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Akinwale O, Li Y, Liu P, Hu Z, Hou X, Jiang S, Lin DD, Pillai JJ, Lu H. Blood-oxygenation-level-dependent (BOLD) MRI responses to CO 2 and O 2 inhalation in brain gliomas. Magn Reson Imaging 2025; 119:110364. [PMID: 40023408 PMCID: PMC11994284 DOI: 10.1016/j.mri.2025.110364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2024] [Revised: 02/17/2025] [Accepted: 02/26/2025] [Indexed: 03/04/2025]
Abstract
PURPOSE Cerebrovascular abnormalities are intricately involved in gliomas. While static cerebrovascular properties such as cerebral blood flow, volume, and permeability have been extensively studied, dynamic vascular parameters have not been fully understood. This study aimed to characterize the vascular responses to CO2 and O2 inhalation in brain gliomas. METHODS In 15 glioma patients, concomitant CO2 and O2 inhalation was applied while BOLD MR images were continuously acquired for nine minutes, resulting in the measurement of O2-reactivity, CO2-reactivity, and bolus arrival time (BAT). Vascular parameters were compared between the tumor regions and contralateral healthy tissue using Student t-tests. The dependence of vascular parameters on glioma grade, glioma subtypes, and molecular biomarkers were assessed using a multiple linear regression. RESULTS Visual inspection suggested that reliable O2-reactivity, CO2-reactivity, and BAT maps could be obtained in every patient. Compared to the contralateral healthy tissue, glioma regions on average revealed a diminished O2-reactivity (p < 0.001) and CO2-reactivity (p < 0.001), but a lengthened BAT (p < 0.001). Intra-tumoral heterogeneity in the vascular parameters between core and periphery was also observed. Astrocytomas had a lower CO2-reactivity (p = 0.014) and a longer BAT (p = 0.012) relative to oligodendrogliomas. Glioma grade had no association with O2-reactivity, CO2-reactivity, or BAT. Patients who lost ATRX expression had a lower CO2- and O2-reactivity (p = 0.005 and p = 0.035) compared to patients who retained ATRX expression. CONCLUSIONS Gliomas are associated with abnormal CO2- and O2-reactivity measured with MRI. These dynamic parameters may provide new insights into the vascular pathophysiology in gliomas.
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Affiliation(s)
- Oluwateniola Akinwale
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yang Li
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Peiying Liu
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Diagnostic Radiology & Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Zhiyi Hu
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Xirui Hou
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Shanshan Jiang
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Doris D Lin
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jay J Pillai
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Division of Neuroradiology, Mayo Clinic College of Medicine and Science, Rochester, MN, USA; Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Hanzhang Lu
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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Calvo‐Imirizaldu M, Solis‐Barquero S, Aramendía‐Vidaurreta V, García de Eulate R, Domínguez P, Vidorreta M, Echeveste J, Argueta A, Cacho‐Asenjo E, Martinez‐Simon A, Bejarano B, Fernández‐Seara M. Cerebrovascular Reactivity Mapping in Brain Tumors Based on a Breath-Hold Task Using Arterial Spin Labeling. NMR IN BIOMEDICINE 2025; 38:e5317. [PMID: 39844376 PMCID: PMC11754703 DOI: 10.1002/nbm.5317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Revised: 11/16/2024] [Accepted: 12/19/2024] [Indexed: 01/24/2025]
Abstract
Hemodynamic measurements such as cerebral blood flow (CBF) and cerebrovascular reactivity (CVR) can provide useful information for the diagnosis and characterization of brain tumors. Previous work showed that arterial spin labeling (ASL) in combination with vasoactive stimulation enabled simultaneous non-invasive evaluation of both parameters, however this approach had not been previously tested in tumors. The aim of this work was to investigate the application of this technique, using a pseudo-continuous ASL (PCASL) sequence combined with breath-holding at 3 T, to measure CBF and CVR in high-grade gliomas and metastatic lesions, and to explore differences across tumoral-peritumoral regions and tumor types. To that end, 27 patients with brain tumor were studied. Baseline CBF and CVR were measured in tumor, edema, and gray matter (GM) volumes-of-interest (VOIs). Peritumoral ipsilateral ring-shaped VOIs were also generated and mirrored to the contralateral hemisphere. Differences in baseline CBF and CVR were evaluated between contralateral and ipsilateral GM, contralateral and ipsilateral peritumoral rings, and among VOIs and tumor types. CBF in the tumor was higher in grade 4 gliomas than metastases. In grade 4 gliomas, edema had lower CBF than the tumor and contralateral GM. CVR values were different between grade 3 and grade 4 gliomas, and between grade 4 and metastases. CVR values in the tumor were lower compared to the contralateral GM. Differences in CVR between contralateral and ipsilateral-ring VOIs were also found in grade 4 gliomas, presumably suggesting tumor infiltration within the peritumoral tissue. A cut-off value for CVR of 27.9%-signal-change is suggested to differentiate between grade 3 and grade 4 gliomas (specificity = 83.3%, sensitivity = 70.6%). In conclusion, CBF and CVR mapping with ASL offered insights into the perilesional environment that could help to detect infiltrative disease, particularly in grade 4 gliomas. CVR emerged as a potential biomarker to differentiate between grade 3 and grade 4 gliomas.
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Affiliation(s)
| | - Sergio M. Solis‐Barquero
- Department of RadiologyClínica Universidad de NavarraPamplonaSpain
- Navarra Institute for Health Research (IdiSNA)PamplonaSpain
| | - Verónica Aramendía‐Vidaurreta
- Department of RadiologyClínica Universidad de NavarraPamplonaSpain
- Navarra Institute for Health Research (IdiSNA)PamplonaSpain
| | - Reyes García de Eulate
- Department of RadiologyClínica Universidad de NavarraPamplonaSpain
- Navarra Institute for Health Research (IdiSNA)PamplonaSpain
| | - Pablo Domínguez
- Department of RadiologyClínica Universidad de NavarraPamplonaSpain
- Navarra Institute for Health Research (IdiSNA)PamplonaSpain
| | | | | | - Allan Argueta
- Department of PathologyClínica Universidad de NavarraPamplonaSpain
| | - Elena Cacho‐Asenjo
- Navarra Institute for Health Research (IdiSNA)PamplonaSpain
- Department of Anesthesia and Intensive CareClínica Universidad de NavarraPamplonaSpain
| | - Antonio Martinez‐Simon
- Navarra Institute for Health Research (IdiSNA)PamplonaSpain
- Department of Anesthesia and Intensive CareClínica Universidad de NavarraPamplonaSpain
| | | | - María A. Fernández‐Seara
- Department of RadiologyClínica Universidad de NavarraPamplonaSpain
- Navarra Institute for Health Research (IdiSNA)PamplonaSpain
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Woods JG, Achten E, Asllani I, Bolar DS, Dai W, Detre JA, Fan AP, Fernández-Seara M, Golay X, Günther M, Guo J, Hernandez-Garcia L, Ho ML, Juttukonda MR, Lu H, MacIntosh BJ, Madhuranthakam AJ, Mutsaerts HJ, Okell TW, Parkes LM, Pinter N, Pinto J, Qin Q, Smits M, Suzuki Y, Thomas DL, Van Osch MJ, Wang DJJ, Warnert EA, Zaharchuk G, Zelaya F, Zhao M, Chappell MA. Recommendations for quantitative cerebral perfusion MRI using multi-timepoint arterial spin labeling: Acquisition, quantification, and clinical applications. Magn Reson Med 2024; 92:469-495. [PMID: 38594906 PMCID: PMC11142882 DOI: 10.1002/mrm.30091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 02/09/2024] [Accepted: 03/07/2024] [Indexed: 04/11/2024]
Abstract
Accurate assessment of cerebral perfusion is vital for understanding the hemodynamic processes involved in various neurological disorders and guiding clinical decision-making. This guidelines article provides a comprehensive overview of quantitative perfusion imaging of the brain using multi-timepoint arterial spin labeling (ASL), along with recommendations for its acquisition and quantification. A major benefit of acquiring ASL data with multiple label durations and/or post-labeling delays (PLDs) is being able to account for the effect of variable arterial transit time (ATT) on quantitative perfusion values and additionally visualize the spatial pattern of ATT itself, providing valuable clinical insights. Although multi-timepoint data can be acquired in the same scan time as single-PLD data with comparable perfusion measurement precision, its acquisition and postprocessing presents challenges beyond single-PLD ASL, impeding widespread adoption. Building upon the 2015 ASL consensus article, this work highlights the protocol distinctions specific to multi-timepoint ASL and provides robust recommendations for acquiring high-quality data. Additionally, we propose an extended quantification model based on the 2015 consensus model and discuss relevant postprocessing options to enhance the analysis of multi-timepoint ASL data. Furthermore, we review the potential clinical applications where multi-timepoint ASL is expected to offer significant benefits. This article is part of a series published by the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group, aiming to guide and inspire the advancement and utilization of ASL beyond the scope of the 2015 consensus article.
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Affiliation(s)
- Joseph G. Woods
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Center for Functional Magnetic Resonance Imaging, Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Eric Achten
- Ghent Institute for Functional and Metabolic Imaging (GIfMI), Ghent University, Ghent, Belgium
| | - Iris Asllani
- Department of Neuroscience, University of Sussex, UK and Department of Biomedical Engineering, Rochester Institute of Technology, USA
| | - Divya S. Bolar
- Center for Functional Magnetic Resonance Imaging, Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Weiying Dai
- Department of Computer Science, State University of New York at Binghamton, Binghamton, NY, USA, 13902
| | - John A. Detre
- Department of Neurology, University of Pennsylvania, 3 Dulles Building, 3400 Spruce Street, Philadelphia, PA 19104 USA
| | - Audrey P. Fan
- Department of Biomedical Engineering, Department of Neurology, University of California Davis, Davis, CA, USA
| | - Maria Fernández-Seara
- Department of Radiology, Clínica Universidad de Navarra, Pamplona, Spain; IdiSNA, Instituto de Investigación Sanitaria de Navarra, Pamplona, Spain
| | - Xavier Golay
- UCL Queen Square Institute of Neurology, University College London, London, UK; Gold Standard Phantoms, UK
| | - Matthias Günther
- Imaging Physics, Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany
- Departments of Physics and Electrical Engineering, University of Bremen, Bremen, Germany
| | - Jia Guo
- Department of Bioengineering, University of California Riverside, Riverside, CA, USA
| | | | - Mai-Lan Ho
- Department of Radiology, University of Missouri, Columbia, MO, USA. ORCID: 0000-0002-9455-1350
| | - Meher R. Juttukonda
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Hanzhang Lu
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Bradley J. MacIntosh
- Hurvitz Brain Sciences Program, Centre for Brain Resilience & Recovery, Sunnybrook Research Institute, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
- Computational Radiology & Artificial Intelligence unit, Oslo University Hospital, Oslo, Norway
| | - Ananth J. Madhuranthakam
- Department of Radiology and Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Henk-Jan Mutsaerts
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Thomas W. Okell
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Laura M. Parkes
- School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, UK
| | - Nandor Pinter
- Dent Neurologic Institute, Buffalo, New York, USA; University at Buffalo Neurosurgery, Buffalo, New York, USA
| | - Joana Pinto
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Qin Qin
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Marion Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Medical Delta, Delft, The Netherlands
- Erasmus MC Cancer Institute, Erasmus MC, Rotterdam, NL
| | - Yuriko Suzuki
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - David L. Thomas
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Matthias J.P. Van Osch
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Danny JJ Wang
- Laboratory of FMRI Technology (LOFT), Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Esther A.H. Warnert
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Erasmus MC Cancer Institute, Erasmus MC, Rotterdam, NL
| | - Greg Zaharchuk
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Fernando Zelaya
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
| | - Moss Zhao
- Department of Radiology, Stanford University, Stanford, CA, USA
- Maternal & Child Health Research Institute, Stanford University, Stanford, CA, USA
| | - Michael A. Chappell
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
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Chabert S, Salas R, Cantor E, Veloz A, Cancino A, González M, Torres F, Bennett C. Hemodynamic response function description in patients with glioma. J Neuroradiol 2024; 51:101156. [PMID: 37805126 DOI: 10.1016/j.neurad.2023.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 10/04/2023] [Accepted: 10/05/2023] [Indexed: 10/09/2023]
Abstract
INTRODUCTION Functional magnetic resonance imaging is a powerful tool that has provided many insights into cognitive sciences. Yet, as its analysis is mostly based on the knowledge of an a priori canonical hemodynamic response function (HRF), its reliability in patients' applications has been questioned. There have been reports of neurovascular uncoupling in patients with glioma, but no specific description of the Hemodynamic Response Function (HRF) in glioma has been reported so far. The aim of this work is to describe the HRF in patients with glioma. METHODS Forty patients were included. MR images were acquired on a 1.5T scanner. Activated clusters were identified using a fuzzy general linear model; HRFs were adjusted with a double-gamma function. Analyses were undertaken considering the tumor grade, age, sex, tumor location, and activated location. RESULTS Differences are found in the occipital, limbic, insular, and sub-lobar areas, but not in the frontal, temporal, and parietal lobes. The presence of a glioma slows the time-to-peak and onset times by 5.2 and 3.8 % respectively; high-grade gliomas present 8.1 % smaller HRF widths than low-grade gliomas. DISCUSSION AND CONCLUSION There is significant HRF variation due to the presence of glioma, but the magnitudes of the observed differences are small. Most processing pipelines should be robust enough for this magnitude of variation and little if any impact should be visible on functional maps. The differences that have been observed in the literature between functional mapping obtained with magnetic resonance vs. that obtained with direct electrostimulation during awake surgery are more probably due to the intrinsic difference in the mapping process: fMRI mapping detects all recruited areas while intra-surgical mapping indicates only the areas indispensable for the realization of a certain task. Surgical mapping might not be the gold standard to use when trying to validate the fMRI mapping process.
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Affiliation(s)
- Stéren Chabert
- School of Biomedical Engineering, Universidad de Valparaiso, General Cruz 222, Valparaiso, Chile; Millennium Science Initiative Intelligent Healthcare Engineering, Santiago, Chile.
| | - Rodrigo Salas
- School of Biomedical Engineering, Universidad de Valparaiso, General Cruz 222, Valparaiso, Chile; Millennium Science Initiative Intelligent Healthcare Engineering, Santiago, Chile
| | - Erika Cantor
- Institute of Statistics, Universidad de Valparaíso, Valparaíso, Chile
| | - Alejandro Veloz
- School of Biomedical Engineering, Universidad de Valparaiso, General Cruz 222, Valparaiso, Chile
| | - Astrid Cancino
- Millennium Science Initiative Intelligent Healthcare Engineering, Santiago, Chile; Doctorado en Ciencias e Ingeniería para la Salud, Universidad de Valparaiso, Valparaiso, Chile
| | - Matías González
- Neurosurgery Department, Hospital Carlos van Buren, Valparaiso, Chile
| | - Francisco Torres
- Millennium Science Initiative Intelligent Healthcare Engineering, Santiago, Chile; Radiology Department, Hospital Carlos van Buren, Valparaiso, Chile
| | - Carlos Bennett
- Neurosurgery Department, Hospital Carlos van Buren, Valparaiso, Chile
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Woodward OB, Driver I, Schwarz ST, Hart E, Wise R. Assessment of brainstem function and haemodynamics by MRI: challenges and clinical prospects. Br J Radiol 2023; 96:20220940. [PMID: 37721043 PMCID: PMC10607409 DOI: 10.1259/bjr.20220940] [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: 10/04/2022] [Revised: 04/25/2023] [Accepted: 05/24/2023] [Indexed: 09/19/2023] Open
Abstract
MRI offers techniques for non-invasively measuring a range of aspects of brain tissue function. Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) is widely used to assess neural activity, based on the brain's haemodynamic response, while arterial spin labelling (ASL) MRI is a non-invasive method of quantitatively mapping cerebral perfusion. Both techniques can be applied to measure cerebrovascular reactivity (CVR), an important marker of the health of the cerebrovascular system. BOLD, ASL and CVR have been applied to study a variety of disease processes and are already used in certain clinical circumstances. The brainstem is a critical component of the central nervous system and is implicated in a variety of disease processes. However, its function is difficult to study using MRI because of its small size and susceptibility to physiological noise. In this article, we review the physical and biological underpinnings of BOLD and ASL and their application to measure CVR, discuss the challenges associated with applying them to the brainstem and the opportunities for brainstem MRI in the research and clinical settings. With further optimisation, functional MRI techniques could feasibly be used to assess brainstem haemodynamics and neural activity in the clinical setting.
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Affiliation(s)
- Owen Bleddyn Woodward
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Ian Driver
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | | | - Emma Hart
- University of Bristol, Bristol, United Kingdom
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van Niftrik CHB, Hiller A, Sebök M, Halter M, Duffin J, Fisher JA, Mikulis DJ, Regli L, Piccirelli M, Fierstra J. Heterogeneous motor BOLD-fMRI responses in brain areas exhibiting negative BOLD cerebrovascular reactivity indicate that steal phenomenon does not always result from exhausted cerebrovascular reserve capacity. Magn Reson Imaging 2023; 103:124-130. [PMID: 37481092 DOI: 10.1016/j.mri.2023.07.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 07/11/2023] [Accepted: 07/19/2023] [Indexed: 07/24/2023]
Abstract
INTRODUCTION Brain areas exhibiting negative blood oxygenation-level dependent cerebrovascular reactivity (BOLD-CVR) responses to carbon dioxide (CO2) are thought to suffer from a completely exhausted autoregulatory cerebrovascular reserve capacity and exhibit vascular steal phenomenon. If this assumption is correct, the presence of vascular steal phenomenon should subsequently result in an equal negative fMRI signal response during a motor-task based BOLD-fMRI study (increase in metabolism without an increase in cerebral blood flow due to exhausted reserve capacity) in otherwise functional brain tissue. To investigate this premise, the aim of this study was to further investigate motor-task based BOLD-fMRI signal responses in brain areas exhibiting negative BOLD-CVR. MATERIAL AND METHODS Seventy-one datasets of patients with cerebrovascular steno-occlusive disease without motor defects, who underwent a CO2-calibrated motor task-based BOLD-fMRI study with a fingertapping paradigm and a subsequent BOLD-CVR study with a precisely controlled CO2-challenge during the same MRI examination, were included. We compared BOLD-fMRI signal responses in the bilateral pre- and postcentral gyri - i.e. Region of Interest (ROI) with the corresponding BOLD-CVR in this ROI. The ROI was determined using a second level group analysis of the BOLD-fMRI task study of 42 healthy individuals undergoing the same study protocol. RESULTS An overall decrease in BOLD-CVR was associated with a decrease in BOLD-fMRI signal response within the ROI. For patients exhibiting negative BOLD-CVR, we found both positive and negative motor-task based BOLD-fMRI signal responses. CONCLUSION We show that the presence of negative BOLD-CVR responses to CO2 is associated with heterogeneous motor task-based BOLD-fMRI signal responses, where some patients show -more presumed- negative BOLD-fMRI signal responses, while other patient showed positive BOLD-fMRI signal responses. This finding may indicate that the autoregulatory vasodilatory reserve capacity does not always need to be completely exhausted for vascular steal phenomenon to occur.
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Affiliation(s)
- Christiaan Hendrik Bas van Niftrik
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Switzerland; Clinical Neuroscience Center, University Hospital Zurich, Switzerland.
| | - Aimée Hiller
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Switzerland; Clinical Neuroscience Center, University Hospital Zurich, Switzerland; Department of Abdominal and Transplant Surgery, University Hospital Zurich, University of Zurich. Switzerland
| | - Martina Sebök
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Switzerland; Clinical Neuroscience Center, University Hospital Zurich, Switzerland
| | - Matthias Halter
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Switzerland; Clinical Neuroscience Center, University Hospital Zurich, Switzerland
| | - James Duffin
- Department of Physiology, University of Toronto, Toronto, ON, Canada
| | - Joseph A Fisher
- Department of Anesthesia and Pain Management, University Health Network, Toronto, ON, Canada.; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - David J Mikulis
- Joint Department of Medical Imaging and the Functional Neuroimaging Laboratory, University Health Network, Toronto, ON, Canada
| | - Luca Regli
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Switzerland; Clinical Neuroscience Center, University Hospital Zurich, Switzerland
| | - Marco Piccirelli
- Clinical Neuroscience Center, University Hospital Zurich, Switzerland; Department of Neuroradiology, University Hospital Zurich, University of Zurich, Switzerland
| | - Jorn Fierstra
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Switzerland; Clinical Neuroscience Center, University Hospital Zurich, Switzerland
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Kearney E, Brownsett SLE, Copland DA, Drummond KJ, Jeffree RL, Olson S, Murton E, Ong B, Robinson GA, Tolkacheva V, McMahon KL, de Zubicaray GI. Relationships between reading performance and regional spontaneous brain activity following surgical removal of primary left-hemisphere tumors: A resting-state fMRI study. Neuropsychologia 2023; 188:108631. [PMID: 37356540 DOI: 10.1016/j.neuropsychologia.2023.108631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 06/08/2023] [Accepted: 06/23/2023] [Indexed: 06/27/2023]
Abstract
Left-hemisphere intraparenchymal primary brain tumor patients are at risk of developing reading difficulties that may be stable, improve or deteriorate after surgery. Previous studies examining language organization in brain tumor patients have provided insights into neural plasticity supporting recovery. Only a single study, however, has examined the role of white matter tracts in preserving reading ability post-surgery and none have examined the functional reading network. The current study aimed to investigate the regional spontaneous brain activity associated with reading performance in a group of 36 adult patients 6-24 months following left-hemisphere tumor resection. Spontaneous brain activity was assessed using resting-state fMRI (rs-fMRI) regional homogeneity (ReHo) and fractional amplitude low frequency fluctuation (fALFF) metrics, which measure local functional connectivity and activity, respectively. ReHo in the left occipito-temporal and right superior parietal regions was negatively correlated with reading performance. fALFF in the putamen bilaterally and the left cerebellum was negatively correlated with reading performance, and positively correlated in the right superior parietal gyrus. These findings are broadly consistent with reading networks reported in healthy participants, indicating that reading ability following brain tumor surgery might not involve substantial functional re-organization.
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Affiliation(s)
- Elaine Kearney
- School of Psychology and Counselling, Queensland University of Technology, Brisbane, 4059, Australia.
| | - Sonia L E Brownsett
- Queensland Aphasia Research Centre, School of Health and Rehabilitation Sciences, University of Queensland, Brisbane, 4072, Australia; Surgical Treatment and Rehabilitation Service (STARS), Education and Research Alliance, University of Queensland and Metro North Health, Queensland, Australia; Centre of Research Excellence in Aphasia Recovery and Rehabilitation, Australia
| | - David A Copland
- Queensland Aphasia Research Centre, School of Health and Rehabilitation Sciences, University of Queensland, Brisbane, 4072, Australia; Surgical Treatment and Rehabilitation Service (STARS), Education and Research Alliance, University of Queensland and Metro North Health, Queensland, Australia; Centre of Research Excellence in Aphasia Recovery and Rehabilitation, Australia
| | - Katharine J Drummond
- Department of Neurosurgery, Royal Melbourne Hospital, Parkville, 3050, Australia; Department of Surgery, University of Melbourne, Parkville, 3052, Australia
| | | | - Sarah Olson
- Princess Alexandra Hospital, Brisbane, 4102, Australia
| | - Emma Murton
- Department of Speech Pathology, Royal Melbourne Hospital, Parkville, 3050, Australia
| | - Benjamin Ong
- Princess Alexandra Hospital, Brisbane, 4102, Australia
| | - Gail A Robinson
- Queensland Brain Institute and School of Psychology, University of Queensland, Brisbane, 4072, Australia
| | - Valeriya Tolkacheva
- School of Psychology and Counselling, Queensland University of Technology, Brisbane, 4059, Australia
| | - Katie L McMahon
- School of Clinical Sciences, Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, 4059, Australia; Herston Imaging Research Facility, Royal Brisbane & Women's Hospital, Brisbane, 4029, Australia
| | - Greig I de Zubicaray
- School of Psychology and Counselling, Queensland University of Technology, Brisbane, 4059, Australia
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Agarwal S, Welker KM, Black DF, Little JT, DeLone DR, Messina SA, Passe TJ, Bettegowda C, Pillai JJ. Detection and Mitigation of Neurovascular Uncoupling in Brain Gliomas. Cancers (Basel) 2023; 15:4473. [PMID: 37760443 PMCID: PMC10527022 DOI: 10.3390/cancers15184473] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 08/28/2023] [Accepted: 09/01/2023] [Indexed: 09/29/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) with blood oxygen level-dependent (BOLD) technique is useful for preoperative mapping of brain functional networks in tumor patients, providing reliable in vivo detection of eloquent cortex to help reduce the risk of postsurgical morbidity. BOLD task-based fMRI (tb-fMRI) is the most often used noninvasive method that can reliably map cortical networks, including those associated with sensorimotor, language, and visual functions. BOLD resting-state fMRI (rs-fMRI) is emerging as a promising ancillary tool for visualization of diverse functional networks. Although fMRI is a powerful tool that can be used as an adjunct for brain tumor surgery planning, it has some constraints that should be taken into consideration for proper clinical interpretation. BOLD fMRI interpretation may be limited by neurovascular uncoupling (NVU) induced by brain tumors. Cerebrovascular reactivity (CVR) mapping obtained using breath-hold methods is an effective method for evaluating NVU potential.
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Affiliation(s)
- Shruti Agarwal
- Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA;
| | - Kirk M. Welker
- Division of Neuroradiology, Department of Radiology, Mayo Clinic Rochester & Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA; (K.M.W.); (D.F.B.); (J.T.L.); (D.R.D.); (S.A.M.); (T.J.P.)
| | - David F. Black
- Division of Neuroradiology, Department of Radiology, Mayo Clinic Rochester & Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA; (K.M.W.); (D.F.B.); (J.T.L.); (D.R.D.); (S.A.M.); (T.J.P.)
| | - Jason T. Little
- Division of Neuroradiology, Department of Radiology, Mayo Clinic Rochester & Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA; (K.M.W.); (D.F.B.); (J.T.L.); (D.R.D.); (S.A.M.); (T.J.P.)
| | - David R. DeLone
- Division of Neuroradiology, Department of Radiology, Mayo Clinic Rochester & Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA; (K.M.W.); (D.F.B.); (J.T.L.); (D.R.D.); (S.A.M.); (T.J.P.)
| | - Steven A. Messina
- Division of Neuroradiology, Department of Radiology, Mayo Clinic Rochester & Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA; (K.M.W.); (D.F.B.); (J.T.L.); (D.R.D.); (S.A.M.); (T.J.P.)
| | - Theodore J. Passe
- Division of Neuroradiology, Department of Radiology, Mayo Clinic Rochester & Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA; (K.M.W.); (D.F.B.); (J.T.L.); (D.R.D.); (S.A.M.); (T.J.P.)
| | - Chetan Bettegowda
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA;
| | - Jay J. Pillai
- Division of Neuroradiology, Department of Radiology, Mayo Clinic Rochester & Mayo Clinic College of Medicine and Science, Rochester, MN 55905, USA; (K.M.W.); (D.F.B.); (J.T.L.); (D.R.D.); (S.A.M.); (T.J.P.)
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA;
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9
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Liu P, Hu B, Kartchner L, Joshi P, Xu C, Jiang D. Dependence of resting-state-based cerebrovascular reactivity (CVR) mapping on spatial resolution. FRONTIERS IN NEUROIMAGING 2023; 2:1205459. [PMID: 37554643 PMCID: PMC10406303 DOI: 10.3389/fnimg.2023.1205459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 06/12/2023] [Indexed: 08/10/2023]
Abstract
Cerebrovascular reactivity (CVR) is typically assessed with a carbon dioxide (CO2) stimulus combined with BOLD fMRI. Recently, resting-state (RS) BOLD fMRI has been shown capable of generating CVR maps, providing a potential for broader CVR applications in neuroimaging studies. However, prior RS-CVR studies have primarily been performed at a spatial resolution of 3-4 mm voxel sizes. It remains unknown whether RS-CVR can also be obtained at high-resolution without major degradation in image quality. In this study, we investigated RS-CVR mapping based on resting-state BOLD MRI across a range of spatial resolutions in a group of healthy subjects, in an effort to examine the feasibility of RS-CVR measurement at high resolution. Comparing the results of RS-CVR with the maps obtained by the conventional CO2-inhalation method, our results suggested that good CVR map quality can be obtained at a voxel size as small as 2 mm isotropic. Our results also showed that, RS-CVR maps revealed resolution-dependent sensitivity. However, even at a high resolution of 2 mm isotropic voxel size, the voxel-wise sensitivity is still greater than that of typical task-evoked fMRI. Scan duration affected the sensitivity of RS-CVR mapping, but had no significant effect on its accuracy. These findings suggest that RS-CVR mapping can be applied at a similar resolution as state-of-the-art fMRI studies, which will broaden the use of CVR mapping in basic science and clinical applications including retrospective analysis of previously collected fMRI data.
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Affiliation(s)
- Peiying Liu
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Beini Hu
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Lincoln Kartchner
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Parimal Joshi
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Cuimei Xu
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Dengrong Jiang
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
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10
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Lawrence A, Carvajal M, Ormsby J. Beyond Broca's and Wernicke's: Functional Mapping of Ancillary Language Centers Prior to Brain Tumor Surgery. Tomography 2023; 9:1254-1275. [PMID: 37489468 PMCID: PMC10366753 DOI: 10.3390/tomography9040100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 06/21/2023] [Accepted: 06/23/2023] [Indexed: 07/26/2023] Open
Abstract
Functional MRI is a well-established tool used for pre-surgical planning to help the neurosurgeon have a roadmap of critical functional areas that should be avoided, if possible, during surgery to minimize morbidity for patients with brain tumors (though this also has applications for surgical resection of epileptogenic tissue and vascular lesions). This article reviews the locations of secondary language centers within the brain along with imaging findings to help improve our confidence in our knowledge on language lateralization. Brief overviews of these language centers and their contributions to the language networks will be discussed. These language centers include primary language centers of "Broca's Area" and "Wernicke's Area". However, there are multiple secondary language centers such as the dorsal lateral prefrontal cortex (DLPFC), frontal eye fields, pre- supplemental motor area (pre-SMA), Basal Temporal Language Area (BTLA), along with other areas of activation. Knowing these foci helps to increase self-assurance when discussing the nature of laterality with the neurosurgeon. By knowing secondary language centers for language lateralization, via fMRI, one can feel confident on providing neurosurgeon colleagues with appropriate information on the laterality of language in preparation for surgery.
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Affiliation(s)
- Ashley Lawrence
- Center for Neuropsychological Services, University of New Mexico, MSC 10 5530 1 University of New Mexico, Albuquerque, NM 87131-5001, USA
| | - Michael Carvajal
- Center for Neuropsychological Services, University of New Mexico, MSC 10 5530 1 University of New Mexico, Albuquerque, NM 87131-5001, USA
| | - Jacob Ormsby
- Department of Radiology, University of New Mexico, MSC 10 5530 1 University of New Mexico, Albuquerque, NM 87131-5001, USA
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11
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Piccirilli E, Sestieri C, Di Clemente L, Delli Pizzi A, Colasurdo M, Panara V, Caulo M. The effect of different brain lesions on the reorganization of language functions within the dominant hemisphere assessed with task-based BOLD-fMRI. LA RADIOLOGIA MEDICA 2023:10.1007/s11547-023-01642-5. [PMID: 37184809 DOI: 10.1007/s11547-023-01642-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 04/26/2023] [Indexed: 05/16/2023]
Abstract
BACKGROUND AND PURPOSE Language reorganization has been described in brain lesions with respect to their location and timing, but little is known with respect to their etiology. We used fMRI to investigate the effects of different types of left hemisphere lesions (GL = gliomas, TLE = temporal lobe epilepsy and CA = cavernous angioma) on the topographic intra-hemispheric language plasticity, also considering their location. METHODS Forty-seven right-handed patients with 3 different left hemisphere lesions (16 GL, 15 TLE and 16 CA) and 17 healthy controls underwent BOLD fMRI with a verb-generation task. Euclidean distance was used to measure activation peak shifts among groups with respect to reference Tailarach coordinates of Inferior Frontal Gyrus, Superior Temporal Sulcus and Temporo-Parietal Junction. Mixed-model ANOVAs were used to test for differences in activation peak shifts. RESULTS Significant activation peak shifts were found in GL patients with respect both to HC and other groups (TLA and CA). In addition, in the same group of patients a significant effect of tumor location (anterior or posterior) was detected. CONCLUSIONS We demonstrated that intra-hemispheric language plasticity is influenced by the type of lesion affecting the left hemisphere and that fMRI is especially valuable in the preoperative assessment of such reorganization in glioma patients.
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Affiliation(s)
- Eleonora Piccirilli
- Department of Neuroscience, Imaging and Clinical Sciences (DNISC), Università Degli Studi Gabriele d'Annunzio Di Chieti Pescara, 66100, Chieti, Italy
- Institute for Advanced Biomedical Technologies (ITAB), Università Degli Studi Gabriele d'Annunzio Di Chieti Pescara, Chieti, Italy
- Department of Imaging, Ospedale Pediatrico Bambino Gesù, IRCSS, Rome, Italy
| | - Carlo Sestieri
- Department of Neuroscience, Imaging and Clinical Sciences (DNISC), Università Degli Studi Gabriele d'Annunzio Di Chieti Pescara, 66100, Chieti, Italy
- Institute for Advanced Biomedical Technologies (ITAB), Università Degli Studi Gabriele d'Annunzio Di Chieti Pescara, Chieti, Italy
| | - Loris Di Clemente
- Institute for Advanced Biomedical Technologies (ITAB), Università Degli Studi Gabriele d'Annunzio Di Chieti Pescara, Chieti, Italy
| | - Andrea Delli Pizzi
- Department of Innovative Technologies in Medicine and Dentistry, Università Degli Studi Gabriele d'Annunzio Di Chieti Pescara, Chieti, Italy
- Department of Radiology, SS. Annunziata University Hospital, Chieti, Italy
| | - Marco Colasurdo
- Department of Radiology, SS. Annunziata University Hospital, Chieti, Italy
| | - Valentina Panara
- Institute for Advanced Biomedical Technologies (ITAB), Università Degli Studi Gabriele d'Annunzio Di Chieti Pescara, Chieti, Italy
- Department of Radiology, SS. Annunziata University Hospital, Chieti, Italy
| | - Massimo Caulo
- Department of Neuroscience, Imaging and Clinical Sciences (DNISC), Università Degli Studi Gabriele d'Annunzio Di Chieti Pescara, 66100, Chieti, Italy.
- Institute for Advanced Biomedical Technologies (ITAB), Università Degli Studi Gabriele d'Annunzio Di Chieti Pescara, Chieti, Italy.
- Department of Radiology, SS. Annunziata University Hospital, Chieti, Italy.
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12
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Pre-Operative Functional Mapping in Patients with Brain Tumors by fMRI and MEG: Advantages and Disadvantages in the Use of One Technique over the Other. Life (Basel) 2023; 13:life13030609. [PMID: 36983765 PMCID: PMC10051860 DOI: 10.3390/life13030609] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 02/17/2023] [Accepted: 02/20/2023] [Indexed: 02/24/2023] Open
Abstract
Pre-operative mapping of brain functions is crucial to plan neurosurgery and investigate potential plasticity processes. Due to its availability, functional magnetic resonance imaging (fMRI) is widely used for this purpose; on the other hand, the demanding cost and maintenance limit the use of magnetoencephalography (MEG), despite several studies reporting its accuracy in localizing brain functions of interest in patient populations. In this review paper, we discuss the strengths and weaknesses of both techniques, from a methodological perspective first; then, we scrutinized and commented on the findings from 16 studies, identified by a database search, that made pre-operative assessments using both techniques in patients with brain tumors. We commented on the results by accounting for study limitations associated with small sample sizes and variability in the used tasks. Overall, we found that, although some studies reported the superiority for MEG, the majority of them underlined the complementary use of these techniques and suggested assessment using both. Indeed, both fMRI and MEG present some disadvantages, although the development of novel devices and processing procedures has enabled ever more accurate assessments. In particular, the development of new, more feasible MEG devices will allow widespread availability of this technique and its routinely combined use with fMRI.
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13
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Liu P, Baker Z, Li Y, Li Y, Xu J, Park DC, Welch BG, Pinho M, Pillai JJ, Hillis AE, Mori S, Lu H. CVR-MRICloud: An online processing tool for CO2-inhalation and resting-state cerebrovascular reactivity (CVR) MRI data. PLoS One 2022; 17:e0274220. [PMID: 36170233 PMCID: PMC9518872 DOI: 10.1371/journal.pone.0274220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 08/23/2022] [Indexed: 12/02/2022] Open
Abstract
Cerebrovascular Reactivity (CVR) provides an assessment of the brain's vascular reserve and has been postulated to be a sensitive marker in cerebrovascular diseases. MRI-based CVR measurement typically employs alterations in arterial carbon dioxide (CO2) level while continuously acquiring Blood-Oxygenation-Level-Dependent (BOLD) images. CO2-inhalation and resting-state methods are two commonly used approaches for CVR MRI. However, processing of CVR MRI data often requires special expertise and may become an obstacle in broad utilization of this promising technique. The aim of this work was to develop CVR-MRICloud, a cloud-based CVR processing pipeline, to enable automated processing of CVR MRI data. The CVR-MRICloud consists of several major steps including extraction of end-tidal CO2 (EtCO2) curve from raw CO2 recording, alignment of EtCO2 curve with BOLD time course, computation of CVR value on a whole-brain, regional, and voxel-wise basis. The pipeline also includes standard BOLD image processing steps such as motion correction, registration between functional and anatomic images, and transformation of the CVR images to canonical space. This paper describes these algorithms and demonstrates the performance of the CVR-MRICloud in lifespan healthy subjects and patients with clinical conditions such as stroke, brain tumor, and Moyamoya disease. CVR-MRICloud has potential to be used as a data processing tool for a variety of basic science and clinical applications.
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Affiliation(s)
- Peiying Liu
- Department of Diagnostic Radiology & Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Zachary Baker
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Yue Li
- AnatomyWorks, LLC, Baltimore, Maryland, United States of America
| | - Yang Li
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Jiadi Xu
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, United States of America
| | - Denise C. Park
- Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, Texas, United States of America
| | - Babu G. Welch
- Department of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America
| | - Marco Pinho
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America
| | - Jay J. Pillai
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Argye E. Hillis
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Susumu Mori
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, United States of America
| | - Hanzhang Lu
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, United States of America
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14
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Liu P, Jiang D, Albert M, Bauer CE, Caprihan A, Gold BT, Greenberg SM, Helmer KG, Jann K, Jicha G, Rodriguez P, Satizabal CL, Seshadri S, Singh H, Thompson JF, Wang DJJ, Lu H. Multi-vendor and multisite evaluation of cerebrovascular reactivity mapping using hypercapnia challenge. Neuroimage 2021; 245:118754. [PMID: 34826595 PMCID: PMC8783393 DOI: 10.1016/j.neuroimage.2021.118754] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 11/05/2021] [Accepted: 11/22/2021] [Indexed: 01/22/2023] Open
Abstract
Cerebrovascular reactivity (CVR), which measures the ability of cerebral blood vessels to dilate or constrict in response to vasoactive stimuli such as CO2 inhalation, is an important index of the brain's vascular health. Quantification of CVR using BOLD MRI with hypercapnia challenge has shown great promises in research and clinical studies. However, in order for it to be used as a potential imaging biomarker in large-scale and multi-site studies, the reliability of CO2-CVR quantification across different MRI acquisition platforms and researchers/raters must be examined. The goal of this report from the MarkVCID small vessel disease biomarkers consortium is to evaluate the reliability of CO2-CVR quantification in three studies. First, the inter-rater reliability of CO2-CVR data processing was evaluated by having raters from 5 MarkVCID sites process the same 30 CVR datasets using a cloud-based CVR data processing pipeline. Second, the inter-scanner reproducibility of CO2-CVR quantification was assessed in 10 young subjects across two scanners of different vendors. Third, test-retest repeatability was evaluated in 20 elderly subjects from 4 sites with a scan interval of less than 2 weeks. In all studies, the CO2 CVR measurements were performed using the fixed inspiration method, where the subjects wore a nose clip and a mouthpiece and breathed room air and 5% CO2 air contained in a Douglas bag alternatively through their mouth. The results showed that the inter-rater CoV of CVR processing was 0.08 ± 0.08% for whole-brain CVR values and ranged from 0.16% to 0.88% in major brain regions, with ICC of absolute agreement above 0.9959 for all brain regions. Inter-scanner CoV was found to be 6.90 ± 5.08% for whole-brain CVR values, and ranged from 4.69% to 12.71% in major brain regions, which are comparable to intra-session CoVs obtained from the same scanners on the same day. ICC of consistency between the two scanners was 0.8498 for whole-brain CVR and ranged from 0.8052 to 0.9185 across major brain regions. In the test-retest evaluation, test-retest CoV across different days was found to be 18.29 ± 17.12% for whole-brain CVR values, and ranged from 16.58% to 19.52% in major brain regions, with ICC of absolute agreement ranged from 0.6480 to 0.7785. These results demonstrated good inter-rater, inter-scanner, and test-retest reliability in healthy volunteers, and suggested that CO2-CVR has suitable instrumental properties for use as an imaging biomarker of cerebrovascular function in multi-site and longitudinal observational studies and clinical trials.
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Affiliation(s)
- Peiying Liu
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Dengrong Jiang
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Marilyn Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | | | | | - Brian T Gold
- Department of Neuroscience, University of Kentucky, Lexington, KY, USA
| | - Steven M Greenberg
- Department of Neurology, Massachusetts General Hospital Stroke Research Center, Harvard Medical School, Boston, MA, USA
| | - Karl G Helmer
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Kay Jann
- Laboratory of Functional MRI Technology, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Gregory Jicha
- Department of Neurology, University of Kentucky, Lexington, KY, USA
| | - Pavel Rodriguez
- Department of Radiology, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA; Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX, USA
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX, USA
| | - Herpreet Singh
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Jeffrey F Thompson
- Department of Neurology, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Danny J J Wang
- Laboratory of Functional MRI Technology, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Hanzhang Lu
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore 21287, USA; F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, 21205, USA.
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15
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Fesharaki NJ, Mathew AB, Mathis JR, Huddleston WE, Reuss JL, Pillai JJ, DeYoe EA. Effects of Thresholding on Voxel-Wise Correspondence of Breath-Hold and Resting-State Maps of Cerebrovascular Reactivity. Front Neurosci 2021; 15:654957. [PMID: 34504411 PMCID: PMC8421787 DOI: 10.3389/fnins.2021.654957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 07/22/2021] [Indexed: 11/13/2022] Open
Abstract
Functional magnetic resonance imaging for presurgical brain mapping enables neurosurgeons to identify viable tissue near a site of operable pathology which might be at risk of surgery-induced damage. However, focal brain pathology (e.g., tumors) may selectively disrupt neurovascular coupling while leaving the underlying neurons functionally intact. Such neurovascular uncoupling can result in false negatives on brain activation maps thereby compromising their use for surgical planning. One way to detect potential neurovascular uncoupling is to map cerebrovascular reactivity using either an active breath-hold challenge or a passive resting-state scan. The equivalence of these two methods has yet to be fully established, especially at a voxel level of resolution. To quantitatively compare breath-hold and resting-state maps of cerebrovascular reactivity, we first identified threshold settings that optimized coverage of gray matter while minimizing false responses in white matter. When so optimized, the resting-state metric had moderately better gray matter coverage and specificity. We then assessed the spatial correspondence between the two metrics within cortical gray matter, again, across a wide range of thresholds. Optimal spatial correspondence was strongly dependent on threshold settings which if improperly set tended to produce statistically biased maps. When optimized, the two CVR maps did have moderately good correspondence with each other (mean accuracy of 73.6%). Our results show that while the breath-hold and resting-state maps may appear qualitatively similar they are not quantitatively identical at a voxel level of resolution.
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Affiliation(s)
- Nooshin J Fesharaki
- College of Health Sciences, University of Wisconsin-Milwaukee, Milwaukee, WI, United States.,Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Amy B Mathew
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Jedidiah R Mathis
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Wendy E Huddleston
- College of Health Sciences, University of Wisconsin-Milwaukee, Milwaukee, WI, United States
| | - James L Reuss
- Prism Clinical Imaging, Inc., Milwaukee, WI, United States
| | - Jay J Pillai
- Neuroradiology Division, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Edgar A DeYoe
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
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16
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Stickland RC, Zvolanek KM, Moia S, Ayyagari A, Caballero-Gaudes C, Bright MG. A practical modification to a resting state fMRI protocol for improved characterization of cerebrovascular function. Neuroimage 2021; 239:118306. [PMID: 34175427 PMCID: PMC8552969 DOI: 10.1016/j.neuroimage.2021.118306] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 06/18/2021] [Accepted: 06/23/2021] [Indexed: 12/22/2022] Open
Abstract
Cerebrovascular reactivity (CVR), defined here as the Blood Oxygenation Level Dependent (BOLD) response to a CO2 pressure change, is a useful metric of cerebrovascular function. Both the amplitude and the timing (hemodynamic lag) of the CVR response can bring insight into the nature of a cerebrovascular pathology and aid in understanding noise confounds when using functional Magnetic Resonance Imaging (fMRI) to study neural activity. This research assessed a practical modification to a typical resting-state fMRI protocol, to improve the characterization of cerebrovascular function. In 9 healthy subjects, we modelled CVR and lag in three resting-state data segments, and in data segments which added a 2–3 minute breathing task to the start of a resting-state segment. Two different breathing tasks were used to induce fluctuations in arterial CO2 pressure: a breath-hold task to induce hypercapnia (CO2 increase) and a cued deep breathing task to induce hypocapnia (CO2 decrease). Our analysis produced voxel-wise estimates of the amplitude (CVR) and timing (lag) of the BOLD-fMRI response to CO2 by systematically shifting the CO2 regressor in time to optimize the model fit. This optimization inherently increases gray matter CVR values and fit statistics. The inclusion of a simple breathing task, compared to a resting-state scan only, increases the number of voxels in the brain that have a significant relationship between CO2 and BOLD-fMRI signals, and improves our confidence in the plausibility of voxel-wise CVR and hemodynamic lag estimates. We demonstrate the clinical utility and feasibility of this protocol in an incidental finding of Moyamoya disease, and explore the possibilities and challenges of using this protocol in younger populations. This hybrid protocol has direct applications for CVR mapping in both research and clinical settings and wider applications for fMRI denoising and interpretation.
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Affiliation(s)
- Rachael C Stickland
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.
| | - Kristina M Zvolanek
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States; Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
| | - Stefano Moia
- Basque Center on Cognition, Brain and Language, Donostia, Gipuzkoa, Spain; University of the Basque Country EHU/UPV, Donostia, Gipuzkoa, Spain
| | - Apoorva Ayyagari
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States; Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
| | | | - Molly G Bright
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States; Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
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Clinical applications of neurolinguistics in neurosurgery. Front Med 2021; 15:562-574. [PMID: 33983605 DOI: 10.1007/s11684-020-0771-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 03/05/2020] [Indexed: 11/27/2022]
Abstract
The protection of language function is one of the major challenges of brain surgery. Over the past century, neurosurgeons have attempted to seek the optimal strategy for the preoperative and intraoperative identification of language-related brain regions. Neurosurgeons have investigated the neural mechanism of language, developed neurolinguistics theory, and provided unique evidence to further understand the neural basis of language functions by using intraoperative cortical and subcortical electrical stimulation. With the emergence of modern neuroscience techniques and dramatic advances in language models over the last 25 years, novel language mapping methods have been applied in the neurosurgical practice to help neurosurgeons protect the brain and reduce morbidity. The rapid advancements in brain-computer interface have provided the perfect platform for the combination of neurosurgery and neurolinguistics. In this review, the history of neurolinguistics models, advancements in modern technology, role of neurosurgery in language mapping, and modern language mapping methods (including noninvasive neuroimaging techniques and invasive cortical electroencephalogram) are presented.
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Distinct Cerebrovascular Reactivity Patterns for Brain Radiation Necrosis. Cancers (Basel) 2021; 13:cancers13081840. [PMID: 33924308 PMCID: PMC8069508 DOI: 10.3390/cancers13081840] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 03/31/2021] [Accepted: 04/09/2021] [Indexed: 11/17/2022] Open
Abstract
Background: Current imaging-based discrimination between radiation necrosis versus recurrent glioblastoma contrast-enhancing lesions remains imprecise but is paramount for prognostic and therapeutic evaluation. We examined whether patients with radiation necrosis exhibit distinct patterns of blood oxygenation-level dependent fMRI cerebrovascular reactivity (BOLD-CVR) as the first step to better distinguishing patients with radiation necrosis from recurrent glioblastoma compared with patients with newly diagnosed glioblastoma before surgery and radiotherapy. Methods: Eight consecutive patients with primary and secondary brain tumors and a multidisciplinary clinical and radiological diagnosis of radiation necrosis, and fourteen patients with a first diagnosis of glioblastoma underwent BOLD-CVR mapping. For all these patients, the contrast-enhancing lesion was derived from high-resolution T1-weighted MRI and rendered the volume-of-interest (VOI). From this primary VOI, additional 3 mm concentric expanding VOIs up to 30 mm were created for a detailed perilesional BOLD-CVR tissue analysis between the two groups. Receiver operating characteristic curves assessed the discriminative properties of BOLD-CVR for both groups. Results: Mean intralesional BOLD-CVR values were markedly lower in radiation necrosis than in glioblastoma contrast-enhancing lesions (0.001 ± 0.06 vs. 0.057 ± 0.05; p = 0.04). Perilesionally, a characteristic BOLD-CVR pattern was observed for radiation necrosis and glioblastoma patients, with an improvement of BOLD-CVR values in the radiation necrosis group and persisting lower perilesional BOLD-CVR values in glioblastoma patients. The ROC analysis discriminated against both groups when these two parameters were analyzed together (area under the curve: 0.85, 95% CI: 0.65-1.00). Conclusions: In this preliminary analysis, distinctive intralesional and perilesional BOLD-cerebrovascular reactivity patterns are found for radiation necrosis.
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Yang J, Gohel S, Zhang Z, Hatzoglou V, Holodny AI, Vachha BA. Glioma-Induced Disruption of Resting-State Functional Connectivity and Amplitude of Low-Frequency Fluctuations in the Salience Network. AJNR Am J Neuroradiol 2021; 42:551-558. [PMID: 33384293 DOI: 10.3174/ajnr.a6929] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 10/02/2020] [Indexed: 12/15/2022]
Abstract
BACKGROUND AND PURPOSE Cognitive challenges are prevalent in survivors of glioma, but their neurobiology is incompletely understood. The purpose of this study was to investigate the effect of glioma presence and tumor characteristics on resting-state functional connectivity and amplitude of low-frequency fluctuations of the salience network, a key neural network associated with cognition. MATERIALS AND METHODS Sixty-nine patients with glioma (mean age, 48.74 [SD, 14.32] years) who underwent resting-state fMRI were compared with 31 healthy controls (mean age, 49.68 [SD, 15.54] years). We identified 4 salience network ROIs: left/right dorsal anterior cingulate cortex and left/right anterior insula. Average salience network resting-state functional connectivity and amplitude of low-frequency fluctuations within the 4 salience network ROIs were computed. RESULTS Patients with gliomas showed decreased overall salience network resting-state functional connectivity (P = .001) and increased amplitude of low-frequency fluctuations in all salience network ROIs (P < .01) except in the left dorsal anterior cingulate cortex. Compared with controls, patients with left-sided gliomas showed increased amplitude of low-frequency fluctuations in the right dorsal anterior cingulate cortex (P = .002) and right anterior insula (P < .001), and patients with right-sided gliomas showed increased amplitude of low-frequency fluctuations in the left anterior insula (P = .002). Anterior tumors were associated with decreased salience network resting-state functional connectivity (P < .001) and increased amplitude of low-frequency fluctuations in the right anterior insula, left anterior insula, and right dorsal anterior cingulate cortex. Patients with high-grade gliomas had decreased salience network resting-state functional connectivity compared with healthy controls (P < .05). The right anterior insula showed increased amplitude of low-frequency fluctuations in patients with grade II and IV gliomas compared with controls (P < .01). CONCLUSIONS By demonstrating decreased resting-state functional connectivity and an increased amplitude of low-frequency fluctuations related to the salience network in patients with glioma, this study adds to our understanding of the neurobiology underpinning observable cognitive deficits in these patients. In addition to more conventional functional connectivity, amplitude of low-frequency fluctuations is a promising functional-imaging biomarker of tumor-induced vascular and neural pathology.
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Affiliation(s)
- J Yang
- From the Departments of Radiology (J.Y., V.H., A.I.H., B.A.V.)
- New York University Grossman School of Medicine (J.Y.), New York University, New York, New York
| | - S Gohel
- Department of Health Informatics (S.G.), Rutgers University School of Health Professions, Newark, New Jersey
| | - Z Zhang
- Epidemiology and Biostatistics (Z.Z.)
| | - V Hatzoglou
- From the Departments of Radiology (J.Y., V.H., A.I.H., B.A.V.)
- Brain Tumor Center (V.H., A.I.H., B.A.V.), Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Radiology (V.H., A.I.H., B.A.V.), Weill Medical College of Cornell University, New York, New York
| | - A I Holodny
- From the Departments of Radiology (J.Y., V.H., A.I.H., B.A.V.)
- Brain Tumor Center (V.H., A.I.H., B.A.V.), Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Radiology (V.H., A.I.H., B.A.V.), Weill Medical College of Cornell University, New York, New York
- Department of Neuroscience (A.I.H.), Weill-Cornell Graduate School of the Medical Sciences, New York, New York
| | - B A Vachha
- From the Departments of Radiology (J.Y., V.H., A.I.H., B.A.V.)
- Brain Tumor Center (V.H., A.I.H., B.A.V.), Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Radiology (V.H., A.I.H., B.A.V.), Weill Medical College of Cornell University, New York, New York
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20
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Pinto J, Bright MG, Bulte DP, Figueiredo P. Cerebrovascular Reactivity Mapping Without Gas Challenges: A Methodological Guide. Front Physiol 2021; 11:608475. [PMID: 33536935 PMCID: PMC7848198 DOI: 10.3389/fphys.2020.608475] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 12/02/2020] [Indexed: 01/08/2023] Open
Abstract
Cerebrovascular reactivity (CVR) is defined as the ability of vessels to alter their caliber in response to vasoactive factors, by means of dilating or constricting, in order to increase or decrease regional cerebral blood flow (CBF). Importantly, CVR may provide a sensitive biomarker for pathologies where vasculature is compromised. Furthermore, the spatiotemporal dynamics of CVR observed in healthy subjects, reflecting regional differences in cerebral vascular tone and response, may also be important in functional MRI studies based on neurovascular coupling mechanisms. Assessment of CVR is usually based on the use of a vasoactive stimulus combined with a CBF measurement technique. Although transcranial Doppler ultrasound has been frequently used to obtain global flow velocity measurements, MRI techniques are being increasingly employed for obtaining CBF maps. For the vasoactive stimulus, vasodilatory hypercapnia is usually induced through the manipulation of respiratory gases, including the inhalation of increased concentrations of carbon dioxide. However, most of these methods require an additional apparatus and complex setups, which not only may not be well-tolerated by some populations but are also not widely available. For these reasons, strategies based on voluntary breathing fluctuations without the need for external gas challenges have been proposed. These include the task-based methodologies of breath holding and paced deep breathing, as well as a new generation of methods based on spontaneous breathing fluctuations during resting-state. Despite the multitude of alternatives to gas challenges, existing literature lacks definitive conclusions regarding the best practices for the vasoactive modulation and associated analysis protocols. In this work, we perform an extensive review of CVR mapping techniques based on MRI and CO2 variations without gas challenges, focusing on the methodological aspects of the breathing protocols and corresponding data analysis. Finally, we outline a set of practical guidelines based on generally accepted practices and available data, extending previous reports and encouraging the wider application of CVR mapping methodologies in both clinical and academic MRI settings.
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Affiliation(s)
- Joana Pinto
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
- Institute for Systems and Robotics - Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Molly G. Bright
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, IL, United States
| | - Daniel P. Bulte
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Patrícia Figueiredo
- Institute for Systems and Robotics - Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
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Hussain MM, Shabbir A, Bakhshi SK, Shamim MS. Are Thinking Machines Breaking New Frontiers in Neuro-Oncology? A Narrative Review on the Emerging Role of Machine Learning in Neuro-Oncological Practice. Asian J Neurosurg 2021; 16:8-13. [PMID: 34211861 PMCID: PMC8202358 DOI: 10.4103/ajns.ajns_265_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 08/07/2020] [Accepted: 09/17/2020] [Indexed: 11/21/2022] Open
Abstract
Medical science in general and oncology in particular are dynamic, rapidly evolving subjects. Brain and spine tumors, whether primary or secondary, constitute a significant number of cases in any oncological practice. With the rapid influx of data in all aspects of neuro-oncological care, it is almost impossible for practicing clinicians to remain abreast with the current trends, or to synthesize the available data for it to be maximally beneficial for their patients. Machine-learning (ML) tools are fast gaining acceptance as an alternative to conventional reliance on online data. ML uses artificial intelligence to provide a computer algorithm-based information to clinicians. Different ML models have been proposed in the literature with a variable degree of precision and database requirements. ML can potentially solve the aforementioned problems for practicing clinicians by not just extracting and analyzing useful data, by minimizing or eliminating certain potential areas of human error, by creating patient-specific treatment plans, and also by predicting outcomes with reasonable accuracy. Current information on ML in neuro-oncology is scattered, and this literature review is an attempt to consolidate it and provide recent updates.
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Affiliation(s)
| | - Ainsia Shabbir
- Department of Computer and Information Systems Engineering, NED University of Engineering and Technology, Karachi, Pakistan
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Abstract
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.
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Affiliation(s)
- Shruti Agarwal
- Division of Neuroradiology, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Baltimore, MD 21287, USA
| | - Haris I Sair
- Division of Neuroradiology, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Baltimore, MD 21287, USA; The Malone Center for Engineering in Healthcare, The Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jay J Pillai
- Division of Neuroradiology, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600 North Wolfe Street, Baltimore, MD 21287, USA; Department of Neurosurgery, Johns Hopkins University School of Medicine, 1800 Orleans Street, Baltimore, MD 21287, USA.
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Qiu T, Hameed NUF, Lin CP, Biswal BB, Wu J. Hemodynamic Scaling of Task-Induced Signal Changes in Tumor Subjects. Front Hum Neurosci 2020; 14:569463. [PMID: 33132884 PMCID: PMC7566414 DOI: 10.3389/fnhum.2020.569463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 08/24/2020] [Indexed: 11/24/2022] Open
Abstract
Background: FMRI signal amplitude can change during stimulus presentation due to underlying neural function and hemodynamic responses limiting the accuracy of fMRI in pre-surgical planning. To account for these changes in fMRI activation signal, we used breath-hold tasks to mimic hemodynamic changes in brain tumor subjects and scaled the activation response. Methods: Motor and/or language fMRI was performed in 21 subjects with brain tumor. A breath-hold task was also performed in these subjects to obtain the hemodynamic response changes independent of neural changes. The task activation signals were calibrated on a voxel wise basis for all the subjects. Direct cortical stimulation was used to verify the scaled results of task-based fMRI. Results: After scaling for the hemodynamic response function (HRF) on a voxel wise basis, the spatial extent of the scaled activation was more clustered together and appeared to minimize false positives. Similarly, accounting for the underlying canonical HRF, the percentage increase of active voxels after scaling had lower standard non-deviation suggesting that the activation response across voxels were more similar. Conclusion: Although preliminary in nature, this study suggests that the variation in hemodynamic changes can be calibrated using breath-hold in brain tumor subjects and can also be used for other clinical cases where the underlying HRF has been altered.
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Affiliation(s)
- Tianming Qiu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- Neurosurgical Institute of Fudan University, Shanghai, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, China
| | - N. U. Farrukh Hameed
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang-Ming University, Taipei, China
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Bharat B. Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, United States
- *Correspondence: Jinsong Wu
| | - Jinsong Wu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- Neurosurgical Institute of Fudan University, Shanghai, China
- Shanghai Clinical Medical Center of Neurosurgery, Shanghai, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, China
- Bharat B. Biswal
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Muscas G, van Niftrik CHB, Sebök M, Seystahl K, Piccirelli M, Stippich C, Weller M, Regli L, Fierstra J. Hemodynamic investigation of peritumoral impaired blood oxygenation-level dependent cerebrovascular reactivity in patients with diffuse glioma. Magn Reson Imaging 2020; 70:50-56. [PMID: 32302735 DOI: 10.1016/j.mri.2020.03.012] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2020] [Revised: 03/27/2020] [Accepted: 03/31/2020] [Indexed: 12/26/2022]
Abstract
INTRODUCTION The presence of peritumorally impaired blood oxygenation-level dependent cerebrovascular reactivity (BOLD-CVR) has been unequivocally demonstrated in patients with diffuse glioma, and may have value to better identify tumor infiltration zone. Since BOLD-CVR does not measure hemodynamic changes directly, we performed additional MR perfusion studies to better characterize the peritumoral hemodynamic environment. METHODS Seventeen patients with WHO grade III and IV diffuse glioma underwent high resolution advanced hemodynamic MR imaging including BOLD-CVR and MR perfusion. The obtained multiparametric hemodynamic factors (i.e., regional cerebral blood flow (rCBF), relative cerebral blood volume (rCBV), mean transit time (MTT), time-to-peak (TTP) and BOLD-CVR, were analyzed within 10 concentric expanding 3 mm volumes of interest (VOIs) up to 30 mm from the tumor tissue mask. RESULTS BOLD-CVR impairment was found within the tumor tissue mask and the peritumoral VOIs up to 21 mm as compared to the contralateral flipped CVR analysis (p<0.05). In the affected hemisphere, we observed positive spatial correlations including all VOIs between BOLD-CVR and rCBV values (r=0.27; p<0.001), rCBF (r=0.42; p<0.001) and a negative correlation between BOLD-CVR and TTP (r=-0.47; p<0.001). CONCLUSIONS Peritumorally impaired BOLD-CVR is associated with concomitant hemodynamic alterations with severity correlating to tumor volume. The distribution of these multiparametric hemodynamic MRI patterns may be considered for future studies characterizing the hemodynamic peritumoral environment, thereby better identifying the extent of tumor infiltration.
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Affiliation(s)
- Giovanni Muscas
- Department of Neurosurgery, University Hospital of Zurich and University of Zurich, Zurich, Switzerland; Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland; Department of Neurosurgery, Careggi University Hospital, Florence, Italy
| | - Christiaan Hendrik Bas van Niftrik
- Department of Neurosurgery, University Hospital of Zurich and University of Zurich, Zurich, Switzerland; Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland
| | - Martina Sebök
- Department of Neurosurgery, University Hospital of Zurich and University of Zurich, Zurich, Switzerland; Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland
| | - Katharina Seystahl
- Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland; Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Marco Piccirelli
- Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland; Department of Neuroradiology, University Hospital of Zurich and University of Zurich, Zurich, Switzerland
| | - Christoph Stippich
- Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland; Department of Neuroradiology, University Hospital of Zurich and University of Zurich, Zurich, Switzerland
| | - Michael Weller
- Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland; Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Luca Regli
- Department of Neurosurgery, University Hospital of Zurich and University of Zurich, Zurich, Switzerland; Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland
| | - Jorn Fierstra
- Department of Neurosurgery, University Hospital of Zurich and University of Zurich, Zurich, Switzerland; Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland.
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Sun H, Vachha B, Laino ME, Jenabi M, Flynn JR, Zhang Z, Holodny AI, Peck KK. Decreased Hand Motor Resting-State Functional Connectivity in Patients with Glioma: Analysis of Factors including Neurovascular Uncoupling. Radiology 2020; 294:610-621. [PMID: 31934827 DOI: 10.1148/radiol.2019190089] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background Resting-state functional MRI holds substantial potential for clinical application, but limitations exist in current understanding of how tumors exert local effects on resting-state functional MRI readings. Purpose To investigate the association between tumors, tumor characteristics, and changes in resting-state connectivity, to explore neurovascular uncoupling as a mechanism underlying these changes, and to evaluate seeding methodologies as a clinical tool. Materials and Methods Institutional review board approval was obtained for this HIPAA-compliant observational retrospective study of patients with glioma who underwent MRI and resting-state functional MRI between January 2016 and July 2017. Interhemispheric symmetry of connectivity was assessed in the hand motor region, incorporating tumor position, perfusion, grade, and connectivity generated from seed-based correlation. Statistical analysis was performed by using one-tailed t tests, Wilcoxon rank sum tests, one-way analysis of variance, Pearson correlation, and Spearman rank correlation, with significance at P < .05. Results Data in a total of 45 patients with glioma (mean age, 51.3 years ± 14.3 [standard deviation]) were compared with those in 10 healthy control subjects (mean age, 50.3 years ± 17.2). Patients showed loss of symmetry in measures of hand motor resting-state connectivity compared with control subjects (P < .05). Tumor distance from the ipsilateral hand motor (IHM) region correlated with the degree (R = 0.38, P = .01) and strength (R = 0.33, P = .03) of resting-state connectivity. In patients with World Health Organization grade IV glioblastomas 40 mm or less from the IHM region, loss of symmetry in strength of resting-state connectivity was correlated with tumor perfusion (R = 0.74, P < .01). In patients with gliomas 40 mm or less from the IHM region, seeding the nontumor hemisphere yielded less asymmetric hand motor resting-state connectivity than seeding the tumor hemisphere (connectivity seeded:contralateral = 1.34 nontumor vs 1.38 tumor hemisphere seeded; P = .03, false discovery rate threshold = 0.01). Conclusion Hand motor resting-state connectivity was less symmetrical in a tumor distance-dependent manner in patients with glioma. Differences in resting-state connectivity may be false-negative results driven by a neurovascular uncoupling mechanism. Seeding from the nontumor hemisphere may attenuate asymmetry in patients with tumors near ipsilateral hand motor cortices. © RSNA, 2020 Online supplemental material is available for this article.
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Affiliation(s)
- Herie Sun
- From the Departments of Radiology (H.S., B.V., M.E.L., M.J., A.I.H., K.K.P.), Medical Physics (K.K.P.), and Epidemiology-Biostatistics (J.R.F., Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Catholic University of the Sacred Heart-A. Gemelli Hospital, Rome, Italy (M.E.L.); Department of Neuroscience, Weill Cornell Graduate School of the Medical Sciences, New York, NY (A.I.H.); and Department of Radiology, Weill Medical College of Cornell University, New York, NY (A.I.H.)
| | - Behroze Vachha
- From the Departments of Radiology (H.S., B.V., M.E.L., M.J., A.I.H., K.K.P.), Medical Physics (K.K.P.), and Epidemiology-Biostatistics (J.R.F., Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Catholic University of the Sacred Heart-A. Gemelli Hospital, Rome, Italy (M.E.L.); Department of Neuroscience, Weill Cornell Graduate School of the Medical Sciences, New York, NY (A.I.H.); and Department of Radiology, Weill Medical College of Cornell University, New York, NY (A.I.H.)
| | - Maria E Laino
- From the Departments of Radiology (H.S., B.V., M.E.L., M.J., A.I.H., K.K.P.), Medical Physics (K.K.P.), and Epidemiology-Biostatistics (J.R.F., Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Catholic University of the Sacred Heart-A. Gemelli Hospital, Rome, Italy (M.E.L.); Department of Neuroscience, Weill Cornell Graduate School of the Medical Sciences, New York, NY (A.I.H.); and Department of Radiology, Weill Medical College of Cornell University, New York, NY (A.I.H.)
| | - Mehrnaz Jenabi
- From the Departments of Radiology (H.S., B.V., M.E.L., M.J., A.I.H., K.K.P.), Medical Physics (K.K.P.), and Epidemiology-Biostatistics (J.R.F., Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Catholic University of the Sacred Heart-A. Gemelli Hospital, Rome, Italy (M.E.L.); Department of Neuroscience, Weill Cornell Graduate School of the Medical Sciences, New York, NY (A.I.H.); and Department of Radiology, Weill Medical College of Cornell University, New York, NY (A.I.H.)
| | - Jessica R Flynn
- From the Departments of Radiology (H.S., B.V., M.E.L., M.J., A.I.H., K.K.P.), Medical Physics (K.K.P.), and Epidemiology-Biostatistics (J.R.F., Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Catholic University of the Sacred Heart-A. Gemelli Hospital, Rome, Italy (M.E.L.); Department of Neuroscience, Weill Cornell Graduate School of the Medical Sciences, New York, NY (A.I.H.); and Department of Radiology, Weill Medical College of Cornell University, New York, NY (A.I.H.)
| | - Zhigang Zhang
- From the Departments of Radiology (H.S., B.V., M.E.L., M.J., A.I.H., K.K.P.), Medical Physics (K.K.P.), and Epidemiology-Biostatistics (J.R.F., Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Catholic University of the Sacred Heart-A. Gemelli Hospital, Rome, Italy (M.E.L.); Department of Neuroscience, Weill Cornell Graduate School of the Medical Sciences, New York, NY (A.I.H.); and Department of Radiology, Weill Medical College of Cornell University, New York, NY (A.I.H.)
| | - Andrei I Holodny
- From the Departments of Radiology (H.S., B.V., M.E.L., M.J., A.I.H., K.K.P.), Medical Physics (K.K.P.), and Epidemiology-Biostatistics (J.R.F., Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Catholic University of the Sacred Heart-A. Gemelli Hospital, Rome, Italy (M.E.L.); Department of Neuroscience, Weill Cornell Graduate School of the Medical Sciences, New York, NY (A.I.H.); and Department of Radiology, Weill Medical College of Cornell University, New York, NY (A.I.H.)
| | - Kyung K Peck
- From the Departments of Radiology (H.S., B.V., M.E.L., M.J., A.I.H., K.K.P.), Medical Physics (K.K.P.), and Epidemiology-Biostatistics (J.R.F., Z.Z.), Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10065; Department of Radiology, Catholic University of the Sacred Heart-A. Gemelli Hospital, Rome, Italy (M.E.L.); Department of Neuroscience, Weill Cornell Graduate School of the Medical Sciences, New York, NY (A.I.H.); and Department of Radiology, Weill Medical College of Cornell University, New York, NY (A.I.H.)
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van Niftrik CHB, Piccirelli M, Muscas G, Sebök M, Fisher JA, Bozinov O, Stippich C, Valavanis A, Regli L, Fierstra J. The voxel-wise analysis of false negative fMRI activation in regions of provoked impaired cerebrovascular reactivity. PLoS One 2019; 14:e0215294. [PMID: 31059517 PMCID: PMC6502350 DOI: 10.1371/journal.pone.0215294] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Accepted: 03/30/2019] [Indexed: 12/30/2022] Open
Abstract
Task-evoked Blood-oxygenation-level-dependent (BOLD-fMRI) signal activation is widely used to interrogate eloquence of brain areas. However, data interpretation can be improved, especially in regions with absent BOLD-fMRI signal activation. Absent BOLD-fMRI signal activation may actually represent false-negative activation due to impaired cerebrovascular reactivity (BOLD-CVR) of the vascular bed. The relationship between impaired BOLD-CVR and BOLD-fMRI signal activation may be better studied in healthy subjects where neurovascular coupling is known to be intact. Using a model-based prospective end-tidal carbon dioxide (CO2) targeting algorithm, we performed two controlled 3 tesla BOLD-CVR studies on 17 healthy subjects: 1: at the subjects’ individual resting end-tidal CO2 baseline. 2: Around +6.0 mmHg CO2 above the subjects’ individual resting baseline. Two BOLD-fMRI finger-tapping experiments were performed at similar normo- and hypercapnic levels. Relative BOLD fMRI signal activation and t-values were calculated for BOLD-CVR and BOLD-fMRI data. For each component of the cerebral motor-network (precentral gyrus, postcentral gyrus, supplementary motor area, cerebellum und fronto-operculum), the correlation between BOLD-CVR and BOLD-fMRI signal changes and t-values was investigated. Finally, a voxel-wise quantitative analysis of the impact of BOLD-CVR on BOLD-fMRI was performed. For the motor-network, the linear correlation coefficient between BOLD-CVR and BOLD-fMRI t-values were significant (p<0.01) and in the range 0.33–0.55, similar to the correlations between the CVR and fMRI Δ%signal (p<0.05; range 0.34–0.60). The linear relationship between CVR and fMRI is challenged by our voxel-wise analysis of Δ%signal and t-value change between normo- and hypercapnia. Our main finding is that BOLD fMRI signal activation maps are markedly dampened in the presence of impaired BOLD-CVR and highlights the importance of a complementary BOLD-CVR assessment in addition to a task-evoked BOLD fMRI to identify brain areas at risk for false-negative BOLD-fMRI signal activation.
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Affiliation(s)
- Christiaan Hendrik Bas van Niftrik
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- * E-mail:
| | - Marco Piccirelli
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Neuroradiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Giovanni Muscas
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Neurosurgery, Careggi University Hospital, Florence, University of Florence, Florence, Italy
| | - Martina Sebök
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Joseph Arnold Fisher
- Department of Anesthesiology, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Oliver Bozinov
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Christoph Stippich
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Neuroradiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Antonios Valavanis
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Neuroradiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Luca Regli
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Jorn Fierstra
- Department of Neurosurgery, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
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27
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Agarwal S, Sair HI, Gujar S, Hua J, Lu H, Pillai JJ. Functional Magnetic Resonance Imaging Activation Optimization in the Setting of Brain Tumor-Induced Neurovascular Uncoupling Using Resting-State Blood Oxygen Level-Dependent Amplitude of Low Frequency Fluctuations. Brain Connect 2019; 9:241-250. [PMID: 30547681 DOI: 10.1089/brain.2017.0562] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
The goal of this study was to demonstrate that a novel resting state BOLD ALFF (amplitude of low frequency fluctuations)-based correction method can substantially enhance the detectability of motor task activation in the presence of tumor-induced neurovascular uncoupling (NVU). Twelve de novo brain tumor patients who underwent comprehensive clinical BOLD fMRI exams including task fMRI and resting state fMRI (rsfMRI) were evaluated. Each patient displayed decreased/absent task fMRI activation in the ipsilesional primary motor cortex in the absence of corresponding motor deficit or suboptimal task performance, consistent with NVU. Z-score maps for the motor tasks were obtained from general linear model (GLM) analysis (reflecting motor activation vs. rest). ALFF maps were calculated from rsfMRI data. Precentral and postcentral gyri in contralesional (CL) and ipsilesional (IL) hemispheres were parcellated using an Automated Anatomical Labeling (AAL) template for each patient. A novel ALFF-based correction method was used to identify the NVU affected voxels in the ipsilesional primary motor cortex (PMC), and a correction factor was applied to normalize the baseline Z-scores for these voxels. In all cases, substantially greater activation was seen on post-ALFF correction motor activation maps within the ipsilesional precentral gyri than in the pre-ALFF correction activation maps. We have demonstrated the feasibility of a new resting state ALFF-based technique for effective correction of brain tumor-related NVU in the primary motor cortex.
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Affiliation(s)
- Shruti Agarwal
- 1 Divisions of Neuroradiology and Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Haris I Sair
- 1 Divisions of Neuroradiology and Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Sachin Gujar
- 1 Divisions of Neuroradiology and Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Jun Hua
- 2 Divisions of MR Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,3 F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Hanzhang Lu
- 2 Divisions of MR Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,3 F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland
| | - Jay J Pillai
- 1 Divisions of Neuroradiology and Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,4 Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland
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28
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Wu G, Shi Z, Chen Y, Wang Y, Yu J, Lv X, Chen L, Ju X, Chen Z. A sparse representation-based radiomics for outcome prediction of higher grade gliomas. Med Phys 2018; 46:250-261. [PMID: 30418680 DOI: 10.1002/mp.13288] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2018] [Revised: 10/29/2018] [Accepted: 10/30/2018] [Indexed: 12/24/2022] Open
Abstract
PURPOSE Accurately predicting outcome (i.e., overall survival (OS) time) for higher grade glioma (HGG) has great clinical value and would provide optimized guidelines for treatment planning. Radiomics focuses on revealing underlying pathophysiological information in biomedical images for disease analysis and demonstrates promising prognostic clinical performance. In this paper, we propose a novel sparse representation-based radiomics framework to predict if HGG patients would have long or short OS time. METHODS First, taking advantages of the scale invariant feature transform (SIFT) feature in image characterizing, we developed a sparse representation-based method to convert a local SIFT descriptor into a global tumor feature. Next, because preserving sample structure is beneficial for feature selection, we proposed a locality preserving projection and sparse representation-combined feature selection method to select more discriminative features for tumor classification. Finally, we employed a multifeature collaborative sparse representation classification to combine the information of multimodal images to classify OS time. RESULTS Three experiments were performed on the two datasets provided by different institutions. Specifically, the proposed model was trained and independently tested on dataset 1 (135 subjects), on dataset 2 (86 subjects), and on the combination of dataset 1 and dataset 2, respectively. Experimental results demonstrated that the proposed method achieved encouraging prediction performance, exhibiting a testing accuracy of 93.33% on dataset 1 (one modality), 92.31% on dataset 2 (two modalities), and 87.93% on the combined dataset (one modality). CONCLUSIONS The sparse representation theory provides reasonable solutions to feature extraction, feature selection, and classification for radiomics. This study provides a promising tool to enhance the prediction performance of HGG patient's outcome.
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Affiliation(s)
- Guoqing Wu
- Department of Electronic Engineering, Fudan University, Shanghai, 200433, China
| | - Zhifeng Shi
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, 200433, China
| | - Yinsheng Chen
- Department of Neurosurgery/Neuro-oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510000, China
| | - Yuanyuan Wang
- Department of Electronic Engineering, Fudan University and Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai, Shanghai, 200433, China
| | - Jinhua Yu
- Department of Electronic Engineering, Fudan University and Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai, Shanghai, 200433, China
| | - Xiaofei Lv
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510000, China
| | - Liang Chen
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, 200433, China
| | - Xue Ju
- Department of Neurosurgery/Neuro-oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510000, China
| | - Zhongping Chen
- Department of Neurosurgery/Neuro-oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510000, China
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29
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Agarwal S, Sair HI, Pillai JJ. Limitations of Resting-State Functional MR Imaging in the Setting of Focal Brain Lesions. Neuroimaging Clin N Am 2018; 27:645-661. [PMID: 28985935 DOI: 10.1016/j.nic.2017.06.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Methods of image acquisition and analysis for resting-state functional MR imaging (rsfMR imaging) are still evolving. Neurovascular uncoupling and susceptibility artifact are important confounds of rsfMR imaging in the setting of focal brain lesions such as brain tumors. This article reviews the detection of these confounds using rsfMR imaging metrics in the setting of focal brain lesions. In the near future, with the wide range of ongoing research in rsfMR imaging, these issues likely will be overcome and will open new windows into brain function and connectivity.
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Affiliation(s)
- Shruti Agarwal
- Division of Neuroradiology, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Phipps B-100, 1800 Orleans Street, Baltimore, MD 21287, USA
| | - Haris I Sair
- Division of Neuroradiology, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Phipps B-100, 1800 Orleans Street, Baltimore, MD 21287, USA
| | - Jay J Pillai
- Division of Neuroradiology, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Phipps B-100, 1800 Orleans Street, Baltimore, MD 21287, USA.
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30
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Agarwal S, Lu H, Pillai JJ. Value of Frequency Domain Resting-State Functional Magnetic Resonance Imaging Metrics Amplitude of Low-Frequency Fluctuation and Fractional Amplitude of Low-Frequency Fluctuation in the Assessment of Brain Tumor-Induced Neurovascular Uncoupling. Brain Connect 2018; 7:382-389. [PMID: 28657344 DOI: 10.1089/brain.2016.0480] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The aim of this study was to explore whether the phenomenon of brain tumor-related neurovascular uncoupling (NVU) in resting-state blood oxygen level-dependent functional magnetic resonance imaging (BOLD fMRI) (rsfMRI) may also affect the resting-state fMRI (rsfMRI) frequency domain metrics the amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF). Twelve de novo brain tumor patients, who underwent clinical fMRI examinations, including task-based fMRI (tbfMRI) and rsfMRI, were included in this Institutional Review Board-approved study. Each patient displayed decreased/absent tbfMRI activation in the primary ipsilesional (IL) sensorimotor cortex in the absence of a corresponding motor deficit or suboptimal task performance, consistent with NVU. Z-score maps for the motor tasks were obtained from general linear model analysis (reflecting motor activation vs. rest). Seed-based correlation analysis (SCA) maps of sensorimotor network, ALFF, and fALFF were calculated from rsfMRI data. Precentral and postcentral gyri in contralesional (CL) and IL hemispheres were parcellated using an automated anatomical labeling template for each patient. Region of interest (ROI) analysis was performed on four maps: tbfMRI, SCA, ALFF, and fALFF. Voxel values in the CL and IL ROIs of each map were divided by the corresponding global mean of ALFF and fALFF in the cortical brain tissue. Group analysis revealed significantly decreased IL ALFF (p = 0.02) and fALFF (p = 0.03) metrics compared with CL ROIs, consistent with similar findings of significantly decreased IL BOLD signal for tbfMRI (p = 0.0005) and SCA maps (p = 0.0004). The frequency domain metrics ALFF and fALFF may be markers of lesion-induced NVU in rsfMRI similar to previously reported alterations in tbfMRI activation and SCA-derived resting-state functional connectivity maps.
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Affiliation(s)
- Shruti Agarwal
- 1 Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine , Baltimore, Maryland
| | - Hanzhang Lu
- 1 Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine , Baltimore, Maryland.,2 Division of MR Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine , Baltimore, Maryland
| | - Jay J Pillai
- 1 Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine , Baltimore, Maryland.,3 Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland
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31
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Liu P, De Vis JB, Lu H. Cerebrovascular reactivity (CVR) MRI with CO2 challenge: A technical review. Neuroimage 2018; 187:104-115. [PMID: 29574034 DOI: 10.1016/j.neuroimage.2018.03.047] [Citation(s) in RCA: 177] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Revised: 02/06/2018] [Accepted: 03/19/2018] [Indexed: 11/16/2022] Open
Abstract
Cerebrovascular reactivity (CVR) is an indicator of cerebrovascular reserve and provides important information about vascular health in a range of brain conditions and diseases. Unlike steady-state vascular parameters, such as cerebral blood flow (CBF) and cerebral blood volume (CBV), CVR measures the ability of cerebral vessels to dilate or constrict in response to challenges or maneuvers. Therefore, CVR mapping requires a physiological challenge while monitoring the corresponding hemodynamic changes in the brain. The present review primarily focuses on methods that use CO2 inhalation as a physiological challenge while monitoring changes in hemodynamic MRI signals. CO2 inhalation has been increasingly used in CVR mapping in recent literature due to its potency in causing vasodilation, rapid onset and cessation of the effect, as well as advances in MRI-compatible gas delivery apparatus. In this review, we first discuss the physiological basis of CVR mapping using CO2 inhalation. We then review the methodological aspects of CVR mapping, including gas delivery apparatus, the timing paradigm of the breathing challenge, the MRI imaging sequence, and data analysis. In addition, we review alternative approaches for CVR mapping that do not require CO2 inhalation.
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Affiliation(s)
- Peiying Liu
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, United States.
| | - Jill B De Vis
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, United States
| | - Hanzhang Lu
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, United States; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, 21287, United States; F.M. Kirby Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, 21205, United States
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32
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Hsu AL, Hou P, Johnson JM, Wu CW, Noll KR, Prabhu SS, Ferguson SD, Kumar VA, Schomer DF, Hazle JD, Chen JH, Liu HL. IClinfMRI Software for Integrating Functional MRI Techniques in Presurgical Mapping and Clinical Studies. Front Neuroinform 2018; 12:11. [PMID: 29593520 PMCID: PMC5854683 DOI: 10.3389/fninf.2018.00011] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Accepted: 02/23/2018] [Indexed: 01/25/2023] Open
Abstract
Task-evoked and resting-state (rs) functional magnetic resonance imaging (fMRI) techniques have been applied to the clinical management of neurological diseases, exemplified by presurgical localization of eloquent cortex, to assist neurosurgeons in maximizing resection while preserving brain functions. In addition, recent studies have recommended incorporating cerebrovascular reactivity (CVR) imaging into clinical fMRI to evaluate the risk of lesion-induced neurovascular uncoupling (NVU). Although each of these imaging techniques possesses its own advantage for presurgical mapping, a specialized clinical software that integrates the three complementary techniques and promptly outputs the analyzed results to radiology and surgical navigation systems in a clinical format is still lacking. We developed the Integrated fMRI for Clinical Research (IClinfMRI) software to facilitate these needs. Beyond the independent processing of task-fMRI, rs-fMRI, and CVR mapping, IClinfMRI encompasses three unique functions: (1) supporting the interactive rs-fMRI mapping while visualizing task-fMRI results (or results from published meta-analysis) as a guidance map, (2) indicating/visualizing the NVU potential on analyzed fMRI maps, and (3) exporting these advanced mapping results in a Digital Imaging and Communications in Medicine (DICOM) format that are ready to export to a picture archiving and communication system (PACS) and a surgical navigation system. In summary, IClinfMRI has the merits of efficiently translating and integrating state-of-the-art imaging techniques for presurgical functional mapping and clinical fMRI studies.
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Affiliation(s)
- Ai-Ling Hsu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.,Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
| | - Ping Hou
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jason M Johnson
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Changwei W Wu
- Graduate Institute of Humanities in Medicine, Taipei Medical University, Taipei, Taiwan
| | - Kyle R Noll
- Section of Neuropsychology, Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Sujit S Prabhu
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Sherise D Ferguson
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Vinodh A Kumar
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Donald F Schomer
- Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - John D Hazle
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jyh-Horng Chen
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
| | - Ho-Ling Liu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
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33
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Hadjiabadi DH, Pung L, Zhang J, Ward BD, Lim WT, Kalavar M, Thakor NV, Biswal BB, Pathak AP. Brain tumors disrupt the resting-state connectome. NEUROIMAGE-CLINICAL 2018; 18:279-289. [PMID: 29876248 PMCID: PMC5987800 DOI: 10.1016/j.nicl.2018.01.026] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/06/2017] [Revised: 01/15/2018] [Accepted: 01/20/2018] [Indexed: 01/18/2023]
Abstract
Brain tumor patients often experience functional deficits that extend beyond the tumor site. While resting-state functional MRI (rsfMRI) has been used to map such functional connectivity changes in brain tumor patients, the interplay between abnormal tumor vasculature and the rsfMRI signal is still not well understood. Therefore, there is an exigent need for new tools to elucidate how the blood‑oxygenation-level-dependent (BOLD) rsfMRI signal is modulated in brain cancer. In this initial study, we explore the utility of a preclinical model for quantifying brain tumor-induced changes on the rsfMRI signal and resting-state brain connectivity. We demonstrate that brain tumors induce brain-wide alterations of resting-state networks that extend to the contralateral hemisphere, accompanied by global attenuation of the rsfMRI signal. Preliminary histology suggests that some of these alterations in brain connectivity may be attributable to tumor-related remodeling of the neurovasculature. Moreover, this work recapitulates clinical rsfMRI findings from brain tumor patients in terms of the effects of tumor size on the neurovascular microenvironment. Collectively, these results lay the foundation of a preclinical platform for exploring the usefulness of rsfMRI as a potential new biomarker in patients with brain cancer.
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Affiliation(s)
- Darian H Hadjiabadi
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Leland Pung
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jiangyang Zhang
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - B D Ward
- Department of Biophysics, The Medical College of Wisconsin, Milwaukee, WI, USA
| | - Woo-Taek Lim
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Meghana Kalavar
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nitish V Thakor
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Bharat B Biswal
- Department of Biomedical Engineering, The New Jersey Institute of Technology, Newark NJ, USA
| | - Arvind P Pathak
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA; Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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34
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Agarwal S, Sair HI, Pillai JJ. The Resting-State Functional Magnetic Resonance Imaging Regional Homogeneity Metrics-Kendall's Coefficient of Concordance-Regional Homogeneity and Coherence-Regional Homogeneity-Are Valid Indicators of Tumor-Related Neurovascular Uncoupling. Brain Connect 2018; 7:228-235. [PMID: 28363248 DOI: 10.1089/brain.2016.0482] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The aim of this study is to determine whether regional homogeneity (ReHo) of resting-state blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (rsfMRI) data based on Kendall's coefficient of concordance (KCC-ReHo) and coherence (Cohe-ReHo) metrics may allow detection of brain tumor-induced neurovascular uncoupling (NVU) in the sensorimotor network similar to findings in standard motor task-based BOLD fMRI (tbfMRI) activation. Twelve de novo brain tumor patients undergoing clinical fMRI exams (tbfMRI and rsfMRI) were included in this Institutional Review Board (IRB)-approved study. Each patient displayed decreased/absent tbfMRI activation in the primary ipsilesional sensorimotor cortex in the absence of corresponding motor deficit or suboptimal task performance, consistent with NVU. Z-score maps for motor tasks were obtained from the general linear model (GLM) analysis (reflecting motor activation vs. rest). KCC-ReHo and Cohe-ReHo maps were calculated from rsfMRI data. Precentral and postcentral gyri in contralesional (CL) and ipsilesional (IL) hemispheres were parcellated using an automated anatomical labeling (AAL) template for each patient. Similar region of interest (ROI) analysis was performed on tbfMRI, KCC-ReHo, and Cohe-ReHo maps to allow direct comparison of results. Voxel values in CL and IL ROIs of each map were divided by the corresponding global mean of KCC-ReHo and Cohe-ReHo in bihemispheric cortical brain tissue. Group analysis revealed significantly decreased IL mean KCC-ReHo (p = 0.02) and Cohe-ReHo (p = 0.04) metrics compared with respective values in the CL ROIs, consistent with similar findings of significantly decreased ipsilesional BOLD signal for tbfMRI (p = 0.0005). Ipsilesional abnormalities in ReHo derived from rsfMRI may serve as potential indicators of NVU in patients with brain tumors and other resectable brain lesions; as such, ReHo findings may complement findings on tbfMRI used for presurgical planning.
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Affiliation(s)
- Shruti Agarwal
- Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine , Baltimore, Maryland
| | - Haris I Sair
- Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine , Baltimore, Maryland
| | - Jay J Pillai
- Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine , Baltimore, Maryland
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35
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Wu G, Wang Y, Yu J. Overall Survival Time Prediction for High Grade Gliomas Based on Sparse Representation Framework. BRAINLESION: GLIOMA, MULTIPLE SCLEROSIS, STROKE AND TRAUMATIC BRAIN INJURIES 2018. [DOI: 10.1007/978-3-319-75238-9_7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
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36
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Pak RW, Hadjiabadi DH, Senarathna J, Agarwal S, Thakor NV, Pillai JJ, Pathak AP. Implications of neurovascular uncoupling in functional magnetic resonance imaging (fMRI) of brain tumors. J Cereb Blood Flow Metab 2017; 37:3475-3487. [PMID: 28492341 PMCID: PMC5669348 DOI: 10.1177/0271678x17707398] [Citation(s) in RCA: 66] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Functional magnetic resonance imaging (fMRI) serves as a critical tool for presurgical mapping of eloquent cortex and changes in neurological function in patients diagnosed with brain tumors. However, the blood-oxygen-level-dependent (BOLD) contrast mechanism underlying fMRI assumes that neurovascular coupling remains intact during brain tumor progression, and that measured changes in cerebral blood flow (CBF) are correlated with neuronal function. Recent preclinical and clinical studies have demonstrated that even low-grade brain tumors can exhibit neurovascular uncoupling (NVU), which can confound interpretation of fMRI data. Therefore, to avoid neurosurgical complications, it is crucial to understand the biophysical basis of NVU and its impact on fMRI. Here we review the physiology of the neurovascular unit, how it is remodeled, and functionally altered by brain cancer cells. We first discuss the latest findings about the components of the neurovascular unit. Next, we synthesize results from preclinical and clinical studies to illustrate how brain tumor induced NVU affects fMRI data interpretation. We examine advances in functional imaging methods that permit the clinical evaluation of brain tumors with NVU. Finally, we discuss how the suppression of anomalous tumor blood vessel formation with antiangiogenic therapies can "normalize" the brain tumor vasculature, and potentially restore neurovascular coupling.
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Affiliation(s)
- Rebecca W Pak
- 1 Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, USA
| | - Darian H Hadjiabadi
- 1 Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, USA
| | - Janaka Senarathna
- 1 Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, USA
| | - Shruti Agarwal
- 2 Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, USA
| | - Nitish V Thakor
- 1 Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, USA
| | - Jay J Pillai
- 2 Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, USA
| | - Arvind P Pathak
- 1 Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, USA.,2 Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, USA.,3 Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, USA
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van Niftrik CHB, Piccirelli M, Bozinov O, Pangalu A, Fisher JA, Valavanis A, Luft AR, Weller M, Regli L, Fierstra J. Iterative analysis of cerebrovascular reactivity dynamic response by temporal decomposition. Brain Behav 2017; 7:e00705. [PMID: 28948064 PMCID: PMC5607533 DOI: 10.1002/brb3.705] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2016] [Revised: 02/28/2017] [Accepted: 03/01/2017] [Indexed: 12/24/2022] Open
Abstract
OBJECTIVE To improve quantitative cerebrovascular reactivity (CVR) measurements and CO 2 arrival times, we present an iterative analysis capable of decomposing different temporal components of the dynamic carbon dioxide- Blood Oxygen-Level Dependent (CO 2-BOLD) relationship. EXPERIMENTAL DESIGN Decomposition of the dynamic parameters included a redefinition of the voxel-wise CO 2 arrival time, and a separation from the vascular response to a stepwise increase in CO 2 (Delay to signal Plateau - DTP) and a decrease in CO 2 (Delay to signal Baseline -DTB). Twenty-five (normal) datasets, obtained from BOLD MRI combined with a standardized pseudo-square wave CO 2 change, were co-registered to generate reference atlases for the aforementioned dynamic processes to score the voxel-by-voxel deviation probability from normal range. This analysis is further illustrated in two subjects with unilateral carotid artery occlusion using these reference atlases. PRINCIPAL OBSERVATIONS We have found that our redefined CO 2 arrival time resulted in the best data fit. Additionally, excluding both dynamic BOLD phases (DTP and DTB) resulted in a static CVR, that is maximal response, defined as CVR calculated only over a normocapnic and hypercapnic calibrated plateau. CONCLUSION Decomposition and novel iterative modeling of different temporal components of the dynamic CO 2-BOLD relationship improves quantitative CVR measurements.
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Affiliation(s)
- Christiaan Hendrik Bas van Niftrik
- Department of NeurosurgeryUniversity Hospital ZurichUniversity of ZurichZurichSwitzerland
- Clinical Neuroscience CenterUniversity Hospital ZurichZurichSwitzerland
| | - Marco Piccirelli
- Clinical Neuroscience CenterUniversity Hospital ZurichZurichSwitzerland
- Department of NeuroradiologyUniversity Hospital ZurichUniversity of ZurichZurichSwitzerland
| | - Oliver Bozinov
- Department of NeurosurgeryUniversity Hospital ZurichUniversity of ZurichZurichSwitzerland
- Clinical Neuroscience CenterUniversity Hospital ZurichZurichSwitzerland
| | - Athina Pangalu
- Clinical Neuroscience CenterUniversity Hospital ZurichZurichSwitzerland
- Department of NeuroradiologyUniversity Hospital ZurichUniversity of ZurichZurichSwitzerland
| | - Joseph A. Fisher
- Department of AnesthesiologyUniversity Health NetworkUniversity of TorontoTorontoONCanada
| | - Antonios Valavanis
- Clinical Neuroscience CenterUniversity Hospital ZurichZurichSwitzerland
- Department of NeuroradiologyUniversity Hospital ZurichUniversity of ZurichZurichSwitzerland
| | - Andreas R. Luft
- Clinical Neuroscience CenterUniversity Hospital ZurichZurichSwitzerland
- Department of NeurologyUniversity Hospital ZurichUniversity of ZurichZurichSwitzerland
- Cereneo Center for Neurology and RehabilitationVitznauSwitzerland
| | - Michael Weller
- Clinical Neuroscience CenterUniversity Hospital ZurichZurichSwitzerland
- Department of NeurologyUniversity Hospital ZurichUniversity of ZurichZurichSwitzerland
| | - Luca Regli
- Department of NeurosurgeryUniversity Hospital ZurichUniversity of ZurichZurichSwitzerland
- Clinical Neuroscience CenterUniversity Hospital ZurichZurichSwitzerland
| | - Jorn Fierstra
- Department of NeurosurgeryUniversity Hospital ZurichUniversity of ZurichZurichSwitzerland
- Clinical Neuroscience CenterUniversity Hospital ZurichZurichSwitzerland
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Black DF, Vachha B, Mian A, Faro SH, Maheshwari M, Sair HI, Petrella JR, Pillai JJ, Welker K. American Society of Functional Neuroradiology-Recommended fMRI Paradigm Algorithms for Presurgical Language Assessment. AJNR Am J Neuroradiol 2017; 38:E65-E73. [PMID: 28860215 DOI: 10.3174/ajnr.a5345] [Citation(s) in RCA: 97] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
INTRODUCTION Functional MR imaging is increasingly being used for presurgical language assessment in the treatment of patients with brain tumors, epilepsy, vascular malformations, and other conditions. The inherent complexity of fMRI, which includes numerous processing steps and selective analyses, is compounded by institution-unique approaches to patient training, paradigm choice, and an eclectic array of postprocessing options from various vendors. Consequently, institutions perform fMRI in such markedly different manners that data sharing, comparison, and generalization of results are difficult. The American Society of Functional Neuroradiology proposes widespread adoption of common fMRI language paradigms as the first step in countering this lost opportunity to advance our knowledge and improve patient care. LANGUAGE PARADIGM REVIEW PROCESS A taskforce of American Society of Functional Neuroradiology members from multiple institutions used a broad literature review, member polls, and expert opinion to converge on 2 sets of standard language paradigms that strike a balance between ease of application and clinical usefulness. ASFNR RECOMMENDATIONS The taskforce generated an adult language paradigm algorithm for presurgical language assessment including the following tasks: Sentence Completion, Silent Word Generation, Rhyming, Object Naming, and/or Passive Story Listening. The pediatric algorithm includes the following tasks: Sentence Completion, Rhyming, Antonym Generation, or Passive Story Listening. DISCUSSION Convergence of fMRI language paradigms across institutions offers the first step in providing a "Rosetta Stone" that provides a common reference point with which to compare and contrast the usefulness and reliability of fMRI data. From this common language task battery, future refinements and improvements are anticipated, particularly as objective measures of reliability become available. Some commonality of practice is a necessary first step to develop a foundation on which to improve the clinical utility of this field.
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Affiliation(s)
- D F Black
- From the Mayo Clinic (D.F.B., K.W.), Rochester Minnesota
| | - B Vachha
- Memorial Sloan Kettering Cancer Center (B.V.), New York, New York
| | - A Mian
- Boston University School of Medicine (A.M.), Boston, Massachusetts
| | - S H Faro
- Johns Hopkins University School of Medicine and the Johns Hopkins Hospital (S.H.F., H.I.S., J.J.P.), Baltimore, Maryland
| | - M Maheshwari
- Children's Hospital of Wisconsin (M.M.), Milwaukee, Wisconsin
| | - H I Sair
- Johns Hopkins University School of Medicine and the Johns Hopkins Hospital (S.H.F., H.I.S., J.J.P.), Baltimore, Maryland
| | - J R Petrella
- Duke University School of Medicine, (J.R.P.) Durham, North Carolina
| | - J J Pillai
- Johns Hopkins University School of Medicine and the Johns Hopkins Hospital (S.H.F., H.I.S., J.J.P.), Baltimore, Maryland
| | - K Welker
- From the Mayo Clinic (D.F.B., K.W.), Rochester Minnesota
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Para AE, Sam K, Poublanc J, Fisher JA, Crawley AP, Mikulis DJ. Invalidation of fMRI experiments secondary to neurovascular uncoupling in patients with cerebrovascular disease. J Magn Reson Imaging 2017; 46:1448-1455. [PMID: 28152241 DOI: 10.1002/jmri.25639] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2016] [Accepted: 01/03/2017] [Indexed: 12/29/2022] Open
Abstract
PURPOSE Blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is a technique used to infer neuronal activity from the observed changes in blood flow. Cerebrovascular reactivity (CVR) is the ability of arterioles to increase blood flow in response to vasodilatory stimulus. We hypothesize that in areas of disease where there is exhausted vascular reserve and impaired CVR there will be diminished blood flow response following neuronal activation, and that these areas would appear as false-negative tests on BOLD fMRI. MATERIALS AND METHODS Patients with steno-occlusive disease and unilateral hemodynamic impairment received a standardized hypercapnic stimuli while being imaged with BOLD fMRI to generate CVR maps. These were compared to traditional BOLD fMRI maps of neuronal activation in the motor cortex in response to a motor task. RESULTS Neuronal activation from the motor task was found to be linearly correlated with CVR (n = 11 patients, R = 0.82). Regions with positive (normal) CVR showed positive activation on BOLD fMRI, while regions with negative CVR had attenuated neuronal activation on BOLD fMRI. CONCLUSION In areas with cerebrovascular disease where CVR is impaired, there is uncoupling of neuronal activation and blood flow that confounds traditional BOLD fMRI. CVR mapping is a noninvasive MRI-based imaging technique that can provide information about the vascular reactivity of the brain that is important to consider when interpreting traditional BOLD fMRI studies. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1448-1455.
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Affiliation(s)
- Andrea E Para
- Department of Medical Imaging, University of Western Ontario, London, Canada.,Division of Neuroradiology, Joint Department of Medical Imaging, University Health Network, Toronto, Canada
| | - Kevin Sam
- Division of Neuroradiology, Joint Department of Medical Imaging, University Health Network, Toronto, Canada
| | - Julien Poublanc
- Division of Neuroradiology, Joint Department of Medical Imaging, University Health Network, Toronto, Canada
| | - Joseph A Fisher
- Department of Anesthesiology, University Health Network and University of Toronto, Toronto, Canada
| | - Adrian P Crawley
- Division of Neuroradiology, Joint Department of Medical Imaging, University Health Network, Toronto, Canada.,Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - David J Mikulis
- Division of Neuroradiology, Joint Department of Medical Imaging, University Health Network, Toronto, Canada.,Department of Medical Imaging, University of Toronto, Toronto, Canada
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Iranmahboob A, Peck KK, Brennan NP, Karimi S, Fisicaro R, Hou B, Holodny AI. Vascular Reactivity Maps in Patients with Gliomas Using Breath-Holding BOLD fMRI. J Neuroimaging 2017; 26:232-9. [PMID: 26250554 DOI: 10.1111/jon.12278] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2015] [Accepted: 05/31/2015] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND AND PURPOSE To evaluate whether breath-holding (BH) blood oxygenation level-dependent (BOLD) fMRI can quantify differences in vascular reactivity (VR), as there is a need for improved contrast mechanisms in gliomas. METHODS 16 patients (gliomas, grade II = 5, III = 2, IV = 9) were evaluated using the BH paradigm: 4-second single deep breath followed by 16 seconds of BH and 40 seconds of regular breathing for five cycles. VR was defined as the difference in BOLD signal between the minimal signal seen at the end of the deep breath and maximal signal seen at the end of BH (peak-to-trough). VR was measured for every voxel and compared for gray versus white matter and tumor versus normal contralateral brain. VR maps were compared to the areas of enhancement and FLAIR/T2 abnormality. RESULTS VR was significantly lower in normal white matter than gray matter (P < .05) and in tumors compared to the normal, contralateral brain (P < 0.002). The area of abnormal VR (1103 ± 659 mm²) was significantly greater (P = .019) than the enhancement (543 ± 530 mm²), but significantly smaller (P = .0011) than the FLAIR abnormality (2363 ± 1232 mm²). However, the variability in the areas of gadolinium contrast enhancement versus VR abnormality indicates that the contrast mechanism elicited by BH (caused by abnormal arteriolar smooth muscles) appears to be fundamentally different from the contrast mechanism of gadolinium enhancement (caused by the presence of "leaky" gap junctions). CONCLUSIONS BH maps based on peak-to-trough can be used to characterize VR in brain tumors. VR maps in brain tumor patients appear to be caused by a different mechanism than gadolinium enhancement.
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Bright MG, Tench CR, Murphy K. Potential pitfalls when denoising resting state fMRI data using nuisance regression. Neuroimage 2016; 154:159-168. [PMID: 28025128 PMCID: PMC5489212 DOI: 10.1016/j.neuroimage.2016.12.027] [Citation(s) in RCA: 74] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2016] [Revised: 12/07/2016] [Accepted: 12/10/2016] [Indexed: 12/15/2022] Open
Abstract
In resting state fMRI, it is necessary to remove signal variance associated with noise sources, leaving cleaned fMRI time-series that more accurately reflect the underlying intrinsic brain fluctuations of interest. This is commonly achieved through nuisance regression, in which the fit is calculated of a noise model of head motion and physiological processes to the fMRI data in a General Linear Model, and the "cleaned" residuals of this fit are used in further analysis. We examine the statistical assumptions and requirements of the General Linear Model, and whether these are met during nuisance regression of resting state fMRI data. Using toy examples and real data we show how pre-whitening, temporal filtering and temporal shifting of regressors impact model fit. Based on our own observations, existing literature, and statistical theory, we make the following recommendations when employing nuisance regression: pre-whitening should be applied to achieve valid statistical inference of the noise model fit parameters; temporal filtering should be incorporated into the noise model to best account for changes in degrees of freedom; temporal shifting of regressors, although merited, should be achieved via optimisation and validation of a single temporal shift. We encourage all readers to make simple, practical changes to their fMRI denoising pipeline, and to regularly assess the appropriateness of the noise model used. By negotiating the potential pitfalls described in this paper, and by clearly reporting the details of nuisance regression in future manuscripts, we hope that the field will achieve more accurate and precise noise models for cleaning the resting state fMRI time-series.
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Affiliation(s)
- Molly G Bright
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, United Kingdom; Division of Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom.
| | - Christopher R Tench
- Division of Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Kevin Murphy
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom; CUBRIC, School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
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Abstract
Cortical reorganization of function due to the growth of an adjacent brain tumor has clearly been demonstrated in a number of surgically proven cases. Such cases demonstrate the unmistakable implications for the neurosurgical treatment of brain tumors, as the cortical function may not reside where one may initially suspect based solely on the anatomical magnetic resonance imaging (MRI). Consequently, preoperative localization of eloquent areas adjacent to a brain tumor is necessary, as this may demonstrate unexpected organization, which may affect the neurosurgical approach to the lesion. However, in interpreting functional MRI studies, the interpreting physician must be cognizant of artifacts, which may limit the accuracy of functional MRI in the setting of brain tumors.
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Nie D, Zhang H, Adeli E, Liu L, Shen D. 3D Deep Learning for Multi-modal Imaging-Guided Survival Time Prediction of Brain Tumor Patients. MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION : MICCAI ... INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION 2016; 9901:212-220. [PMID: 28149967 DOI: 10.1007/978-3-319-46723-8_25] [Citation(s) in RCA: 74] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
High-grade glioma is the most aggressive and severe brain tumor that leads to death of almost 50% patients in 1-2 years. Thus, accurate prognosis for glioma patients would provide essential guidelines for their treatment planning. Conventional survival prediction generally utilizes clinical information and limited handcrafted features from magnetic resonance images (MRI), which is often time consuming, laborious and subjective. In this paper, we propose using deep learning frameworks to automatically extract features from multi-modal preoperative brain images (i.e., T1 MRI, fMRI and DTI) of high-grade glioma patients. Specifically, we adopt 3D convolutional neural networks (CNNs) and also propose a new network architecture for using multi-channel data and learning supervised features. Along with the pivotal clinical features, we finally train a support vector machine to predict if the patient has a long or short overall survival (OS) time. Experimental results demonstrate that our methods can achieve an accuracy as high as 89.9% We also find that the learned features from fMRI and DTI play more important roles in accurately predicting the OS time, which provides valuable insights into functional neuro-oncological applications.
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Affiliation(s)
- Dong Nie
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, USA; Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, USA
| | - Han Zhang
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, USA
| | - Ehsan Adeli
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, USA
| | - Luyan Liu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, USA
| | - Dinggang Shen
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, USA
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Liu P, Welch BG, Li Y, Gu H, King D, Yang Y, Pinho M, Lu H. Multiparametric imaging of brain hemodynamics and function using gas-inhalation MRI. Neuroimage 2016; 146:715-723. [PMID: 27693197 DOI: 10.1016/j.neuroimage.2016.09.063] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2016] [Revised: 09/21/2016] [Accepted: 09/26/2016] [Indexed: 12/30/2022] Open
Abstract
Diagnosis and treatment monitoring of cerebrovascular diseases routinely require hemodynamic imaging of the brain. Current methods either only provide part of the desired information or require the injection of multiple exogenous agents. In this study, we developed a multiparametric imaging scheme for the imaging of brain hemodynamics and function using gas-inhalation MRI. The proposed technique uses a single MRI scan to provide simultaneous measurements of baseline venous cerebral blood volume (vCBV), cerebrovascular reactivity (CVR), bolus arrival time (BAT), and resting-state functional connectivity (fcMRI). This was achieved with a novel, concomitant O2 and CO2 gas inhalation paradigm, rapid MRI image acquisition with a 9.3min BOLD sequence, and an advanced algorithm to extract multiple hemodynamic information from the same dataset. In healthy subjects, CVR and vCBV values were 0.23±0.03%/mmHg and 0.0056±0.0006%/mmHg, respectively, with a strong correlation (r=0.96 for CVR and r=0.91 for vCBV) with more conventional, separate acquisitions that take twice the scan time. In patients with Moyamoya syndrome, CVR in the stenosis-affected flow territories (typically anterior-cerebral-artery, ACA, and middle-cerebral-artery, MCA, territories) was significantly lower than that in posterior-cerebral-artery (PCA), which typically has minimal stenosis, flow territories (0.12±0.06%/mmHg vs. 0.21±0.05%/mmHg, p<0.001). BAT of the gas bolus was significantly longer (p=0.008) in ACA/MCA territories, compared to PCA, and the maps were consistent with the conventional contrast-enhanced CT perfusion method. FcMRI networks were robustly identified from the gas-inhalation MRI data after factoring out the influence of CO2 and O2 on the signal time course. The spatial correspondence between the gas-data-derived fcMRI maps and those using a separate, conventional fcMRI scan was excellent, showing a spatial correlation of 0.58±0.17 and 0.64±0.20 for default mode network and primary visual network, respectively. These findings suggest that advanced gas-inhalation MRI provides reliable measurements of multiple hemodynamic parameters within a clinically acceptable imaging time and is suitable for patient examinations.
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Affiliation(s)
- Peiying Liu
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, United States
| | - Babu G Welch
- Department of Neurological Surgery, UT Southwestern Medical Center, Dallas, TX 75390, United States; Department of Radiology, UT Southwestern Medical Center, Dallas, TX 75390, United States
| | - Yang Li
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, United States; Biomedical Engineering Graduate Program, UT Southwestern Medical Center, Dallas, TX 75390, United States
| | - Hong Gu
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD 21224, United States
| | - Darlene King
- Department of Neurological Surgery, UT Southwestern Medical Center, Dallas, TX 75390, United States
| | - Yihong Yang
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD 21224, United States
| | - Marco Pinho
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX 75390, United States
| | - Hanzhang Lu
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, United States.
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Hypercapnic evaluation of vascular reactivity in healthy aging and acute stroke via functional MRI. NEUROIMAGE-CLINICAL 2016; 12:173-9. [PMID: 27437178 PMCID: PMC4939388 DOI: 10.1016/j.nicl.2016.06.016] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/17/2016] [Revised: 05/26/2016] [Accepted: 06/22/2016] [Indexed: 11/23/2022]
Abstract
Functional MRI (fMRI) is well-established for the study of brain function in healthy populations, although its clinical application has proven more challenging. Specifically, cerebrovascular reactivity (CVR), which allows the assessment of the vascular response that serves as the basis for fMRI, has been shown to be reduced in healthy aging as well as in a range of diseases, including chronic stroke. However, the timing of when this occurs relative to the stroke event is unclear. We used a breath-hold fMRI task to evaluate CVR across gray matter in a group of acute stroke patients (< 10 days from stroke; N = 22) to address this question. These estimates were compared with those from both age-matched (N = 22) and younger (N = 22) healthy controls. As expected, young controls had the greatest mean CVR, as indicated by magnitude and extent of fMRI activation; however, stroke patients did not differ from age-matched controls. Moreover, the ipsilesional and contralesional hemispheres of stroke patients did not differ with respect to any of these measures. These findings suggest that fMRI remains a valid tool within the first few days of a stroke, particularly for group fMRI studies in which findings are compared with healthy subjects of similar age. However, given the relatively high variability in CVR observed in our stroke sample, caution is warranted when interpreting fMRI data from individual patients or a small cohort. We conclude that a breath-hold task can be a useful addition to functional imaging protocols for stroke patients. Breath-holding can be used to assess the validity of fMRI in stroke patients. Vascular reactivity, estimated by breath-hold fMRI, was greatest in young controls. Acute stroke patients and age-matched controls had similar vascular reactivity. Modeling the breath-hold response on an individual basis can improve results.
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Leung J, Kosinski PD, Croal PL, Kassner A. Developmental trajectories of cerebrovascular reactivity in healthy children and young adults assessed with magnetic resonance imaging. J Physiol 2016; 594:2681-9. [PMID: 26847953 DOI: 10.1113/jp271056] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2015] [Accepted: 01/28/2016] [Indexed: 01/13/2023] Open
Abstract
KEY POINTS Cerebrovascular reactivity (CVR) reflects the vasodilatory reserve of cerebral resistance vessels. Normal development in children is associated with significant changes in blood pressure, cerebral blood flow (CBF) and cerebral oxygen metabolism. Therefore, it stands to reason that CVR will also undergo changes during this period. The study acquired magnetic resonance imaging measures of CVR and CBF in healthy children and young adults to trace their changes with age. We found that CVR changes in two phases, increasing with age until the mid-teens, followed by a decrease. Baseline CBF declined steadily with age. We conclude that CVR varies with age during childhood, which prompts future CVR studies involving children to take into account the effect of development. ABSTRACT Cerebrovascular reactivity (CVR) reflects the vasculature's ability to accommodate changes in blood flow demand thereby serving as a critical imaging tool for mapping vascular reserve. Normal development is associated with extensive physiological changes in blood pressure, cerebral blood flow and cerebral metabolic rate of oxygen, all of which can affect CVR. Moreover, the evolution of these physiological parameters is most prominent during childhood. Therefore, the aim of this study was to use non-invasive magnetic resonance imaging (MRI) to characterize the developmental trajectories of CVR in healthy children and young adults, and relate them to changes in cerebral blood flow (CBF). Thirty-four healthy subjects (17 males, 17 females; age 9-30 years) underwent CVR assessment using blood oxygen level-dependent MRI in combination with a computer controlled CO2 stimulus. In addition, baseline CBF was measured with a pulsed arterial spin labelling sequence. CVR exhibited a gradual increase with age in both grey and white matter up to 14.7 years. After this break point, a negative correlation with age was detected. Baseline CBF maintained a consistent negative linear correlation across the entire age range. The significant age-dependent changes in CVR and CBF demonstrate the evolution of cerebral haemodynamics in children and should be taken into consideration. The shift in developmental trajectory of CVR from increasing to decreasing suggests that physiological factors beyond baseline CBF also influence CVR.
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Affiliation(s)
- Jackie Leung
- Department of Physiology and Experimental Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada, M5G 1X8
| | - Przemyslaw D Kosinski
- Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada, M5S 3E2
| | - Paula L Croal
- Department of Physiology and Experimental Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada, M5G 1X8
| | - Andrea Kassner
- Department of Physiology and Experimental Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada, M5G 1X8.,Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada, M5S 3E2
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Fierstra J, Burkhardt JK, van Niftrik CHB, Piccirelli M, Pangalu A, Kocian R, Neidert MC, Valavanis A, Regli L, Bozinov O. Blood oxygen-level dependent functional assessment of cerebrovascular reactivity: Feasibility for intraoperative 3 Tesla MRI. Magn Reson Med 2016; 77:806-813. [PMID: 26918794 DOI: 10.1002/mrm.26135] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2015] [Revised: 11/29/2015] [Accepted: 12/26/2015] [Indexed: 11/10/2022]
Abstract
PURPOSE To assess the feasibility of functional blood oxygen-level dependent (BOLD) MRI to evaluate intraoperative cerebrovascular reactivity (CVR) at 3 Tesla field strength. METHODS Ten consecutive neurosurgical subjects scheduled for a clinical intraoperative MRI examination were enrolled in this study. In addition to the clinical protocol a BOLD sequence was implemented with three cycles of 44 s apnea to calculate CVR values on a voxel-by-voxel basis throughout the brain. The CVR range was then color-coded and superimposed on an anatomical volume to create high spatial resolution CVR maps. RESULTS Ten subjects (mean age 34.8 ± 13.4; 2 females) uneventfully underwent the intraoperative BOLD protocol, with no complications occurring. Whole-brain CVR for all subjects was (mean ± SD) 0.69 ± 0.42, whereas CVR was markedly higher for tumor subjects as compared to vascular subjects, 0.81 ± 0.44 versus 0.33 ± 0.10, respectively. Furthermore, color-coded functional maps could be robustly interpreted for a whole-brain assessment of CVR. CONCLUSION We demonstrate that intraoperative BOLD MRI is feasible in creating functional maps to assess cerebrovascular reactivity throughout the brain in subjects undergoing a neurosurgical procedure. Magn Reson Med 77:806-813, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Jorn Fierstra
- Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | - Jan-Karl Burkhardt
- Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | | | - Marco Piccirelli
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | - Athina Pangalu
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | - Roman Kocian
- Department of Neuro-anesthesia, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | - Marian Christoph Neidert
- Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | - Antonios Valavanis
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | - Luca Regli
- Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
| | - Oliver Bozinov
- Department of Neurosurgery, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Switzerland
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Pinto J, Jorge J, Sousa I, Vilela P, Figueiredo P. Fourier modeling of the BOLD response to a breath-hold task: Optimization and reproducibility. Neuroimage 2016; 135:223-31. [PMID: 26908316 DOI: 10.1016/j.neuroimage.2016.02.037] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2015] [Revised: 01/09/2016] [Accepted: 02/12/2016] [Indexed: 11/18/2022] Open
Abstract
Cerebrovascular reactivity (CVR) reflects the capacity of blood vessels to adjust their caliber in order to maintain a steady supply of brain perfusion, and it may provide a sensitive disease biomarker. Measurement of the blood oxygen level dependent (BOLD) response to a hypercapnia-inducing breath-hold (BH) task has been frequently used to map CVR noninvasively using functional magnetic resonance imaging (fMRI). However, the best modeling approach for the accurate quantification of CVR maps remains an open issue. Here, we compare and optimize Fourier models of the BOLD response to a BH task with a preparatory inspiration, and assess the test-retest reproducibility of the associated CVR measurements, in a group of 10 healthy volunteers studied over two fMRI sessions. Linear combinations of sine-cosine pairs at the BH task frequency and its successive harmonics were added sequentially in a nested models approach, and were compared in terms of the adjusted coefficient of determination and corresponding variance explained (VE) of the BOLD signal, as well as the number of voxels exhibiting significant BOLD responses, the estimated CVR values, and their test-retest reproducibility. The brain average VE increased significantly with the Fourier model order, up to the 3rd order. However, the number of responsive voxels increased significantly only up to the 2nd order, and started to decrease from the 3rd order onwards. Moreover, no significant relative underestimation of CVR values was observed beyond the 2nd order. Hence, the 2nd order model was concluded to be the optimal choice for the studied paradigm. This model also yielded the best test-retest reproducibility results, with intra-subject coefficients of variation of 12 and 16% and an intra-class correlation coefficient of 0.74. In conclusion, our results indicate that a Fourier series set consisting of a sine-cosine pair at the BH task frequency and its two harmonics is a suitable model for BOLD-fMRI CVR measurements based on a BH task with preparatory inspiration, yielding robust estimates of this important physiological parameter.
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Affiliation(s)
- Joana Pinto
- Institute for Systems and Robotics, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal.
| | - João Jorge
- Institute for Systems and Robotics, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal; Biomedical Imaging Research Center, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Inês Sousa
- Institute for Systems and Robotics, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal; Healthcare Sector, Siemens, S.A., Portugal
| | - Pedro Vilela
- Imaging Department, Hospital da Luz, Lisbon, Portugal
| | - Patrícia Figueiredo
- Institute for Systems and Robotics, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
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Agarwal S, Sair HI, Yahyavi-Firouz-Abadi N, Airan R, Pillai JJ. Neurovascular uncoupling in resting state fMRI demonstrated in patients with primary brain gliomas. J Magn Reson Imaging 2015. [PMID: 26201672 DOI: 10.1002/jmri.25012] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
BACKGROUND To demonstrate that the problem of brain tumor-related neurovascular uncoupling (NVU) is a significant issue with respect to resting state blood oxygen level dependent (BOLD) functional MRI (rsfMRI) similar to task-based BOLD fMRI, in which signal detectability can be compromised by breakdown of normal neurovascular coupling. METHODS We evaluated seven de novo brain tumor patients who underwent resting state fMRI as part of comprehensive clinical fMRI exams at 3 Tesla. For each of the seven patients who demonstrated evidence of NVU on task-based motor fMRI, we performed both an independent component analysis (ICA) and an atlas-based parcellation-based seed correlation analysis (SCA) of the resting state fMRI data. For each patient, ipsilesional (IL) and contralesional (CL) regions of interest (ROIs) comprising primary motor and somatosensory cortices were used to evaluate BOLD signal changes on Z score maps derived from both ICA and SCA analysis for evidence of NVU. A subsequent two-tailed t-test was performed to determine whether statistically significant differences between the two sides were present that were consistent with NVU. RESULTS In seven patients, overall decreased BOLD signal (based on suprathreshold voxels in ICA and SCA-derived Z-score maps) was noted in IL compared with CL ROIs (P < 0.01), consistent with NVU. CONCLUSION We have demonstrated that NVU can result in false negative BOLD signal changes on rsfMRI comparable to previously published findings on standard motor task-based fMRI.
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Affiliation(s)
- Shruti Agarwal
- Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Haris I Sair
- Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Noushin Yahyavi-Firouz-Abadi
- Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Raag Airan
- Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jay J Pillai
- Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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DeYoe EA, Ulmer JL, Mueller WM, Sabsevitz DS, Reitsma DC, Pillai JJ. Imaging of the Functional and Dysfunctional Visual System. Semin Ultrasound CT MR 2015; 36:234-48. [PMID: 26233858 DOI: 10.1053/j.sult.2015.05.015] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Functional magnetic resonance imaging (fMRI) is used clinically to map the visual cortex before brain surgery or other invasive treatments to achieve an optimal balance between therapeutic effect and the avoidance of postoperative vision deficits. Clinically optimized stimuli, analyses, and displays permit identification of cortical subregions supporting high-acuity central vision that is critical for reading and other essential visual functions. A novel data display permits instant appreciation of the functional relationship between the pattern of fMRI brain activation and the pattern of vision loss and preservation within the patient׳s field of view. Neurovascular uncoupling and its detection in the visual cortex are key issues for the interpretation of fMRI results in patients with existing brain pathology.
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Affiliation(s)
- Edgar A DeYoe
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI.
| | - John L Ulmer
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI
| | - Wade M Mueller
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI
| | - David S Sabsevitz
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI
| | | | - Jay J Pillai
- Department of Radiology, Johns Hopkins University, Baltimore, MD
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