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T1 Magnetization Prepared Two Rapid Acquisition Gradient Echo (MP2RAGE) with compress sensing (CS) has been proposed as an improvement of the standard MPRAGE sequence with multiple advantages including reduced acquisition time needed to provide a quantitative 3D anatomical image coupled with T1-map. Here we investigated the agreement between FreeSurfer-derived volume measurements obtained from MPRAGE and CS MP2RAGE acquisitions.MPRAGE and CS MP2RAGE images of 37 subjects (14 patients with neurodegenerative disorders and 23 healthy controls) were acquired on a 3 T MR scanner and grey matter volumes were extracted using standard FreeSurfer parcellation. Lin's concordance correlation coefficient (Lin's CCC), Bland-Altman analysis, Passing-Bablok regression and DICE similarity coefficient were calculated to assess the agreement between the two.We found a good correspondence for most of the regions examined, with 93.5 % of them showing a mean DICE index0.70. Poorer results were found with Lin's CCC especially for subcortical labels across patients. The Bland-Altman analysis showed CS MP2RAGE tended to measure lower cortical volumes compared to MPRAGE but in most cases the difference wasn't statistically relevant. The Passing-Bablock regression indicated overall an absence of systematic constant and proportional bias when CS MP2RAGE was used instead of MPRAGE.We found a good concordance for volumes obtained from MPRAGE and CS MP2RAGE images using FreeSurfer, suggesting a possible role of CS MP2RAGE for structural analysis with significant advantages like shorter acquisition time and the possibility to simultaneously obtain quantitative T1-maps of the brain enriching the diagnostic power of this technique.

Double inversion recovery (DIR) imaging is used in multiple sclerosis (MS) clinical protocols to improve the detection of cortical and juxtacortical gray matter lesions by nulling confounding signals originating from the cerebrospinal fluid and white matter. Achieving a high isotropic spatial resolution, to depict the neocortex and its typically small lesions, is challenged by the reduced signal-to-noise ratio (SNR) determined by multiple tissue signal nulling. Here, we evaluate both conventional and optimized DIR implementations to improve tissue contrast (TC), SNR, and MS lesion conspicuity.DIR images were obtained from MS patients and healthy controls using both conventional and prototype implementations featuring a T2-preparation module (T2P), to improve SNR and TC, as well as an image reconstruction routine with iterative denoising (ID). We obtained quantitative measures of SNR and TC, and evaluated the visibility of MS cortical, cervical cord, and optic nerve lesions in the different DIR images.DIR implementations adopting T2P and ID enabled improving the SNR and TC of conventional DIR. In MS patients, 34% of cortical, optic nerve, and cervical cord lesions were visible only in DIR images acquired with T2P, and not in conventional DIR images. In the studied cases, image reconstruction with ID did not improve lesion conspicuity.DIR with T2P should be preferred to conventional DIR imaging in protocols studying MS patients, as it improves SNR and TC and determines an improvement in cortical, optic nerve, and cervical cord lesion conspicuity.

This study aims to investigate the correlation between intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) parameters in magnetic resonance imaging (MRI) and programmed death-ligand 1 (PD-L1) expression in non-small cell lung cancer (NSCLC). Twenty-one patients diagnosed with stage III NSCLC from April 2021 to April 2022 were included. The tumors were distinguished into two groups: no PD-L1 expression (

Soma and Neurite Density Image (SANDI) is an advanced diffusion magnetic resonance imaging (dMRI) signal model devised to probe in vivo microstructural information from both grey and white matter. However, this model requires multi-shell acquisitions that include b-values that are at least 6 times higher than those used in clinical practice. Here we present a 10-minute acquisition protocol that enables to acquire the necessary images for SANDI modelling on a clinical 3T scanner. We demonstrate the feasibility and assess the repeatability and reproducibility of our approach by computing microstructural metrics of SANDI and other state-of-the-art models on five healthy subjects and we present its potential clinical impact on five subjects affected by multiple sclerosis with relapsing-remitting course. Our results suggest that SANDI is a repeatable, reproducible, feasible, and practical method to characterize both white and grey matter tissues in both the healthy brain and in neurological diseases.

The study of patients after glioma resection offers a unique opportunity to investigate brain reorganization. It is currently unknown how the whole-brain connectomic profile evolves longitudinally after surgical resection of a glioma and how this may be associated with tumor characteristics and cognitive outcome. In this longitudinal study, we investigate the impact of tumor lateralization and grade on functional connectivity (FC) in highly connected networks, or hubs, and cognitive performance. Twenty-eight patients (17 high-grade, 11 low-grade gliomas) underwent longitudinal pre/post-surgery resting-state fMRI scans and neuropsychological assessments (73 total measures). FC matrices were constructed considering as functional hubs the default mode (DMN) and fronto-parietal networks. No-hubs included primary sensory functional networks and any other no-hubs nodes. Both tumor hemisphere and grade affected brain reorganization post-resection. In right-hemisphere tumor patients, regardless of grade and relative to left-hemisphere gliomas, FC increased longitudinally after the intervention, both in terms of FC within hubs (phubs = 0.0004) and FC between hubs and no-hubs (phubs-no-hubs = 0.005). Regardless of tumor side, only lower-grade gliomas showed longitudinal FC increases relative to high-grade tumors within a precise hub network, the DMN. The neurocognitive profile was longitudinally associated with spatial features of the connectome, mainly within the DMN. We provide evidence that clinical glioma features, such as lateralization and grade, affect post-surgical longitudinal functional reorganization and cognitive recovery. The data suggest a possible role of the DMN in supporting cognition, providing useful information for prognostic prediction and surgical planning.

BackgroundProton beam therapy (PBT) is an effective pediatric brain tumor treatment. However, resulting microstructural changes within and around irradiated tumors are unknown. We retrospectively applied Diffusion-Tensor-Imaging (DTI) and Free-Water-Imaging (FWI) on diffusion-weighted Magnetic Resonance Imaging (dMRI) data to monitor microstructural changes during-PBT and after 8 months, in a pilocytic astrocytoma (PA) and normal-appearing white matter (NAWM).MethodsWe evaluated conventional MRI and dMRI-derived indices from six MRI sessions in a child with a hypothalamic PA: at baseline (t0), during-PBT (t1-t4), and after 8 months (t5). Tumor voxels were classified as “solid” or “fluid” based on FWI.ResultsWhile during PBT tumor volume remained stable, dMRI analyses identified two different response patterns: i) an increase in fluid content and diffusivity with anisotropy reductions in solid voxels at t1, followed by ii) smaller variations in fluid content but higher anisotropy in solid voxels at t2-t4. At follow-up (t5), tumor volume, its fluid content, and diffusivity in solid voxels increased. NAWM showed dose-dependent microstructural changes.ConclusionsThe use of dMRI and FWI showed complex dynamic microstructural changes in the irradiated mass during PBT and at follow-up, opening new avenues in our understanding of radiation-induced pathophysiologic mechanisms in tumor and surrounding tissues.

Explorations of the relation between brain anatomy and functional connections in the brain are crucial for shedding more light on network connectivity that sustains brain communication. In this study, by means of an integrative approach, we examined both the structural and functional connections of the default mode network (DMN) in a group of sixteen healthy subjects. For each subject, the DMN was extracted from the structural and functional resonance imaging data; the areas that were part of the DMN were defined as the regions of interest. Then, the target network was structurally explored by diffusion-weighted imaging, tested by neurophysiological means, and retested by means of concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG). A series of correlational analyses were performed to explore the relationship between the amplitude of early-latency TMS-evoked potentials and the indexes of structural connectivity (weighted number of fibres and fractional anisotropy). Stimulation of the left or right parietal nodes of the DMN-induced activation in the contralateral parietal and frontocentral electrodes within 60 ms; this activation correlated with fractional anisotropy measures of the corpus callosum. These results showed that distant secondary activations after target stimulation can be predicted based on the target’s anatomical connections. Interestingly, structural features of the corpus callosum predicted the activation of the directly connected nodes, i.e., parietal-parietal nodes, and of the broader DMN network, i.e., parietal-frontal nodes, as identified with functional magnetic resonance imaging. Our results suggested that the proposed integrated approach would allow us to describe the contributory causal relationship between structural connectivity and functional connectivity of the DMN.

Background Patterns of coordinated variations of gray matter (GM) morphology across individuals are promising indicators of disease. However, it remains unclear if they can help characterize first-episode psychosis (FEP) and symptoms’ severity. Methods Sixty-seven FEP and 67 matched healthy controls (HC) were assessed with structural MRI to evaluate the existence of distributed GM structural covariance patterns associated to brain areas belonging to salience network. Voxel-based morphometry (VBM) and structural covariance differences, investigated with salience network seed-based Partial Least Square, were applied to explore differences between groups. GM density associations with Raven's intelligent quotient (IQ) and Positive and Negative Syndrome Scale (PANSS) scores were investigated. Results Univariate VBM results gave trend without significant GM differences across groups. GM and IQ correlated positively in both groups: in FEP, mostly in hippocampus, insula, and fronto-temporal structures, while in HC mostly in amygdala, thalamus and fronto-temporal regions. GM and PANSS scores correlated negatively in FEP, with widespread clusters located in limbic regions. Multivariate analysis showed strong and opposite structural GM covariance with salience network for FEP and HC. Moreover, structural covariance of the salience network in FEP correlated negatively with severity of clinical symptoms. Conclusion Our study provides evidence supporting the insular dysfunction model of psychosis. Reduced structural GM covariance of the salience network, with its association to symptom's severity, appears a promising morphometry feature for FEP detection.

BACKGROUND Head motion during brain structural MRI scans biases brain morphometry measurements but quantitative retrospective methods estimating head motion from structural MRI have not been evaluated. PURPOSE To verify the hypothesis that two metrics retrospectively computed from MR images: 1) average edge strength (AES, reduced with image blurring) and 2) entropy (ENT, increased with blurring and ringing artifacts) could be sensitive to in-scanner head motion during acquisition of T1 -weighted MR images. STUDY TYPE Retrospective. POPULATION/SUBJECTS/PHANTOM/SPECIMEN/ANIMAL MODEL In all, 83 healthy control (HC) and 120 Parkinson's disease (PD) patients. FIELD STRENGTH/SEQUENCE 3D magnetization-prepared rapid gradient-echo (MPRAGE) images at 3T. ASSESSMENT We 1) compared AES and ENT distribution between HC and PD; 2) evaluated the correlation between tremor score (TS) and AES (or ENT) in PD; and 3) investigated cortical regions showing an association between AES (or ENT) and local and network-level covariance measures of cortical thickness (CT), gray to white matter contrast (GWC) and gray matter density maps (GMx). STATISTICAL TESTS 1) Student's t-test. 2) Spearman's rank correlation. 3) General linear model and partial least square analysis. RESULTS AES, but not ENT, differentiated HC and PD (P = 0.02, HC median AES = 39.8, interquartile range = 9.8, PD median AES = 37.6, interquartile range = 8.1). In PD, AES correlated negatively with TS (ρ = -0.21, P = 0.02) and showed a significant relationship (|Z| >3, P

Head motion during brain structural MRI scans biases brain morphometry measurements but quantitative retrospective methods estimating head motion from structural MRI have not been evaluated.To verify the hypothesis that two metrics retrospectively computed from MR images: 1) average edge strength (AES, reduced with image blurring) and 2) entropy (ENT, increased with blurring and ringing artifacts) could be sensitive to in-scanner head motion during acquisition of TRetrospective.In all, 83 healthy control (HC) and 120 Parkinson's disease (PD) patients.3D magnetization-prepared rapid gradient-echo (MPRAGE) images at 3T.We 1) compared AES and ENT distribution between HC and PD; 2) evaluated the correlation between tremor score (TS) and AES (or ENT) in PD; and 3) investigated cortical regions showing an association between AES (or ENT) and local and network-level covariance measures of cortical thickness (CT), gray to white matter contrast (GWC) and gray matter density maps (GMx).1) Student's t-test. 2) Spearman's rank correlation. 3) General linear model and partial least square analysis.AES, but not ENT, differentiated HC and PD (P = 0.02, HC median AES = 39.8, interquartile range = 9.8, PD median AES = 37.6, interquartile range = 8.1). In PD, AES correlated negatively with TS (ρ = -0.21, P = 0.02) and showed a significant relationship (|Z|3, P 0.001) with structural covariance of CT and GWC in 54 out of 68 cortical regions.In clinical populations prone to head motion, AES can provide a reliable retrospective index of motion during structural scans, identifying brain areas whose morphometric measures covary with motion.3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:927-937.

OBJECTIVEResting-state functional MRI (rs-fMRI) represents a promising and cost-effective alternative to task-based fMRI for presurgical mapping. However, the lack of clinically streamlined and reliable rs-fMRI analysis tools has prevented wide adoption of this technique. In this work, the authors introduce an rs-fMRI processing pipeline (ReStNeuMap) for automatic single-patient rs-fMRI network analysis.METHODSThe authors provide a description of the rs-fMRI network analysis steps implemented in ReStNeuMap and report their initial experience with this tool after performing presurgical mapping in 6 patients. They verified the spatial agreement between rs-fMRI networks derived by ReStNeuMap and localization of activation with intraoperative direct electrical stimulation (DES).RESULTSThe authors automatically extracted rs-fMRI networks including eloquent cortex in spatial proximity with the resected lesion in all patients. The distance between DES points and corresponding rs-fMRI networks was less than 1 cm in 78% of cases for motor, 100% of cases for visual, 87.5% of cases for language, and 100% of cases for speech articulation mapping.CONCLUSIONSThe authors’ initial experience with ReStNeuMap showed good spatial agreement between presurgical rs-fMRI predictions and DES findings during awake surgery. The availability of the rs-fMRI analysis tools for clinicians aiming to perform noninvasive mapping of brain functional networks may extend its application beyond surgical practice.

BACKGROUND AND PURPOSE To determine whether lesion to activation distance (LAD) on presurgical blood-oxygen-level-dependent functional magnetic resonance imaging (fMRI) and degree of white matter involvement by primary or metastatic brain lesions predict perioperative motor and language deficits. METHODS We retrospectively evaluated 76 patients with intra-axial brain lesions referred for presurgical fMRI and diffusion tensor imaging (DTI). We measured expressive, receptive, global language and motor LAD and assessed degree of involvement of the corticospinal tract (CST) and the superior longitudinal fasciculus (SLF). We performed a Wilcoxon rank-sum test to determine whether the LAD and the degree of CST/SLF involvement were statistically significantly different between patients with and without preoperative or postoperative neurological deficits. RESULTS In preoperatively symptomatic patients, motor and expressive language LAD were significantly lower (z = –3.78, P = .0002, and z = –2.51, P = .01, respectively) than in asymptomatic patients. No significant difference was noted in LAD between postoperative symptomatic and asymptomatic patients, except for a trend level effect for motor LAD (P = .07). The degree of CST involvement was significantly different between symptomatic and asymptomatic patients (z = 3.40, P = .0007 and z = 2.97, P = .003, respectively, for pre- and postoperative motor deficits).The degree of SLF involvement was significantly different between preoperatively (but not postoperatively) symptomatic and asymptomatic patients (z = 2.85, P = .004). CONCLUSION Presurgical motor and expressive language LAD as well as degree of tract involvement on DTI are predictive of preoperative but not postoperative deficits, except for CST DTI and (trend level) motor LAD; inability of language LAD to predict postoperative deficits suggests that preoperative fMRI is valuable to neurosurgeons in avoiding resection of eloquent cortex.

Purpose To evaluate how retrospective head motion correction strategies affect the estimation of scalar metrics commonly used in clinical diffusion tensor imaging (DTI) studies along with their across-session reproducibility errors. Materials and Methods Fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD) and their respective across-session reproducibility errors were measured on a 4T test–retest dataset of healthy participants using five processing pipelines. These differed in: 1) the number of b0 volumes used for motion correction reference (one or five); 2) the estimations of the gradient matrix rotation (based on 6 or 12 degrees of freedom derived from coregistration); and 3) the software packages used (FSL or DTIPrep). Biases and reproducibility were evaluated in three regions of interest (ROIs) (bilateral arcuate fasciculi, cingula, and the corpus callosum) and also at the full brain level with tract based skeleton images. Results Preprocessing choices affected DTI measures and their reproducibility. The DTIPrep pipeline exhibited higher DTI metrics: FA/MD and AD (P

In this review, limitations affecting the results of presurgical mapping with blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) are discussed. There is a great need to standardize fMRI acquisition and analysis methods and establish guidelines to address quality control issues. Several national and international organizations are formulating guidelines and standards for both clinical and research applications of BOLD fMRI. Consensus regarding management of these issues will likely both improve the clinical standard of care and enhance future research applications of fMRI.

An outstanding issue in graph-based analysis of resting-state functional MRI is choice of network nodes. Individual consideration of entire brain voxels may represent a less biased approach than parcellating the cortex according to pre-determined atlases, but entails establishing connectedness for 1(9)-1(11) links, with often prohibitive computational cost. Using a representative Human Connectome Project dataset, we show that, following appropriate time-series normalization, it may be possible to accelerate connectivity determination replacing Pearson correlation with l1-norm. Even though the adjacency matrices derived from correlation coefficients and l1-norms are not identical, their similarity is high. Further, we describe and provide in full an example vector hardware implementation of l1-norm on an array of 4096 zero instruction-set processors. Calculation times

Purpose (i) to validate blood oxygenation level dependent (BOLD) breathhold cerebrovascular reactivity (BH CVR) mapping as an effective technique for potential detection of neurovascular uncoupling (NVU) in a cohort of patients with perirolandic low grade gliomas undergoing presurgical functional MRI (fMRI) for sensorimotor mapping, and (ii) to determine whether NVU potential, as assessed by BH CVR mapping, is prevalent in this tumor group. Materials and Methods We retrospectively evaluated 12 patients, with histological diagnosis of grade II glioma, who performed multiple motor tasks and a BH task. Sensorimotor activation maps and BH CVR maps were compared in two automatically defined regions of interest (ROIs), ipsilateral to the lesion (i.e., ipsilesional) and contralateral to the lesion (i.e., contralesional). Results Motor task mean T-value was significantly higher in the contralesional ROIs (6.00 ± 1.74 versus 4.34 ± 1.68; P = 0.00004) as well as the BH mean T-value (4.74 ± 2.30 versus 4.09 ± 2.50; P = 0.009). The number of active voxels was significantly higher in the contralesional ROIs (Z = 2.99; P = 0.03). Actual NVU prevalence was 75%. Conclusion Presurgical sensorimotor fMRI mapping can be affected by NVU-related false negative activation in low grade gliomas (76% of analyzed tasks). J. Magn. Reson. Imaging 2014;40:383–390. © 2013 Wiley Periodicals, Inc.

The aim of this study was to compare the relative effectiveness of 6 different commonly used language fMRI activation paradigms, including receptive and expressive, as well as semantic and phonological tasks, for hemispheric lateralization in brain tumor patients utilizing both threshold-dependent and threshold-independent approaches. We studied 46 right-handed patients with primary intra-axial brain tumors with BOLD fMRI on a 3-T MRI system. A linear fit of the laterality indices (LIs) as a function of the t-value (which varied from 2.0 to 6.5) was calculated and the slope (M) taken as measure of LI variability in the threshold-dependent LI approach; for the threshold-independent approach, the LIs were determined by comparing the integrated T-score weighted distributions of all positively task-correlated voxels of the left and the right hemispheric regions of interest. We demonstrated that silent word generation (SWG) and rhyming (R) were the two expressive tasks that provided the best hemispheric language lateralization in this group, based on concordant threshold-dependent and threshold-independent analyses. Furthermore, R (mean LI value = 61.91, M = 7.9 ± 1.5) had a higher mean LI value and was less threshold-dependent than SWG (mean LI = 52.97, M = 11.40 ± 0.64) for LI determination. SWG and R were able to provide effective language lateralization even in the subgroup of patients with lesions located in the left hemisphere and in the frontal or parietal lobes. The receptive language paradigms examined in this study (passive listening [PL], listening comprehension [LC], and reading comprehension [RC]) were less effective than SWG and R for language lateralization.

The development of new MRI techniques in the last two decades has provided neuroradiologists and neurosurgeons with additional noninvasive imaging tools for management and treatment of brain tumors. When coupled with standard structural MR sequences in imaging brain tumors, Blood Oxygenation Level Dependent (BOLD) functional MRI (fMRI), Perfusion Weighted Imaging (PWI) and Diffusion Tensor Imaging (DTI) provide additional physiologic information that is very useful for differential diagnosis, presurgical planning and prognosis. In this review after a brief technical description of BOLD fMRI, PWI and DTI, studies are described from the literature that have extensively validated these imaging techniques in comparison with invasive “gold standard” techniques such as intraoperative electrical cortical and subcortical stimulation mapping or biopsy. Additional studies are mentioned that demonstrate the positive impact of BOLD fMRI, PWI and DTI on brain tumor treatment and clinical outcome. In the final section an interesting clinical case treated at our institution is presented that highlights the clinical utility of this integrated physiologic brain tumor imaging approach.

To evaluate how retrospective head motion correction strategies affect the estimation of scalar metrics commonly used in clinical diffusion tensor imaging (DTI) studies along with their across-session reproducibility errors.Fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD) and their respective across-session reproducibility errors were measured on a 4T test-retest dataset of healthy participants using five processing pipelines. These differed in: 1) the number of b0 volumes used for motion correction reference (one or five); 2) the estimations of the gradient matrix rotation (based on 6 or 12 degrees of freedom derived from coregistration); and 3) the software packages used (FSL or DTIPrep). Biases and reproducibility were evaluated in three regions of interest (ROIs) (bilateral arcuate fasciculi, cingula, and the corpus callosum) and also at the full brain level with tract based skeleton images.Preprocessing choices affected DTI measures and their reproducibility. The DTIPrep pipeline exhibited higher DTI metrics: FA/MD and AD (P 0.05) relative to FSL pipelines both at the ROI and full brain level, and lower RD estimates (P 0.05) at the ROI level. Within FSL pipelines no such effects were found (P-values ranging between 0.25 and 0.97). The DTIPrep pipeline showed the highest number of white matter skeleton voxels, with significantly higher reproducibility (P 0.001) relative to the other pipelines (tested on P 0.01 uncorrected maps).The use of an iteratively averaged b0 image as motion correction reference (as performed by DTIPrep) affects both scalar values and improves test-retest reliability relative to the other tested pipelines. These considerations are potentially relevant for data analysis in longitudinal DTI studies.

To determine whether lesion to activation distance (LAD) on presurgical blood-oxygen-level-dependent functional magnetic resonance imaging (fMRI) and degree of white matter involvement by primary or metastatic brain lesions predict perioperative motor and language deficits.We retrospectively evaluated 76 patients with intra-axial brain lesions referred for presurgical fMRI and diffusion tensor imaging (DTI). We measured expressive, receptive, global language and motor LAD and assessed degree of involvement of the corticospinal tract (CST) and the superior longitudinal fasciculus (SLF). We performed a Wilcoxon rank-sum test to determine whether the LAD and the degree of CST/SLF involvement were statistically significantly different between patients with and without preoperative or postoperative neurological deficits.In preoperatively symptomatic patients, motor and expressive language LAD were significantly lower (z = -3.78, P = .0002, and z = -2.51, P = .01, respectively) than in asymptomatic patients. No significant difference was noted in LAD between postoperative symptomatic and asymptomatic patients, except for a trend level effect for motor LAD (P = .07). The degree of CST involvement was significantly different between symptomatic and asymptomatic patients (z = 3.40, P = .0007 and z = 2.97, P = .003, respectively, for pre- and postoperative motor deficits).The degree of SLF involvement was significantly different between preoperatively (but not postoperatively) symptomatic and asymptomatic patients (z = 2.85, P = .004).Presurgical motor and expressive language LAD as well as degree of tract involvement on DTI are predictive of preoperative but not postoperative deficits, except for CST DTI and (trend level) motor LAD; inability of language LAD to predict postoperative deficits suggests that preoperative fMRI is valuable to neurosurgeons in avoiding resection of eloquent cortex.

Resting state fMRI (rs-fMRI) has recently been considered as a possible complement or alternative to task-based fMRI (tb-fMRI) for presurgical mapping. However, evidence of its usefulness remains scant, because existing studies have investigated relatively small samples and focused primarily on qualitative evaluation. The aim of this study is to investigate the clinical usefulness of rs-fMRI in the context of presurgical mapping of motor functions, and in particular to determine the degree of correspondence with tb-fMRI which, while not a gold-standard, is commonly used in preoperative setting. A group of 13 patients with lesions close to the sensorimotor cortex underwent rs-fMRI and tb-fMRI to localize the hand, foot and mouth motor areas. We assessed quantitatively the degree of correspondence between multiple rs-fMRI analyses (independent-component and seed-based analyses) and tb-fMRI, with reference to sensitivity and specificity of rs-fMRI with respect to tb-fMRI, and centre-of-mass distances. Agreement with electro-cortical stimulation (ECS) was also investigated, and a traditional map thresholding approach based on agreement between two experienced operators was compared to an automatic threshold determination method. Rs-fMRI can localize the sensorimotor cortex successfully, providing anatomical specificity for hand, foot and mouth motor subregions, in particular with seed-based analyses. Agreement with tb-fMRI was only partial and rs-fMRI tended to provide larger patterns of correlated activity. With respect to the ECS data available, rs-fMRI and tb-fMRI performed comparably, even though the shortest distance to stimulation points was observed for the latter. Notably, the results of both were on the whole robust to thresholding procedure. Localization performed by rs-fMRI is not equivalent to tb-fMRI, hence rs-fMRI cannot be considered as an outright replacement for tb-fMRI. Nevertheless, since there is significant agreement between the two techniques, rs-fMRI can be considered with caution as a potential alternative to tb-fMRI when patients are unable to perform the task.

BACKGROUND AND PURPOSE: The optimal paradigm choice for language mapping in clinical fMRI studies is challenging due to the variability in activation among different paradigms, the contribution to activation of cognitive processes other than language, and the difficulties in monitoring patient performance. In this study, we compared language localization and lateralization between 2 commonly used clinical language paradigms and 3 newly designed dual-choice semantic paradigms to define a streamlined and adequate language-mapping protocol. MATERIALS AND METHODS: Twelve healthy volunteers performed 5 language paradigms: Silent Word Generation, Sentence Completion, Visual Antonym Pair, Auditory Antonym Pair, and Noun-Verb Association. Group analysis was performed to assess statistically significant differences in fMRI percentage signal change and lateralization index among these paradigms in 5 ROIs: inferior frontal gyrus, superior frontal gyrus, middle frontal gyrus for expressive language activation, middle temporal gyrus, and superior temporal gyrus for receptive language activation. RESULTS: In the expressive ROIs, Silent Word Generation was the most robust and best lateralizing paradigm (greater percentage signal change and lateralization index than semantic paradigms at P < .01 and P < .05 levels, respectively). In the receptive region of interest, Sentence Completion and Noun-Verb Association were the most robust activators (greater percentage signal change than other paradigms, P < .01). All except Auditory Antonym Pair were good lateralizing tasks (the lateralization index was significantly lower than other paradigms, P < .05). CONCLUSIONS: The combination of Silent Word Generation and ≥1 visual semantic paradigm, such as Sentence Completion and Noun-Verb Association, is adequate to determine language localization and lateralization; Noun-Verb Association has the additional advantage of objective monitoring of patient performance.

The goal of this chapter is to provide the reader with a comprehensive review of the current applications of presurgical language mapping by Blood Oxygen Level Dependent (BOLD) functional MRI (fMRI). The first part of the chapter includes a review of the physical principles, data acquisition, and data analysis techniques of BOLD fMRI followed by an introduction to the clinical applications of functional imaging accompanied by a discussion of its limitations. In the second part, after a description of the most commonly used paradigms in clinical language fMRI, a review of the major studies available in the literature pertaining to clinical validation of fMRI for language localization and lateralization is presented, and two illustrative cases of patients treated at our institution for brain tumors involving language cortex are presented.

(i) to validate blood oxygenation level dependent (BOLD) breathhold cerebrovascular reactivity (BH CVR) mapping as an effective technique for potential detection of neurovascular uncoupling (NVU) in a cohort of patients with perirolandic low grade gliomas undergoing presurgical functional MRI (fMRI) for sensorimotor mapping, and (ii) to determine whether NVU potential, as assessed by BH CVR mapping, is prevalent in this tumor group.We retrospectively evaluated 12 patients, with histological diagnosis of grade II glioma, who performed multiple motor tasks and a BH task. Sensorimotor activation maps and BH CVR maps were compared in two automatically defined regions of interest (ROIs), ipsilateral to the lesion (i.e., ipsilesional) and contralateral to the lesion (i.e., contralesional).Motor task mean T-value was significantly higher in the contralesional ROIs (6.00 ± 1.74 versus 4.34 ± 1.68; P = 0.00004) as well as the BH mean T-value (4.74 ± 2.30 versus 4.09 ± 2.50; P = 0.009). The number of active voxels was significantly higher in the contralesional ROIs (Z = 2.99; P = 0.03). Actual NVU prevalence was 75%.Presurgical sensorimotor fMRI mapping can be affected by NVU-related false negative activation in low grade gliomas (76% of analyzed tasks).

Chemical exchange saturation transfer (CEST) is a magnetization transfer (MT) technique to indirectly detect pools of exchangeable protons through the water signal. CEST MRI has focused predominantly on signals from exchangeable protons downfield (higher frequency) from water in the CEST spectrum. Low power radiofrequency (RF) pulses can slowly saturate protons with minimal interference of conventional semi-solid based MT contrast (MTC). When doing so, saturation-transfer signals are revealed upfield from water, which is the frequency range of non-exchangeable aliphatic and olefinic protons. The visibility of such signals indicates the presence of a relayed transfer mechanism to the water signal, while their finite width reflects that these signals are likely due to mobile solutes. It is shown here in protein phantoms and the human brain that these signals build up slower than conventional CEST, at a rate typical for intramolecular nuclear Overhauser enhancement (NOE) effects in mobile macromolecules such as proteins/peptides and lipids. These NOE-based saturation transfer signals show a pH dependence, suggesting that this process is the inverse of the well-known exchange-relayed NOEs in high resolution NMR protein studies, thus an relayed-NOE CEST process. When studying 6 normal volunteers with a low-power pulsed CEST approach, the relayed-NOE CEST effect was about twice as large as the CEST effects downfield and larger in white matter than gray matter. This NOE contrast upfield from water provides a way to study mobile macromolecules in tissue. First data on a tumor patient show reduction in both relayed NOE and CEST amide proton signals leading to an increase in magnetization transfer ratio asymmetry, providing insight into previously reported amide proton transfer (APT) effects in tumors.

The coupling mechanism between neuronal firing and cerebrovascular dilatation can be significantly compromised in cerebral diseases, making it difficult to identify eloquent cortical areas near or within resectable lesions by using Blood Oxygen Level Dependent (BOLD) fMRI. Several metabolic and vascular factors have been considered to account for this lesion-induced neurovascular uncoupling (NVU), but no imaging gold standard exists currently for the detection of NVU. However, it is critical in clinical fMRI studies to evaluate the risk of NVU because the presence of NVU may result in false negative activation that may result in inadvertent resection of eloquent cortex, resulting in permanent postoperative neurologic deficits. Although NVU results from a disruption of one or more components of a complex cellular and chemical neurovascular coupling cascade (NCC) MR imaging is only able to evaluate the final step in this NCC involving the ultimate cerebrovascular response. Since anything that impairs cerebrovascular reactivity (CVR) will necessarily result in NVU, regardless of its effect more proximally along the NCC, we can consider mapping of CVR as a surrogate marker of NVU potential. We hypothesized that BOLD breath-hold (BH) CVR mapping can serve as a better marker of NVU potential than T2* Dynamic Susceptibility Contrast gadolinium perfusion MR imaging, because the latter is known to only reflect NVU risk associated with high grade gliomas by determining elevated relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) related to tumor angiogenesis. However, since low and intermediate grade gliomas are not associated with such tumoral hyperperfusion, BOLD BH CVR mapping may be able to detect such NVU potential even in lower grade gliomas without angiogenesis, which is the hallmark of glioblastomas. However, it is also known that glioblastomas are associated with variable NVU, since angiogenesis may not always result in NVU. Perfusion metrics obtained by T2* gadolinium perfusion MR imaging were compared to BOLD percentage signal change on BH CVR maps in a group of 19 patients with intracranial brain tumors of different nature and grade. Single pixel maximum rCBV and rCBF within holotumoral regions of interest (i.e., "ipsilesional" ROIs) were normalized to contralateral hemispheric homologous (i.e., "contralesional") normal tissue. Furthermore, percentage signal change on BH CVR maps within ipsilesional ROIs were normalized to the percentage signal change within contralesional homologous ROIs. Inverse linear correlation was found between normalized rCBF (r(flow)) or rCBV (r(vol)) and normalized CVR percentage signal change (r(CVR)) in grade IV lesions. In the grade III lesions a less steep inverse linear trend was seen that did not reach statistical significance, whereas no correlation at all was seen in the grade II group. Statistically significant difference was present for r(flow) and r(vol) between the grade II and IV groups and between the grade III and IV groups but not for r(CVR). The r(CVR) was significantly lower than 1 in every group. Our results demonstrate that while T2*MR perfusion maps and CVR maps are both adequate to map tumoral regions at risk of NVU in high grade gliomas, CVR maps can detect areas of decreased CVR also in low and intermediate grade gliomas where NVU may be caused by factors other than tumor neovascularity alone. Comparison of areas of abnormally decreased regional CVR with areas of absent BOLD task-based activation in expected eloquent cortical regions infiltrated by or adjacent to the tumors revealed overall 95% concordance, thus confirming the capability of BH CVR mapping to effectively demonstrate areas of NVU. ed by factors other than tumor neovascularity alone. Comparison of areas of abnormally decreased regional CVR with areas of absent BOLD task-based activation in expected eloquent cortical regions infiltrated by or adjacent to the tumors revealed overall 95% concordance, thus confirming the capability of BH CVR mapping to effectively demonstrate areas of NVU.

This chapter discusses how the combination of blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) can be used for presurgical mapping of brain lesions such as brain tumors. The need to map both eloquent cortex and eloquent white matter in a complementary manner will be stressed. Both the underlying physical principles and the clinical applications of BOLD fMRI and DTI will be explained in detail with inclusion of several clinical examples that illustrate how the integration of these techniques is practically utilized.

AIM: To evaluate neurovascular uncoupling (NVU) associated with low grade gliomas (LGG) using blood oxygen level dependent (BOLD) cerebrovascular reactivity mapping. METHODS: Seven patients with low grade gliomas referred by neurosurgeons for presurgical mapping were included in this pilot study. Cerebrovascular reactivity (CVR) mapping was performed by acquiring BOLD images while patients performed a block-design breath-hold (BH) hypercapnia task. CVR mapping was expressed as BOLD percentage signal change (PSC) from baseline associated with performance of the BH hypercapnia task. Standard T2* Dynamic Susceptibility Contrast perfusion imaging was performed and relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) maps were generated. Structural T1 weighted MR images were also acquired. A correlation analysis between intratumoral normalized (via ratio with contralateral homologous regions) BOLD BH PSC [referred to as (nCVR)] and intratumoral normalized resting state rCBV (rCBF) values (i.e., nCBV and nCBF, respectively) was performed. RESULTS: No significant correlation was seen between the normalized BOLD BH PSC (i.e., nCBV) and nCBV or nCBF. However, the average nCVR (median = 0.50, z = -2.28, P = 0.01) was significantly less than 1.0, indicating abnormally reduced vascular responses in the tumor regions relative to normal contralesional homologous regions, whereas the average nCBV (median = 0.94, z = -0.92, P = 0.375) and nCBF (median = 0.93, z = -1.16, P = 0.25) were not significantly higher or lower than 1.0, indicating iso-perfusion in the tumor regions relative to normal contralesional homologous regions. These find ings suggest that in LGG, hyperperfusion that is seen in high grade gliomas is not present, but, nevertheless, abnormally decreased regional CVR is present within and adjacent to LGG. Since the patients all demonstrated at least some residual function attributable to the cortical regions of impaired CVR, but were incapable of producing a BOLD response in these regions regardless of the tasks performed, such regionally decreased CVR is indicative of NVU. The low nCVR ratios indicate high prevalence of NVU in this LGG cohort, which is an important consideration in the interpretation of clinical presurgical mapping with functional magnetic resonance (MR) imaging. CONCLUSION: Our preliminary study shows that BH CVR mapping is clinically feasible and demonstrates an unexpectedly high prevalence of NVU in patients with LGG.