Comparison of fMRI coregistration results between human experts and software solutions in patients and healthy subjects

Improved dynamic distortion correction for fMRI using single-echo EPI and a readout-reversed first image (REFILL)

The boundaries between tissues with different magnetic susceptibilities generate inhomogeneities in the main magnetic field which change over time due to motion, respiration and system instabilities. The dynamically changing field can be measured from the phase of the fMRI data and corrected. However, methods for doing so need multi-echo data, time-consuming reference scans and/or involve error-prone processing steps, such as phase unwrapping, which are difficult to implement robustly on the MRI host. The improved dynamic distortion correction method we propose is based on the phase of the single-echo EPI data acquired for fMRI, phase offsets calculated from a triple-echo, bipolar reference scan of circa 3-10 s duration using a method which avoids the need for phase unwrapping and an additional correction derived from one EPI volume in which the readout direction is reversed. This Reverse-Encoded First Image and Low resoLution reference scan (REFILL) approach is shown to accurately measure B0 as it changes due to shim, motion and respiration, even with large dynamic changes to the field at 7 T, where it led to a > 20% increase in time-series signal to noise ratio compared to data corrected with the classic static approach. fMRI results from REFILL-corrected data were free of stimulus-correlated distortion artefacts seen when data were corrected with static field mapping. The method is insensitive to shim changes and eddy current differences between the reference scan and the fMRI time series, and employs calculation steps that are simple and robust, allowing most data processing to be performed in real time on the scanner image reconstruction computer. These improvements make it feasible to routinely perform dynamic distortion correction in fMRI.

Improving sensitivity, specificity, and reproducibility of individual brainstem activation

Functional imaging of the brainstem may open new avenues for clinical diagnostics. However, for reliable assessments of brainstem activation, further efforts improving signal quality are needed. Six healthy subjects performed four repeated functional magnetic resonance imaging (fMRI) sessions on different days with jaw clenching as a motor task to elicit activation in the trigeminal motor nucleus. Functional images were acquired with a 7 T MR scanner using an optimized multiband EPI sequence. Activation measures in the trigeminal nucleus and a control region were assessed using different physiological noise correction methods (aCompCor and RETROICOR-based approaches with variable numbers of regressors) combined with cerebrospinal fluid or brainstem masking. Receiver-operating characteristic analyses accounting for sensitivity and specificity, activation overlap analyses to estimate the reproducibility between sessions, and intraclass correlation analyses (ICC) for testing reliability between subjects and sessions were used to systematically compare the physiological noise correction approaches. Masking the brainstem led to increased activation in the target ROI and resulted in higher values for the area under the curve (AUC) as a combined measure for sensitivity and specificity. With the highest values for AUC, activation overlap, and ICC, the most favorable physiological noise correction method was to control for the cerebrospinal fluid time series (aCompCor with one regressor). Brainstem motor nuclei activation can be reliably identified using high-field fMRI with optimized acquisition and processing strategies—even on single-subject level. Applying specific physiological noise correction methods improves reproducibility and reliability of brainstem activation encouraging future clinical applications.

A method for the dynamic correction of B0-related distortions in single-echo EPI at 7T

We propose a method to calculate field maps from the phase of each EPI in an fMRI time series. These field maps can be used to correct the corresponding magnitude images for distortion caused by inhomogeneity in the static magnetic field. In contrast to conventional static distortion correction, in which one ‘snapshot’ field map is applied to all subsequent fMRI time points, our method also captures dynamic changes to B₀ which arise due to motion and respiration. The approach is based on the assumption that the non-B₀-related contribution to the phase measured by each radio-frequency coil, which is dominated by the coil sensitivity, is stable over time and can therefore be removed to yield a field map from EPI.

Our solution addresses imaging with multi-channel coils at ultra-high field (7 T), where phase offsets vary rapidly in space, phase processing is non-trivial and distortions are comparatively large. We propose using dual-echo gradient echo reference scan for the phase offset calculation, which yields estimates with high signal-to-noise ratio. An extrapolation method is proposed which yields reliable estimates for phase offsets even where motion is large and a tailored phase unwrapping procedure for EPI is suggested which gives robust results in regions with disconnected tissue or strong signal decay.

Phase offsets are shown to be stable during long measurements (40 min) and for large head motions. The dynamic distortion correction proposed here is found to work accurately in the presence of large motion (up to 8.1°), whereas a conventional method based on single field map fails to correct or even introduces distortions (up to 11.2 mm). Finally, we show that dynamic unwarping increases the temporal stability of EPI in the presence of motion.

Our approach can be applied to any EPI measurements without the need for sequence modification.

Landmark-free geometric methods in biological shape analysis

In this paper, we propose a new approach for computing a distance between two shapes embedded in three-dimensional space. We take as input a pair of triangulated genus zero surfaces that are topologically equivalent to spheres with no holes or handles, and construct a discrete conformal map f between the surfaces. The conformal map is chosen to minimize a symmetric deformation energy Esd(f) which we introduce. This measures the distance of f from an isometry, i.e. a non-distorting correspondence. We show that the energy of the minimizing map gives a well-behaved metric on the space of genus zero surfaces. In contrast to most methods in this field, our approach does not rely on any assignment of landmarks on the two surfaces. We illustrate applications of our approach to geometric morphometrics using three datasets representing the bones and teeth of primates. Experiments on these datasets show that our approach performs remarkably well both in shape recognition and in identifying evolutionary patterns, with success rates similar to, and in some cases better than, those obtained by expert observers.

A framework to analyze cerebral mean diffusivity using surface guided diffusion mapping in diffusion tensor imaging

The mean diffusivity (MD) value has been used to describe microstructural properties in Diffusion Tensor Imaging (DTI) in cortical gray matter (GM). Recently, researchers have applied a cortical surface generated from the T1-weighted volume. When the DTI data are analyzed using the cortical surface, it is important to assign an accurate MD value from the volume space to the vertex of the cortical surface, considering the anatomical correspondence between the DTI and the T1-weighted image. Previous studies usually sampled the MD value using the nearest-neighbor (NN) method or Linear method, even though there are geometric distortions in diffusion-weighted volumes. Here we introduce a Surface Guided Diffusion Mapping (SGDM) method to compensate for such geometric distortions. We compared our SGDM method with results using NN and Linear methods by investigating differences in the sampled MD value. We also projected the tissue classification results of non-diffusion-weighted volumes to the cortical midsurface. The CSF probability values provided by the SGDM method were lower than those produced by the NN and Linear methods. The MD values provided by the NN and Linear methods were significantly greater than those of the SGDM method in regions suffering from geometric distortion. These results indicate that the NN and Linear methods assigned the MD value in the CSF region to the cortical midsurface (GM region). Our results suggest that the SGDM method is an effective way to correct such mapping errors.

Intensity-Curvature Measurement Approaches for the Diagnosis of Magnetic Resonance Imaging Brain Tumors

This research presents signal-image post-processing techniques called Intensity-Curvature Measurement Approaches with application to the diagnosis of human brain tumors detected through Magnetic Resonance Imaging (MRI). Post-processing of the MRI of the human brain encompasses the following model functions: (i) bivariate cubic polynomial, (ii) bivariate cubic Lagrange polynomial, (iii) monovariate sinc, and (iv) bivariate linear. The following Intensity-Curvature Measurement Approaches were used: (i) classic-curvature, (ii) signal resilient to interpolation, (iii) intensity-curvature measure and (iv) intensity-curvature functional. The results revealed that the classic-curvature, the signal resilient to interpolation and the intensity-curvature functional are able to add additional information useful to the diagnosis carried out with MRI. The contribution to the MRI diagnosis of our study are: (i) the enhanced gray level scale of the tumor mass and the well-behaved representation of the tumor provided through the signal resilient to interpolation, and (ii) the visually perceptible third dimension perpendicular to the image plane provided through the classic-curvature and the intensity-curvature functional.

The benefits of skull stripping in the normalization of clinical fMRI data

Establishing a reliable correspondence between lesioned brains and a template is challenging using current normalization techniques. The optimum procedure has not been conclusively established, and a critical dichotomy is whether to use input data sets which contain skull signal, or whether skull signal should be removed. Here we provide a first investigation into whether clinical fMRI benefits from skull stripping, based on data from a presurgical language localization task. Brain activation changes related to deskulled/not-deskulled input data are determined in the context of very recently developed (New Segment, Unified Segmentation) and standard normalization approaches. Analysis of structural and functional data demonstrates that skull stripping improves language localization in MNI space — particularly when used in combination with the New Segment normalization technique.

•

First investigation of the possible effects of skull-stripping with clinical fMRI data.

•

Comparison of standard and most recent normalization approaches.

•

Skull stripping improves language localization in MNI space.

A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps

Meta-analyses are essential to summarize the results of the growing number of neuroimaging studies in psychiatry, neurology and allied disciplines. Image-based meta-analyses use full image information (i.e. the statistical parametric maps) and well-established statistics, but images are rarely available making them highly unfeasible. Peak-probability meta-analyses such as activation likelihood estimation (ALE) or multilevel kernel density analysis (MKDA) are more feasible as they only need reported peak coordinates. Signed-differences methods, such as signed differential mapping (SDM) build upon the positive features of existing peak-probability methods and enable meta-analyses of studies comparing patients with controls. In this paper we present a new version of SDM, named Effect Size SDM (ES-SDM), which enables the combination of statistical parametric maps and peak coordinates and uses well-established statistics. We validated the new method by comparing the results of an ES-SDM meta-analysis of studies on the brain response to fearful faces with the results of a pooled analysis of the original individual data. The results showed that ES-SDM is a valid and reliable coordinate-based method, whose performance might be additionally increased by including statistical parametric maps. We anticipate that ES-SDM will be a helpful tool for researchers in the fields of psychiatry, neurology and allied disciplines.

Clinical fMRI: evidence for a 7T benefit over 3T

Despite there being an increasing number of installations of ultra high field MR systems (>3T) in clinical environments, no functional patient investigations have yet examined possible benefits for functional diagnostics. Here we performed presurgical localization of the primary motor hand area on 3T and 7T Siemens scanners with identical investigational procedures and comparable system specific sequence optimizations. Results from 17 patients showed significantly higher functional sensitivity of the 7T system measured via percent signal change, mean t-values, number of suprathreshold voxels and contrast to noise ratio. On the other hand, 7T data suffered from a significant increase of artifacts (ghosting, head motion). We conclude that ultra high field systems provide a clinically relevant increase of functional sensitivity for patient investigations.

How much are clinical fMRI reports influenced by standard postprocessing methods? An investigation of normalization and region of interest effects in the medial temporal lobe

Recent evidence has indicated that standard postprocessing methods such as template-based region of interest (ROI) definition and normalization of individual brains to a standard template may influence final outcome of functional magnetic resonance imaging investigations. Here, we provide the first comprehensive investigation into whether ROI definition and normalization may also change the clinical interpretation of patient data. A series of medial temporal lobe epilepsy patients were investigated with a clinical memory paradigm and individually delineated as well as template-based ROIs. Different metrics for activation quantification were applied. Results show that the application of template-based ROIs can significantly change the clinical interpretation of individual patient data. This relates to sensitivity for brain activation and hemispheric dominance. We conclude that individual ROIs should be defined on nontransformed functional data and that use of more than one metric for activation quantification is beneficial.

[Methodological problems with clinical functional MRI investigations]

During presurgical diagnostics clinical functional magnetic resonance imaging is increasingly being performed to improve the management of epilepsy and tumor patients. Rapid technical developments in fMRI technology continuously further new diagnostic applications. Safe clinical application requires a profound and critical handling of the various methodological problems inherent with this complex technique. This article reviews relevant problems and solutions for patient investigations up to the preparation of an individual clinical fMRI report.

Does clinical memory fMRI provide a comprehensive map of medial temporal lobe structures?

Successful clinical application of fMRI tasks requires reliable knowledge about the brain structures mapped by the task. With memory fMRI, diverging evidence exists concerning the location of major signal sources as well as hippocampal contributions. To clarify these issues, we investigated a frequently applied memory test (home town walking) in 33 patients with unilateral medial temporal lobe pathology, comparing healthy and diseased hemispheres. We focused on a detailed investigation of individual fMRI maps on non-transformed high-resolution functional images. Results show a clear dominance of activations around the collateral sulcus, corresponding to parahippocampal and entorhinal cortex activities. Hippocampus activity was absent in the vast majority of patients. The diseased hemispheres showed lower activation than the healthy hemispheres. We conclude that (1) the investigated memory test may be successfully applied for evaluation of the parahippocampal cortex, (2) the hippocampus is not reliably mapped by the task, and (3) the methods described for investigation of individual high-resolution functional images allow generation of application profiles for clinical fMRI tasks.

Cortical lateralization of bilateral symmetric chin movements and clinical relevance in tumor patients—A high field BOLD–FMRI study

Although unilateral lesion studies concerning the opercular part of primary motor cortex report clinically severe motor deficits (e.g. anarthria, masticatory paralysis), functional lateralization of this area has not yet been addressed in neuroimaging studies. Using BOLD-FMRI, this study provides the first quantitative evaluation of a possible cortical lateralization of symmetric chin movements (rhythmic contraction of masticatory muscles) in right-handed healthy subjects and presurgical patients suffering tumorous lesions in the opercular primary motor cortex. Data were analyzed according to "activation volume" and "activation intensity". At group level, results showed a strong left-hemispheric dominance for chin movements in the group of healthy subjects. In contrast, patients indicated dominance of the healthy hemisphere. Here, a clinically relevant dissociation was found between "activation volume" and "activation intensity": Although "activation volume" may be clearly lateralized to the healthy hemisphere, "activation intensity" may indicate residual functionally important tissue close to the pathological tissue. In these cases, consideration of BOLD-FMRI maps with the exclusive focus on "activation volume" may lead to erroneous presurgical conclusions. We conclude that comprehensive analyses of presurgical fMRI data may help to avoid sustained postoperative motor deficits and dysarthria in patients with lesions in the opercular part of primary motor cortex.