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Immune profile and radiological characteristics of progressive multifocal leukoencephalopathy
(2021)
Background and purpose: Progressive multifocal leukoencephalopathy (PML) constitutes a severe disease with increasing incidence, mostly in the context of immunosuppressive therapies. A detailed understanding of immune response in PML appears critical for the treatment strategy. The aim was a comprehensive immunoprofiling and radiological characterization of magnetic resonance imaging (MRI) defined PML variants.
Methods: All biopsy-confirmed PML patients (n = 15) treated in our department between January 2004 and July 2019 were retrospectively analysed. Data from MRI, histology as well as detailed clinical and outcome data were collected. The MRI-defined variants of classical (cPML) and inflammatory (iPML) PML were discriminated based on the intensity of gadolinium enhancement. In these PML variants, intensity and localization (perivascular vs. parenchymal) of inflammation in MRI and histology as well as the cellular composition by immunohistochemistry were assessed. The size of the demyelinating lesions was correlated with immune cell infiltration.
Results: Patients with MRI-defined iPML showed a stronger intensity of inflammation with an increased lymphocyte infiltration on histological level. Also, iPML was characterized by a predominantly perivascular inflammation. However, cPML patients also demonstrated certain inflammatory tissue alterations. Infiltration of CD163-positive microglia and macrophage (M/M) subtypes correlated with PML lesion size.
Conclusions: The non-invasive MRI-based discrimination of PML variants allows for an estimation of inflammatory tissue alterations, although exhibiting limitations in MRI-defined cPML. The association of a distinct phagocytic M/M subtype with the extent of demyelination might reflect disease progression.
A precise definition of a brain state has proven elusive. Here, we introduce the novel local-global concept of intrinsic ignition characterizing the dynamical complexity of different brain states. Naturally occurring intrinsic ignition events reflect the capability of a given brain area to propagate neuronal activity to other regions, giving rise to different levels of integration. The ignitory capability of brain regions is computed by the elicited level of integration for each intrinsic ignition event in each brain region, averaged over all events. This intrinsic ignition method is shown to clearly distinguish human neuroimaging data of two fundamental brain states (wakefulness and deep sleep). Importantly, whole-brain computational modelling of this data shows that at the optimal working point is found where there is maximal variability of the intrinsic ignition across brain regions. Thus, combining whole brain models with intrinsic ignition can provide novel insights into underlying mechanisms of brain states.