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Olfactory Pathology in Central Nervous System Demyelinating Diseases.

ABSTRACT: Olfactory dysfunction is common in multiple sclerosis (MS). Olfactory bulb and tract pathology in MS and other demyelinating diseases remain unexplored. A human autopsy cohort of pathologically confirmed cases encompassing the spectrum of demyelinating disease (MS; n = 17), neuromyelitis optica [(NMO); n = 3] and acute disseminated encephalomyelitis [(ADEM); n = 7] was compared to neuroinflammatory [herpes simplex virus encephalitis (HSE); n = 3], neurodegenerative [Alzheimer's disease (AD); n = 4] and non-neurologic (n = 8) controls. For each case, olfactory bulbs and/or tracts were stained for myelin, axons and inflammation. Inferior frontal cortex and hippocampus were stained for myelin in a subset of MS and ADEM cases. Olfactory bulb/tract demyelination was frequent in all demyelinating diseases [MS 12/17 (70.6%); ADEM 3/7 (42.9%); NMO 2/3 (66.7%)] but was absent in HSE, AD and non-neurologic controls. Inflammation was greater in the demyelinating diseases compared to non-neurologic controls. Olfactory bulb/tract axonal loss was most severe in MS where it correlated significantly with the extent of demyelination (r = 0.610, P = 0.009) and parenchymal inflammation (r = 0.681, P = 0.003). The extent of olfactory bulb/tract demyelination correlated with that found in the adjacent inferior frontal cortex but not hippocampus. We provide unequivocal evidence that olfactory bulb/tract demyelination is frequent, can occur early and is highly inflammatory, and is specific to demyelinating disease.

SUBMITTER: DeLuca GC

PROVIDER: S-EPMC8029356 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundDifferential diagnosis of demyelinating diseases of the central nervous system is a challenging task that is prone to errors and inconsistent reading, requiring expertise and additional examination approaches. Advancements in deep-learning-based image interpretations allow for prompt and automated analyses of conventional magnetic resonance imaging (MRI), which can be utilized in classifying multi-sequence MRI, and thus may help in subsequent treatment referral.MethodsImaging and clinical data from 290 patients diagnosed with demyelinating diseases from August 2013 to October 2021 were included for analysis, including 67 patients with multiple sclerosis (MS), 162 patients with aquaporin 4 antibody-positive (AQP4+) neuromyelitis optica spectrum disorder (NMOSD), and 61 patients with myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). Considering the heterogeneous nature of lesion size and distribution in demyelinating diseases, multi-modal MRI of brain and/or spinal cord were utilized to build the deep-learning model. This novel transformer-based deep-learning model architecture was designed to be versatile in handling with multiple image sequences (coronal T2-weighted and sagittal T2-fluid attenuation inversion recovery) and scanning locations (brain and spinal cord) for differentiating among MS, NMOSD, and MOGAD. Model performances were evaluated using the area under the receiver operating curve (AUC) and the confusion matrices measurements. The classification accuracy between the fusion model and the neuroradiological raters was also compared.ResultsThe fusion model that was trained with combined brain and spinal cord MRI achieved an overall improved performance, with the AUC of 0.933 (95%CI: 0.848, 0.991), 0.942 (95%CI: 0.879, 0.987) and 0.803 (95%CI: 0.629, 0.949) for MS, AQP4+ NMOSD, and MOGAD, respectively. This exceeded the performance using the brain or spinal cord MRI alone for the identification of the AQP4+ NMOSD (AUC of 0.940, brain only and 0.689, spinal cord only) and MOGAD (0.782, brain only and 0.714, spinal cord only). In the multi-category classification, the fusion model had an accuracy of 81.4%, which was significantly higher compared to rater 1 (64.4%, p=0.04<0.05) and comparable to rater 2 (74.6%, p=0.388).ConclusionThe proposed novel transformer-based model showed desirable performance in the differentiation of MS, AQP4+ NMOSD, and MOGAD on brain and spinal cord MRI, which is comparable to that of neuroradiologists. Our model is thus applicable for interpretating conventional MRI in the differential diagnosis of demyelinating diseases with overlapping lesions.

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Olfactory Pathology in Central Nervous System Demyelinating Diseases.

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