Introdução:O Forame Oval Patente (FOP) é a comunicação direita-esquerda (CDE) ou shunt direita-esquerda (SDE) mais comum e frequentemente encontrada em adultos jovens com Acidente Vascular Cerebral (AVC) relacionado ao mecanismo de embolia paradoxal. A Ecocardiografia Transesofágia (ETE) é considerada o padrão para visualização direta do FOP. O Doppler Transcraniano com o teste de microbolhas é frequentemente usado para detectar CDE com boa correlação com o ETE para o diagnóstico de FOP. Mais recentemente, a Ultrassonografia Transcraniana Colorida (TCCS) com inclusão do modo-B e fluxo de cor tem superado o DTC (que é realizado \"as cegas\") em muitas aplicações clínicas mas a acurácia do TCCS para a detecção de CDE e FOP não tem sido sistematicamente avaliada. Objetivo: Determinar se o TCCS é uma ferramenta acurada para identificar tanto FOP quanto CDE. Métodos: Foram recrutados 106 pacientes prospectivamente com Acidente Vascular Cerebral Isquêmico menores de 55 anos admitidos na Unidade de Emergência do Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto (HCFMRP). Os pacientes foram submetidos aos exames de ETE, DTC e TCCS e todos os exames incluíram a técnica do teste de microbolhas. Os examinadores foram cegos para os resultados desses exames e foi calculado a concordância Kappa de Cohen inter-examinadores para o TCCS e DTC. A acurácia para o TCCS foi calculada em comparação ao ETE. Resultados: Foram detectados CDE em 54 (50.9%) dos pacientes (idade média 43.9 ± 8.2 anos) com Kappa de Cohen de 0.92 (IC 95% 0.78-1.0) quando realizados TCCS e TCD. TEE e TCSS foram positivos em 23/98 (23.4%) e ETE negative em 20/98 (20.4%). Em 30 (28.3%) o ETE revelou FOP. O TCSS teve uma sensibilidade de 88.4%(IC 95% 0.68-0.97) e especificidade de 72.2%(IC 95% 0.60-0.81) e uma razão de verossimilhança positive de 3.18 (IC 95% 2.14-4.73) para o diagnóstico de FOP. Conclusão: TCCS e DTC tiveram excelente concordância. TCCS tem uma boa acurácia para a detecção de FOP e CDE em pacientes jovens com Acidente Vascular Isquêmico / Introduction: Patent Foramen Ovale (PFO) is the most common right-to-left shunt (RLS) and is often found in young patients with stroke related to paradoxical embolism. ContrastEnhanced Transesophageal Echocardiography (TEE) is considered a gold standard to visualize PFO. Transcranial Doppler (TCD) with bubble test is often used to detect RLS with good correlation to TEE for the diagnostic of PFO. More recently, Transcranial Color Coded Sonography (TCCS) which included B-mode and color coded imaging has overcome blind TCD in many clinical applications but the accuracy of TCCS for detection of RLS and PFO has not been systematically evaluated. Hypothesis: To determine if the TCCS is an accurate tool to identify both PFO and RLS. Methods: We investigate 106 patients with ischemic stroke under 55 years-old admitted from 2012 to 2014 in a tertiary academic hospital. Patients were evaluated with TEE, TCD and TCCS, and all exams included a saline bubble test. The examiners were blinded for the other tests results. Kappa agreement was calculated inter-examiners for TCCS and TCD. Accuracy of TCCS was calculated in comparison to TEE. Results: We detected a RLS in 54 (50.9%) patients (age mean 43.9 ± 8.2) with kappa agreement 0.92 (95%CI 0.78-1.0) when performed TCCS and TCD. TEE and TCSS were positive in 23/98 (23.4%) and TEE did not reveal contrast in 20/98 (20.4%). In 30 (28.3%) patients only TEE revealed a PFO. TCSS had a sensitivity of 88.4% (95%CI 0.68-0.97), specificity of 72.2% (95%CI 0.60-0.81) and positive likelihood ratio of 3.18 (2.14-4.73) of the diagnosis of PFO. Conclusion: TCCS and TCD had an excellent agreement. TCCS has a good accuracy for the detection of PFO and RLS in young patients with stroke

Thirty-four patients with acute hemispheric ischemic strokes underwent both CT angiography and contrast-enhanced transcranial color-coded duplexsonography (TCCD) to study the effectiveness of the combined noninvasive techniques for evaluation of the circle of Willis. In 3/34 patients, CT angiography and contrast-enhanced TCCD demonstrated middle cerebral artery (MCA) occlusion, in 5 others MCA stenosis. A severe posterior cerebral artery stenosis was missed by CT angiography. In 8 patients, contrast-enhanced TCCD failed because of poor bone windows. In these patients, CT angiography was normal. CT angiography and contrast-enhanced TCCD are complementary noninvasive diagnostic tools. Disagreements between the diagnostic findings of these methods still need further evaluation by digital subtraction angiography. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

We prospectively evaluated 30 consecutive patients with echo-enhanced transcranial color-coded duplexsonography (TCCD) and correlative transfemoral digital subtraction angiography to assess the diagnostic efficacy of echo-enhanced TCCD for evaluation of collateral pathways through the circle of Willis in patients with limited acoustic bone windows and critical symptomatic carotid disease. Echo-enhanced TCCD detected collateral blood flow through the anterior communicating artery in 16 of 18 patients (sensitivity 89%, 95% CI 65–99%) and was false positive in one out of 12 patients without collateral flow (specificity 92%, 95% CI 59–100%). For the posterior communicating artery, sensitivity was 11/14 (79%, 95% CI 49–95%) and specificity was 15/16 (94%, 95% CI 70–100%). Echo-enhanced TCCD enables to study collateral blood flow through the communicating arteries of the circle of Willis with high sensitivity and specificity in patients with obstructions of the internal carotid artery and limited acoustic bone windows. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

This thesis proposes a novel approach to extracting pose information from image sequences. Current state of the art techniques focus exclusively on the image space occupied by the body for pose and action recognition. The method proposed here, however, focuses on the negative spaces: the areas surrounding the individual. This has resulted in the colour-coded negative space approach, an image preprocessing step that circumvents the need for complicated model fitting or template matching methods. The approach can be described as follows: negative spaces surrounding the human silhouette are extracted using horizontal and vertical scanning processes. These negative space areas are more numerous, and undergo more radical changes in shape than the single area occupied by the figure of the person performing an action. The colour-coded negative space representation is formed using the four binary images produced by the scanning processes. Features are then extracted from the colour-coded images. These are based on the percentage of area occupied by distinct coloured regions as well as the bounding box proportions. Pose clusters are identified using feedback from an independent action set. Subsequent images are classified using a simple Euclidean distance measure. An image sequence is thus temporally segmented into its corresponding pose representations. Action recognition simply becomes the detection of a temporally ordered sequence of poses that characterises the action. The method is purely vision-based, utilising monocular images with no need for body markers or special clothing. Two datasets were constructed using several actors performing different poses and actions. Some of these actions included actors waving their arms, sitting down or kicking a leg. These actions were recorded against a monochrome background to simplify the segmentation of the actors from the background. The actions were then recorded on DV cam and digitised into a data base. The silhouette images from these actions were isolated and placed in a frame or bounding box. The next step was to highlight the negative spaces using a directional scanning method. This scanning method colour-codes the negative spaces of each action. What became immediately apparent is that very distinctive colour patterns formed for different actions. To emphasise the action, different colours were allocated to negative spaces surrounding the image. For example, the space between the legs of an actor standing in a T - pose with legs apart would be allocated yellow, while the space below the arms were allocated different shades of green. The space surrounding the head would be different shades of purple. During an action when the actor moves one leg up in a kicking fashion, the yellow colour would increase. Inversely, when the actor closes his legs and puts them together, the yellow colour filling the negative space would decrease substantially. What also became apparent is that these coloured negative spaces are interdependent and that they influence each other during the course of an action. For example, when an actor lifts one of his legs, increasing the yellow-coded negative space, the green space between that leg and the arm decreases. This interrelationship between colours hold true for all poses and actions as presented in this thesis. In terms of pose recognition, it is significant that these colour coded negative spaces and the way the change during an action or a movement are substantial and instantly recognisable. Compare for example, looking at someone lifting an arm as opposed to seeing a vast negative space changing shape. In a controlled research environment, several actors were instructed to perform a number of different actions. After colour coding the negative spaces, it became apparent that every action can be recognised by a unique colour coded pattern. The challenge is to ascribe a numerical presentation, a mathematical quotation, to extract the essence of what is so visually apparent. The essence of pose recognition and it's measurability lies in the relationship between the colours in these negative spaces and how they impact on each other during a pose or an action. The simplest way of measuring this relationship is by calculating the percentage of each colour present during an action. These calculated percentages become the basis of pose and action recognition. By plotting these percentages on a graph confirms that the essence of these different actions and poses can in fact been captured and recognised. Despite variations in these traces caused by time differences, personal appearance and mannerisms, what emerged is a clear recognisable pattern that can be married to an action or different parts of an action. 7 Actors might lift their left leg, some slightly higher than others, some slower than others and these variations in terms of colour percentages would be recorded as a trace, but there would be very specific stages during the action where the traces would correspond, making the action recognisable.In conclusion, using negative space as a tool in human pose and tracking recognition presents an exiting research avenue because it is influenced less by variations such as difference in personal appearance and changes in the angle of observation. This approach is also simplistic and does not rely on complicated models and templates