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Trapp N, Co DO, Rebsamen S, Ikonomidou C, Ahmed R, Knox A. Bilateral Rasmussen Encephalitis: Good Outcome Following Hemispherotomy. Pediatr Neurol 2024; 151:1-4. [PMID: 38041904 DOI: 10.1016/j.pediatrneurol.2023.10.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 09/20/2023] [Accepted: 10/16/2023] [Indexed: 12/04/2023]
Abstract
BACKGROUND Bilateral Rasmussen encephalitis is a rare variant of a debilitating, typically unihemispheric disease with limited treatment options. Few cases with bilateral histopathology have been reported, all with poor seizure control following surgery. Here we report a favorable outcome following hemispherotomy in a four-year-old male with biopsy-confirmed bilateral disease. CASE The patient presented with right hemispheric focal seizures with behavioral arrest and over a year progressed to left lower extremity clonic seizures, epilepsia partialis continua, and loss of ambulation, with transient response to steroids and tacrolimus. Histopathology confirmed bilateral disease. The patient developed super-refractory status epilepticus and underwent right functional hemispherotomy 4.5 years after initial presentation. In a 2.5-year follow-up period, an Engel 1D outcome classification was observed with substantially improved quality of life. CONCLUSION Previous reports of bilateral Rasmussen encephalitis describe universally poor outcomes, and hemispherotomy is often considered contraindicated. However, hemispherotomy in a patient with bilateral Rasmussen encephalitis may have a good outcome if seizures are unihemispheric.
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Affiliation(s)
- Noah Trapp
- Section of Pediatric Neurology, Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.
| | - Dominic O Co
- Division of Allergy, Immunology and Rheumatology, Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Susan Rebsamen
- Section of Neuroradiology, Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Chris Ikonomidou
- Section of Pediatric Neurology, Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Raheel Ahmed
- Section of Pediatric Neurosurgery, Department of Neurosurgery, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Andrew Knox
- Section of Pediatric Neurology, Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
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Yu T, Cai LY, Morgan VL, Goodale SE, Englot DJ, Chang CE, Landman BA, Schilling KG. SynBOLD-DisCo: Synthetic BOLD images for distortion correction of fMRI without additional calibration scans. Proc SPIE Int Soc Opt Eng 2023; 12464:1246417. [PMID: 37465092 PMCID: PMC10353777 DOI: 10.1117/12.2653647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
The blood oxygen level dependent (BOLD) signal from functional magnetic resonance imaging (fMRI) is a noninvasive technique that has been widely used in research to study brain function. However, fMRI suffers from susceptibility-induced off resonance fields which may cause geometric distortions and mismatches with anatomical images. State-of-the-art correction methods require acquiring reverse phase encoded images or additional field maps to enable distortion correction. However, not all imaging protocols include these additional scans and thus cannot take advantage of these susceptibility correction capabilities. As such, in this study we aim to enable state-of-the-art distortion correction with FSL's topup algorithm of historical and/or limited fMRI data that include only a structural image and single phase encoded fMRI. To do this, we use 3D U-net models to synthesize undistorted fMRI BOLD contrast images from the structural image and use this undistorted synthetic image as an anatomical target for distortion correction with topup. We evaluate the efficacy of this approach, named SynBOLD-DisCo (synthetic BOLD images for distortion correction), and show that BOLD images corrected using our approach are geometrically more similar to structural images than the distorted BOLD data and are practically equivalent to state-of-the-art correction methods which require reverse phase encoded data. Future directions include additional validation studies, integration with other preprocessing operations, retraining with broader pathologies, and investigating the effects of spin echo versus gradient echo images for training and distortion correction. In summary, we demonstrate SynBOLD-DisCo corrects distortion of fMRI when reverse phase encoding scans or field maps are not available.
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Affiliation(s)
- Tian Yu
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Leon Y Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Victoria L Morgan
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sarah E Goodale
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Dario J Englot
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Catherine E Chang
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Bennett A Landman
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Kurt G Schilling
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
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