36 resultados para Computational Delay-Time
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BACKGROUND: The pre-conditioning of tumor vessels by low-dose photodynamic therapy (L-PDT) was shown to enhance the distribution of chemotherapy in different tumor types. However, how light dose affects drug distribution and tumor response is unknown. Here we determined the effect of L-PDT fluence on vascular transport in human mesothelioma xenografts. The best L-PDT conditions regarding drug transport were then combined with Lipoplatin(®) to determine tumor response. in vivo. Lasers Surg. Med. 47:323-330, 2015. © 2015 Wiley Periodicals, Inc. METHODS: Nude mice bearing dorsal skinfold chambers were implanted with H-Meso1 cells. Tumors were treated by Visudyne(®) -mediated photodynamic therapy with 100 mW/cm(2) fluence rate and a variable fluence (5, 10, 30, and 50 J/cm(2) ). FITC-Dextran (FITC-D) distribution was assessed in real time in tumor and normal tissues. Tumor response was then determined with best L-PDT conditions combined to Lipoplatin(®) and compared to controls in luciferase expressing H-Meso1 tumors by size and whole body bioluminescence assessment (n = 7/group). RESULTS: Tumor uptake of FITC-D following L-PDT was significantly enhanced by 10-fold in the 10 J/cm(2) but not in the 5, 30, and 50 J/cm(2) groups compared to controls. Normal surrounding tissue uptake of FITC-D following L-PDT was significantly enhanced in the 30 J/cm(2) and 50 J/cm(2) groups compared to controls. Altogether, the FITC-D tumor to normal tissue ratio was significantly higher in the 10 J/cm(2) group compared others. Tumor growth was significantly delayed in animals treated by 10 J/cm2-L-PDT combined to Lipoplatin(®) compared to controls. CONCLUSIONS: Fluence of L-PDT is critical for the optimal distribution and effect of subsequently administered chemotherapy. These findings have an importance for the clinical translation of the vascular L-PDT concept in the clinics. Lasers Surg. Med. 47:323-330, 2015.
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INTRODUCTION: Perfusion-CT (PCT) processing involves deconvolution, a mathematical operation that computes the perfusion parameters from the PCT time density curves and an arterial curve. Delay-sensitive deconvolution does not correct for arrival delay of contrast, whereas delay-insensitive deconvolution does. The goal of this study was to compare delay-sensitive and delay-insensitive deconvolution PCT in terms of delineation of the ischemic core and penumbra. METHODS: We retrospectively identified 100 patients with acute ischemic stroke who underwent admission PCT and CT angiography (CTA), a follow-up vascular study to determine recanalization status, and a follow-up noncontrast head CT (NCT) or MRI to calculate final infarct volume. PCT datasets were processed twice, once using delay-sensitive deconvolution and once using delay-insensitive deconvolution. Regions of interest (ROIs) were drawn, and cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT) in these ROIs were recorded and compared. Volume and geographic distribution of ischemic core and penumbra using both deconvolution methods were also recorded and compared. RESULTS: MTT and CBF values are affected by the deconvolution method used (p < 0.05), while CBV values remain unchanged. Optimal thresholds to delineate ischemic core and penumbra are different for delay-sensitive (145 % MTT, CBV 2 ml × 100 g(-1) × min(-1)) and delay-insensitive deconvolution (135 % MTT, CBV 2 ml × 100 g(-1) × min(-1) for delay-insensitive deconvolution). When applying these different thresholds, however, the predicted ischemic core (p = 0.366) and penumbra (p = 0.405) were similar with both methods. CONCLUSION: Both delay-sensitive and delay-insensitive deconvolution methods are appropriate for PCT processing in acute ischemic stroke patients. The predicted ischemic core and penumbra are similar with both methods when using different sets of thresholds, specific for each deconvolution method.
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PURPOSE OF REVIEW: Current computational neuroanatomy based on MRI focuses on morphological measures of the brain. We present recent methodological developments in quantitative MRI (qMRI) that provide standardized measures of the brain, which go beyond morphology. We show how biophysical modelling of qMRI data can provide quantitative histological measures of brain tissue, leading to the emerging field of in-vivo histology using MRI (hMRI). RECENT FINDINGS: qMRI has greatly improved the sensitivity and specificity of computational neuroanatomy studies. qMRI metrics can also be used as direct indicators of the mechanisms driving observed morphological findings. For hMRI, biophysical models of the MRI signal are being developed to directly access histological information such as cortical myelination, axonal diameters or axonal g-ratio in white matter. Emerging results indicate promising prospects for the combined study of brain microstructure and function. SUMMARY: Non-invasive brain tissue characterization using qMRI or hMRI has significant implications for both research and clinics. Both approaches improve comparability across sites and time points, facilitating multicentre/longitudinal studies and standardized diagnostics. hMRI is expected to shed new light on the relationship between brain microstructure, function and behaviour, both in health and disease, and become an indispensable addition to computational neuroanatomy.
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Some recent studies have characterized the stability of blood variables commonly measured for the Athlete Biological Passport. The aim of this study was to characterize the impact of different shipments conditions and the quality of the results returned by the haematological analyzer. Twenty-two healthy male subjects provided five EDTA tubes each. Four shipment conditions (24, 36, 48, 72 h) under refrigerated conditions were tested and compared to a set of samples left in the laboratory also under refrigerated conditions (group control). All measurements were conducted using two Sysmex XT-2000i analyzers. Haemoglobin concentration, reticulocytes percentage, and OFF-score numerical data were the same for samples analyzed just after collection and after a shipment under refrigerated conditions up to 72 h. Detailed information reported especially by the differential (DIFF) channel scatterplot of the Sysmex XT-2000i indicated that there were signs of blood deterioration, but were not of relevance for the variables used in the Athlete Biological Passport. As long as the cold chain is guaranteed, the time delay between the collection and the analyses of blood variables can be extended. Copyright© 2015 John Wiley & Sons, Ltd.
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BACKGROUND: Despite a low positive predictive value, diagnostic tests such as complete blood count (CBC) and C-reactive protein (CRP) are commonly used to evaluate whether infants with risk factors for early-onset neonatal sepsis (EOS) should be treated with antibiotics. STUDY DESIGN: We investigated the impact of imple- menting a protocol aiming at reducing the number of dia- gnostic tests in infants with risk factors for EOS in order to compare the diagnostic performance of repeated clinical examination with CBC and CRP measurement. The primary outcome was the time between birth and the first dose of antibiotics in infants treated for suspected EOS. RESULTS: Among the 11,503 infants born at 35 weeks during the study period, 222 were treated with antibiotics for suspected EOS. The proportion of infants receiving an- tibiotics for suspected EOS was 2.1% and 1.7% before and after the change of protocol (p = 0.09). Reduction of dia- gnostic tests was associated with earlier antibiotic treat- ment in infants treated for suspected EOS (hazard ratio 1.58; 95% confidence interval [CI] 1.20-2.07; p <0.001), and in infants with neonatal infection (hazard ratio 2.20; 95% CI 1.19-4.06; p = 0.01). There was no difference in the duration of hospital stay nor in the proportion of infants requiring respiratory or cardiovascular support before and after the change of protocol. CONCLUSION: Reduction of diagnostic tests such as CBC and CRP does not delay initiation of antibiotic treat- ment in infants with suspected EOS. The importance of clinical examination in infants with risk factors for EOS should be emphasised.
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The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.