Optimizing the Definition of Ischemic Core in CT Perfusion: Influence of Infarct Growth and Tissue-Specific Thresholds.

BACKGROUND AND PURPOSE: CTP allows estimating ischemic core in patients with acute stroke. However, these estimations have limited accuracy compared with MR imaging. We studied the effect of applying WM- and GM-specific thresholds and analyzed the infarct growth from baseline imaging to reperfusion. MATERIALS AND METHODS: This was a single-center cohort of consecutive patients (n = 113) with witnessed strokes due to proximal carotid territory occlusions with baseline CT perfusion, complete reperfusion, and follow-up DWI. We segmented GM and WM, coregistered CTP with DWI, and compared the accuracy of the different predictions for each voxel on DWI through receiver operating characteristic analysis. We assessed the yield of different relative CBF thresholds to predict the final infarct volume and an estimated infarct growth-corrected volume (subtracting the infarct growth from baseline imaging to complete reperfusion) for a single relative CBF threshold and GM- and WM-specific thresholds. RESULTS: The fixed threshold underestimated lesions in GM and overestimated them in WM. Double GM- and WM-specific thresholds of relative CBF were superior to fixed thresholds in predicting infarcted voxels. The closest estimations of the infarct on DWI were based on a relative CBF of 25% for a single threshold, 35% for GM, and 20% for WM, and they decreased when correcting for infarct growth: 20% for a single threshold, 25% for GM, and 15% for WM. The combination of 25% for GM and 15% for WM yielded the best prediction. CONCLUSIONS: GM- and WM-specific thresholds result in different estimations of ischemic core in CTP and increase the global accuracy. More restrictive thresholds better estimate the actual extent of the infarcted tissue.

COVID-19 and Acute Respiratory Distress Syndrome. Impact of corticosteroid treatment and predictors of poor outcome.

OBJECTIVE: To assess the impact of corticosteroids on inflammatory and respiratory parameters of patients with COVID-19 and acute respiratory distress syndrome (ARDS). METHODS: Longitudinal, retrospective, observational study conducted in an ICU of a second level hospital. Adult patients with COVID-19 were included. Baseline characteristics, data on SARS-CoV-2 infection, treatment received, evolution of respiratory and inflammatory parameters, and ICU and hospital stay and mortality were analyzed. RESULTS: A total of 27 patients were included, 63% men, median age: 68.4 (51.8, 72.2) years. All patients met ARDS criteria and received MV and corticosteroids. After corticosteroids treatment we observed a reduction in the O2 A-a gradient [day 0: 322 (249, 425); day 3: 169 (129.5, 239.5) p<0.001; day 5: 144 (127.5, 228.0) p<0.001; day 7: 192 (120, 261) p=0.002] and an increase in the pO2/FiO2 ratio on days 3 and 5, but not on day 7 [day 0: 129 (100, 168); day 3: 193 (140, 236) p=0.002; day 5: 183 (141, 255) p=0.004; day 7: 170 (116, 251) p=0.057]. CRP also decreased on days 3 and 5 and increased again on day 7 [day 0: 16 (8.6, 24); day 3: 3.4 (1.7, 10.2) p<0.001; day 5: 4.1 (1.4, 10.2) p<0.001; day 7: 13.5 (6.8, 17.3) p=0.063]. Persistence of moderate ARDS on day 7 was related to a greater risk of poor outcome (OR 6.417 [1.091-37.735], p=0.040). CONCLUSIONS: Corticosteroids appears to reduce the inflammation and temporarily improve the oxygenation in COVID-19 and ARDS patients. Persistence of ARDS after 7 days treatment is a predictor of poor outcome.

Trombo flotante en cavidades cardíacas derechas causante de embolismo pulmonar en paciente con ictus isquémico agudo. Caso clínico y revisión de la literatura / Floating right heart thrombus causing pulmonary embolism in a patient with acute ischaemic stroke: A case report and review of literatura

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Neuroimagen en el diagnóstico y pronóstico de la encefalopatía hipoglucémica: a propósito de un caso / Neuroimaging in hypoglycaemic encephalopathy diagnosis and prognosis: A case report

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A bio-inspired two-layer mixed-signal flexible programmable chip for early vision.

A bio-inspired model for an analog programmable array processor (APAP), based on studies on the vertebrate retina, has permitted the realization of complex programmable spatio-temporal dynamics in VLSI. This model mimics the way in which images are processed in the visual pathway, what renders a feasible alternative for the implementation of early vision tasks in standard technologies. A prototype chip has been designed and fabricated in 0.5 /spl mu/m CMOS. It renders a computing power per silicon area and power consumption that is amongst the highest reported for a single chip. The details of the bio-inspired network model, the analog building block design challenges and trade-offs and some functional tests results are presented in this paper.

Neuro-fuzzy chip to handle complex tasks with analog performance.

This paper presents a mixed-signal neuro-fuzzy controller chip which, in terms of power consumption, input-output delay, and precision, performs as a fully analog implementation. However, it has much larger complexity than its purely analog counterparts. This combination of performance and complexity is achieved through the use of a mixed-signal architecture consisting of a programmable analog core of reduced complexity, and a strategy, and the associated mixed-signal circuitry, to cover the whole input space through the dynamic programming of this core. Since errors and delays are proportional to the reduced number of fuzzy rules included in the analog core, they are much smaller than in the case where the whole rule set is implemented by analog circuitry. Also, the area and the power consumption of the new architecture are smaller than those of its purely analog counterparts simply because most rules are implemented through programming. The paper presents a set of building blocks associated to this architecture, and gives results for an exemplary prototype. This prototype, called multiplexing fuzzy controller (MFCON), has been realized in a CMOS 0.7 /spl mu/m standard technology. It has two inputs, implements 64 rules, and features 500 ns of input to output delay with 16-mW of power consumption. Results from the chip in a control application with a dc motor are also provided.

CMOS realization of a 2-layer CNN universal machine chip.

Some features of the biological retina can be modelled by a 2-layer cellular neural network (CNN) composed of locally connected elementary nonlinear processors. In order to explore these complex spatiotemporal dynamics for image processing, a prototype chip has been designed and fabricated in a 0.5 microm CMOS technology. Design challenges, trade-offs, the building blocks and the tests results for this system with 0.5 x 10(6) transistors, most of them operating in analog mode, are presented in this paper.

A CMOS analog adaptive BAM with on-chip learning and weight refreshing.

The transconductance-mode (T-mode) approach is extended to implement analog continuous-time neural network hardware systems to include on-chip Hebbian learning and on-chip analog weight storage capability. The demonstration vehicle used is a 5+5-neuron bidirectional associative memory (BAM) prototype fabricated in a standard 2-mum double-metal double-polysilicon CMOS process. Mismatches and nonidealities in learning neural hardware are not supposed to be critical if on-chip learning is available, because they will be implicitly compensated. However, mismatches in the learning circuits themselves cannot always be compensated. This mismatch is specially important if the learning circuits use transistors operating in weak inversion. The authors estimate the expected mismatch between learning circuits in the BAM network prototype and evaluate its effect on the learning performance, using theoretical computations and Monte Carlo HSPICE simulations. These theoretical predictions are verified using experimentally measured results on the test vehicle prototype.