Non-contrast CT markers of intracerebral hematoma expansion : a reliability study

Objectives: We evaluated whether clinicians agree in the detection of non-contrast CT markers of intracerebral hemorrhage (ICH) expansion. Methods: From our local dataset, we randomly sampled 60 patients diagnosed with spontaneous ICH. Fifteen physicians and trainees (Stroke Neurology, Interventional and Diagnostic Neuroradiology) were trained to identify six density (Barras density, black hole, blend, hypodensity, fluid level, swirl) and three shape (Barras shape, island, satellite) expansion markers, using standardized definitions. Thirteen raters performed a second assessment. Inter and intra-rater agreement were measured using Gwet’s AC1, with a coefficient > 0.60 indicating substantial to almost perfect agreement. Results: Almost perfect inter-rater agreement was observed for the swirl (0.85, 95% CI: 0.78-0.90) and fluid level (0.84, 95% CI: 0.76-0.90) markers, while the hypodensity (0.67, 95% CI: 0.56-0.76) and blend (0.62, 95% CI: 0.51-0.71) markers showed substantial agreement. Inter-rater agreement was otherwise moderate, and comparable between density and shape markers. Inter-rater agreement was lower for the three markers that require the rater to identify one specific axial slice (Barras density, Barras shape, island: 0.46, 95% CI: 0.40-0.52 versus others: 0.60, 95% CI: 0.56-0.63). Inter-observer agreement did not differ when stratified for raters’ experience, hematoma location, volume or anticoagulation status. Intrarater agreement was substantial to almost perfect for all but the black hole marker. Conclusion: In a large sample of raters with different backgrounds and expertise levels, only four of nine non-contrast CT markers of ICH expansion showed substantial to almost perfect inter-rater agreement

Antihypertensives for combating dementia? A perspective on candidate molecular mechanisms and population-based prevention

Age-related increases in prevalent dementia over the next 30–40 years risk collapsing medical resources or radically altering the way we treat patients. Better prevention of dementia therefore needs to be one of our highest medical priorities. We propose a perspective on the pathological basis of dementia based on a cerebrovascular-Alzheimer disease spectrum that provides a more powerful explanatory framework when considering the impact of possible public health interventions. With this in mind, a synthesis of evidence from basic, clinical and epidemiological studies indeed suggests that the enhanced treatment of hypertension could be effective for the primary prevention of dementia of either Alzheimer or vascular etiology. In particular, we focus on candidate preventative mechanisms, including reduced cerebrovascular disease, disruption of hypoxia-dependent amyloidogenesis and the potential neuroprotective properties of calcium channel blockers. Following the successful translation of large, long-term and resource-intense trials in cardiology into improved vascular health outcomes in many countries, new multinational prevention trials with dementia-related primary outcomes are now urgently required

Deep polarization imaging for 3D shape and SVBRDF acquisition

We present a novel method for efficient acquisition of shape and spatially varying reflectance of 3D objects using polarization cues. Unlike previous works that have exploited polarization to estimate material or object appearance under certain constraints (known shape or multiview acquisition), we lift such restrictions by coupling polarization imaging with deep learning to achieve high quality estimate of 3D object shape (surface normals and depth)and SVBRDF using single-view polarization imaging under frontal flash illumination. In addition to acquired polarization images, we provide our deep network with strong novel cues related to shape and reflectance, in the form of a normalized Stokes map and an estimate of diffuse color. We additionally describe modifications to network architecture and training loss which provide further qualitative improvements. We demonstrate our approach to achieve superior results compared to recent works employing deep learning in conjunction with flash illumination

Spectral upsampling approaches for RGB illumination

We present two practical approaches for high fidelity spectral upsampling of previously recorded RGB illumination in the form of an image-based representation such as an RGB light probe. Unlike previous approaches that require multiple measurements with a spectrometer or a reference color chart under a target illumination environment, our method requires no additional information for the spectral upsampling step. Instead, we construct a data-driven basis of spectral distributions for incident illumination from a set of six RGBW LEDs (three narrowband and three broadband) that we employ to represent a given RGB color using a convex combination of the six basis spectra. We propose two different approaches for estimating the weights of the convex combination using – (a) genetic algorithm, and (b) neural networks. We additionally propose a theoretical basis consisting of a set of narrow and broad Gaussians as a generalization of the approach, and also evaluate an alternate LED basis for spectral upsampling. We achieve good qualitative matches of the predicted illumination spectrum using our spectral upsampling approach to ground truth illumination spectrum while achieving near perfect matching of the RGB color of the given illumination in the vast majority of cases. We demonstrate that the spectrally upsampled RGB illumination can be employed for various applications including improved lighting reproduction as well as more accurate spectral rendering

Guided Fine-Tuning for Large-Scale Material Transfer

International audienceSVBRDF exemplar Rendering HD Input SVBRDF exemplar Rendering Figure 1: Our method transfers the appearance of one or a few exemplar SVBRDFs to a target picture. This approach allows the capture of large planar surfaces taken with ambient lighting (far left), by extracting the SVBRDF exemplars from close-up flash pictures (lower left), as well as the creation of plausible SVBRDFs from internet pictures by using existing artist-designed materials as exemplars (right). Please see supplemental materials for high-resolution SVBRDF parameter maps and animated renderings of all our results, which give a much better impression of the material properties. Abstract We present a method to transfer the appearance of one or a few exemplar SVBRDFs to a target image representing similar materials. Our solution is extremely simple: we fine-tune a deep appearance-capture network on the provided exemplars, such that it learns to extract similar SVBRDF values from the target image. We introduce two novel material capture and design workflows that demonstrate the strength of this simple approach. Our first workflow allows to produce plausible SVBRDFs of large-scale objects from only a few pictures. Specifically, users only need take a single picture of a large surface and a few close-up flash pictures of some of its details. We use existing methods to extract SVBRDF parameters from the close-ups, and our method to transfer these parameters to the entire surface, enabling the lightweight capture of surfaces several meters wide such as murals, floors and furniture. In our second workflow, we provide a powerful way for users to create large SVBRDFs from internet pictures by transferring the appearance of existing, pre-designed SVBRDFs. By selecting different exemplars, users can control the materials assigned to the target image, greatly enhancing the creative possibilities offered by deep appearance capture

A randomized pragmatic care trial on endovascular acute stroke interventions (EASI): criticisms, responses, and ethics of integrating research and clinical care

Abstract Background The Endovascular Acute Stroke Intervention (EASI) trial was conceived as a pragmatic care trial, designed to integrate trial methods with clinical practice. Reporting the EASI experience was met with objections and criticisms during peer review concerning both scientific and ethical issues. Our goal is to discuss these criticisms in order to promote the pragmatic approach of care trials in outcome-based medical care. Methods The comments and criticisms of 11 reviewers from 5 journals were collected and analyzed. The EASI protocol was also compared to the protocols of seven thrombectomy trials using the pragmatic-explanatory continuum indicator summary (PRECIS). Results Main criticisms of EASI concerned selection criteria that were judged to be too vague and too inclusive, brain and vascular imaging methods that were not sufficiently prescribed by protocol, lack of blinding of outcome assessment, and lack of power. EASI was at the pragmatic end of the spectrum of thrombectomy trials. Conclusion The pragmatic care trial methodology is not currently well-established. More work needs to be done to integrate scientific methods and ethical care in the best medical interest of current patients

Predictors of Outcome After Mechanical Thrombectomy in Stroke Patients Aged ≥85 Years

International audienceBACKGROUND: The effectiveness of mechanical thrombectomy (MT) in elderly stroke patients remains debated. We aimed to describe outcomes and their predictors in a cohort of patients aged ≥ 85 years treated with MT. METHODS: Data from consecutive patients aged ≥ 85 years undergoing MT at two stroke centers between January 2016 and November 2019 were reviewed. Admission National Institutes of Health Stroke Scale (NIHSS), pre-stroke, and 3-month modified Rankin scale (mRS) were collected. Successful recanalization was defined as modified thrombolysis in cerebral ischemia score ≥ 2b. Good outcome was defined as mRS 0-3 or equal to pre-stroke mRS at 3 months. RESULTS: Of 151 included patients, successful recanalization was achieved in 74.2%. At 3 months, 44.7% of patients had a good outcome and 39% had died. Any intracranial hemorrhage (ICH) and symptomatic ICH occurred in 20.3% and 3.6%, respectively. Logistic regression analysis identified lower pre-stroke mRS score (adjusted odds ratio [aOR], 0.52; 95% CI, 0.36-0.76), lower admission NIHSS score (aOR, 0.90; 95% CI, 0.83-0.97), successful recanalization (aOR, 3.65; 95% CI, 1.32-10.09), and absence of ICH on follow-up imaging (aOR, 0.42; 95% CI, 0.08-0.75), to be independent predictors of good outcome. Patients with successful recanalization had a higher proportion of good outcome (45.3% vs 34.3%, p = 0.013) and lower mortality at 3 months (35.8% vs 48.6%, p = 0.006) compared to patients with unsuccessful recanalization. CONCLUSIONS: Among patients aged ≥ 85 years, successful recanalization with MT is relatively common and associated with better 3-month outcome and lower mortality than failed recanalization. Attempting to achieve recanalization in elderly patients using MT appears reasonable