Resting-state functional magnetic resonance imaging versus task-based activity for language mapping and correlation with perioperative cortical mapping

Systematic Review Between Resting-State fMRI and Task fMRI in Planning for Brain Tumour Surgery

As an alternative to task-based functional magnetic resonance imaging (T-fMRI), resting-state functional magnetic resonance imaging (Rs-fMRI) is suggested for preoperative mapping of patients with brain tumours, with an emphasis on treatment guidance and neurodegeneration prediction. A systematic review was conducted of 18 recent studies involving 1035 patients with brain tumours and Rs-fMRI protocols. This was accomplished by searching the electronic databases PubMed, Scopus, and Web of Science. For clinical benefit, we compared Rs-fMRI to standard T-fMRI and intraoperative direct cortical stimulation (DCS). The results of Rs-fMRI and T-fMRI were compared and their correlation with intraoperative DCS results was examined through a systematic review. Our exhaustive investigation demonstrated that Rs-fMRI is a dependable and sensitive preoperative mapping technique that detects neural networks in the brain with precision and identifies crucial functional regions in agreement with intraoperative DCS. Rs-fMRI comes in handy, especially in situations where T-fMRI proves to be difficult because of patient-specific factors. Additionally, our exhaustive investigation demonstrated that Rs-fMRI is a valuable tool in the preoperative screening and evaluation of brain tumours. Furthermore, its capability to assess brain function, forecast surgical results, and enhance decision-making may render it applicable in the clinical management of brain tumours.

An update on tests used for intraoperative monitoring of cognition during awake craniotomy

PURPOSE

Mapping higher-order cognitive functions during awake brain surgery is important for cognitive preservation which is related to postoperative quality of life. A systematic review from 2018 about neuropsychological tests used during awake craniotomy made clear that until 2017 language was most often monitored and that the other cognitive domains were underexposed (Ruis, J Clin Exp Neuropsychol 40(10):1081-1104, 218). The field of awake craniotomy and cognitive monitoring is however developing rapidly. The aim of the current review is therefore, to investigate whether there is a change in the field towards incorporation of new tests and more complete mapping of (higher-order) cognitive functions.

METHODS

We replicated the systematic search of the study from 2018 in PubMed and Embase from February 2017 to November 2023, yielding 5130 potentially relevant articles. We used the artificial machine learning tool ASReview for screening and included 272 papers that gave a detailed description of the neuropsychological tests used during awake craniotomy.

RESULTS

Comparable to the previous study of 2018, the majority of studies (90.4%) reported tests for assessing language functions (Ruis, J Clin Exp Neuropsychol 40(10):1081-1104, 218). Nevertheless, an increasing number of studies now also describe tests for monitoring visuospatial functions, social cognition, and executive functions.

CONCLUSIONS

Language remains the most extensively tested cognitive domain. However, a broader range of tests are now implemented during awake craniotomy and there are (new developed) tests which received more attention. The rapid development in the field is reflected in the included studies in this review. Nevertheless, for some cognitive domains (e.g., executive functions and memory), there is still a need for developing tests that can be used during awake surgery.

A Comprehensive Review on the Role of Resting-State Functional Magnetic Resonance Imaging in Predicting Post-Stroke Motor and Sensory Outcomes

Stroke is a major leading cause of chronic disability, often affecting patients' motor and sensory functions. Functional magnetic resonance imaging (fMRI) is the most commonly used method of functional neuroimaging, and it allows for the non-invasive study of brain activity. The time-dependent coactivation of different brain regions at rest is described as resting-state activation. As a non-invasive task-independent functional neuroimaging approach, resting-state fMRI (rs-fMRI) may provide therapeutically useful information on both the focal vascular lesion and the connectivity-based reorganization and subsequent functional recovery in stroke patients. Considering the role of a prompt and accurate prognosis in stroke survivors along with the potential of rs-fMRI in identifying patterns of neuroplasticity in different post-stroke phases, this review provides a comprehensive overview of the latest literature regarding the role of rs-fMRI in stroke prognosis in terms of motor and sensory outcomes. Our comprehensive review suggests that with the advancement of MRI acquisition and data analysis methods, rs-fMRI emerges as a promising tool to study the motor and sensory outcomes in stroke patients and evaluate the effects of different interventions.

Implementation of Automated Pipeline for Resting-State fMRI Analysis with PACS Integration

In recent years, the quantity and complexity of medical imaging acquisition and processing have increased tremendously. The explosion in volume and need for advanced imaging analysis have led to the creation of numerous software programs, which have begun to be incorporated into clinical practice for indications such as automated stroke assessment, brain tumor perfusion processing, and hippocampal volume analysis. Despite these advances, there remains a need for specialized, custom-built software for advanced algorithms and new areas of research that is not widely available or adequately integrated in these "out-of-the-box" solutions. The purpose of this paper is to describe the implementation of an image-processing pipeline that is versatile and simple to create, which allows for rapid prototyping of image analysis algorithms and subsequent testing in a clinical environment. This pipeline uses a combination of Orthanc server, custom MATLAB code, and publicly available FMRIB Software Library and RestNeuMap tools to automatically receive and analyze resting-state functional MRI data collected from a custom filter on the MR scanner output. The processed files are then sent directly to Picture Archiving and Communications System (PACS) without the need for user input. This initial experience can serve as a framework for those interested in simple implementation of an automated pipeline customized to clinical needs.

Heart rate variability during slow wave sleep is linked to functional connectivity in the central autonomic network

Reduced heart rate variability can be an early sign of autonomic dysfunction in neurodegenerative diseases and may be related to brain dysfunction in the central autonomic network. As yet, such autonomic dysfunction has not been examined during sleep-which is an ideal physiological state to study brain-heart interaction as both the central and peripheral nervous systems behave differently compared to during wakefulness. Therefore, the primary aim of the current study was to examine whether heart rate variability during nocturnal sleep, specifically slow wave (deep) sleep, is associated with central autonomic network functional connectivity in older adults 'at-risk' of dementia. Older adults (n = 78; age range = 50-88 years; 64% female) attending a memory clinic for cognitive concerns underwent resting-state functional magnetic resonance imaging and an overnight polysomnography. From these, central autonomic network functional connectivity strength and heart rate variability data during sleep were derived, respectively. High-frequency heart rate variability was extracted to index parasympathetic activity during distinct periods of sleep, including slow wave sleep as well as secondary outcomes of non-rapid eye movement sleep, wake after sleep onset, and rapid eye movement sleep. General linear models were used to examine associations between central autonomic network functional connectivity and high-frequency heart rate variability. Analyses revealed that increased high-frequency heart rate variability during slow wave sleep was associated with stronger functional connectivity (F = 3.98, P = 0.022) in two core brain regions within the central autonomic network, the right anterior insular and posterior midcingulate cortex, as well as stronger functional connectivity (F = 6.21, P = 0.005) between broader central autonomic network brain regions-the right amygdala with three sub-nuclei of the thalamus. There were no significant associations between high-frequency heart rate variability and central autonomic network connectivity during wake after sleep onset or rapid eye movement sleep. These findings show that in older adults 'at-risk' of dementia, parasympathetic regulation during slow wave sleep is uniquely linked to differential functional connectivity within both core and broader central autonomic network brain regions. It is possible that dysfunctional brain-heart interactions manifest primarily during this specific period of sleep known for its role in memory and metabolic clearance. Further studies elucidating the pathophysiology and directionality of this relationship should be conducted to determine if heart rate variability drives neurodegeneration, or if brain degeneration within the central autonomic network promotes aberrant heart rate variability.

Improved localization of language areas using single voxel signal analysis of unprocessed fMRI data

Activated brain regions can be visualized and localized with the use of fMRI (functional magnetic imaging). This is based on changes in the blood flow in activated regions, or more precisely on the hemodynamic response function (HRF) and the Blood-Oxygen-Level-Dependent (BOLD) effect. This study used a task-based fMRI examination with language paradigms in order to stimulate the language areas. The measured fMRI data are frequently altered by different preprocessing steps for the analysis and the display of activations. These changes can lead to discrepancies between the displayed and the truly measured location of the activations. Simple t-maps were created with unprocessed fMRI data, to provide a more realistic representation of the language areas. HRF-dependent single-voxel fMRI signal analysis was performed to improve the analyzability of these activation maps.

Advanced Neuroimaging Approaches to Pediatric Brain Tumors

Simple Summary

After leukemias, brain tumors are the most common cancers in children, and early, accurate diagnosis is critical to improve patient outcomes. Beyond the conventional imaging methods of computed tomography (CT) and magnetic resonance imaging (MRI), advanced neuroimaging techniques capable of both structural and functional imaging are moving to the forefront to improve the early detection and differential diagnosis of tumors of the central nervous system. Here, we review recent developments in neuroimaging techniques for pediatric brain tumors.

Abstract

Central nervous system tumors are the most common pediatric solid tumors; they are also the most lethal. Unlike adults, childhood brain tumors are mostly primary in origin and differ in type, location and molecular signature. Tumor characteristics (incidence, location, and type) vary with age. Children present with a variety of symptoms, making early accurate diagnosis challenging. Neuroimaging is key in the initial diagnosis and monitoring of pediatric brain tumors. Conventional anatomic imaging approaches (computed tomography (CT) and magnetic resonance imaging (MRI)) are useful for tumor detection but have limited utility differentiating tumor types and grades. Advanced MRI techniques (diffusion-weighed imaging, diffusion tensor imaging, functional MRI, arterial spin labeling perfusion imaging, MR spectroscopy, and MR elastography) provide additional and improved structural and functional information. Combined with positron emission tomography (PET) and single-photon emission CT (SPECT), advanced techniques provide functional information on tumor metabolism and physiology through the use of radiotracer probes. Radiomics and radiogenomics offer promising insight into the prediction of tumor subtype, post-treatment response to treatment, and prognostication. In this paper, a brief review of pediatric brain cancers, by type, is provided with a comprehensive description of advanced imaging techniques including clinical applications that are currently utilized for the assessment and evaluation of pediatric brain tumors.

Transfer Learning from Healthy to Unhealthy Patients for the Automated Classification of Functional Brain Networks in fMRI

Functional Magnetic Resonance Imaging (fMRI) is an essential tool for the pre-surgical planning of brain tumor removal, which allows the identification of functional brain networks to preserve the patient’s neurological functions. One fMRI technique used to identify the functional brain network is the resting-state-fMRI (rs-fMRI). This technique is not routinely available because of the necessity to have an expert reviewer who can manually identify each functional network. The lack of sufficient unhealthy data has so far hindered a data-driven approach based on machine learning tools for full automation of this clinical task. In this article, we investigate the possibility of such an approach via the transfer learning method from healthy control data to unhealthy patient data to boost the detection of functional brain networks in rs-fMRI data. The end-to-end deep learning model implemented in this article distinguishes seven principal functional brain networks using fMRI images. The best performance of a 75% correct recognition rate is obtained from the proposed deep learning architecture, which shows its superiority over other machine learning algorithms that were equally tested for this classification task. Based on this best reference model, we demonstrate the possibility of boosting the results of our algorithm with transfer learning from healthy patients to unhealthy patients. This application of the transfer learning technique opens interesting possibilities because healthy control subjects can be easily enrolled for fMRI data acquisition since it is non-invasive. Consequently, this process helps to compensate for the usual small cohort of unhealthy patient data. This transfer learning approach could be extended to other medical imaging modalities and pathology.

A Dedicated Tool for Presurgical Mapping of Brain Tumors and Mixed-Reality Navigation During Neurosurgery

Brain tumor surgery requires a delicate tradeoff between complete removal of neoplastic tissue while minimizing loss of brain function. Functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) have emerged as valuable tools for non-invasive assessment of human brain function and are now used to determine brain regions that should be spared to prevent functional impairment after surgery. However, image analysis requires different software packages, mainly developed for research purposes and often difficult to use in a clinical setting, preventing large-scale diffusion of presurgical mapping. We developed a specialized software able to implement an automatic analysis of multimodal MRI presurgical mapping in a single application and to transfer the results to the neuronavigator. Moreover, the imaging results are integrated in a commercially available wearable device using an optimized mixed-reality approach, automatically anchoring 3-dimensional holograms obtained from MRI with the physical head of the patient. This will allow the surgeon to virtually explore deeper tissue layers highlighting critical brain structures that need to be preserved, while retaining the natural oculo-manual coordination. The enhanced ergonomics of this procedure will significantly improve accuracy and safety of the surgery, with large expected benefits for health care systems and related industrial investors.

[Comparison of resting state and task-based functional MRI in preoperative mapping in patients with brain gliomas]

OBJECTIVE

To analyze and compare the results of cerebral cortex mapping with task-based (tb-fMRI) and resting-state functional MRI in patients with glioma of eloquent cortical areas.

MATERIAL AND METHODS

There were 55 patients (24 men and 31 women aged 24 - 74 years, median 39) with glial tumors. In 26 patients, the tumor was located in motor areas. Twenty-nine patients had lesions of Broca and Wernicke's areas. All patients underwent preoperative tb-fMRI and rs-fMRI. Then, resection of tumor was carried out in all cases.

RESULTS

Comparison of fMRI and rs-fMRI activation maps was assessed by calculating the Dice coefficient for inclusive speech and motor cortex masks and exclusive masks without brainstem, cerebellum, subcortical nuclei. Inclusive Dice coefficient for motor cortex ranged from 0.11 to 0.50, for speech cortex - from 0.006 to 0.240 (p<0.05). In case of exclusive masks, this value ranged from 0.15 to 0.55 for motor cortex and from 0.004 to 0.205 for speech cortex (p<0.05).

CONCLUSION

When comparing the results of cortical mapping in patients with glial tumors, the use of hemispheric exclusive and inclusive masks did not significantly increase activation maps matching. Probably, low degree of correspondence was associated with different genesis of activations, as well as with high variability of speech cortex.

The genetic architecture of language functional connectivity

Language is a unique trait of the human species, of which the genetic architecture remains largely unknown. Through language disorders studies, many candidate genes were identified. However, such complex and multifactorial trait is unlikely to be driven by only few genes and case-control studies, suffering from a lack of power, struggle to uncover significant variants. In parallel, neuroimaging has significantly contributed to the understanding of structural and functional aspects of language in the human brain and the recent availability of large scale cohorts like UK Biobank have made possible to study language via image-derived endophenotypes in the general population. Because of its strong relationship with task-based fMRI (tbfMRI) activations and its easiness of acquisition, resting-state functional MRI (rsfMRI) have been more popularised, making it a good surrogate of functional neuronal processes. Taking advantage of such a synergistic system by aggregating effects across spatially distributed traits, we performed a multivariate genome-wide association study (mvGWAS) between genetic variations and resting-state functional connectivity (FC) of classical brain language areas in the inferior frontal (pars opercularis, triangularis and orbitalis), temporal and inferior parietal lobes (angular and supramarginal gyri), in 32,186 participants from UK Biobank. Twenty genomic loci were found associated with language FCs, out of which three were replicated in an independent replication sample. A locus in 3p11.1, regulating EPHA3 gene expression, is found associated with FCs of the semantic component of the language network, while a locus in 15q14, regulating THBS1 gene expression is found associated with FCs of the perceptual-motor language processing, bringing novel insights into the neurobiology of language.

Resting-State Functional Magnetic Resonance Imaging for Surgical Neuro-Oncology Planning: Towards a Standardization in Clinical Settings

Resting-state functional magnetic resonance imaging (rest-f-MRI) is a neuroimaging technique that has demonstrated its potential in providing new insights into brain physiology. rest-f-MRI can provide useful information in pre-surgical mapping aimed to balancing long-term survival by maximizing the extent of resection of brain neoplasms, while preserving the patient’s functional connectivity. Rest-fMRI may replace or can be complementary to task-driven fMRI (t-fMRI), particularly in patients unable to cooperate with the task paradigm, such as children or sedated, paretic, aphasic patients. Although rest-fMRI is still under standardization, this technique has been demonstrated to be feasible and valuable in the routine clinical setting for neurosurgical planning, along with intraoperative electrocortical mapping. In the literature, there is growing evidence that rest-fMRI can provide valuable information for the depiction of glioma-related functional brain network impairment. Accordingly, rest-fMRI could allow a tailored glioma surgery improving the surgeon’s ability to increase the extent of resection (EOR), and simultaneously minimize the risk of damage of eloquent brain structures and neuronal networks responsible for the integrity of executive functions. In this article, we present a review of the literature and illustrate the feasibility of rest-fMRI in the clinical setting for presurgical mapping of eloquent networks in patients affected by brain tumors, before and after tumor resection.

Overt speech critically changes lateralization index and did not allow determination of hemispheric dominance for language: an fMRI study

Background

Pre-surgical mapping of language using functional MRI aimed principally to determine the dominant hemisphere. This mapping is currently performed using covert linguistic task in way to avoid motion artefacts potentially biasing the results. However, overt task is closer to natural speaking, allows a control on the performance of the task, and may be easier to perform for stressed patients and children. However, overt task, by activating phonological areas on both hemispheres and areas involved in pitch prosody control in the non-dominant hemisphere, is expected to modify the determination of the dominant hemisphere by the calculation of the lateralization index (LI).

Objective

Here, we analyzed the modifications in the LI and the interactions between cognitive networks during covert and overt speech task.

Methods

Thirty-three volunteers participated in this study, all but four were right-handed. They performed three functional sessions consisting of (1) covert and (2) overt generation of a short sentence semantically linked with an audibly presented word, from which we estimated the “Covert” and “Overt” contrasts, and a (3) resting-state session. The resting-state session was submitted to spatial independent component analysis to identify language network at rest (LANG), cingulo-opercular network (CO), and ventral attention network (VAN). The LI was calculated using the bootstrapping method.

Results

The LI of the LANG was the most left-lateralized (0.66 ± 0.38). The LI shifted from a moderate leftward lateralization for the Covert contrast (0.32 ± 0.38) to a right lateralization for the Overt contrast (− 0.13 ± 0.30). The LI significantly differed from each other. This rightward shift was due to the recruitment of right hemispheric temporal areas together with the nodes of the CO.

Conclusion

Analyzing the overt speech by fMRI allowed improvement in the physiological knowledge regarding the coordinated activity of the intrinsic connectivity networks. However, the rightward shift of the LI in this condition did not provide the basic information on the hemispheric language dominance. Overt linguistic task cannot be recommended for clinical purpose when determining hemispheric dominance for language.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12868-021-00671-y.

Current and Future Challenges of Functional MRI and Diffusion Tractography in the Surgical Setting: From Eloquent Brain Mapping to Neural Plasticity

Decades ago, Spetzler (1986) and Sawaya (1998) provided a rough brain segmentation of the eloquent areas of the brain, aimed to help surgical decisions in cases of vascular malformations and tumors, respectively. Currently in clinical use, their criteria are in need of revision. Defining functions (eg, sensorimotor, language and visual) that should be preserved during surgery seems a straightforward task. In practice, locating the specific areas that could cause a permanent vs transient deficit is not an easy task. This is particularly true for the associative cortex and cognitive domains such as language. The old model, with Broca's and Wernicke's areas at the forefront, has been superseded by a dual-stream model of parallel language processing; named ventral and dorsal pathways. This complicated network of cortical hubs and subcortical white matter pathways needing preservation during surgery is a work in progress. Preserving not only cortical regions but most importantly preserving the connections, or white matter fiber bundles, of core regions in the brain is the new paradigm. For instance, the arcuate fascicululs and inferior fronto-occipital fasciculus are key components of the dorsal and ventral language pathways, respectively; and their damage result in permanent language deficits. Interestedly, the damage of the temporal portions of these bundles -where there is a crossroad with other multiple bundles-, appears to be more important (permanent) than the damage of the frontal portions - where plasticity and contralateral activation could help. Although intraoperative direct cortical and subcortical stimulation have contributed largely, advanced MR techniques such as functional MRI (fMRI) and diffusion tractography (DT), are at the epi-center of our current understanding. Nevertheless, these techniques posse important challenges: such as neurovascular uncoupling or venous bias on fMRI; and appropriate anatomical validation or accurate representation of crossing fibers on DT. These limitations should be well understood and taken into account in clinical practice. Unifying multidisciplinary research and clinical efforts is desirable, so these techniques could contribute more efficiently not only to locate eloquent areas but to improve outcomes and our understanding of neural plasticity. Finally, although there are constant anatomical and functional regions at the individual level, there is a known variability at the inter-individual level. This concept should strengthen the importance of a personalized approach when evaluating these regions on fMRI and DT. It should strengthen the importance of personalized treatments as well, aimed to meet tailored needs and expectations.

Role of Functional Magnetic Resonance Imaging in the Presurgical Mapping of Brain Tumors

When planning for brain tumor resection, a balance between maximizing resection and minimizing injury to eloquent brain parenchyma is paramount. The advent of blood oxygenation level-dependent functional magnetic resonance (fMR) imaging has allowed researchers and clinicians to reliably measure physiologic fluctuations in brain oxygenation related to neuronal activity with good spatial resolution. fMR imaging can offer a unique insight into preoperative planning for brain tumors by identifying eloquent areas of the brain affected or spared by the neoplasm. This article discusses the fMR imaging techniques and their applications in neurosurgical planning.

fMRI Resting-State Connectivity between Language and Nonlanguage Areas as Defined by Intraoperative Electrocortical Stimulation in Low-Grade Glioma Patients

BACKGROUND AND OBJECTIVES

 It remains to be determined whether noninvasive functional imaging techniques can rival the clinical potential of direct electrocortical stimulation (DES). In this study, we compared the results of resting-state functional magnetic resonance imaging (rs-fMRI) to those of DES for language mapping. Our goals were twofold: (1) to replicate a previous study that demonstrated that resting-state connectivity (RSC) was significantly larger between positive DES language sites than between negative DES language sites and (2) to compare the spatial resolution of rs-fMRI to that of DES.

METHODS

 We conducted a retrospective study of nine low-grade glioma patients. Language sites were identified by intraoperative DES. We compared RSC values between and within groups of DES-positive and DES-negative regions of interest (ROIs). Both close-negative sites (i.e., DES-negative sites <1 cm apart from and on the same gyrus as DES-positive sites) and far-negative sites (i.e., purely randomly chosen sites not in the vicinity of the tumor or of the DES-positive sites but on the same lobe) were included. Receiver operating characteristics were used to quantify comparisons.

RESULTS

 Functional connectivity between all positive language sites was on average significantly higher than between all close-negative sites and between all far-negative sites. The functional connectivity between the positive language ROIs and their respective close-negative control sites was not smaller than between all positive language sites.

CONCLUSION

 rs-fMRI likely reflects similar neural information as detected with DES, but in its current form does not reach the spatial resolution of DES.

Age-Related Decline of Sensorimotor Integration Influences Resting-State Functional Brain Connectivity

Age-related decline in sensorimotor integration involves both peripheral and central components related to proprioception and kinesthesia. To explore the role of cortical motor networks, we investigated the association between resting-state functional connectivity and a gap-detection angle measured during an arm-reaching task. Four region pairs, namely the left primary sensory area with the left primary motor area (S1left-M1left), the left supplementary motor area with M1left (SMAleft-M1left), the left pre-supplementary motor area with SMAleft (preSMAleft-SMAleft), and the right pre-supplementary motor area with the right premotor area (preSMAright-PMdright), showed significant age-by-gap detection ability interactions in connectivity in the form of opposite-sign correlations with gap detection ability between younger and older participants. Morphometry and tractography analyses did not reveal corresponding structural effects. These results suggest that the impact of aging on sensorimotor integration at the cortical level may be tracked by resting-state brain activity and is primarily functional, rather than structural. From the observation of opposite-sign correlations, we hypothesize that in aging, a "low-level" motor system may hyper-engage unsuccessfully, its dysfunction possibly being compensated by a "high-level" motor system, wherein stronger connectivity predicts higher gap-detection performance. This hypothesis should be tested in future neuroimaging and clinical studies.

The Problem of Neurovascular Uncoupling

Neurovascular uncoupling (NVU) is one of the most important confounds of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMR imaging) in the setting of focal brain lesions such as brain tumors. This article reviews the assessment of NVU related to focal brain lesions with emphasis on the use of cerebrovascular reactivity mapping measurement methods and resting state BOLD fMR imaging metrics in the detection of NVU, as well as the use of amplitude of low-frequency fluctuation metrics to mitigate the effects of NVU on clinical fMR imaging activation.

Mapping language function with task-based vs. resting-state functional MRI

Background

Use of functional MRI (fMRI) in pre-surgical planning is a non-invasive method for pre-operative functional mapping for patients with brain tumors, especially tumors located near eloquent cortex. Currently, this practice predominantly involves task-based fMRI (T-fMRI). Resting state fMRI (RS-fMRI) offers an alternative with several methodological advantages. Here, we compare group-level analyses of RS-fMRI vs. T-fMRI as methods for language localization.

Purpose

To contrast RS-fMRI vs. T-fMRI as techniques for localization of language function.

Methods

We analyzed data obtained in 35 patients who had both T-fMRI and RS-fMRI scans during the course of pre-surgical evaluation. The RS-fMRI data were analyzed using a previously trained resting-state network classifier. The T-fMRI data were analyzed using conventional techniques. Group-level results obtained by both methods were evaluated in terms of two outcome measures: (1) inter-subject variability of response magnitude and (2) sensitivity/specificity analysis of response topography, taking as ground truth previously reported maps of the language system based on intraoperative cortical mapping as well as meta-analytic maps of language task fMRI responses.

Results

Both fMRI methods localized major components of the language system (areas of Broca and Wernicke) although not with equal inter-subject consistency. Word-stem completion T-fMRI strongly activated Broca's area but also several task-general areas not specific to language. RS-fMRI provided a more specific representation of the language system.

Conclusion

We demonstrate several advantages of classifier-based mapping of language representation in the brain. Language T-fMRI activated task-general (i.e., not language-specific) functional systems in addition to areas of Broca and Wernicke. In contrast, classifier-based analysis of RS-fMRI data generated maps confined to language-specific regions of the brain.

The role of resting-state functional MRI for clinical preoperative language mapping

Background

Task-based functional MRI (tb-fMRI) is a well-established technique used to identify eloquent cortex, but has limitations, particularly in cognitively impaired patients who cannot perform language paradigms. Resting-state functional MRI (rs-fMRI) is a potential alternative modality for presurgical mapping of language networks that does not require task performance. The purpose of our study is to determine the utility of rs-fMRI for clinical preoperative language mapping when tb-fMRI is limited.

Methods

We retrospectively reviewed 134 brain tumor patients who underwent preoperative fMRI language mapping. rs-fMRI was post-processed with seed-based correlation (SBC) analysis, when language tb-fMRI was limited. Two neuroradiologists reviewed both the tb-fMRI and rs-fMRI results. Six neurosurgeons retrospectively rated the usefulness of rs-fMRI for language mapping in their patients.

Results

Of the 134 patients, 49 cases had limited tb-fMRI and rs-fMRI was post-processed. Two neuroradiologists found rs-fMRI beneficial for functional language mapping in 41(84%) and 43 (88%) cases respectively; Cohen’s kappa is 0.83, with a 95% confidence interval (0.61, 1.00). The neurosurgeons found rs-fMRI “definitely” useful in 26 cases (60%) and “somewhat” useful in 13 cases (30%) in locating potential eloquent language centers of clinical interest. Six unsuccessful rs-fMRI cases were due to: head motion (2 cases), nonspecific functionality connectivity outside the posterior language network (1 case), and an unknown system instability (3 cases).

Conclusions

This study is a proof of concept that shows SBC rs-fMRI may be a viable alternative for clinical language mapping when tb-fMRI is limited.

The ventral attention network: the mirror of the language network in the right brain hemisphere

Resting-state functional MRI (RfMRI) analyses have identified two anatomically separable fronto-parietal attention networks in the human brain: a bilateral dorsal attention network and a right-lateralised ventral attention network (VAN). The VAN has been implicated in visuospatial cognition and, thus, potentially in the unilateral spatial neglect associated with right hemisphere lesions. Its parietal, frontal and temporal endpoints are thought to be structurally supported by undefined white matter tracts. We investigated the white matter tract connecting the VAN. We used three approaches to study the structural anatomy of the VAN: (a) independent component analysis on RfMRI (50 subjects), defining the endpoints of the VAN, (b) tractography in the same 50 healthy volunteers, with regions of interest defined by the MNI coordinates of cortical areas involved in the VAN used in a seed-based approach and (c) dissection, by Klingler's method, of 20 right hemispheres, for ex vivo studies of the fibre tracts connecting VAN endpoints. The VAN includes the temporoparietal junction and the ventral frontal cortex. The endpoints of the superior longitudinal fasciculus in its third portion (SLF III) and the arcuate fasciculus (AF) overlap with the VAN endpoints. The SLF III connects the supramarginal gyrus to the ventral portion of the precentral gyrus and the pars opercularis. The AF connects the middle and inferior temporal gyrus and the middle and inferior frontal gyrus. We reconstructed the structural connectivity of the VAN and considered it in the context if the pathophysiology of unilateral neglect and right hemisphere awake brain surgery.

Resting-state functional magnetic resonance imaging versus task-based activity for language mapping and correlation with perioperative cortical mapping

INTRODUCTION

Preoperative language mapping using functional magnetic resonance imaging (fMRI) aims to identify eloquent areas in the vicinity of surgically resectable brain lesions. fMRI methodology relies on the blood-oxygen-level-dependent (BOLD) analysis to identify brain language areas. Task-based fMRI studies the BOLD signal increase in brain areas during a language task to identify brain language areas, which requires patients' cooperation, whereas resting-state fMRI (rsfMRI) allows identification of functional networks without performing any explicit task through the analysis of the synchronicity of spontaneous BOLD signal oscillation between brain areas. The aim of this study was to compare preoperative language mapping using rsfMRI and task fMRI to cortical mapping (CM) during awake craniotomies.

METHODS

Fifty adult patients surgically treated for a brain lesion were enrolled. All patients had a presurgical language mapping with both task fMRI and rsfMRI. Identified language networks were compared to perioperative language mapping using electric cortical stimulation.

RESULTS

Resting-state fMRI was able to detect brain language areas during CM with a sensitivity of 100% compared to 65.6% with task fMRI. However, we were not able to perform a specificity analysis and compare task-based and rest fMRI with our perioperative setting in the current study. In second-order analysis, task fMRI imaging included main nodes of the SN and main areas involved in semantics were identified in rsfMRI.

CONCLUSION

Resting-state fMRI for presurgical language mapping is easy to implement, allowing the identification of functional brain language network with a greater sensitivity than task-based fMRI, at the cost of some precautions and a lower specificity. Further study is required to compare both the sensitivity and the specificity of the two methods and to evaluate the clinical value of rsfMRI as an alternative tool for the presurgical identification of brain language areas.