The Non Invasive Brain Injury Evaluation, NIBIE – A New Image Technology for Studying the Mechanical Consequences of Traumatic Brain Injury

Traumatic brain injury (TBI) is an epidemiologically well-known disorder that ranges from minor to severe conditions (Kleiven, Peloso, von Holst, 2003). The aetiology of TBI is due to external violence and similar all over the world. About 80 % is defined as mild and in this category, most patients recover completely after a certain time, ranging from days to months

Cerebral near infra-red spectroscopy in traumatic brain injury as a potential independent monitoring modality and alternative to invasive tissue oxygen tension sensors

Background: Traumatic brain injury (TBI) is pathology of growing international importance. Near Infrared spectroscopy (NIRS) represents a non-invasive, cost effective and easily applies cerebral tissue monitoring modality with the potential to direct therapy and guide management decisions. Currently the use of this technology within mainstream TBI care is limited considering its potential inherent advantages. Recent advances in NIRS parameter recovery techniques and data processing potentially offer an improvement on previously evaluated technology. Frequency domain (FD) parameter recovery NIRS is one such advancement now available in clinically viable and commercially available devices. This technology has not yet been evaluated within the context of TBI care. Aims: i) To assess the current evidence within the published literature regarding the use of NIRS within the field of TBI management. ii) To compare the abilities of a frequency domain clinically viable point of care NIRS device to radiological and invasive gold standards in measuring changes in cerebral physiology. Methods: A number of specific original investigations to assess the abilities of clinically viable NIRS technology benefiting from FD parameter recovery for use in the management of TBI patients were undertaken along with a review of the existing literature. Results. NIR.S has demonstrated certain useful abilities in the monitoring of cerebral oxygenation in the care of individuals who have sustained a TBI, however sufficient evidence does not exist to support its independent use in TBI. The FD NIRS device tested demonstrated good correlation with fMRI (Valsalva and Hyperventilation), and equivalent abilities in differentiating activity within superficial extra-cranial and cerebral tissue. Manipulating of blood flow into the overlying extra-cranial tissue did not significantly affect the output parameters seen in these models. However the FD NIRS device tested did not demonstrate sufficient abilities to replace invasive brain tissue oxygen tension measurement in TBI patients. Also, within the context of controlled hypoxia (relevant to TBI) no discernable advantage was observed in utilising a device benefiting from frequency domain parameter recovery. Conclusion: NIRS still remains the best available prospect for a non-invasive monitoring modality to direct therapy and guide management in TBI care. However, further development and translation of the multitude of advancements in NIRS technology achieved recently in the science of biological optics may be required to realise this potential

Radiological Society of North America (RSNA) 3D printing Special Interest Group (SIG): Guidelines for medical 3D printing and appropriateness for clinical scenarios

Este número da revista Cadernos de Estudos Sociais estava em organização quando fomos colhidos pela morte do sociólogo Ernesto Laclau. Seu falecimento em 13 de abril de 2014 surpreendeu a todos, e particularmente ao editor Joanildo Burity, que foi seu orientando de doutorado na University of Essex, Inglaterra, e que recentemente o trouxe à Fundação Joaquim Nabuco para uma palestra, permitindo que muitos pudessem dialogar com um dos grandes intelectuais latinoamericanos contemporâneos. Assim, buscamos fazer uma homenagem ao sociólogo argentino publicando uma entrevista inédita concedida durante a sua passagem pelo Recife, em 2013, encerrando essa revista com uma sessão especial sobre a sua trajetória

Hemodynamic study in a real intracranial aneurysm: an in vitro and in silico approach

Mestrado de dupla diplomação com o Centro Federal de Educação Tecnológica Celso Suckow da Fonseca - Cefet/RJIntracranial aneurysm (IA) is a cerebrovascular disease with high rates of mortality and morbidity when it ruptures. It is known that changes in the intra-aneurysmal hemodynamic load play a significant factor in the development and rupture of IA. However, these factors are not fully understood. In this sense, the main objective of this work is to study the hemodynamic behavior during the blood analogues flow inside an AI and to determine its influence on the evolution of this pathology. To this end, experimental and numerical studies were carried out, using a real AI model obtained using computerized angiography. In the experimental approach, it was necessary, in the initial phase, to develop and manufacture biomodels from medical images of real aneurysms. Two techniques were used to manufacture the biomodels: rapid prototyping and gravity casting. The materials used to obtain the biomodels were of low cost. After manufacture, the biomodels were compared to each other for their transparency and final structure and proved to be suitable for testing flow visualizations. Numerical studies were performed with the aid of the Ansys Fluent software, using computational fluid dynamics (CFD), using the finite volume method. Subsequently, flow tests were performed experimentally and numerically using flow rates calculated from the velocity curve of a patient's doppler test. The experimental and numerical tests, in steady-state, made it possible to visualize the three-dimensional behavior of the flow inside the aneurysm, identifying the vortex zones created throughout the cardiac cycle. Correlating the results obtained in the two analyzes, it was possible to identify that the areas of vortexes are characterized by low speed and with increasing the fluid flow, the vortexes are positioned closer to the wall. These characteristics are associated with the rupture of an intracranial aneurysm. There was also a good qualitative correlation between numerical and experimental results.O aneurisma intracraniano (AI) é uma patologia cerebrovascular com altas taxas de mortalidade e morbidade quando se rompe. Sabe-se que alterações na carga hemodinâmica intra-aneurismática exerce um fator significativo no desenvolvimento e ruptura de AI, porém, esses fatores não estão totalmente compreendidos. Nesse sentido, o objetivo principal deste trabalho é o de estudar o comportamento hemodinâmico durante o escoamento de fluidos análogos do sangue no interior de um AI e determinar a sua influência na evolução da patologia. Para tal, foram realizados estudos experimentais e numéricos, utilizando um modelo de AI real obtido por meio de uma angiografia computadorizada. Na abordagem experimental foi necessário, na fase inicial, desenvolver e fabricar biomodelos a partir de imagens médicas de um aneurisma real. No fabrico dos biomodelos foram utilizadas duas técnicas: a prototipagem rápida e o vazamento por gravidade. Os materiais utilizados para a obtenção dos biomodelos foram de baixo custo. Após a fabricação, os biomodelos foram comparados entre si quanto à sua transparência e estrutura final e verificou-se serem adequados para testes de visualizações do fluxo. Os estudos numéricos foram realizados com recurso ao software Ansys Fluent, utilizando a dinâmica dos fluidos computacional (CFD), através do método dos volumes finitos. Posteriormente, foram realizados testes de escoamento experimentais e numéricos, utilizando caudais determinados a partir da curva de velocidades do ensaio doppler de um paciente. Os testes experimentais e numéricos, em regime permanente, possibilitaram a visualização do comportamento tridimensional do fluxo no interior do aneurisma, identificando as zonas de vórtices criadas ao longo do ciclo cardíaco. Correlacionando os resultados obtidos nas duas análises, foi possível identificar que as áreas de vórtices são caracterizadas por uma baixa velocidade e com o aumento do caudal os vórtices posicionam-se mais próximos da parede. Essas características apresentadas estão associadas com a ruptura de aneurisma intracraniano. Verificou-se, também, uma boa correlação qualitativa entre os resultados numéricos e experimentais

Cerebral Autoregulation-Based Blood Pressure Management In The Neuroscience Intensive Care Unit: Towards Individualizing Care In Ischemic Stroke And Subarachnoid Hemorrhage

The purpose of this thesis is to review the concept of cerebral autoregulation, to establish the feasibility of continuous bedside monitoring of autoregulation, and to examine the impact of impaired autoregulation on functional and clinical outcomes following subarachnoid hemorrhage and ischemic stroke. Autoregulation plays a key role in the regulation of brain blood flow and has been shown to fail in acute brain injury. Disturbed autoregulation may lead to secondary brain injury as well as worse outcomes. Furthermore, there exist several methodologies, both invasive and non-invasive, for the continuous assessment of autoregulation in individual patients. Resultant autoregulatory parameters of brain blood flow can be harnessed to derive optimal cerebral perfusion pressures, which may be targeted to achieve better outcomes. Multiple studies in adults and several in children have highlighted the feasibility of individualizing mean arterial pressure in this fashion. The thesis herein argues for the high degree of translatability of this personalized approach within the neuroscience intensive care unit, while underscoring the clinical import of autoregulation monitoring in critical care patients. In particular, this document recapitulates findings from two separate, prospectively enrolled patient groups with subarachnoid hemorrhage and ischemic stroke, elucidating how deviation from dynamic and personalized blood pressure targets associates with worse outcome in each cohort. While definitive clinical benefits remain elusive (pending randomized controlled trials), autoregulation-guided blood pressure parameters wield great potential for constructing an ideal physiologic environment for the injured brain. The first portion of this thesis discusses basic autoregulatory physiology as well as various tools to interrogate the brain’s pressure reactivity at the bedside. It then reviews the development of the optimal cerebral perfusion pressure as a biological hemodynamic construct. The second chapter pertains to the clinical applications of bedside neuromonitoring in patients with aneurysmal subarachnoid hemorrhage. In this section, the personalized approach to blood pressure monitoring is discussed in greater detail. Finally, in the third chapter, a similar autoregulation-oriented blood pressure algorithm is applied to a larger cohort of patients with ischemic stroke. This section contends that our novel, individualized strategy to hemodynamic management in stroke patients represents a better alternative to the currently endorsed practice of maintaining systolic blood pressures below fixed and static thresholds

Year in review in Intensive Care Medicine 2011: III. ARDS and ECMO, weaning, mechanical ventilation, noninvasive ventilation, pediatrics and miscellanea

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

Optimization of the assessment of cerebral autoregulation in neurocritical care unit

Introduction Cerebral autoregulation (CA) refers to the physiological mechanisms in the brain to maintain constant blood flow despite changes in cerebral perfusion pressure (CPP). It plays an important protective role against the danger of ischaemia or oedema of the brain. Over the years, various methods for CA assessment have been proposed, while most commonly used parameters include the autoregulation index (ARI), which grades CA into ten levels; transfer function (TF) analysis, describing CA as a high pass filter; the mean flow index (Mx), that estimates CA through the correlation coefficient between slow waves of mean cerebral blood flow velocity (CBFV) and CPP; and pressure reactivity index (PRx), calculated as a moving correlation coefficient between mean arterial blood pressure (ABP) and intracranial pressure (ICP). However, until now, how these parameters are related with each other is still not clear. A comprehensive investigation of the relationship between all these parameters is therefore needed. In addition, the methods mentioned above mostly assume the system being analysed is linear and the signals are stationary, with the announcement of non-stationary characteristic of CA, a more robust method, in particular suitable for non-stationary signal analysis, needs to be explored. Objectives and Methods This thesis addresses three primary questions: 1. What are the relationships between currently widely used CA parameters, i.e. Mx, ARI, TF parameters, from theoretical and practical point of view? 2. It there an effective method that can be introduced to assess CA, which is suitable for analyses of non-stationary signals? 3. How can bedside monitoring of cerebral autoregulation be improved in traumatic brain injury patients? These general aims have been translated into a series of experiments, retrospective analyses and background studies that are presented in different chapters of this thesis. Results and Conclusions This PhD project carefully scrutinised currently used CA assessment methodologies in TBI patients, demonstrating significant relationships between ARI, Mx and TF phase. A new introduced wavelet-transform-based method, wPRx was validated and showed more stable result for CA assessment than the well-established parameter, PRx. A multi-window approach with weighting system for optimal CPP estimation was described. The result showed a significant improvement in the continuity and stability of CPPopt estimation, which made it possible to be applied in the future clinical management of TBI patients.Gates Cambridge Scholarshi

Artificial intelligence in cancer imaging: Clinical challenges and applications

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care