AbstractThe relationship between clinicopathologic diagnosis and 123I‐FP‐CIT SPECT in 18 patients with dementia (12 with Lewy body disease) from one center in the United States was assessed. The sensitivity and specificity of abnormal 123I‐FP‐CIT SPECT with reduced striatal uptake on visual inspection for predicting Lewy body disease were 91.7% and 83.3%, respectively. The mean calculated putamen to occipital ratio (mPOR) based on regions of interest was significantly reduced in Lewy body disease compared to non‐Lewy body disease cases (P = 0.002). In this study, abnormal 123I‐FP‐CIT SPECT was strongly associated with underlying Lewy body disease pathology, supporting the utility of 123I‐FP‐CIT SPECT in the clinical diagnosis of dementia with Lewy bodies.
Immune-Mediated Autonomic Neuropathies following Allogeneic Stem Cell Transplantation in Acute Myeloid Leukemia
Background/Aims. Autonomic dysfunction (AD) after allogeneic stem cell transplant (SCT) is a rare occurrence and likely immune-mediated in etiology. There is limited literature on this topic and hence, we wish to briefly describe management of two cases at our institution and their outcomes. Methods. We retrospectively identified two patients with immune-mediated AD after SCT from our database. Immune-mediated AD was defined as AD secondary to an immune-mediated etiology without an alternative cause and responding to immunosuppression. Results. The first case is of a 32-year-old man with acute myeloid leukemia (AML) who underwent double umbilical cord allogeneic SCT. The second patient was a 51-year-old woman with secondary AML who underwent matched-related donor allogeneic SCT. Both underwent an extensive work-up for an underlying etiology prior to treatment with intravenous immunoglobulin (IVIG). Conclusions. AD after SCT is a rare yet significant clinical entity. A work-up of underlying etiology should be performed. IVIG is a treatment option for these patients.
AbstractIntroductionRapid eye movement sleep behavior disorder (RBD) is strongly associated with synucleinopathies. In 2012, we reported an increased risk of mild cognitive impairment (MCI) and Parkinson disease (PD) in cognitively normal Olmsted County, Minnesota, residents, aged 70 to 89 years with probable RBD. Here, we examine their progression to dementia and other neurodegenerative phenotypes.MethodsFifteen participants with RBD who were diagnosed with either MCI or PD were longitudinally followed, and their subsequent clinical courses were reviewed.ResultsOver 6.4 ± 2.9 years, six of the 14 participants with MCI developed additional neurodegenerative signs, five of whom had Lewy body disease features. Four of them progressed to dementia at a mean age 84.8 ± 4.9 years, three of whom met the criteria for probable dementia with Lewy bodies. One subject with PD developed MCI, but not dementia.DiscussionOur findings from the population‐based sample of Olmsted County, Minnesota, residents suggest that a substantial number of RBD patients tend to develop overt synucleinopathy features over time, and RBD patients who develop MCI and subsequent dementia have clinical features most consistent with dementia with Lewy bodies.
Abstract Objective . Automated behavioral state classification can benefit next generation implantable epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow wave sleep (SWS) classification using wide bandwidth intracranial EEG (iEEG) in patients undergoing evaluation for epilepsy surgery. Approach . Data from seven patients (age 34 ± 12 , 4 women) who underwent intracranial depth electrode implantation for iEEG monitoring were included. Spectral power features (0.1–600 Hz) spanning several frequency bands from a single electrode were used to train and test a support vector machine classifier. Main results . Classification accuracy of 97.8 ± 0.3% (normal tissue) and 89.4 ± 0.8% (epileptic tissue) across seven subjects using multiple spectral power features from a single electrode was achieved. Spectral power features from electrodes placed in normal temporal neocortex were found to be more useful (accuracy 90.8 ± 0.8%) for sleep-wake state classification than electrodes located in normal hippocampus (87.1 ± 1.6%). Spectral power in high frequency band features (Ripple (80–250 Hz), Fast Ripple (250–600 Hz)) showed comparable performance for AW and SWS classification as the best performing Berger bands (Alpha, Beta, low Gamma) with accuracy ⩾90% using a single electrode contact and single spectral feature. Significance . Automated classification of wake and SWS should prove useful for future implantable epilepsy devices with limited computational power, memory, and number of electrodes. Applications include quantifying patient sleep patterns and behavioral state dependent detection, prediction, and electrical stimulation therapies.