Survey on batch-to-batch variation in spray paints: a collaborative study

This study represents the most extensive analysis of batch-to-batch variations in spray paint samples to date. The survey was performed as a collaborative project of the ENFSI (European Network of Forensic Science Institutes) Paint and Glass Working Group (EPG) and involved 11 laboratories. Several studies have already shown that paint samples of similar color but from different manufacturers can usually be differentiated using an appropriate analytical sequence. The discrimination of paints from the same manufacturer and color (batch-to-batch variations) is of great interest and these data are seldom found in the literature. This survey concerns the analysis of batches from different color groups (white, papaya (special shade of orange), red and black) with a wide range of analytical techniques and leads to the following conclusions. Colored batch samples are more likely to be differentiated since their pigment composition is more complex (pigment mixtures, added pigments) and therefore subject to variations. These variations may occur during the paint production but may also occur when checking the paint shade in quality control processes. For these samples, techniques aimed at color/pigment(s) characterization (optical microscopy, microspectrophotometry (MSP), Raman spectroscopy) provide better discrimination than techniques aimed at the organic (binder) or inorganic composition (fourier transform infrared spectroscopy (FTIR) or elemental analysis (SEM - scanning electron microscopy and XRF - X-ray fluorescence)). White samples contain mainly titanium dioxide as a pigment and the main differentiation is based on the binder composition (Csingle bondH stretches) detected either by FTIR or Raman. The inorganic composition (elemental analysis) also provides some discrimination. Black samples contain mainly carbon black as a pigment and are problematic with most of the spectroscopic techniques. In this case, pyrolysis-GC/MS represents the best technique to detect differences. Globally, Py-GC/MS may show a high potential of discrimination on all samples but the results are highly dependent on the specific instrumental conditions used. Finally, the discrimination of samples when data was interpreted visually as compared to statistically using principal component analysis (PCA) yielded very similar results. PCA increases sensitivity and could perform better on specific samples, but one first has to ensure that all non-informative variation (baseline deviation) is eliminated by applying correct pre-treatments. Statistical treatments can be used on a large data set and, when combined with an expert's opinion, will provide more objective criteria for decision making.

Estimating vadose zone hydraulic properties using ground penetrating radar: The impact of prior information

A number of geophysical methods, such as ground-penetrating radar (GPR), have the potential to provide valuable information on hydrological properties in the unsaturated zone. In particular, the stochastic inversion of such data within a coupled geophysical-hydrological framework may allow for the effective estimation of vadose zone hydraulic parameters and their corresponding uncertainties. A critical issue in stochastic inversion is choosing prior parameter probability distributions from which potential model configurations are drawn and tested against observed data. A well chosen prior should reflect as honestly as possible the initial state of knowledge regarding the parameters and be neither overly specific nor too conservative. In a Bayesian context, combining the prior with available data yields a posterior state of knowledge about the parameters, which can then be used statistically for predictions and risk assessment. Here we investigate the influence of prior information regarding the van Genuchten-Mualem (VGM) parameters, which describe vadose zone hydraulic properties, on the stochastic inversion of crosshole GPR data collected under steady state, natural-loading conditions. We do this using a Bayesian Markov chain Monte Carlo (MCMC) inversion approach, considering first noninformative uniform prior distributions and then more informative priors derived from soil property databases. For the informative priors, we further explore the effect of including information regarding parameter correlation. Analysis of both synthetic and field data indicates that the geophysical data alone contain valuable information regarding the VGM parameters. However, significantly better results are obtained when we combine these data with a realistic, informative prior.

A comparison of Bayesian and frequentist approaches to incorporating external information for the prediction of prostate cancer risk.

We present the most comprehensive comparison to date of the predictive benefit of genetics in addition to currently used clinical variables, using genotype data for 33 single-nucleotide polymorphisms (SNPs) in 1,547 Caucasian men from the placebo arm of the REduction by DUtasteride of prostate Cancer Events (REDUCE®) trial. Moreover, we conducted a detailed comparison of three techniques for incorporating genetics into clinical risk prediction. The first method was a standard logistic regression model, which included separate terms for the clinical covariates and for each of the genetic markers. This approach ignores a substantial amount of external information concerning effect sizes for these Genome Wide Association Study (GWAS)-replicated SNPs. The second and third methods investigated two possible approaches to incorporating meta-analysed external SNP effect estimates - one via a weighted PCa 'risk' score based solely on the meta analysis estimates, and the other incorporating both the current and prior data via informative priors in a Bayesian logistic regression model. All methods demonstrated a slight improvement in predictive performance upon incorporation of genetics. The two methods that incorporated external information showed the greatest receiver-operating-characteristic AUCs increase from 0.61 to 0.64. The value of our methods comparison is likely to lie in observations of performance similarities, rather than difference, between three approaches of very different resource requirements. The two methods that included external information performed best, but only marginally despite substantial differences in complexity.

Sparse regularization for fiber ODF reconstruction: from the suboptimality of ℓ2 and ℓ1 priors to ℓ0.

Diffusion MRI is a well established imaging modality providing a powerful way to probe the structure of the white matter non-invasively. Despite its potential, the intrinsic long scan times of these sequences have hampered their use in clinical practice. For this reason, a large variety of methods have been recently proposed to shorten the acquisition times. Among them, spherical deconvolution approaches have gained a lot of interest for their ability to reliably recover the intra-voxel fiber configuration with a relatively small number of data samples. To overcome the intrinsic instabilities of deconvolution, these methods use regularization schemes generally based on the assumption that the fiber orientation distribution (FOD) to be recovered in each voxel is sparse. The well known Constrained Spherical Deconvolution (CSD) approach resorts to Tikhonov regularization, based on an ℓ(2)-norm prior, which promotes a weak version of sparsity. Also, in the last few years compressed sensing has been advocated to further accelerate the acquisitions and ℓ(1)-norm minimization is generally employed as a means to promote sparsity in the recovered FODs. In this paper, we provide evidence that the use of an ℓ(1)-norm prior to regularize this class of problems is somewhat inconsistent with the fact that the fiber compartments all sum up to unity. To overcome this ℓ(1) inconsistency while simultaneously exploiting sparsity more optimally than through an ℓ(2) prior, we reformulate the reconstruction problem as a constrained formulation between a data term and a sparsity prior consisting in an explicit bound on the ℓ(0)norm of the FOD, i.e. on the number of fibers. The method has been tested both on synthetic and real data. Experimental results show that the proposed ℓ(0) formulation significantly reduces modeling errors compared to the state-of-the-art ℓ(2) and ℓ(1) regularization approaches.

Global tractography with embedded anatomical priors for quantitative connectivity analysis.

Tractography algorithms provide us with the ability to non-invasively reconstruct fiber pathways in the white matter (WM) by exploiting the directional information described with diffusion magnetic resonance. These methods could be divided into two major classes, local and global. Local methods reconstruct each fiber tract iteratively by considering only directional information at the voxel level and its neighborhood. Global methods, on the other hand, reconstruct all the fiber tracts of the whole brain simultaneously by solving a global energy minimization problem. The latter have shown improvements compared to previous techniques but these algorithms still suffer from an important shortcoming that is crucial in the context of brain connectivity analyses. As no anatomical priors are usually considered during the reconstruction process, the recovered fiber tracts are not guaranteed to connect cortical regions and, as a matter of fact, most of them stop prematurely in the WM; this violates important properties of neural connections, which are known to originate in the gray matter (GM) and develop in the WM. Hence, this shortcoming poses serious limitations for the use of these techniques for the assessment of the structural connectivity between brain regions and, de facto, it can potentially bias any subsequent analysis. Moreover, the estimated tracts are not quantitative, every fiber contributes with the same weight toward the predicted diffusion signal. In this work, we propose a novel approach for global tractography that is specifically designed for connectivity analysis applications which: (i) explicitly enforces anatomical priors of the tracts in the optimization and (ii) considers the effective contribution of each of them, i.e., volume, to the acquired diffusion magnetic resonance imaging (MRI) image. We evaluated our approach on both a realistic diffusion MRI phantom and in vivo data, and also compared its performance to existing tractography algorithms.

Improvement of therapeutic drug monitoring of imatinib by Bayesian prediction of trough levels. Personalized drug dosage

Aims: Plasma concentrations of imatinib differ largely between patients despite same dosage, owing to large inter-individual variability in pharmacokinetic (PK) parameters. As the drug concentration at the end of the dosage interval (Cmin) correlates with treatment response and tolerability, monitoring of Cmin is suggested for therapeutic drug monitoring (TDM) of imatinib. Due to logistic difficulties, random sampling during the dosage interval is however often performed in clinical practice, thus rendering the respective results not informative regarding Cmin values.Objectives: (I) To extrapolate randomly measured imatinib concentrations to more informative Cmin using classical Bayesian forecasting. (II) To extend the classical Bayesian method to account for correlation between PK parameters. (III) To evaluate the predictive performance of both methods.Methods: 31 paired blood samples (random and trough levels) were obtained from 19 cancer patients under imatinib. Two Bayesian maximum a posteriori (MAP) methods were implemented: (A) a classical method ignoring correlation between PK parameters, and (B) an extended one accounting for correlation. Both methods were applied to estimate individual PK parameters, conditional on random observations and covariate-adjusted priors from a population PK model. The PK parameter estimates were used to calculate trough levels. Relative prediction errors (PE) were analyzed to evaluate accuracy (one-sample t-test) and to compare precision between the methods (F-test to compare variances).Results: Both Bayesian MAP methods allowed non-biased predictions of individual Cmin compared to observations: (A) - 7% mean PE (CI95% - 18 to 4 %, p = 0.15) and (B) - 4% mean PE (CI95% - 18 to 10 %, p = 0.69). Relative standard deviations of actual observations from predictions were 22% (A) and 30% (B), i.e. comparable to the intraindividual variability reported. Precision was not improved by taking into account correlation between PK parameters (p = 0.22).Conclusion: Clinical interpretation of randomly measured imatinib concentrations can be assisted by Bayesian extrapolation to maximum likelihood Cmin. Classical Bayesian estimation can be applied for TDM without the need to include correlation between PK parameters. Both methods could be adapted in the future to evaluate other individual pharmacokinetic measures correlated to clinical outcomes, such as area under the curve(AUC).

Evaluation de la douleur chez les personnes cérébrolésées non-communicantes aux soins intensifs

La douleur est fréquente en milieu de soins intensifs et sa gestion est l'une des missions des infirmières. Son évaluation est une prémisse indispensable à son soulagement. Cependant lorsque le patient est incapable de signaler sa douleur, les infirmières doivent se baser sur des signes externes pour l'évaluer. Les guides de bonne pratique recommandent chez les personnes non communicantes l'usage d'un instrument validé pour la population donnée et basé sur l'observation des comportements. A l'heure actuelle, les instruments d'évaluation de la douleur disponibles ne sont que partiellement adaptés aux personnes cérébrolésées dans la mesure où ces personnes présentent des comportements qui leur sont spécifiques. C'est pourquoi, cette étude vise à identifier, décrire et valider des indicateurs, et des descripteurs, de la douleur chez les personnes cérébrolésées. Un devis d'étude mixte multiphase avec une dominante quantitative a été choisi pour cette étude. Une première phase consistait à identifier des indicateurs et des descripteurs de la douleur chez les personnes cérébrolésées non communicantes aux soins intensifs en combinant trois sources de données : une revue intégrative des écrits, une démarche consultative utilisant la technique du groupe nominal auprès de 18 cliniciens expérimentés (6 médecins et 12 infirmières) et les résultats d'une étude pilote observationnelle réalisée auprès de 10 traumatisés crâniens. Les résultats ont permis d'identifier 6 indicateurs et 47 descripteurs comportementaux, vocaux et physiologiques susceptibles d'être inclus dans un instrument d'évaluation de la douleur destiné aux personnes cérébrolésées non- communicantes aux soins intensifs. Une deuxième phase séquentielle vérifiait les propriétés psychométriques des indicateurs et des descripteurs préalablement identifiés. La validation de contenu a été testée auprès de 10 experts cliniques et 4 experts scientifiques à l'aide d'un questionnaire structuré qui cherchait à évaluer la pertinence et la clarté/compréhensibilité de chaque descripteur. Cette démarche a permis de sélectionner 33 des 47 descripteurs et valider 6 indicateurs. Dans un deuxième temps, les propriétés psychométriques de ces indicateurs et descripteurs ont été étudiés au repos, lors de stimulation non nociceptive et lors d'une stimulation nociceptive (la latéralisation du patient) auprès de 116 personnes cérébrolésées aux soins intensifs hospitalisées dans deux centres hospitaliers universitaires. Les résultats montrent d'importantes variations dans les descripteurs observés lors de stimulation nociceptive probablement dues à l'hétérogénéité des patients au niveau de leur état de conscience. Dix descripteurs ont été éliminés, car leur fréquence lors de la stimulation nociceptive était inférieure à 5% ou leur fiabilité insuffisante. Les descripteurs physiologiques ont tous été supprimés en raison de leur faible variabilité et d'une fiabilité inter juge problématique. Les résultats montrent que la validité concomitante, c'est-à-dire la corrélation entre l'auto- évaluation du patient et les mesures réalisées avec les descripteurs, est satisfaisante lors de stimulation nociceptive {rs=0,527, p=0,003, n=30). Par contre la validité convergente, qui vérifiait l'association entre l'évaluation de la douleur par l'infirmière en charge du patient et les mesures réalisés avec les descripteurs, ainsi que la validité divergente, qui vérifiait si les indicateurs discriminent entre la stimulation nociceptive et le repos, mettent en évidence des résultats variables en fonction de l'état de conscience des patients. Ces résultats soulignent la nécessité d'étudier les descripteurs de la douleur chez des patients cérébrolésés en fonction du niveau de conscience et de considérer l'hétérogénéité de cette population dans la conception d'un instrument d'évaluation de la douleur pour les personnes cérébrolésées non communicantes aux soins intensifs. - Pain is frequent in the intensive care unit (ICU) and its management is a major issue for nurses. The assessment of pain is a prerequisite for appropriate pain management. However, pain assessment is difficult when patients are unable to communicate about their experience and nurses have to base their evaluation on external signs. Clinical practice guidelines highlight the need to use behavioral scales that have been validated for nonverbal patients. Current behavioral pain tools for ICU patients unable to communicate may not be appropriate for nonverbal brain-injured ICU patients, as they demonstrate specific responses to pain. This study aimed to identify, describe and validate pain indicators and descriptors in brain-injured ICU patients. A mixed multiphase method design with a quantitative dominant was chosen for this study. The first phase aimed to identify indicators and descriptors of pain for nonverbal brain- injured ICU patients using data from three sources: an integrative literature review, a consultation using the nominal group technique with 18 experienced clinicians (12 nurses and 6 physicians) and the results of an observational pilot study with 10 traumatic brain injured patients. The results of this first phase identified 6 indicators and 47 behavioral, vocal and physiological descriptors of pain that could be included in a pain assessment tool for this population. The sequential phase two tested the psychometric properties of the list of previously identified indicators and descriptors. Content validity was tested with 10 clinical and 4 scientific experts for pertinence and comprehensibility using a structured questionnaire. This process resulted in 33 descriptors to be selected out of 47 previously identified, and six validated indicators. Then, the psychometric properties of the descriptors and indicators were tested at rest, during non nociceptive stimulation and nociceptive stimulation (turning) in a sample of 116 brain-injured ICLI patients who were hospitalized in two university centers. Results showed important variations in the descriptors observed during the nociceptive stimulation, probably due to the heterogeneity of patients' level of consciousness. Ten descriptors were excluded, as they were observed less than 5% of the time or their reliability was insufficient. All physiologic descriptors were deleted as they showed little variability and inter observer reliability was lacking. Concomitant validity, testing the association between patients' self report of pain and measures performed using the descriptors, was acceptable during nociceptive stimulation (rs=0,527, p=0,003, n=30). However, convergent validity ( testing for an association between the nurses' pain assessment and measures done with descriptors) and divergent validity (testing for the ability of the indicators to discriminate between rest and a nociceptive stimulation) varied according to the level of consciousness These results highlight the need to study pain descriptors in brain-injured patients with different level of consciousness and to take into account the heterogeneity of this population forthe conception of a pain assessment tool for nonverbal brain-injured ICU patients.

Non-assisted versus neuro-navigated and XperCT-guided external ventricular catheter placement: a comparative cadaver study.

BACKGROUND AND PURPOSE: Accurate placement of an external ventricular drain (EVD) for the treatment of hydrocephalus is of paramount importance for its functionality and in order to minimize morbidity and complications. The aim of this study was to compare two different drain insertion assistance tools with the traditional free-hand anatomical landmark method, and to measure efficacy, safety and precision. METHODS: Ten cadaver heads were prepared by opening large bone windows centered on Kocher's points on both sides. Nineteen physicians, divided in two groups (trainees and board certified neurosurgeons) performed EVD insertions. The target for the ventricular drain tip was the ipsilateral foramen of Monro. Each participant inserted the external ventricular catheter in three different ways: 1) free-hand by anatomical landmarks, 2) neuronavigation-assisted (NN), and 3) XperCT-guided (XCT). The number of ventricular hits and dangerous trajectories; time to proceed; radiation exposure of patients and physicians; distance of the catheter tip to target and size of deviations projected in the orthogonal plans were measured and compared. RESULTS: Insertion using XCT increased the probability of ventricular puncture from 69.2 to 90.2 % (p = 0.02). Non-assisted placements were significantly less precise (catheter tip to target distance 14.3 ± 7.4 mm versus 9.6 ± 7.2 mm, p = 0.0003). The insertion time to proceed increased from 3.04 ± 2.06 min. to 7.3 ± 3.6 min. (p < 0.001). The X-ray exposure for XCT was 32.23 mSv, but could be reduced to 13.9 mSv if patients were initially imaged in the hybrid-operating suite. No supplementary radiation exposure is needed for NN if patients are imaged according to a navigation protocol initially. CONCLUSION: This ex vivo study demonstrates a significantly improved accuracy and safety using either NN or XCT-assisted methods. Therefore, efforts should be undertaken to implement these new technologies into daily clinical practice. However, the accuracy versus urgency of an EVD placement has to be balanced, as the image-guided insertion technique will implicate a longer preparation time due to a specific image acquisition and trajectory planning.

Carcinoembryonic antigen (CEA) in non digestive cancerous and normal tissues.

Carcinoembryonic antigen (CEA), immunologically identical to CEA derived from colonic carcinoma, was identified and purified from perchloric acid (PCA) extracts of bronchial and mammary carcinoma. CEA extracted from bronchial and mammary carcinoma was quantitated by single radial immunodiffusion and was found to be in average about 50-75 times less abundant in these tumors than in colonic carcinoma. CEA could also be detected in one normal breast in lactation and at lower concentrations in normal lung (1000-4000 times lower than in colonic carcinoma). The small amounts of CEA present in normal tissues are distinct from the glycoprotein of small mol. wt showing only partial identity with CEA, that we recently identified and extracted in much larger quantities from normal lung and spleen. The demonstration of the presence of CEA in non digestive carcinoma by classical gel precipitation analysis suggests that the CEA detected in the plasma of such patients by radioimmunoassay is also identical to colonic carcinoma CEA. Our comparative study of plasma CEA from bronchial and colonic carcinoma, showing that CEA from both types of patient has the same elution pattern on Sephadex G-200 and gives parallel inhibition curves in the radioimmunoassay, is in favor of this hypothesis. However, it should not be concluded that all positive CEA radioimmunoassay indicate the presence of an antigen identical to colonic carcinoma CEA. A word of warning concerning the interpretation of radioimmunoassay is required by the observation that the addition of mg amounts of PCA extract of normal plasma, cleared of CEA by Sephadex filtration, could interfere in the test and mimic the presence of CEA.

Food habits and sport activity during adolescence: differences between athletic and non-athletic teenagers in Switzerland.

OBJECTIVE: To describe food habits and dietary intakes of athletic and non-athletic adolescents in Switzerland. SETTING: College, high schools and professional centers in the Swiss canton of Vaud. METHOD: A total of 3,540 subjects aged 9-19 y answered a self-reported anonymous questionnaire to assess lifestyles, physical plus sports activity and food habits. Within this sample, a subgroup of 246 subjects aged 11-15 also participated in an in-depth ancillary study including a 3 day dietary record completed by an interview with a dietician. RESULTS: More boys than girls reported engaging in regular sports activities (P<0.001). Adolescent food habits are quite traditional: up to 15 y, most of the respondents have a breakfast and eat at least two hot meals a day, the percentages decreasing thereafter. Snacking is widespread among adolescents (60-80% in the morning, 80-90% in the afternoon). Food habits among athletic adolescents are healthier and also are perceived as such in a higher proportion. Among athletic adolescents, consumption frequency is higher for dairy products and ready to eat (RTE) cereals, for fruit, fruit juices and salad (P<0.05 at least). Thus the athletic adolescent's food brings more micronutrients than the diet of their non-athletic counterparts. Within the subgroup (ancillary study), mean energy intake corresponds to requirements for age/gender group. CONCLUSIONS: Athletic adolescents display healthier food habits than non-athletic adolescents: this result supports the idea that healthy behavior tends to cluster and suggests that prevention programs among this age group should target simultaneously both sports activity and food habits.

Properties of functional brain networks correlate with frequency of psychogenic non-epileptic seizures.

Abnormalities in the topology of brain networks may be an important feature and etiological factor for psychogenic non-epileptic seizures (PNES). To explore this possibility, we applied a graph theoretical approach to functional networks based on resting state EEGs from 13 PNES patients and 13 age- and gender-matched controls. The networks were extracted from Laplacian-transformed time-series by a cross-correlation method. PNES patients showed close to normal local and global connectivity and small-world structure, estimated with clustering coefficient, modularity, global efficiency, and small-worldness (SW) metrics, respectively. Yet the number of PNES attacks per month correlated with a weakness of local connectedness and a skewed balance between local and global connectedness quantified with SW, all in EEG alpha band. In beta band, patients demonstrated above-normal resiliency, measured with assortativity coefficient, which also correlated with the frequency of PNES attacks. This interictal EEG phenotype may help improve differentiation between PNES and epilepsy. The results also suggest that local connectivity could be a target for therapeutic interventions in PNES. Selective modulation (strengthening) of local connectivity might improve the skewed balance between local and global connectivity and so prevent PNES events.

Predicting trabecular bone microdamage initiation and accumulation using a non-linear perfect damage model

Studies evaluating the mechanical behavior of the trabecular microstructure play an important role in our understanding of pathologies such as osteoporosis, and in increasing our understanding of bone fracture and bone adaptation. Understanding of such behavior in bone is important for predicting and providing early treatment of fractures. The objective of this study is to present a numerical model for studying the initiation and accumulation of trabecular bone microdamage in both the pre- and post-yield regions. A sub-region of human vertebral trabecular bone was analyzed using a uniformly loaded anatomically accurate microstructural three-dimensional finite element model. The evolution of trabecular bone microdamage was governed using a non-linear, modulus reduction, perfect damage approach derived from a generalized plasticity stress-strain law. The model introduced in this paper establishes a history of microdamage evolution in both the pre- and post-yield regions

Creation of an Age-Adjusted, Dual-Energy X-ray Absorptiometry-Derived Trabecular Bone Score Curve for the Lumbar Spine in Non-Hispanic US White Women.

The trabecular bone score (TBS, Med-Imaps, Pessac, France) is an index of bone microarchitecture texture extracted from anteroposterior dual-energy X-ray absorptiometry images of the spine. Previous studies have documented the ability of TBS of the spine to differentiate between women with and without fractures among age- and areal bone mineral density (aBMD)-matched controls, as well as to predict future fractures. In this cross-sectional analysis of data collected from 3 geographically dispersed facilities in the United States, we investigated age-related changes in the microarchitecture of lumbar vertebrae as assessed by TBS in a cohort of non-Hispanic US white American women. All subjects were 30 yr of age and older and had an L1-L4aBMDZ-score within ±2 SD of the population mean. Individuals were excluded if they had fractures, were on any osteoporosis treatment, or had any illness that would be expected to impact bone metabolism. All data were extracted from Prodigy dual-energy X-ray absorptiometry devices (GE-Lunar, Madison, WI). Cross-calibrations between the 3 participating centers were performed for TBS and aBMD. aBMD and TBS were evaluated for spine L1-L4 but also for all other possible vertebral combinations. To validate the cohort, a comparison between the aBMD normative data of our cohort and US non-Hispanic white Lunar data provided by the manufacturer was performed. A database of 619 non-Hispanic US white women, ages 30-90 yr, was created. aBMD normative data obtained from this cohort were not statistically different from the non-Hispanic US white Lunar normative data provided by the manufacturer (p = 0.30). This outcome thereby indirectly validates our cohort. TBS values at L1-L4 were weakly inversely correlated with body mass index (r = -0.17) and weight (r = -0.16) and not correlated with height. TBS values for all lumbar vertebral combinations decreased significantly with age. There was a linear decrease of 16.0% (-2.47 T-score) in TBS at L1-L4 between 45 and 90 yr of age (vs. -2.34 for aBMD). Microarchitectural loss rate increased after age 65 by 50% (-0.004 to -0.006). Similar results were obtained for other combinations of lumbar vertebra. TBS, an index of bone microarchitectural texture, decreases with advancing age in non-Hispanic US white women. Little change in TBS is observed between ages 30 and 45. Thereafter, a progressive decrease is observed with advancing age. The changes we observed in these American women are similar to that previously reported for a French population of white women (r(2) > 0.99). This reference database will facilitate the use of TBS to assess bone microarchitectural deterioration in clinical practice.