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Neuroimaging characteristics may aid in diagnosis, subtyping, and prognosis in autoimmune encephalitis.

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Title: Neuroimaging characteristics may aid in diagnosis, subtyping, and prognosis in autoimmune encephalitis.
Authors: Broadley, James (AUTHOR), Wesselingh, Robb (AUTHOR), Beech, Paul (AUTHOR), Seneviratne, Udaya (AUTHOR), Kyndt, Chris (AUTHOR), Buzzard, Katherine (AUTHOR), Nesbitt, Cassie (AUTHOR), D'Souza, Wendyl (AUTHOR), Brodtmann, Amy (AUTHOR), Macdonell, Richard (AUTHOR), Kalincik, Tomas (AUTHOR), O'Brien, Terence J. (AUTHOR), Butzkueven, Helmut (AUTHOR), Monif, Mastura (AUTHOR), on behalf of the Australian Autoimmune Encephalitis Consortium (AUTHOR), Griffiths, Sarah (AUTHOR), Rushen, Tiffany (AUTHOR), Tan, Tracie (AUTHOR), Malpas, Charles (AUTHOR), Halliday, Amy (AUTHOR)
Source: Neurological Sciences. Apr2023, Vol. 44 Issue 4, p1327-1340. 14p. 2 Color Photographs, 1 Black and White Photograph, 4 Charts, 2 Graphs.
Subjects: Positron emission tomography, Encephalitis, Magnetic resonance imaging, Disease relapse, Brain imaging
Abstract: Objective: To examine the utility of neuroimaging characteristics as biomarkers of prognosis in seropositive autoimmune encephalitis (AE). Methods: In this multi-center study, we retrospectively analyzed 66 cases of seropositive AE. The MRI and PET imaging was assessed by independent visual inspection. Whole brain and regional volumes were imputed by IcoMetrix, an automated volumetric assessment package. The modified Rankin Scale (mRS) was utilized to assess the patients' follow-up disability. Other outcomes were mortality, first line treatment failure, medial temporal lobe (MTL) atrophy, and clinical relapse. Univariate and multivariable regression analysis was performed. Results: Abnormalities on MRI were detected in 35.1% of patients, while PET was abnormal in 46.4%. Initial median whole brain and hippocampal volumes were below the 5th and 20th percentile respectively compared to an age-matched healthy database. After a median follow-up of 715 days, 85.2% had good functional outcome (mRS ≤ 2). Nine patients developed MTL atrophy during follow-up. On multivariable analysis, inflammatory MTL changes were associated with development of MTL atrophy (HR 19.6, p = 0.007) and initial hippocampal volume had an inverse relationship with mortality (HR 0.04, p = 0.011). Patients who developed MTL atrophy had a reduced chance of good final mRS (HR 0.16, p = 0.015). Conclusions: Neuroimaging on initial hospital admission may be provide important diagnostic and prognostic information. This study demonstrates that structural and inflammatory changes of the MTL may have importance in clinical and radiological prognosis in seropositive AE. [ABSTRACT FROM AUTHOR]
Copyright of Neurological Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Neuroimaging characteristics may aid in diagnosis, subtyping, and prognosis in autoimmune encephalitis.
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  Data: <searchLink fieldCode="JN" term="%22Neurological+Sciences%22">Neurological Sciences</searchLink>. Apr2023, Vol. 44 Issue 4, p1327-1340. 14p. 2 Color Photographs, 1 Black and White Photograph, 4 Charts, 2 Graphs.
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  Data: <searchLink fieldCode="DE" term="%22Positron+emission+tomography%22">Positron emission tomography</searchLink><br /><searchLink fieldCode="DE" term="%22Encephalitis%22">Encephalitis</searchLink><br /><searchLink fieldCode="DE" term="%22Magnetic+resonance+imaging%22">Magnetic resonance imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Disease+relapse%22">Disease relapse</searchLink><br /><searchLink fieldCode="DE" term="%22Brain+imaging%22">Brain imaging</searchLink>
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  Data: Objective: To examine the utility of neuroimaging characteristics as biomarkers of prognosis in seropositive autoimmune encephalitis (AE). Methods: In this multi-center study, we retrospectively analyzed 66 cases of seropositive AE. The MRI and PET imaging was assessed by independent visual inspection. Whole brain and regional volumes were imputed by IcoMetrix, an automated volumetric assessment package. The modified Rankin Scale (mRS) was utilized to assess the patients' follow-up disability. Other outcomes were mortality, first line treatment failure, medial temporal lobe (MTL) atrophy, and clinical relapse. Univariate and multivariable regression analysis was performed. Results: Abnormalities on MRI were detected in 35.1% of patients, while PET was abnormal in 46.4%. Initial median whole brain and hippocampal volumes were below the 5th and 20th percentile respectively compared to an age-matched healthy database. After a median follow-up of 715 days, 85.2% had good functional outcome (mRS ≤ 2). Nine patients developed MTL atrophy during follow-up. On multivariable analysis, inflammatory MTL changes were associated with development of MTL atrophy (HR 19.6, p = 0.007) and initial hippocampal volume had an inverse relationship with mortality (HR 0.04, p = 0.011). Patients who developed MTL atrophy had a reduced chance of good final mRS (HR 0.16, p = 0.015). Conclusions: Neuroimaging on initial hospital admission may be provide important diagnostic and prognostic information. This study demonstrates that structural and inflammatory changes of the MTL may have importance in clinical and radiological prognosis in seropositive AE. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Neurological Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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