Clinical Features and Inflammatory Markers in Autoimmune Encephalitis Associated With Antibodies Against Neuronal Surface in Brazilian Patients

Acute encephalitis is a debilitating neurological disorder associated with brain inflammation and rapidly progressive encephalopathy. Autoimmune encephalitis (AE) is increasingly recognized as one of the most frequent causes of encephalitis, however signs of inflammation are not always present at the onset which may delay the diagnosis. We retrospectively assessed patients with AE associated with antibodies against neuronal surface diagnosed in reference centers in Northeast of Brazil between 2014 to 2017. CNS inflammatory markers were defined as altered CSF (pleocytosis >5 cells/mm3) and/or any brain parenchymal MRI signal abnormality. Thirteen patients were evaluated, anti-NMDAR was the most common antibody found (10/13, 77%), followed by anti-LGI1 (2/13, 15%), and anti-AMPAR (1/13, 7%). Median time to diagnosis was 4 months (range 2–9 months). Among these 13 patients, 6 (46.1%) had inflammatory markers and when compared to those who did not present signs of inflammation, there were no significant differences regarding the age of onset, time to diagnosis and modified Rankin scale score at the last visit. Most of the patients presented partial or complete response to immunotherapy during follow-up. Our findings suggest that the presence of inflammatory markers may not correlate with clinical presentation or prognosis in patients with AE associated with antibodies against neuronal surface. Neurologists should be aware to recognize clinical features of AE and promptly request antibody testing even without evidence of inflammation in CSF or MRI studies

PET imaging of multiple sclerosis-related processes: clinical study

INTRODUÇÃO: Perfis distintos de neuroinflamação e de conteúdo de mielina são descritos dentre os fenótipos da esclerose múltipla (EM), tanto na substância branca (SB) quanto cinzenta (SC). A imagem de tomografia por emissão de pósitrons (do inglês, Positron Emission Tomography - PET) pode ajudar a desvendar as nuances desses processos patológicos in vivo nos diferetes estágios de incapacidade. OBJETIVO: Analisar o perfil de ativação microglial e conteúdo de mielina em uma coorte de pacientes com EM e um grupo de controles saudáveis (CS), com ênfase na diferenciação dos fenótipos. MÉTODO: Imagens PET utilizando [11C]PK11195 e [11C]PIB (do inglês, Pittsburgh Compound B) foram adquiridas em um sistema híbrido de PET e ressonância magnética (RM) 3T, para caracterizar, respectivamente, o perfil de células da resposta imune inata e o conteúdo de mielina em 47 pacientes com EM e 18 CS. Para a análise baseada em volume de interesse (VOI), o volume de distribuição (VT) do [11C]PK11195 foi determinado usando a função de entrada arterial corrigida para metabólitos, enquanto a razão de volume de distribuição (DVR) do [11C]PIB foi estimada usando uma região de referência individual extraída por um algoritmo específico. Uma análise baseada em voxels também foi realizada usando Statistical Parametric Mapping. A incapacidade funcional foi avaliada pela Escala Expandida do Estado de Incapacidade (EDSS), a Multiple Sclerosis Functional Composite, e o Symbol Digit Modality Test (SDMT). RESULTADO: Na análise baseada em VOI, a captação de [11C]PIB (DVR) diferiu entre pacientes e CS no corpo caloso (P = 0,019), enquanto não foram observadas diferenças na captação de [11C]PK11195 (VT). Além disso, não foram observadas correlações ou associações entre os dois traçadores dentro dos VOI analisados. Na análise baseada em voxel, maior captação de [11C]PK11195 foi observada difusamente na SB ao comparar o fenótipo progressivo e CS, e menor captação de [11C]PIB foi observada em certas regiões de SB ao comparar o fenótipo remitente-recorrente e CS. Nenhum dos traçadores foi capaz de diferenciar os fenótipos a nível de voxel ou VOI em nossa coorte. Modelos de regressão linear ajustados para idade, sexo e fenótipo demonstraram que maior incapacidade no EDSS estava associado a uma maior captação de [11C]PK11195 (VT) e menor captação de [11C]PIB (DVR) no corpo caloso (P = 0,001; P = 0,023), caudado (P = 0,015 ; P = 0,008) e lesão T2 total (P = 0,007; P = 0,012), enquanto melhor desempenho cognitivo no SDMT foi associado a maior captação de [11C]PIB (DVR) no corpo caloso (P = 0,001) e menor captação de [11C]PK11195 (VT) (P = 0,013). CONCLUSÃO: Um perfil de ativação difuso de células da resposta imune inata e uma perda acentuada de mielina nas lesões T2 e regiões próximas aos ventrículos foi observada nos pacientes com EM. Esses processos patológicos parecem ocorrer de forma independente, estando ambos associados à maior incapacidade, tanto em estruturas de SB quanto de SC. Nenhum dos traçadores foi capaz de diferenciar os fenótipos de EM a nível de VOI ou voxel em nossa coorteINTRODUCTION: Neuropathological studies have demonstrated distinct profiles of neuroinflammation and myelin injury in the white matter (WM) and gray matter (GM) among different multiple sclerosis (MS) phenotypes and disability stages. Positron Emission Tomography (PET) using specific tracers may uncover the in vivo molecular pathology and broaden the understanding of the disease heterogeneity. OBJECTIVE: To analyze the microglia profile and myelin content using PET imaging in a cohort of patients with multiple sclerosis (relapsingremitting and progressive phenotypes) and a group healthy control (HC), with an emphasis on differentiating MS phenotypes. METHOD: We used the 18-kDa translocator protein (TSPO) tracer [11C]PK11195 and [11C]PIB (Pittsburgh Compound B) PET images acquired in a hybrid PET/MR 3 T system to characterize, respectively, the profile of innate immune cells and myelin content in 47 patients with MS and 18 HC. For the volume of interest (VOI)based analysis of the dynamic data, [11C]PK11195 distribution volume (VT) was determined for each subject using a metabolite-corrected arterial plasma input function while [11C]PIB distribution volume ratio (DVR) was estimated using an individual reference region extracted by a supervised clustering algorithm. A voxel-based analysis was also performed using Statistical Parametric Mapping. Functional disability was evaluated by the Expanded Disability Status Scale (EDSS), Multiple Sclerosis Functional Composite (MSFC), and Symbol Digit Modality Test (SDMT). RESULT: In the VOI-based analysis, [11C]PIB DVR differed between patients and HC in the corpus callosum (P=0.019) while no differences [11C]PK11195 VT were observed in patients relative to HC. Furthermore, no correlations or associations were observed between both tracers within the VOI analyzed. In the voxel-based analysis, high [11C]PK11195 uptake was observed diffusively in the WM when comparing the progressive phenotype and HC, and lower [11C]PIB uptake was observed in certain WM regions when comparing the relapsingremitting phenotype and HC. None of the tracers were able to differentiate phenotypes at voxel or VOI level in our cohort. Linear regression models adjusted for age, sex, and phenotype demonstrated that higher EDSS was associated with an increased [11C]PK11195 VT and lower [11C]PIB DVR in corpus callosum (P = 0.001; P = 0.023), caudate (P = 0.015; P = 0.008), and total T2 lesion (P = 0.007; P = 0.012), while better cognitive scores in SDMT were associated with higher [11C]PIB DVR in the corpus callosum (P = 0.001), and lower [11C]PK11195 VT (P = 0.013). CONCLUSION: Widespread innate immune cells activated profile and marked loss of myelin in T2 lesions and regions close to the ventricles was observed in patients with MS. These pathological processes seem to occur independently, and are associated with greater disability, both in SB and SC structures. None of the tracers were able to differentiate phenotypes at the voxel or VOI level in our cohor

Generating PET-derived maps of myelin content from clinical MRI using curricular discriminator training in generative adversarial networks

International audienceMultiple sclerosis (MS) is a demyenalinating inflammatory neurological disease. In vivo biomarkers of myelin content are of major importance for patient care and clinical trials. Positron Emission Tomography (PET) with Pittsburgh Compound B (PiB) provides a specific myelin marker. However, it is not available in clinical routine. In this paper, we propose a method to generate myelin maps by synthesizing PiB PET from clinical routine MRI sequences (T1-weighted and FLAIR). To that purpose, we introduce a new curriculum learning strategy for training generative adversarial networks (GAN). Specifically, we design a curricular approach for training the discriminator: training starts with only lesion patches and random patches (from anywhere in the white matter) are progressively introduced. We relied on two distinct cohorts of MS patients acquired each on a different scanner and in a different country. One cohort was used for training/validation and the other one for testing. We found that the synthetic PiB PET was strongly correlated to the ground-truth both at the lesion level (r = 0.70, p < 10-5) and the patient level (r = 0.74, p < 10-5). Moreover, the correlations were stronger when using the curricular learning strategy compared to starting the discriminator training from random patches. Our results demonstrate the interest of this new curriculum learning strategy for PET image synthesis. Even though further evaluations are needed, our approach has the potential to provide a useful biomarker for clinical routine follow-up of patients with MS

Generating PET-derived maps of myelin content from clinical MRI using curricular discriminator training in generative adversarial networks

International audienceMultiple sclerosis (MS) is a demyenalinating inflammatory neurological disease. In vivo biomarkers of myelin content are of major importance for patient care and clinical trials. Positron Emission Tomography (PET) with Pittsburgh Compound B (PiB) provides a specific myelin marker. However, it is not available in clinical routine. In this paper, we propose a method to generate myelin maps by synthesizing PiB PET from clinical routine MRI sequences (T1-weighted and FLAIR). To that purpose, we introduce a new curriculum learning strategy for training generative adversarial networks (GAN). Specifically, we design a curricular approach for training the discriminator: training starts with only lesion patches and random patches (from anywhere in the white matter) are progressively introduced. We relied on two distinct cohorts of MS patients acquired each on a different scanner and in a different country. One cohort was used for training/validation and the other one for testing. We found that the synthetic PiB PET was strongly correlated to the ground-truth both at the lesion level (r = 0.70, p < 10-5) and the patient level (r = 0.74, p < 10-5). Moreover, the correlations were stronger when using the curricular learning strategy compared to starting the discriminator training from random patches. Our results demonstrate the interest of this new curriculum learning strategy for PET image synthesis. Even though further evaluations are needed, our approach has the potential to provide a useful biomarker for clinical routine follow-up of patients with MS