Acute neuropsychiatry:a confused patient and a puzzled doctor

BACKGROUND: Anti-NMDA-receptor-encephalitis is a progressive autoimmune disease with significant mortality if left untreated.CASE DESCRIPTION: A 58-year-old man without previous psychiatric or neurologic history presented at the emergency department after brief loss of consciousness at work. Within a few hours, the patient developed acute neuropsychiatric symptoms, including altered levels of consciousness, aggression, incoherence, change in behaviour, and psychomotor agitation. Initially, additional blood, cerebrospinal fluid and EEG tests showed no abnormalities. Over the course of the following days, catatonia, orofacial dyskinesia and autonomic-function disorder developed, eventually with respiratory insufficiency, necessitating transfer to the intensive-care unit. At this stage, the EEG did show abnormalities, and cerebrospinal fluid analysis showed marginal pleocytosis. The patient was treated with intravenous methylprednisolone and immunoglobins. Anti-NMDA-receptor antibodies were present in the blood and cerebrospinal fluid. Screening for malignancy identified small-cell lung carcinoma, for which the patient was treated with cytostatic agents.CONCLUSION: Acute neuropsychiatric symptoms in a middle-aged patient with no psychiatric medical history are suggestive of an underlying somatic cause. Timely recognition and treatment of anti-NMDA-receptor encephalitis is essential to improve the prognosis.</p

Clinical utility of convolutional neural networks for treatment planning in radiotherapy for spinal metastases

Background and purpose: Spine delineation is essential for high quality radiotherapy treatment planning of spinal metastases. However, manual delineation is time-consuming and prone to interobserver variability. Automatic spine delineation, especially using deep learning, has shown promising results in healthy subjects. We aimed to evaluate the clinical utility of deep learning-based vertebral body delineations for radiotherapy planning purposes. Materials and methods: A multi-scale convolutional neural network (CNN) was used for automatic segmentation and labeling. Two approaches were tested: the combined approach using one CNN for both segmentation and labeling, and the sequential approach using separate CNN's for these tasks. Training and internal validation data included 580 vertebrae, external validation data included 202 vertebrae. For quantitative assessment, Dice similarity coefficient (DSC) and Hausdorff distance (HD) were used. Axial slices from external images were presented to radiation oncologists for subjective evaluation. Results: Both approaches performed comparably during the internal validation (DSC: 96.7%, HD: 3.6 mm), but the sequential approach proved more robust during the external validation (DSC: 94.5% vs 94.4%, p < 0.001, HD: 4.5 vs 7.1 mm, p < 0.001). Subsequently, subjective evaluation of this sequential approach showed that experienced radiation oncologists could distinguish automatic from human-made contours in 63% of cases. They rated automatic contours clinically acceptable in 77% of cases, compared to 88% of human-made contours. Conclusion: We present a feasible approach for automatic vertebral body delineation using two variants of a multi-scale CNN. This approach generates high quality automatic delineations, which can save time in a clinical radiotherapy workflow

Remineralization of lytic spinal metastases after radiotherapy

BACKGROUND CONTEXT: Palliative radiotherapy (RT) can lead to remineralization of osteolytic lesions thereby potentially restoring some of the weight-bearing capacity and preventing vertebral collapse. It is not clear, however, under which circumstances remineralization of osteolytic lesions occurs. PURPOSE: The aim of this study was to investigate the change in bone mineral density in spinal metastases after RT compared to a reference region, and find associated factors. STUDY DESIGN: Retrospective analysis within prospective observational cohort OUTCOME MEASURES: change in bone mineral density measured in Hounsfield Units (HU). PATIENT SAMPLE: patients treated with RT for (painful) bone metastases. METHODS: Patients with spinal metastases were included if computed tomography scans both pre- and post-RT were available. Bone density was measured in HU. A region of interest (ROI) was drawn manually in the metastatic lesion. As a reference, a measurement of bone density in adjacent, unaffected, and non-irradiated vertebrae was used. Factors tested for association were origin of the primary tumor, RT dose and fractionation scheme, and concomitant use of bisphosphonates. RESULTS: A total of 31 patients with 49 spinal metastases, originating from various primary tumors, were included. The median age on baseline was 58 years (IQR: 53–63) and median time between baseline and follow-up scan was 8.2 months (IQR: 3.0–18.4). Difference in HU in the lesion before and after treatment was 146.9 HU (95% CI 68.4–225.4; p<.01). Difference in HU in the reference vertebra between baseline and first follow-up was 19.1 HU (95% CI -47.9 to 86.0; p=.58). Difference between reference vertebrae and metastatic lesions on baseline was -194.1 HU (95% CI -276.2 to -112.0; p<.01). After RT, this difference was reduced to -50.3 HU (95% CI -199.6 to 99.0; p=.52). Patients using bisphosphonates showed a greater increase in HU, 194.1 HU versus 60.6 HU, p=.01. CONCLUSIONS: Palliative radiation of osteolytic lytic spinal metastases is positively associated with an increased bone mineral density at follow-up. The use of bisphosphonates was linked to an increased bone mineral density when used during or after RT

Massive Peatland Carbon Banks Vulnerable to Rising Temperatures

Peatlands contain one-third of the world’s soil carbon (C). If destabilized, decomposition of this vast C bank could accelerate climate warming; however, the likelihood of this outcome remains unknown. Here, we examine peatland C stability through five years of whole-ecosystem warming and two years of elevated atmospheric carbon dioxide concentrations (eCO2). Warming exponentially increased methane (CH4) emissions and enhanced CH4 production rates throughout the entire soil profile; although surface CH4 production rates remain much greater than those at depth. Additionally, older deeper C sources played a larger role in decomposition following prolonged warming. Most troubling, decreases in CO2:CH4 ratios in gas production, porewater concentrations, and emissions, indicate that the peatland is becoming more methanogenic with warming. We observed limited evidence of eCO2 effects. Our results suggest that ecosystem responses are largely driven by surface peat, but that the vast C bank at depth in peatlands is responsive to prolonged warming

Peatland Initiation, Carbon Accumulation, and 2 ka Depth in the James Bay Lowland and Adjacent Regions

Copyright © 2014 University of Colorado at Boulder, Institute of Arctic and Alpine ResearchPeatlands surrounding Hudson and James Bays form the second largest peatland complex in the world and contain major stores of soil carbon (C). This study utilized a transect of eight ombrotrophic peat cores from remote regions of central and northern Ontario to quantify the magnitude and rate of C accumulation since peatland initiation and for the past 2000 calendar years before present (2 ka). These new data were supplemented by 17 millennially resolved chronologies from a literature review covering the Boreal Shield, Hudson Plains, and Taiga Shield bordering Hudson and James Bays. Peatlands initiated in central and northern Ontario by 7.8 ka following deglaciation and isostatic emergence of northern areas to above sea level. Total C accumulated since inception averaged 109.7 ± (std. dev.) 36.2 kg C m–2. Approximately 40% of total soil C has accumulated since 2 ka at an average apparent rate of 20.2 ± 6.9 g C m–2 yr–1. The 2 ka depths correlate significantly and positively with modern gridded climate estimates for mean annual precipitation, mean annual air temperature, growing degree-days > 0 °C, and photosynthetically active radiation integrated over days > 0 °C. There are significantly shallower depths in permafrost peatlands. Vertical peat accumulation was likely constrained by temperature, growing season length, and photosynthetically active radiation over the last 2 ka in the Hudson Bay Lowlands and surrounding regions.US National Science Foundatio