Improvement of presurgical patient evaluation by generation of functional magnetic resonance risk maps

Key clinical benefits of neuroimaging at 7T

The growing interest in ultra-high field MRI, with more than 35.000 MR examinations already performed at 7T, is related to improved clinical results with regard to morphological as well as functional and metabolic capabilities. Since the signal-to-noise ratio increases with the field strength of the MR scanner, the most evident application at 7T is to gain higher spatial resolution in the brain compared to 3T. Of specific clinical interest for neuro applications is the cerebral cortex at 7T, for the detection of changes in cortical structure, like the visualization of cortical microinfarcts and cortical plaques in Multiple Sclerosis. In imaging of the hippocampus, even subfields of the internal hippocampal anatomy and pathology may be visualized with excellent spatial resolution. Using Susceptibility Weighted Imaging, the plaque-vessel relationship and iron accumulations in Multiple Sclerosis can be visualized, which may provide a prognostic factor of disease. Vascular imaging is a highly promising field for 7T which is dealt with in a separate dedicated article in this special issue. The static and dynamic blood oxygenation level-dependent contrast also increases with the field strength, which significantly improves the accuracy of pre-surgical evaluation of vital brain areas before tumor removal. Improvement in acquisition and hardware technology have also resulted in an increasing number of MR spectroscopic imaging studies in patients at 7T. More recent parallel imaging and short-TR acquisition approaches have overcome the limitations of scan time and spatial resolution, thereby allowing imaging matrix sizes of up to 128×128. The benefits of these acquisition approaches for investigation of brain tumors and Multiple Sclerosis have been shown recently. Together, these possibilities demonstrate the feasibility and advantages of conducting routine diagnostic imaging and clinical research at 7T.

Robust presurgical functional MRI at 7 T using response consistency

Functional MRI is valuable in presurgical planning due to its non-invasive nature, repeatability, and broad availability. Using ultra-high field MRI increases the specificity and sensitivity, increasing the localization reliability and reducing scan time. Ideally, fMRI analysis for this application should identify unreliable runs and work even if the patient deviates from the prescribed task timing or if there are changes to the hemodynamic response due to pathology. In this study, a model-free analysis method-UNBIASED-based on the consistency of fMRI responses over runs was applied, to ultra-high field fMRI localizations of the hand area. Ten patients with brain tumors and epilepsy underwent 7 Tesla fMRI with multiple runs of a hand motor task in a block design. FMRI data were analyzed with the proposed approach (UNBIASED) and the conventional General Linear Model (GLM) approach. UNBIASED correctly identified and excluded fMRI runs that contained little or no activation. Generally, less motion artifact contamination was present in UNBIASED than in GLM results. Some cortical regions were identified as activated in UNBIASED but not GLM results. These were confirmed to show reproducible delayed or transient activation, which was time-locked to the task. UNBIASED is a robust approach to generating activation maps without the need for assumptions about response timing or shape. In presurgical planning, UNBIASED can complement model-based methods to aid surgeons in making prudent choices about optimal surgical access and resection margins for each patient, even if the hemodynamic response is modified by pathology. Hum Brain Mapp 38:3163-3174, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

The clinical relevance of distortion correction in presurgical fMRI at 7T

Presurgical planning with fMRI benefits from increased reliability and the possibility to reduce measurement time introduced by using ultra-high field. Echo-planar imaging suffers, however, from geometric distortions which scale with field strength and potentially give rise to clinically significant displacement of functional activation. We evaluate the effectiveness of a dynamic distortion correction (DDC) method based on unmodified single-echo EPI in the context of simulated presurgical planning fMRI at 7T and compare it with static distortion correction (SDC). The extent of distortion in EPI and activation shifts are investigated in a group of eleven patients with a range of neuropathologies who performed a motor task. The consequences of neglecting to correct images for susceptibility-induced distortions are assessed in a clinical context. It was possible to generate time series of EPI-based field maps which were free of artifacts in the eloquent brain areas relevant to presurgical fMRI, despite the presence of signal dropouts caused by pathologies and post-operative sites. Distortions of up to 5.1mm were observed in the primary motor cortex in raw EPI. These were accurately corrected with DDC and slightly less accurately with SDC. The dynamic nature of distortions in UHF clinical fMRI was demonstrated via investigation of temporal variation in voxel shift maps, confirming the potential inadequacy of SDC based on a single reference field map, particularly in the vicinity of pathologies or in the presence of motion. In two patients, the distortion correction was potentially clinically significant in that it might have affected the localization or interpretation of activation and could thereby have influenced the treatment plan. Distortion correction is shown to be effective and clinically relevant in presurgical planning at 7T.

Improving the clinical potential of ultra-high field fMRI using a model-free analysis method based on response consistency

Objective

To develop an analysis method that is sensitive to non-model-conform responses often encountered in ultra-high field presurgical planning fMRI. Using the consistency of time courses over a number of experiment repetitions, it should exclude low quality runs and generate activation maps that reflect the reliability of responses.

Materials and methods

7 T fMRI data were acquired from six healthy volunteers: three performing purely motor tasks and three a visuomotor task. These were analysed with the proposed approach (UNBIASED) and the GLM.

Results

UNBIASED results were generally less affected by false positive results than the GLM. Runs that were identified as being of low quality were confirmed to contain little or no activation. In two cases, regions were identified as activated in UNBIASED but not GLM results. Signal changes in these areas were time-locked to the task, but were delayed or transient.

Conclusion

UNBIASED is shown to be a reliable means of identifying consistent task-related signal changes regardless of response timing. In presurgical planning, UNBIASED could be used to rapidly generate reliable maps of the consistency with which eloquent brain regions are activated without recourse to task timing and despite modified hemodynamics.

Electronic supplementary material

The online version of this article (doi:10.1007/s10334-016-0533-8) contains supplementary material, which is available to authorized users.

Improving fMRI reliability in presurgical mapping for brain tumours

PURPOSE

Functional MRI (fMRI) is becoming increasingly integrated into clinical practice for presurgical mapping. Current efforts are focused on validating data quality, with reliability being a major factor. In this paper, we demonstrate the utility of a recently developed approach that uses receiver operating characteristic-reliability (ROC-r) to: (1) identify reliable versus unreliable data sets; (2) automatically select processing options to enhance data quality; and (3) automatically select individualised thresholds for activation maps.

METHODS

Presurgical fMRI was conducted in 16 patients undergoing surgical treatment for brain tumours. Within-session test-retest fMRI was conducted, and ROC-reliability of the patient group was compared to a previous healthy control cohort. Individually optimised preprocessing pipelines were determined to improve reliability. Spatial correspondence was assessed by comparing the fMRI results to intraoperative cortical stimulation mapping, in terms of the distance to the nearest active fMRI voxel.

RESULTS

The average ROC-r reliability for the patients was 0.58±0.03, as compared to 0.72±0.02 in healthy controls. For the patient group, this increased significantly to 0.65±0.02 by adopting optimised preprocessing pipelines. Co-localisation of the fMRI maps with cortical stimulation was significantly better for more reliable versus less reliable data sets (8.3±0.9 vs 29±3 mm, respectively).

CONCLUSIONS

We demonstrated ROC-r analysis for identifying reliable fMRI data sets, choosing optimal postprocessing pipelines, and selecting patient-specific thresholds. Data sets with higher reliability also showed closer spatial correspondence to cortical stimulation. ROC-r can thus identify poor fMRI data at time of scanning, allowing for repeat scans when necessary. ROC-r analysis provides optimised and automated fMRI processing for improved presurgical mapping.

Strategies to maximize resection of complex, or high surgical risk, low-grade gliomas

OBJECT

Early and aggressive resection of low-grade gliomas (LGGs) leads to increased overall patient survival, decreased malignant progression, and better seizure control. This case series describes the authors' approach to achieving optimal neurological and surgical outcomes in patients referred by outside neurosurgeons for stereotactic biopsy of tumors believed to be complex or a high surgical risk, due to their diffuse nature on neuroimaging and their obvious infiltration of functional cortex.

METHODS

Seven patients underwent individualized neuroimaging evaluation preoperatively, which included routine brain MRI with and without contrast administration for intraoperative neuronavigation, functional MRI with speech and motor mapping, diffusion tensor imaging to delineate white matter tracts, and MR perfusion to identify potential foci of higher grade malignancy within the tumor. Awake craniotomy with intraoperative motor and speech mapping was performed in all patients. Tumor removal was initiated through a transsylvian approach for insular lesions, and through multiple corticotomies in stimulation-confirmed noneloquent areas for all other lesions. Resection was continued until neuronavigation indicated normal brain, cortical or subcortical stimulation revealed functional cortex, or the patient began to experience a minor neurological deficit on intraoperative testing.

RESULTS

Gross-total resection was achieved in 1 patient and subtotal resection (> 80%) in 6 patients, as assessed by postoperative MRI. Over the average follow-up duration of 31 months, no patient experienced a progression or recurrence. Long-term seizure control was excellent in 6 patients who achieved Engel Class I outcomes. Neurologically, all 7 patients experienced mild temporary deficits or seizures that completely resolved, and 1 patient continues to have mild expressive aphasia.

CONCLUSIONS

Significant resection of diffuse, infiltrating LGGs is possible, even in presumed eloquent cortex. Aggressive resection maximizes seizure control and does not necessarily cause permanent neurological deficits. Individualized preoperative neuroimaging evaluation, including tractography and awake craniotomy with intraoperative speech and motor mapping, is an essential tool in achieving these outcomes.

Differential functional benefits of ultra highfield MR systems within the language network

Several investigations have shown limitations of fMRI reliability with the current standard field strengths. Improvement is expected from ultra highfield systems but studies on possible benefits for cognitive networks are lacking. Here we provide an initial investigation on a prominent and clinically highly-relevant cognitive function: language processing in individual brains. 26 patients evaluated for presurgical language localization were investigated with a standardized overt language fMRI paradigm on both 3T and 7T MR scanners. During data acquisition and analysis we made particular efforts to minimize effects not related to static magnetic field strength differences. Six measures relevant for functional activation showed a large dissociation between essential language network nodes: although in Wernicke's area 5/6 measures indicated a benefit of ultra highfield, in Broca's area no comparison was significant. The most important reason for this discrepancy was identified as being an increase in susceptibility-related artifacts in inferior frontal brain areas at ultra high field. We conclude that functional UHF benefits are evident, however these depend crucially on the brain region investigated and the ability to control local artifacts.

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.

Applying independent component analysis to clinical FMRI at 7 t

Increased BOLD sensitivity at 7 T offers the possibility to increase the reliability of fMRI, but ultra-high field is also associated with an increase in artifacts related to head motion, Nyquist ghosting, and parallel imaging reconstruction errors. In this study, the ability of independent component analysis (ICA) to separate activation from these artifacts was assessed in a 7 T study of neurological patients performing chin and hand motor tasks. ICA was able to isolate primary motor activation with negligible contamination by motion effects. The results of General Linear Model (GLM) analysis of these data were, in contrast, heavily contaminated by motion. Secondary motor areas, basal ganglia, and thalamus involvement were apparent in ICA results, but there was low capability to isolate activation in the same brain regions in the GLM analysis, indicating that ICA was more sensitive as well as more specific. A method was developed to simplify the assessment of the large number of independent components. Task-related activation components could be automatically identified via these intuitive and effective features. These findings demonstrate that ICA is a practical and sensitive analysis approach in high field fMRI studies, particularly where motion is evoked. Promising applications of ICA in clinical fMRI include presurgical planning and the study of pathologies affecting subcortical brain areas.

Task and task-free FMRI reproducibility comparison for motor network identification

Test-retest reliability of individual functional magnetic resonance imaging (fMRI) results is of importance in clinical practice and longitudinal experiments. While several studies have investigated reliability of task-induced motor network activation, less is known about the reliability of the task-free motor network. Here, we investigate the reproducibility of task-free fMRI, and compare it to motor task activity. Sixteen healthy subjects participated in this study with a test-retest interval of seven weeks. The task-free motor network was assessed with a univariate, seed-voxel-based correlation analysis. Reproducibility was tested by means of intraclass correlation (ICC) values and ratio of overlap. Higher ICC values and a better overlap were found for task fMRI as compared to task-free fMRI. Furthermore, ratio of overlap improved for task fMRI at higher thresholds, while it decreased for task-free fMRI, suggesting a less focal spatial pattern of the motor network during resting state. However, for both techniques the most active voxels were located in the primary motor cortex. This indicates that, just like task fMRI, task-free fMRI can properly identify critical brain areas for motor task performance. Although both fMRI techniques are able to detect the motor network, resting-state fMRI is less reliable than task fMRI.

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.

Improvement of clinical language localization with an overt semantic and syntactic language functional MR imaging paradigm

BACKGROUND AND PURPOSE

Functional MR imaging (fMRI) is a promising but, in some aspects, still debated noninvasive tool for functional language mapping. We developed a clinical fMRI overt language design at the sentential level to optimize sensitivity for language-related areas of the brain. To evaluate applicability and sensitivity, we investigated a consecutive series of presurgical patients with epilepsy with minimal morphologic brain abnormalities.

MATERIALS AND METHODS

Thirty right-handed patients with temporal lobe epilepsy (TLE) and a control group of 23 right-handed healthy subjects participated in the study. The language design included semantic and syntactic error-detection tasks and was constructed to represent the most relevant aspects of everyday language demands. It was applied during block-designed fMRI runs. We performed image preprocessing and statistical analysis with SPM5 at a group level, applying widely used statistical criteria. The study was approved by the local ethics committee, and all participants gave written informed consent.

RESULTS

Given the strict statistical criteria, the sensitivity for inferior frontal and posterior temporal activations (comprising Broca and Wernicke regions) was improved relative to previous findings in the literature. For both language areas, we found 100% sensitivity in healthy subjects (Brodmann areas, BA22 and BA44) and 97% sensitivity in patients (when including BA47). Lateralization results demonstrated the capability to detect atypical language lateralizations in patients, which were more frequent in than those in healthy subjects.

CONCLUSIONS

We developed a clinical language fMRI design that integrates various relevant aspects of everyday language demands and provides robust localization of core language areas.

fMRI activation mapping as a percentage of local excitation: consistent presurgical motor maps without threshold adjustment

PURPOSE

To evaluate the performance of a relative activation amplitude algorithm, versus standard t-value thresholding, for reliably establishing the location, amplitude, and spatial extent of functional magnetic resonance imaging (fMRI) brain activation for presurgical planning.

MATERIALS AND METHODS

Diagnostic fMRI maps from 42 neurosurgical patients performing a simple hand movement task were analyzed. Relative activation maps were made by normalizing statistical t-value maps to the local peak activation amplitude within each functional brain region. The spatial distribution of activation was quantified and compared across mapping algorithms, subjects, and scan duration.

RESULTS

Whereas the spatial distribution of blood oxygenation level-dependent (BOLD) t-value statistical activation maps was highly variable across subjects and scan duration, the spatial distribution of relative activation maps was highly reproducible both within individual subjects and across different subjects. In every case the 40% most active voxels in the cortical hand region were consistently localized to the pre- and postcentral gyri of the sensorimotor cortex.

CONCLUSION

The reproducibility and anatomical specificity of the spatiotemporal pattern of BOLD activation makes relative amplitude fMRI mapping a useful tool for clinical imaging, where accuracy, reproducibility, and quality control are critical concerns.

Magnetic resonance imaging methodology

INTRODUCTION

Magnetic resonance (MR) methods are non-invasive techniques to provide detailed, multi-parametric information on human anatomy, function and metabolism. Sensitivity, specificity, spatial and temporal resolution may, however, vary depending on hardware (e.g., field strength, gradient strength and speed) and software (optimised measurement protocols and parameters for the various techniques). Furthermore, multi-modality imaging may enhance specificity to better characterise complex disease patterns.

OBJECTIVE

Positron emission tomography (PET) is an interesting, largely complementary modality, which might be combined with MR. Despite obvious advantages, combining these rather different physical methods may also pose challenging problems. At this early stage, it seems that PET quality may be preserved in the magnetic field and, if an adequate detector material is used for the PET, MR sensitivity should not be significantly degraded. Again, this may vary for the different MR techniques, whereby functional and metabolic MR is more susceptible than standard anatomical imaging.

DISCUSSION

Here we provide a short introduction to MR basics and MR techniques, also discussing advantages, artefacts and problems when MR hardware and PET detectors are combined. In addition to references for more detailed descriptions of MR fundamentals and applications, we provide an early outlook on this novel and exciting multi-modality approach to PET/MR.

Surface-based functional magnetic resonance imaging analysis of partial brain echo planar imaging data at 1.5 T

Surface-based functional magnetic resonance imaging (fMRI) analysis is more sensitive and accurate than volume-based analysis for detecting neural activation. However, these advantages are less important in practical fMRI experiments with commonly used 1.5-T magnetic resonance devices because of the resolution gap between the echo planar imaging data and the cortical surface models. We expected high-resolution segmented partial brain echo planar imaging (EPI) data to overcome this problem, and the activation patterns of the high-resolution data could be different from the low-resolution data. For the practical applications of surface-based fMRI analysis using segmented EPI techniques, the effects of some important factors (e.g., activation patterns, registration and local distortions) should be intensively evaluated because the results of surface-based fMRI analyses could be influenced by them. In this study, we demonstrated the difference between activations detected from low-resolution EPI data, which were covering whole brain, and high-resolution segmented EPI data covering partial brain by volume- and surface-based analysis methods. First, we compared the activation maps of low- and high-resolution EPI datasets detected by volume- and surface-based analyses, with the spatial patterns of activation clusters, and analyzed the distributions of activations in occipital lobes. We also analyzed the high-resolution EPI data covering motor areas and fusiform gyri of human brain, and presented the differences of activations detected by volume- and surface-based methods.

Detection and scaling of task-induced fMRI-BOLD response using resting state fluctuations

This study evaluated a calibration technique for scaling the fMRI-BOLD response during a simple motor task. A novel scaling parameter, resting state physiological fluctuation amplitude (RSFA), was tested using previously established scaling factors such as breath hold or 5% CO(2). RSFA was hypothesized to contain vascular reactivity information present in the resting state fMRI signal. Subjects were scanned under various stimulus conditions: (a) rest while breathing room air, (b) bilateral fingertapping, (c) breath holding and (d) moderate hypercapnia (breathing 5% CO(2)+air). In all subjects who breathed 5% CO(2), RSFA correlated highly with the BOLD response amplitude during 5% CO(2) inhalation. Also, RSFA correlated highly with the amplitude of the BOLD response elicited by breath hold. RSFA was therefore used as a hemodynamic scaling factor to calibrate both the amplitude and spatial extent of the fMRI-BOLD response during the motor task (fingertapping). Results revealed that amplitude scaling using RSFA was similar to that using breath hold or 5% CO(2), where the spatial extent of activation diminished by 20-37% over all subjects. Spatial extent of activation changed significantly after scaling and only 30-40% of the activated area overlapped with the unscaled activation. RSFA-scaled task-induced fMRI-BOLD response in both amplitude and spatial extent was comparable to that obtained using breath hold or 5% CO(2). We conclude that RSFA may be used to hemodynamically scale the fMRI-BOLD response and does not require the use of a hypercapnic challenge (which may not be purely non-neural), which can be difficult to implement in special populations.

Artificial shifting of fMRI activation localized by volume- and surface-based analyses

Spatial smoothing is an important post-processing procedure that is used to increase the signal-to-noise ratio (SNR) of blood oxygenation level-dependent signals (BOLD) in common functional magnetic resonance imaging (fMRI) applications. However, recent studies have shown that smoothing artificially shifts probabilistic local maxima of fMRI activations. In this study, we show shifting of the localization of functional centers in hand motor areas of the cerebral cortex by three-dimensional isotropic Gaussian kernel smoothing or two-dimensional heat kernel smoothing in volume- and surface-based fMRI analyses. Activation maps derived from smoothed echo planar imaging (EPI) data by volume- and surface-based analyses were assigned to the nodes of individual cortical surface models, and local maxima in the primary motor area (M1) and the primary somatosensory cortex (S1) were compared with those derived from non-smoothed risk map analysis, which is commonly used in presurgical applications. For each analysis, the Euclidean and geodesic distances between the correlation coefficients of local maxima derived from smoothed and non-smoothed EPI data were measured. The results show that the correlation coefficients derived from the volume- and surface-based analyses were about 29.4% and 42.9% higher for smoothed than for non-smoothed risk map analyses, and show minimum shifting of localizations by 12.1 mm and 6.9 mm on average in Euclidean distance, respectively, and about 9.5 mm and 5.7 mm on average in geodesic distance, respectively.

Hemodynamic scaling of fMRI-BOLD signal: validation of low-frequency spectral amplitude as a scalability factor

Functional magnetic resonance imaging blood-oxygenation-level-dependent (fMRI-BOLD) signal representing neural activity may be optimized by discriminating MR signal components related to neural activity and those related to intrinsic properties of the cortical vasculature. The objective of this study was to reduce the hemodynamic change independent of neural activity to obtain a scaled fMRI-BOLD response using two factors, namely, low-frequency spectral amplitude (LFSA) and breath-hold amplitude (BHA). Ten subjects (age range, 22-38 years) were scanned during four task conditions: (a) rest while breathing room air, (b) bilateral finger tapping while breathing room air, (c) rest during a partial inspirational breath-hold, and (d) rest during moderate hypercapnia (breathing 5% CO2, 20% O2 and 75% N2). In all subjects who breathed 5% CO2, regions with significant BOLD response during breath-hold correlated significantly with the percent signal increase during 5% CO2 inhalation. Finger-tapping-induced responses in the motor cortex were diminished to a similar extent after scaling using either LFSA or BHA. Inter- and intrasubject variation in the amplitude of the BOLD signal response reduced after hemodynamic scaling using LFSA or BHA. The results validated the hemodynamic amplitude scaling using LFSA with the earlier established BHA. LFSA free from motor-task contamination can be used to calibrate the fMRI-BOLD response in lieu of BHA or hypercapnia to minimize intra- and intersubject variation arising from vascular anatomy and vasodilative capacity.

Contrast-to-noise ratio (CNR) as a quality parameter in fMRI

PURPOSE

To evaluate the impact of data quality on the localization of brain activation in functional magnetic resonance imaging (fMRI) and to explore whether the temporal contrast-to-noise-ratio (CNR) provides a quantitative parameter to estimate fMRI quality.

MATERIALS AND METHODS

We investigated two methods for defining the CNR by comparing them on a single-run, single session, as well as on a group-wise basis. The CNRs of healthy subjects and a group of patients with brain lesions were calculated using two different strategies: one based on a general linear model (GLM) analysis (CNR_SPM), and one that acts as an adaptive low-pass filter and assumes that the high-frequency components contain the temporal noise (CNR_SG). Runs with low CNR were identified as outliers using a common exclusion criterion (2 x standard deviation (SD)).

RESULTS

The results of the two CNR methods are highly correlated. Both between and within subjects and patients the CNR showed quite large variations, but the average CNR did not differ between a group of healthy subjects and a patient group. In total, seven of 213 runs (3.3% of all runs) had to be excluded when CNR_SG was used, and 14 of 213 (6.6%) runs had to be excluded when CNR_SPM was used.

CONCLUSION

Calculating the CNR using an adaptive low-pass filter gives similar results to a GLM-based approach and could be advantageous for cases in which the hemodynamic response function (HRF) differs significantly from common assumptions. The CNR can be used to identify and exclude runs with suboptimal CNR, and to identify sessions with insufficient data quality. The CNR may serve as a quantitative and intuitive parameter to assess the performance and quality of clinical fMRI investigations, including information on both functional performance (contrast) and data quality (noise caused by the system and physiology).

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.

Reproducibility of activation in four motor paradigms. An fMRI study

Most functional imaging data are collected in single session experiments; little is known about the reproducibility or test-retest reliability of the activation patterns found in these experiments. In our study, 15 healthy volunteers performed four simple motor-paradigms ("Hand", "Foot", "Mouth" and "Tongue") for functional magnetic resonance imaging (fMRI) in 3 sessions on different days. Reproducibility of activations in four anatomical regions (pre- and postcentral gyri, paracentral lobule and the supplementary motor area) was measured in terms of voxels active in all sessions (common voxels) relative to voxels active in single sessions, giving reliability coefficients from 0 to 1. Two significance levels were used to identify active voxels. Reproducibility of activations was highest for foot and hand movements in the primary motorsensory areas; reliability coefficients were in the range of 0.62 to 0.78. Activations for mouth movements showed a very poor reproducibility. Application of the more stringent statistical threshold always led to a reduction of reproducible voxels. Reliability of fMRI data is not only a theoretical issue, but is of special practical importance in clinical settings such as integration of fMRI into neuronavigation for neurosurgical planning. Much care has to be taken if only single session data are available for interpretation.

Functional magnetic resonance imaging at 3T as a clinical tool in patients with intracranial tumors

PURPOSE

To investigate the potential of functional magnetic resonance imaging (fMRI) at 3T as a clinical tool in the preoperative evaluation of patients with intracranial tumors. High magnetic field strength such as 3T is of benefit for fMRI because signal-to-noise ratio and sensitivity to susceptibility changes are field-strength-dependent.

MATERIAL AND METHODS

Twenty patients with tumors close to eloquent sensorimotor or language areas were studied. Motor, sensory, and two language paradigms (word generation, rhyming) were used; their effectiveness was determined as the percentage of patients in whom the functional area of interest was activated. Activation maps were calculated and their quality rated as high, adequate, or insufficient. The influence of fMRI on the neurosurgical decision regarding operability, surgical approach, and extent of the resection, was assessed.

RESULTS

Paradigm effectiveness was 90% for motor and 95% for sensory stimulation, and varied from 79% to 95% for word generation and rhyming in combination. Ninety percent of the activation maps held high or adequate quality. fMRI proved useful: in the decision to operate (9 patients), in the surgical approach (13 patients), and in extent of the resection (12 patients).

CONCLUSION

fMRI at 3T is a clinically applicable tool in the work-up of patients with intracranial tumors.

Evaluation of preoperative high magnetic field motor functional MRI (3 Tesla) in glioma patients by navigated electrocortical stimulation and postoperative outcome

OBJECTIVES

The validity of 3 Tesla motor functional magnetic resonance imaging (fMRI) in patients with gliomas involving the primary motor cortex was investigated by intraoperative navigated motor cortex stimulation (MCS).

METHODS

Twenty two patients (10 males, 12 females, mean age 39 years, range 10-65 years) underwent preoperative fMRI studies, performing motor tasks including hand, foot, and mouth movements. A recently developed high field clinical fMRI technique was used to generate pre-surgical maps of functional high risk areas defining a motor focus. Motor foci were tested for validity by intraoperative motor cortex stimulation (MCS) employing image fusion and neuronavigation. Clinical outcome was assessed using the Modified Rankin Scale.

RESULTS

FMRI motor foci were successfully detected in all patients preoperatively. In 17 of 22 patients (77.3%), a successful stimulation of the primary motor cortex was possible. All 17 correlated patients showed 100% agreement on MCS and fMRI motor focus within 10 mm. Technical problems during stimulation occurred in three patients (13.6%), no motor response was elicited in two (9.1%), and MCS induced seizures occurred in three (13.6%). Combined fMRI and MCS mapping results allowed large resections in 20 patients (91%) (gross total in nine (41%), subtotal in 11 (50%)) and biopsy in two patients (9%). Pathology revealed seven low grade and 15 high grade gliomas. Mild to moderate transient neurological deterioration occurred in six patients, and a severe hemiparesis in one. All patients recovered within 3 months (31.8% transient, 0% permanent morbidity).

CONCLUSIONS

The validation of clinically optimised high magnetic field motor fMRI confirms high reliability as a preoperative and intraoperative adjunct in glioma patients selected for surgery within or adjacent to the motor cortex.

FMRI reveals functional cortex in a case of inconclusive Wada testing

OBJECTIVES

The intracarotid amobarbital test (Wada test) currently represents the gold standard for preoperative lateralization of hemispheric dominance. Here, we report an epileptic patient with a longstanding extended lesion of the left hemisphere showing absence of motor and speech dysfunction with left carotid amobarbital injection, but tetraplegia and speech arrest with right carotid injection interpreted as a neuroplastic shift of motor and language functions to the right hemisphere. In contrast to the Wada results, motor functional magnetic resonance imaging (fMRI) showed a strong left hemispheric activation with right hand movements.

METHODS

Right and left hand motor fMRI was performed. FMRI results and neurophysiological information obtained by motor and sensory evoked potential measurements were compared with the Wada test results.

RESULTS

Initial interpretation of neuroplastic shifts of intrinsic left hemisphere functions to the right brain was revised after fMRI results which were confirmed by motor and sensory evoked potentials.

CONCLUSION

As motor inactivation usually is thought to be the most robust feature of the Wada test, this case demonstrates that fMRI may reveal residual functional cortex in cases of inconclusive Wada results.

Influence of fMRI smoothing procedures on replicability of fine scale motor localization

Recent publications analyzing the influence of spatial smoothing on fMRI brain activation results demonstrated that smoothing may artificially combine activations from adjacent though functionally and anatomically distinct brain regions and that activation from large draining vessels may be smoothed into neighboring neuronal tissue. To investigate whether functional localizations may be artificially shifted by the smoothing procedure we performed replicability measurements. Localization centers of motor hand activations achieved during different conditions (isolated hand movements and simultaneous hand and chin movements) were compared with respect to smoothing effects. The voxel with the highest probability to represent a true positive activation was localized with a non-smoothed and a standard 4 x 4 x 6 mm smoothed correlational data analysis technique. Results show an increase of motor center aberrations between measurements by about 100% due to data smoothing indicating a statistically significant decrease in localization replicability.

Paradigm design of sensory-motor and language tests in clinical fMRI

Functional magnetic resonance imaging (fMRI) paradigms on sensory-motor and language functions are reviewed from a clinical user's perspective. The objective was to identify special requirements regarding the design of fMRI paradigms for clinical applications. A wide range of methods for setting up fMRI examinations were found in the literature. It was concluded that there is a need for standardised procedures adapted for clinical settings. Sensory-motor activation patterns do not vary much at different hand motion tasks. Nevertheless it is one of the most important clinical tests. In contrast, the language system is much more complex. In several studies it has been observed that word production tasks are preferable in determination of language lateralisation. Broca's area is activated by most tasks, whereas sentence processing and semantic decision also involve activation in temporoparietal and frontal areas. However, combined task analysis (CTA) of several different tasks has been found to be more robust and reliable for clinical fMRI compared to separate task analysis.

Real time fMRI: a tool for the routine presurgical localisation of the motor cortex

In patients with brain lesions adjacent to the central area, exact preoperative knowledge of the spatial relation of the tumour to the motor cortex is of major importance. Many studies have shown that functional magnetic resonance imaging (fMRI) is a reliable tool to identify the motor cortex. However, fMRI data acquisition and data processing are time-consuming procedures, and this prevents general routine clinical application. We report a new application of real time fMRI that allows immediate access to fMRI results by automatic on-line data processing. Prior to surgery we examined ten patients with a brain tumour adjacent to the central area. Three measurements were performed at a 1.5-T Magnetom Vision Scanner (Siemens, Forchheim, Germany) on seven patients and at a 1.5-T Intera Scanner (Philips, Best, The Netherlands) on three patients using a sequential finger-tapping paradigm for motor cortex activation versus at rest condition. Blood oxygen level-dependant (BOLD) images were acquired using a multislice EPI sequence (16 slices, TE 60, TR 6000, FOV 210x210, matrix 64x64). The central sulcus of the left hemisphere could be clearly identified by a maximum of cortical activity after finger tapping of the right hand in all investigated patients. In eight of ten patients the right central sulcus was localised by a signal maximum, whereas in two patients the central sulcus could not be identified due to a hemiparesis in one and strong motion artefacts in the second patient. Finger tapping with one side versus rest condition seems to result in more motion artefacts, while finger tapping of the right versus the left hand yielded the strongest signal in the central area. Real time fMRI is a quick and reliable method to identify the central sulcus and has the potential to become a clinical tool to assess patients non-invasively before neurosurgical treatment.

Localization of the motor and speech zones of the cerebral cortex by functional magnetic resonance tomography

Functional magnetic resonance tomography provides a non-invasive method for mapping the cerebral cortex. The aim of the present work was to assess the potential and suitability of this method in a series of brain disorders. Studies were performed on 32 volunteers (mean age 37.8 +/- 20.9 years) and 16 patients with tumors of the cerebral cortex (mean age 36.2 +/- 24.2 years). Initial functional images were processed by statistical methods. Computed activation maps were superimposed on anatomical images. In 89% of cases, functional magnetic resonance tomography allowed the motor cortex and Broca's area to be localized; in almost 69%, the method impinged on the therapeutic tactics used in patients with cerebral cortex lesions. Thus, functional magnetic resonance tomography can be used in clinical conditions to obtain information not yielded by other diagnostic methods and which can be used to plan the neurosurgical treatment of patients with supratentorial brain tumors with maximum preservation of cerebral cortex function. Assessments of the state of the motor and speech areas by this tomographic method has potential applications in neurosurgery and neurophysiology.

Fuzzy cluster analysis of high-field functional MRI data

Functional magnetic resonance imaging (fMRI) based on blood-oxygen level dependent (BOLD) contrast today is an established brain research method and quickly gains acceptance for complementary clinical diagnosis. However, neither the basic mechanisms like coupling between neuronal activation and haemodynamic response are known exactly, nor can the various artifacts be predicted or controlled. Thus, modeling functional signal changes is non-trivial and exploratory data analysis (EDA) may be rather useful. In particular, identification and separation of artifacts as well as quantification of expected, i.e. stimulus correlated, and novel information on brain activity is important for both, new insights in neuroscience and future developments in functional MRI of the human brain. After an introduction on fuzzy clustering and very high-field fMRI we present several examples where fuzzy cluster analysis (FCA) of fMRI time series helps to identify and locally separate various artifacts. We also present and discuss applications and limitations of fuzzy cluster analysis in very high-field functional MRI: differentiate temporal patterns in MRI using (a) a test object with static and dynamic parts, (b) artifacts due to gross head motion artifacts. Using a synthetic fMRI data set we quantitatively examine the influences of relevant FCA parameters on clustering results in terms of receiver-operator characteristics (ROC) and compare them with a commonly used model-based correlation analysis (CA) approach. The application of FCA in analyzing in vivo fMRI data is shown for (a) a motor paradigm, (b) data from multi-echo imaging, and (c) a fMRI study using mental rotation of three-dimensional cubes. We found that differentiation of true "neural" from false "vascular" activation is possible based on echo time dependence and specific activation levels, as well as based on their signal time-course. Exploratory data analysis methods in general and fuzzy cluster analysis in particular may help to identify artifacts and add novel and unexpected information valuable for interpretation, classification and characterization of functional MRI data which can be used to design new data acquisition schemes, stimulus presentations, neuro(physio)logical paradigms, as well as to improve quantitative biophysical models.

Now you see it, now you don't: statistical and methodological considerations in fMRI

We illustrate the effects of statistical threshold, spatial clustering, voxel size, and two approaches to multiple comparison correction on fMRI results. We first analyzed fMRI images obtained from a single subject during a noun-verb matching task. Data were analyzed with Statistical Parametric Mapping (SPM) using two different voxel sizes, and results were displayed at three different levels of statistical significance. At each statistical threshold, results were first uncorrected for multiple comparisons and spatial extent and then presented using a spatial extent cluster of 20 voxels. We then statistically controlled the Type I error rate associated with multiple comparisons by using the false discovery rate and by the random field adjustment for false-positive rate used by SPM. We also examined group results from language and graphesthesia paradigms at three levels of statistical significance. In all circumstances, apparent random activations decreased as more conservative statistical approaches were employed, but activation in areas considered to be functionally significant was also reduced. These issues are important in the choice of analytic approach and interpretation of fMRI results, with clear implications for the surgical management of individual patients when fMRI results are used to delineate specific areas of eloquent cortex.

Ethical issues in the clinical application of fMRI: factors affecting the validity and interpretation of activations

The ability of functional magnetic resonance imaging (fMRI) to localize activations in a single patient, along with the safety and widespread availability of this methodology, has lead to an increasing use of fMRI for clinical purposes such as pre-surgical planning. As methodology continues to improve and more experience with fMRI in the clinical setting is acquired, clinical functional neuroimaging will likely have an increasing influence over patient care. Therefore, ethical use of fMRI, as with other medical techniques, requires understanding the factors impacting the interpretation of the methodology. Issues affecting the validity and interpretation of clinical functional neuroimaging, including effects of altered hemodynamic response function, head motion, and structural changes in the brain, are reviewed. The distinction between correlated and necessary activation in a clinical context is discussed. Different types of statistical errors in fMRI analysis are described, along with their consequences to the patient. Finally, for the future of clinical fMRI development, the need for normative patient data, as well as standardized tasks, scan protocols, and data analyses, is discussed.

Interhemispheric reorganization of motor hand function to the primary motor cortex predicted with functional magnetic resonance imaging and transcranial magnetic stimulation

The objective of this study was presurgical assessment of reorganization of motor hand function in an 11-year-old girl with intractable epilepsy and a right-sided hemiplegia resulting from an extensive perinatal left hemispheric stroke. Prior to a left functional hemispherectomy, functional magnetic resonance imaging (MRI) showed that both nonparetic and paretic motor hand function predominantly activated the right primary motor cortex, whereas no activation was found in the left hemisphere. Transcranial magnetic stimulation of the right central area yielded responses in both the nonparetic and the paretic hand, whereas no responses were obtained after stimulation of the affected hemisphere. Both techniques indicated that motor function was mediated by corticospinal fibers originating from the undamaged (primary) motor cortex and predicted no further loss of motor hand function after surgery. Indeed, subsequent functional hemispherectomy induced no new sensorimotor deficits. Functional MRI was repeated 22 months after surgery and matched preoperative sensorimotor functional MRI findings, confirming reorganization of the primary motor cortex. No additional reorganization was introduced by surgery.

Characterization of BOLD activation in multi-echo fMRI data using fuzzy cluster analysis and a comparison with quantitative modeling

A combination of multiple gradient-echo imaging and exploratory data analysis (EDA), i.e. fuzzy cluster analysis (FCA), is proposed for separation and characterization of BOLD activation in single-shot spiral functional magnetic resonance imaging (fMRI) experiments at 3 T. Differentiation of functional activation using FCA is performed by clustering pixel signal changes (DeltaS) as a function of echo time (TE). Further vascular classification is supported by the localization of activation and the comparison with a single-exponential decay model. In some subjects, an additional indication for large vessels within a voxel was found as oscillation of the fMRI signal difference vs echo time (TE). Such large vessels may be separated from small vessel activation and, therefore, our proposed procedure might prove useful if a more specific functional localization is desired in fMRI. In addition to the signal change DeltaS, DeltaT(2)*/T(2)* is significantly different between activated regions. Averaged over all eight subjects DeltaT(2)* is 1.7 +/- 0.2 ms in ROIs with the highest signal change characterized as containing large vessels, whereas in ROIs corresponding to microvascular environment average DeltaT(2)* values are 0.8 +/- 0.1 ms.

Finger Somatotopy in Human Motor Cortex

Although qualitative reports about somatotopic representation of fingers in the human motor cortex exist, up to now no study could provide clear statistical evidence. The goal of the present study was to reinvestigate finger motor somatotopy by means of a thorough investigation of standardized movements of the index and little finger of the right hand. Using high resolution fMRI at 3 Tesla, blood oxygenation level-dependent (BOLD) responses in a group of 26 subjects were repeatedly measured to achieve reliable statistical results. The center of mass of all activated voxels within the primary motor cortex was calculated for each finger and each run. Results of all runs were averaged to yield an individual index and little finger representation for each subject. The mean center of mass localizations for all subjects were then submitted to a paired t test. Results show a highly significant though small scale somatotopy of fingerspecific activation patterns in the order indicated by Penfields motor homunculus. In addition, considerable overlap of finger specific BOLD responses was found. Comparing various methods of analysis, the mean center of mass distance for the two fingers was 2--3 mm with overlapping voxels included and 4--5 mm with overlapping voxels excluded. Our data may be best understood in the context of the work of Schieber (1999) who recently described overlapping somatotopic gradients in lesion studies with humans.