Single Time Point Measurements Research Articles

Nonlinear Growth Models as Measurement Models: A Second-Order Growth Curve Model for Measuring Potential

ABSTRACTRecent methodological work has highlighted the promise of nonlinear growth models for addressing substantive questions in the behavioral sciences. In this article, we outline a second-order nonlinear growth model in order to measure a critical notion in development and education: potential. Here, potential is conceptualized as having three components—ability, capacity, and availability—where ability is the amount of skill a student is estimated to have at a given timepoint, capacity is the maximum amount of ability a student is predicted to be able to develop asymptotically, and availability is the difference between capacity and ability at any particular timepoint. We argue that single timepoint measures are typically insufficient for discerning information about potential, and we therefore describe a general framework that incorporates a growth model into the measurement model to capture these three components. Then, we provide an illustrative example using the public-use Early Childhood Longitudinal Study–Kindergarten data set using a Michaelis-Menten growth function (reparameterized from its common application in biochemistry) to demonstrate our proposed model as applied to measuring potential within an educational context. The advantage of this approach compared to currently utilized methods is discussed as are future directions and limitations.

Longitudinal monitoring of reconstructed activity concentration on a clinical time-of-flight PET/CT scanner.

Positron emission tomography (PET) images are potential quantitative biomarkers. Understanding long-term (months/years) biomarker variability is important for establishing confidence intervals on studies using such biomarkers over these time frames. PET biomarkers are derived from activity concentration ([Formula: see text]) extracted from PET images. Over 30 months, we measured the stability of decay-normalized counts ([Formula: see text]) and [Formula: see text] by scanning the same 4.5-cm-diameter Ge-68 cylinder weekly, the same Na-22 point source daily, and a refilled 20-cm F-18 cylinder phantom monthly on a clinical TOF-PET/CT scanner. Longitudinal and adjacent-measurement variability was characterized. We found no drift in [Formula: see text] or [Formula: see text] for properly calibrated images over 24 months. During this time, [Formula: see text] ranged [Formula: see text] to 6% for count-matched Ge-68 and F-18 images, with coefficient of variation (COV) across time of 2.3% (Ge-68, 81 scans) and 3.2% (F-18, 24 scans). At typical patient image count levels the Ge-68 [Formula: see text] ([Formula: see text]) COV across time was 6.9% (9.6%). Changes in [Formula: see text] between adjacent F-18 scans ([Formula: see text]) ranged between [Formula: see text], with corresponding date-matched changes in Ge-68 [Formula: see text] ranging [Formula: see text]. We recommend (1)tracking trends in [Formula: see text] with image [Formula: see text] as a check of quantitative data corrections/calibrations and (2)tracking both mean and COV of [Formula: see text] (single time point measures) to hundredths precision using standardized uptake values.

On the Determination of Magnesium Degradation Rates under Physiological Conditions.

The current physiological in vitro tests of Mg degradation follow the procedure stated according to the ASTM standard. This standard, although useful in predicting the initial degradation behavior of an alloy, has its limitations in interpreting the same for longer periods of immersion in cell culture media. This is an important consequence as the alloy’s degradation is time dependent. Even if two different alloys show similar corrosion rates in a short term experiment, their degradation characteristics might differ with increased immersion times. Furthermore, studies concerning Mg corrosion extrapolate the corrosion rate from a single time point measurement to the order of a year (mm/y), which might not be appropriate because of time dependent degradation behavior. In this work, the above issues are addressed and a new methodology of performing long-term immersion tests in determining the degradation rates of Mg alloys was put forth. For this purpose, cast and extruded Mg-2Ag and powder pressed and sintered Mg-0.3Ca alloy systems were chosen. DMEM Glutamax +10% FBS (Fetal Bovine Serum) +1% Penicillin streptomycin was used as cell culture medium. The advantages of such a method in predicting the degradation rates in vivo deduced from in vitro experiments are discussed.

A high‐throughput assay for screening modifiers of calcium oxalate crystallization

Controlling crystal habit using growth modifiers provides novel avenues for tailoring properties of crystalline materials. Here, we report on the design of a high‐throughput screening assay for rapid identification of growth modifiers using calcium oxalate monohydrate crystallization as a model system. We conducted a systematic study of assay parameters (sample volume, shaking, and temperature) on crystallization kinetics. Crystallization half‐time (t1/2), defined as the time at which crystallization is 50% complete, was obtained from the logistic fit of kinetic data and used as a measure of growth modifier potency. A test library of 13 peptides composed of aspartic acid and alanine residues was screened to determine their growth promotion or inhibition potentials. Leads identified from this study are in good agreement with ion‐selective electrode measurements and a single time point measurement of free calcium ion concentration is an excellent end‐point for evaluating modifier potency. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3538–3546, 2016

Measuring students' school context exposures: A trajectory-based approach

Studies of school effects on children's outcomes usually use single time-point measures. I argue that this approach fails to account for (1) age-based variation in children's sensitivity to their surroundings; (2) differential effects stemming from differences in the length of young people's exposures; and (3) moves between contexts and endogenous changes over time within them. To evaluate the merits of this argument, I specify and test a longitudinal model of school effects on children's academic performance. Drawing on recent advances in finite mixture modeling, I identify a series of distinct school context trajectories that extend across a substantial portion of respondents' elementary and secondary school years. I find that these trajectories vary significantly with respect to shape, with some students experiencing significant changes in their environments over time. I then show that students' trajectories of exposure are related to their 8th grade achievement, even after controlling for point-in-time measures of school context.

Improving Classification Accuracy by Combining Longitudinal Biomarker Measurements Subject to Detection Limits

ABSTRACTDiagnostic or prognostic performance of a biomarker is commonly assessed by the area under the receiver operating characteristic (ROC) curve. Longitudinal information of a biomarker may lead to better performance than a single time point measurement. However, incorporating repeated measurements in the ROC analysis is not straightforward, and the evaluation may be even complicated by the limitation of technical accuracy that causes biomarker measurements being left or right censored at detection limits. Ignorance of correlated nature of longitudinal data and censoring issue may yield spurious estimation of the area under the ROC curve (AUC), and could rule out potentially informative biomarkers from further investigation. In this article, we introduce a linear combination of longitudinal measurements under the goal of optimizing AUC, while accounting for censored observations. Investigators are able to not only evaluate the potential classification power of a marker, but also determine relative importance of each time point in the clinical decision-making process. Our method is assessed in the simulation study and illustrated using a real dataset collected from hospitalized patients with community acquired pneumonia.

Semi-automated quantification of living cells with internalized nanostructures.

BackgroundNanostructures fabricated by different methods have become increasingly important for various applications in biology and medicine, such as agents for medical imaging or cancer therapy. In order to understand their interaction with living cells and their internalization kinetics, several attempts have been made in tagging them. Although methods have been developed to measure the number of nanostructures internalized by the cells, there are only few approaches aimed to measure the number of cells that internalize the nanostructures, and they are usually limited to fixed-cell studies. Flow cytometry can be used for live-cell assays on large populations of cells, however it is a single time point measurement, and does not include any information about cell morphology. To date many of the observations made on internalization events are limited to few time points and cells.ResultsIn this study, we present a method for quantifying cells with internalized magnetic nanowires (NWs). A machine learning-based computational framework, CellCognition, is adapted and used to classify cells with internalized and no internalized NWs, labeled with the fluorogenic pH-dependent dye pHrodo™ Red, and subsequently to determine the percentage of cells with internalized NWs at different time points. In a “proof-of-concept”, we performed a study on human colon carcinoma HCT 116 cells and human epithelial cervical cancer HeLa cells interacting with iron (Fe) and nickel (Ni) NWs.ConclusionsThis study reports a novel method for the quantification of cells that internalize a specific type of nanostructures. This approach is suitable for high-throughput and real-time data analysis and has the potential to be used to study the interaction of different types of nanostructures in live-cell assays.Electronic supplementary materialThe online version of this article (doi:10.1186/s12951-015-0153-x) contains supplementary material, which is available to authorized users.

PO20VOXEL-BASED PARAMETRIC RESPONSE USING THE SERIAL MEASUREMENT OF APPARENT DIFFUSION COEFFICIENT FOR PREDICTING SUBSEQUENT TREATMENT RESPONSE PATTERN IN PATIENTS WITH GLIOBLASTOMA

INTRODUCTION: Determining treatment response after concurrent chemoradiotherapy (CCRT) in glioblastoma is important to minimize morbidity and the financial burden associated with prolonged ineffective treatment. We performed this study to determine the diagnostic superiority of apparent diffusion coefficient (ADC) parametric response (ADCPR) for predicting glioblastoma treatment response, compared to single time point measurement. METHOD: 50 post-treatment glioblastoma patients were enrolled. ADCPR was calculated from serial ADC maps acquired before and at the time of first detection of an enlarged contrast-enhancing lesion on voxel-by-voxel basis. The percentage-decrease in ADCPR and 10% histogram cutoff of ADC (ADC10) were compared as potential predictors of treatment response at subsequent 3 months and 1 year follow-up studies. RESULTS: The percentage-decrease in ADCPR was significantly higher in progression group than in stable-response group both at 3 months follow-up studies (p <.001) and at 1 year follow-up studies (p = 0.003-0.002). ADCPR significantly improved area under the receiver operating characteristic curve from 0.67 to 0.88 and from 0.70 to 0.92 for both readers, respectively, compared to ADC10 at 3 months follow-up studies but did not significantly improve at 1 year follow-up studies. The interreader agreement was higher for ADCPR than ADC10 (intraclass correlation coefficient, 0.93 versus 0.86). CONCLUSION: Voxel-based ADCPR appears to be a superior imaging biomarker than single time point measurement of ADC particularly for predicting early tumor progression in patients with glioblastoma.

Computational analysis of liquid chromatography-tandem mass spectrometric steroid profiling in NCI H295R cells following angiotensin II, forskolin and abiraterone treatment

Adrenal steroid hormones, which regulate a plethora of physiological functions, are produced via tightly controlled pathways. Investigations of these pathways, based on experimental data, can be facilitated by computational modeling for calculations of metabolic rate alterations. We therefore used a model system, based on mass balance and mass reaction equations, to kinetically evaluate adrenal steroidogenesis in human adrenal cortex-derived NCI H295R cells. For this purpose a panel of 10 steroids was measured by liquid chromatographic-tandem mass spectrometry. Time-dependent changes in cell incubate concentrations of steroids – including cortisol, aldosterone, dehydroepiandrosterone and their precursors – were measured after incubation with angiotensin II, forskolin and abiraterone. Model parameters were estimated based on experimental data using weighted least square fitting. Time-dependent angiotensin II- and forskolin-induced changes were observed for incubate concentrations of precursor steroids with peaks that preceded maximal increases in aldosterone and cortisol. Inhibition of 17-alpha-hydroxylase/17,20-lyase with abiraterone resulted in increases in upstream precursor steroids and decreases in downstream products. Derived model parameters, including rate constants of enzymatic processes, appropriately quantified observed and expected changes in metabolic pathways at multiple conversion steps. Our data demonstrate limitations of single time point measurements and the importance of assessing pathway dynamics in studies of adrenal cortical cell line steroidogenesis. Our analysis provides a framework for evaluation of steroidogenesis in adrenal cortical cell culture systems and demonstrates that computational modeling-derived estimates of kinetic parameters are an effective tool for describing perturbations in associated metabolic pathways.

Reproducibility of Retinol Binding Protein 4 and Omentin-1 Measurements over a Four Months Period: A Reliability Study in a Cohort of 207 Apparently Healthy Participants.

The reliability of single time point measurements of the novel adipokines retinol-binding protein 4 and omentin-1 in the blood has not been evaluated in large samples yet. The present study aimed to assess the amount of biological variation of these two adipokines within individuals. The study sample comprised 207 participants (124 women and 83 men) from Potsdam (Germany) and surrounding areas, with an average age of 56.5 years (SD 4.2). Blood samples were collected from each participant twice, approximately four months apart. Using enzyme linked immunosorbent assays, the concentrations of retinol-binding protein 4 and omentin-1 were determined in EDTA plasma. As indicators of reliability, intraclass correlation coefficients (ICCs) were calculated from the repeated biomarker measurements. The ICCs for repeated retinol-binding protein 4 and omentin-1 measurements were 0.77 (95% CI 0.71, 0.82) and 0.83 (95% CI 0.78, 0.87), respectively, indicating for both adipokines excellent reliability. ICCs were stable across strata according to sex, age, BMI, and blood pressure. Thus, for epidemiological studies it seems reasonable to rely on concentrations of retinol-binding protein 4 and omentin-1 in samples from a single time point if repeated measurements are not available.

Apparent diffusion coefficient parametric response mapping MRI for follow-up of glioblastoma.

To determine the diagnostic superiority of parametric response mapping of apparent diffusion coefficient (ADCPR) for predicting glioblastoma treatment response, compared to single time point measurement. Fifty post-treatment glioblastoma patients were enrolled. ADCPR was calculated from serial apparent diffusion coefficient (ADC) maps acquired before and at the time of first detection of an enlarged contrast-enhancing lesion on voxel-by-voxel basis. The percentage-decrease in ADCPR and tenth percentile histogram cutoff value of ADC (ADC10) were compared at subsequent 3-month and 1-year follow-ups. The percentage-decrease in ADCPR was significantly higher in the progression group (mean = 33.2-38.3 %) than in the stable-response group (mean = 9.7 %) at 3 months follow-up (corrected p < 0.001 for both readers). ADCPR significantly improved area under the receiver operating characteristic curve from 0.67 to 0.88 (corrected p = 0.037) and from 0.70 to 0.92 (corrected p = 0.020) for both readers, respectively, compared to ADC10 at 3-month follow-up, but did not significantly improve at 1-year follow-up. The inter-reader agreement was higher for ADCPR than ADC10 (intraclass correlation coefficient, 0.93 versus 0.86). Voxel-based ADCPR appears to be a superior imaging biomarker than ADC, particularly for predicting early tumour progression in patients with glioblastoma. • Treatment response pattern of glioblastoma was evaluated using voxel-based ADCPR and ADC10. • Voxel-based ADCPR was more accurate in predicting treatment response pattern than ADC10. • Inter-reader agreement was higher in ADCPR calculation than in ADC10 calculation. • Voxel-based ADCPR can be a predictor of early treatment response pattern for glioblastoma.

Functional multi-locus QTL mapping of temporal trends in Scots pine wood traits.

Quantitative trait loci (QTL) mapping of wood properties in conifer species has focused on single time point measurements or on trait means based on heterogeneous wood samples (e.g., increment cores), thus ignoring systematic within-tree trends. In this study, functional QTL mapping was performed for a set of important wood properties in increment cores from a 17-yr-old Scots pine (Pinus sylvestris L.) full-sib family with the aim of detecting wood trait QTL for general intercepts (means) and for linear slopes by increasing cambial age. Two multi-locus functional QTL analysis approaches were proposed and their performances were compared on trait datasets comprising 2 to 9 time points, 91 to 455 individual tree measurements and genotype datasets of amplified length polymorphisms (AFLP), and single nucleotide polymorphism (SNP) markers. The first method was a multilevel LASSO analysis whereby trend parameter estimation and QTL mapping were conducted consecutively; the second method was our Bayesian linear mixed model whereby trends and underlying genetic effects were estimated simultaneously. We also compared several different hypothesis testing methods under either the LASSO or the Bayesian framework to perform QTL inference. In total, five and four significant QTL were observed for the intercepts and slopes, respectively, across wood traits such as earlywood percentage, wood density, radial fiberwidth, and spiral grain angle. Four of these QTL were represented by candidate gene SNPs, thus providing promising targets for future research in QTL mapping and molecular function. Bayesian and LASSO methods both detected similar sets of QTL given datasets that comprised large numbers of individuals.

Measuring stem cell dynamics in the human colon--where there's a wiggle, there's a way.

The last decade has seen huge improvements in our understanding of intestinal stem cell biology, with major advances arising from the ability to transgenically label, and thus identify, murine stem cells and their progeny. In the human, transgenic labelling is not an available option and stem cell dynamic observations have been based on rare hereditary mutations and polymorphisms. Somatic mitochondrial DNA mutations cause a histochemically detectable, but neutrally selected, change in cytochrome c oxidase (CCO) enzyme activity and when this occurs in an intestinal stem cell, it can be used as an effective clonal marker in both health and disease. The intestinal crypt is the functional unit of the gut. Daughter cells are ‘born’ in the stem cell niche at the crypt base and proliferate, differentiate, and then apoptose as they migrate along the vertical crypt axis over 5–7 days. This stereotypical architecture provides a historical record of cell dynamics, as the distance travelled along the crypt axis is proportional to the time since the daughter cell was born. By staining, identifying, and carefully reconstructing crypt maps from serial en face sections of partially mutated mtDNA crypts, clonal ribbon images can be generated. ‘Wiggles’ in the width of the clonal ribbon reflect mtDNA mutated stem cell expansion or contraction events and these biological observations are applied in mathematical models. This clever approach is able to infer temporal evolutionary dynamics from a static, single time point measurement, in both normal and familial adenomatous polyposis tissue. As we have seen in the mouse, the simple ability to identify stem cell progeny can lead to a vast expansion in our understanding of stem cell evolution. The use of these techniques to trace recent stem cell dynamics in the human colon makes some headway into the knowledge gap in our understanding of murine and human intestinal stem cell biology.

Abstract 3695: The utility of plasma vascular endothelial growth factor and heparanase as pharmacodynamic markers following treatment with PG545, a heparan sulfate mimetic: preliminary evidence from preclinical and clinical settings

Abstract Background: The heparan sulfate mimetic PG545 has been demonstrated to inhibit the function of vascular endothelial growth factor (VEGF) and heparanase (HPSE) in vitro whilst downregulating HPSE expression in tumor and metastatic tissue in vivo. Although there are reports of consistent drug-induced increases in plasma VEGF with VEGF inhibitors such as bevacizumab, similar data are lacking for HS mimetics. Given PG545's mechanism of action which involves inhibition of both angiogenesis and metastasis, the evaluation of plasma VEGF and HPSE may represent pharmacodynamic (PD) biomarkers for each of these key processes. Materials and Methods: The levels of plasma VEGF and HPSE were measured using ELISA in samples from preclinical models of ovarian cancer (syngeneic ID8 and xenogeneic A2780 models) and a small cohort of patients (dosed with PG545 by the subcutaneous route) with advanced solid tumors from a Phase I clinical study. In tumor models, PG545 was administered once weekly by intravenous or intraperitoneal routes and efficacy was determined by quantifying tumor burden using the following methods: measurement of palpable solid tumors, abdominal circumference, ascites volume and/or by tracking cells using bioluminescent reporter imaging (depending on the model). In the A2780 model and the clinical samples, the pharmacokinetics of PG545 was also evaluated using LC-MS/MS, which ensured multiple samples to facilitate the measurement of VEGF and HPSE in plasma over the duration of the dosing interval following treatment with PG545. Results: PG545 demonstrated potent antitumor and antimetastatic activity when administered once weekly via intravenous or intraperitoneal routes in preclinical studies. These studies also indicated that PG545 treatment led to increases in plasma VEGF and HPSE. Importantly, plasma samples from advanced cancer patients treated with PG545 also revealed increases in these PD markers with initial peaks often correlating with Cmax of PG545 but longer-term gradual increases also noted in some instances. We consider that these increases in plasma levels result from PG545 binding to, thereby inhibiting, VEGF and HPSE in the tumor microenvironment. Conclusion: Given the questionable utility of single time point measures of plasma PD markers (including VEGF), these preliminary data suggest that kinetic profiling can reveal the previously undetermined dynamics of circulating VEGF and HPSE following treatment with PG545. Thus, the measurement of VEGF and HPSE appears to represent potential markers of pharmacodynamic activity. A new Phase I trial with intravenously-administered PG545 has recently commenced and should further clarify the potential utility of these basic PD biomarker responses in advanced cancer patients. Citation Format: Keith Dredge, Edward Hammond, Boris Winterhoff, Shailendra Giri, Attila Teoman, Darryn Bampton, Michael Millward, Viji Shridhar. The utility of plasma vascular endothelial growth factor and heparanase as pharmacodynamic markers following treatment with PG545, a heparan sulfate mimetic: preliminary evidence from preclinical and clinical settings. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3695. doi:10.1158/1538-7445.AM2014-3695

Hematopoietic clonal dominance, stem cell mutations, and evolutionary pattern of JAK2V617F allele burden in polycythemia vera.

Clonal dominance is characteristic of patients with post-polycythemia vera myelofibrosis (post-PV MF), whereas patients in chronic phase usually display polyclonal hematopoiesis. The aim of this work was to study the mutational burden of JAK2V617F at the progenitor level in patients with PV and correlate it with the evolutive phase of the disease and the presence of mutations in genes different to JAK2V617F. JAK2V617F was measured in stem cells, progenitor cells, and granulocytes of 45 patients with PV (early chronic phase n = 26, late chronic phase n = 10, post-PV MF n = 9). In addition, screening of TET2, DNMT3A, ASXL1, SF3B1, SRSF2, U2AF1, and TP53 was performed with quantification of the mutation in CD34+ cells in positive cases. Moreover, we assessed whether JAK2V617F allele burden in granulocytes (at a single time point or monitoring) could be used as a surrogate of clonal dominance. Ten patients presented clonal dominance at progenitor level (PV at diagnosis n = 2, late chronic phase n = 1, post-PV MF n = 7). Additional mutations were identified in four patients at diagnosis, three in TET2, and one in DNMT3A gene, with clonal dominance present in three of them. At PV diagnosis, clonal dominance was demonstrated only in patients with additional mutations. JAK2V617F monitoring showed better diagnostic accuracy than single time point measurement as a marker of clonal dominance. Clonal dominance may be present at diagnosis, especially in those cases carrying other mutations. JAK2V617F monitoring during follow-up could help in the identification of patients with clonal dominance.

Observer Variability in Mesothelioma Tumor Thickness Measurements: Defining Minimally Measurable Lesions

Single time-point unidimensional tumor thickness measurements define measurable disease for clinical trial inclusion and also constitute a field in the International Association for the Study of Lung Cancer prospective mesothelioma staging database. The modified Response Evaluation Criteria in Solid Tumors (RECIST) guidelines for mesothelioma did not alter the 10-mm minimum tumor measurement recommendation. However, as computed tomography technology has advanced, we sought to examine whether interobserver agreement was acceptable at smaller tumor thickness in mesothelioma. The primary observer selected 170 discrete measurement sites from 105 thoracic computed tomography scans from 50 consenting patients with pleural mesothelioma. Sites represented a range of tumor thickness, lesion morphology, and location. The outer (parietal) tumor margin was marked at each site and presented to five additional observers, who then selected the visceral margin of the tumor to create a line segment that captured tumor thickness. Relative differences among the observer measurements were estimated using a random-effects analysis of variance model to identify the smallest tumor thickness at which linear measurements could be made reliably. Systematic bias was observed, with some observers consistently measuring larger or smaller thicknesses than the thickness measured by others. The mean range across all 170 sites was 15.1% of the mean per-site measurement (SD = 9.1%; median range, 13.1%). Measurements acquired at sites with mean tumor thickness less than 7.5 mm demonstrated interobserver variability with a 75th percentile included 20% of the tumor thickness. The 95% confidence interval for relative interobserver measurement differences obtained for mean measurement lengths in the range 5 to 7.5 mm does not exceed the RECIST thresholds. This study has implications for the definition of minimally measurable tumor adopted by clinical trial and staging protocols. Although the statistical findings suggest that a reduction in "minimally measurable disease" from 10 mm to 5 or 7.5 mm might be warranted, clinical factors may ultimately dictate the most appropriate definition.

The Application of Functional Imaging Techniques to Personalise Chemoradiotherapy in Upper Gastrointestinal Malignancies

Functional imaging gives information about physiological heterogeneity in tumours. The utility of functional imaging tests in providing predictive and prognostic information after chemoradiotherapy for both oesophageal cancer and pancreatic cancer will be reviewed. The benefit of incorporating functional imaging into radiotherapy planning is also evaluated. In cancers of the upper gastrointestinal tract, the vast majority of functional imaging studies have used 18F-fluorodeoxyglucose positron emission tomography (FDG-PET). Few studies in locally advanced pancreatic cancer have investigated the utility of functional imaging in risk-stratifying patients or aiding target volume definition. Certain themes from the oesophageal data emerge, including the need for a multiparametric assessment of functional images and the added value of response assessment rather than relying on single time point measures. The sensitivity and specificity of FDG-PET to predict treatment response and survival are not currently high enough to inform treatment decisions. This suggests that a multimodal, multiparametric approach may be required. FDG-PET improves target volume definition in oesophageal cancer by improving the accuracy of tumour length definition and by improving the nodal staging of patients. The ideal functional imaging test would accurately identify patients who are unlikely to achieve a pathological complete response after chemoradiotherapy and would aid the delineation of a biological target volume that could be used for treatment intensification. The current limitations of published studies prevent integrating imaging-derived parameters into decision making on an individual patient basis. These limitations should inform future trial design in oesophageal and pancreatic cancers.

Quantitative computer tomography analysis of post-operative subdural fluid volume predicts recurrence of chronic subdural haematoma

AbstarctBackground: Post-operative volume of subdural fluid is considered to correlate with recurrence in chronic subdural haematoma (CSDH). Information on the applications of computer-assisted volumetric analysis in patients with CSDHs is lacking.Objective: To investigate the relationship between haematoma recurrence and longitudinal changes in subdural fluid volume using CT volumetric analysis.Methods: Fifty-four patients harbouring 64 CSDHs were studied prospectively. The association between recurrence rate and CT findings were investigated.Results: Eleven patients (20.4%) experienced post-operative recurrence. Higher pre-operative (over 120 ml) and/or pre-discharge subdural fluid volumes (over 22 ml) were significantly associated with recurrence; the probability of non-recurrence for values below these thresholds were 92.7% and 95.2%, respectively. CSDHs with larger pre-operative (over 15.1 mm) and/or residual (over 11.7 mm) widths also had significantly increased recurrence rates. Bilateral CSDHs were not found to be more likely to recur in this series. On receiver-operating characteristic curve, the areas under curve for the magnitude of changes in subdural fluid volume were greater than a single time-point measure of either width or volume of the subdural fluid cavity.Conclusions: Close imaging follow-up is important for CSDH patients for recurrence prediction. Using quantitative CT volumetric analysis, strong evidence was provided that changes in the residual fluid volume during the ‘self-resolution’ period can be used as significantly radiological predictors of recurrence.

Targeted Metabolomics Identifies Reliable and Stable Metabolites in Human Serum and Plasma Samples

BackgroundInformation regarding the variability of metabolite levels over time in an individual is required to estimate the reproducibility of metabolite measurements. In intervention studies, it is critical to appropriately judge changes that are elicited by any kind of intervention. The pre-analytic phase (collection, transport and sample processing) is a particularly important component of data quality in multi-center studies.MethodsReliability of metabolites (within-and between-person variance, intraclass correlation coefficient) and stability (shipment simulation at different temperatures, use of gel-barrier collection tubes, freeze-thaw cycles) were analyzed in fasting serum and plasma samples of 22 healthy human subjects using a targeted LC-MS approach.ResultsReliability of metabolite measurements was higher in serum compared to plasma samples and was good in most saturated short-and medium-chain acylcarnitines, amino acids, biogenic amines, glycerophospholipids, sphingolipids and hexose. The majority of metabolites were stable for 24 h on cool packs and at room temperature in non-centrifuged tubes. Plasma and serum metabolite stability showed good coherence. Serum metabolite concentrations were mostly unaffected by tube type and one or two freeze-thaw cycles.ConclusionA single time point measurement is assumed to be sufficient for a targeted metabolomics analysis of most metabolites. For shipment, samples should ideally be separated and frozen immediately after collection, as some amino acids and biogenic amines become unstable within 3 h on cool packs. Serum gel-barrier tubes can be used safely for this process as they have no effect on concentration in most metabolites. Shipment of non-centrifuged samples on cool packs is a cost-efficient alternative for most metabolites.

Epidemiology and genetic determinants of progressive deterioration of glycaemia in American Indians: the Strong Heart Family Study.

Type 2 diabetes is a chronic, heterogeneous disease and a major risk factor for cardiovascular diseases. The underlying mechanisms leading to progression to type 2 diabetes are not fully understood and genetic tools may help to identify important pathways of glycaemic deterioration. Using prospective data on American Indians from the Strong Heart Family Study, we identified 373 individuals defined as progressors (diabetes incident cases), 566 individuals with transitory impaired fasting glucose (IFG) and 1,011 controls (normal fasting glycaemia at all visits). We estimated the heritability (h(2)) of the traits and the evidence for association with 16 known variants identified in type 2 diabetes genome-wide association studies. We noted high h(2) for diabetes progression (h(2) = 0.65 ± 0.16, p = 2.7 × 10(-6)) but little contribution of genetic factors to transitory IFG (h(2) = 0.09 ± 0.10, p = 0.19) for models adjusted for multiple risk factors. At least three variants (in WFS1, TSPAN8 and THADA) were nominally associated with diabetes progression in age- and sex-adjusted analyses with estimates showing the same direction of effects as reported in the discovery European ancestry studies. Our findings do not exclude these loci for diabetes susceptibility in American Indians and suggest phenotypic heterogeneity of the IFG trait, which may have implications for genetic studies when diagnosis is based on a single time-point measure.