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Jensen MA, Fine A, Kerezoudis P, Wong Kisiel L, Alden E, Hermes D, Miller KJ. Functional Mapping of Movement and Speech Using Task-Based Electrophysiological Changes in Stereoelectroencephalography. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.29.582865. [PMID: 38496670 PMCID: PMC10942370 DOI: 10.1101/2024.02.29.582865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Introduction Stereoelectroencephalography (sEEG) has become the predominant method for intracranial seizure localization. When imaging, semiology, and scalp EEG are not in full agreement or definitively localizing, implanted sEEG recordings are used to test candidate seizure onset zones (SOZs). Discovered SOZs may then be targeted for resection, laser ablation, or neurostimulation. If a SOZ is eloquent, resection and ablation are both contraindicated, so identifying functional representation is crucial for therapeutic decision making. Objective We present a novel functional brain mapping technique that utilizes task-based electrophysiological changes in sEEG during behavioral tasks and test this in pediatric and adult patients. Methods sEEG was recorded in twenty patients with epilepsy, aged 6-39 (12 female, 18 of 20 patients < 21 years old), who underwent implanted monitoring to identify seizure onset. Each performed 1) visually cued simple repetitive movements of the hand, foot, or tongue while electromyography was recorded, and 2) simple picture naming or verb generation speech tasks while audio was recorded. Broadband changes in the power spectrum of the sEEG were compared between behavior and rest. Results Electrophysiological functional mapping of movement and/or speech areas was completed in all 20 patients. Eloquent representation was identified in both cortex and white matter, and generally corresponded to classically described functional anatomic organization as well as other clinical mapping results. Robust maps of brain activity were identified in healthy brain, regions of developmental or acquired structural abnormality, and SOZs. Conclusion Task based electrophysiological mapping using broadband changes in the sEEG signal reliably identifies movement and speech representation in pediatric and adult epilepsy patients.
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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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Nabavizadeh A, Barkovich MJ, Mian A, Ngo V, Kazerooni AF, Villanueva-Meyer JE. Current state of pediatric neuro-oncology imaging, challenges and future directions. Neoplasia 2023; 37:100886. [PMID: 36774835 PMCID: PMC9945752 DOI: 10.1016/j.neo.2023.100886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 01/20/2023] [Accepted: 02/05/2023] [Indexed: 02/12/2023]
Abstract
Imaging plays a central role in neuro-oncology including primary diagnosis, treatment planning, and surveillance of tumors. The emergence of quantitative imaging and radiomics provided an uprecedented opportunity to compile mineable databases that can be utilized in a variety of applications. In this review, we aim to summarize the current state of conventional and advanced imaging techniques, standardization efforts, fast protocols, contrast and sedation in pediatric neuro-oncologic imaging, radiomics-radiogenomics, multi-omics and molecular imaging approaches. We will also address the existing challenges and discuss future directions.
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Affiliation(s)
- Ali Nabavizadeh
- Department of Radiology, Hospital of University of Pennsylvania, Perelman School of Medicine of the University of Pennsylvania, Philadelphia, Pennsylvania, USA; Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
| | - Matthew J Barkovich
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Ali Mian
- Division of Neuroradiology, Mallinckrodt Institute of Radiology, Washington University in St. Louis, Missouri, USA
| | - Van Ngo
- Saint Louis University School of Medicine, St. Louis, Missouri, USA
| | - Anahita Fathi Kazerooni
- Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
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Krishnamurthy M, You X, Sepeta LN, Matuska E, Oluigbo C, Berl MM, Gaillard WD, Gholipour T. Resting-state functional MRI for motor cortex mapping in childhood-onset focal epilepsy. J Neuroimaging 2022; 32:1201-1210. [PMID: 35881496 PMCID: PMC9649846 DOI: 10.1111/jon.13030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 07/08/2022] [Accepted: 07/12/2022] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND AND PURPOSE Task-based functional MRI (fMRI) mapping of the motor function prior to epilepsy surgery has limitations in children with epilepsy. We present a data-driven method to automatically delineate the motor cortex using task-free, resting-state fMRI (rsfMRI) data. METHODS We used whole-brain rsfMRI for independent component analysis (ICA). A template matching process with Discriminability Index-based Component Identification score was used for each participant to select and combine motor ICA components in their native brain space, resulting in a whole-brain ICA Motor Map (wIMM). We validated wIMM by comparing individual results with bilateral finger-tapping motor task fMRI activation, and evaluated its reproducibility in controls. RESULTS Data from 64 patients and 12 controls were used to generate group wIMM maps. The hit rate between wIMM and motor task activation ranged from 60% to 79% across all participants. Sensitivity of wIMM for capturing the task activation peak was 87.5% among 32 patients and 100% in 12 controls with available motor task results. We also showed high similarity in repeated runs in controls. CONCLUSIONS Our results show the sensitivity and reproducibility of an automated motor mapping method based on ICA analysis of rsfMRI in children with epilepsy. The ICA maps may provide different, but useful, information than task fMRI. Future studies will expand our method to mapping other brain functions, and may lead to a surgical planning tool for patients who cannot perform task fMRI and help predict their postsurgical function.
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Affiliation(s)
- Manu Krishnamurthy
- Center for Neuroscience, Children’s National Hospital, the George Washington University, Washington, DC
| | - Xiaozhen You
- Center for Neuroscience, Children’s National Hospital, the George Washington University, Washington, DC
| | - Leigh N. Sepeta
- Center for Neuroscience, Children’s National Hospital, the George Washington University, Washington, DC
| | - Emily Matuska
- Center for Neuroscience, Children’s National Hospital, the George Washington University, Washington, DC
| | - Chima Oluigbo
- Center for Neuroscience, Children’s National Hospital, the George Washington University, Washington, DC
| | - Madison M. Berl
- Center for Neuroscience, Children’s National Hospital, the George Washington University, Washington, DC
| | - William D. Gaillard
- Center for Neuroscience, Children’s National Hospital, the George Washington University, Washington, DC
| | - Taha Gholipour
- Center for Neuroscience, Children’s National Hospital, the George Washington University, Washington, DC
- Department of Neurology, the George Washington University, Washington, DC
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