Citations

Abstract Background: As part of the CurePSP brain donation program, a questionnaire was developed to capture basic information from the next-of-kin or someone familiar with the brain donor with respect to symptoms and clinical course. The usefulness of information from the questionnaire has not been assessed. Objective: To assess the value of information from the brain donation questionnaire as it relates to differential diagnosis of parkinsonian disorders. Methods: We reviewed 150 questionnaires, including 50 patients, each with a neuropathologic diagnosis of Lewy body disease (LBD), multiple system atrophy (MSA), or progressive supranuclear palsy (PSP). The frequency of clinical features recorded in the questionnaires was compared for the three disorders, and machine learning algorithm, XGBoost, was applied to tabulated information from the questionnaires to identify features that had predictive value with respect to neuropathologic diagnosis. Results: The information from the questionnaires correlated with core clinical features for each disorder - hallucinations for LBD, autonomic dysfunction for MSA, and early falls for PSP. Age at onset and early falls were identified as the key variables that contributed most to prediction of neuropathology. Conclusion: While less optimal than prospectively collected information, a questionnaire can provide useful clinical information for clinicopathological correlative studies.

Abstract Neuropathological assessment at autopsy is the gold standard for diagnosing neurodegenerative disorders. We aimed to develop a pipeline for diagnosing Alzheimer's disease and other tauopathies, including corticobasal degeneration, globular glial tauopathy, Pick’s disease, and progressive supranuclear palsy. We used deep learning (DL)-based approach called clustering-constrained-attention multiple instance learning (CLAM) on whole slide images (WSIs) of tau immunohistochemistry in three brain regions from 120 patients. We also augmented gradient-weighted class activation mapping (Grad-CAM) to the model for visualizing cellular-level evidence in the model’s decisions. The model using the sections of cingulate and superior frontal gyri achieved the highest area under the curve (0.970±0.037) and diagnostic accuracy (0.873±0.087). Grad-CAM showed the highest attention in known pathognomonic tau lesions for each disease (e.g., Pick bodies for Pick’s disease). Our findings supported the feasibility of the DL-based approach for the classification task on WSIs, which encouraged further investigation, especially focusing on clinicopathological correlation studies.

Abstract Neuropathological assessment at autopsy is the gold standard for diagnosing neurodegenerative disorders. We aimed to develop a pipeline for diagnosing Alzheimer's disease and other tauopathies, including corticobasal degeneration, globular glial tauopathy, Pick’s disease, and progressive supranuclear palsy. We used deep learning (DL)-based approach called clustering-constrained-attention multiple instance learning (CLAM) on whole slide images (WSIs) of tau immunohistochemistry in three brain regions from 120 patients. We also augmented gradient-weighted class activation mapping (Grad-CAM) to the model for visualizing cellular-level evidence in the model’s decisions. The model using the sections of cingulate and superior frontal gyri achieved the highest area under the curve (0.970±0.037) and diagnostic accuracy (0.873±0.087). Grad-CAM showed the highest attention in known pathognomonic tau lesions for each disease (e.g., Pick bodies for Pick’s disease). Our findings supported the feasibility of the DL-based approach for the classification task on WSIs, which encouraged further investigation, especially focusing on clinicopathological correlation studies.

AbstractBackgroundMultiple system atrophy (MSA) is a progressive neurodegenerative disorder characterized by various combinations of autonomic failure, parkinsonism, and cerebellar syndromes. Although consensus criteria have been widely used to diagnose MSA, accurate clinical diagnosis remains challenging. Other neurodegenerative disorders, such as Lewy body disease, can mimic MSA.ObjectivesWe described clinical and neuropathologic findings of two patients with Creutzfeldt–Jakob disease (CJD) who had antemortem clinical diagnoses of MSA.MethodsThe brain bank for neurodegenerative disorders was queried for cases with a clinical diagnosis of MSA, but neuropathologic findings of CJD.ResultsCase 1 was a 55‐year‐old man with a 6‐month history of orthostatic hypotension, parkinsonism, cerebellar ataxia, bradyphrenia, and memory impairment. Case 2 was a 65‐year‐old man who had a 5‐year history of cerebellar ataxia, parkinsonism, and cognitive impairment, as well as a 7‐year history of dream enactment behavior. Neither case had characteristic α‐synuclein immunoreactive neuronal or glial inclusions typical of MSA. Instead, they had spongiform encephalopathy with neuronal loss and gliosis with prion protein‐immunoreactive kuru‐like plaques. Genetic analyses in case 1 had wild‐type PRNP, whereas case 2 revealed a 4‐octapeptide repeat insertion in PRNP.ConclusionsEven when clinical features suggest MSA, CJD should also be considered if the progression is rapid or the disease course is atypical, such as the absence of autonomic dysfunction for an extended period.

ABSTRACTBackgroundAdult‐onset leukoencephalopathy with axonal spheroids and pigmented glia (ALSP) is a rare neurodegenerative disorder with characteristic clinicopathological features. Identification of pathogenic mutations in CSF1R, AARS1, and AARS2 genes led to increased recognition and diagnosis of the ALSP.ObjectivesThis paper presents the first family with typical clinical, radiological, and pathological features of ALSP, yet negative for CSF1R, AARS1, and AARS2 mutations.MethodsThe index case was a 30‐year‐old male who presented with gait difficulty, followed by cognitive decline and incontinence.ResultsNeurological examination evidenced progressive dementia, dysarthria, spasticity, parkinsonism, and severe gait disturbances. Brain MRI showed confluent white matter abnormalities with scattered foci of restricted diffusion, and atrophy of the corpus callosum. He was suspected of ALSP; however, the extensive genetic work‐up did not find pathogenic mutation. He died at 33 years, and brain autopsy was performed. He had myelin staining pallor and axonal swellings, spheroids, and pigmented glia in affected white matter. His father developed similar symptoms in his early 40s and died at 46 years. Neuropathological examination also confirmed ALSP diagnosis. We found two similar cases in the literature with typical ALSP features but negative for CSF1R mutation; however, none were tested for AARS1 and AARS2 mutations.ConclusionsWe draw attention to a new entity within the ALSP disease spectrum that needs further investigation. As the disease‐modifying therapy is already available for ALSP‐CSF1R, there is a strong need to identify the genetic cause of patients such as these in the ALSP spectrum, enabling research toward implementing effective treatment.