Разработка противотуманного стационарного светильника для автомагистралей

Современное дорожное освещение имеет ряд проблем, в числе которых низкая эффективность в условиях тумана. Улучшение качества освещения путем использования противотуманных светильников позволит повысить безопасность на дорогах и снизить усталость водителей. Существующие разработки противотуманных светильников не предусмотрены для работы в условиях Сибири, поэтому возникает необходимость разработки устойчивого дизайна противотуманного светильника. В работе описан процесс разработки дизайна стационарного противотуманного светильника, способного полноценно функционировать в условиях Сибири.Conventional road luminaire has a number of shortcomings and is ineffective in fog. By improving the quality of road lighting it will be possible to decrease the accident rate and drivers' fatigue. Existing fog lighting developments are not designed to be used in harsh conditions of Siberia, so a new luminaire design should be proposed. In this work is described the design process of a new stationary fog luminaire, adapted to the use in Siberia

Clinical Predictors of Hyperperfusion Syndrome Following Carotid Stenting: Results From a National Prospective Multicenter Study

[Objectives] The aim of the HISPANIAS (HyperperfusIon Syndrome Post-carotid ANgIoplasty And Stenting) study was to define CHS rates and develop a clinical predictive model for cerebral hyperperfusion syndrome (CHS) after carotid artery stenting (CAS).[Background] CHS is a severe complication following CAS. The presence of clinical manifestations is estimated on the basis of retrospective reviews and is still uncertain.[Methods] The HISPANIAS study was a national prospective multicenter study with 14 recruiting hospitals. CHS was classified as mild (headache only) and moderate-severe (seizure, impaired level of consciousness, or development of focal neurological signs).[Results] A total of 757 CAS procedures were performed. CHS occurred in 22 (2.9%) patients, in which 16 (2.1%) had moderate-severe CHS and 6 (0.8%) had mild CHS (only headache). The rate of hemorrhages was 0.7% and was associated with high mortality (20%). Pre-operative predictors of moderate-severe CHS in multivariate analysis were female sex (odds ratio [OR]: 3.24; 95% confidence interval [CI]: 1.11 to 9.47; p = 0.03), older patients (OR: 1.09; 95% CI: 1.01 to 1.17; p = 0.02), left carotid artery treated (OR: 4.13; 95% CI: 1.11 to 15.40; p = 0.03), and chronic renal failure (OR: 6.29; 95% CI: 1.75 to 22.57; p = 0.005). The area under the curve of this clinical and radiological model was 0.86 (95% CI: 0.81 to 0.92; p = 0.001).[Conclusions] The rate of CHS in the HISPANIAS study was 2.9%, with moderate-severe CHS of 2.1%. CHS was independently associated with female sex, older age, history of chronic kidney disease, and a treated left carotid artery. Although further investigations are needed, the authors propose a model to identify high-risk patients and develop strategies to decrease CHS morbidity and mortality in the future.This study was supported by a Spanish grant from the Instituto de Salud Carlos III (ISCIII-FIS IP14/00971, 2014–2017). The ITRIBIS project has the registration number REGPOT-2013-1. Cooperative Cerebrovascular Disease Research Network (INVICTUS+) (RD16/0019/0015). Dr. Mancha is supported by a Río Hortega contract (CM16/00015). Abbott and Grifols have partial financial supported the conduction of the HISPANIAS project but had no role in the design of the study, interpretation of the data, or manuscript approval.Peer reviewe

A prospective, international, randomized, noninferiority study comparing an implantable titanium vertebral augmentation device versus balloon kyphoplasty in the reduction of vertebral compression fractures (SAKOS study)

Producción CientíficaBackground context: Balloon kyphoplasty (BKP) is a commonly performed vertebral augmentation procedure for painful osteoporotic vertebral compression fractures (OVCFs). Objective: This study aimed to support a non-inferiority finding for the use of a titanium implantable vertebral augmentation device (TIVAD) compared to BKP. Study design: Prospective, parallel group, controlled comparative randomized study. Patient sample: Patients who presented with one or two painful OVCFs located between T7 and L4 aged <3 months, failed conservative treatment, and had an Oswestry Disability Index (ODI) score ≥30/100 were eligible for the study. Results: Among the 141 patients (78.7% female, mean age 73.3±9.5 years) who underwent surgery (TIVAD=68; BKP=73), 126 patients (89.4%) completed the 12-month follow-up period (TIVAD=61; BKP=65). The analysis of primary endpoint on the ITT population demonstrated non-inferiority of the TIVAD to BKP. The analysis of the additional composite endpoint demonstrated the superiority of TIVAD over BKP (p<0.0001) at 6 months (88.1% vs. 60.9%) and at 12 months (79.7% vs. 59.3%). Midline VB height restoration was more improved for TIVAD than for BKP at 6 months (1.14±2.61 mm vs. 0.31±2.22 mm); p=0.0246) and 12 months after surgery (1.31±2.58 mm vs. 0.10±2.34 mm; p=0.0035). No statistically significant differences were shown between procedures for improvement in functional capacity and quality of life. Pain relief was significantly more marked in the TIVAD group compared to the BKP group at 1 month (p=0.029) and at 6 months (p=0.021) after surgery. No patient required surgical reintervention or retreatment at the treated level. No symptomatic cement leakage was reported. Adverse events were similar for both groups (41.2% in the TIVAD group and 45.2% in the BKP group). The incidence of adjacent fractures was significantly lower after the TIVAD procedure than after BKP (12.9% vs. 27.3%; p=0.043). Conclusions: Study results demonstrated non-inferiority of the TIVAD to the predicate BKP with an excellent risk/benefit profile for results up to 12 months

A primer on deep learning and convolutional neural networks for clinicians

Deep learning is nowadays at the forefront of artificial intelligence. More precisely, the use of convolutional neural networks has drastically improved the learning capabilities of computer vision applications, being able to directly consider raw data without any prior feature extraction. Advanced methods in the machine learning field, such as adaptive momentum algorithms or dropout regularization, have dramatically improved the convolutional neural networks predicting ability, outperforming that of conventional fully connected neural networks. This work summarizes, in an intended didactic way, the main aspects of these cutting-edge techniques from a medical imaging perspective.We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI).Consejo Superior de Investigaciones Cientificas (JS-CSIC-BMCSO-0920) Deep-Hybrid DataCloud (H2020—Grant agreement No 777435) Servicio Cantabro de Salud.Peer reviewe

A deep learning model for prognosis prediction after intracranial hemorrhage

[Background and purpose]: Intracranial hemorrhage (ICH) is a common life-threatening condition that must be rapidly diagnosed and treated. However, there is still a lack of consensus regarding treatment, driven to some extent by prognostic uncertainty. While several prediction models for ICH detection have already been published, here we present a deep learning predictive model for ICH prognosis.[Methods]: We included patients with ICH (n = 262), and we trained a custom model for the classification of patients into poor prognosis and good prognosis, using a hybrid input consisting of brain CT images and other clinical variables. We compared it with two other models, one trained with images only (I-model) and the other with tabular data only (D-model).[Results]: Our hybrid model achieved an area under the receiver operating characteristic curve (AUC) of .924 (95% confidence interval [CI]: .831-.986), and an accuracy of .861 (95% CI: .760-.960). The I- and D-models achieved an AUC of .763 (95% CI: .622-.902) and .746 (95% CI: .598-.876), respectively.[Conclusions]: The proposed hybrid model was able to accurately classify patients into good and poor prognosis. To the best of our knowledge, this is the first ICH prognosis prediction deep learning model. We concluded that deep learning can be applied for prognosis prediction in ICH that could have a great impact on clinical decision-making. Further, hybrid inputs could be a promising technique for deep learning in medical imaging.Peer reviewe

De novo headache in ischemic stroke patients treated with thrombectomy: a prospective study

Background and aim Headache attributed to intracranial endovascular procedures is described in the ICHD-3. Our aim was to study the frequency and characteristics of headache specifically related to thrombectomy in patients with ischemic stroke. Methods Prospective evaluation of clinical features of headache after thrombectomy using an ad hoc questionnaire. Results One hundred seventeen patients were included (52.1% females). Most had an anterior circulation artery occlusion (91.5%). 93 (79.5%) received general anaesthesia. 111 (94.9%) required stent retriever, 21 (24.4%) angioplasty and 19 (16.2%) aspiration thrombectomy. 31 (26.5%; 95% CI 18.8?35.5%) had headache related to thrombectomy, and it was associated with a history of primary headache (p =?0.004). No differences about sex, initial NIHSS score, or the type or complexity of the procedure were observed. Headache was usually moderate and oppressive, ipsilateral to the artery occlusion and usually lasted less than 48?hours. Conclusions Almost one-third of patients with ischemic stroke who undergo endovascular thrombectomy experience headache in the first 24?hours, occurring more frequently in patients who had a previous history of headaches regardless of the procedure complexity.Acknowledgments: The authors received no financial suppor

Corrigendum to "Visualization, quantification and correlation of brain atrophy with clinical symptoms in spinocerebellar ataxia types 1, 3 and 6" [NeuroImage 49 (2010) 158-168] (DOI:10.1016/j.neuroimage.2009.07.027)

SCOPUS: er.jinfo:eu-repo/semantics/publishe

Visualization, quantification and correlation of brain atrophy with clinical symptoms in spinocerebellar ataxia types 1, 3 and 6.

BACKGROUND AND OBJECTIVE: Biomarkers to monitor neurological dysfunction in autosomal dominant inherited spinocerebellar ataxias (SCA) are lacking. We therefore aimed to visualize, quantify and correlate localized brain atrophy with clinical symptoms in SCA1, SCA3, and SCA6. METHODS: We compared patients suffering from SCA1 (n=48), SCA3 (n=24), and SCA6 (n=10) with 32 controls using magnetic resonance imaging (MRI) on four different scanners in eight centers followed by voxel-based morphometry (VBM) and quantitative three-dimensional (3D) volumetry. RESULTS: SCA1 and SCA3 patients presented with severe atrophy in total brainstem (consisting of midbrain, pons, and medulla), pons, medulla, total cerebellum, cerebellar hemispheres and cerebellar vermis, putamen and caudate nucleus. Atrophy in the cerebellar hemispheres was less severe in SCA3 than in SCA1 and SCA6. Atrophy in SCA6 was restricted to the grey matter of the cerebellum (VBM and volumetry), total brainstem and pons (volumetry only). Overall, we did not observe substantial atrophy in the cerebral cortex. A discriminant analysis taking into account data from pons, cerebellar hemispheres, medulla, midbrain and putamen achieved a reclassification probability of 81.7% for SCA1, SCA3, and SCA6. The repeat length of the expanded allele showed a weak negative correlation with the volume of the brainstem, pons, caudate nucleus and putamen in SCA3, and a weak correlation with the pons in SCA1, whereas no such correlation was found in SCA6. Clinical dysfunction as measured by the Scale for the Assessment and Rating of Ataxia (SARA) and the Unified Huntington's Disease Rating Scale functional assessment correlated best with the atrophy of pons in SCA1, with total brainstem atrophy in SCA3 and atrophy of total cerebellum in SCA6. CONCLUSIONS: Our data provide strong evidence that MRI is an attractive surrogate marker for clinical studies of SCA. In each SCA genotype clinical dysfunction may be caused by different patho-anatomical processes.Journal ArticleResearch Support, Non-U.S. Gov'tinfo:eu-repo/semantics/publishe