Lower Absolute Difference Research Articles

Equity trends for the UHC service coverage sub-index for reproductive, maternal, newborn and child health in Pakistan: evidence from demographic health surveys

BackgroundPakistan, the world's sixth most populous country and the second largest in South Asia, is facing challenges related to reproductive, maternal, newborn and child health (RMNCH) that are exacerbated by various inequities. RMNCH coverage indicators such as antenatal care (ANC) and deliveries at health facilities have been improving over time, and the maternal mortality ratio (MMR) is gradually declining but not at the desired rates. Analysing and documenting inequities with reference to key characteristics are useful to unmask the disparities and to amicably implement targeted equity-oriented interventions.MethodsPakistan Demographic Health Survey (PDHS) based UHC service coverage tracer indicators were derived for the RMNCH domain at the national and subnational levels for the two rounds of the PDHS in 2012 and 2017. These derivations were subgrouped into wealth quintiles, place of residence, education and mothers’ age. Dumbbell charts were created to show the trends and quintile-specific coverage. The UHC service coverage sub-index for RMNCH was constructed to measure the absolute and relative parity indices, such as high to low absolute difference and high to low ratios, to quantify health inequities. The population attributable risk was computed to determine the overall population health improvement that is possible if all regions have the same level of health services as the reference point (national level) across the equity domains.ResultsThe results indicate an overall improvement in coverage across all indicators over time, but with a higher concentration of data points towards higher coverage among the wealthiest groups, although the poorest quintile continues to have low coverage in all regions. The UHC service coverage sub-index on RMNCH shows that Pakistan has improved from 45 to 63 overall, while Punjab improved from 50 to 59 and Sindh from 43 to 55. The highest improvement is evident in Khyber Pakhtunkhwa (KP) province, which has increased from 31 in 2012 to 51 in 2017. All regions made slow progress in narrowing the gap between the poorest and wealthiest groups, with particularly noteworthy improvements in KP and Sindh, as indicated by the parity ratio. The RMNCH service coverage sub-index gap was the greatest among women aged 15–19 years, those who belonged to the poorest wealth quintile, had no education, and resided in rural areas.ConclusionsAnalysing existing data sources from an equity lens supports evidence-based policies, programs and practices with a focus on disadvantaged subgroups.

A pH-responsive sensor based on intramolecular internal standard for reproducible detection of strong acids and bases via 19F NMR spectroscopy

Numerous methods, including pH meters and optical sensors, have been developed for the detection of pH, which is an important indicator in various fields. However, those methods are susceptible to errors in strongly acidic and basic ranges and inaccurate pH measurement due to sample turbidity, hindering their application such as photographic industries and wastewater treatment facilities. Eco-friendly and non-invasive 19F NMR spectroscopy is a promising technique for measurement of strong acids and bases owing to its high sensitivity and little interference; nevertheless, inconsistencies in reproducibility impede its widespread adoption. Herein, we developed a19F NMR-based pH sensor by introducing an intramolecular internal standard strategy into a pH-responsive fluorinated material. Based on the acceptable deviation (ΔδF = 17−19 ppb) in the evaluation of the internal standard signal, this pH-sensing platform enabled reproducible pH measurements in strongly acidic and basic environments. Moreover, its 19F NMR response showed reversibility and high stability to potential interfering factors, and the low absolute difference (0.026−0.086 in pH) for real samples such as diet Coke suggests its potential suitability for various acidic beverages.

The ENmix DNA methylation analysis pipeline for Illumina BeadChip and comparisons with seven other preprocessing pipelines

BackgroundIllumina DNA methylation arrays are high-throughput platforms for cost-effective genome-wide profiling of individual CpGs. Experimental and technical factors introduce appreciable measurement variation, some of which can be mitigated by careful “preprocessing” of raw data.MethodsHere we describe the ENmix preprocessing pipeline and compare it to a set of seven published alternative pipelines (ChAMP, Illumina, SWAN, Funnorm, Noob, wateRmelon, and RnBeads). We use two large sets of duplicate sample measurements with 450 K and EPIC arrays, along with mixtures of isogenic methylated and unmethylated cell line DNA to compare raw data and that preprocessed via different pipelines.ResultsOur evaluations show that the ENmix pipeline performs the best with significantly higher correlation and lower absolute difference between duplicate pairs, higher intraclass correlation coefficients (ICC) and smaller deviations from expected methylation level in mixture experiments. In addition to the pipeline function, ENmix software provides an integrated set of functions for reading in raw data files from mouse and human arrays, quality control, data preprocessing, visualization, detection of differentially methylated regions (DMRs), estimation of cell type proportions, and calculation of methylation age clocks. ENmix is computationally efficient, flexible and allows parallel computing. To facilitate further evaluations, we make all datasets and evaluation code publicly available.ConclusionCareful selection of robust data preprocessing methods is critical for DNA methylation array studies. ENmix outperformed other pipelines in our evaluations to minimize experimental variation and to improve data quality and study power.

The effect of patient positioning on the accuracy and reliability of assessment of knee range of motion over a telemedicine platform

Introduction Diagnostic accuracy is one of the key considerations of telemedicine usage in orthopedic surgery. The aim of this study was to determine the optimal patient positioning to achieve accurate and reliable visual estimation of the knee joint range of motion over a digital platform for telemedicine. Methods A single volunteer was recruited to perform a total of 120 discrete and random knee range of motion angles in three patient positions: sitting, standing and supine. The patient image was broadcast over a digital platform to six raters. The raters recorded their visual estimation of each discrete knee flexion angle independently. After each discrete knee flexion angle, a physical goniometer was used to obtain the actual flexion angle of the knee. Results A total of 120 discrete measurements (40 measurements in the sitting, standing, and supine positions each) were recorded by each of the six raters. The supine position resulted in the highest intraclass correlation of 0.97 (95% confidence interval: 0.98, 0.99). All three patient positions achieved low absolute difference between the goniometer and the raters with 5.6 degrees (95% limits of agreement: −21.0, 9.8) in sitting, 2.7 degrees (95% limits of agreement: −10.1, 15.4), and 1.2 degrees (95% limits of agreement: −9.8, 12.3) in the supine position. The supine position had the highest accuracy and reliability. Discussion Visual estimation of the knee joint range of motion over telemedicine is clinically accurate and reliable. Patients should be assessed in a supine position to obtain the highest accuracy and reliability for visual estimation of the knee joint range of motion during telemedicine.

Evaluation of a Method for Calculating the Height of the Stable Boundary Layer Based on Wind Profile Lidar and Turbulent Fluxes

The height of the stable boundary layer (SBL), known as the nocturnal boundary layer height, is controlled by numerous factors of different natures. The SBL height defines the state of atmospheric turbulence and describes the diffusion capacity of the atmosphere. Therefore, it is unsurprising that many alternative (sometimes contradictory) formulations for the SBL height have been proposed to date, and no consensus has been achieved. In our study, we propose an iterative algorithm to determine the SBL height h based on the flux–profile relationship using wind profiles and turbulent fluxes. This iterative algorithm can obtain temporally continuous, accurate estimates of h and is widely applicable. The predicted h presents relatively good agreement with four observation-derived SBL heights, hJ, h1, hi, and hθ (hJ: maximum wind speed height, h1: zero wind shear height, hi: temperature inversion height, and hθ: height at which 0.8 times the inversion strength appears for the first time), especially with hθ, which shows the best fit. In addition, h exhibits a low absolute difference and relative difference with hJ, which presents the second-best result. The agreement with hi and h1 may be satisfactory, but small differences are observed, and the one standard deviation of the mean relative difference is large. In addition, the predicted h is compared with other SBL height estimation methods, including diagnostic, λ1, λ2 and λ3 (three typical dimensional scale height parameters) and prognostic equation-based methods, λ(h) (an equation for the growth of h developed). The diagnostic formulas are found to be appropriate, especially under extremely stable conditions. Additionally, the equation of λ3 presents the best result of all the dimensional scale height parameters. However, the prognostic equation λ(h) in our study is very unsatisfactory.

Improved cortical surface reconstruction using sub-millimeter resolution MPRAGE by image denoising

Automatic cerebral cortical surface reconstruction is a useful tool for cortical anatomy quantification, analysis and visualization. Recently, the Human Connectome Project and several studies have shown the advantages of using T1-weighted magnetic resonance (MR) images with sub-millimeter isotropic spatial resolution instead of the standard 1-mm isotropic resolution for improved accuracy of cortical surface positioning and thickness estimation. Nonetheless, sub-millimeter resolution images are noisy by nature and require averaging multiple repetitions to increase the signal-to-noise ratio for precisely delineating the cortical boundary. The prolonged acquisition time and potential motion artifacts pose significant barriers to the wide adoption of cortical surface reconstruction at sub-millimeter resolution for a broad range of neuroscientific and clinical applications. We address this challenge by evaluating the cortical surface reconstruction resulting from denoised single-repetition sub-millimeter T1-weighted images. We systematically characterized the effects of image denoising on empirical data acquired at 0.6 mm isotropic resolution using three classical denoising methods, including denoising convolutional neural network (DnCNN), block-matching and 4-dimensional filtering (BM4D) and adaptive optimized non-local means (AONLM). The denoised single-repetition images were found to be highly similar to 6-repetition averaged images, with a low whole-brain averaged mean absolute difference of ~0.016, high whole-brain averaged peak signal-to-noise ratio of ~33.5 dB and structural similarity index of ~0.92, and minimal gray matter–white matter contrast loss (2% to 9%). The whole-brain mean absolute discrepancies in gray matter–white matter surface placement, gray matter–cerebrospinal fluid surface placement and cortical thickness estimation were lower than 165 μm, 155 μm and 145 μm—sufficiently accurate for most applications. These discrepancies were approximately one third to half of those from 1-mm isotropic resolution data. The denoising performance was equivalent to averaging ~2.5 repetitions of the data in terms of image similarity, and 1.6–2.2 repetitions in terms of the cortical surface placement accuracy. The scan-rescan variability of the cortical surface positioning and thickness estimation was lower than 170 μm. Our unique dataset and systematic characterization support the use of denoising methods for improved cortical surface reconstruction at sub-millimeter resolution.

Piezoelectric Photoacoustic System for Fluid Flow Monitoring

The aim of this study is to investigate the feasibility of using a laboratory assembled piezoelectric based photoacoustic (PA) system for noncontact monitoring fluid flow. This is to overcome the drawbacks of some existing fluid flow detection systems, which include expensive equipment and their maintenance cost, limited sensitivity and specificity in detecting signals from restricted regions or at low flow velocity. The produced PA signal waves detected by a piezoelectric transducer used in this study was processed to determine the required phase value (Ф), which value was found to correlate linearly with fluid flow status. The fluid pressure difference of 1.16 pascals (Pa) and 11.90 Pa applied to the developed mock circulatory system was observed to produce changes in phase value with mean ± standard deviation (SD) ΔФ of 0.79 ± 0.07 rad and 2.17 ± 0.07 rad, respectively, suggesting a linear response of the developed system with changes in circulation system. This trend was supported with the relatively low absolute difference of 0.07 ± 0.01 rad in the predicted values as compared to that of the ground truth. This work concluded that the capabilities and simplicity of the proposed PA system renders it feasible for cost effective, non-destructive assessment of fluid flow in future studies.

Cross-cultural adaption and validation of the German version of the Mini-BESTest in individuals after stroke: an observational study

BackgroundPostural control is a very important function in everyday life. However, assessing postural control with commonly used measurement instruments (MIs) is limited due to deficits in their psychometric properties. The Mini-Balance Evaluation Systems Test (Mini-BESTest) is a comprehensive and multidimensional MI for assessing postural control in persons with limited balance function, such as individuals after stroke. Despite the increasing use of the Mini-BESTest worldwide, no German version is available.Research questionIs the German version of the Mini-BESTest (GVMBT) comprehensible and valid for measuring postural control in individuals after stroke?MethodsThe Mini-BESTest was translated and cross-culturally adapted, following established guidelines. It was pilot-tested with ten participants. This observational measurement and validation study was conducted at one point and included 50 participants with subacute and chronic stroke (mean age: 64.58 ± 13.34 years/ 34 men/ 16 women). Convergent validity was investigated using 1) the Berg Balance Scale (BBS) and 2) the Timed “Up & Go” (TUG). The MIs were evaluated for normal distribution with the calculation of skewness, kurtosis and Q-Q-Plots. Spearman correlation coefficients and Bland Altman analysis were used to examine the relationship between the MIs. The internal consistency was assessed using Cronbach’s alpha.ResultsComprehension of the GVMBT was confirmed. The GVMBT correlated significantly with the BBS (rs = 0.93) and the TUG (rs = − 0.85). Bland Altman analysis revealed low absolute differences. The GVMBT demonstrated no significant floor or ceiling effects and showed excellent internal consistency (Cronbach’s α = 0.90).SignificanceThe GVMBT has excellent validity and internal consistency. Due to this and its specific subcategories, the GVMBT is recommended for the use in research and clinical practice. Further psychometric properties should be evaluated.

Estimation of left ventricular stroke work based on a large cohort of healthy children

Left ventricular stroke work is an important prognostic marker to analyze cardiac function. Standard values for children are, however, missing. For clinicians, standards can help to improve the treatment decision of heart failures. For engineers, they can help to optimize medical devices.In this study, we estimated the left ventricular stroke work for children based on modeled pressure–volume loops. A lumped parameter model was fitted to clinical data of 340 healthy children. Reference curves for standard values were created over age, weight, and height. Left ventricular volume was measured with 3D echocardiography, while maximal ventricular pressure was approximated with a regression model from the literature.For validation of this method, we used 18 measurements acquired by a conductance catheter in 11 patients. The method demonstrated a low absolute mean difference of 0.033 J (SD: 0.031 J) for stroke work between measurement and estimation, while the percentage error was 21.66 %.According to the resulting reference curves, left ventricular stroke work of newborns has a median of 0.06 J and increases to 1.15 J at the age of 18 years. Stroke work increases over weight and height in a similar trend. The percentile curves depict the distribution.We demonstrate how reference curves can be used for quantification of differences and comparison in patients.

Using 3D digital image correlation in an identification of defects of trees subjected to bending

Abrupt changes of climate have intensified during the last few decades, bringing higher risks from tree failures by either uprooting or stem breakage. To eliminate the risks, many techniques of tree assessment are being used. In the presented work, an optical technique based on 3D Digital Image Correlation (3D-DIC) was investigated as one of the tools to be used in identification of tree defects. Within the work, two ash trees were examined by pulling tests coupling 3D-DIC and standard techniques. The trees were measured in five consecutive steps of artificially made defects of two kinds - root and stem damage. We hypothesized defects can be identified using full-field strains and displacements. Results indicated that 3D-DIC provides comparable strains as standard semi-destructive extensometers. Statistical tests (α = 0.05) showed the 3D-DIC technique method is capable of identifying changes of displacements and strains after creating artificial defects in trees. However, despite the statistical differences, the practical arboricultural considerations of findings are still limited due to low absolute differences. The study also suggests there might exist path-dependency of the defect creation order when evaluating stiffness/strains from extensometers of two different positions. This could have impact on a practical assessment of tree stability in the future, but it must be further tested on larger data sets due to the proof-of-concept character of this work. In general, 3D-DIC brings extensive improvement in data acquisition quality and quantity, especially from the perspective of natural variability and heterogeneity in trees and wood.

Monitoring subnational regional inequalities in health: measurement approaches and challenges.

BackgroundMonitoring inequalities based on subnational regions is a useful practice to unmask geographical differences in health, and deploy targeted, equity-oriented interventions. Our objective is to describe, compare and contrast current methods of measuring subnational regional inequality. We apply a selection of summary measures to empirical data from four low- or middle-income countries to highlight the characteristics and overall performance of the different measures.MethodsWe use data from Demographic and Health Surveys conducted in Bangladesh, Egypt, Ghana and Zimbabwe to calculate subnational regional inequality estimates for reproductive, maternal, newborn, and child health services generated from 11 summary measures: pairwise measures included high to low absolute difference, high to low relative difference, and high to low ratio; complex measures included population attributable risk, weighted variance, absolute weighted mean difference from overall mean, index of dissimilarity, Theil index, population attributable risk percentage, coefficient of variation, and relative weighted mean difference from overall mean. Four of these summary measures (high to low absolute difference, high to low ratio, absolute weighted mean difference from overall mean, and relative weighted mean difference from overall mean) were selected to compare their performance in measuring trend over time in inequality for one health indicator.ResultsOverall, the 11 different measures were more remarkable for their similarities than for their differences. Pairwise measures tended to support the same conclusions as complex summary measures–that is, by identifying same best and worst coverage indicators in each country and indicating similar time trends. Complex measures may be useful to illustrate more nuanced results in countries with a great number of subnational regions.ConclusionsWhen pairwise and complex measures lead to the same conclusions about the state of subnational regional inequality, pairwise measures may be sufficient for reporting inequality. In cases where complex measures are required, mean difference from mean measures can be easily communicated to non-technical audiences.

Cell Nuclei Classification and Immunohistochemical Scoring of Oral Cancer Tissue Images: Machine-learning Approach

In this paper, a novel cell nuclei feature extraction method has been proposed for immunohisto chemical (IHC) scoring of oral cancer tissue images. This method is based on maximal separation approaches, which was mainly used to find immuno-positive area of tissue sections. The performance of of the proposed method is evaluated using machine-learning classifiers such as support vector machine (SVM), k-nearest neighbor(k-NN), linear discriminant analysis(LDA), and naive bayes, and compared the results with other state-of-art methods including intensity and texture features. According to the performance outcomes, the best classification accuracy of 96.09% is achieved by the proposed method for LDA classifiers. However, an automatic IHC scoring technique has been implemented using highly correlated feature elements as input to the classifiers. The statistical analysis between manual and automatic techniques (LDA) revealed that the agreement between both techniques have high correlation coefficient (CC), low mean absolute difference(MAD), and within the range of 95% confidence interval(CI) of manual techniques (CC>0.966, MAD 0.649). Therefore, the proposed feature extraction method and automatic scoring technique have high potential in IHC stained tissue image analysis.

Towards reducing DBP formation potential of drinking water by favouring direct ozone over hydroxyl radical reactions during ozonation

When ozonation is employed in advanced water treatment plants to produce drinking water, dissolved organic matter reacts with ozone (O3) and/or hydroxyl radicals (OH) affecting disinfection byproduct (DBP) formation with subsequently used chlorine-based disinfectants. This study presents the effects of varying exposures of O3 and OH on DBP concentrations and their associated toxicity generated after subsequent chlorination. DBP formation potential tests and in vitro bioassays were conducted after batch ozonation experiments of coagulated surface water with and without addition of tertiary butanol (t-BuOH, 10 mM) and hydrogen peroxide (H2O2, 1 mg/mg O3), and at different pH (6–8) and transferred ozone doses (0–1 mg/mg TOC).Although ozonation led to a 24–37% decrease in formation of total trihalomethanes, haloacetic acids, haloacetonitriles, and trihaloacetamides, an increase in formation of total trihalonitromethanes, chloral hydrate, and haloketones was observed. This effect however was less pronounced for samples ozonated at conditions favoring molecular ozone (e.g., pH 6 and in the presence of t-BuOH) over OH reactions (e.g., pH 8 and in the presence of H2O2). Compared to ozonation only, addition of H2O2 consistently enhanced formation of all DBP groups (20–61%) except trihalonitromethanes. This proves that OH-transformed organic matter is more susceptible to halogen incorporation. Analogously, adsorbable organic halogen (AOX) concentrations increased under conditions that favor OH reactions. The ratio of unknown to known AOX, however, was greater at conditions that promote direct O3 reactions. Although significant correlation was found between AOX and genotoxicity with the p53 bioassay, toxicity tests using 4 in vitro bioassays showed relatively low absolute differences between various ozonation conditions.

Reproducibility and reliability of anti-3-[¹⁸F]FACBC uptake measurements in background structures and malignant lesions on follow-up PET-CT in prostate carcinoma: an exploratory analysis.

The aim of this study is to examine the reproducibility of anti-1-amino-3-[(18)F]fluorocyclobutane-1-carboxylic acid (anti-3-[(18)F]FACBC) quantitative measurements in key background structures and untreated malignant lesions. Retrospective review of 14 patients who underwent follow-up anti-3-[(18)F]FACBC positron emission tomography-X-ray computed tomography (PET-CT) for prostate carcinoma recurrence. Standard uptake values (SUV) were measured in both original and follow-up scans in key background structures and untreated malignant lesions. Absolute and percent mean difference in SUV between scans and interclass correlation coefficients (ICC) were also computed. Mean (±SD, range) scan interval was 17.4 months (±7.1, 4-29). %Mean difference in SUVmean was <20 % in background structures with low absolute differences. ICCs were >0.6 except for early-phase blood pool (ICC = 0.4). SUVmax in malignant lesions without interim therapy increased or remained stable over time. Despite variable time interval between scans, FACBC PET-CT demonstrates acceptable reproducibility in key background structures. Untreated malignant lesions showed stable or increased uptake over time. A formal test-retest study is planned.

Physical, Bio-Optical State and Correlations in North–Western European Shelf Seas

Color of seawater has become an integral tool in understanding surface marine ecosystems and processes. In this paper we seek to assess the correlations and consequently the potential of using shipborne remote sensing products to infer marine environmental parameters. Typical seawater parameters are chlorophyll–a (chl–a), colored dissolved organic material (CDOM), suspended particulate material (SPM), Secchi–disk depth (SDD), temperature, and salinity. These parameters and radiometric quantities were observed from a total of 60 stations covering German Bight, North Sea, Inner Seas, Irish Sea, and Celtic Sea. Bio-optical models developed in this study were used to predict the in situ measured parameters, with low mean unbiased percent differences and absolute percent difference less than 35%. Our investigations show that the use of ocean color products namely the Forel–Ule Index to infer seawater parameters is encouraging. The constrained spatial and temporal span of measured in situ parameters does limit the accuracy of our models. Absorption coefficients of the main color producing agents CDOM, chl–a, and inorganic fraction of SPM (iSPM) were determined to estimate absorption budgets. During the field campaign, iSPM was the primary light absorber over the spectral range (400–700 nm) although variabilities were observed in the regional seas.

TH‐E‐17A‐06: Anatomical‐Adaptive Compressed Sensing (AACS) Reconstruction for Thoracic 4‐Dimensional Cone‐Beam CT

Purpose:The Feldkamp‐Davis‐Kress (FDK) algorithm currently used for clinical thoracic 4‐dimensional (4D) cone‐beam CT (CBCT) reconstruction suffers from noise and streaking artifacts due to projection under‐sampling. Compressed sensing theory enables reconstruction of under‐sampled datasets via total‐variation (TV) minimization, but TV‐minimization algorithms such as adaptive‐steepest‐descent‐projection‐onto‐convex‐sets (ASD‐POCS) often converge slowly and are prone to over‐smoothing anatomical details. These disadvantages can be overcome by incorporating general anatomical knowledge via anatomy segmentation. Based on this concept, we have developed an anatomical‐adaptive compressed sensing (AACS) algorithm for thoracic 4D‐CBCT reconstruction.Methods:AACS is based on the ASD‐POCS framework, where each iteration consists of a TV‐minimization step and a data fidelity constraint step. Prior to every AACS iteration, four major thoracic anatomical structures – soft tissue, lungs, bony anatomy, and pulmonary details – were segmented from the updated solution image. Based on the segmentation, an anatomical‐adaptive weighting was applied to the TV‐minimization step, so that TV‐minimization was enhanced at noisy/streaky regions and suppressed at anatomical structures of interest. The image quality and convergence speed of AACS was compared to conventional ASD‐POCS using an XCAT digital phantom and a patient scan.Results:For the XCAT phantom, the AACS image represented the ground truth better than the ASD‐POCS image, giving a higher structural similarity index (0.93 vs. 0.84) and lower absolute difference (1.1*104 vs. 1.4*104). For the patient case, while both algorithms resulted in much less noise and streaking than FDK, the AACS image showed considerably better contrast and sharpness of the vessels, tumor, and fiducial marker than the ASD‐POCS image. In addition, AACS converged over 50% faster than ASD‐POCS in both cases.Conclusions:The proposed AACS algorithm was shown to reconstruct thoracic 4D‐CBCT images more accurately and with faster convergence compared to ASD‐POCS. The superior image quality and rapid convergence makes AACS promising for future clinical use.

A comprehensive approach to the segmentation of multichannel three-dimensional MR brain images in multiple sclerosis

Accurate classification and quantification of brain tissues is important for monitoring disease progression, measurement of atrophy, and correlating magnetic resonance (MR) measures with clinical disability. Classification of MR brain images in the presence of lesions, such as multiple sclerosis (MS), is particularly challenging. Images obtained with lower resolution often suffer from partial volume averaging leading to false classifications. While partial volume averaging can be reduced by acquiring volumetric images at high resolution, image segmentation and quantification can be technically challenging. In this study, we integrated the brain anatomical knowledge with non-parametric and parametric statistical classifiers for automatically classifying tissues and lesions on high resolution multichannel three-dimensional images acquired on 60 MS brains. The results of automatic lesion segmentation were reviewed by the expert. The agreement between results obtained by the automated analysis and the expert was excellent as assessed by the quantitative metrics, low absolute volume difference percent (36.18 ± 34.90), low average symmetric surface distance (1.64 mm ± 1.30 mm), high true positive rate (84.75 ± 12.69), and low false positive rate (34.10 ± 16.00). The segmented results were also in close agreement with the corrected results as assessed by Bland–Altman and regression analyses. Finally, our lesion segmentation was validated using the MS lesion segmentation grand challenge dataset (MICCAI 2008).

MR Evaluation of Left Ventricular Volumes and Function

Our study aimed to evaluate a three-dimensional (3D) threshold-based, region-growing segmentation algorithm for the assessment of left ventricular (LV) volumes in cardiac MRI. Two-dimensional cine steady-state free precession short-axis scans (TR 3 milliseconds, TE 1.5 milliseconds, FA 60 degrees , section thickness 8 mm) covering the entire LV without slice gap were acquired in 44 consecutive patients on a 1.5 Tesla MR system (Magnetom Avanto, Siemens, Germany). LV volumes were assessed with an in-house written 3D threshold-based, interslice region-growing segmentation algorithm, and were compared with manual tracing and short-axis planimetry with semiautomatic contour detection (Argus software, Siemens, Germany). Three-dimensional threshold-based segmentation was feasible in 41 of 44 patients. Results of threshold-based segmentation were not statistically significantly different to manual tracing for the assessment of end-diastolic (EDV: 104.5 +/- 32.3 mL vs. 104.7 +/- 33.26 mL, P > 0.05), end-systolic (ESV: 34.5 +/- 17.2 mL vs. 33.8 +/- 17.45 mL, P > 0.05), and stroke (SV: 69.9 +/- 25.0 mL vs. 70.9 +/- 25.0 mL, P > 0.05) volumes. Bland-Altmann plots showed systematic lower EDV (-12.0 +/- 6.7 mL), ESV (-4.8 +/- 3.7 mL), and SV (-7.3 +/- 7.6 mL), and a systematic higher ejection fraction (0.4% +/- 5.0%) for threshold-based segmentation compared with short-axis planimetry with semiautomatic contour detection. Threshold-based segmentation showed an excellent reproducibility with low absolute differences between 2 consecutive analyses (EDV: 0.2 +/- 2.2 mL; ESV: 0.5 +/- 1.9 mL; SV: 0.6 +/- 3.4 mL; EF: 0.5% +/- 2.1%). Evaluation times were significantly shorter for threshold-based segmentation (60 +/- 16 vs. 278 +/- 31 seconds/669 +/- 157 seconds, P < 0.0001). Automated threshold-based segmentation of the left ventricle allows fast and reproducible assessment of LV volumes in cardiac MRI. Exclusion of papillary muscles and myocardial trabeculations from LV volumes leads to systematically lower LV volumes compared with short axis planimetry with semi-automatic contour detection.

Stepped-Dose Versus Full-Dose Efavirenz for HIV Infection and Neuropsychiatric Adverse Events

More than 50% of patients who start efavirenz treatment develop limiting neuropsychiatric adverse events (NPAEs). To assess whether stepwise dosing of efavirenz decreases the incidence and severity of NPAEs while maintaining virologic efficacy. Randomized, double-blind, controlled trial. 7 HIV clinics in Spain. 114 HIV-infected patients eligible for efavirenz treatment plus 2 nucleoside or nucleotide reverse transcriptase inhibitors. Random assignment (by computer-generated sequence) to receive efavirenz, 200 mg/d on days 1 through 6, 400 mg/d on days 7 through 13, and 600 mg/d on day 14 and after, or efavirenz, 600 mg/d, from day 1. Both groups received 2 nucleoside or nucleotide reverse transcriptase inhibitors chosen by the patient's physician. Neuropsychiatric symptoms and sleep quality were assessed by questionnaires at 0, 7, 14, and 30 days. The primary outcome was efavirenz-related NPAEs during the first 2 weeks, and the secondary outcome was plasma HIV RNA level at 24 weeks. Compared with the stepped-dose group, the full-dose group had higher incidence and severity of dizziness (66.0% vs. 32.8%; P = 0.001), hangover (45.8% vs. 20.7%; P = 0.008), impaired concentration (22.9% vs. 8.9%; P = 0.038), and hallucinations (6.1% vs. 0%; P = 0.056) during the first week. From week 2, the incidence of efavirenz-related NPAEs was similar in both groups, although the severity was greater in the full-dose group. Virologic and immunologic efficacy seemed similar in both groups. The sample size was calculated on the basis of a high absolute difference in rates of efavirenz-related NPAEs between the groups. A lower absolute difference and a larger sample size could have made the differences between groups reach statistical significance beyond the first week. In addition, the sample size does not allow confirmation of similar efficacy between treatment groups. Stepwise dose escalation of efavirenz over 2 weeks reduces the incidence and intensity of efavirenz-related NPAEs while maintaining efficacy. Consejería de Salud, Junta de Andalucía, Spain.

An Emissivity Modulation Method for Spatial Enhancement of Thermal Satellite Images in Urban Heat Island Analysis

This study examines and validates a technique for spatial enhancement of thermal satellite images for urban heat island analysis, using a nighttime ASTER satellite image. The technique, termed Emissivity Modulation, enhances the spatial resolution while simultaneously correcting the image derived temperatures for emissivity differences of earth surface materials. A classified image derived from a higher resolution visible wavelength sensor is combined with a lower resolution thermal image in the emissivity correction equation in a procedure derived from the Stephan Bolzmann law. This has the effect of simultaneously correcting the image-derived “Brightness Temperature” (Tb) to the true Kinetic Temperature (Ts), while enhancing the spatial resolution of the thermal data. Although the method has been used for studies of the urban heat island, it has not been validated by comparison with “in situ” derived surface or air temperatures, and researchers may be discouraged from its use due to the fact that it creates sharp boundaries in the image. The emissivity modulated image with 10 m pixel size was found to be highly correlated with 18 in situ surface and air temperature measurements and a low Mean Absolute Difference of 1 K was observed between image and in situ surface temperatures. Lower accuracies were obtained for the Ts and Tb images at 90 m resolution. The study demonstrates that the emissivity modulation method can increase accuracy in the computation of kinetic temperature, improve the relationship between image values and air temperature, and enable the observation of microscale temperature patterns.