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Iannotti GR, Nadin I, Ivanova V, Tourdot Q, Lascano AM, Momjian S, Schaller KL, Lovblad KO, Grouiller F. Specificity of Quantitative Functional Brain Mapping with Arterial Spin-Labeling for Preoperative Assessment. AJNR Am J Neuroradiol 2023; 44:1302-1308. [PMID: 37857448 PMCID: PMC10631521 DOI: 10.3174/ajnr.a8006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 08/28/2023] [Indexed: 10/21/2023]
Abstract
BACKGROUND AND PURPOSE Arterial spin-labeling is a noninvasive MR imaging technique allowing direct and quantitative measurement of brain perfusion. Arterial spin-labeling is well-established in clinics for investigating the overall cerebral perfusion, but it is still occasionally employed during tasks. The typical contrast for functional MR imaging is blood oxygen level-dependent (BOLD) imaging, whose specificity could be biased in neurologic patients due to altered neurovascular coupling. This work aimed to validate the use of functional ASL as a noninvasive tool for presurgical functional brain mapping. This is achieved by comparing the spatial accuracy of functional ASL with transcranial magnetic stimulation as the criterion standard. MATERIALS AND METHODS Twenty-eight healthy participants executed a motor task and received a somatosensory stimulation, while BOLD imaging and arterial spin-labeling were acquired simultaneously. Transcranial magnetic stimulation was subsequently used to define hand somatotopy. RESULTS Functional ASL was found more adjacent to transcranial magnetic stimulation than BOLD imaging, with a significant shift along the inferior-to-superior direction. With respect to BOLD imaging, functional ASL was localized significantly more laterally, anteriorly, and inferiorly during motor tasks and pneumatic stimulation. CONCLUSIONS Our results confirm the specificity of functional ASL in targeting the regional neuronal excitability. Functional ASL could be considered as a valid supplementary technique to BOLD imaging for presurgical mapping when spatial accuracy is crucial for delineating eloquent cortex.
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Affiliation(s)
- Giannina R Iannotti
- From the Division of Neuroradiology, Diagnostic Department (G.R.I., K.O.L.), Geneva University Hospitals and University of Geneva, Geneva, Switzerland
- Department of Neurosurgery (G.R.I., I.N., V.I., S.M., K.L.S.), Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Isaure Nadin
- Department of Neurosurgery (G.R.I., I.N., V.I., S.M., K.L.S.), Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Vladimira Ivanova
- Department of Neurosurgery (G.R.I., I.N., V.I., S.M., K.L.S.), Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Quentin Tourdot
- Faculty of Pharmacy (Q.T.), University of Montpellier, Montpellier, France
| | - Agustina M Lascano
- Division of Neurology (A.M.L.), Department of Clinical Neuroscience, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Shahan Momjian
- Department of Neurosurgery (G.R.I., I.N., V.I., S.M., K.L.S.), Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Karl L Schaller
- Department of Neurosurgery (G.R.I., I.N., V.I., S.M., K.L.S.), Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Karl O Lovblad
- From the Division of Neuroradiology, Diagnostic Department (G.R.I., K.O.L.), Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Frederic Grouiller
- Swiss Centre for Affective Sciences (F.G.), University of Geneva, Geneva, Switzerland
- Center for Biomedical Imaging (F.G.), MRI University of Geneva Cognitive and Affective Neuroimaging Section, Geneva, Switzerland
- Laboratory of Neurology and Imaging of Cognition (F.G.), Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland
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Paschoal AM, da Silva PHR, Rondinoni C, Arrigo IV, Paiva FF, Leoni RF. Semantic verbal fluency brain network: delineating a physiological basis for the functional hubs using dual-echo ASL and graph theory approach. J Neural Eng 2021; 18. [PMID: 34087805 DOI: 10.1088/1741-2552/ac0864] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Accepted: 06/04/2021] [Indexed: 01/07/2023]
Abstract
Objective. Semantic verbal fluency (SFV) is a cognitive process that engages and modulates specific brain areas related to language comprehension and production, decision making, response inhibition, and memory retrieval. The impairment of the brain network responsible for these functions is related to various neurological conditions, and different strategies have been proposed to assess SVF-related deficits in such diseases. In the present study, the concomitant changes of brain perfusion and functional connectivity were investigated during the resting state and SVF task performance.Approach. Arterial spin labeling (ASL), a perfusion-based magnetic resonance imaging (MRI) method, was used with a pseudocontinuous labeling approach and dual-echo readout in 28 healthy right-handed Brazilian Portuguese speakers. The acquisition was performed in a resting state condition and during the performance of a SVF task.Main results. During task performance, a significant increase in cerebral blood flow (CBF) was observed in language-related regions of the frontal lobe, including Brodmann's areas 6, 9, 45, and 47, associated with semantic processing, word retrieval, and speech motor programming. Such regions, along with the posterior cingulate, showed a crucial role in the SVF functional network, assessed by seed-to-voxel and graph analysis. Our approach successfully overcame the generalization problem regarding functional MRI (fMRI) graph analysis with cognitive, task-based paradigms. Moreover, the CBF maps enabled the functional assessment of orbital frontal and temporal regions commonly affected by magnetic susceptibility artifacts in conventional T2*-weighted fMRI approaches.Significance. Our results demonstrated the capability of ASL to evaluate perfusion alterations and functional patterns simultaneously regarding the SVF network providing a quantitative physiological basis to functional hubs in this network, which may support future clinical studies.
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Affiliation(s)
- André Monteiro Paschoal
- LIM44, Instituto e Departamento de Radiologia, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil.,Inbrain Lab, Department of Physics, FFCLRP, University of Sao Paulo, Ribeirao Preto, Brazil
| | | | - Carlo Rondinoni
- Inbrain Lab, Department of Physics, FFCLRP, University of Sao Paulo, Ribeirao Preto, Brazil
| | | | | | - Renata Ferranti Leoni
- Inbrain Lab, Department of Physics, FFCLRP, University of Sao Paulo, Ribeirao Preto, Brazil
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De Blasi B, Caciagli L, Storti SF, Galovic M, Koepp M, Menegaz G, Barnes A, Galazzo IB. Noise removal in resting-state and task fMRI: functional connectivity and activation maps. J Neural Eng 2020; 17:046040. [PMID: 32663803 DOI: 10.1088/1741-2552/aba5cc] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Blood-oxygenated-level dependent (BOLD)-based functional magnetic resonance imaging (fMRI) is a widely used non-invasive tool for mapping brain function and connectivity. However, the BOLD signal is highly affected by non-neuronal contributions arising from head motion, physiological noise and scanner artefacts. Therefore, it is necessary to recover the signal of interest from the other noise-related fluctuations to obtain reliable functional connectivity (FC) results. Several pre-processing pipelines have been developed, mainly based on nuisance regression and independent component analysis (ICA). The aim of this work was to investigate the impact of seven widely used denoising methods on both resting-state and task fMRI. APPROACH Task fMRI can provide some ground truth given that the task administered has well established brain activations. The resulting cleaned data were compared using a wide range of measures: motion evaluation and data quality, resting-state networks and task activations, FC. MAIN RESULTS Improved signal quality and reduced motion artefacts were obtained with all advanced pipelines, compared to the minimally pre-processed data. Larger variability was observed in the case of brain activation and FC estimates, with ICA-based pipelines generally achieving more reliable and accurate results. SIGNIFICANCE This work provides an evidence-based reference for investigators to choose the most appropriate method for their study and data.
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Affiliation(s)
- Bianca De Blasi
- Department of Medical Physics and Bioengineering, University College London, London, United Kingdom. Author to whom any correspondence should be addressed
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Boscolo Galazzo I, Storti SF, Barnes A, De Blasi B, De Vita E, Koepp M, Duncan JS, Groves A, Pizzini FB, Menegaz G, Fraioli F. Arterial Spin Labeling Reveals Disrupted Brain Networks and Functional Connectivity in Drug-Resistant Temporal Epilepsy. Front Neuroinform 2019; 12:101. [PMID: 30894811 PMCID: PMC6414423 DOI: 10.3389/fninf.2018.00101] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Accepted: 12/12/2018] [Indexed: 01/08/2023] Open
Abstract
Resting-state networks (RSNs) and functional connectivity (FC) have been increasingly exploited for mapping brain activity and identifying abnormalities in pathologies, including epilepsy. The majority of studies currently available are based on blood-oxygenation-level-dependent (BOLD) contrast in combination with either independent component analysis (ICA) or pairwise region of interest (ROI) correlations. Despite its success, this approach has several shortcomings as BOLD is only an indirect and non-quantitative measure of brain activity. Conversely, promising results have recently been achieved by arterial spin labeling (ASL) MRI, primarily developed to quantify brain perfusion. However, the wide application of ASL-based FC has been hampered by its complexity and relatively low robustness to noise, leaving several aspects of this approach still largely unexplored. In this study, we firstly aimed at evaluating the effect of noise reduction on spatio-temporal ASL analyses and quantifying the impact of two ad-hoc processing pipelines (basic and advanced) on connectivity measures. Once the optimal strategy had been defined, we investigated the applicability of ASL for connectivity mapping in patients with drug-resistant temporal epilepsy vs. controls (10 per group), aiming at revealing between-group voxel-wise differences in each RSN and ROI-wise FC changes. We first found ASL was able to identify the main network (DMN) along with all the others generally detected with BOLD but never previously reported from ASL. For all RSNs, ICA-based denoising (advanced pipeline) allowed to increase their similarity with the corresponding BOLD template. ASL-based RSNs were visibly consistent with literature findings; however, group differences could be identified in the structure of some networks. Indeed, statistics revealed areas of significant FC decrease in patients within different RSNs, such as DMN and cerebellum (CER), while significant increases were found in some cases, such as the visual networks. Finally, the ROI-based analyses identified several inter-hemispheric dysfunctional links (controls > patients) mainly between areas belonging to the DMN, right-left thalamus and right-left temporal lobe. Conversely, fewer connections, predominantly intra-hemispheric, showed the opposite pattern (controls < patients). All these elements provide novel insights into the pathological modulations characterizing a "network disease" as epilepsy, shading light on the importance of perfusion-based approaches for identifying the disrupted areas and communications between brain regions.
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Affiliation(s)
| | | | - Anna Barnes
- Institute of Nuclear Medicine, University College London, London, United Kingdom
| | - Bianca De Blasi
- Department of Medical Physics, University College London, London, United Kingdom
| | - Enrico De Vita
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's Health Partners, King's College London, London, United Kingdom
| | - Matthias Koepp
- Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London, United Kingdom
| | - John Sidney Duncan
- Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London, United Kingdom
| | - Ashley Groves
- Institute of Nuclear Medicine, University College London, London, United Kingdom
| | | | - Gloria Menegaz
- Department of Computer Science, University of Verona, Verona, Italy
| | - Francesco Fraioli
- Institute of Nuclear Medicine, University College London, London, United Kingdom
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