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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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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: 1.0] [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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3
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Ahmed SR, Jenabi M, Gene M, Moreno R, Peck KK, Holodny A. Power spectral analysis can determine language laterality from resting-state functional MRI data in healthy controls. J Neuroimaging 2023; 33:661-670. [PMID: 37032593 PMCID: PMC10523910 DOI: 10.1111/jon.13105] [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: 01/11/2023] [Revised: 03/27/2023] [Accepted: 03/27/2023] [Indexed: 04/11/2023] Open
Abstract
BACKGROUND AND PURPOSE Resting-state functional magnetic resonance imaging (rsfMRI) has been proposed as an alternative to task-based fMRI including clinical situations such as preoperative brain tumor planning, due to advantages including ease of performance and time savings. However, one of its drawbacks is the limited ability to accurately lateralize language function. METHODS Using the rsfMRI data of healthy controls, we carried out a power spectra analysis on three regions of interest (ROIs): Broca's area (BA) in the frontal cortex for language, hand motor (HM) area in the primary motor cortex, and the primary visual cortex (V1). Spike removal, motion correction, linear trend removal, and spatial smoothing were applied. Spontaneous low-frequency fluctuations (0.01-0.1 Hz) were filtered to enable functional integration. RESULTS BA showed greater power on the left hemisphere relative to the right (p = .0055), while HM (p = .1563) and V1 (p = .4681) were not statistically significant. A novel index, termed the power laterality index (PLI), computed to estimate the degree of power lateralization for each brain region, revealed a statistically significant difference between BA and V1 (p < .00001), where V1 was used as a control since the primary visual cortex does not lateralize. Validation studies used to compare PLI to a laterality index computed using phonemic fluency, a task-based, language fMRI paradigm, demonstrated good correlation. CONCLUSIONS The power spectra for BA revealed left language lateralization, which was not replicated in HM or V1. This work demonstrates the feasibility and validity of an ROI-based power spectra analysis on rsfMRI data for language lateralization.
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Affiliation(s)
- Syed Rakin Ahmed
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, US
- Harvard Graduate Program in Biophysics, Harvard Medical School, Harvard University, Cambridge, MA, US
- Geisel School of Medicine at Dartmouth, Dartmouth College, Hanover, NH, US
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, US
- Broad Institute of MIT and Harvard, Cambridge, MA, US
| | - Mehrnaz Jenabi
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, US
| | - Madeleine Gene
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, US
| | - Raquel Moreno
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, US
| | - Kyung K. Peck
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, US
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, US
| | - Andrei Holodny
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, US
- Brain Tumor Center, Memorial Sloan Kettering Cancer Center, New York, NY, US
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, US
- Department of Neuroscience, Weill-Cornell Graduate School of the Medical Sciences, New York, NY, US
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4
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Hou X, Guo P, Wang P, Liu P, Lin DDM, Fan H, Li Y, Wei Z, Lin Z, Jiang D, Jin J, Kelly C, Pillai JJ, Huang J, Pinho MC, Thomas BP, Welch BG, Park DC, Patel VM, Hillis AE, Lu H. Deep-learning-enabled brain hemodynamic mapping using resting-state fMRI. NPJ Digit Med 2023; 6:116. [PMID: 37344684 PMCID: PMC10284915 DOI: 10.1038/s41746-023-00859-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 06/09/2023] [Indexed: 06/23/2023] Open
Abstract
Cerebrovascular disease is a leading cause of death globally. Prevention and early intervention are known to be the most effective forms of its management. Non-invasive imaging methods hold great promises for early stratification, but at present lack the sensitivity for personalized prognosis. Resting-state functional magnetic resonance imaging (rs-fMRI), a powerful tool previously used for mapping neural activity, is available in most hospitals. Here we show that rs-fMRI can be used to map cerebral hemodynamic function and delineate impairment. By exploiting time variations in breathing pattern during rs-fMRI, deep learning enables reproducible mapping of cerebrovascular reactivity (CVR) and bolus arrival time (BAT) of the human brain using resting-state CO2 fluctuations as a natural "contrast media". The deep-learning network is trained with CVR and BAT maps obtained with a reference method of CO2-inhalation MRI, which includes data from young and older healthy subjects and patients with Moyamoya disease and brain tumors. We demonstrate the performance of deep-learning cerebrovascular mapping in the detection of vascular abnormalities, evaluation of revascularization effects, and vascular alterations in normal aging. In addition, cerebrovascular maps obtained with the proposed method exhibit excellent reproducibility in both healthy volunteers and stroke patients. Deep-learning resting-state vascular imaging has the potential to become a useful tool in clinical cerebrovascular imaging.
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Affiliation(s)
- Xirui Hou
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Pengfei Guo
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Puyang Wang
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Peiying Liu
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Doris D M Lin
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Hongli Fan
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yang Li
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Zhiliang Wei
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Zixuan Lin
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Dengrong Jiang
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jin Jin
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Catherine Kelly
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jay J Pillai
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Judy Huang
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Marco C Pinho
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Binu P Thomas
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Babu G Welch
- Department of Neurologic Surgery, UT Southwestern Medical Center, Dallas, TX, USA
- Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, USA
| | - Denise C Park
- Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, USA
| | - Vishal M Patel
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Argye E Hillis
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Hanzhang Lu
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
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5
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Chaganti J. Editorial for "Cerebrovascular Reactivity Mapping Using Resting-State Functional MRI in Patients With Gliomas". J Magn Reson Imaging 2022; 56:1872-1873. [PMID: 35393730 DOI: 10.1002/jmri.28192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 03/18/2022] [Indexed: 01/04/2023] Open
Affiliation(s)
- Joga Chaganti
- St Vincent's Hospital, St Vincent's Hospital, 390,Victoria Street, Sydney, NSW, 2100, Australia
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6
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Fang S, Li L, Weng S, Guo Y, Zhong Z, Fan X, Jiang T, Wang Y. Contralesional Sensorimotor Network Participates in Motor Functional Compensation in Glioma Patients. Front Oncol 2022; 12:882313. [PMID: 35530325 PMCID: PMC9072743 DOI: 10.3389/fonc.2022.882313] [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: 02/23/2022] [Accepted: 03/11/2022] [Indexed: 11/18/2022] Open
Abstract
Background Some gliomas in sensorimotor areas induce motor deficits, while some do not. Cortical destruction and reorganization contribute to this phenomenon, but detailed reasons remain unclear. This study investigated the differences of the functional connectivity and topological properties in the contralesional sensorimotor network (cSMN) between patients with motor deficit and those with normal motor function. Methods We retrospectively reviewed 65 patients (32 men) between 2017 and 2020. The patients were divided into four groups based on tumor laterality and preoperative motor status (deficit or non-deficit). Thirty-three healthy controls (18 men) were enrolled after matching for sex, age, and educational status. Graph theoretical measurement was applied to reveal alterations of the topological properties of the cSMN by analyzing resting-state functional MRI. Results The results for patients with different hemispheric gliomas were similar. The clustering coefficient, local efficiency, transitivity, and vulnerability of the cSMN significantly increased in the non-deficit group and decreased in the deficit group compared to the healthy group (p < 0.05). Moreover, the nodes of the motor-related thalamus showed a significantly increased nodal efficiency and nodal local efficiency in the non-deficit group and decreased in the deficit group compared with the healthy group (p < 0.05). Conclusions We posited the existence of two stages of alterations of the preoperative motor status. In the compensatory stage, the cSMN sacrificed stability to acquire high efficiency and to compensate for impaired motor function. With the glioma growing and the motor function being totally damaged, the cSMN returned to a stable state and maintained healthy hemispheric motor function, but with low efficiency.
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Affiliation(s)
- Shengyu Fang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Lianwang Li
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Shimeng Weng
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Yuhao Guo
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Zhang Zhong
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xing Fan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Tao Jiang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Research Unit of Accurate Diagnosis, Treatment and Translational Medicine of Brain Tumors, Chinese Academy of Medical Sciences, Beijing, China
| | - Yinyan Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
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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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Maniar YM, Peck KK, Jenabi M, Gene M, Holodny AI. Functional MRI Shows Altered Deactivation and a Corresponding Decrease in Functional Connectivity of the Default Mode Network in Patients with Gliomas. AJNR Am J Neuroradiol 2021; 42:1505-1512. [PMID: 33985945 DOI: 10.3174/ajnr.a7138] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Accepted: 02/19/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND AND PURPOSE The default mode network normally decreases in activity during externally directed tasks. Although default mode network connectivity is disrupted in numerous brain pathologies, default mode network deactivation has not been studied in patients with brain tumors. We investigated default mode network deactivation with language task-based fMRI by measuring the anticorrelation of a critical default mode network node, the posterior cingulate cortex, in patients with gliomas and controls; furthermore, we examined default mode network functional connectivity in these patients with task-based and resting-state fMRI. MATERIALS AND METHODS In 10 healthy controls and 30 patients with gliomas, the posterior cingulate cortex was identified on task-based fMRI and was used as an ROI to create connectivity maps from task-based and resting-state fMRI data. We compared the average correlation in each default mode network region between patients and controls for each correlation map and stratified patients by tumor location, hemisphere, and grade. RESULTS Patients with gliomas (P = .001) and, in particular, patients with tumors near the posterior default mode network (P < .001) showed less posterior cingulate cortex anticorrelation in task-based fMRI than controls. Patients with both left- and right-hemisphere tumors, as well as those with grade IV tumors, showed significantly lower posterior cingulate cortex anticorrelation than controls (P = .02, .03, and <.001, respectively). Functional connectivity in each default mode network region was not significantly different between task-based and resting-state maps. CONCLUSIONS Task-based fMRI showed impaired deactivation of the default mode network in patients with gliomas. The functional connectivity of the default mode network in both task-based and resting-state fMRI in patients with gliomas using the posterior cingulate cortex identified in task-based fMRI as an ROI for seed-based correlation analysis has strong overlap.
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Affiliation(s)
- Y M Maniar
- From the Department of Radiology (Y.M.M., K.K.P., M.J., M.G., A.I.H.), Memorial Sloan Kettering Cancer Center, New York, New York
| | - K K Peck
- From the Department of Radiology (Y.M.M., K.K.P., M.J., M.G., A.I.H.), Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Medical Physics (K.K.P.), Memorial Sloan Kettering Cancer Center, New York, New York
| | - M Jenabi
- From the Department of Radiology (Y.M.M., K.K.P., M.J., M.G., A.I.H.), Memorial Sloan Kettering Cancer Center, New York, New York
| | - M Gene
- From the Department of Radiology (Y.M.M., K.K.P., M.J., M.G., A.I.H.), Memorial Sloan Kettering Cancer Center, New York, New York
| | - A I Holodny
- From the Department of Radiology (Y.M.M., K.K.P., M.J., M.G., A.I.H.), Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Radiology (A.I.H.), 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
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9
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Petridis PD, Horenstein C, Pereira B, Wu P, Samanamud J, Marie T, Boyett D, Sudhakar T, Sheth SA, McKhann GM, Sisti MB, Bruce JN, Canoll P, Grinband J. BOLD Asynchrony Elucidates Tumor Burden in IDH-Mutated Gliomas. Neuro Oncol 2021; 24:78-87. [PMID: 34214170 DOI: 10.1093/neuonc/noab154] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND Gliomas comprise the most common type of primary brain tumor, are highly invasive, and often fatal. IDH-mutated gliomas are particularly challenging to image and there is currently no clinically accepted method for identifying the extent of tumor burden in these neoplasms. This uncertainty poses a challenge to clinicians who must balance the need to treat the tumor while sparing healthy brain from iatrogenic damage. The purpose of this study was to investigate the feasibility of using resting-state blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) to detect glioma-related asynchrony in vascular dynamics for distinguishing tumor from healthy brain. METHODS Twenty-four stereotactically localized biopsies were obtained during open surgical resection from ten treatment-naïve patients with IDH-mutated gliomas who received standard of care preoperative imaging as well as echo-planar resting-state BOLD fMRI. Signal intensity for BOLD asynchrony and standard of care imaging was compared to cell counts of total cellularity (H&E), tumor density (IDH1 & Sox2), cellular proliferation (Ki67), and neuronal density (NeuN), for each corresponding sample. RESULTS BOLD asynchrony was directly related to total cellularity (H&E, p = 4 x 10 -5), tumor density (IDH1, p = 4 x 10 -5; Sox2, p = 3 x 10 -5), cellular proliferation (Ki67, p = 0.002), and as well as inversely related to neuronal density (NeuN, p = 1 x 10 -4). CONCLUSIONS Asynchrony in vascular dynamics, as measured by resting-state BOLD fMRI, correlates with tumor burden and provides a radiographic delineation of tumor boundaries in IDH-mutated gliomas.
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Affiliation(s)
- Petros D Petridis
- Vagelos College of Physicians & Surgeons, Columbia University, New York, New York USA.,Department of Psychiatry, New York University, New York, New York, USA
| | - Craig Horenstein
- Department of Radiology, School of Medicine at Hofstra/Northwell, Manhasset, New York USA
| | - Brianna Pereira
- Vagelos College of Physicians & Surgeons, Columbia University, New York, New York USA
| | - Peter Wu
- Vagelos College of Physicians & Surgeons, Columbia University, New York, New York USA
| | - Jorge Samanamud
- Department of Neurological Surgery, Columbia University, New York, New York USA
| | - Tamara Marie
- Department of Pediatrics Oncology, Columbia University, New York, New York USA
| | - Deborah Boyett
- Department of Neurological Surgery, Columbia University, New York, New York USA
| | - Tejaswi Sudhakar
- Department of Neurological Surgery, Columbia University, New York, New York USA
| | - Sameer A Sheth
- Department of Neurological Surgery, Baylor College of Medicine, Houston, Texas, USA
| | - Guy M McKhann
- Department of Neurological Surgery, Columbia University, New York, New York USA
| | - Michael B Sisti
- Department of Neurological Surgery, Columbia University, New York, New York USA
| | - Jeffrey N Bruce
- Department of Neurological Surgery, Columbia University, New York, New York USA
| | - Peter Canoll
- Department of Pathology & Cell Biology, Columbia University, New York, New York USA
| | - Jack Grinband
- Department of Radiology, Columbia University, New York, New York, USA.,Department of Psychiatry, Columbia University, New York, New York, USA
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10
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Jalilianhasanpour R, Beheshtian E, Ryan D, Luna LP, Agarwal S, Pillai JJ, Sair HI, Gujar SK. Role of Functional Magnetic Resonance Imaging in the Presurgical Mapping of Brain Tumors. Radiol Clin North Am 2021; 59:377-393. [PMID: 33926684 DOI: 10.1016/j.rcl.2021.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
When planning for brain tumor resection, a balance between maximizing resection and minimizing injury to eloquent brain parenchyma is paramount. The advent of blood oxygenation level-dependent functional magnetic resonance (fMR) imaging has allowed researchers and clinicians to reliably measure physiologic fluctuations in brain oxygenation related to neuronal activity with good spatial resolution. fMR imaging can offer a unique insight into preoperative planning for brain tumors by identifying eloquent areas of the brain affected or spared by the neoplasm. This article discusses the fMR imaging techniques and their applications in neurosurgical planning.
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Affiliation(s)
- Rozita Jalilianhasanpour
- 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
| | - Elham Beheshtian
- 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
| | - Daniel Ryan
- 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
| | - Licia P Luna
- 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
| | - 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
| | - 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
| | - 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, 3400 North Charles Street, Baltimore, MD 21218, USA
| | - Sachin K Gujar
- 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.
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11
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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: 2.7] [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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12
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Manan HA, Franz EA, Yahya N. The utilisation of resting-state fMRI as a pre-operative mapping tool in patients with brain tumours in comparison to task-based fMRI and intraoperative mapping: A systematic review. Eur J Cancer Care (Engl) 2021; 30:e13428. [PMID: 33592671 DOI: 10.1111/ecc.13428] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 01/25/2021] [Accepted: 01/28/2021] [Indexed: 12/13/2022]
Abstract
PURPOSE Resting-state functional Magnetic Resonance Imaging (rs-fMRI) is suggested to be a viable option for pre-operative mapping for patients with brain tumours. However, it remains an open issue whether the tool is useful in the clinical setting compared to task-based fMRI (T-fMRI) and intraoperative mapping. Thus, a systematic review was conducted to investigate the usefulness of this technique. METHODS A systematic literature search of rs-fMRI methods applied as a pre-operative mapping tool was conducted using the PubMed/MEDLINE and Cochrane Library electronic databases following PRISMA guidelines. RESULTS Results demonstrated that 50% (six out of twelve) of the studies comparing rs-fMRI and T-fMRI showed good concordance for both language and sensorimotor networks. In comparison to intraoperative mapping, 86% (six out of seven) studies found a good agreement to rs-fMRI. Finally, 87% (twenty out of twenty-three) studies agreed that rs-fMRI is a suitable and useful pre-operative mapping tool. CONCLUSIONS rs-fMRI is a promising technique for pre-operative mapping in assessing the functional brain areas. However, the agreement between rs-fMRI with other techniques, including T-fMRI and intraoperative maps, is not yet optimal. Studies to ascertain and improve the sophistication in pre-processing of rs-fMRI imaging data are needed.
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Affiliation(s)
- Hanani Abdul Manan
- Makmal Pemprosesan Imej Kefungsian (Functional Image Processing Laboratory, Department of Radiology, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia
| | - Elizabeth A Franz
- Department of Psychology and fMRIotago, University of Otago, Dunedin, New Zealand
| | - Noorazrul Yahya
- Diagnostic Imaging & Radiotherapy Program, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
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13
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Zhang H, Bai X, Diaz MT. The intensity and connectivity of spontaneous brain activity in a language network relate to aging and language. Neuropsychologia 2021; 154:107784. [PMID: 33571489 DOI: 10.1016/j.neuropsychologia.2021.107784] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 01/16/2021] [Accepted: 02/06/2021] [Indexed: 01/03/2023]
Abstract
Neuroimaging studies often either look at functional activation in response to an explicit task, or functional connectivity (i.e., interregional correlations) during resting-state. Few studies have looked at the intensity of brain activity or its relationship with age, behavior, and language. The current study investigated both intensity (i.e., the Amplitude of Low-Frequency Fluctuations, ALFF) and the functional connectivity of spontaneous brain activity during rest and their relationship with age and language. A life-span sample of individuals (N = 152) completed a battery of neuropsychological tests to assess basic cognitive functions and resting-state functional MRI data to assess spontaneous brain activity. Focusing on an extend language network, the mean ALFF and total degree were calculated for this network. We found that increased age was associated with more intense activity (i.e., higher ALFF) but lower within-network connectivity. Additionally, these increases in activity within the language network during resting-state were related to worse language ability, particularly in younger adults, supporting a dedifferentiation account of cognition. Our results support the utility of using resting-state data as an indicator of cognition and support the role of ALFF as a potential biomarker in characterizing the relationships between resting-state brain activity, age, and cognition.
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Affiliation(s)
- Haoyun Zhang
- Social, Life, and Engineering Sciences Imaging Center, The Pennsylvania State University, USA
| | - Xiaoxiao Bai
- Social, Life, and Engineering Sciences Imaging Center, The Pennsylvania State University, USA
| | - Michele T Diaz
- Social, Life, and Engineering Sciences Imaging Center, The Pennsylvania State University, USA; Department of Psychology, The Pennsylvania State University, USA.
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14
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Utility of Preoperative Blood-Oxygen-Level-Dependent Functional MR Imaging in Patients with a Central Nervous System Neoplasm. Neuroimaging Clin N Am 2021; 31:93-102. [PMID: 33220831 PMCID: PMC10040207 DOI: 10.1016/j.nic.2020.09.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Functional neuroimaging provides means to understand the relationship between brain structure and associated functions. Functional MR (fMR) imaging can offer a unique insight into preoperative planning for central nervous system (CNS) neoplasms by identifying areas of the brain effected or spared by the neoplasm. BOLD (blood-oxygen-level-dependent) fMR imaging can be reliably used to map eloquent cortex presurgically and is sufficiently accurate for neurosurgical planning. In patients with brain tumors undergoing neurosurgical intervention, fMR imaging can decrease postoperative morbidity. This article discusses the applications, significance, and interpretation of BOLD fMR imaging, and its applications in presurgical planning for CNS neoplasms.
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15
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Li M, Liu Q, Guo R, Yang S, Jiang P, Chen X, Wu J, Cao Y, Wang S. Perinidal Angiogenesis Is a Predictor for Neurovascular Uncoupling in the Periphery of Brain Arteriovenous Malformations: A Task-Based and Resting-State fMRI Study. J Magn Reson Imaging 2020; 54:186-196. [PMID: 33345355 DOI: 10.1002/jmri.27469] [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: 10/01/2020] [Revised: 11/25/2020] [Accepted: 11/25/2020] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Potential neurovascular uncoupling (NVU) related to perinidal angiogenesis (PA) of brain arteriovenous malformations (AVMs) may cause inappropriate presurgical mapping using functional magnetic resonance imaging (fMRI), resulting in overconfident resection and postoperative morbidity. PURPOSE To evaluate the potential impact of PA upon fMRI blood oxygen level-dependent signal in the periphery of AVMs. STUDY TYPE Prospective. POPULATION Twenty-one patients with AVMs located in the primary sensorimotor cortex (SM1) undergoing task-based fMRI (hand motor), and 19 patients with supratentorial AVMs undergoing resting-state fMRI. FIELD STRENGTH/SEQUENCE 3.0T, echo-planar, time-of-flight, and magnetization-prepared rapid gradient-echo. ASSESSMENT The presence of PA was determined by three observers (Y.C., J.W., and X.C.) according to digital subtraction angiography and MR angiography. Interhemispheric asymmetry of fMRI activations contralateral to hand movements was evaluated with the interhemispheric ratio of the average t-value within ipsilesional SM1 to contralesional SM1. Regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFF) were extracted from ring-shaped perinidal regions and contralateral homologous regions, and the corresponding interhemispheric ratios were calculated. The effect of PA on the interhemispheric asymmetry of motor activations, ReHo, and fALFF was estimated. STATISTICAL TESTS Pearson analysis, paired and independent t-test, multiple linear regression, Friedman test, and factorial analysis of variance were used. RESULTS Motor activations were significantly reduced in ipsilesional SM1 compared to contralesional SM1 (P < 0.05). The presence of PA was the independent predictor of activation loss in ipsilateral SM1(P < 0.05). Furthermore, perinidal regions exhibited reduced ReHo compared to the homologous regions (P < 0.05). PA was significantly associated with the decline of ReHo and fALFF in perinidal regions (P < 0.05, for both). DATA CONCLUSION The presence of PA can predict perinidal NVU that may confound the interpretation of both task-based and resting-state fMRI, highlighting the importance of alternative approaches of brain functional localization in improving treatment of AVMs. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Maogui Li
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, China
| | - Qingyuan Liu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, China
| | - Rui Guo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, China
| | - Shuzhe Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, China
| | - Pengjun Jiang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, China
| | - Xin Chen
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, China
| | - Jun Wu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, China
| | - Yong Cao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, China
| | - Shuo Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Translational Medicine for Cerebrovascular Diseases, Beijing, China
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16
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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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17
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Duffau H. Functional Mapping before and after Low-Grade Glioma Surgery: A New Way to Decipher Various Spatiotemporal Patterns of Individual Neuroplastic Potential in Brain Tumor Patients. Cancers (Basel) 2020; 12:E2611. [PMID: 32933174 PMCID: PMC7565450 DOI: 10.3390/cancers12092611] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Revised: 09/07/2020] [Accepted: 09/11/2020] [Indexed: 12/21/2022] Open
Abstract
Intraoperative direct electrostimulation mapping (DEM) is currently the gold-standard for glioma surgery, since functional-based resection allows an optimization of the onco-functional balance (increased resection with preserved quality of life). Besides intrasurgical awake mapping of conation, cognition, and behavior, preoperative mapping by means of functional neuroimaging (FNI) and transcranial magnetic stimulation (TMS) has increasingly been utilized for surgical selection and planning. However, because these techniques suffer from several limitations, particularly for direct functional mapping of subcortical white matter pathways, DEM remains crucial to map neural connectivity. On the other hand, non-invasive FNI and TMS can be repeated before and after surgical resection(s), enabling longitudinal investigation of brain reorganization, especially in slow-growing tumors like low-grade gliomas. Indeed, these neoplasms generate neuroplastic phenomena in patients with usually no or only slight neurological deficits at diagnosis, despite gliomas involving the so-called "eloquent" structures. Here, data gained from perioperative FNI/TMS mapping methods are reviewed, in order to decipher mechanisms underpinning functional cerebral reshaping induced by the tumor and its possible relapse, (re)operation(s), and postoperative rehabilitation. Heterogeneous spatiotemporal patterns of rearrangement across patients and in a single patient over time have been evidenced, with structural changes as well as modifications of intra-hemispheric (in the ipsi-lesional and/or contra-lesional hemisphere) and inter-hemispheric functional connectivity. Such various fingerprints of neural reconfiguration were correlated to different levels of cognitive compensation. Serial multimodal studies exploring neuroplasticity might lead to new management strategies based upon multistage therapeutic approaches adapted to the individual profile of functional reallocation.
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Affiliation(s)
- Hugues Duffau
- Department of Neurosurgery, Montpellier University Medical Center, 34295 Montpellier, France; ; Tel.: +33-4-67-33-66-12; Fax: +33-4-67-33-69-12
- Institute of Functional Genomics, INSERM U-1191, University of Montpellier, 34298 Montpellier, France
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18
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Yang J, Gohel S, Vachha B. Current methods and new directions in resting state fMRI. Clin Imaging 2020; 65:47-53. [PMID: 32353718 DOI: 10.1016/j.clinimag.2020.04.004] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 03/24/2020] [Accepted: 04/08/2020] [Indexed: 12/12/2022]
Abstract
Resting state functional connectivity magnetic resonance imaging (rsfcMRI) has become a key component of investigations of neurocognitive and psychiatric behaviors. Over the past two decades, several methods and paradigms have been adopted to utilize and interpret data from resting-state fluctuations in the brain. These findings have increased our understanding of changes in many disease states. As the amount of resting state data available for research increases with big datasets and data-sharing projects, it is important to review the established traditional analysis methods and recognize areas where research methodology can be adapted to better accommodate the scale and complexity of rsfcMRI analysis. In this paper, we review established methods of analysis as well as areas that have been receiving increasing attention such as dynamic rsfcMRI, independent vector analysis, multiband rsfcMRI and network of networks.
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Affiliation(s)
- Jackie Yang
- NYU Grossman School of Medicine, 550 1(st) Avenue, New York, NY 10016, USA
| | - Suril Gohel
- Department of Health Informatics, Rutgers University School of Health Professions, 65 Bergen Street, Newark, NJ 07107, USA
| | - Behroze Vachha
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA.
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19
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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: 3.8] [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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20
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Chaudhry AA, Naim S, Gul M, Chaudhry A, Chen M, Jandial R, Badie B. Utility of Preoperative Blood-Oxygen-Level-Dependent Functional MR Imaging in Patients with a Central Nervous System Neoplasm. Radiol Clin North Am 2019; 57:1189-1198. [PMID: 31582044 DOI: 10.1016/j.rcl.2019.07.006] [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] [Indexed: 12/13/2022]
Abstract
Functional neuroimaging provides means to understand the relationship between brain structure and associated functions. Functional MR (fMR) imaging can offer a unique insight into preoperative planning for central nervous system (CNS) neoplasms by identifying areas of the brain effected or spared by the neoplasm. BOLD (blood-oxygen-level-dependent) fMR imaging can be reliably used to map eloquent cortex presurgically and is sufficiently accurate for neurosurgical planning. In patients with brain tumors undergoing neurosurgical intervention, fMR imaging can decrease postoperative morbidity. This article discusses the applications, significance, and interpretation of BOLD fMR imaging, and its applications in presurgical planning for CNS neoplasms.
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Affiliation(s)
- Ammar A Chaudhry
- Precision Imaging Lab, Department of Diagnostic Radiology, City of Hope National Cancer Center, 1500 East Duarte Road, Los Angeles, CA 91010, USA.
| | - Sohaib Naim
- Department of Diagnostic Radiology, City of Hope National Cancer Center, 1500 East Duarte Road, Los Angeles, CA 91010, USA
| | - Maryam Gul
- Department of Diagnostic Radiology, City of Hope National Cancer Center, 1500 East Duarte Road, Los Angeles, CA 91010, USA
| | - Abbas Chaudhry
- Department of Diagnostic Radiology, City of Hope National Cancer Center, 1500 East Duarte Road, Los Angeles, CA 91010, USA
| | - Mike Chen
- Department of Neurosurgery, City of Hope National Cancer Center, 1500 East Duarte Road, Los Angeles, CA 91010, USA
| | - Rahul Jandial
- Department of Neurosurgery, City of Hope National Cancer Center, 1500 East Duarte Road, Los Angeles, CA 91010, USA
| | - Behnam Badie
- Department of Neurosurgery, City of Hope National Cancer Center, 1500 East Duarte Road, Los Angeles, CA 91010, USA
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21
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Fox ME, King TZ. Functional Connectivity in Adult Brain Tumor Patients: A Systematic Review. Brain Connect 2019; 8:381-397. [PMID: 30141339 DOI: 10.1089/brain.2018.0623] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Brain tumor (BT) patients often experience reduced cognitive abilities and disrupted adaptive functioning before and after treatment. An innovative approach to understanding the underlying brain networks associated with these outcomes has been to study the brain's functional connectivity (FC), the spatially distributed and temporally correlated activity throughout the brain, and how it can be affected by a tumor. The present review synthesized the extant BT FC literature that utilizes functional magnetic resonance imaging to study FC strength of commonly observed networks during rest and task. A systematic review of English articles using PubMed was conducted. Search terms included brain tumor OR glioma AND functional connectivity, independent component analysis, ICA, psychophysiological interaction, OR PPI. Studies in which participants were diagnosed with BTs as adults that evaluated specific networks of interest using independent component analysis or seed-based component analysis were included. Twenty-five studies met inclusion criteria. BT patients often presented with decreases in FC strength within well-established networks and increases in atypical FC patterns. Network differences were tumor adjacent and distal, and left hemisphere tumors generally had a greater impact on FC. FC alterations often correlated with behavioral or cognitive outcomes when assessed. Overall, BTs appear to lead to various alterations in FC across different functional networks, and the most common change is a decrease in expected FC strength. More longitudinal studies are needed to determine the time course of network alterations across treatment and recovery, the role of medical treatments in BT survivors' FC, and the potential of FC patterns as biomarkers of cognitive outcomes.
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Affiliation(s)
- Michelle E Fox
- 1 Department of Psychology, Georgia State University , Atlanta, Georgia
| | - Tricia Z King
- 1 Department of Psychology, Georgia State University , Atlanta, Georgia .,2 Neuroscience Institute, Georgia State University , Atlanta, Georgia
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22
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Sprugnoli G, Monti L, Lippa L, Neri F, Mencarelli L, Ruffini G, Salvador R, Oliveri G, Batani B, Momi D, Cerase A, Pascual-Leone A, Rossi A, Rossi S, Santarnecchi E. Reduction of intratumoral brain perfusion by noninvasive transcranial electrical stimulation. SCIENCE ADVANCES 2019; 5:eaau9309. [PMID: 31453319 PMCID: PMC6693907 DOI: 10.1126/sciadv.aau9309] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Accepted: 07/10/2019] [Indexed: 05/04/2023]
Abstract
Malignant brain neoplasms have a poor prognosis despite aggressive treatments. Animal models and evidence from human bodily tumors reveal that sustained reduction in tumor perfusion via electrical stimulation promotes tumor necrosis, therefore possibly representing a therapeutic option for patients with brain tumors. Here, we demonstrate that transcranial electrical stimulation (tES) allows to safely and noninvasively reduce intratumoral perfusion in humans. Selected patients with glioblastoma or metastasis underwent tES, while perfusion was assessed using magnetic resonance imaging. Multichannel tES was applied according to personalized biophysical modeling, to maximize the induced electrical field over the solid tumor mass. All patients completed the study and tolerated the procedure without adverse effects, with tES selectively reducing the perfusion of the solid tumor. Results potentially open the door to noninvasive therapeutic interventions in brain tumors based on stand-alone tES or its combination with other available therapies.
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Affiliation(s)
- G. Sprugnoli
- Brain Investigation and Neuromodulation Laboratory, Department of Medicine, Surgery and Neuroscience, Unit of Neurology and Clinical Neurophysiology, Siena Medical School, Siena, Italy
| | - L. Monti
- Unit of Neuroimaging and Neurointervention, “Santa Maria alle Scotte” Medical Center, Siena, Italy
| | - L. Lippa
- Unit of Neurosurgery, “Santa Maria alle Scotte” Medical Center, Siena, Italy
| | - F. Neri
- Brain Investigation and Neuromodulation Laboratory, Department of Medicine, Surgery and Neuroscience, Unit of Neurology and Clinical Neurophysiology, Siena Medical School, Siena, Italy
| | - L. Mencarelli
- Brain Investigation and Neuromodulation Laboratory, Department of Medicine, Surgery and Neuroscience, Unit of Neurology and Clinical Neurophysiology, Siena Medical School, Siena, Italy
| | | | | | - G. Oliveri
- Unit of Neurosurgery, “Santa Maria alle Scotte” Medical Center, Siena, Italy
| | - B. Batani
- Unit of Neurosurgery, “Santa Maria alle Scotte” Medical Center, Siena, Italy
| | - D. Momi
- Brain Investigation and Neuromodulation Laboratory, Department of Medicine, Surgery and Neuroscience, Unit of Neurology and Clinical Neurophysiology, Siena Medical School, Siena, Italy
| | - A. Cerase
- Unit of Neuroimaging and Neurointervention, “Santa Maria alle Scotte” Medical Center, Siena, Italy
| | - A. Pascual-Leone
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Medical Center, Harvard Medical School, Boston, MA, USA
- Institut Guttmann, Universitat Autonoma Barcelona, Barcelona, Spain
| | - A. Rossi
- Brain Investigation and Neuromodulation Laboratory, Department of Medicine, Surgery and Neuroscience, Unit of Neurology and Clinical Neurophysiology, Siena Medical School, Siena, Italy
- Department of Medicine, Surgery and Neuroscience, Human Physiology Section, Siena Medical School, Siena, Italy
| | - S. Rossi
- Brain Investigation and Neuromodulation Laboratory, Department of Medicine, Surgery and Neuroscience, Unit of Neurology and Clinical Neurophysiology, Siena Medical School, Siena, Italy
- Department of Medicine, Surgery and Neuroscience, Human Physiology Section, Siena Medical School, Siena, Italy
| | - E. Santarnecchi
- Brain Investigation and Neuromodulation Laboratory, Department of Medicine, Surgery and Neuroscience, Unit of Neurology and Clinical Neurophysiology, Siena Medical School, Siena, Italy
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Medical Center, Harvard Medical School, Boston, MA, USA
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23
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Reliability of Functional Magnetic Resonance Imaging in Patients with Brain Tumors: A Critical Review and Meta-Analysis. World Neurosurg 2019; 125:183-190. [DOI: 10.1016/j.wneu.2019.01.194] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Revised: 01/19/2019] [Accepted: 01/21/2019] [Indexed: 11/20/2022]
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24
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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: 1.8] [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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25
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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: 1.3] [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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26
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Bowden SG, Gill BJA, Englander ZK, Horenstein CI, Zanazzi G, Chang PD, Samanamud J, Lignelli A, Bruce JN, Canoll P, Grinband J. Local Glioma Cells Are Associated with Vascular Dysregulation. AJNR Am J Neuroradiol 2018; 39:507-514. [PMID: 29371254 DOI: 10.3174/ajnr.a5526] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2017] [Accepted: 11/09/2017] [Indexed: 12/20/2022]
Abstract
BACKGROUND AND PURPOSE Malignant glioma is a highly infiltrative malignancy that causes variable disruptions to the structure and function of the cerebrovasculature. While many of these structural disruptions have known correlative histopathologic alterations, the mechanisms underlying vascular dysfunction identified by resting-state blood oxygen level-dependent imaging are not yet known. The purpose of this study was to characterize the alterations that correlate with a blood oxygen level-dependent biomarker of vascular dysregulation. MATERIALS AND METHODS Thirty-two stereotactically localized biopsies were obtained from contrast-enhancing (n = 16) and nonenhancing (n = 16) regions during open surgical resection of malignant glioma in 17 patients. Preoperative resting-state blood oxygen level-dependent fMRI was used to evaluate the relationships between radiographic and histopathologic characteristics. Signal intensity for a blood oxygen level-dependent biomarker was compared with scores of tumor infiltration and microvascular proliferation as well as total cell and neuronal density. RESULTS Biopsies corresponded to a range of blood oxygen level-dependent signals, ranging from relatively normal (z = -4.79) to markedly abnormal (z = 8.84). Total cell density was directly related to blood oxygen level-dependent signal abnormality (P = .013, R2 = 0.19), while the neuronal labeling index was inversely related to blood oxygen level-dependent signal abnormality (P = .016, R2 = 0.21). The blood oxygen level-dependent signal abnormality was also related to tumor infiltration (P = .014) and microvascular proliferation (P = .045). CONCLUSIONS The relationship between local, neoplastic characteristics and a blood oxygen level-dependent biomarker of vascular function suggests that local effects of glioma cell infiltration contribute to vascular dysregulation.
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Affiliation(s)
- S G Bowden
- From the Department of Neurological Surgery (S.G.B.), Oregon Health & Science University, Portland, Oregon.,The Gabriele Bartoli Brain Tumor Research Laboratory (S.G.B., B.J.A.G., Z.K.E., J.S., J.N.B., P.C.)
| | - B J A Gill
- The Gabriele Bartoli Brain Tumor Research Laboratory (S.G.B., B.J.A.G., Z.K.E., J.S., J.N.B., P.C.).,Departments of Neurological Surgery (B.J.A.G., Z.K.E., J.N.B., P.C.)
| | - Z K Englander
- The Gabriele Bartoli Brain Tumor Research Laboratory (S.G.B., B.J.A.G., Z.K.E., J.S., J.N.B., P.C.).,Departments of Neurological Surgery (B.J.A.G., Z.K.E., J.N.B., P.C.)
| | - C I Horenstein
- Department of Radiology (C.I.H.), North Shore University Hospital, Long Island, New York
| | - G Zanazzi
- Pathology and Cell Biology (G.Z., P.C.)
| | - P D Chang
- Department of Radiology (P.D.C.), University of California, San Francisco, California
| | - J Samanamud
- The Gabriele Bartoli Brain Tumor Research Laboratory (S.G.B., B.J.A.G., Z.K.E., J.S., J.N.B., P.C.)
| | - A Lignelli
- Radiology (A.L., J.G.), Columbia University Medical Center, New York, New York
| | - J N Bruce
- The Gabriele Bartoli Brain Tumor Research Laboratory (S.G.B., B.J.A.G., Z.K.E., J.S., J.N.B., P.C.).,Departments of Neurological Surgery (B.J.A.G., Z.K.E., J.N.B., P.C.)
| | - P Canoll
- The Gabriele Bartoli Brain Tumor Research Laboratory (S.G.B., B.J.A.G., Z.K.E., J.S., J.N.B., P.C.).,Departments of Neurological Surgery (B.J.A.G., Z.K.E., J.N.B., P.C.).,Pathology and Cell Biology (G.Z., P.C.)
| | - J Grinband
- Radiology (A.L., J.G.), Columbia University Medical Center, New York, New York
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