36 resultados para Cross-validation
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OBJECTIVES Molecular subclassification of non small-cell lung cancer (NSCLC) is essential to improve clinical outcome. This study assessed the prognostic and predictive value of circulating micro-RNA (miRNA) in patients with non-squamous NSCLC enrolled in the phase II SAKK (Swiss Group for Clinical Cancer Research) trial 19/05, receiving uniform treatment with first-line bevacizumab and erlotinib followed by platinum-based chemotherapy at progression. MATERIALS AND METHODS Fifty patients with baseline and 24 h blood samples were included from SAKK 19/05. The primary study endpoint was to identify prognostic (overall survival, OS) miRNA's. Patient samples were analyzed with Agilent human miRNA 8x60K microarrays, each glass slide formatted with eight high-definition 60K arrays. Each array contained 40 probes targeting each of the 1347 miRNA. Data preprocessing included quantile normalization using robust multi-array average (RMA) algorithm. Prognostic and predictive miRNA expression profiles were identified by Spearman's rank correlation test (percentage tumor shrinkage) or log-rank testing (for time-to-event endpoints). RESULTS Data preprocessing kept 49 patients and 424 miRNA for further analysis. Ten miRNA's were significantly associated with OS, with hsa-miR-29a being the strongest prognostic marker (HR=6.44, 95%-CI 2.39-17.33). Patients with high has-miR-29a expression had a significantly lower survival at 10 months compared to patients with a low expression (54% versus 83%). Six out of the 10 miRNA's (hsa-miRN-29a, hsa-miR-542-5p, hsa-miR-502-3p, hsa-miR-376a, hsa-miR-500a, hsa-miR-424) were insensitive to perturbations according to jackknife cross-validation on their HR for OS. The respective principal component analysis (PCA) defined a meta-miRNA signature including the same 6 miRNA's, resulting in a HR of 0.66 (95%-CI 0.53-0.82). CONCLUSION Cell-free circulating miRNA-profiling successfully identified a highly prognostic 6-gene signature in patients with advanced non-squamous NSCLC. Circulating miRNA profiling should further be validated in external cohorts for the selection and monitoring of systemic treatment in patients with advanced NSCLC.
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Purpose: Proper delineation of ocular anatomy in 3D imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic Resonance Imaging (MRI) is nowadays utilized in clinical practice for the diagnosis confirmation and treatment planning of retinoblastoma in infants, where it serves as a source of information, complementary to the Fundus or Ultrasound imaging. Here we present a framework to fully automatically segment the eye anatomy in the MRI based on 3D Active Shape Models (ASM), we validate the results and present a proof of concept to automatically segment pathological eyes. Material and Methods: Manual and automatic segmentation were performed on 24 images of healthy children eyes (3.29±2.15 years). Imaging was performed using a 3T MRI scanner. The ASM comprises the lens, the vitreous humor, the sclera and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens and the optic nerve, then aligning the model and fitting it to the patient. We validated our segmentation method using a leave-one-out cross validation. The segmentation results were evaluated by measuring the overlap using the Dice Similarity Coefficient (DSC) and the mean distance error. Results: We obtained a DSC of 94.90±2.12% for the sclera and the cornea, 94.72±1.89% for the vitreous humor and 85.16±4.91% for the lens. The mean distance error was 0.26±0.09mm. The entire process took 14s on average per eye. Conclusion: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor and the lens using MRI. We additionally present a proof of concept for fully automatically segmenting pathological eyes. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor.
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INTRODUCTION Anatomic imaging alone is often inadequate for tuning systemic treatment for individual tumor response. Optically based techniques could potentially contribute to fast and objective response monitoring in personalized cancer therapy. In the present study, we evaluated the feasibility of dual-modality diffuse reflectance spectroscopy-autofluorescence spectroscopy (DRS-AFS) to monitor the effects of systemic treatment in a mouse model for hereditary breast cancer. METHODS Brca1(-/-); p53(-/-) mammary tumors were grown in 36 mice, half of which were treated with a single dose of cisplatin. Changes in the tumor physiology and morphology were measured for a period of 1 week using dual-modality DRS-AFS. Liver and muscle tissues were also measured to distinguish tumor-specific alterations from systemic changes. Model-based analyses were used to derive different optical parameters like the scattering and absorption coefficients, as well as sources of intrinsic fluorescence. Histopathologic analysis was performed for cross-validation with trends in optically based parameters. RESULTS Treated tumors showed a significant decrease in Mie-scattering slope and Mie-to-total scattering fraction and an increase in both fat volume fraction and tissue oxygenation after 2 days of follow-up. Additionally, significant tumor-specific changes in the fluorescence spectra were seen. These longitudinal trends were consistent with changes observed in the histopathologic analysis, such as vital tumor content and formation of fibrosis. CONCLUSIONS This study demonstrates that dual-modality DRS-AFS provides quantitative functional information that corresponds well with the degree of pathologic response. DRS-AFS, in conjunction with other imaging modalities, could be used to optimize systemic cancer treatment on the basis of early individual tumor response.
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Extraction of surface models of a hip joint from CT data is a pre-requisite step for computer assisted diagnosis and planning (CADP) of periacetabular osteotomy (PAO). Most of existing CADP systems are based on manual segmentation, which is time-consuming and hard to achieve reproducible results. In this paper, we present a Fully Automatic CT Segmentation (FACTS) approach to simultaneously extract both pelvic and femoral models. Our approach works by combining fast random forest (RF) regression based landmark detection, multi-atlas based segmentation, with articulated statistical shape model (aSSM) based fitting. The two fundamental contributions of our approach are: (1) an improved fast Gaussian transform (IFGT) is used within the RF regression framework for a fast and accurate landmark detection, which then allows for a fully automatic initialization of the multi-atlas based segmentation; and (2) aSSM based fitting is used to preserve hip joint structure and to avoid penetration between the pelvic and femoral models. Taking manual segmentation as the ground truth, we evaluated the present approach on 30 hip CT images (60 hips) with a 6-fold cross validation. When the present approach was compared to manual segmentation, a mean segmentation accuracy of 0.40, 0.36, and 0.36 mm was found for the pelvis, the left proximal femur, and the right proximal femur, respectively. When the models derived from both segmentations were used to compute the PAO diagnosis parameters, a difference of 2.0 ± 1.5°, 2.1 ± 1.6°, and 3.5 ± 2.3% were found for anteversion, inclination, and acetabular coverage, respectively. The achieved accuracy is regarded as clinically accurate enough for our target applications.
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OBJECTIVE Our aim was to assess the diagnostic and predictive value of several quantitative EEG (qEEG) analysis methods in comatose patients. METHODS In 79 patients, coupling between EEG signals on the left-right (inter-hemispheric) axis and on the anterior-posterior (intra-hemispheric) axis was measured with four synchronization measures: relative delta power asymmetry, cross-correlation, symbolic mutual information and transfer entropy directionality. Results were compared with etiology of coma and clinical outcome. Using cross-validation, the predictive value of measure combinations was assessed with a Bayes classifier with mixture of Gaussians. RESULTS Five of eight measures showed a statistically significant difference between patients grouped according to outcome; one measure revealed differences in patients grouped according to the etiology. Interestingly, a high level of synchrony between the left and right hemisphere was associated with mortality on intensive care unit, whereas higher synchrony between anterior and posterior brain regions was associated with survival. The combination with the best predictive value reached an area-under the curve of 0.875 (for patients with post anoxic encephalopathy: 0.946). CONCLUSIONS EEG synchronization measures can contribute to clinical assessment, and provide new approaches for understanding the pathophysiology of coma. SIGNIFICANCE Prognostication in coma remains a challenging task. qEEG could improve current multi-modal approaches.
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Index tracking has become one of the most common strategies in asset management. The index-tracking problem consists of constructing a portfolio that replicates the future performance of an index by including only a subset of the index constituents in the portfolio. Finding the most representative subset is challenging when the number of stocks in the index is large. We introduce a new three-stage approach that at first identifies promising subsets by employing data-mining techniques, then determines the stock weights in the subsets using mixed-binary linear programming, and finally evaluates the subsets based on cross validation. The best subset is returned as the tracking portfolio. Our approach outperforms state-of-the-art methods in terms of out-of-sample performance and running times.
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This paper addresses the issue of fully automatic segmentation of a hip CT image with the goal to preserve the joint structure for clinical applications in hip disease diagnosis and treatment. For this purpose, we propose a Multi-Atlas Segmentation Constrained Graph (MASCG) method. The MASCG method uses multi-atlas based mesh fusion results to initialize a bone sheetness based multi-label graph cut for an accurate hip CT segmentation which has the inherent advantage of automatic separation of the pelvic region from the bilateral proximal femoral regions. We then introduce a graph cut constrained graph search algorithm to further improve the segmentation accuracy around the bilateral hip joint regions. Taking manual segmentation as the ground truth, we evaluated the present approach on 30 hip CT images (60 hips) with a 15-fold cross validation. When the present approach was compared to manual segmentation, an average surface distance error of 0.30 mm, 0.29 mm, and 0.30 mm was found for the pelvis, the left proximal femur, and the right proximal femur, respectively. A further look at the bilateral hip joint regions demonstrated an average surface distance error of 0.16 mm, 0.21 mm and 0.20 mm for the acetabulum, the left femoral head, and the right femoral head, respectively.
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Surface sediments from 68 small lakes in the Alps and 9 well-dated sediment core samples that cover a gradient of total phosphorus (TP) concentrations of 6 to 520 μg TP l-1 were studied for diatom, chrysophyte cyst, cladocera, and chironomid assemblages. Inference models for mean circulation log10 TP were developed for diatoms, chironomids, and benthic cladocera using weighted-averaging partial least squares. After screening for outliers, the final transfer functions have coefficients of determination (r2, as assessed by cross-validation, of 0.79 (diatoms), 0.68 (chironomids), and 0.49 (benthic cladocera). Planktonic cladocera and chrysophytes show very weak relationships to TP and no TP inference models were developed for these biota. Diatoms showed the best relationship with TP, whereas the other biota all have large secondary gradients, suggesting that variables other than TP have a strong influence on their composition and abundance. Comparison with other diatom – TP inference models shows that our model has high predictive power and a low root mean squared error of prediction, as assessed by cross-validation.
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Individual analysis of functional Magnetic Resonance Imaging (fMRI) scans requires user-adjustment of the statistical threshold in order to maximize true functional activity and eliminate false positives. In this study, we propose a novel technique that uses radiomic texture analysis (TA) features associated with heterogeneity to predict areas of true functional activity. Scans of 15 right-handed healthy volunteers were analyzed using SPM8. The resulting functional maps were thresholded to optimize visualization of language areas, resulting in 116 regions of interests (ROIs). A board-certified neuroradiologist classified different ROIs into Expected (E) and Non-Expected (NE) based on their anatomical locations. TA was performed using the mean Echo-Planner Imaging (EPI) volume, and 20 rotation-invariant texture features were obtained for each ROI. Using forward stepwise logistic regression, we built a predictive model that discriminated between E and NE areas of functional activity, with a cross-validation AUC and success rate of 79.84% and 80.19% respectively (specificity/sensitivity of 78.34%/82.61%). This study found that radiomic TA of fMRI scans may allow for determination of areas of true functional activity, and thus eliminate clinician bias.
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High-resolution ultrasound is becoming increasingly important in the diagnosis of carpal tunnel syndrome (CTS). Most studies define cut-off values of the cross-sectional area (CSA) of the median nerve in different locations. The individual range of nerve swelling, the size of the nerve, and its CSA are not addressed. The aim of the study is to define the intra- and interobserver reliability of diagnostic ultrasound using two different cross-sectional areas of the median nerve at the carpal tunnel in predefined locations.
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The Advanced Very High Resolution Radiometer (AVHRR) carried on board the National Oceanic and Atmospheric Administration (NOAA) and the Meteorological Operational Satellite (MetOp) polar orbiting satellites is the only instrument offering more than 25 years of satellite data to analyse aerosols on a daily basis. The present study assessed a modified AVHRR aerosol optical depth τa retrieval over land for Europe. The algorithm might also be applied to other parts of the world with similar surface characteristics like Europe, only the aerosol properties would have to be adapted to a new region. The initial approach used a relationship between Sun photometer measurements from the Aerosol Robotic Network (AERONET) and the satellite data to post-process the retrieved τa. Herein a quasi-stand-alone procedure, which is more suitable for the pre-AERONET era, is presented. In addition, the estimation of surface reflectance, the aerosol model, and other processing steps have been adapted. The method's cross-platform applicability was tested by validating τa from NOAA-17 and NOAA-18 AVHRR at 15 AERONET sites in Central Europe (40.5° N–50° N, 0° E–17° E) from August 2005 to December 2007. Furthermore, the accuracy of the AVHRR retrieval was related to products from two newer instruments, the Medium Resolution Imaging Spectrometer (MERIS) on board the Environmental Satellite (ENVISAT) and the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Aqua/Terra. Considering the linear correlation coefficient R, the AVHRR results were similar to those of MERIS with even lower root mean square error RMSE. Not surprisingly, MODIS, with its high spectral coverage, gave the highest R and lowest RMSE. Regarding monthly averaged τa, the results were ambiguous. Focusing on small-scale structures, R was reduced for all sensors, whereas the RMSE solely for MERIS substantially increased. Regarding larger areas like Central Europe, the error statistics were similar to the individual match-ups. This was mainly explained with sampling issues. With the successful validation of AVHRR we are now able to concentrate on our large data archive dating back to 1985. This is a unique opportunity for both climate and air pollution studies over land surfaces.
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Objectives To describe, using routine data in selected countries, chlamydia control activities and rates of chlamydia infection, pelvic inflammatory disease (PID), ectopic pregnancy and infertility and to compare trends in chlamydia positivity with rates of PID and ectopic pregnancy. Methods Cross-national comparison including national data from Australia, Denmark, the Netherlands, New Zealand, Sweden and Switzerland. Routine data sources about chlamydia diagnosis and testing and International Classification of Disease-10 coded diagnoses of PID, ectopic pregnancy and infertility in women aged 15–39 years from 1999 to 2008 were described. Trends over time and relevant associations were examined using Poisson regression. Results Opportunistic chlamydia testing was recommended in all countries except Switzerland, but target groups differed. Rates of chlamydia testing were highest in New Zealand. Chlamydia positivity was similar in all countries with available data (Denmark, New Zealand and Sweden) and increased over time. Increasing chlamydia positivity rates were associated with decreasing PID rates in Denmark and Sweden and with decreasing ectopic pregnancy rates in Denmark, New Zealand and Sweden. Ectopic pregnancy rates appeared to increase over time in 15–19-year-olds in several countries. Trends in infertility diagnoses were very variable. Conclusions The intensity of recommendations about chlamydia control varied between countries but was not consistently related to levels of chlamydia diagnosis or testing. Relationships between levels of chlamydia infection and complication rates between or within countries over time were not straightforward. Development and validation of indicators of chlamydia-related morbidity that can be compared across countries and over time should be pursued.
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The aim of this in vitro study was to assess the agreement among four techniques used as gold standard for the validation of methods for occlusal caries detection. Sixty-five human permanent molars were selected and one site in each occlusal surface was chosen as the test site. The teeth were cut and prepared according to each technique: stereomicroscopy without coloring (1), dye enhancement with rhodamine B (2) and fuchsine/acetic light green (3), and semi-quantitative microradiography (4). Digital photographs from each prepared tooth were assessed by three examiners for caries extension. Weighted kappa, as well as Friedman's test with multiple comparisons, was performed to compare all techniques and verify statistical significant differences. Results: kappa values varied from 0.62 to 0.78, the latter being found by both dye enhancement methods. Friedman's test showed statistical significant difference (P < 0.001) and multiple comparison identified these differences among all techniques, except between both dye enhancement methods (rhodamine B and fuchsine/acetic light green). Cross-tabulation showed that the stereomicroscopy overscored the lesions. Both dye enhancement methods showed a good agreement, while stereomicroscopy overscored the lesions. Furthermore, the outcome of caries diagnostic tests may be influenced by the validation method applied. Dye enhancement methods seem to be reliable as gold standard methods.
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Context-Daytime sleepiness in kidney transplant recipients has emerged as a potential predictor of impaired adherence to the immunosuppressive medication regimen. Thus there is a need to assess daytime sleepiness in clinical practice and transplant registries.Objective-To evaluate the validity of a single-item measure of daytime sleepiness integrated in the Swiss Transplant Cohort Study (STCS), using the American Educational Research Association framework.Methods-Using a cross-sectional design, we enrolled a convenience sample of 926 home-dwelling kidney transplant recipients (median age, 59.69 years; 25%-75% quartile [Q25-Q75], 50.27-59.69), 63% men; median time since transplant 9.42 years (Q25-Q75, 4.93-15.85). Daytime sleepiness was assessed by using a single item from the STCS and the 8 items of the validated Epworth Sleepiness Scale. Receiver operating characteristic curve analysis was used to determine the cutoff for the STCS daytime sleepiness item against the Epworth Sleepiness Scale score.Results-Based on the receiver operating characteristic curve analysis, a score greater than 4 on the STCS daytime sleepiness item is recommended to detect daytime sleepiness. Content validity was high as all expert reviews were unanimous. Concurrent validity was moderate (Spearman ϱ, 0.531; P< .001) and convergent validity with depression and poor sleep quality although low, was significant (ϱ, 0.235; P<.001 and ϱ, 0.318, P=.002, respectively). For the group difference validity: kidney transplant recipients with moderate, severe, and extremely severe depressive symptom scores had 3.4, 4.3, and 5.9 times higher odds of having daytime sleepiness, respectively, as compared with recipients without depressive symptoms.Conclusion-The accumulated evidence provided evidence for the validity of the STCS daytime sleepiness item as a simple screening scale for daytime sleepiness.
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MIPAS observations of temperature, water vapor, and ozone in October 2009 as derived with the scientific level-2 processor run by Karlsruhe Institute of Technology (KIT), Institute for Meteorology and Climate Research (IMK) and CSIC, Instituto de Astrofísica de Andalucía (IAA) and retrieved from version 4.67 level-1b data have been compared to co-located field campaign observations obtained during the MOHAVE-2009 campaign at the Table Mountain Facility near Pasadena, California in October 2009. The MIPAS measurements were validated regarding any potential biases of the profiles, and with respect to their precision estimates. The MOHAVE-2009 measurement campaign provided measurements of atmospheric profiles of temperature, water vapor/relative humidity, and ozone from the ground to the mesosphere by a suite of instruments including radiosondes, ozonesondes, frost point hygrometers, lidars, microwave radiometers and Fourier transform infra-red (FTIR) spectrometers. For MIPAS temperatures (version V4O_T_204), no significant bias was detected in the middle stratosphere; between 22 km and the tropopause MIPAS temperatures were found to be biased low by up to 2 K, while below the tropopause, they were found to be too high by the same amount. These findings confirm earlier comparisons of MIPAS temperatures to ECMWF data which revealed similar differences. Above 12 km up to 45 km, MIPAS water vapor (version V4O_H2O_203) is well within 10% of the data of all correlative instruments. The well-known dry bias of MIPAS water vapor above 50 km due to neglect of non-LTE effects in the current retrievals has been confirmed. Some instruments indicate that MIPAS water vapor might be biased high by 20 to 40% around 10 km (or 5 km below the tropopause), but a consistent picture from all comparisons could not be derived. MIPAS ozone (version V4O_O3_202) has a high bias of up to +0.9 ppmv around 37 km which is due to a non-identified continuum like radiance contribution. No further significant biases have been detected. Cross-comparison to co-located observations of other satellite instruments (Aura/MLS, ACE-FTS, AIRS) is provided as well.