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Stadlbauer A, Kinfe TM, Zimmermann M, Eyüpoglu I, Brandner N, Buchfelder M, Zaiss M, Dörfler A, Brandner S. Association between tissue hypoxia, perfusion restrictions, and microvascular architecture alterations with lesion-induced impairment of neurovascular coupling. J Cereb Blood Flow Metab 2022; 42:526-539. [PMID: 32787542 PMCID: PMC8985434 DOI: 10.1177/0271678x20947546] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Functional magnetic resonance imaging (fMRI) has been mainly utilized for the preoperative localization of eloquent cortical areas. However, lesion-induced impairment of neurovascular coupling (NVC) in the lesion border zone may lead to false-negative fMRI results. The purpose of this study was to determine physiological factors impacting the NVC. Twenty patients suffering from brain lesions were preoperatively examined using multimodal neuroimaging including fMRI, magnetoencephalography (MEG) during language or sensorimotor tasks (depending on lesion location), and a novel physiologic MRI approach for the combined quantification of oxygen metabolism, perfusion state, and microvascular architecture. Congruence of brain activity patterns between fMRI and MEG were found in 13 patients. In contrast, we observed missing fMRI activity in perilesional cortex that demonstrated MEG activity in seven patients, which was interpreted as lesion-induced impairment of NVC. In these brain regions with impaired NVC, physiologic MRI revealed significant brain tissue hypoxia, as well as significantly decreased macro- and microvascular perfusion and microvascular architecture. We demonstrated that perilesional hypoxia with reduced vascular perfusion and architecture is associated with lesion-induced impairment of NVC. Our physiologic MRI approach is a clinically applicable method for preoperative risk assessment for the presence of false-negative fMRI results and may prevent severe postoperative functional deficits.
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Affiliation(s)
- Andreas Stadlbauer
- Department of Neurosurgery, Friedrich-Alexander University (FAU) of Erlangen-Nürnberg, Erlangen, Germany.,Institute of Medical Radiology, University Clinic of St. Pölten, St. Pölten, Austria
| | - Thomas M Kinfe
- Department of Neurosurgery, Friedrich-Alexander University (FAU) of Erlangen-Nürnberg, Erlangen, Germany.,Division of Functional Neurosurgery and Stereotaxy, Friedrich-Alexander University (FAU) of Erlangen-Nürnberg, Erlangen, Germany
| | - Max Zimmermann
- Department of Neurosurgery, Friedrich-Alexander University (FAU) of Erlangen-Nürnberg, Erlangen, Germany.,Department of Preclinical Imaging and Radiopharmacy, University of Tübingen, Tübingen, Germany
| | - Ilker Eyüpoglu
- Department of Neurosurgery, Friedrich-Alexander University (FAU) of Erlangen-Nürnberg, Erlangen, Germany
| | - Nadja Brandner
- Department of Neurosurgery, Friedrich-Alexander University (FAU) of Erlangen-Nürnberg, Erlangen, Germany
| | - Michael Buchfelder
- Department of Neurosurgery, Friedrich-Alexander University (FAU) of Erlangen-Nürnberg, Erlangen, Germany
| | - Moritz Zaiss
- Department of Neuroradiology, Friedrich-Alexander University of Erlangen-Nürnberg, Erlangen, Germany
| | - Arnd Dörfler
- Department of Neuroradiology, Friedrich-Alexander University of Erlangen-Nürnberg, Erlangen, Germany
| | - Sebastian Brandner
- Department of Neurosurgery, Friedrich-Alexander University (FAU) of Erlangen-Nürnberg, Erlangen, Germany
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Trattnig S, Springer E, Bogner W, Hangel G, Strasser B, Dymerska B, Cardoso PL, Robinson SD. Key clinical benefits of neuroimaging at 7T. Neuroimage 2018; 168:477-489. [PMID: 27851995 PMCID: PMC5832016 DOI: 10.1016/j.neuroimage.2016.11.031] [Citation(s) in RCA: 89] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Revised: 10/06/2016] [Accepted: 11/12/2016] [Indexed: 01/15/2023] Open
Abstract
The growing interest in ultra-high field MRI, with more than 35.000 MR examinations already performed at 7T, is related to improved clinical results with regard to morphological as well as functional and metabolic capabilities. Since the signal-to-noise ratio increases with the field strength of the MR scanner, the most evident application at 7T is to gain higher spatial resolution in the brain compared to 3T. Of specific clinical interest for neuro applications is the cerebral cortex at 7T, for the detection of changes in cortical structure, like the visualization of cortical microinfarcts and cortical plaques in Multiple Sclerosis. In imaging of the hippocampus, even subfields of the internal hippocampal anatomy and pathology may be visualized with excellent spatial resolution. Using Susceptibility Weighted Imaging, the plaque-vessel relationship and iron accumulations in Multiple Sclerosis can be visualized, which may provide a prognostic factor of disease. Vascular imaging is a highly promising field for 7T which is dealt with in a separate dedicated article in this special issue. The static and dynamic blood oxygenation level-dependent contrast also increases with the field strength, which significantly improves the accuracy of pre-surgical evaluation of vital brain areas before tumor removal. Improvement in acquisition and hardware technology have also resulted in an increasing number of MR spectroscopic imaging studies in patients at 7T. More recent parallel imaging and short-TR acquisition approaches have overcome the limitations of scan time and spatial resolution, thereby allowing imaging matrix sizes of up to 128×128. The benefits of these acquisition approaches for investigation of brain tumors and Multiple Sclerosis have been shown recently. Together, these possibilities demonstrate the feasibility and advantages of conducting routine diagnostic imaging and clinical research at 7T.
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Affiliation(s)
- Siegfried Trattnig
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria; Christian Doppler Laboratory for Clinical Molecular MRI, Vienna, Austria.
| | - Elisabeth Springer
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria; Christian Doppler Laboratory for Clinical Molecular MRI, Vienna, Austria.
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria.
| | - Gilbert Hangel
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria.
| | - Bernhard Strasser
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria.
| | - Barbara Dymerska
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria.
| | - Pedro Lima Cardoso
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria.
| | - Simon Daniel Robinson
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria.
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3
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Niendorf T, Barth M, Kober F, Trattnig S. From ultrahigh to extreme field magnetic resonance: where physics, biology and medicine meet. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2017; 29:309-11. [PMID: 27221262 DOI: 10.1007/s10334-016-0564-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Affiliation(s)
- Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrueck Center for Molecular Medicine in the Helmholtz Association, Robert Roessle Strasse 10, 13125, Berlin, Germany.
| | - Markus Barth
- Centre for Advanced Imaging, The University of Queensland, Building 57, Research Road, St Lucia, QLD, 4072, Australia
| | - Frank Kober
- Centre de Résonance Magnétique Biologique et Médicale (CRMBM), Aix-Marseille Université, CNRS UMR7339, 13385, Marseille Cedex 05, France
| | - Siegfried Trattnig
- High Field MR Center, Department of Biomedical Imaging and Image Guided Therapy, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
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Lima Cardoso P, Fischmeister FPS, Dymerska B, Geißler A, Wurnig M, Trattnig S, Beisteiner R, Robinson SD. Robust presurgical functional MRI at 7 T using response consistency. Hum Brain Mapp 2017; 38:3163-3174. [PMID: 28321965 PMCID: PMC5434844 DOI: 10.1002/hbm.23582] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2016] [Revised: 03/07/2017] [Accepted: 03/11/2017] [Indexed: 12/31/2022] Open
Abstract
Functional MRI is valuable in presurgical planning due to its non-invasive nature, repeatability, and broad availability. Using ultra-high field MRI increases the specificity and sensitivity, increasing the localization reliability and reducing scan time. Ideally, fMRI analysis for this application should identify unreliable runs and work even if the patient deviates from the prescribed task timing or if there are changes to the hemodynamic response due to pathology. In this study, a model-free analysis method-UNBIASED-based on the consistency of fMRI responses over runs was applied, to ultra-high field fMRI localizations of the hand area. Ten patients with brain tumors and epilepsy underwent 7 Tesla fMRI with multiple runs of a hand motor task in a block design. FMRI data were analyzed with the proposed approach (UNBIASED) and the conventional General Linear Model (GLM) approach. UNBIASED correctly identified and excluded fMRI runs that contained little or no activation. Generally, less motion artifact contamination was present in UNBIASED than in GLM results. Some cortical regions were identified as activated in UNBIASED but not GLM results. These were confirmed to show reproducible delayed or transient activation, which was time-locked to the task. UNBIASED is a robust approach to generating activation maps without the need for assumptions about response timing or shape. In presurgical planning, UNBIASED can complement model-based methods to aid surgeons in making prudent choices about optimal surgical access and resection margins for each patient, even if the hemodynamic response is modified by pathology. Hum Brain Mapp 38:3163-3174, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
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Affiliation(s)
- Pedro Lima Cardoso
- High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaLazarettgasse 14, A‐1090ViennaAustria
| | - Florian Ph. S. Fischmeister
- Study Group Clinical fMRI, Department of NeurologyMedical University of ViennaWähringer Gürtel 18‐20, A‐1090ViennaAustria
| | - Barbara Dymerska
- High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaLazarettgasse 14, A‐1090ViennaAustria
| | - Alexander Geißler
- Study Group Clinical fMRI, Department of NeurologyMedical University of ViennaWähringer Gürtel 18‐20, A‐1090ViennaAustria
| | - Moritz Wurnig
- Study Group Clinical fMRI, Department of NeurologyMedical University of ViennaWähringer Gürtel 18‐20, A‐1090ViennaAustria
| | - Siegfried Trattnig
- High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaLazarettgasse 14, A‐1090ViennaAustria
| | - Roland Beisteiner
- Study Group Clinical fMRI, Department of NeurologyMedical University of ViennaWähringer Gürtel 18‐20, A‐1090ViennaAustria
| | - Simon Daniel Robinson
- High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaLazarettgasse 14, A‐1090ViennaAustria
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Lima Cardoso P, Dymerska B, Bachratá B, Fischmeister FPS, Mahr N, Matt E, Trattnig S, Beisteiner R, Robinson SD. The clinical relevance of distortion correction in presurgical fMRI at 7T. Neuroimage 2016; 168:490-498. [PMID: 28027961 DOI: 10.1016/j.neuroimage.2016.12.070] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Revised: 12/21/2016] [Accepted: 12/23/2016] [Indexed: 11/19/2022] Open
Abstract
Presurgical planning with fMRI benefits from increased reliability and the possibility to reduce measurement time introduced by using ultra-high field. Echo-planar imaging suffers, however, from geometric distortions which scale with field strength and potentially give rise to clinically significant displacement of functional activation. We evaluate the effectiveness of a dynamic distortion correction (DDC) method based on unmodified single-echo EPI in the context of simulated presurgical planning fMRI at 7T and compare it with static distortion correction (SDC). The extent of distortion in EPI and activation shifts are investigated in a group of eleven patients with a range of neuropathologies who performed a motor task. The consequences of neglecting to correct images for susceptibility-induced distortions are assessed in a clinical context. It was possible to generate time series of EPI-based field maps which were free of artifacts in the eloquent brain areas relevant to presurgical fMRI, despite the presence of signal dropouts caused by pathologies and post-operative sites. Distortions of up to 5.1mm were observed in the primary motor cortex in raw EPI. These were accurately corrected with DDC and slightly less accurately with SDC. The dynamic nature of distortions in UHF clinical fMRI was demonstrated via investigation of temporal variation in voxel shift maps, confirming the potential inadequacy of SDC based on a single reference field map, particularly in the vicinity of pathologies or in the presence of motion. In two patients, the distortion correction was potentially clinically significant in that it might have affected the localization or interpretation of activation and could thereby have influenced the treatment plan. Distortion correction is shown to be effective and clinically relevant in presurgical planning at 7T.
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Affiliation(s)
- Pedro Lima Cardoso
- High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090 Vienna, Austria.
| | - Barbara Dymerska
- High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090 Vienna, Austria.
| | - Beáta Bachratá
- High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090 Vienna, Austria.
| | - Florian Ph S Fischmeister
- High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090 Vienna, Austria; Study Group Clinical fMRI, Department of Neurology, Medical University of Vienna, Währinger Gürtel 18-20, A-1090 Vienna, Austria.
| | - Nina Mahr
- High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090 Vienna, Austria; Study Group Clinical fMRI, Department of Neurology, Medical University of Vienna, Währinger Gürtel 18-20, A-1090 Vienna, Austria.
| | - Eva Matt
- High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090 Vienna, Austria; Study Group Clinical fMRI, Department of Neurology, Medical University of Vienna, Währinger Gürtel 18-20, A-1090 Vienna, Austria.
| | - Siegfried Trattnig
- High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090 Vienna, Austria.
| | - Roland Beisteiner
- High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090 Vienna, Austria; Study Group Clinical fMRI, Department of Neurology, Medical University of Vienna, Währinger Gürtel 18-20, A-1090 Vienna, Austria.
| | - Simon Daniel Robinson
- High Field Magnetic Resonance Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090 Vienna, Austria.
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Task-Related Edge Density (TED)-A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain. PLoS One 2016; 11:e0158185. [PMID: 27341204 PMCID: PMC4920409 DOI: 10.1371/journal.pone.0158185] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2016] [Accepted: 06/10/2016] [Indexed: 12/22/2022] Open
Abstract
The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach "Task-related Edge Density" (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function.
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