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

7 T and beyond: toward a synergy between fMRI-based presurgical mapping at ultrahigh magnetic fields, AI, and robotic neurosurgery

Presurgical evaluation with functional magnetic resonance imaging (fMRI) can reduce postsurgical morbidity. Here, we discuss presurgical fMRI mapping at ultra-high magnetic fields (UHF), i.e., ≥ 7 T, in the light of the current growing interest in artificial intelligence (AI) and robot-assisted neurosurgery. The potential of submillimetre fMRI mapping can help better appreciate uncertainty on resection margins, though geometric distortions at UHF might lessen the accuracy of fMRI maps. A useful trade-off for UHF fMRI is to collect data with 1-mm isotropic resolution to ensure high sensitivity and subsequently a low risk of false negatives. Scanning at UHF might yield a revival interest in slow event-related fMRI, thereby offering a richer depiction of the dynamics of fMRI responses. The potential applications of AI concern denoising and artefact removal, generation of super-resolution fMRI maps, and accurate fusion or coregistration between anatomical and fMRI maps. The latter can benefit from the use of T1-weighted echo-planar imaging for better visualization of brain activations. Such AI-augmented fMRI maps would provide high-quality input data to robotic surgery systems, thereby improving the accuracy and reliability of robot-assisted neurosurgery. Ultimately, the advancement in fMRI at UHF would promote clinically useful synergies between fMRI, AI, and robotic neurosurgery.Relevance statement This review highlights the potential synergies between fMRI at UHF, AI, and robotic neurosurgery in improving the accuracy and reliability of fMRI-based presurgical mapping.Key points• Presurgical fMRI mapping at UHF improves spatial resolution and sensitivity.• Slow event-related designs offer a richer depiction of fMRI responses dynamics.• AI can support denoising, artefact removal, and generation of super-resolution fMRI maps.• AI-augmented fMRI maps can provide high-quality input data to robotic surgery systems.

Dynamic Causal Modeling of the Prefrontal/Amygdala Network During Processing of Emotional Faces

Introduction: The importance of the amygdala/medial orbitofrontal cortex (OFC) network during processing of emotional stimuli, emotional faces in particular, is well established. This premise is supported by converging evidence from animal models, human neuroanatomical results, and neuroimaging studies. However, there is missing evidence from human brain connectivity studies that the OFC and no other prefrontal brain areas such as the dorsolateral prefrontal cortex (DLPFC) or ventrolateral prefrontal cortex (VLPFC) are responsible for amygdala regulation in the functional context of emotional face stimuli. Methods: Dynamic causal modeling of ultrahigh-field functional magnetic resonance imaging data acquired at 7 Tesla in 38 healthy subjects and a well-established paradigm for emotional face processing were used to assess the central role of the OFC to provide empirical validation for the assumed network architecture. Results: Using Bayesian model selection, it is demonstrated that indeed the OFC, and not the VLPFC and the DLPFC, downregulates amygdala activation during the emotion discrimination task. In addition, Bayesian model averaging group results were rigorously tested using bootstrapping, further corroborating these findings and providing an estimator for robustness and optimal sample sizes. Discussion: While it is true that VLPFC and DLPFC are relevant for the processing of emotional faces and are connected to the OFC, the OFC appears to be a central hub for the prefrontal/amygdala interaction. Impact statement Using dynamic causal modeling (DCM), abnormal effective connectivity in the orbitofrontal cortex (OFC)/amygdala network has been repeatedly observed in the pathophysiology of psychiatric disorders. However, it has to be considered that these findings are all based on the a priori assumption of the OFC being the central area for prefrontal control regulating amygdala activation. This is particularly important, as DCM results conditionally depend on the underlying model space used for model selection. Using Bayesian model comparison methods, it is shown that the OFC (and not the dorsolateral prefrontal cortex or ventrolateral prefrontal cortex) engages in amygdala downregulation in the context emotional face processing.

Tumor location and reduction in functional MRI estimates of language laterality

OBJECTIVE

Brain tumors located close to the language cortex may distort functional MRI (fMRI)-based estimates of language dominance. The nature of this distortion, and whether this is an artifact of numerous confounders, remains unknown. The authors hypothesized tumor bias based on laterality estimates independent of confounders and that the effects are the greatest for tumors proximal to Broca's area.

METHODS

To answer this question, the authors reviewed more than 1113 patients who underwent preoperative fMRI to match samples on 11 known confounders (tumor location, size, type, and grade; seizure history; prior neurosurgery; aphasia presence and severity; and patient age, sex, and handedness). The samples included 30 patients with left hemisphere tumors (15 anterior and 15 posterior) and 30 with right hemisphere tumors (15 anterior and 15 posterior), thus totaling 60 patients (25 women; 18 left-handed and 4 ambidextrous; mean age 47 [SD 14.1] years). Importantly, the authors matched not only patients with left and right hemisphere tumors but also those with anterior and posterior tumors. Standard fMRI laterality indices (LIs) were calculated using whole-brain and region of interest (ROI) approaches (Broca's and Wernicke's areas).

RESULTS

Tumors close to Broca's area in the left hemisphere decreased LIs independently of known confounders. At the whole-brain level, this appeared to reflect a decrease in LI values in patients with left anterior tumors compared with patients with right anterior tumors. ROI analysis replicated these findings. Broca's area LIs were significantly lower (p = 0.02) in patients with left anterior tumors (mean LI 0.28) when compared with patients with right anterior tumors (mean LI 0.70). Changes in Wernicke's area-based LIs did not differ as a function of the tumor hemisphere. Therefore, in patients with left anterior tumors, it is essential to assess language laterality using left posterior ROIs. In all remaining tumor groups (left posterior tumors and right hemisphere tumors), language laterality derived from the anterior language ROI was the most robust measure of language dominance.

CONCLUSIONS

Patients with tumors close to Broca's area showed more bilateral fMRI language maps independent of known confounders. The authors caution against the assumption that this reduced language laterality suggests no or little risk to language function following tumor resection in the left inferior frontal gyrus. Their results address how to interpret fMRI data for neurosurgical purposes, along with theoretical questions of contralesional functional compensation and disinhibition.

Organizing Variables Affecting fMRI Estimates of Language Dominance in Patients with Brain Tumors

Numerous variables can affect the assessment of language dominance using presurgical functional magnetic resonance (fMRI) in patients with brain tumors. This work organizes the variables into confounding and modulating factors. Confounding factors give the appearance of changed language dominance. Most confounding factors are fMRI-specific and they can substantially disrupt the evaluation of language dominance. Confounding factors can be divided into two categories: tumor-related and fMRI analysis. The tumor-related confounds further subdivide into tumor characteristics (e.g., tumor grade) and tumor-induced conditions (aphasia). The fMRI analysis confounds represent technical aspects of fMRI methods (e.g., a fixed versus an individual threshold). Modulating factors can modify language dominance without confounding it. They are not fMRI-specific, and they can impact language dominance both in healthy individuals and neurosurgical patients. The effect of most modulating factors on fMRI language dominance is smaller than that of confounding factors. Modulating factors include demographics (e.g., age) and linguistic variables (e.g., early bilingualism). Three cases of brain tumors in the left hemisphere are presented to illustrate how modulating confounding and modulating factors can impact fMRI estimates of language dominance. Distinguishing between confounding and modulating factors can help interpret the results of presurgical language mapping with fMRI.

Individualized cognitive neuroscience needs 7T: Comparing numerosity maps at 3T and 7T MRI

The field of cognitive neuroscience is weighing evidence about whether to move from the current standard field strength of 3 Tesla (3T) to ultra-high field (UHF) of 7T and above. The present study contributes to the evidence by comparing a computational cognitive neuroscience paradigm at 3T and 7T. The goal was to evaluate the practical effects, i.e. model predictive power, of field strength on a numerosity task using accessible pre-processing and analysis tools. Previously, using 7T functional magnetic resonance imaging and biologically-inspired analyses, i.e. population receptive field modelling, we discovered topographical organization of numerosity-selective neural populations in human parietal cortex. Here we show that these topographic maps are also detectable at 3T. However, averaging of many more functional runs was required at 3T to reliably reconstruct numerosity maps. On average, one 7T run had about four times the model predictive power of one 3T run. We believe that this amount of scanning would have made the initial discovery of the numerosity maps on 3T highly infeasible in practice. Therefore, we suggest that the higher signal-to-noise ratio and signal sensitivity of UHF MRI is necessary to build mechanistic models of the organization and function of our cognitive abilities in individual participants.

Prior Neurosurgery Decreases fMRI Estimates of Language Laterality in Patients with Gliomas within Anterior Language Sites

The impact of previous surgery on the assessment of language dominance with preoperative fMRI remains inconclusive in patients with recurrent brain tumors. Samples in this retrospective study included 17 patients with prior brain surgery and 21 patients without prior surgery (38 patients total; mean age 43.2, SD = 11.9; 18 females; seven left-handed). All the patients were left language dominant, as determined clinically. The two samples were matched on 10 known confounds, including, for example, tumor laterality and location (all tumors affected Brodmann areas 44/45/47). We calculated fMRI language dominance with laterality indices using a whole-brain and region of interest approach (ROI; Broca’s and Wernicke’s area). Patients with prior surgery had decreased fMRI language dominance (p = 0.03) with more activity in the right hemisphere (p = 0.03) than patients without surgery. Patients with prior brain surgery did not display less language activity in the left hemisphere than patients without surgery. These results were replicated using an ROI approach in the affected Broca’s area. Further, we observed no differences between our samples in the unaffected Wernicke’s area. In sum, prior brain surgery affecting Broca’s area could be a confounding factor that needs to be considered when evaluating fMRI language dominance.

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.

Clinical Neuroimaging Using 7 T MRI: Challenges and Prospects

The aim of this article is to illustrate the principal challenges, from the medical and technical point of view, associated with the use of ultrahigh field (UHF) scanners in the clinical setting and to present available solutions to circumvent these limitations. We would like to show the differences between UHF scanners and those used routinely in clinical practice, the principal advantages, and disadvantages, the different UHFs that are ready be applied to routine clinical practice such as susceptibility-weighted imaging, fluid-attenuated inversion recovery, 3-dimensional time of flight, magnetization-prepared rapid acquisition gradient echo, magnetization-prepared 2 rapid acquisition gradient echo, and diffusion-weighted imaging, the technical principles of these sequences, and the particularities of advanced techniques such as diffusion tensor imaging, spectroscopy, and functional imaging at 7TMR. Finally, the main clinical applications in the field of the neuroradiology are discussed and the side effects are reported.

Neural Correlates of Consumer Buying Motivations: A 7T functional Magnetic Resonance Imaging (fMRI) Study

Consumer buying motivations can be distinguished into three categories: functional, experiential, or symbolic motivations (Keller, 1993). Although prior neuroimaging studies have examined the neural substrates which enable these motivations, direct comparisons between these three types of consumer motivations have yet to be made. In the current study, we used 7 Tesla (7T) functional magnetic resonance imaging (fMRI) to assess the neural correlates of each motivation by instructing participants to view common consumer goods while emphasizing either functional, experiential, or symbolic values of these products. The results demonstrated mostly consistent activations between symbolic and experiential motivations. Although, these motivations differed in that symbolic motivation was associated with medial frontal gyrus (MFG) activation, whereas experiential motivation was associated with posterior cingulate cortex (PCC) activation. Functional motivation was associated with dorsolateral prefrontal cortex (DLPFC) activation, as compared to other motivations. These findings provide a neural basis for how symbolic and experiential motivations may be similar, yet different in subtle ways. Furthermore, the dissociation of functional motivation within the DLPFC supports the notion that this motivation relies on executive function processes relatively more than hedonic motivation. These findings provide a better understanding of the underlying neural functioning which may contribute to poor self-control choices.

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.

Language Mapping Using T2-Prepared BOLD Functional MRI in the Presence of Large Susceptibility Artifacts-Initial Results in Patients With Brain Tumor and Epilepsy

At present, presurgical functional mapping is the most prevalent clinical application of functional magnetic resonance imaging (fMRI). Signal dropouts and distortions caused by susceptibility effects in the current standard echo planar imaging (EPI)-based fMRI images are well-known problems and pose a major hurdle for the application of fMRI in several brain regions, many of which are related to language mapping in presurgical planning. Such artifacts are particularly problematic in patients with previous surgical resection cavities, craniotomy hardware, hemorrhage, and vascular malformation. A recently developed T2-prepared (T2prep) fMRI approach showed negligible distortion and dropouts in the entire brain even in the presence of large susceptibility effects. Here, we present initial results comparing T2prep- and multiband EPI-fMRI scans for presurgical language mapping using a sentence completion task in patients with brain tumor and epilepsy. In all patients scanned, T2prep-fMRI showed minimal image artifacts (distortion and dropout) and greater functional sensitivity than EPI-fMRI around the lesions containing blood products and in air-filled cavities. This enhanced sensitivity in T2prep-fMRI was also evidenced by the fact that functional activation during the sentence completion task was detected with T2prep-fMRI but not with EPI-fMRI in the affected areas with the same statistical threshold, whereas cerebrovascular reactivity during a breath-hold task was preserved in these same regions, implying intact neurovascular coupling in these patients. Although further investigations are required to validate these findings with invasive methods such as direct cortical stimulation mapping as the gold standard, this approach provides an alternative method for performing fMRI in brain regions with large susceptibility effects.

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.

Between- and within-site variability of fMRI localizations

This study provides first data about the spatial variability of fMRI sensorimotor localizations when investigating the same subjects at different fMRI sites. Results are comparable to a previous patient study. We found a median between-site variability of about 6 mm independent of task (motor or sensory) and experimental standardization (high or low). An intraclass correlation coefficient analysis using data quality measures indicated a major influence of the fMRI site on variability. In accordance with this, within-site localization variability was considerably lower (about 3 mm). We conclude that the fMRI site is a considerable confound for localization of brain activity. However, when performed by experienced clinical fMRI experts, brain pathology does not seem to have a relevant impact on the reliability of fMRI localizations. Hum Brain Mapp 37:2151-2160, 2016. © 2016 Wiley Periodicals, Inc.

Presurgical brain mapping in epilepsy using simultaneous EEG and functional MRI at ultra-high field: feasibility and first results

OBJECTIVES

The aim of this study was to demonstrate that eloquent cortex and epileptic-related hemodynamic changes can be safely and reliably detected using simultaneous electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) recordings at ultra-high field (UHF) for clinical evaluation of patients with epilepsy.

MATERIALS AND METHODS

Simultaneous EEG-fMRI was acquired at 7 T using an optimized setup in nine patients with lesional epilepsy. According to the localization of the lesion, mapping of eloquent cortex (language and motor) was also performed in two patients.

RESULTS

Despite strong artifacts, efficient correction of intra-MRI EEG could be achieved with optimized artifact removal algorithms, allowing robust identification of interictal epileptiform discharges. Noise-sensitive topography-related analyses and electrical source localization were also performed successfully. Localization of epilepsy-related hemodynamic changes compatible with the lesion were detected in three patients and concordant with findings obtained at 3 T. Local loss of signal in specific regions, essentially due to B 1 inhomogeneities were found to depend on the geometric arrangement of EEG leads over the cap.

CONCLUSION

These results demonstrate that presurgical mapping of epileptic networks and eloquent cortex is both safe and feasible at UHF, with the benefits of greater spatial resolution and higher blood-oxygenation-level-dependent sensitivity compared with the more traditional field strength of 3 T.