bilateral disease.

A systematic comparison of kinetic modelling methods generating parametric maps for [(11)C]-(R)-PK11195

[(11)C]-(R)-PK11195 is presently the most widely used radiotracer for the monitoring of microglia activity in the central nervous system (CNS). Microglia, the resident immune cells of the brain, play a critical role in acute and chronic diseases of the central nervous system and in host defence against neoplasia. The purpose of this investigation was to evaluate the reliability and sensitivity of five kinetic modelling methods for the formation of parametric maps from dynamic [(11)C]-(R)-PK11195 studies. The methods we tested were the simplified reference tissue model (SRTM), basis pursuit, a simple target-to-reference ratio, the Logan plot and a wavelet based Logan plot. For the reliability assessment, the test-retest data consisted of four Alzheimer's patients that were scanned twice at approximately a six-week interval. For the sensitivity assessment, comparison of [(11)C]-(R)-PK11195 binding in Huntington's disease (HD) patients and normal subjects was performed using a group contrast to localize significant increases in mean pixel volume of distribution (VD) in HD. In all instances, a reference region kinetic extracted by a supervised clustering technique was used as input function. Reliability was assessed by use of the intra-class correlation coefficient (ICC) across a wide set of anatomical regions and it was found that the wavelet-based Logan plot, basis pursuit and SRTM gave the highest ICC values on average. The same methods produced the highest z-scores resulting from increases in mean striatal VD in HD patients compared with controls. The reference-to-target ratio and the Logan graphical approach were significantly less reliable and less sensitive.

Measurement of methylphenidate-induced change in extrastriatal dopamine concentration using [11C]FLB 457 PET

[(11)C]FLB 457 is a very high-affinity radiotracer that allows the measurement of dopamine D(2/3) receptor availability in regions of the brain where densities are very low, such as the cerebral cortex. It is not known if [(11)C]FLB 457 binding is sensitive to the concentration of endogenous dopamine in humans in a manner analogous to [(11)C]raclopride and [(123)I]IBZM in the striatum. To test this possibility, extrastriatal [(11)C]FLB 457 binding was measured at baseline and after the oral administration of 40 to 60 mg of the psychostimulant methylphenidate (MP) in 12 healthy volunteers using positron emission tomography (PET) in a balanced-order, double-blind design. The dynamic PET data were quantified using a two-tissue compartment model with a metabolite-corrected arterial plasma input function. Two volunteers were excluded because of excessive head movement. In the remainder, MP caused significant reductions in the volume of distribution (VD) in temporal and frontal cortical regions and thalamus, suggesting that [(11)C]FLB 457 binding is sensitive to endogenous dopamine concentration. Moreover, the change in [(11)C]FLB 457 binding after MP correlated with the dose of MP (in mg/kg body weight) in all regions assessed. We conclude that MP in doses within the therapeutic range for the treatment of attention deficit hyperactivity disorder causes increases in dopamine concentrations in extrastriatal regions and that [(11)C]FLB 457 PET may be a useful tool for the assessment of change in dopamine concentration in these areas in humans.

Quantification of PET studies with the very high-affinity dopamine D2/D3 receptor ligand [11C]FLB 457: re-evaluation of the validity of using a cerebellar reference region

The very high-affinity position emission tomography (PET) radioligand [(11)C]FLB 457 was developed in order to study extrastriatal tissues, where the density of dopamine D(2)/D(3) receptors is one to two orders of magnitude lower than in the striatum. The present study investigated the validity of using the cerebellum as a reference region. Ten healthy volunteers underwent a 90-min dynamic PET study after the bolus injection of [(11)C]FLB 457. The total volume of distribution (VD(t)) was estimated for the thalamus, hippocampus, frontal cortex, and cerebellum using a two-tissue compartmental model with a metabolite-corrected arterial plasma input function. VD(t) was sensitive to co-injected stable FLB 457 in all regions, including the cerebellum. Ex vivo saturation studies were also conducted in 17 rats where the dose of stable ligand was varied over five orders of magnitude. Specific binding was estimated to account for more than half of the rat cerebellar uptake of [(11)C]FLB 457, questioning the latter as an estimate of nonspecific binding in human PET studies. To check whether the cerebellum is a reference region, the binding potential (BP) was calculated either from the VD(t) ratio or using the simplified reference tissue model (SRTM). A non-negligible density of D(2)/D(3) receptors in the cerebellum was shown to lead to underestimation of BP as well as erroneous estimation of differential occupancies. Binging potential estimates from the SRTM were found to be sensitive to changes in cerebral blood flow, providing further evidence for caution in the use of the cerebellum as a reference region in measures of [(11)C]FLB 457 binding.

Virtual spatial registration of stand-alone fNIRS data to MNI space

The registration of functional brain data to common stereotaxic brain space facilitates data sharing and integration across different subjects, studies, and even imaging modalities. Thus, we previously described a method for the probabilistic registration of functional near-infrared spectroscopy (fNIRS) data onto Montreal Neurological Institute (MNI) coordinate space that can be used even when magnetic resonance images of the subjects are not available. This method, however, requires the careful measurement of scalp landmarks and fNIRS optode positions using a 3D-digitizer. Here we present a novel registration method, based on simulations in place of physical measurements for optode positioning. First, we constructed a holder deformation algorithm and examined its validity by comparing virtual and actual deformation of holders on spherical phantoms and real head surfaces. The discrepancies were negligible. Next, we registered virtual holders on synthetic heads and brains that represent size and shape variations among the population. The registered positions were normalized to MNI space. By repeating this process across synthetic heads and brains, we statistically estimated the most probable MNI coordinate values, and clarified errors, which were in the order of several millimeters across the scalp, associated with this estimation. In essence, the current method allowed the spatial registration of completely stand-alone fNIRS data onto MNI space without the use of supplementary measurements. This method will not only provide a practical solution to the spatial registration issues in fNIRS studies, but will also enhance cross-modal communications within the neuroimaging community.

Validation of a tracer kinetic model for the quantification of 5-HT(2A) receptors in human brain with [(11)C]MDL 100,907

The positron emission tomography (PET) ligand [(11)C]MDL 100,907 has previously been introduced to image the serotonin 2A (5-HT(2A)) receptor in human brain. The aim of this work was to contribute to the verification of the tracer kinetic modelling in human studies. Five healthy volunteers were scanned twice after intravenous bolus injection of approximately 370 MBq [(11)C]MDL 100,907 using dynamic PET. One scan was performed under baseline condition, the other scan commenced 90 mins after a single oral dose of 30 mg of the antidepressant mirtazapine, which binds to the 5-HT(2A) receptor. There did not appear to be radiolabelled metabolites of [(11)C]MDL 100,907 in human plasma, which are likely to cross the blood-brain barrier. Total volumes of distribution VD in 11 different brain regions were estimated using a reversible, two tissue, four rate constants compartment model with a variable fractional blood volume term and the metabolite-corrected plasma input function. There were no significant changes of the VD in the cerebellum between the baseline and the blocked scans confirming the cerebellum as a region devoid of displaceable binding. Regional estimates of binding potential were then obtained indirectly using the cerebellar VD and occupancies calculated. The mean occupancy with this clinically effective dose of mirtazapine was 60% without significant regional differences. This study confirmed the use of an arterial input kinetic model for the quantification of 5-HT(2A) receptor binding with [(11)C]MDL 100,907 and the use of the cerebellum as a reference region for the free and nonspecific binding.

Groupwise combined segmentation and registration for atlas construction

The creation of average anatomical atlases has been a growing area of research in recent years. It is of increased value to construct representations of, not only intensity atlases, but also their segmentation into required tissues or structures. This paper presents novel groupwise combined segmentation and registration approaches, which aim to simultaneously improve both the alignment of intensity images to their average shape, as well as the segmentations of structures in the average space. An iterative EM framework is used to build average 3D MR atlases of populations for which prior atlases do not currently exist: preterm infants at one- and two-years old. These have been used to quantify the growth of tissues occurring between these ages.

Statistical neuroanatomy of the human inferior frontal gyrus and probabilistic atlas in a standard stereotaxic space

We manually defined the inferior frontal gyrus (IFG) on high-resolution MRIs in native space in 30 healthy subjects (15 female, median age 31 years; 15 male, median age 30 years), resulting in 30 individual atlases. Using standard software (SPM99), these were spatially transformed to a widely used stereotaxic space (MNI/ICBM 152) to create probabilistic maps. In native space, the total IFG volume was on average 5%, and the gray matter (GM) portion 12% larger in women (not significant). Expressed as a percentage of ipsilateral frontal lobe volume (i.e., correcting for brain size), the IFG was an average of 20%, and the GM portion of the IFG 27%, larger in women (P < 0.005). Correcting for total lobar volume yielded the same result. No asymmetry was found in IFG volumes. There were significant positional differences between the right and left IFGs, with the right IFG being further lateral in both native and stereotaxic space. Variability was similar on the left and right, but more pronounced anteriorly and superiorly. We show differences in IFG volume, composition, and position between sexes and between hemispheres. Applications include probabilistic determination of location in group studies, automatic labeling of new scans, and detection of anatomical abnormalities in patients.

Automated template-based PET region of interest analyses in the aging brain

The definition of regions of interest for PET data analysis poses a number of complex problems. While studies have shown that regions drawn on a template can be appropriate for extracting data for normal healthy subjects, it is unclear how these results can be applied to different populations. In this study, we focused on the aging population and examined how different parameters in the template data-extraction process may affect the accuracy of the results. We first present an automated method for extracting PET counts using a region-of-interest approach within a template framework. Then, we discuss two studies in which we measure the effects of varying specific parameters in this process. In study 1 we examined three parameters that may influence this process: choice of template, region, and threshold. In study 2 we focused on the hippocampus. We considered 6 different templates, and examined how well the subject-specific hippocampal masks overlapped with each other and with the template hippocampal masks after normalization. While the data in the older cohort are more variable than the normal population, the results suggest that using an appropriate template and selecting the correct parameters for the template-based ROI method can provide template-extracted counts that are highly correlated to counts extracted using subject-specific ROIs.

Automatic anatomical brain MRI segmentation combining label propagation and decision fusion

Regions in three-dimensional magnetic resonance (MR) brain images can be classified using protocols for manually segmenting and labeling structures. For large cohorts, time and expertise requirements make this approach impractical. To achieve automation, an individual segmentation can be propagated to another individual using an anatomical correspondence estimate relating the atlas image to the target image. The accuracy of the resulting target labeling has been limited but can potentially be improved by combining multiple segmentations using decision fusion. We studied segmentation propagation and decision fusion on 30 normal brain MR images, which had been manually segmented into 67 structures. Correspondence estimates were established by nonrigid registration using free-form deformations. Both direct label propagation and an indirect approach were tested. Individual propagations showed an average similarity index (SI) of 0.754+/-0.016 against manual segmentations. Decision fusion using 29 input segmentations increased SI to 0.836+/-0.009. For indirect propagation of a single source via 27 intermediate images, SI was 0.779+/-0.013. We also studied the effect of the decision fusion procedure using a numerical simulation with synthetic input data. The results helped to formulate a model that predicts the quality improvement of fused brain segmentations based on the number of individual propagated segmentations combined. We demonstrate a practicable procedure that exceeds the accuracy of previous automatic methods and can compete with manual delineations.

Converging language streams in the human temporal lobe

There is general agreement that, after initial processing in unimodal sensory cortex, the processing pathways for spoken and written language converge to access verbal meaning. However, the existing literature provides conflicting accounts of the cortical location of this convergence. Most aphasic stroke studies localize verbal comprehension to posterior temporal and inferior parietal cortex (Wernicke's area), whereas evidence from focal cortical neurodegenerative syndromes instead implicates anterior temporal cortex. Previous functional imaging studies in normal subjects have failed to reconcile these opposing positions. Using a functional imaging paradigm in normal subjects that used spoken and written narratives and multiple baselines, we demonstrated common activation during implicit comprehension of spoken and written language in inferior and lateral regions of the left anterior temporal cortex and at the junction of temporal, occipital, and parietal cortex. These results indicate that verbal comprehension uses unimodal processing streams that converge in both anterior and posterior heteromodal cortical regions in the left temporal lobe.

An automated method for the extraction of regional data from PET images

Manual drawing of regions of interest (ROIs) on brain positron emission tomography (PET) images is labour intensive and subject to intra- and inter-individual variations. To standardize analysis and improve the reproducibility of PET measures, we have developed image analysis software for automated quantification of PET data. The method is based on the individualization of a set of standard ROIs using a magnetic resonance (MR) image co-registered with the PET image. To evaluate the performance of this automated method, the software-based quantification has been compared with conventional manual quantification of PET images obtained using three different PET radiotracers: [(11)C]-WAY 100635, [(11)C]-raclopride and [(11)C]-DASB. Our results show that binding potential estimates obtained using the automated method correlate highly with those obtained by trained raters using manual delineation of ROIs for frontal and temporal cortex, thalamus, and striatum (global intraclass correlation coefficient >0.8). For the three radioligands, the software yields time-activity data that are similar (within 8%) to those obtained by manual quantification, eliminates investigator-dependent variability, considerably shortens the time required for analysis and thus provides an alternative method for accurate quantification of PET data.

An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest

In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.

Diffeomorphic registration using B-splines

In this paper we propose a diffeomorphic non-rigid registration algorithm based on free-form deformations (FFDs) which are modelled by B-splines. In contrast to existing non-rigid registration methods based on FFDs the proposed diffeomorphic non-rigid registration algorithm based on free-form deformations (FFDs) which are modelled by B-splines. To construct a diffeomorphic transformation we compose a sequence of free-form deformations while ensuring that individual FFDs are one-to-one transformations. We have evaluated the algorithm on 20 normal brain MR images which have been manually segmented into 67 anatomical structures. Using the agreement between manual segmentation and segmentation propagation as a measure of registration quality we have compared the algorithm to an existing FFD registration algorithm and a modified FFD registration algorithm which penalises non-diffeomorphic transformations. The results show that the proposed algorithm generates diffeomorphic transformations while providing similar levels of performance as the existing FFD registration algorithm in terms of registration accuracy.