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Teo JM, Kumar VA, Lee J, Eldaya RW, Hou P, Jen ML, Noll KR, Wei P, Ferguson SD, Prabhu SS, Wintermark M, Liu HL. Probabilistic Presurgical Language fMRI Atlas of Patients with Brain Tumors. AJNR Am J Neuroradiol 2024:ajnr.A8383. [PMID: 38889968 DOI: 10.3174/ajnr.a8383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Accepted: 06/09/2024] [Indexed: 06/20/2024]
Abstract
BACKGROUND AND PURPOSE Patients with brain tumors have high intersubject variation in putative language regions, which may limit the utility of straightforward application of healthy subject brain atlases in clinical scenarios. The purpose of this study was to develop a probabilistic functional brain atlas that consolidates language functional activations of sentence completion and Silent Word Generation language paradigms using a large sample of patients with brain tumors. MATERIALS AND METHODS The atlas was developed using retrospectively collected fMRI data from patients with brain tumors who underwent their first standard-of-care presurgical language fMRI scan at our institution between July 18, 2015, and May 13, 2022. Three hundred seventeen patients (861 fMRI scans) were used to develop the language functional atlas. An independent presurgical language fMRI data set of 39 patients with brain tumors from a previous study was used to evaluate our atlas. Family-wise error-corrected binary functional activation maps from sentence completion, letter fluency, and category fluency presurgical fMRI were used to create probability overlap maps and pooled probabilistic overlap maps in Montreal Neurological Institute standard space. The Wilcoxon signed-rank test was used to determine a significant difference in the maximum Dice coefficient for our atlas compared with a meta-analysis-based template with respect to expert-delineated primary language area activations. RESULTS Probabilities of activating the left anterior primary language area and left posterior primary language area in the temporal lobe were 87.9% and 91.5%, respectively, for sentence completion, 88.5% and 74.2%, respectively, for letter fluency, and 83.6% and 67.6%, respectively, for category fluency. Maximum Dice coefficients for templates derived from our language atlas were significantly higher than the meta-analysis-based template in the left anterior primary language area (0.351 and 0.326, respectively, P < .05) and the left posterior primary language area in the temporal lobe (0.274 and 0.244, respectively, P < .005). CONCLUSIONS Brain tumor patient- and paradigm-specific probabilistic language atlases were developed. These atlases had superior spatial agreement with fMRI activations in individual patients compared with the meta-analysis-based template.
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Affiliation(s)
- Jian Ming Teo
- From the Department of Imaging Physics (J.M.T., P.H., M.-L.J., H.-L.L.), The University of Texas MD Anderson Cancer Center, Houston, Texas
- Medical Physics Graduate Program (J.M.T.), The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, Texas
| | - Vinodh A Kumar
- Department of Diagnostic Radiology (V.A.K., J.L., R.W.E., M.W.), The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jina Lee
- Department of Diagnostic Radiology (V.A.K., J.L., R.W.E., M.W.), The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Rami W Eldaya
- Department of Diagnostic Radiology (V.A.K., J.L., R.W.E., M.W.), The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Ping Hou
- From the Department of Imaging Physics (J.M.T., P.H., M.-L.J., H.-L.L.), The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Mu-Lan Jen
- From the Department of Imaging Physics (J.M.T., P.H., M.-L.J., H.-L.L.), The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Kyle R Noll
- Department of Neuro-Oncology (K.R.N.), The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Peng Wei
- Department of Biostatistics (P.W.), The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Sherise D Ferguson
- Department of Neurosurgery (S.D.F., S.S.P.), The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Sujit S Prabhu
- Department of Neurosurgery (S.D.F., S.S.P.), The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Max Wintermark
- Department of Diagnostic Radiology (V.A.K., J.L., R.W.E., M.W.), The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Ho-Ling Liu
- From the Department of Imaging Physics (J.M.T., P.H., M.-L.J., H.-L.L.), The University of Texas MD Anderson Cancer Center, Houston, Texas
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Coolen T, Mihai Dumitrescu A, Wens V, Bourguignon M, Rovai A, Sadeghi N, Urbain C, Goldman S, De Tiège X. Spectrotemporal cortical dynamics and semantic control during sentence completion. Clin Neurophysiol 2024; 163:90-101. [PMID: 38714152 DOI: 10.1016/j.clinph.2024.04.012] [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: 01/23/2024] [Revised: 03/27/2024] [Accepted: 04/14/2024] [Indexed: 05/09/2024]
Abstract
OBJECTIVE To investigate cortical oscillations during a sentence completion task (SC) using magnetoencephalography (MEG), focusing on the semantic control network (SCN), its leftward asymmetry, and the effects of semantic control load. METHODS Twenty right-handed adults underwent MEG while performing SC, consisting of low cloze (LC: multiple responses) and high cloze (HC: single response) stimuli. Spectrotemporal power modulations as event-related synchronizations (ERS) and desynchronizations (ERD) were analyzed: first, at the whole-brain level; second, in key SCN regions, posterior middle/inferior temporal gyri (pMTG/ITG) and inferior frontal gyri (IFG), under different semantic control loads. RESULTS Three cortical response patterns emerged: early (0-200 ms) theta-band occipital ERS; intermediate (200-700 ms) semantic network alpha/beta-band ERD; late (700-3000 ms) dorsal language stream alpha/beta/gamma-band ERD. Under high semantic control load (LC), pMTG/ITG showed prolonged left-sided engagement (ERD) and right-sided inhibition (ERS). Left IFG exhibited heightened late (2500-2550 ms) beta-band ERD with increased semantic control load (LC vs. HC). CONCLUSIONS SC involves distinct cortical responses and depends on the left IFG and asymmetric engagement of the pMTG/ITG for semantic control. SIGNIFICANCE Future use of SC in neuromagnetic preoperative language mapping and for understanding the pathophysiology of language disorders in neurological conditions.
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Affiliation(s)
- Tim Coolen
- Université Libre de Bruxelles (ULB), ULB Neuroscience Institute (UNI), Laboratoire de Neuroanatomie et Neuroimagerie Translationnelles (LN(2)T), Brussels, Belgium; Université Libre de Bruxelles, Hôpital Universitaire de Bruxelles (HUB), CUB Hôpital Erasme, Department of Radiology, Brussels, Belgium.
| | - Alexandru Mihai Dumitrescu
- Université Libre de Bruxelles (ULB), ULB Neuroscience Institute (UNI), Laboratoire de Neuroanatomie et Neuroimagerie Translationnelles (LN(2)T), Brussels, Belgium
| | - Vincent Wens
- Université Libre de Bruxelles (ULB), ULB Neuroscience Institute (UNI), Laboratoire de Neuroanatomie et Neuroimagerie Translationnelles (LN(2)T), Brussels, Belgium
| | - Mathieu Bourguignon
- Université Libre de Bruxelles (ULB), ULB Neuroscience Institute (UNI), Laboratoire de Neuroanatomie et Neuroimagerie Translationnelles (LN(2)T), Brussels, Belgium; Université Libre de Bruxelles (ULB), ULB Neuroscience Institute (UNI), Laboratory of Neurophysiology and Movement Biomechanics, Brussels, Belgium
| | - Antonin Rovai
- Université Libre de Bruxelles (ULB), ULB Neuroscience Institute (UNI), Laboratoire de Neuroanatomie et Neuroimagerie Translationnelles (LN(2)T), Brussels, Belgium
| | - Niloufar Sadeghi
- Université Libre de Bruxelles, Hôpital Universitaire de Bruxelles (HUB), CUB Hôpital Erasme, Department of Radiology, Brussels, Belgium
| | - Charline Urbain
- Université Libre de Bruxelles (ULB), ULB Neuroscience Institute (UNI), Laboratoire de Neuroanatomie et Neuroimagerie Translationnelles (LN(2)T), Brussels, Belgium; Université Libre de Bruxelles (ULB), ULB Neuroscience Institute (UNI), Centre for Research in Cognition and Neurosciences (CRCN), Neuropsychology and Functional Neuroimaging Research Unit (UR2NF), Brussels, Belgium
| | - Serge Goldman
- Université Libre de Bruxelles (ULB), ULB Neuroscience Institute (UNI), Laboratoire de Neuroanatomie et Neuroimagerie Translationnelles (LN(2)T), Brussels, Belgium
| | - Xavier De Tiège
- Université Libre de Bruxelles (ULB), ULB Neuroscience Institute (UNI), Laboratoire de Neuroanatomie et Neuroimagerie Translationnelles (LN(2)T), Brussels, Belgium
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Kokkinos V, Chatzisotiriou A, Seimenis I. Functional Magnetic Resonance Imaging and Diffusion Tensor Imaging-Tractography in Resective Brain Surgery: Lesion Coverage Strategies and Patient Outcomes. Brain Sci 2023; 13:1574. [PMID: 38002534 PMCID: PMC10670090 DOI: 10.3390/brainsci13111574] [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: 09/26/2023] [Revised: 11/04/2023] [Accepted: 11/07/2023] [Indexed: 11/26/2023] Open
Abstract
Diffusion tensor imaging (DTI)-tractography and functional magnetic resonance imaging (fMRI) have dynamically entered the presurgical evaluation context of brain surgery during the past decades, providing novel perspectives in surgical planning and lesion access approaches. However, their application in the presurgical setting requires significant time and effort and increased costs, thereby raising questions regarding efficiency and best use. In this work, we set out to evaluate DTI-tractography and combined fMRI/DTI-tractography during intra-operative neuronavigation in resective brain surgery using lesion-related preoperative neurological deficit (PND) outcomes as metrics. We retrospectively reviewed medical records of 252 consecutive patients admitted for brain surgery. Standard anatomical neuroimaging protocols were performed in 127 patients, 69 patients had additional DTI-tractography, and 56 had combined DTI-tractography/fMRI. fMRI procedures involved language, motor, somatic sensory, sensorimotor and visual mapping. DTI-tractography involved fiber tracking of the motor, sensory, language and visual pathways. At 1 month postoperatively, DTI-tractography patients were more likely to present either improvement or preservation of PNDs (p = 0.004 and p = 0.007, respectively). At 6 months, combined DTI-tractography/fMRI patients were more likely to experience complete PND resolution (p < 0.001). Low-grade lesion patients (N = 102) with combined DTI-tractography/fMRI were more likely to experience complete resolution of PNDs at 1 and 6 months (p = 0.001 and p < 0.001, respectively). High-grade lesion patients (N = 140) with combined DTI-tractography/fMRI were more likely to have PNDs resolved at 6 months (p = 0.005). Patients with motor symptoms (N = 80) were more likely to experience complete remission of PNDs at 6 months with DTI-tractography or combined DTI-tractography/fMRI (p = 0.008 and p = 0.004, respectively), without significant difference between the two imaging protocols (p = 1). Patients with sensory symptoms (N = 44) were more likely to experience complete PND remission at 6 months with combined DTI-tractography/fMRI (p = 0.004). The intraoperative neuroimaging modality did not have a significant effect in patients with preoperative seizures (N = 47). Lack of PND worsening was observed at 6 month follow-up in patients with combined DTI-tractography/fMRI. Our results strongly support the combined use of DTI-tractography and fMRI in patients undergoing resective brain surgery for improving their postoperative clinical profile.
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Affiliation(s)
- Vasileios Kokkinos
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA
- Harvard Medical School, Boston, MA 02215, USA
| | | | - Ioannis Seimenis
- Department of Medicine, School of Health Sciences, Democritus University of Thrace, 387479 Alexandroupolis, Greece;
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Pasquini L, Peck KK, Jenabi M, Holodny A. Functional MRI in Neuro-Oncology: State of the Art and Future Directions. Radiology 2023; 308:e222028. [PMID: 37668519 PMCID: PMC10546288 DOI: 10.1148/radiol.222028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 05/15/2023] [Accepted: 05/26/2023] [Indexed: 09/06/2023]
Abstract
Since its discovery in the early 1990s, functional MRI (fMRI) has been used to study human brain function. One well-established application of fMRI in the clinical setting is the neurosurgical planning of patients with brain tumors near eloquent cortical areas. Clinical fMRI aims to preoperatively identify eloquent cortices that serve essential functions in daily life, such as hand movement and language. The primary goal of neurosurgery is to maximize tumor resection while sparing eloquent cortices adjacent to the tumor. When a lesion presents in the vicinity of an eloquent cortex, surgeons may use fMRI to plan their best surgical approach by determining the proximity of the lesion to regions of activation, providing guidance for awake brain surgery and intraoperative brain mapping. The acquisition of fMRI requires patient preparation prior to imaging, determination of functional paradigms, monitoring of patient performance, and both processing and analysis of images. Interpretation of fMRI maps requires a strong understanding of functional neuroanatomy and familiarity with the technical limitations frequently present in brain tumor imaging, including neurovascular uncoupling, patient compliance, and data analysis. This review discusses clinical fMRI in neuro-oncology, relevant ongoing research topics, and prospective future developments in this exciting discipline.
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Affiliation(s)
- Luca Pasquini
- From the Neuroradiology Service, Department of Radiology (L.P.,
K.K.P., M.J., A.H.), Department of Medical Physics (K.K.P.), and Brain Tumor
Center (A.H.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York,
NY 10065; Neuroradiology Unit, NESMOS Department, Sant'Andrea Hospital,
La Sapienza University, Rome, Italy (L.P.); Department of Radiology, Weill
Medical College of Cornell University, New York, NY (A.H.); and Department of
Neuroscience, Weill Cornell Medicine Graduate School of Medical Sciences, New
York, NY (A.H.)
| | - Kyung K. Peck
- From the Neuroradiology Service, Department of Radiology (L.P.,
K.K.P., M.J., A.H.), Department of Medical Physics (K.K.P.), and Brain Tumor
Center (A.H.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York,
NY 10065; Neuroradiology Unit, NESMOS Department, Sant'Andrea Hospital,
La Sapienza University, Rome, Italy (L.P.); Department of Radiology, Weill
Medical College of Cornell University, New York, NY (A.H.); and Department of
Neuroscience, Weill Cornell Medicine Graduate School of Medical Sciences, New
York, NY (A.H.)
| | - Mehrnaz Jenabi
- From the Neuroradiology Service, Department of Radiology (L.P.,
K.K.P., M.J., A.H.), Department of Medical Physics (K.K.P.), and Brain Tumor
Center (A.H.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York,
NY 10065; Neuroradiology Unit, NESMOS Department, Sant'Andrea Hospital,
La Sapienza University, Rome, Italy (L.P.); Department of Radiology, Weill
Medical College of Cornell University, New York, NY (A.H.); and Department of
Neuroscience, Weill Cornell Medicine Graduate School of Medical Sciences, New
York, NY (A.H.)
| | - Andrei Holodny
- From the Neuroradiology Service, Department of Radiology (L.P.,
K.K.P., M.J., A.H.), Department of Medical Physics (K.K.P.), and Brain Tumor
Center (A.H.), Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York,
NY 10065; Neuroradiology Unit, NESMOS Department, Sant'Andrea Hospital,
La Sapienza University, Rome, Italy (L.P.); Department of Radiology, Weill
Medical College of Cornell University, New York, NY (A.H.); and Department of
Neuroscience, Weill Cornell Medicine Graduate School of Medical Sciences, New
York, NY (A.H.)
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Meyer NK, Kang D, Black DF, Campeau NG, Welker KM, Gray EM, In MH, Shu Y, Huston III J, Bernstein MA, Trzasko JD. Enhanced clinical task-based fMRI metrics through locally low-rank denoising of complex-valued data. Neuroradiol J 2023; 36:273-288. [PMID: 36063799 PMCID: PMC10268095 DOI: 10.1177/19714009221122171] [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] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE This study investigates a locally low-rank (LLR) denoising algorithm applied to source images from a clinical task-based functional MRI (fMRI) exam before post-processing for improving statistical confidence of task-based activation maps. METHODS Task-based motor and language fMRI was obtained in eleven healthy volunteers under an IRB approved protocol. LLR denoising was then applied to raw complex-valued image data before fMRI processing. Activation maps generated from conventional non-denoised (control) data were compared with maps derived from LLR-denoised image data. Four board-certified neuroradiologists completed consensus assessment of activation maps; region-specific and aggregate motor and language consensus thresholds were then compared with nonparametric statistical tests. Additional evaluation included retrospective truncation of exam data without and with LLR denoising; a ROI-based analysis tracked t-statistics and temporal SNR (tSNR) as scan durations decreased. A test-retest assessment was performed; retest data were matched with initial test data and compared for one subject. RESULTS fMRI activation maps generated from LLR-denoised data predominantly exhibited statistically significant (p = 4.88×10-4 to p = 0.042; one p = 0.062) increases in consensus t-statistic thresholds for motor and language activation maps. Following data truncation, LLR data showed task-specific increases in t-statistics and tSNR respectively exceeding 20 and 50% compared to control. LLR denoising enabled truncation of exam durations while preserving cluster volumes at fixed thresholds. Test-retest showed variable activation with LLR data thresholded higher in matching initial test data. CONCLUSION LLR denoising affords robust increases in t-statistics on fMRI activation maps compared to routine processing, and offers potential for reduced scan duration while preserving map quality.
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Affiliation(s)
- Nolan K Meyer
- Mayo Clinic Graduate School of Biomedical Sciences, Rochester, MN, USA
| | - Daehun Kang
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - David F Black
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | | - Kirk M Welker
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Erin M Gray
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Myung-Ho In
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Yunhong Shu
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
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BOLD fMRI and DTI fiber tracking for preoperative mapping of eloquent cerebral regions in brain tumor patients: impact on surgical approach and outcome. Neurol Sci 2023:10.1007/s10072-023-06667-2. [PMID: 36914833 DOI: 10.1007/s10072-023-06667-2] [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: 03/31/2022] [Accepted: 02/01/2023] [Indexed: 03/15/2023]
Abstract
PURPOSE Task-based BOLD fMRI and DTI-fiber tracking have become part of the routine presurgical work-up of brain tumor patients in many institutions. However, their potential impact on both surgical treatment and neurologic outcome remains unclear, in despite of the high costs and complex implementation. METHODS We retrospectively investigated whether performing fMRI and DTI-ft preoperatively substantially impacted surgical planning and patient outcome in a series of brain tumor patients. We assessed (i) the quality of fMRI and DTI-ft results, by using a scale of 0-2 (0 = failed mapping; 1 = intermediate confidence; 2 = good confidence), (ii) whether functional planning substantially contributed to defining the surgical strategy to be undertaken (i.e., no surgery, biopsy, or resection, with or without ESM), the surgical entry point and extent of resection, and (iii) the incidence of neurological deficits post-operatively. RESULTS Twenty-seven patients constituted the study population. The mean confidence rating was 1.9/2 for fMRI localization of the eloquent cortex and lateralization of the language function and 1.7/2 for DTI-ft results. Treatment strategy was altered in 33% (9/27) of cases. Surgical entry point was modified in 8% (2/25) of cases. The extent of resection was modified in 40% (10/25). One patient (1/25, 4%) developed one new functional deficit post-operatively. CONCLUSION Functional MR mapping - which must not be considered an alternative to ESM - has a critical role preoperatively, potentially modifying treatment strategy or increasing the neurosurgeons' confidence in the surgical approach hypothesized based on conventional imaging.
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Fetscher L, Batra M, Klose U. Improved localization of language areas using single voxel signal analysis of unprocessed fMRI data. FRONTIERS IN RADIOLOGY 2022; 2:997330. [PMID: 37492663 PMCID: PMC10365080 DOI: 10.3389/fradi.2022.997330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 09/06/2022] [Indexed: 07/27/2023]
Abstract
Activated brain regions can be visualized and localized with the use of fMRI (functional magnetic imaging). This is based on changes in the blood flow in activated regions, or more precisely on the hemodynamic response function (HRF) and the Blood-Oxygen-Level-Dependent (BOLD) effect. This study used a task-based fMRI examination with language paradigms in order to stimulate the language areas. The measured fMRI data are frequently altered by different preprocessing steps for the analysis and the display of activations. These changes can lead to discrepancies between the displayed and the truly measured location of the activations. Simple t-maps were created with unprocessed fMRI data, to provide a more realistic representation of the language areas. HRF-dependent single-voxel fMRI signal analysis was performed to improve the analyzability of these activation maps.
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Monitoring Cortico-cortical Evoked Potentials Using Only Two 6-strand Strip Electrodes for Gliomas Extending to the Dominant Side of Frontal Operculum During One-step Tumor Removal Surgery. World Neurosurg 2022; 165:e732-e742. [PMID: 35798294 DOI: 10.1016/j.wneu.2022.06.141] [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: 04/09/2022] [Revised: 06/27/2022] [Accepted: 06/28/2022] [Indexed: 12/14/2022]
Abstract
OBJECTIVE Resection of the dominant side of gliomas extending to the frontal operculum has high risk of severe language dysfunction. Here, we report recording cortico-cortical evoked potentials (CCEP) using only two 6-strand strip electrodes to monitor language-related fibers intraoperatively. We examined whether this simple procedure is useful for removing gliomas extending to the dominant side of frontal operculum. METHODS This study included 7 cases of glioma extending to the left frontal operculum. The frontal language area (FLA) was first identified by functional mapping during awake craniotomy. Next, a 6-strand strip electrode was placed on the FLA, while on the temporal side, an electrode was placed so as to slide parallel to the sylvian fissure toward the posterior language area. Electrical stimulation was performed using the electrode on the frontal side, and CCEPs were measured from the electrode on the temporal side. RESULTS CCEPs were detected in all cases. Immediately after surgery, all patients demonstrated language dysfunction to varying degree. CCEP decreased to 10% in 1 patient, who recovered language function after 24 months. CCEP decreased slightly 80% in 1, and, in the 5 other cases, CCEPs did not change. These 5 patients soon recovered language function within 2 weeks to 1 month. CONCLUSIONS This study confirmed the utility of CCEP monitoring using only two 6-strand strip electrodes during one-step surgery. We believe this simple method helped in monitoring intraoperative language function and predicting its postoperative recovery in patients with gliomas extending to the dominant side of frontal operculum.
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Riley SP, Chu DY, Nair VA, Baskaya MK, Kuo JS, Meyerand ME, Prabhakaran V. Characterizing the relationship between lesion-activation distance using fMRI and verbal measures in brain tumor patients. INTERDISCIPLINARY NEUROSURGERY 2022; 27. [PMID: 34950570 PMCID: PMC8691738 DOI: 10.1016/j.inat.2021.101391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/29/2022] Open
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Nenning KH, Langs G. Machine learning in neuroimaging: from research to clinical practice. RADIOLOGIE (HEIDELBERG, GERMANY) 2022; 62:1-10. [PMID: 36044070 PMCID: PMC9732070 DOI: 10.1007/s00117-022-01051-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 07/07/2022] [Indexed: 12/14/2022]
Abstract
Neuroimaging is critical in clinical care and research, enabling us to investigate the brain in health and disease. There is a complex link between the brain's morphological structure, physiological architecture, and the corresponding imaging characteristics. The shape, function, and relationships between various brain areas change during development and throughout life, disease, and recovery. Like few other areas, neuroimaging benefits from advanced analysis techniques to fully exploit imaging data for studying the brain and its function. Recently, machine learning has started to contribute (a) to anatomical measurements, detection, segmentation, and quantification of lesions and disease patterns, (b) to the rapid identification of acute conditions such as stroke, or (c) to the tracking of imaging changes over time. As our ability to image and analyze the brain advances, so does our understanding of its intricate relationships and their role in therapeutic decision-making. Here, we review the current state of the art in using machine learning techniques to exploit neuroimaging data for clinical care and research, providing an overview of clinical applications and their contribution to fundamental computational neuroscience.
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Affiliation(s)
- Karl-Heinz Nenning
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA
- Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria
| | - Georg Langs
- Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria.
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Resting-State Functional Magnetic Resonance Imaging for Surgical Neuro-Oncology Planning: Towards a Standardization in Clinical Settings. Brain Sci 2021; 11:brainsci11121613. [PMID: 34942915 PMCID: PMC8699779 DOI: 10.3390/brainsci11121613] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 11/26/2021] [Accepted: 12/02/2021] [Indexed: 02/03/2023] Open
Abstract
Resting-state functional magnetic resonance imaging (rest-f-MRI) is a neuroimaging technique that has demonstrated its potential in providing new insights into brain physiology. rest-f-MRI can provide useful information in pre-surgical mapping aimed to balancing long-term survival by maximizing the extent of resection of brain neoplasms, while preserving the patient’s functional connectivity. Rest-fMRI may replace or can be complementary to task-driven fMRI (t-fMRI), particularly in patients unable to cooperate with the task paradigm, such as children or sedated, paretic, aphasic patients. Although rest-fMRI is still under standardization, this technique has been demonstrated to be feasible and valuable in the routine clinical setting for neurosurgical planning, along with intraoperative electrocortical mapping. In the literature, there is growing evidence that rest-fMRI can provide valuable information for the depiction of glioma-related functional brain network impairment. Accordingly, rest-fMRI could allow a tailored glioma surgery improving the surgeon’s ability to increase the extent of resection (EOR), and simultaneously minimize the risk of damage of eloquent brain structures and neuronal networks responsible for the integrity of executive functions. In this article, we present a review of the literature and illustrate the feasibility of rest-fMRI in the clinical setting for presurgical mapping of eloquent networks in patients affected by brain tumors, before and after tumor resection.
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Richards TJ, Anderson KL, Anderson JS. "Fully automated segmentation of the corticospinal tract using the TractSeg algorithm in patients with brain tumors". Clin Neurol Neurosurg 2021; 210:107001. [PMID: 34749021 DOI: 10.1016/j.clineuro.2021.107001] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 10/11/2021] [Accepted: 10/12/2021] [Indexed: 11/18/2022]
Abstract
OBJECTIVE Tractography has been used to define the presurgical location of white matter tracts, but this is subjective and time-intensive, making incorporation to imaging workflow at scale problematic. The objective is to validate a fully automated pipeline using the TractSeg algorithm (Wasserthal et al. NeuroImage 2018;183:239-253) to segment the corticospinal tract in patients with brain tumors adjacent to the corticospinal tract. METHODS The process of importing a structural MPRAGE sequence and raw diffusion weighted images from PACS, executing the TractSeg algorithm, overlaying the resulting bilateral corticospinal tracts on the MPRAGE image, and exporting this composite image to PACS was automated. This procedure was used to segment the corticospinal tract in 28 patients with brain masses adjacent to or displacing the corticospinal tract. These segmentations were compared with both manual deterministic tractography performed with DSI Studio using seeds placed in the pons and an automated tractography method in DSI Studio. RESULTS The automated algorithm was able to segment the bilateral corticospinal tracts in all 28 patients whereas the manual reference method and DSI Studio based automated tractography were unsuccessful in 2 and 1 patients, respectively. In all cases, the TractSeg segmentations very closely matched the manual segmentations. Also, TractSeg appeared to include larger portions of the lateral corticospinal tract fibers than the other 2 methods. CONCLUSION The TractSeg algorithm demonstrated robust performance in segmenting the corticospinal tract in patients with brain tumors adjacent to this tract. The algorithm is fast to perform and has great potential for optimizing and streamlining neurosurgical planning.
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Affiliation(s)
- Tyler J Richards
- University of Utah School of Medicine, Department of Radiology and Imaging Sciences, 30 North 1900 East #1A071, Salt Lake City, UT 84132-2140, USA.
| | - Keri L Anderson
- University of Utah School of Computing, Department of Computer Science, Merrill Engineering, 50 Central Campus Dr, Salt Lake City, UT 84112, USA.
| | - Jeffrey S Anderson
- University of Utah School of Medicine, Department of Radiology and Imaging Sciences, 30 North 1900 East #1A071, Salt Lake City, UT 84132-2140, USA.
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13
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Maheshwari M, Deshmukh T, Leuthardt EC, Shimony JS. Task-based and Resting State Functional MRI in Children. Magn Reson Imaging Clin N Am 2021; 29:527-541. [PMID: 34717843 DOI: 10.1016/j.mric.2021.06.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Functional MR imaging (MRI) is a valuable tool for presurgical planning and is well established in adult patients. The use of task-based fMRI is increasing in pediatric populations because it provides similar benefits for pre-surgical planning in children. This article reviews special adaptations that are required for successful applications of task-based fMRI in children, especially in the motor and language systems. The more recently introduced method of resting state fMRI is reviewed and its relative advantages and disadvantages discussed. Common pitfalls and other systems and networks that may be of interest in special circumstances also are reviewed.
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Affiliation(s)
- Mohit Maheshwari
- Department of Radiology, Medical College of Wisconsin, Children's Wisconsin, MS - 721, 9000 W Wisconsin Avenue, Milwaukee, WI 53226, USA.
| | - Tejaswini Deshmukh
- Department of Radiology, Medical College of Wisconsin, Children's Wisconsin, MS - 721, 9000 W Wisconsin Avenue, Milwaukee, WI 53226, USA
| | - Eric C Leuthardt
- Department of Neurosurgery, Washington University, 4525 Scott Avenue Campus Box 8131, St Louis, MO 63141, USA
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University, 4525 Scott Avenue Campus Box 8131, St Louis, MO 63141, USA
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14
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Li M, Zhang Q, Yang K. Role of MRI-Based Functional Imaging in Improving the Therapeutic Index of Radiotherapy in Cancer Treatment. Front Oncol 2021; 11:645177. [PMID: 34513659 PMCID: PMC8429950 DOI: 10.3389/fonc.2021.645177] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 07/30/2021] [Indexed: 02/05/2023] Open
Abstract
Advances in radiation technology, such as intensity-modulated radiation therapy (IMRT), have largely enabled a biological dose escalation of the target volume (TV) and reduce the dose to adjacent tissues or organs at risk (OARs). However, the risk of radiation-induced injury increases as more radiation dose utilized during radiation therapy (RT), which predominantly limits further increases in TV dose distribution and reduces the local control rate. Thus, the accurate target delineation is crucial. Recently, technological improvements for precise target delineation have obtained more attention in the field of RT. The addition of functional imaging to RT can provide a more accurate anatomy of the tumor and normal tissues (such as location and size), along with biological information that aids to optimize the therapeutic index (TI) of RT. In this review, we discuss the application of some common MRI-based functional imaging techniques in clinical practice. In addition, we summarize the main challenges and prospects of these imaging technologies, expecting more inspiring developments and more productive research paths in the near future.
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Affiliation(s)
- Mei Li
- Department of Gynecology and Obstetrics, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China.,West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Qin Zhang
- West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Kaixuan Yang
- Department of Gynecology and Obstetrics, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China
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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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Automated eloquent cortex localization in brain tumor patients using multi-task graph neural networks. Med Image Anal 2021; 74:102203. [PMID: 34474216 DOI: 10.1016/j.media.2021.102203] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 06/04/2021] [Accepted: 06/08/2021] [Indexed: 11/20/2022]
Abstract
Localizing the eloquent cortex is a crucial part of presurgical planning. While invasive mapping is the gold standard, there is increasing interest in using noninvasive fMRI to shorten and improve the process. However, many surgical patients cannot adequately perform task-based fMRI protocols. Resting-state fMRI has emerged as an alternative modality, but automated eloquent cortex localization remains an open challenge. In this paper, we develop a novel deep learning architecture to simultaneously identify language and primary motor cortex from rs-fMRI connectivity. Our approach uses the representational power of convolutional neural networks alongside the generalization power of multi-task learning to find a shared representation between the eloquent subnetworks. We validate our method on data from the publicly available Human Connectome Project and on a brain tumor dataset acquired at the Johns Hopkins Hospital. We compare our method against feature-based machine learning approaches and a fully-connected deep learning model that does not account for the shared network organization of the data. Our model achieves significantly better performance than competing baselines. We also assess the generalizability and robustness of our method. Our results clearly demonstrate the advantages of our graph convolution architecture combined with multi-task learning and highlight the promise of using rs-fMRI as a presurgical mapping tool.
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17
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Beheshtian E, Jalilianhasanpour R, Modir Shanechi A, Sethi V, Wang G, Lindquist MA, Caffo BS, Agarwal S, Pillai JJ, Gujar SK, Sair HI. Identification of the Somatomotor Network from Language Task-based fMRI Compared with Resting-State fMRI in Patients with Brain Lesions. Radiology 2021; 301:178-184. [PMID: 34282966 DOI: 10.1148/radiol.2021204594] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background Resting-state functional MRI (rs-fMRI) is a potential alternative to task-based functional MRI (tb-fMRI) for somatomotor network (SMN) identification. Brain networks can also be generated from tb-fMRI by using independent component analysis (ICA). Purpose To investigate whether the SMN can be identified by using ICA from a language task without a motor component, the sentence completion functional MRI (sc-fMRI) task, compared with rs-fMRI. Materials and Methods The sc-fMRI and rs-fMRI scans in patients who underwent presurgical brain mapping between 2012 and 2016 were analyzed, using the same imaging parameters (other than scanning time) on a 3.0-T MRI scanner. ICA was performed on rs-fMRI and sc-fMRI scans with use of a tool to separate data sets into their spatial and temporal components. Two neuroradiologists independently determined the presence of the dorsal SMN (dSMN) and ventral SMN (vSMN) on each study. Groups were compared by using t tests, and logistic regression was performed to identify predictors of the presence of SMNs. Results One hundred patients (mean age, 40.9 years ± 14.8 [standard deviation]; 61 men) were evaluated. The dSMN and vSMN were identified in 86% (86 of 100) and 76% (76 of 100) of rs-fMRI scans and 85% (85 of 100) and 69% (69 of 100) of sc-fMRI scans, respectively. The concordance between rs-fMRI and sc-fMRI for presence of dSMN and vSMN was 75% (75 of 100 patients) and 53% (53 of 100 patients), respectively. In 10 of 14 patients (71%) where rs-fMRI did not show the dSMN, sc-fMRI demonstrated it. This rate was 67% for the vSMN (16 of 24 patients). Conclusion In the majority of patients, independent component analysis of sentence completion task functional MRI scans reliably demonstrated the somatomotor network compared with resting-state functional MRI scans. Identifying target networks with a single sentence completion scan could reduce overall functional MRI scanning times by eliminating the need for separate motor tasks. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Field and Birn in this issue.
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Affiliation(s)
- Elham Beheshtian
- From the Division of Neuroradiology, the Russell H. Morgan Department of Radiology and Radiological Science (E.B., R.J., A.M.S., S.A., J.J.P., S.K.G., H.I.S.) and the Department of Neurosurgery (J.J.P.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD 21287; Division of Neuroradiology, Department of Radiology, Temple University Hospital, Philadelphia, Pa (V.S.); Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Md (G.W., M.A.L., B.S.C.); and the Malone Center for Engineering in Healthcare, the Whiting School of Engineering, Johns Hopkins University, Baltimore, Md (H.I.S.)
| | - Rozita Jalilianhasanpour
- From the Division of Neuroradiology, the Russell H. Morgan Department of Radiology and Radiological Science (E.B., R.J., A.M.S., S.A., J.J.P., S.K.G., H.I.S.) and the Department of Neurosurgery (J.J.P.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD 21287; Division of Neuroradiology, Department of Radiology, Temple University Hospital, Philadelphia, Pa (V.S.); Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Md (G.W., M.A.L., B.S.C.); and the Malone Center for Engineering in Healthcare, the Whiting School of Engineering, Johns Hopkins University, Baltimore, Md (H.I.S.)
| | - Amirali Modir Shanechi
- From the Division of Neuroradiology, the Russell H. Morgan Department of Radiology and Radiological Science (E.B., R.J., A.M.S., S.A., J.J.P., S.K.G., H.I.S.) and the Department of Neurosurgery (J.J.P.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD 21287; Division of Neuroradiology, Department of Radiology, Temple University Hospital, Philadelphia, Pa (V.S.); Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Md (G.W., M.A.L., B.S.C.); and the Malone Center for Engineering in Healthcare, the Whiting School of Engineering, Johns Hopkins University, Baltimore, Md (H.I.S.)
| | - Varun Sethi
- From the Division of Neuroradiology, the Russell H. Morgan Department of Radiology and Radiological Science (E.B., R.J., A.M.S., S.A., J.J.P., S.K.G., H.I.S.) and the Department of Neurosurgery (J.J.P.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD 21287; Division of Neuroradiology, Department of Radiology, Temple University Hospital, Philadelphia, Pa (V.S.); Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Md (G.W., M.A.L., B.S.C.); and the Malone Center for Engineering in Healthcare, the Whiting School of Engineering, Johns Hopkins University, Baltimore, Md (H.I.S.)
| | - Guoqing Wang
- From the Division of Neuroradiology, the Russell H. Morgan Department of Radiology and Radiological Science (E.B., R.J., A.M.S., S.A., J.J.P., S.K.G., H.I.S.) and the Department of Neurosurgery (J.J.P.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD 21287; Division of Neuroradiology, Department of Radiology, Temple University Hospital, Philadelphia, Pa (V.S.); Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Md (G.W., M.A.L., B.S.C.); and the Malone Center for Engineering in Healthcare, the Whiting School of Engineering, Johns Hopkins University, Baltimore, Md (H.I.S.)
| | - Martin A Lindquist
- From the Division of Neuroradiology, the Russell H. Morgan Department of Radiology and Radiological Science (E.B., R.J., A.M.S., S.A., J.J.P., S.K.G., H.I.S.) and the Department of Neurosurgery (J.J.P.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD 21287; Division of Neuroradiology, Department of Radiology, Temple University Hospital, Philadelphia, Pa (V.S.); Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Md (G.W., M.A.L., B.S.C.); and the Malone Center for Engineering in Healthcare, the Whiting School of Engineering, Johns Hopkins University, Baltimore, Md (H.I.S.)
| | - Brian S Caffo
- From the Division of Neuroradiology, the Russell H. Morgan Department of Radiology and Radiological Science (E.B., R.J., A.M.S., S.A., J.J.P., S.K.G., H.I.S.) and the Department of Neurosurgery (J.J.P.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD 21287; Division of Neuroradiology, Department of Radiology, Temple University Hospital, Philadelphia, Pa (V.S.); Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Md (G.W., M.A.L., B.S.C.); and the Malone Center for Engineering in Healthcare, the Whiting School of Engineering, Johns Hopkins University, Baltimore, Md (H.I.S.)
| | - Shruti Agarwal
- From the Division of Neuroradiology, the Russell H. Morgan Department of Radiology and Radiological Science (E.B., R.J., A.M.S., S.A., J.J.P., S.K.G., H.I.S.) and the Department of Neurosurgery (J.J.P.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD 21287; Division of Neuroradiology, Department of Radiology, Temple University Hospital, Philadelphia, Pa (V.S.); Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Md (G.W., M.A.L., B.S.C.); and the Malone Center for Engineering in Healthcare, the Whiting School of Engineering, Johns Hopkins University, Baltimore, Md (H.I.S.)
| | - Jay J Pillai
- From the Division of Neuroradiology, the Russell H. Morgan Department of Radiology and Radiological Science (E.B., R.J., A.M.S., S.A., J.J.P., S.K.G., H.I.S.) and the Department of Neurosurgery (J.J.P.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD 21287; Division of Neuroradiology, Department of Radiology, Temple University Hospital, Philadelphia, Pa (V.S.); Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Md (G.W., M.A.L., B.S.C.); and the Malone Center for Engineering in Healthcare, the Whiting School of Engineering, Johns Hopkins University, Baltimore, Md (H.I.S.)
| | - Sachin K Gujar
- From the Division of Neuroradiology, the Russell H. Morgan Department of Radiology and Radiological Science (E.B., R.J., A.M.S., S.A., J.J.P., S.K.G., H.I.S.) and the Department of Neurosurgery (J.J.P.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD 21287; Division of Neuroradiology, Department of Radiology, Temple University Hospital, Philadelphia, Pa (V.S.); Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Md (G.W., M.A.L., B.S.C.); and the Malone Center for Engineering in Healthcare, the Whiting School of Engineering, Johns Hopkins University, Baltimore, Md (H.I.S.)
| | - Haris I Sair
- From the Division of Neuroradiology, the Russell H. Morgan Department of Radiology and Radiological Science (E.B., R.J., A.M.S., S.A., J.J.P., S.K.G., H.I.S.) and the Department of Neurosurgery (J.J.P.), Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD 21287; Division of Neuroradiology, Department of Radiology, Temple University Hospital, Philadelphia, Pa (V.S.); Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Md (G.W., M.A.L., B.S.C.); and the Malone Center for Engineering in Healthcare, the Whiting School of Engineering, Johns Hopkins University, Baltimore, Md (H.I.S.)
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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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Feasibility, Contrast Sensitivity and Network Specificity of Language fMRI in Presurgical Evaluation for Epilepsy and Brain Tumor Surgery. Brain Topogr 2021; 34:511-524. [PMID: 33837867 DOI: 10.1007/s10548-021-00839-z] [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] [Received: 03/10/2021] [Accepted: 03/30/2021] [Indexed: 02/05/2023]
Abstract
Language fMRI has become an integral part of the planning process in brain surgery. However, fMRI may suffer from confounding factors both on the patient side, as well as on the provider side. In this study, we investigate how patient-related confounds affect the ability of the patient to perform language fMRI tasks (feasibility), the task sensitivity from an image contrast point of view, and the anatomical specificity of expressive and receptive language fMRI protocols. 104 patients were referred for language fMRI in the context of presurgical procedures for epilepsy and brain tumor surgery. Four tasks were used: (1) a verbal fluency (VF) task to map vocabulary use, (2) a semantic description (SD) task to map sentence formation/semantic integration skills, (3) a reading comprehension (RC) task and (4) a listening comprehension (LC) task. Feasibility was excellent in the LC task (100%), but in the acceptable to mediocre range for the rest of the tasks (SD: 87.50%, RC: 85.57%, VF: 67.30%). Feasibility was significantly confounded by age (p = 0.020) and education level (p = 0.003) in VF, by education level (p = 0.004) and lesion laterality (p = 0.019) in SD and by age (p = 0.001), lesion laterality (p = 0.007) and lesion severity (p = 0.048) in RC. All tasks were comparable regarding sensitivity in generating statistically significant image contrast (VF: 90.00%, SD: 92.30%, RC: 93.25%, LC: 88.46%). The lobe of the lesion (p = 0.005) and the age (p = 0.009) confounded contrast sensitivity in the VF and SD tasks respectively. Both VF and LC tasks demonstrated unilateral lateralization of posterior language areas; only the LC task showed unilateral lateralization of anterior language areas. Our study highlights the effects of patient-related confounding factors on language fMRI and proposes LC as the most feasible, less confounded, and efficiently lateralizing task in the clinical presurgical context.
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Ades-Aron B, Lemberskiy G, Veraart J, Golfinos J, Fieremans E, Novikov DS, Shepherd T. Improved Task-based Functional MRI Language Mapping in Patients with Brain Tumors through Marchenko-Pastur Principal Component Analysis Denoising. Radiology 2020; 298:365-373. [PMID: 33289611 DOI: 10.1148/radiol.2020200822] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Background Functional MRI improves preoperative planning in patients with brain tumors, but task-correlated signal intensity changes are only 2%-3% above baseline. This makes accurate functional mapping challenging. Marchenko-Pastur principal component analysis (MP-PCA) provides a novel strategy to separate functional MRI signal from noise without requiring user input or prior data representation. Purpose To determine whether MP-PCA denoising improves activation magnitude for task-based functional MRI language mapping in patients with brain tumors. Materials and Methods In this Health Insurance Portability and Accountability Act-compliant study, MP-PCA performance was first evaluated by using simulated functional MRI data with a known ground truth. Right-handed, left-language-dominant patients with brain tumors who successfully performed verb generation, sentence completion, and finger tapping functional MRI tasks were retrospectively identified between January 2017 and August 2018. On the group level, for each task, histograms of z scores for original and MP-PCA denoised data were extracted from relevant regions and contralateral homologs were seeded by a neuroradiologist blinded to functional MRI findings. Z scores were compared with paired two-sided t tests, and distributions were compared with effect size measurements and the Kolmogorov-Smirnov test. The number of voxels with a z score greater than 3 was used to measure task sensitivity relative to task duration. Results Twenty-three patients (mean age ± standard deviation, 43 years ± 18; 13 women) were evaluated. MP-PCA denoising led to a higher median z score of task-based functional MRI voxel activation in left hemisphere cortical regions for verb generation (from 3.8 ± 1.0 to 4.5 ± 1.4; P < .001), sentence completion (from 3.7 ± 1.0 to 4.3 ± 1.4; P < .001), and finger tapping (from 6.9 ± 2.4 to 7.9 ± 2.9; P < .001). Median z scores did not improve in contralateral homolog regions for verb generation (from -2.7 ± 0.54 to -2.5 ± 0.40; P = .90), sentence completion (from -2.3 ± 0.21 to -2.4 ± 0.37; P = .39), or finger tapping (from -2.3 ± 1.20 to -2.7 ± 1.40; P = .07). Individual functional MRI task durations could be truncated by at least 40% after MP-PCA without degradation of clinically relevant correlations between functional cortex and functional MRI tasks. Conclusion Denoising with Marchenko-Pastur principal component analysis led to higher task correlations in relevant cortical regions during functional MRI language mapping in patients with brain tumors. © RSNA, 2020 Online supplemental material is available for this article.
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Affiliation(s)
- Benjamin Ades-Aron
- From the Center for Biomedical Imaging, Department of Radiology (B.A.A., G.L., J.V., E.F., D.S.N., T.S.) and Department of Neurosurgery (J.G.), New York University School of Medicine, 2nd Floor, 660 First Ave, New York, NY 10016; and Department of Electrical and Computer Engineering, New York University Tandon School of Engineering, New York, NY (B.A.A.)
| | - Gregory Lemberskiy
- From the Center for Biomedical Imaging, Department of Radiology (B.A.A., G.L., J.V., E.F., D.S.N., T.S.) and Department of Neurosurgery (J.G.), New York University School of Medicine, 2nd Floor, 660 First Ave, New York, NY 10016; and Department of Electrical and Computer Engineering, New York University Tandon School of Engineering, New York, NY (B.A.A.)
| | - Jelle Veraart
- From the Center for Biomedical Imaging, Department of Radiology (B.A.A., G.L., J.V., E.F., D.S.N., T.S.) and Department of Neurosurgery (J.G.), New York University School of Medicine, 2nd Floor, 660 First Ave, New York, NY 10016; and Department of Electrical and Computer Engineering, New York University Tandon School of Engineering, New York, NY (B.A.A.)
| | - John Golfinos
- From the Center for Biomedical Imaging, Department of Radiology (B.A.A., G.L., J.V., E.F., D.S.N., T.S.) and Department of Neurosurgery (J.G.), New York University School of Medicine, 2nd Floor, 660 First Ave, New York, NY 10016; and Department of Electrical and Computer Engineering, New York University Tandon School of Engineering, New York, NY (B.A.A.)
| | - Els Fieremans
- From the Center for Biomedical Imaging, Department of Radiology (B.A.A., G.L., J.V., E.F., D.S.N., T.S.) and Department of Neurosurgery (J.G.), New York University School of Medicine, 2nd Floor, 660 First Ave, New York, NY 10016; and Department of Electrical and Computer Engineering, New York University Tandon School of Engineering, New York, NY (B.A.A.)
| | - Dmitry S Novikov
- From the Center for Biomedical Imaging, Department of Radiology (B.A.A., G.L., J.V., E.F., D.S.N., T.S.) and Department of Neurosurgery (J.G.), New York University School of Medicine, 2nd Floor, 660 First Ave, New York, NY 10016; and Department of Electrical and Computer Engineering, New York University Tandon School of Engineering, New York, NY (B.A.A.)
| | - Timothy Shepherd
- From the Center for Biomedical Imaging, Department of Radiology (B.A.A., G.L., J.V., E.F., D.S.N., T.S.) and Department of Neurosurgery (J.G.), New York University School of Medicine, 2nd Floor, 660 First Ave, New York, NY 10016; and Department of Electrical and Computer Engineering, New York University Tandon School of Engineering, New York, NY (B.A.A.)
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21
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Abstract
Resting state functional MR imaging methods can provide localization of the language system; however, presurgical functional localization of the language system with task-based functional MR imaging is the current standard of care before resection of brain tumors. These methods provide similar results and comparing them could be helpful for presurgical planning. We combine information from 3 data resources to provide quantitative information on the components of the language system. Tables and figures compare anatomic information, localization information from resting state fMR imaging, and activation patterns in different components of the language system expected from commonly used task fMR imaging experiments.
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22
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Abstract
There are many technical and nontechnical steps involved in a successful clinical functional MRI (fMRI) scan. The output from scanning and analysis can only be as good as the input, so task instruction and rehearsal are the most important steps during an clinical fMRI procedure. Properly pre-processed data significantly affects statistical analysis, which has a great impact on image interpretation. Even though there is general agreement on how to process clinical fMRI data, such as algorithms for head motion detection and correction, the theory and practicalities associated with data processing remain complex and constantly evolving.
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23
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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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24
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Jansma JM, Rutten GJ, Ramsey LE, Snijders TJ, Bizzi A, Rosengarth K, Dodoo-Schittko F, Hattingen E, de la Peña MJ, von Campe G, Jehna M, Ramsey NF. Automatic identification of atypical clinical fMRI results. Neuroradiology 2020; 62:1677-1688. [PMID: 32812070 PMCID: PMC7666675 DOI: 10.1007/s00234-020-02510-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Accepted: 07/30/2020] [Indexed: 01/03/2023]
Abstract
Purpose Functional MRI is not routinely used for neurosurgical planning despite potential important advantages, due to difficulty of determining quality. We introduce a novel method for objective evaluation of fMRI scan quality, based on activation maps. A template matching analysis (TMA) is presented and tested on data from two clinical fMRI protocols, performed by healthy controls in seven clinical centers. Preliminary clinical utility is tested with data from low-grade glioma patients. Methods Data were collected from 42 healthy subjects from seven centers, with standardized finger tapping (FT) and verb generation (VG) tasks. Copies of these “typical” data were deliberately analyzed incorrectly to assess feasibility of identifying them as “atypical.” Analyses of the VG task administered to 32 tumor patients assessed sensitivity of the TMA method to anatomical abnormalities. Results TMA identified all atypical activity maps for both tasks, at the cost of incorrectly classifying 3.6 (VG)–6.5% (FT) of typical maps as atypical. For patients, the average TMA was significantly higher than atypical healthy scans, despite localized anatomical abnormalities caused by a tumor. Conclusion This study supports feasibility of TMA for objective identification of atypical activation patterns for motor and verb generation fMRI protocols. TMA can facilitate the use and evaluation of clinical fMRI in hospital settings that have limited access to fMRI experts. In a clinical setting, this method could be applied to automatically flag fMRI scans showing atypical activation patterns for further investigation to determine whether atypicality is caused by poor scan data quality or abnormal functional topography.
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Affiliation(s)
- J Martijn Jansma
- Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Utrecht, The Netherlands.,Department of Neurosurgery, Elisabeth-TweeSteden Hospital, Tilburg, The Netherlands
| | - Geert-Jan Rutten
- Department of Neurosurgery, Elisabeth-TweeSteden Hospital, Tilburg, The Netherlands
| | - Lenny E Ramsey
- Department of Neurosurgery, McGovern Medical School, University of Texas Health Science Center, Houston, TX, USA
| | - T J Snijders
- Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Alberto Bizzi
- Neuroradiology Unit, Istituto Clinico Humanitas IRCCS, Rozzano, Milan, Italy
| | - Katharina Rosengarth
- Institute for Experimental Psychology, University of Regensburg, Regensburg, Germany
| | - Frank Dodoo-Schittko
- Medical Sociology, Institute for Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Elke Hattingen
- Institute of Neuroradiology, Goethe University, Frankfurt, Germany
| | | | - Gord von Campe
- Department of Neurosurgery, Medical University of Graz, Graz, Austria
| | - Margit Jehna
- Division of Neuroradiology, Vascular and Interventional Radiology, Medical University of Graz, Graz, Austria
| | - Nick F Ramsey
- Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Utrecht, The Netherlands. .,Braincarta BV, Utrecht, The Netherlands.
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25
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Luckett P, Lee JJ, Park KY, Dierker D, Daniel AGS, Seitzman BA, Hacker CD, Ances BM, Leuthardt EC, Snyder AZ, Shimony JS. Mapping of the Language Network With Deep Learning. Front Neurol 2020; 11:819. [PMID: 32849247 PMCID: PMC7419701 DOI: 10.3389/fneur.2020.00819] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 06/30/2020] [Indexed: 01/01/2023] Open
Abstract
Background: Pre-surgical functional localization of eloquent cortex with task-based functional MRI (T-fMRI) is part of the current standard of care prior to resection of brain tumors. Resting state fMRI (RS-fMRI) is an alternative method currently under investigation. Here, we compare group level language localization using T-fMRI vs. RS-fMRI analyzed with 3D deep convolutional neural networks (3DCNN). Methods: We analyzed data obtained in 35 patients with brain tumors that had both language T-fMRI and RS-MRI scans during pre-surgical evaluation. The T-fMRI data were analyzed using conventional techniques. The language associated resting state network was mapped using a 3DCNN previously trained with data acquired in >2,700 normal subjects. Group level results obtained by both methods were evaluated using receiver operator characteristic analysis of probability maps of language associated regions, taking as ground truth meta-analytic maps of language T-fMRI responses generated on the Neurosynth platform. Results: Both fMRI methods localized major components of the language system (areas of Broca and Wernicke). Word-stem completion T-fMRI strongly activated Broca's area but also several task-general areas not specific to language. RS-fMRI provided a more specific representation of the language system. Conclusion: 3DCNN was able to accurately localize the language network. Additionally, 3DCNN performance was remarkably tolerant of a limited quantity of RS-fMRI data.
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Affiliation(s)
- Patrick Luckett
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - John J Lee
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
| | - Ki Yun Park
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
| | - Donna Dierker
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
| | - Andy G S Daniel
- Department of Biomedical Engineering, Washington University, St. Louis, MO, United States
| | - Benjamin A Seitzman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Carl D Hacker
- Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, United States
| | - Beau M Ances
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Eric C Leuthardt
- Department of Biomedical Engineering, Washington University, St. Louis, MO, United States.,Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, United States
| | - Abraham Z Snyder
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States.,Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
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26
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Kumar VA, Heiba IM, Prabhu SS, Chen MM, Colen RR, Young AL, Johnson JM, Hou P, Noll K, Ferguson SD, Rao G, Lang FF, Schomer DF, Liu HL. The role of resting-state functional MRI for clinical preoperative language mapping. Cancer Imaging 2020; 20:47. [PMID: 32653026 PMCID: PMC7353792 DOI: 10.1186/s40644-020-00327-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Accepted: 07/02/2020] [Indexed: 11/10/2022] Open
Abstract
Background Task-based functional MRI (tb-fMRI) is a well-established technique used to identify eloquent cortex, but has limitations, particularly in cognitively impaired patients who cannot perform language paradigms. Resting-state functional MRI (rs-fMRI) is a potential alternative modality for presurgical mapping of language networks that does not require task performance. The purpose of our study is to determine the utility of rs-fMRI for clinical preoperative language mapping when tb-fMRI is limited. Methods We retrospectively reviewed 134 brain tumor patients who underwent preoperative fMRI language mapping. rs-fMRI was post-processed with seed-based correlation (SBC) analysis, when language tb-fMRI was limited. Two neuroradiologists reviewed both the tb-fMRI and rs-fMRI results. Six neurosurgeons retrospectively rated the usefulness of rs-fMRI for language mapping in their patients. Results Of the 134 patients, 49 cases had limited tb-fMRI and rs-fMRI was post-processed. Two neuroradiologists found rs-fMRI beneficial for functional language mapping in 41(84%) and 43 (88%) cases respectively; Cohen’s kappa is 0.83, with a 95% confidence interval (0.61, 1.00). The neurosurgeons found rs-fMRI “definitely” useful in 26 cases (60%) and “somewhat” useful in 13 cases (30%) in locating potential eloquent language centers of clinical interest. Six unsuccessful rs-fMRI cases were due to: head motion (2 cases), nonspecific functionality connectivity outside the posterior language network (1 case), and an unknown system instability (3 cases). Conclusions This study is a proof of concept that shows SBC rs-fMRI may be a viable alternative for clinical language mapping when tb-fMRI is limited.
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Affiliation(s)
- Vinodh A Kumar
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Islam M Heiba
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sujit S Prabhu
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Melissa M Chen
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Rivka R Colen
- Department of Diagnostic Radiology, The University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Angela L Young
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jason M Johnson
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ping Hou
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Kyle Noll
- Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sherise D Ferguson
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ganesh Rao
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Frederick F Lang
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Donald F Schomer
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ho-Ling Liu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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27
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Rani N, Singh B, Kumar N, Singh P, Hazari PP, Vyas S, Hooda M, Chitkara A, Shekhawat AS, Gupta SK, Radotra BD, Mishra AK. [ 99mTc]-Bis-Methionine-DTPA Single-Photon Emission Computed Tomography Impacting Glioma Management: A Sensitive Indicator for Postsurgical/Chemoradiotherapy Response Assessment. Cancer Biother Radiopharm 2020; 36:568-578. [PMID: 32644819 DOI: 10.1089/cbr.2020.3696] [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] [Indexed: 11/13/2022] Open
Abstract
Background: The present study evaluated the prognostic value of [99mTc]MDM (bis-methionine-DTPA) follow-up single-photon emission computed tomography (SPECT) imaging for response assessment to chemoradiotherapy in glioma postoperatively. Materials and Methods: One hundred fourteen glioma patients (80 M:34 F) were followed postoperatively by sequential [99mTc]MDM SPECT, dynamic susceptibility contrast-enhanced (DSCE)-MRI, and magnetic resonance spectroscopy (MRS) at baseline, 6, 12, and 22.5 months postchemoradiotherapy. The quantitative imaging results and the clinical outcome were used for response assessment and for the final diagnosis. The quantitative parameter of [99mTc]MDM SPECT were also used for survival analysis. Results: A significantly (p = 0.001) lower target to nontarget (T/NT) ratio was observed in responders than in nonresponders. The sensitivity and specificity of [99mTc]MDM-SPECT for identifying tumor recurrence from radiation necrosis at a cutoff ratio of 1.90 were estimated at 97.9% and 92%. Whereas, the sensitivity and specificity of DSCE-MRI with the normalized cerebral blood volume (nCBV) cutoff of 3.32 for this differentiation was found to be 84.6% and 93.0%. MRS intensity ratios of Cho/NAA and Cho/Cr provided comparatively lower sensitivity of 81.0% and 85.3% and specificity of 73.0% and 73.7%. T/NT ratios correlated with nCBV (r = 0.775, p < 0.001) and to a moderate extent with Cho/NAA ratios (r = 0.467, p = 0.001). [99mTc]MDM SPECT and DSCE-MRI provided comparable results for predicting response assessment to chemoradiotherapy. There was a final diagnosis in 72 patients, of which 47 cases were tumor recurrence and 25 were radiation necrosis. The Kaplan-Meier analysis indicated that patients with T/NT ratio <1.9 showed prolonged survival (53.8 months) as compared (37.2 months) with those who demonstrated T/NT ratio >1.9 (p = 0.0001). Conclusion: Thus, this low-cost SPECT technique in combination with DSCE-MRI can be used accurately for mapping the disease activity, response assessment, and survival in glioma. [99mTc]MDM SPECT and DSCE-MRI had the same diagnostic efficacy to detect recurrent/residual tumor and radiation necrosis while MRS was inferior to both the techniques.
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Affiliation(s)
- Nisha Rani
- Department of Nuclear Medicine, PGIMER, Chandigarh, India
| | | | | | - Paramjeet Singh
- Department of Radio-Diagnosis and Imaging, PGIMER, Chandigarh, India
| | - Puja P Hazari
- Division of Cyclotron and Radiopharmaceutical Sciences, Institute of Nuclear Medicine and Allied Science, DRDO, New Delhi, India
| | - Sameer Vyas
- Department of Radio-Diagnosis and Imaging, PGIMER, Chandigarh, India
| | - Monika Hooda
- Department of Nuclear Medicine, PGIMER, Chandigarh, India
| | - Ajay Chitkara
- Department of Nuclear Medicine, PGIMER, Chandigarh, India
| | | | - Sunil K Gupta
- Department of Neurosurgery, PGIMER, Chandigarh, India
| | | | - Anil K Mishra
- Division of Cyclotron and Radiopharmaceutical Sciences, Institute of Nuclear Medicine and Allied Science, DRDO, New Delhi, India
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28
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Montgomery MK, Kim SH, Dovas A, Zhao HT, Goldberg AR, Xu W, Yagielski AJ, Cambareri MK, Patel KB, Mela A, Humala N, Thibodeaux DN, Shaik MA, Ma Y, Grinband J, Chow DS, Schevon C, Canoll P, Hillman EMC. Glioma-Induced Alterations in Neuronal Activity and Neurovascular Coupling during Disease Progression. Cell Rep 2020; 31:107500. [PMID: 32294436 PMCID: PMC7443283 DOI: 10.1016/j.celrep.2020.03.064] [Citation(s) in RCA: 55] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Revised: 02/10/2020] [Accepted: 03/18/2020] [Indexed: 12/14/2022] Open
Abstract
Diffusely infiltrating gliomas are known to cause alterations in cortical function, vascular disruption, and seizures. These neurological complications present major clinical challenges, yet their underlying mechanisms and causal relationships to disease progression are poorly characterized. Here, we follow glioma progression in awake Thy1-GCaMP6f mice using in vivo wide-field optical mapping to monitor alterations in both neuronal activity and functional hemodynamics. The bilateral synchrony of spontaneous neuronal activity gradually decreases in glioma-infiltrated cortical regions, while neurovascular coupling becomes progressively disrupted compared to uninvolved cortex. Over time, mice develop diverse patterns of high amplitude discharges and eventually generalized seizures that appear to originate at the tumors' infiltrative margins. Interictal and seizure events exhibit positive neurovascular coupling in uninfiltrated cortex; however, glioma-infiltrated regions exhibit disrupted hemodynamic responses driving seizure-evoked hypoxia. These results reveal a landscape of complex physiological interactions occurring during glioma progression and present new opportunities for exploring novel biomarkers and therapeutic targets.
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Affiliation(s)
- Mary Katherine Montgomery
- Laboratory for Functional Optical Imaging, Zuckerman Mind Brain Behavior Institute, Departments of Biomedical Engineering and Radiology, Columbia University, New York, NY 10027, USA
| | - Sharon H Kim
- Laboratory for Functional Optical Imaging, Zuckerman Mind Brain Behavior Institute, Departments of Biomedical Engineering and Radiology, Columbia University, New York, NY 10027, USA
| | - Athanassios Dovas
- Department of Pathology and Cell Biology, Irving Cancer Research Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Hanzhi T Zhao
- Laboratory for Functional Optical Imaging, Zuckerman Mind Brain Behavior Institute, Departments of Biomedical Engineering and Radiology, Columbia University, New York, NY 10027, USA
| | - Alexander R Goldberg
- Department of Pathology and Cell Biology, Irving Cancer Research Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Weihao Xu
- Laboratory for Functional Optical Imaging, Zuckerman Mind Brain Behavior Institute, Departments of Biomedical Engineering and Radiology, Columbia University, New York, NY 10027, USA
| | - Alexis J Yagielski
- Laboratory for Functional Optical Imaging, Zuckerman Mind Brain Behavior Institute, Departments of Biomedical Engineering and Radiology, Columbia University, New York, NY 10027, USA
| | - Morgan K Cambareri
- Laboratory for Functional Optical Imaging, Zuckerman Mind Brain Behavior Institute, Departments of Biomedical Engineering and Radiology, Columbia University, New York, NY 10027, USA
| | - Kripa B Patel
- Laboratory for Functional Optical Imaging, Zuckerman Mind Brain Behavior Institute, Departments of Biomedical Engineering and Radiology, Columbia University, New York, NY 10027, USA
| | - Angeliki Mela
- Department of Pathology and Cell Biology, Irving Cancer Research Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Nelson Humala
- Department of Pathology and Cell Biology, Irving Cancer Research Center, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - David N Thibodeaux
- Laboratory for Functional Optical Imaging, Zuckerman Mind Brain Behavior Institute, Departments of Biomedical Engineering and Radiology, Columbia University, New York, NY 10027, USA
| | - Mohammed A Shaik
- Laboratory for Functional Optical Imaging, Zuckerman Mind Brain Behavior Institute, Departments of Biomedical Engineering and Radiology, Columbia University, New York, NY 10027, USA
| | - Ying Ma
- Laboratory for Functional Optical Imaging, Zuckerman Mind Brain Behavior Institute, Departments of Biomedical Engineering and Radiology, Columbia University, New York, NY 10027, USA
| | - Jack Grinband
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Daniel S Chow
- Department of Radiological Sciences, University of California, Irvine, Orange, CA 92868, USA
| | - Catherine Schevon
- Department of Neurology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Peter Canoll
- Department of Pathology and Cell Biology, Irving Cancer Research Center, Columbia University Irving Medical Center, New York, NY 10032, USA.
| | - Elizabeth M C Hillman
- Laboratory for Functional Optical Imaging, Zuckerman Mind Brain Behavior Institute, Departments of Biomedical Engineering and Radiology, Columbia University, New York, NY 10027, USA.
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29
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Brumer I, De Vita E, Ashmore J, Jarosz J, Borri M. Implementation of clinically relevant and robust fMRI-based language lateralization: Choosing the laterality index calculation method. PLoS One 2020; 15:e0230129. [PMID: 32163517 PMCID: PMC7067428 DOI: 10.1371/journal.pone.0230129] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Accepted: 02/23/2020] [Indexed: 11/19/2022] Open
Abstract
The assessment of language lateralization has become widely used when planning neurosurgery close to language areas, due to individual specificities and potential influence of brain pathology. Functional magnetic resonance imaging (fMRI) allows non-invasive and quantitative assessment of language lateralization for presurgical planning using a laterality index (LI). However, the conventional method is limited by the dependence of the LI on the chosen activation threshold. To overcome this limitation, different threshold-independent LI calculations have been reported. The purpose of this study was to propose a simplified approach to threshold-independent LI calculation and compare it with three previously reported methods on the same cohort of subjects. Fifteen healthy subjects, who performed picture naming, verb generation, and word fluency tasks, were scanned. LI values were calculated for all subjects using four methods, and considering either the whole hemisphere or an atlas-defined language area. For each method, the subjects were ranked according to the calculated LI values, and the obtained rankings were compared. All LI calculation methods agreed in differentiating strong from weak lateralization on both hemispheric and regional scales (Spearman's correlation coefficients 0.59-1.00). In general, a more lateralized activation was found in the language area than in the whole hemisphere. The new method is well suited for application in the clinical practice as it is simple to implement, fast, and robust. The good agreement between LI calculation methods suggests that the choice of method is not key. Nevertheless, it should be consistent to allow a relative comparison of language lateralization between subjects.
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Affiliation(s)
- Irène Brumer
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Department of Neuroradiology, King’s College Hospital, London, United Kingdom
| | - Enrico De Vita
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Jonathan Ashmore
- Department of Neuroradiology, King’s College Hospital, London, United Kingdom
- Department of Medical Physics and Bioengineering, NHS Highland, Inverness, United Kingdom
| | - Jozef Jarosz
- Department of Neuroradiology, King’s College Hospital, London, United Kingdom
| | - Marco Borri
- Department of Neuroradiology, King’s College Hospital, London, United Kingdom
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30
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Leung LWL, Unadkat P, Bertotti MM, Bi WL, Essayed WI, Bunevicius A, Chavakula V, Rigolo L, Fumagalli L, Tie Z, Golby AJ, Tie Y. Clinical Utility of Preoperative Bilingual Language fMRI Mapping in Patients with Brain Tumors. J Neuroimaging 2020; 30:175-183. [PMID: 32037662 DOI: 10.1111/jon.12690] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Revised: 01/17/2020] [Accepted: 01/21/2020] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND AND PURPOSE Previous literature has demonstrated disparity in the postoperative recovery of first and second language function of bilingual neurosurgical patients. However, it is unclear to whether preoperative brain mapping of both languages is needed. In this study, we aimed to evaluate the clinical utility of language task functional MRI (fMRI) implemented in both languages in bilingual patients. METHODS We retrospectively examined fMRI data of 13 bilingual brain tumor patients (age: 23 to 59 years) who performed antonym generation task-based fMRIs in English and non-English language. The usefulness of bilingual language mapping was evaluated using a structured survey administered to 5 neurosurgeons. Additionally, quantitative comparison between the brain activation maps of both languages was performed. RESULTS Survey responses revealed differences in raters' surgical approach, including asleep versus awake surgery and extent of resection, after viewing the language fMRI maps. Additional non-English fMRI led to changes in surgical decision-making and bettered localization of language areas. Quantitative analysis revealed an increase in laterality index (LI) in non-English fMRI compared to English fMRI. The Dice coefficient demonstrated fair overlap (.458 ± .160) between the activation maps. CONCLUSION Bilingual fMRI mapping of bilingual patients allows to better appreciate functionally active language areas that may be neglected in single language mapping. Utility of bilingual mapping was supported by changes in both surgical approach and LI measurements, suggesting its benefit on preoperative language mapping.
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Affiliation(s)
- Lok Wa Laura Leung
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.,Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong
| | - Prashin Unadkat
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Melina More Bertotti
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.,Hospital Unimed São José, Brazil
| | - Wenya Linda Bi
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Walid Ibn Essayed
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Adomas Bunevicius
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Vamsidhar Chavakula
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Laura Rigolo
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Luca Fumagalli
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.,Neurocenter of Southern Switzerland, Neurosurgery Clinic, Lugano, Switzerland
| | - Ziyun Tie
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.,Department of Psychology, University of California, San Diego, CA
| | - Alexandra J Golby
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.,Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Yanmei Tie
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
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Batouli SAH, Alemi R, Khoshkhouy Delshad H, Oghabian MA. The influence of mental fatigue on the face and word encoding activations. Clin Neurol Neurosurg 2020; 189:105626. [DOI: 10.1016/j.clineuro.2019.105626] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 11/23/2019] [Accepted: 11/27/2019] [Indexed: 11/25/2022]
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Rigolo L, Essayed WI, Tie Y, Norton I, Mukundan S, Golby A. Intraoperative Use of Functional MRI for Surgical Decision Making after Limited or Infeasible Electrocortical Stimulation Mapping. J Neuroimaging 2019; 30:184-191. [PMID: 31867823 DOI: 10.1111/jon.12683] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 11/09/2019] [Accepted: 11/11/2019] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND AND PURPOSE Functional magnetic resonance imaging (fMRI) is becoming widely recognized as a key component of preoperative neurosurgical planning, although intraoperative electrocortical stimulation (ECS) is considered the gold standard surgical brain mapping method. However, acquiring and interpreting ECS results can sometimes be challenging. This retrospective study assesses whether intraoperative availability of fMRI impacted surgical decision-making when ECS was problematic or unobtainable. METHODS Records were reviewed for 191 patients who underwent presurgical fMRI with fMRI loaded into the neuronavigation system. Four patients were excluded as a bur-hole biopsy was performed. Imaging was acquired at 3 Tesla and analyzed using the general linear model with significantly activated pixels determined via individually determined thresholds. fMRI maps were displayed intraoperatively via commercial neuronavigation systems. RESULTS Seventy-one cases were planned ECS; however, 18 (25.35%) of these procedures were either not attempted or aborted/limited due to: seizure (10), patient difficulty cooperating with the ECS mapping (4), scarring/limited dural opening (3), or dural bleeding (1). In all aborted/limited ECS cases, the surgeon continued surgery using fMRI to guide surgical decision-making. There was no significant difference in the incidence of postoperative deficits between cases with completed ECS and those with limited/aborted ECS. CONCLUSIONS Preoperative fMRI allowed for continuation of surgery in over one-fourth of patients in which planned ECS was incomplete or impossible, without a significantly different incidence of postoperative deficits compared to the patients with completed ECS. This demonstrates additional value of fMRI beyond presurgical planning, as fMRI data served as a backup method to ECS.
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Affiliation(s)
- Laura Rigolo
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.,Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Walid Ibn Essayed
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Yanmei Tie
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Isaiah Norton
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Srinivasan Mukundan
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Alexandra Golby
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.,Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
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Lemée JM, Berro DH, Bernard F, Chinier E, Leiber LM, Menei P, Ter Minassian A. Resting-state functional magnetic resonance imaging versus task-based activity for language mapping and correlation with perioperative cortical mapping. Brain Behav 2019; 9:e01362. [PMID: 31568681 PMCID: PMC6790308 DOI: 10.1002/brb3.1362] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Revised: 05/19/2019] [Accepted: 06/24/2019] [Indexed: 12/17/2022] Open
Abstract
INTRODUCTION Preoperative language mapping using functional magnetic resonance imaging (fMRI) aims to identify eloquent areas in the vicinity of surgically resectable brain lesions. fMRI methodology relies on the blood-oxygen-level-dependent (BOLD) analysis to identify brain language areas. Task-based fMRI studies the BOLD signal increase in brain areas during a language task to identify brain language areas, which requires patients' cooperation, whereas resting-state fMRI (rsfMRI) allows identification of functional networks without performing any explicit task through the analysis of the synchronicity of spontaneous BOLD signal oscillation between brain areas. The aim of this study was to compare preoperative language mapping using rsfMRI and task fMRI to cortical mapping (CM) during awake craniotomies. METHODS Fifty adult patients surgically treated for a brain lesion were enrolled. All patients had a presurgical language mapping with both task fMRI and rsfMRI. Identified language networks were compared to perioperative language mapping using electric cortical stimulation. RESULTS Resting-state fMRI was able to detect brain language areas during CM with a sensitivity of 100% compared to 65.6% with task fMRI. However, we were not able to perform a specificity analysis and compare task-based and rest fMRI with our perioperative setting in the current study. In second-order analysis, task fMRI imaging included main nodes of the SN and main areas involved in semantics were identified in rsfMRI. CONCLUSION Resting-state fMRI for presurgical language mapping is easy to implement, allowing the identification of functional brain language network with a greater sensitivity than task-based fMRI, at the cost of some precautions and a lower specificity. Further study is required to compare both the sensitivity and the specificity of the two methods and to evaluate the clinical value of rsfMRI as an alternative tool for the presurgical identification of brain language areas.
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Affiliation(s)
- Jean-Michel Lemée
- Department of Neurosurgery, University Hospital of Angers, Angers, France.,INSERM CRCINA Équipe 17, Bâtiment IRIS, Angers, France
| | | | - Florian Bernard
- Department of Neurosurgery, University Hospital of Angers, Angers, France.,Angers Medical Faculty, Anatomy Laboratory, Angers, France
| | - Eva Chinier
- Department of Physical Medicine and Rehabilitation, University Hospital of Angers, Nantes, France
| | | | - Philippe Menei
- Department of Neurosurgery, University Hospital of Angers, Angers, France.,INSERM CRCINA Équipe 17, Bâtiment IRIS, Angers, France
| | - Aram Ter Minassian
- Department of Anesthesiology, University Hospital of Angers, Angers, France.,LARIS EA 7315, Image Signal et Sciences du Vivant, Angers Teaching Hospital, Angers, France
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Agarwal S, Sair HI, Gujar S, Pillai JJ. Language Mapping With fMRI: Current Standards and Reproducibility. Top Magn Reson Imaging 2019; 28:225-233. [PMID: 31385902 DOI: 10.1097/rmr.0000000000000216] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Clinical use of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) is a relatively new phenomenon, with only about 3 decades of collective experience. Nevertheless, task-based BOLD fMRI has been widely accepted for presurgical planning, over traditional methods, which are invasive and at times perilous. Many studies have demonstrated the ability of BOLD fMRI to make substantial clinical impact with respect to surgical planning and preoperative risk assessment, especially to localize the eloquent motor and visual areas. Reproducibility and repeatability of language fMRI are important in the assessment of its clinical usefulness. There are national efforts currently underway to standardize language fMRI. The American Society of Functional Neuroradiology (ASFNR) has recently provided guidelines on fMRI paradigm algorithms for presurgical language assessment for language lateralization and localization. In this review article, we provide a comprehensive overview of current standards of language fMRI mapping and its reproducibility.
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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
| | - Haris I Sair
- Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Sachin Gujar
- Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD
| | - Jay J Pillai
- Division of Neuroradiology, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD
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Mancini M, Vos SB, Vakharia VN, O'Keeffe AG, Trimmel K, Barkhof F, Dorfer C, Soman S, Winston GP, Wu C, Duncan JS, Sparks R, Ourselin S. Automated fiber tract reconstruction for surgery planning: Extensive validation in language-related white matter tracts. Neuroimage Clin 2019; 23:101883. [PMID: 31163386 PMCID: PMC6545442 DOI: 10.1016/j.nicl.2019.101883] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Revised: 04/18/2019] [Accepted: 05/25/2019] [Indexed: 12/30/2022]
Abstract
Diffusion MRI and tractography hold great potential for surgery planning, especially to preserve eloquent white matter during resections. However, fiber tract reconstruction requires an expert with detailed understanding of neuroanatomy. Several automated approaches have been proposed, using different strategies to reconstruct the white matter tracts in a supervised fashion. However, validation is often limited to comparison with manual delineation by overlap-based measures, which is limited in characterizing morphological and topological differences. In this work, we set up a fully automated pipeline based on anatomical criteria that does not require manual intervention, taking advantage of atlas-based criteria and advanced acquisition protocols available on clinical-grade MRI scanners. Then, we extensively validated it on epilepsy patients with specific focus on language-related bundles. The validation procedure encompasses different approaches, including simple overlap with manual segmentations from two experts, feasibility ratings from external multiple clinical raters and relation with task-based functional MRI. Overall, our results demonstrate good quantitative agreement between automated and manual segmentation, in most cases better performances of the proposed method in qualitative terms, and meaningful relationships with task-based fMRI. In addition, we observed significant differences between experts in terms of both manual segmentation and external ratings. These results offer important insights on how different levels of validation complement each other, supporting the idea that overlap-based measures, although quantitative, do not offer a full perspective on the similarities and differences between automated and manual methods.
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Affiliation(s)
- Matteo Mancini
- Centre for Medical Image Computing, University College London, London, United Kingdom.
| | - Sjoerd B Vos
- Centre for Medical Image Computing, University College London, London, United Kingdom; Epilepsy Society MRI Unit, Chalfont St Peter, United Kingdom
| | - Vejay N Vakharia
- Department of Clinical and Experimental Epilepsy, University College London, London, United Kingdom; National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
| | - Aidan G O'Keeffe
- Department of Statistical Science, University College London, London, UK
| | - Karin Trimmel
- Epilepsy Society MRI Unit, Chalfont St Peter, United Kingdom; Department of Clinical and Experimental Epilepsy, University College London, London, United Kingdom; National Hospital for Neurology and Neurosurgery, Queen Square, London, UK; Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Frederik Barkhof
- Centre for Medical Image Computing, University College London, London, United Kingdom; Brain Repair and Rehabilitation, University College London, London, UK; Radiology & Nuclear Medicine, VU University Medical Centre, Amsterdam, Netherlands
| | - Christian Dorfer
- Department of Neurosurgery, Vienna General Hospital, Medical University of Vienna, Vienna, Austria
| | - Salil Soman
- Harvard Medical School, Beth Israel Deaconess Medical Center, Department of Radiology, Boston, MA 00215, United States
| | - Gavin P Winston
- Epilepsy Society MRI Unit, Chalfont St Peter, United Kingdom; Department of Clinical and Experimental Epilepsy, University College London, London, United Kingdom; Department of Medicine, Division of Neurology, Queen's University, Kingston, Ontario, Canada
| | - Chengyuan Wu
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, USA
| | - John S Duncan
- Epilepsy Society MRI Unit, Chalfont St Peter, United Kingdom; Department of Clinical and Experimental Epilepsy, University College London, London, United Kingdom; National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
| | - Rachel Sparks
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
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Visualization of Brain Shift Corrected Functional Magnetic Resonance Imaging Data for Intraoperative Brain Mapping. World Neurosurg X 2019; 2:100021. [PMID: 31218295 PMCID: PMC6580887 DOI: 10.1016/j.wnsx.2019.100021] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Accepted: 02/06/2019] [Indexed: 11/22/2022] Open
Abstract
Background Brain tumor surgery requires careful balance between maximizing tumor excision and preserving eloquent cortex. In some cases, the surgeon may opt to perform an awake craniotomy including intraoperative mapping of brain function by direct cortical stimulation (DCS) to assist in surgical decision-making. Preoperatively, functional magnetic resonance imaging (fMRI) facilitates planning by identification of eloquent brain areas, helping to guide DCS and other aspects of the surgical plan. However, brain deformation (shift) limits the usefulness of preoperative fMRI during surgery. To address this, an integrated visualization method for fMRI and DCS results is developed that is intuitive for the surgeon. Methods An image registration pipeline was constructed to display preoperative fMRI data corrected for brain shift overlaid on images of the exposed cortical surface at the beginning and completion of DCS mapping. Preoperative fMRI and DCS data were registered for a range of misalignments, and the residual registration errors were calculated. The pipeline was validated on imaging data from five brain tumor patients who underwent awake craniotomy. Results Registration errors were well under 5 mm (the approximate spatial resolution of DCS) for misalignments of up to 25 mm and approximately 10–15°. For rotational misalignments up to 20°, the success rate was 95% for an error tolerance of 5 mm. Failures were negligible for rotational misalignments up to 10°. Good quality registrations were observed for all five patients. Conclusions A proof-of-concept image registration pipeline is presented with acceptable accuracy for intraoperative use, providing multimodality visualization with potential benefits for intraoperative brain mapping.
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Key Words
- 2D, 2-dimensional
- 3D, 3-Dimensional
- Awake craniotomy
- Brain mapping
- Brain tumor resection
- CT, Computed tomography
- DCS, Direct cortical stimulation
- Electric stimulation
- FOV, Field of view
- Functional mapping
- MRI, Magnetic resonance imaging
- Multimodal imaging
- RE, Registration error
- Surgical planning
- TE, Echo time
- TR, Repetition time
- fMRI, Functional magnetic resonance imaging
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Kosteniuk SE, Gui C, Gariscsak PJ, Lau JC, Megyesi JF. Impact of Functional Magnetic Resonance Imaging on Clinical Outcomes in a Propensity-Matched Low Grade Glioma Cohort. World Neurosurg 2018; 120:e1143-e1148. [DOI: 10.1016/j.wneu.2018.08.245] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2018] [Revised: 08/28/2018] [Accepted: 08/30/2018] [Indexed: 10/28/2022]
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Role of presurgical functional MRI and diffusion MR tractography in pediatric low-grade brain tumor surgery: a single-center study. Childs Nerv Syst 2018; 34:2241-2248. [PMID: 29802593 DOI: 10.1007/s00381-018-3828-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Accepted: 05/13/2018] [Indexed: 01/12/2023]
Abstract
PURPOSE Presurgical functional MRI (fMRI) and diffusion MRI tractography (dMRI tractography) are widely employed to delineate eloquent brain regions and their connections prior to brain tumor resection in adults. However, such studies are harder to perform in children, resulting in suboptimal neurosurgical care in pediatric brain tumor surgery as compared to adults. Thus, our objective was to assess the feasibility and the influence of presurgical advanced MR imaging on neurosurgical care in pediatric brain tumor surgery. METHODS Retrospective analyses of 31 presurgical fMRI/dMRI tractography studies were performed in children with low-grade tumors near eloquent brain regions at our site between 2005 and 2017. RESULTS In only 3/31 cases, imaging results were not interpretable (10%). All 28 successful imaging sessions were used for neurosurgical risk assessment. Based on this, surgery was canceled in 2/28 patients, and intention to treat was changed in 5/28 patients. In 4/28 cases, the surgical approach was changed and in 10/28, electrode placement for intraoperative neurophysiological monitoring was guided by imaging results. Gross total resection (GTR) was planned in 21/28 cases and could be achieved in 15/21 (71%). Despite highly eloquent tumor location, only four children suffered from a mild permanent neurological deficit after the operation. CONCLUSIONS We demonstrate that presurgical fMRI/dMRI tractography can have a profound impact on pediatric brain tumor management, optimizing preoperative risk-assessment and pre- as well as intraoperative decision-making. We believe that these tools should be offered to children suffering from eloquent brain tumors as part of a comprehensive operative work-up.
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Zacà D, Corsini F, Rozzanigo U, Dallabona M, Avesani P, Annicchiarico L, Zigiotto L, Faraca G, Chioffi F, Jovicich J, Sarubbo S. Whole-Brain Network Connectivity Underlying the Human Speech Articulation as Emerged Integrating Direct Electric Stimulation, Resting State fMRI and Tractography. Front Hum Neurosci 2018; 12:405. [PMID: 30364298 PMCID: PMC6193478 DOI: 10.3389/fnhum.2018.00405] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2018] [Accepted: 09/20/2018] [Indexed: 11/16/2022] Open
Abstract
Production of fluent speech in humans is based on a precise and coordinated articulation of sounds. A speech articulation network (SAN) has been observed in multiple brain studies typically using either neuroimaging or direct electrical stimulation (DES), thus giving limited knowledge about the whole brain structural and functional organization of this network. In this study, seven right-handed patients underwent awake surgery resection of low-grade gliomas (4) and cavernous angiomas. We combined pre-surgical resting state fMRI (rs-fMRI) and diffusion MRI together with speech arrest sites obtained intra-operatively with DES to address the following goals: (i) determine the cortical areas contributing to the intrinsic functional SAN using the speech arrest sites as functional seeds for rs-fMRI; (ii) evaluate the relative contribution of gray matter terminations from the two major language dorsal stream bundles, the superior longitudinal fasciculus (SLF III) and the arcuate fasciculus (AF); and (iii) evaluate the possible pre-surgical prediction of SAN with rs-fMRI. In all these right-handed patients the intrinsic functional SAN included frontal, inferior parietal, temporal, and insular regions symmetrically and bilaterally distributed across the two hemispheres regardless of the side (four right) of speech arrest evocation. The SLF III provided a much higher density of terminations in the cortical regions of SAN in respect to AF. Pre-surgical rs-fMRI data demonstrated moderate ability to predict the SAN. The set of functional and structural data provided in this multimodal study characterized, at a whole-brain level, a distributed and bi-hemispherical network subserving speech articulation.
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Affiliation(s)
- Domenico Zacà
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Trento, Italy
| | - Francesco Corsini
- Division of Neurosurgery, "S. Chiara" Hospital, Azienda Provinciale per i Servizi Sanitari, Trento, Italy.,Structural and Functional Connectivity Lab (SFC-Lab) Project, Division of Neurosurgery, "S. Chiara" Hospital, Azienda Provinciale per i Servizi Sanitari, Trento, Italy
| | - Umberto Rozzanigo
- Department of Radiology, Neuroradiology Unit, "S. Chiara" Hospital, Azienda Provinciale per i Servizi Sanitari, Trento, Italy
| | - Monica Dallabona
- Division of Neurosurgery, "S. Chiara" Hospital, Azienda Provinciale per i Servizi Sanitari, Trento, Italy
| | - Paolo Avesani
- NiLab, Bruno Kessler Foundation - FBK, Trento, Italy
| | - Luciano Annicchiarico
- Division of Neurosurgery, "S. Chiara" Hospital, Azienda Provinciale per i Servizi Sanitari, Trento, Italy.,Department of Neurosciences, Biomedicine and Movement Sciences, Section of Neurosurgery, University of Verona, Verona, Italy
| | - Luca Zigiotto
- Division of Neurosurgery, "S. Chiara" Hospital, Azienda Provinciale per i Servizi Sanitari, Trento, Italy
| | - Giovanna Faraca
- Division of Neurosurgery, "S. Chiara" Hospital, Azienda Provinciale per i Servizi Sanitari, Trento, Italy
| | - Franco Chioffi
- Division of Neurosurgery, "S. Chiara" Hospital, Azienda Provinciale per i Servizi Sanitari, Trento, Italy.,Structural and Functional Connectivity Lab (SFC-Lab) Project, Division of Neurosurgery, "S. Chiara" Hospital, Azienda Provinciale per i Servizi Sanitari, Trento, Italy
| | - Jorge Jovicich
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Trento, Italy
| | - Silvio Sarubbo
- Division of Neurosurgery, "S. Chiara" Hospital, Azienda Provinciale per i Servizi Sanitari, Trento, Italy.,Structural and Functional Connectivity Lab (SFC-Lab) Project, Division of Neurosurgery, "S. Chiara" Hospital, Azienda Provinciale per i Servizi Sanitari, Trento, Italy
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40
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Rosazza C, Zacà D, Bruzzone MG. Pre-surgical Brain Mapping: To Rest or Not to Rest? Front Neurol 2018; 9:520. [PMID: 30018589 PMCID: PMC6038713 DOI: 10.3389/fneur.2018.00520] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Accepted: 06/12/2018] [Indexed: 12/16/2022] Open
Affiliation(s)
- Cristina Rosazza
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico “Carlo Besta,”, Milan, Italy
| | - Domenico Zacà
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Trento, Italy
| | - Maria G. Bruzzone
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico “Carlo Besta,”, Milan, Italy
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Integration of resting state functional MRI into clinical practice - A large single institution experience. PLoS One 2018; 13:e0198349. [PMID: 29933375 PMCID: PMC6014724 DOI: 10.1371/journal.pone.0198349] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2017] [Accepted: 05/17/2018] [Indexed: 02/02/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) is an important tool for pre-surgical evaluation of eloquent cortex. Classic task-based paradigms require patient participation and individual imaging sequence acquisitions for each functional domain that is being assessed. Resting state fMRI (rs-fMRI), however, enables functional localization without patient participation and can evaluate numerous functional domains with a single imaging session. To date, post-processing of this resting state data has been resource intensive, which limits its widespread application for routine clinical use. Through a novel automated algorithm and advanced imaging IT structure, we report the clinical application and the large-scale integration of rs-fMRI into routine neurosurgical practice. One hundred and ninety one consecutive patients underwent a 3T rs-fMRI, 83 of whom also underwent both motor and language task-based fMRI. Data were processed using a novel, automated, multi-layer perceptron algorithm and integrated into stereotactic navigation using a streamlined IT imaging pipeline. One hundred eighty-five studies were performed for intracranial neoplasm, 14 for refractory epilepsy and 33 for vascular malformations or other neurological disorders. Failure rate of rs-fMRI of 13% was significantly better than that for task-based fMRI (38.5%,) (p <0.001). In conclusion, at Washington University in St. Louis, rs-fMRI has become an integral part of standard imaging for neurosurgical planning. Resting state fMRI can be used in all patients, and due to its lower failure rate than task-based fMRI, it is useful for patients who are unable to cooperate with task-based studies.
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42
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Volz LJ, Kocher M, Lohmann P, Shah NJ, Fink GR, Galldiks N. Functional magnetic resonance imaging in glioma patients: from clinical applications to future perspectives. THE QUARTERLY JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING : OFFICIAL PUBLICATION OF THE ITALIAN ASSOCIATION OF NUCLEAR MEDICINE (AIMN) [AND] THE INTERNATIONAL ASSOCIATION OF RADIOPHARMACOLOGY (IAR), [AND] SECTION OF THE SOCIETY OF RADIOPHARMACEUTICAL CHEMISTRY AND BIOLOGY 2018; 62:295-302. [PMID: 29761998 DOI: 10.23736/s1824-4785.18.03101-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Functional magnetic resonance imaging (fMRI) allows the non-invasive assessment of human brain activity in vivo. In glioma patients, fMRI is frequently used to determine the individual functional anatomy of the motor and language network in a presurgical setting to optimize surgical procedures and prevent extensive damage to functionally eloquent areas. Novel developments based on resting-state fMRI may help to improve presurgical planning for patients which are unable to perform structured tasks and might extend presurgical mapping to include additional functional networks. Recent advances indicate a promising potential for future applications of fMRI in glioma patients which might help to identify neoplastic tissue or predict the long-term functional outcome of individual patients.
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Affiliation(s)
- Lukas J Volz
- Department of Neurology, University of Cologne, Cologne, Germany - .,SAGE Center for the Study of the Mind and Brain, University of California - Santa Barbara, Santa Barbara, CA, USA -
| | - Martin Kocher
- Institute of Neuroscience and Medicine, Jülich Research Center, Jülich, Germany.,Department of Stereotaxy and Functional Neurosurgery, University of Cologne, Cologne, Germany
| | - Philipp Lohmann
- Institute of Neuroscience and Medicine, Jülich Research Center, Jülich, Germany
| | - Nadim J Shah
- Institute of Neuroscience and Medicine, Jülich Research Center, Jülich, Germany.,Department of Neurology, RWTH Aachen University, Aachen, Germany.,JARA-BRAIN Institute for Translational Medicine (INM-3, -4), Forschungszentrum Jülich, Jülich, Germany
| | - Gereon R Fink
- Department of Neurology, University of Cologne, Cologne, Germany.,Institute of Neuroscience and Medicine, Jülich Research Center, Jülich, Germany
| | - Norbert Galldiks
- Department of Neurology, University of Cologne, Cologne, Germany.,Institute of Neuroscience and Medicine, Jülich Research Center, Jülich, Germany.,Center of Integrated Oncology (CIO), Universities of Cologne and Bonn, Cologne, Germany
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Gong S, Zhang F, Norton I, Essayed WI, Unadkat P, Rigolo L, Pasternak O, Rathi Y, Hou L, Golby AJ, O’Donnell LJ. Free water modeling of peritumoral edema using multi-fiber tractography: Application to tracking the arcuate fasciculus for neurosurgical planning. PLoS One 2018; 13:e0197056. [PMID: 29746544 PMCID: PMC5944935 DOI: 10.1371/journal.pone.0197056] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Accepted: 04/25/2018] [Indexed: 12/13/2022] Open
Abstract
Purpose Peritumoral edema impedes the full delineation of fiber tracts due to partial volume effects in image voxels that contain a mixture of cerebral parenchyma and extracellular water. The purpose of this study is to investigate the effect of incorporating a free water (FW) model of edema for white matter tractography in the presence of edema. Materials and methods We retrospectively evaluated 26 consecutive brain tumor patients with diffusion MRI and T2-weighted images acquired presurgically. Tractography of the arcuate fasciculus (AF) was performed using the two-tensor unscented Kalman filter tractography (UKFt) method, the UKFt method with a reduced fiber tracking stopping fractional anisotropy (FA) threshold (UKFt+rFA), and the UKFt method with the addition of a FW compartment (UKFt+FW). An automated white matter fiber tract identification approach was applied to delineate the AF. Quantitative measurements included tract volume, edema volume, and mean FW fraction. Visual comparisons were performed by three experts to evaluate the quality of the detected AF tracts. Results The AF volume in edematous brain hemispheres was significantly larger using the UKFt+FW method (p<0.0001) compared to UKFt, but not significantly larger (p = 0.0996) in hemispheres without edema. The AF size increase depended on the volume of edema: a significant correlation was found between AF volume affected by (intersecting) edema and AF volume change with the FW model (Pearson r = 0.806, p<0.0001). The mean FW fraction was significantly larger in tracts intersecting edema (p = 0.0271). Compared to the UKFt+rFA method, there was a significant increase of the volume of the AF tract that intersected the edema using the UKFt+FW method, while the whole AF volumes were similar. Expert judgment results, based on the five patients with the smallest AF volumes, indicated that the expert readers generally preferred the AF tract obtained by using the FW model, according to their anatomical knowledge and considering the potential influence of the final results on the surgical route. Conclusion Our results indicate that incorporating biophysical models of edema can increase the sensitivity of tractography in regions of peritumoral edema, allowing better tract visualization in patients with high grade gliomas and metastases.
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Affiliation(s)
- Shun Gong
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Neurosurgery, Shanghai Institute of Neurosurgery, Shanghai Changzheng Hospital, Shanghai, China
| | - Fan Zhang
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Isaiah Norton
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Walid I. Essayed
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Prashin Unadkat
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Laura Rigolo
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Ofer Pasternak
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Yogesh Rathi
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Lijun Hou
- Department of Neurosurgery, Shanghai Institute of Neurosurgery, Shanghai Changzheng Hospital, Shanghai, China
| | - Alexandra J. Golby
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Lauren J. O’Donnell
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- * E-mail:
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Temporal reliability of ultra-high field resting-state MRI for single-subject sensorimotor and language mapping. Neuroimage 2018; 168:499-508. [DOI: 10.1016/j.neuroimage.2016.11.029] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2016] [Revised: 10/29/2016] [Accepted: 11/12/2016] [Indexed: 11/19/2022] Open
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Trattnig S, Springer E, Bogner W, Hangel G, Strasser B, Dymerska B, Cardoso PL, Robinson SD. Key clinical benefits of neuroimaging at 7T. Neuroimage 2018; 168:477-489. [PMID: 27851995 PMCID: PMC5832016 DOI: 10.1016/j.neuroimage.2016.11.031] [Citation(s) in RCA: 89] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Revised: 10/06/2016] [Accepted: 11/12/2016] [Indexed: 01/15/2023] Open
Abstract
The growing interest in ultra-high field MRI, with more than 35.000 MR examinations already performed at 7T, is related to improved clinical results with regard to morphological as well as functional and metabolic capabilities. Since the signal-to-noise ratio increases with the field strength of the MR scanner, the most evident application at 7T is to gain higher spatial resolution in the brain compared to 3T. Of specific clinical interest for neuro applications is the cerebral cortex at 7T, for the detection of changes in cortical structure, like the visualization of cortical microinfarcts and cortical plaques in Multiple Sclerosis. In imaging of the hippocampus, even subfields of the internal hippocampal anatomy and pathology may be visualized with excellent spatial resolution. Using Susceptibility Weighted Imaging, the plaque-vessel relationship and iron accumulations in Multiple Sclerosis can be visualized, which may provide a prognostic factor of disease. Vascular imaging is a highly promising field for 7T which is dealt with in a separate dedicated article in this special issue. The static and dynamic blood oxygenation level-dependent contrast also increases with the field strength, which significantly improves the accuracy of pre-surgical evaluation of vital brain areas before tumor removal. Improvement in acquisition and hardware technology have also resulted in an increasing number of MR spectroscopic imaging studies in patients at 7T. More recent parallel imaging and short-TR acquisition approaches have overcome the limitations of scan time and spatial resolution, thereby allowing imaging matrix sizes of up to 128×128. The benefits of these acquisition approaches for investigation of brain tumors and Multiple Sclerosis have been shown recently. Together, these possibilities demonstrate the feasibility and advantages of conducting routine diagnostic imaging and clinical research at 7T.
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Affiliation(s)
- Siegfried Trattnig
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria; Christian Doppler Laboratory for Clinical Molecular MRI, Vienna, Austria.
| | - Elisabeth Springer
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria; Christian Doppler Laboratory for Clinical Molecular MRI, Vienna, Austria.
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria.
| | - Gilbert Hangel
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria.
| | - Bernhard Strasser
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria.
| | - Barbara Dymerska
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria.
| | - Pedro Lima Cardoso
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria.
| | - Simon Daniel Robinson
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Lazarettgasse 14, A-1090, Vienna, Austria.
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Vysotski S, Madura C, Swan B, Holdsworth R, Lin Y, Rio AMD, Wood J, Kundu B, Penwarden A, Voss J, Gallagher T, Nair VA, Field A, Garcia-Ramos C, Meyerand EM, Baskaya M, Prabhakaran V, Kuo JS. Preoperative FMRI Associated with Decreased Mortality and Morbidity in Brain Tumor Patients. INTERDISCIPLINARY NEUROSURGERY-ADVANCED TECHNIQUES AND CASE MANAGEMENT 2018; 13:40-45. [PMID: 31341789 DOI: 10.1016/j.inat.2018.02.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background Functional Magnetic Resonance Imaging (fMRI) is a presurgical planning technique used to localize functional cortex so as to maximize resection of diseased tissue and avoid viable tissue. In this retrospective study, we examined differences in morbidity and mortality of brain tumor patients who received preoperative fMRI in comparison to those who did not. Methods Brain tumor patients (n=206) were selected from a retrospective review of neurosurgical case logs from 2001-2009 at the University of Wisconsin-Madison. Results Univariate analysis showed improved mortality in the fMRI group and the fMRI+Electrical Cortical Stimulation Mapping (ECM) group compared to the No-fMRI group. Multivariate analyses showed improved mortality of the fMRI group and the fMRI+ECM group compared to the No-fMRI group, with age and tumor grade being the most significant influencers. Overall, the fMRI group showed survival benefits at 3 years; twice that of the No-fMRI group. Furthermore, patients with high-grade tumors showed significant survival benefits in the fMRI group, while patients with low-grade tumors did not (controlling for age and ECM). There was also a significant difference in the two groups with respect to morbidity, with patients receiving fMRI showing improved outcomes in the motor and language domains. Conclusions This study analyzing a large retrospective series of brain tumor patients with and without the use of fMRI in the preoperative planning has resulted in improved mortality and morbidity outcomes with the use of fMRI. These results point to the importance of incorporating fMRI in presurgical planning in the clinical management of patients with brain tumors.
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Affiliation(s)
- Siarhei Vysotski
- Department of Radiology, University of Wisconsin-Madison, School of Medicine and Public Health, 600 Highland Avenue, Madison, WI 53792-3252
| | - Casey Madura
- Neurological Surgery, University of Wisconsin-Madison, School of Medicine and Public Health, 600 Highland Avenue, Madison, WI 53792-3252
| | - Benjamin Swan
- Department of Radiology, Mount Auburn Hospital, 330 Mount Auburn Street, Cambridge, MA 02138
| | - Ryan Holdsworth
- Department of Radiology, University of Wisconsin-Madison, School of Medicine and Public Health, 600 Highland Avenue, Madison, WI 53792-3252
| | - Yunzhi Lin
- Department of Statistics, University of Wisconsin Madison, 1300 University Avenue, Madison, WI 53705
| | - Alejandro Munoz Del Rio
- Department of Radiology, University of Wisconsin-Madison, School of Medicine and Public Health, 600 Highland Avenue, Madison, WI 53792-3252.,Department of Medical Physics, University of Wisconsin-Madison, Wisconsin Institutes for Medical Research (WIMR), 1111 Highland Avenue Rm 1005, Madison, WI 53705
| | - Joel Wood
- Department of General Surgery, UW Hospitals and Clinics, 600 Highland Avenue, Madison, WI 53792-3252
| | - Bornali Kundu
- Medical Scientist Training Program, University of Wisconsin Madison, 6001 Research Park Blvd. Rm 1056, Madison, WI 51719
| | - Amy Penwarden
- Department of Anesthesiology, University of North Carolina -Chapel Hill, 106 Bel Arbor Ln Carrboro, NC 27510
| | - Jed Voss
- Department of Radiology, University of Wisconsin-Madison, School of Medicine and Public Health, 600 Highland Avenue, Madison, WI 53792-3252
| | - Thomas Gallagher
- Department of Radiology, Northwestern University Feinberg School of Medicine, NMH/Arkes Family Pavilion Suite 800, 676 N Saint Clair, Chicago IL 60611
| | - Veena A Nair
- Department of Radiology, University of Wisconsin-Madison, School of Medicine and Public Health, 600 Highland Avenue, Madison, WI 53792-3252
| | - Aaron Field
- Department of Radiology, University of Wisconsin-Madison, School of Medicine and Public Health, 600 Highland Avenue, Madison, WI 53792-3252.,Biomedical Engineering, University of Wisconsin-Madison, 1550 Engineering Dr, Madison, WI 53706, USA
| | - Camille Garcia-Ramos
- Department of Medical Physics, University of Wisconsin-Madison, Wisconsin Institutes for Medical Research (WIMR), 1111 Highland Avenue Rm 1005, Madison, WI 53705
| | - Elizabeth M Meyerand
- Biomedical Engineering, University of Wisconsin-Madison, 1550 Engineering Dr, Madison, WI 53706, USA.,Department of Medical Physics, University of Wisconsin-Madison, Wisconsin Institutes for Medical Research (WIMR), 1111 Highland Avenue Rm 1005, Madison, WI 53705
| | - Mustafa Baskaya
- Neurological Surgery, University of Wisconsin-Madison, School of Medicine and Public Health, 600 Highland Avenue, Madison, WI 53792-3252
| | - Vivek Prabhakaran
- Department of Radiology, University of Wisconsin-Madison, School of Medicine and Public Health, 600 Highland Avenue, Madison, WI 53792-3252
| | - John S Kuo
- UW Carbone Cancer Center, University of Wisconsin-Madison, 600 Highland Ave, Madison, WI 53792, USA.,UW Center for Stem Cell and Regenerative Medicine, University of Wisconsin-Madison, School of Medicine and Public Health, K3/803 Clinical Science Center, Mail Code 8660, 600 Highland Avenue, Madison, WI 53792-3252
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Cochereau J, Deverdun J, Herbet G, Charroud C, Boyer A, Moritz-Gasser S, Le Bars E, Molino F, Bonafé A, Menjot de Champfleur N, Duffau H. Comparison between resting state fMRI networks and responsive cortical stimulations in glioma patients. Hum Brain Mapp 2018; 37:3721-3732. [PMID: 27246771 DOI: 10.1002/hbm.23270] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2015] [Revised: 05/01/2016] [Accepted: 05/17/2016] [Indexed: 12/26/2022] Open
Abstract
OBJECTIVES To validate the functional relevance of resting state networks (RSNs) by means of a comparison of resting state connectivity (RSC) between language regions elicited by direct cortical stimulation versus RSC between random regions; and to evaluate the accuracy of resting state fMRI in surgical planning by assessing the overlap between RSNs and intraoperative functional mapping results. METHODS Sensorimotor and language eloquent sites were identified by direct electrical cortical stimulation in 98 patients with a diffuse low-grade glioma. A seed to voxel analysis with inter-language stimulation point connectivity versus inter-random ROIs connectivity was performed (19 patients). An independant component analysis (ICA) was also applied to rsfMRI data. Language and sensorimotor components were selected over 20 independent components and compared to the corresponding stimulation points and resected cortex masks (31 and 90 patients, respectively). RESULTS Mean connectivity value between language seeds was significantly higher than the one between random seeds (0.68 ± 0.39 and 0.12 ± 0.21 respectively, P < 10-10 ). 96 ± 11% of sensorimotor stimulation points were located within 10 mm from sensorimotor ICA maps versus 92 ± 21% for language. 3.1 and 15% of resected cortex overlapped sensorimotor and language networks, respectively. Mean sensorimotor stimulation points and resected cortex z-scores were 2.0 ± 1.2 and -0.050 ± 0.60, respectively (P < 10-10 ). Mean language stimulation points and resected cortex z-scores were 1.6 ± 1.9 and 0.68 ± 0.91, respectively, P < 0.005. CONCLUSION The significantly higher RSC between language seeds than between random seeds validated the functional relevance of RSC. ICA partly succeeded to distinguish eloquent versus surgically removable areas and may be possibly used as a complementary tool to intraoperative mapping. Hum Brain Mapp 37:3721-3732, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Jérôme Cochereau
- Department of Neurosurgery, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France.,Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France
| | - Jérémy Deverdun
- Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Institut de Génomique Fonctionnelle, Unité UMR 5203 - INSERM U661 - Université Montpellier II - Université Montpellier I, France.,Laboratoire Charles Coulomb, Unité CNRS UMR 5221 - Université Montpellier II, Montpellier, France
| | - Guillaume Herbet
- Department of Neurosurgery, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France
| | - Céline Charroud
- Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France
| | - Anthony Boyer
- Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,University of Montpellier 2, LIRMM laboratory, DEMAR Team, CNRS, INRIA, Montpellier, 34095, France
| | - Sylvie Moritz-Gasser
- Department of Neurosurgery, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France
| | - Emmanuelle Le Bars
- Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Laboratoire Charles Coulomb, Unité CNRS UMR 5221 - Université Montpellier II, Montpellier, France
| | - François Molino
- Institut de Génomique Fonctionnelle, Unité UMR 5203 - INSERM U661 - Université Montpellier II - Université Montpellier I, France.,Laboratoire Charles Coulomb, Unité CNRS UMR 5221 - Université Montpellier II, Montpellier, France
| | - Alain Bonafé
- Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France.,Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France
| | - Nicolas Menjot de Champfleur
- Unité I2FH, Institut d'Imagerie Fonctionnelle Humaine, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France.,Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Laboratoire Charles Coulomb, Unité CNRS UMR 5221 - Université Montpellier II, Montpellier, France
| | - Hugues Duffau
- Department of Neurosurgery, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France.,Team "Plasticity of Central Nervous System, Stem Cells and Glial Tumors", INSERM U1051, Institute of Neurosciences of Montpellier, Montpellier, France
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Alemi R, Batouli SAH, Behzad E, Ebrahimpoor M, Oghabian MA. Not single brain areas but a network is involved in language: Applications in presurgical planning. Clin Neurol Neurosurg 2018; 165:116-128. [PMID: 29334640 DOI: 10.1016/j.clineuro.2018.01.009] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Revised: 01/03/2018] [Accepted: 01/08/2018] [Indexed: 01/22/2023]
Abstract
OBJECTIVES Language is an important human function, and is a determinant of the quality of life. In conditions such as brain lesions, disruption of the language function may occur, and lesion resection is a solution for that. Presurgical planning to determine the language-related brain areas would enhance the chances of language preservation after the operation; however, availability of a normative language template is essential. PATIENTS AND METHODS In this study, using data from 60 young individuals who were meticulously checked for mental and physical health, and using fMRI and robust imaging and data analysis methods, functional brain maps for the language production, perception and semantic were produced. RESULTS The obtained templates showed that the language function should be considered as the product of the collaboration of a network of brain regions, instead of considering only few brain areas to be involved in that. CONCLUSION This study has important clinical applications, and extends our knowledge on the neuroanatomy of the language function.
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Affiliation(s)
- Razieh Alemi
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran; Department of Otorhinolaryngology, Faculty of Medicine, McGill University, Canada
| | - Seyed Amir Hossein Batouli
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran; Neuroimaging and Analysis Group, Tehran University of Medical Sciences, Tehran, Iran
| | - Ebrahim Behzad
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Mitra Ebrahimpoor
- Neuroimaging and Analysis Group, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Ali Oghabian
- Neuroimaging and Analysis Group, Tehran University of Medical Sciences, Tehran, Iran; Medical Physics and Biomedical Engineering Department, Tehran University of Medical Sciences, Tehran, Iran.
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Silva MA, See AP, Essayed WI, Golby AJ, Tie Y. Challenges and techniques for presurgical brain mapping with functional MRI. NEUROIMAGE-CLINICAL 2017; 17:794-803. [PMID: 29270359 PMCID: PMC5735325 DOI: 10.1016/j.nicl.2017.12.008] [Citation(s) in RCA: 82] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/20/2017] [Revised: 11/10/2017] [Accepted: 12/05/2017] [Indexed: 01/22/2023]
Abstract
Functional magnetic resonance imaging (fMRI) is increasingly used for preoperative counseling and planning, and intraoperative guidance for tumor resection in the eloquent cortex. Although there have been improvements in image resolution and artifact correction, there are still limitations of this modality. In this review, we discuss clinical fMRI's applications, limitations and potential solutions. These limitations depend on the following parameters: foundations of fMRI, physiologic effects of the disease, distinctions between clinical and research fMRI, and the design of the fMRI study. We also compare fMRI to other brain mapping modalities which should be considered as alternatives or adjuncts when appropriate, and discuss intraoperative use and validation of fMRI. These concepts direct the clinical application of fMRI in neurosurgical patients. fMRI is increasingly used for presurgical brain mapping for surgical planning. Understanding of the limitations of fMRI is critical for its clinical use. Clinical fMRI's challenges and potential solutions are discussed. Intraoperative use and validation of fMRI are discussed.
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Affiliation(s)
- Michael A Silva
- Harvard Medical School, Boston, MA, USA; Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, USA
| | - Alfred P See
- Harvard Medical School, Boston, MA, USA; Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, USA
| | - Walid I Essayed
- Harvard Medical School, Boston, MA, USA; Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, USA
| | - Alexandra J Golby
- Harvard Medical School, Boston, MA, USA; Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, USA; Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA
| | - Yanmei Tie
- Harvard Medical School, Boston, MA, USA; Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, USA.
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De Martin E, Duran D, Ghielmetti F, Visani E, Aquino D, Marchetti M, Sebastiano DR, Cusumano D, Bruzzone MG, Panzica F, Fariselli L. Integration of Functional Magnetic Resonance Imaging and Magnetoencephalography Functional Maps Into a CyberKnife Planning System: Feasibility Study for Motor Activity Localization and Dose Planning. World Neurosurg 2017; 108:756-762. [DOI: 10.1016/j.wneu.2017.08.187] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2017] [Revised: 08/28/2017] [Accepted: 08/30/2017] [Indexed: 12/31/2022]
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