Evaluating requirements for spatial resolution of fMRI for neurosurgical planning

Cues to body-related distortions and hallucinations? Spontaneous sensations correlate with EEG oscillatory activity recorded at rest in the somatosensory cortices

Body awareness may arise in the total absence of sensory input, as suggested by the spontaneous occurrence of normal and pathological (i.e., hallucinatory) bodily sensations. These phenomena may arise due to back-projections from higher-order cortical areas to the primary (SI) and secondary (SII) somatosensory cortices, and would appear to be reflected in cortical oscillatory activity in both SI and SII. Here, we set to investigate the relationship of SI and SII in SPS. Healthy participants underwent an EEG recording session at rest, and then completed an experiment on the perception of spontaneous sensations occurring on the hands. Cortical oscillatory activity was extracted from specified ROIs in the somatosensory cortices. The findings showed that (i) SPS perceived in the fingers correlated positively with alpha-band oscillations recorded in SI, and that (ii) SPS perceived in the palm correlated positively with gamma-band oscillations and negatively with beta-band oscillations recorded in SII. Apart from supporting the idea that the somatosensory cortices are involved in bodily awareness even in the absence of sensory input, these findings also suggest that default oscillatory activity in the somatosensory cortices reflects individual differences in bodily awareness. The results are interpreted in terms of neural and cognitive processes that may give rise to bodily awareness and modulate it, and their importance in understanding body perception distortions and bodily delusions and hallucinations is discussed.

Efficient de-noising of high-resolution fMRI using local and sub-band information

BACKGROUND

High-resolution fMRI, useful for accurate brain mapping, suffers from low functional sensitivity at a reasonable acquisition time. Conventional smoothing techniques although reduce the noise and boost the sensitivity, but degrade the spatial resolution of fMRI.

NEW METHODS

We propose a novel spatial de-noising technique to increase sensitivity while preserving the boundaries of active regions in the high-resolution fMRI. A modified version of PCA that utilizes adjacent voxels information (LPCA) is first suggested for de-noising. This technique is then further empowered by its application to wavelet sub-bands (WLPCA).

RESULTS

Proposed techniques were assessed on both simulated and experimental data. Identifiablity index was calculated for evaluation of the denoising on the simulated data. Maximum and mean z-scores along with LAE and SSIM were reported on experimental data for two presented techniques as well as Guassian smoothing. WLPCA outperformed other techniques in Identifiablity index, for simulation, and in preserving maximum z-score, for experimental study.

COMPARISON WITH EXISTING METHODS

The presented technique was developed to simultaneously suppress the noise and preserve the boundaries of active areas against leakage. For first aim, its achievable mean z-score was compared to conventional Gaussian. For second aim, its maximum z-score was compared to that of no-smoothing. While Gaussian and no-smoothing can work fine with only one measure, WLPCA was able to improve both measures concurrently.

CONCLUSIONS

The local PCA based methods, and in particular WLPCA, is an effective noise reduction step that preserves the spatial resolution by preventing activity leakage of high-resolution fMRI data.

A mixed-effects, spatially varying coefficients model with application to multi-resolution functional magnetic resonance imaging data

Spatial resolution plays an important role in functional magnetic resonance imaging studies as the signal-to-noise ratio increases linearly with voxel volume. In scientific studies, where functional magnetic resonance imaging is widely used, the standard spatial resolution typically used is relatively low which ensures a relatively high signal-to-noise ratio. However, for pre-surgical functional magnetic resonance imaging analysis, where spatial accuracy is paramount, high-resolution functional magnetic resonance imaging may play an important role with its greater spatial resolution. High spatial resolution comes at the cost of a smaller signal-to-noise ratio. This begs the question as to whether we can leverage the higher signal-to-noise ratio of a standard functional magnetic resonance imaging study with the greater spatial accuracy of a high-resolution functional magnetic resonance imaging study in a pre-operative patient. To answer this question, we propose to regress the statistic image from a high resolution scan onto the statistic image obtained from a standard resolution scan using a mixed-effects model with spatially varying coefficients. We evaluate our model via simulation studies and we compare its performance with a recently proposed model that operates at a single spatial resolution. We apply and compare the two models on data from a patient awaiting tumor resection. Both simulation study results and the real data analysis demonstrate that our newly proposed model indeed leverages the larger signal-to-noise ratio of the standard spatial resolution scan while maintaining the advantages of the high spatial resolution scan.

The ovine motor cortex: A review of functional mapping and cytoarchitecture

In recent years, sheep (Ovis aries) have emerged as a useful animal model for neurological research due to their relatively large brain and blood vessel size, their cortical architecture, and their docile temperament. However, the functional anatomy of sheep brain is not as well studied as that of non-human primates, rodents, and felines. For example, while the location of the sheep motor cortex has been known for many years, there have been few studies of the somatotopy of the motor cortex and there were a range of discrepancies across them. The motivation for this review is to provide a definitive resource for studies of the sheep motor cortex. This work critically reviews the literature examining the organization of the motor cortex in sheep, utilizing studies that have applied direct electrical stimulation and histological methods A clearer understanding of the sheep brain will facilitate and progress the use of this species as a scientific animal model for neurological research.

Pre-Surgical fMRI Data Analysis Using a Spatially Adaptive Conditionally Autoregressive Model

Spatial smoothing is an essential step in the analysis of functional magnetic resonance imaging (fMRI) data. One standard smoothing method is to convolve the image data with a three-dimensional Gaussian kernel that applies a fixed amount of smoothing to the entire image. In pre-surgical brain image analysis where spatial accuracy is paramount, this method, however, is not reasonable as it can blur the boundaries between activated and deactivated regions of the brain. Moreover, while in a standard fMRI analysis strict false positive control is desired, for pre-surgical planning false negatives are of greater concern. To this end, we propose a novel spatially adaptive conditionally autoregressive model with variances in the full conditional of the means that are proportional to error variances, allowing the degree of smoothing to vary across the brain. Additionally, we present a new loss function that allows for the asymmetric treatment of false positives and false negatives. We compare our proposed model with two existing spatially adaptive conditionally autoregressive models. Simulation studies show that our model outperforms these other models; as a real model application, we apply the proposed model to the pre-surgical fMRI data of two patients to assess peri- and intra-tumoral brain activity.

The influence of spatial resolution and smoothing on the detectability of resting-state and task fMRI

Functional MRI blood oxygen level-dependent (BOLD) signal changes can be subtle, motivating the use of imaging parameters and processing strategies that maximize the temporal signal-to-noise ratio (tSNR) and thus the detection power of neuronal activity-induced fluctuations. Previous studies have shown that acquiring data at higher spatial resolutions results in greater percent BOLD signal changes, and furthermore that spatially smoothing higher resolution fMRI data improves tSNR beyond that of data originally acquired at a lower resolution. However, higher resolution images come at the cost of increased acquisition time, and the number of image volumes also influences detectability. The goal of our study is to determine how the detection power of neuronally induced BOLD fluctuations acquired at higher spatial resolutions and then spatially smoothed compares to data acquired at the lower resolutions with the same imaging duration. The number of time points acquired during a given amount of imaging time is a practical consideration given the limited ability of certain populations to lie still in the MRI scanner. We compare acquisitions at three different in-plane spatial resolutions (3.50×3.50mm(2), 2.33×2.33mm(2), 1.75×1.75mm(2)) in terms of their tSNR, contrast-to-noise ratio, and the power to detect both task-related activation and resting-state functional connectivity. The impact of SENSE acceleration, which speeds up acquisition time increasing the number of images collected, is also evaluated. Our results show that after spatially smoothing the data to the same intrinsic resolution, lower resolution acquisitions have a slightly higher detection power of task-activation in some, but not all, brain areas. There were no significant differences in functional connectivity as a function of resolution after smoothing. Similarly, the reduced tSNR of fMRI data acquired with a SENSE factor of 2 is offset by the greater number of images acquired, resulting in few significant differences in detection power of either functional activation or connectivity after spatial smoothing.

Systematic approximations of neural fields through networks of neural masses in the virtual brain

Full brain network models comprise a large-scale connectivity (the connectome) and neural mass models as the network's nodes. Neural mass models absorb implicitly a variety of properties in their constant parameters to achieve a reduction in complexity. In situations, where the local network connectivity undergoes major changes, such as in development or epilepsy, it becomes crucial to model local connectivity explicitly. This leads naturally to a description of neural fields on folded cortical sheets with local and global connectivities. The numerical approximation of neural fields in biologically realistic situations as addressed in Virtual Brain simulations (see http://thevirtualbrain.org/app/ (version 1.0)) is challenging and requires a thorough evaluation if the Virtual Brain approach is to be adapted for systematic studies of disease and disorders. Here we analyze the sampling problem of neural fields for arbitrary dimensions and provide explicit results for one, two and three dimensions relevant to realistically folded cortical surfaces. We characterize (i) the error due to sampling of spatial distribution functions; (ii) useful sampling parameter ranges in the context of encephalographic (EEG, MEG, ECoG and functional MRI) signals; (iii) guidelines for choosing the right spatial distribution function for given anatomical and geometrical constraints.

Pneumatically driven finger movement: a novel passive functional MR imaging technique for presurgical motor and sensory mapping

Two of the most common reasons for failure to obtain adequate preoperative functional data are inadequate task performance and excessive head motion. With an MR imaging-compatible pneumatically driven manipulandum, passive motor tasks elicited reproducible contralateral activation in the M1 and S1 in 10 healthy controls and 6 patients. The SMA was localized in all healthy controls and in 5 of 6 patients. Head motion was reduced in passive tasks compared with active tasks.

EEG current source density and the phenomenology of the default network

In recent years, there has been an increasing line of research dedicated to the investigation of the default mode network (DMN) of the brain and resting state networks. However, the mental activity of the DMN has not been rigorously assessed to date. The specific aims of the current study were 2-fold: First, we sought to determine whether the current source density (CSD) levels in the DMN would correspond to other neuroimaging techniques. Second, we sought to understand the subjective mental activity of the DMN during baseline recordings. This study was conducted with 63 nonclinical participants, 34 female and 29 males with a mean age of 19.2 years (standard deviation = 2.0). The participants were recorded in 8 conditions. First, 4-minute eyes-closed baseline (ECB) and eyes-opened baseline (EOB) were obtained. The participants then completed 3 assessment instruments and 3 image conditions while the electroencephalography (EEG) was continuously recorded. Participants completed subjective reports for baselines and image conditions. These were rated by 3 independent raters and compared for reliability using a random effects model with an absolute agreement definition. The mean CSD between all conditions differed significantly, in many but not all regions of interest in the DMN. Interestingly, as suggested by other studies, the DMN appears preferential to self-relevant, self-specific, or self-perceptive processes. The reliability analyses show α for interrater agreement for ECB at .95 and EOB at .96. The subjective reports obtained from the participants regarding the mental activities employed during baseline recordings correspond to attentional and self-regulatory processes, which may also implicate the resting state or DMN as playing a direct role in the maintenance of a complex behavior (eg, being still, attending, and self-regulating). Thus, attention and self-regulation constitute the phenomenology of the resting state (DMN) in this study. The results also demonstrate that EEG CSD is a useful method to examine the DMN during concept-specific tasks to elucidate the neural activity associated with these concepts. Standardized low-resolution electromagnetic tomography (sLORETA) can localize to 5 mm(3), which is comparable to the findings in functional magnetic resonance imaging (fMRI). However, sLORETA can provide data about the difference in activity between groups, individuals, or populations which in many cases fMRI cannot provide.

Special surgical considerations for functional brain mapping

The development of functional mapping techniques gives neurosurgeons many options for preoperative planning. Integrating functional and anatomic data can inform patient selection and surgical planning and makes functional mapping more accessible than when only invasive studies were available. However, the applications of functional mapping to neurosurgical patients are still evolving. Functional imaging remains complex and requires an understanding of the underlying physiologic and imaging characteristics. Neurosurgeons must be accustomed to interpreting highly processed data. Successful implementation of functional image-guided procedures requires efficient interactions between neurosurgeon, neurologist, radiologist, neuropsychologist, and others, but promises to enhance the care of patients.

Transcranial magnetic stimulation and extradural electrodes implanted on secondary auditory cortex for tinnitus suppression

Object

Tinnitus is a prevalent symptom, with clinical, pathophysiological, and treatment features analogous to pain. Noninvasive transcranial magnetic stimulation (TMS) and intracranial auditory cortex stimulation (ACS) via implanted electrodes into the primary or overlying the secondary auditory cortex have been developed to treat severe cases of intractable tinnitus.

Methods

A series of 43 patients who benefited transiently from 2 separate placebo-controlled TMS sessions underwent implantation of auditory cortex electrodes. Targeting was based on blood oxygen level–dependent activation evoked by tinnitus-matched sound, using functional MR imaging–guided neuronavigation.

Results

Thirty-seven percent of the patients responded to ACS with tonic stimulation. Of the 63% who were nonresponders, half benefited from burst stimulation. In total, 33% remained unaffected by the ACS. The average tinnitus reduction was 53% for the entire group. Burst stimulation was capable of suppressing tinnitus in more patients and was better than tonic stimulation, especially for noise-like tinnitus. For pure tone tinnitus, there were no differences between the 2 stimulation designs. The average pure tone tinnitus improvement was 71% versus 37% for noise-like tinnitus and 29% for a combination of both pure tone and noise-like tinnitus. Transcranial magnetic stimulation did not predict response to ACS, but in ACS responders, a correlation (r = 0.38) between the amount of TMS and ACS existed. A patient's sex, age, or tinnitus duration did not influence treatment outcome.

Conclusions

Intracranial ACS might become a valuable treatment option for severe intractable tinnitus. Better understanding of the pathophysiological mechanisms of tinnitus, predictive functional imaging tests, new stimulation designs, and other stimulation targets are needed to improve ACS results.

Regional and hemispheric determinants of language laterality: implications for preoperative fMRI

Language is typically a function of the left hemisphere but the right hemisphere is also essential in some healthy individuals and patients. This inter-subject variability necessitates the localization of language function, at the individual level, prior to neurosurgical intervention. Such assessments are typically made by comparing left and right hemisphere language function to determine "language lateralization" using clinical tests or fMRI. Here, we show that language function needs to be assessed at the region and hemisphere specific level, because laterality measures can be misleading. Using fMRI data from 82 healthy participants, we investigated the degree to which activation for a semantic word matching task was lateralized in 50 different brain regions and across the entire cortex. This revealed two novel findings. First, the degree to which language is lateralized across brain regions and between subjects was primarily driven by differences in right hemisphere activation rather than differences in left hemisphere activation. Second, we found that healthy subjects who have relatively high left lateralization in the angular gyrus also have relatively low left lateralization in the ventral precentral gyrus. These findings illustrate spatial heterogeneity in language lateralization that is lost when global laterality measures are considered. It is likely that the complex spatial variability we observed in healthy controls is more exaggerated in patients with brain damage. We therefore highlight the importance of investigating within hemisphere regional variations in fMRI activation, prior to neuro-surgical intervention, to determine how each hemisphere and each region contributes to language processing.

Long-Term Reproducibility Analysis of Fmri using Hand Motor Task

This article reports test-retest reproducibility of functional MRI (fMRI) measurement on brain activation elicited by auditory-cued sequential finger tapping. Eight right-handed volunteers participated in nine fMRI sessions, approximately eight weeks apart, for the duration of more than a year. The first scan session was repeated within a day to examine the intra-session reproducibility. The frequency of activation for neural substrates relevant to the task was constructed across the subjects and sessions. The spatial reproducibility was measured as the ratio of the size of the volume as well as its overlaps with respect to the first scan session from regions-of-interest in the selected motor circuitry. Consistent activation patterns between sessions and across subjects were observed in the sensorimotor areas such as the left primary, supplementary, and premotor areas, as well as in the right cerebellar areas without evidence of session-dependent trends. Quantitative analysis showed that the reproducibility measures varied within the range obtained from studies on fMRI reproducibility covering much shorter terms. Intra-session fMRI scans yielded slightly better reproducibility measures compared to the results obtained from other scan sessions. The findings suggest that the reproducible fMRI measurement can be obtained for long-term monitoring of brain function.

Automated classification of fMRI data employing trial-based imagery tasks

Automated interpretation and classification of functional MRI (fMRI) data is an emerging research field that enables the characterization of underlying cognitive processes with minimal human intervention. In this work, we present a method for the automated classification of human thoughts reflected on a trial-based paradigm using fMRI with a significantly shortened data acquisition time (less than one minute). Based on our preliminary experience with various cognitive imagery tasks, six characteristic thoughts were chosen as target tasks for the present work: right-hand motor imagery, left-hand motor imagery, right foot motor imagery, mental calculation, internal speech/word generation, and visual imagery. These six tasks were performed by five healthy volunteers and functional images were obtained using a T(*)(2)-weighted echo planar imaging (EPI) sequence. Feature vectors from activation maps, necessary for the classification of neural activity, were automatically extracted from the regions that were consistently and exclusively activated for a given task during the training process. Extracted feature vectors were classified using the support vector machine (SVM) algorithm. Parameter optimization, using a k-fold cross validation scheme, allowed the successful recognition of the six different categories of administered thought tasks with an accuracy of 74.5% (mean)+/-14.3% (standard deviation) across all five subjects. Our proposed study for the automated classification of fMRI data may be utilized in further investigations to monitor/identify human thought processes and their potential link to hardware/computer control.

Utility of neuronavigation and neuromonitoring in epilepsy surgery

The management of medically refractory epilepsy poses both a valuable therapeutic opportunity and a formidable technical challenge to epilepsy surgeons. Recent decades have produced significant advancements in the capabilities and availability of adjunctive tools in epilepsy surgery. In particular, image-based neuronavigation and electrophysiological neuromonitoring represent versatile and informative modalities that can assist a surgeon in performing safe and effective resections. In the present article the authors discuss these 2 subjects with reference to how they can be applied and what evidence supports their use. As technologies evolve with demonstrated and potential utility, it is important for all clinicians who deal with epilepsy to understand where neuronavigation and neuromonitoring stand in the present and what avenues for improvement exist for the future.

Neurofeedback fMRI-mediated learning and consolidation of regional brain activation during motor imagery

We report the long-term effect of real-time functional MRI (rtfMRI) training on voluntary regulation of the level of activation from a hand motor area. During the performance of a motor imagery task of a right hand, blood-oxygenation-level-dependent (BOLD) signal originating from a primary motor area was presented back to the subject in real-time. Demographically matched individuals also received the same procedure without valid feedback information. Followed by the initial rtfMRI sessions, both groups underwent two-week long, daily-practice of the task. Off-line data analysis revealed that the individuals in the experimental group were able to increase the level of BOLD signal from the regulatory target to a greater degree compared to the control group. Furthermore, the learned level of activation was maintained after the two-week period, with the recruitment of additional neural circuitries such as the hippocampus and the limbo-thalamo-cortical pathway. The activation obtained from the control group, in the absence of proper feedback, was indifferent across the training conditions. The level of BOLD activity from the target regulatory region was positively correlated with a self evaluative score within the experimental group, while the majority of control subjects had difficulty adopting a strategy to attain the desired level of functional regulation. Our results suggest that rtfMRI helped individuals learn how to increase region-specific cortical activity associated with a motor imagery task, and the level of increased activation in motor areas was consolidated after the two-week self-practice period, with the involvement of neural circuitries implicated in motor skill learning.

The use of neuroimaging to study behavior in patients with epilepsy

Structural and functional neuroimaging continues to play an increasing role in the presurgical evaluation of patients with epilepsy. In addition to its value in localizing the epileptogenic zone and eloquent cortex, neuroimaging is contributing to our understanding of mood comorbidity in epilepsy. Although the vast majority of research has focused on patients with temporal lobe epilepsy (TLE), neuroimaging studies of patients with extratemporal epilepsy and primary generalized epilepsy are increasing in number. In this review, structural and functional imaging modalities that have received considerable research attention in recent years are reviewed, and their strengths and limitations for understanding behavior in epilepsy are assessed. In addition, advances in multimodal imaging are discussed along with their potential application to the presurgical evaluation of patients with seizure disorders.

Atlas-based multichannel monitoring of functional MRI signals in real-time: automated approach

We report an automated method to simultaneously monitor blood-oxygenation-level-dependent (BOLD) MR signals from multiple cortical areas in real-time. Individual brain anatomy was normalized and registered to a pre-segmented atlas in standardized anatomical space. Subsequently, using real-time fMRI (rtfMRI) data acquisition, localized BOLD signals were measured and displayed from user-selected areas labeled with anatomical and Brodmann's Area (BA) nomenclature. The method was tested on healthy volunteers during the performance of hand motor and internal speech generation tasks employing a trial-based design. Our data normalization and registration algorithm, along with image reconstruction, movement correction and a data display routine were executed with enough processing and communication bandwidth necessary for real-time operation. Task-specific BOLD signals were observed from the hand motor and language areas. One of the study participants was allowed to freely engage in hand clenching tasks, and associated brain activities were detected from the motor-related neural substrates without prior knowledge of the task onset time. The proposed method may be applied to various applications such as neurofeedback, brain-computer-interface, and functional mapping for surgical planning where real-time monitoring of region-specific brain activity is needed.

[Functional MRI imaging in the detection of eloquent areas of the brain]

Functional magnetic resonance imaging--fMRI is a relative new magnetic resonance technique that may be used for identification of eloquent cortical areas. Gold standard for detection of eloquent areas that should be preserved subsequent to resection is a direct cortical stimulation, which is invasive and frequently difficult to be performed. On the other hand, fMRI has proved to be a promising alternative with good time and spatial resolution. The paper explains the method of the functional MR imagining, origins of the signal and its relation to the neuronal activation. fMRI technique is illustrated by the example of the motor cortex identification. Functional Magnetic Resonance Imaging--fMRI is a relatively new MR application that can be used for detection of eloquent areas of the brain. The gold standard for identifying eloquent areas of the brain to be avoided in resections is direct cortical stimulation, which is an invasive and difficult procedure. On the other hand fMRI shows great promise as noninvasive alternative to invasive brain mapping with good temporal and spatial resolution. This paper introduces the technique of fMRI, explain the origin of the signal and his connections with neural activations. An illustrative example of a motor activation study is described.

Probing overtly spoken language at sentential level: a comprehensive high-field BOLD-fMRI protocol reflecting everyday language demands

Regarding the application of functional magnetic resonance imaging (fMRI) to preoperative mapping of language, the majority of previous studies applied silent vocalization at word level. Since mapping of language targets the protection of overt communication, the selection of the stimulation paradigm is a crucial issue. Typically, everyday language demands overt speech with construction of syntactically and semantically complete sentences. Here, 23 healthy right-handed subjects performed overt vocalization of complete german sentences. Subjects produced these sentences based on visually presented semantic choices. Special efforts were undertaken to minimize motion artifacts and maximize signal gain on a 3-T MR unit. Compared to previous studies, results showed a larger amount of highly reliable fMRI activations over the whole brain. Particularly, high sensitivity was found for Broca's and Wernicke's regions, as well as anterior and inferior temporal areas. Regarding the left hemisphere, simultaneous "Broca" and "Wernicke" activities were found in 95% of all subjects. When including atypical lateralizations, "Broca" and "Wernicke" activations were found in every subject. Overt vocalization at sentential level represents a new comprehensive language task with the potential to generate reliable activation maps that reflect brain activity associated with everyday language demands.

Integrated image- and function-guided surgery in eloquent cortex: a technique report

The ability to effectively identify eloquent cortex in close proximity to brain tumours is a critical component of surgical planning prior to resection. The use of electrocortical stimulation testing (ECS) during awake neurosurgical procedures remains the gold standard for mapping functional areas, yet the preoperative use of non-invasive brain imaging techniques such as fMRI are gaining popularity as supplemental surgical planning tools. In addition, the intraoperative three-dimensional display of fMRI findings co-registered to structural imaging data maximizes the utility of the preoperative mapping for the surgeon. Advances in these techniques have the potential to limit the size and duration of craniotomies as well as the strain placed on the patient, but more research accurately demonstrating their efficacy is required. In this paper, we demonstrate the integration of preoperative fMRI within a neuronavigation system to aid in surgical planning, as well as the integration of these fMRI data with intraoperative ECS mapping results into a three-dimensional dataset for the purpose of cross-validation.

Functional brain mapping and its applications to neurosurgery

Functional brain mapping may be useful for both preoperative planning and intraoperative neurosurgical decision making. "Gold standard" functional studies such as direct electrical stimulation and recording are complemented by newer, less invasive techniques such as functional magnetic resonance imaging. Less invasive techniques allow more areas of the brain to be mapped in more subjects (including healthy subjects) more often (including pre- and postoperatively). Expansion of the armamentarium of tools allows convergent evidence from multiple brain mapping techniques to bear on pre- and intraoperative decision making. Functional imaging techniques are used to map motor, sensory, language, and memory areas in neurosurgical patients with conditions as diverse as brain tumors, vascular lesions, and epilepsy. In the future, coregistration of high resolution anatomic and physiological data from multiple complementary sources will be used to plan more neurosurgical procedures, including minimally invasive procedures. Along the way, new insights on fundamental processes such as the biology of tumors and brain plasticity are likely to be revealed.

Rater-dependent accuracy in predicting the spatial location of functional centers on anatomical MR images

OBJECTIVES

The determination of eloquent cortex is essential when planning neurosurgical approaches to brain lesions. This study examined the abilities of medical personnel of various backgrounds to predict the location of functional cortex using anatomical information provided by MR imaging.

PATIENTS AND METHODS

Neurosurgeons, neuroscientists, neuroradiologists, medical students and MR technologists viewed anatomical MR images acquired from patients with brain tumors and healthy controls. These five groups of raters were then asked to locate the primary motor hand, supplementary motor and primary auditory areas and their predictions were compared to fMRI data acquired from the same subjects.

RESULTS

The overall mean distance from the center of the fMRI activation was 2.38 cm. The neuroscientists performed the best and MR technologists performed the worst (mean distance from center of 1.83 and 3.04 cm, respectively, p<0.05). The difference between patients and controls was not significant. The mean distance by ROI was primary motor hand 2.03 cm, auditory area 2.06 cm and supplementary motor area 3.18 cm (p<0.05). Raters also performed best in the medial-lateral direction, compared to superior-inferior and anterior-posterior directions (mean distances from center 0.42, 1.04 and 1.81 cm, respectively). Finally, the approximate minimum fields of view necessary to capture the entire fMRI activations using the raters' predictions ranged from 5 to 15 cm, or 3 to 12 cm larger than the fMRI activations.

CONCLUSION

Medical personnel of various training perform poorly when using only anatomical information to predict the location of functional areas of cortex.

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

Functional magnetic resonance imaging (fMRI) performed by echo-planar imaging (EPI) is often highly distorted, and it is therefore necessary to coregister the functional to undistorted anatomical images, especially for clinical applications. This pilot study provides an evaluation of human and automatic coregistration results in the human motor cortex of normal and pathological brains. Ten healthy right-handed subjects and ten right-handed patients performed simple right hand movements during fMRI. A reference point chosen at a characteristic anatomical location within the fMRI sensorimotor activations was transferred to the high resolution anatomical MRI images by three human fMRI experts and by three automatic coregistration programs. The 3D distance between the median localizations of experts and programs was calculated and compared between patients and healthy subjects. Results show that fMRI localization on anatomical images was better with the experts than software in 70% of the cases and that software performance was worse for patients than healthy subjects (unpaired t-test: P = 0.040). With 45.6 mm the maximum disagreement between experts and software was quite large. The inter-rater consistency was better for the fMRI experts compared to the coregistration programs (ANOVA: P = 0.003). We conclude that results of automatic coregistration should be evaluated carefully, especially in case of clinical application.

Sensorimotor Cortex Localization: Comparison of Magnetoencephalography, Functional MR Imaging, and Intraoperative Cortical Mapping

PURPOSE

To prospectively evaluate magnetoencephalography (MEG) and functional magnetic resonance (MR) imaging, as compared with intraoperative cortical mapping, for identification of the central sulcus.

MATERIALS AND METHODS

Fifteen patients (six men, nine women; age range, 25-58 years) with a lesion near the primary sensorimotor cortex (13 gliomas, one cavernous hemangioma, and one meningioma) were examined after institutional review board approval and written informed consent from each patient were obtained. At MEG, evoked magnetic fields to median nerve stimulation were recorded; at functional MR imaging, hemodynamic responses to self-paced palmar flexion of the wrist were imaged. General linear model analysis with contextual clustering (P < .01) was used to analyze functional MR imaging data, and dipole modeling was used to analyze MEG data. MEG and functional MR localizations were compared with intraoperative cortical mappings. The distance from the area of functional MR imaging activation to the tumor margin was compared between the patients with discordant and those with concordant intraoperative mapping findings by using unpaired t testing.

RESULTS

MEG depicted the central sulcus correctly in all 15 patients, as verified at intraoperative mapping. The functional MR imaging localization results agreed with the intraoperative mappings in 11 patients. In all four patients with a false localization, the primary activation was in the postcentral sulcus region, but it did not differ significantly from the primary activation in the patients with correct localization with respect to proximity to the tumor (P = .38). Furthermore, at functional MR imaging, multiple nonprimary areas were activated, with considerable interindividual variation.

CONCLUSION

Although both MEG and functional MR imaging can provide useful information for neurosurgical planning, in the present study, MEG proved to be superior for locating the central sulcus. Activation of multiple nonprimary cerebral areas may confound the interpretation of functional MR imaging results.

Magnetoencephalography in Neurosurgery

OBJECTIVE:

To present applications of magnetoencephalography (MEG) in studies of neurosurgical patients.

METHODS:

MEG maps magnetic fields generated by electric currents in the brain, and allows the localization of brain areas producing evoked sensory responses and spontaneous electromagnetic activity. The identified sources can be integrated with other imaging modalities, e.g., with magnetic resonance imaging scans of individual patients with brain tumors or intractable epilepsy, or with other types of brain imaging data.

RESULTS:

MEG measurements using modern whole-scalp instruments assist in tailoring individual therapies for neurosurgical patients by producing maps of functionally irretrievable cortical areas and by identifying cortical sources of interictal and ictal epileptiform activity. The excellent time resolution of MEG enables tracking of complex spaciotemporal source patterns, helping, for example, with the separation of the epileptic pacemaker from propagated activity. The combination of noninvasive mapping of subcortical pathways by magnetic resonance imaging diffusion tensor imaging with MEG source localization will, in the near future, provide even more accurate navigational tools for preoperative planning. Other possible future applications of MEG include the noninvasive estimation of language lateralization and the follow-up of brain plasticity elicited by central or peripheral neural lesions or during the treatment of chronic pain.

CONCLUSION:

MEG is a mature technique suitable for producing preoperative “road maps” of eloquent cortical areas and for localizing epileptiform activity.

Intraoperative visualization of the pyramidal tract by diffusion-tensor-imaging-based fiber tracking

Functional neuronavigation allows intraoperative visualization of cortical eloquent brain areas. Major white matter tracts, such as the pyramidal tract, can be delineated by diffusion-tensor-imaging based fiber tracking. These tractography data were integrated into 3-D datasets applied for neuronavigation by rigid registration of the diffusion images with standard anatomical image data so that their course could be superimposed onto the surgical field during resection of gliomas. Intraoperative high-field magnetic resonance imaging was used to compensate for the effects of brain shift, which amounted up to 8 mm. Despite image distortion of echo planar images, which was identified by non-linear registration techniques, navigation was reliable. In none of the 19 patients new postoperative neurological deficits were encountered. Intraoperative visualization of major white matter tracts allows save resection of gliomas near eloquent brain areas. A possible shifting of the pyramidal tract has to be taken into account after major tumor parts are resected.

Comparison of functional MR imaging guidance to electrical cortical mapping for targeting selective motor cortex areas in neuropathic pain: a study based on intraoperative stereotactic navigation

PURPOSE

To assess the concordance between data from functional MR imaging (fMRI) guidance and the intraoperative electrical cortical mapping (iCM) in targeting selective motor cortex areas in refractory neuropathic pain.

METHODS

Twenty-one patients (11 women and 10 men; mean age, 55.6 years) with refractory central (ischemic, 8 cases) and neuropathic pain (trigeminal neuropathy, 6 cases; syrinx/amputation/plexus trauma, 7 cases) underwent surgery for the implantation of an epidural electrode for chronic motor cortex stimulation (MCS) with general anesthesia and a frameless neuronavigation system used for the image-guided targeting procedure. All patients were studied by preoperative fMRI and epidural iCM with somatosensory evoked potentials and motor cortex stimulodetection. fMRI investigated systematically motor tasks of both hands and that related to the somatic area (foot or tongue) affected by pain. fMRI data were analyzed with the Statistical Parametric Mapping99 software (initial analysis threshold [AT] corresponding to P < .001), registered in the neuronavigation system and correlated intraoperatively with iCM. Matching of fMRI and iCM was specifically examined, focusing the study on hand mapping.

RESULTS

Concordance between contours of fMRI activation area and iCM in precentral gyrus (mean distance, 3.8 mm) was found in 20/21 patients (95%). Because precision of iCM was suboptimal in 7 patients, concordance for more restrictive values of the AT (P < .0001) was found in only 13 of these 20 patients. Concordance was not found in one patient, as result of image distortion and residual motion artifact.

CONCLUSIONS

In this study, fMRI guidance provides information that matches those of an independent functional method. These data illustrate the functional accuracy of fMRI guidance for the operative targeting of selective motor cortex areas in neuropathic pain.

Intraoperative functional MRI: Implementation and preliminary experience

For a non-invasive identification of eloquent brain areas in neurosurgical procedures up to now only preoperative functional brain mapping techniques are available. These are based, e.g., on preoperative functional magnetic resonance imaging (fMRI) investigations in awake patients. The aim of this study was to investigate the feasibility to perform fMRI during neurosurgical procedures in anesthetized patients. For that purpose, a passive stimulation paradigm with peripheral nerve stimulation was applied. A 1.5-T MR scanner placed in a radiofrequency-shielded operating room with an adapted operating table was used for intraoperative fMRI. The fMRI data were analyzed during acquisition by an online statistical evaluation package installed on the MR scanner console. In addition, phase reversal of somatosensory evoked potentials was used for verification of intraoperative fMRI. In four anesthetized patients with lesions in the vicinity of the central region a total of 11 fMRI measurements were successfully acquired and analyzed online. Activation was found in the somatosensory cortex, which could be confirmed by intraoperative phase reversal for each measurement. Furthermore, statistical parametric mapping (SPM) was employed for an extensive offline data analysis. We did not observe any neurological deterioration or complications due to the stimulation technique. Intraoperative fMRI is technically feasible allowing a real-time identification of eloquent brain areas despite brain shift.

Combination of Functional Magnetic Resonance Imaging-guided Neuronavigation and Intraoperative Cortical Brain Mapping Improves Targeting of Motor Cortex Stimulation in Neuropathic Pain

OBJECTIVE:

To evaluate, regardless of the clinical results, the contribution of combining functional magnetic resonance imaging (fMRI) with intraoperative cortical brain mapping (iCM) as functional targeting methods for epidural chronic motor cortex stimulation (MCS) in refractory neuropathic pain.

METHODS:

Eighteen neuropathic pain patients (central stroke in six; trigeminal neuropathy in six; syrinx or amputation in six) who underwent operations for epidural MCS were studied with preoperative fMRI and iCM. fMRI investigated motor tasks of hands (as well as foot and tongue, when painful). fMRI data were analyzed with Statistical Parametric Mapping99 software (University College London, London, England; initial analysis threshold corresponding to P &lt; 0.001), registered in a neuronavigation system, and correlated during surgery with iCM. The primary aim of this study was to improve the topographical precision of MCS. Matching of fMRI and iCM specifically was examined.

RESULTS:

Correspondence between the contour of the fMRI activation area and iCM in precentral gyrus (mean distance, 3.8 mm) was found in 17 (94%) of 18 patients. Eleven of them showed correspondence for more restrictive values of the analysis threshold (P &lt; 0.0001); in six patients, the quality of the iCM was reduced by somatosensory wave attenuation and general anesthesia. In this group of six patients, a combination of both techniques was used for the final targeting. Correspondence was not found in one patient as the result of image distortion and residual motion artifact. At follow-up (4–60 mo), MCS induced significant pain relief in a total of 11 patients (61%).

CONCLUSION:

This study confirms the functional accuracy of fMRI guidance in neuropathic pain and illustrates the usefulness of combining fMRI guidance with iCM to improve the functional targeting in MCS. Because appropriate targeting is crucial to obtaining pain relief, this combination may increase the analgesic efficacy of MCS.

Physiological basis and image processing in functional magnetic resonance imaging: neuronal and motor activity in brain

Functional magnetic resonance imaging (fMRI) is recently developing as imaging modality used for mapping hemodynamics of neuronal and motor event related tissue blood oxygen level dependence (BOLD) in terms of brain activation. Image processing is performed by segmentation and registration methods. Segmentation algorithms provide brain surface-based analysis, automated anatomical labeling of cortical fields in magnetic resonance data sets based on oxygen metabolic state. Registration algorithms provide geometric features using two or more imaging modalities to assure clinically useful neuronal and motor information of brain activation. This review article summarizes the physiological basis of fMRI signal, its origin, contrast enhancement, physical factors, anatomical labeling by segmentation, registration approaches with examples of visual and motor activity in brain. Latest developments are reviewed for clinical applications of fMRI along with other different neurophysiological and imaging modalities.