Diffusion-weighted MR imaging in musculoskeletal diseases: Current concepts.

MR imaging is currently regarded as a pivotal technique for the assessment of a variety of musculoskeletal conditions. Diffusion-weighted MR imaging (DWI) is a relatively recent sequence that provides information on the degree of cellularity of lesions. Apparent diffusion coefficient (ADC) value provides information on the movement of water molecules outside the cells. The literature contains many studies that have evaluated the role of DWI in musculoskeletal diseases. However, to date they yielded conflicting results on the use and the diagnostic capabilities of DWI in the area of musculoskeletal diseases. However, many of them have showed that DWI is a useful technique for the evaluation of the extent of the disease in a subset of musculoskeletal cancers. In terms of tissue characterization, DWI may be an adjunct to the more conventional MR imaging techniques but should be interpreted along with the signal of the lesion as observed on conventional sequences, especially in musculoskeletal cancers. Regarding the monitoring of response to therapy in cancer or inflammatory disease, the use of ADC value may represent a more reliable additional tool but must be compared to the initial ADC value of the lesions along with the knowledge of the actual therapy.

Single breath-hold 3D measurement of left atrial volume using compressed sensing cardiovascular magnetic resonance and a non-model-based reconstruction approach.

BACKGROUND: Left atrial (LA) dilatation is associated with a large variety of cardiac diseases. Current cardiovascular magnetic resonance (CMR) strategies to measure LA volumes are based on multi-breath-hold multi-slice acquisitions, which are time-consuming and susceptible to misregistration. AIM: To develop a time-efficient single breath-hold 3D CMR acquisition and reconstruction method to precisely measure LA volumes and function. METHODS: A highly accelerated compressed-sensing multi-slice cine sequence (CS-cineCMR) was combined with a non-model-based 3D reconstruction method to measure LA volumes with high temporal and spatial resolution during a single breath-hold. This approach was validated in LA phantoms of different shapes and applied in 3 patients. In addition, the influence of slice orientations on accuracy was evaluated in the LA phantoms for the new approach in comparison with a conventional model-based biplane area-length reconstruction. As a reference in patients, a self-navigated high-resolution whole-heart 3D dataset (3D-HR-CMR) was acquired during mid-diastole to yield accurate LA volumes. RESULTS: Phantom studies. LA volumes were accurately measured by CS-cineCMR with a mean difference of -4.73 ± 1.75 ml (-8.67 ± 3.54%, r2 = 0.94). For the new method the calculated volumes were not significantly different when different orientations of the CS-cineCMR slices were applied to cover the LA phantoms. Long-axis "aligned" vs "not aligned" with the phantom long-axis yielded similar differences vs the reference volume (-4.87 ± 1.73 ml vs. -4.45 ± 1.97 ml, p = 0.67) and short-axis "perpendicular" vs. "not-perpendicular" with the LA long-axis (-4.72 ± 1.66 ml vs. -4.75 ± 2.13 ml; p = 0.98). The conventional bi-plane area-length method was susceptible for slice orientations (p = 0.0085 for the interaction of "slice orientation" and "reconstruction technique", 2-way ANOVA for repeated measures). To use the 3D-HR-CMR as the reference for LA volumes in patients, it was validated in the LA phantoms (mean difference: -1.37 ± 1.35 ml, -2.38 ± 2.44%, r2 = 0.97). Patient study: The CS-cineCMR LA volumes of the mid-diastolic frame matched closely with the reference LA volume (measured by 3D-HR-CMR) with a difference of -2.66 ± 6.5 ml (3.0% underestimation; true LA volumes: 63 ml, 62 ml, and 395 ml). Finally, a high intra- and inter-observer agreement for maximal and minimal LA volume measurement is also shown. CONCLUSIONS: The proposed method combines a highly accelerated single-breathhold compressed-sensing multi-slice CMR technique with a non-model-based 3D reconstruction to accurately and reproducibly measure LA volumes and function.

Mapping Bias Overestimates Reference Allele Frequencies at the HLA Genes in the 1000 Genomes Project Phase I Data.

Next-generation sequencing (NGS) technologies have become the standard for data generation in studies of population genomics, as the 1000 Genomes Project (1000G). However, these techniques are known to be problematic when applied to highly polymorphic genomic regions, such as the human leukocyte antigen (HLA) genes. Because accurate genotype calls and allele frequency estimations are crucial to population genomics analyses, it is important to assess the reliability of NGS data. Here, we evaluate the reliability of genotype calls and allele frequency estimates of the single-nucleotide polymorphisms (SNPs) reported by 1000G (phase I) at five HLA genes (HLA-A, -B, -C, -DRB1, and -DQB1). We take advantage of the availability of HLA Sanger sequencing of 930 of the 1092 1000G samples and use this as a gold standard to benchmark the 1000G data. We document that 18.6% of SNP genotype calls in HLA genes are incorrect and that allele frequencies are estimated with an error greater than ±0.1 at approximately 25% of the SNPs in HLA genes. We found a bias toward overestimation of reference allele frequency for the 1000G data, indicating mapping bias is an important cause of error in frequency estimation in this dataset. We provide a list of sites that have poor allele frequency estimates and discuss the outcomes of including those sites in different kinds of analyses. Because the HLA region is the most polymorphic in the human genome, our results provide insights into the challenges of using of NGS data at other genomic regions of high diversity.

LC-MS/MS based assay and reference intervals in children and adolescents for oxysterols elevated in Niemann-Pick diseases.

BACKGROUND: Niemann-Pick type C (NP-C) is a rare progressive neurodegenerative lipid storage disorder with heterogeneous clinical presentation and challenging diagnostic procedures. Recently oxysterols have been reported to be specific biomarkers for NP-C but knowledge on the intra-individual variation and on reference intervals in children and adolescents are lacking. METHODS: We established a LC-MS/MS assay to measure Cholestane-3β, 5α, 6β-triol (C-triol) and 7-Ketocholesterol (7-KC) following Steglich esterification. To assess reference intervals and intra-individual variation we determined oxysterols in 148 children and adolescents from 0 to 18 years and repeat measurements in 19 of them. RESULTS: The reported method is linear (r>0.99), sensitive (detection limit of 0.03 ng/mL [0.07 nM] for C-triol, and 0.54 ng/mL [1.35 nM] for 7-KC) and precise, with an intra-day imprecision of 4.8% and 4.1%, and an inter-day imprecision of 7.0% and 11.0% for C-triol (28 ng/ml, 67 nM) and 7-KC (32 ng/ml, 80 nM), respectively. Recoveries for 7-KC and C-triol range between 93% and 107%. The upper reference limit obtained for C-triol is 40.4 ng/mL (95% CI: 26.4-61.7 ng/mL, 96.0 nM, 95% CI: 62.8-146.7 nM) and 75.0 ng/mL for 7-KC (95% CI: 55.5-102.5 ng/mL, 187.2 nM, 95% CI: 138.53-255.8 nM), with no age or gender dependency. Both oxysterols have a broad intra-individual variation of 46%±23% for C-triol and 52%±29% for 7-KC. Nevertheless, all Niemann-Pick patients showed increased C-triol levels including Niemann-Pick type A and B patients. CONCLUSIONS: The LC-MS/MS assay is a robust assay to quantify C-triol and 7-KC in plasma with well documented reference intervals in children and adolescents to screen for NP-C in the pediatric population. In addition our results suggest that especially the C-triol is a biomarker for all three Niemann-Pick diseases.

Survey on current practices for neurological prognostication after cardiac arrest.

PURPOSE: To investigate current practices and timing of neurological prognostication in comatose cardiac arrest patients. METHODS: An anonymous questionnaire was distributed to the 8000 members of the European Society of Intensive Care Medicine during September and October 2012. The survey had 27 questions divided into three categories: background data, clinical data, decision-making and consequences. RESULTS: A total of 1025 respondents (13%) answered the survey with complete forms in more than 90%. Twenty per cent of respondents practiced outside of Europe. Overall, 22% answered that they had national recommendations, with the highest percentage in the Netherlands (>80%). Eighty-nine per cent used induced hypothermia (32-34 °C) for comatose cardiac arrest patients, while 11% did not. Twenty per cent had separate prognostication protocols for hypothermia patients. Seventy-nine per cent recognized that neurological examination alone is not enough to predict outcome and a similar number (76%) used additional methods. Intermittent electroencephalography (EEG), brain computed tomography (CT) scan and evoked potentials (EP) were considered most useful. Poor prognosis was defined as cerebral performance category (CPC) 3-5 (58%) or CPC 4-5 (39%) or other (3%). When prognosis was considered poor, 73% would actively withdraw intensive care while 20% would not and 7% were uncertain. CONCLUSION: National recommendations for neurological prognostication after cardiac arrest are uncommon and only one physician out of five uses a separate protocol for hypothermia treated patients. A neurological examination alone was considered insufficient to predict outcome in comatose patients and most respondents advocated a multimodal approach: EEG, brain CT and EP were considered most useful. Uncertainty regarding neurological prognostication and decisions on level of care was substantial.

Reasons to use e-cigarettes and associations with other substances among adolescents in Switzerland.

BACKGROUND: The objectives of this research were to describe the main reason(s) why adolescents use electronic cigarettes, to assess how e-cigarette experimenters and users differ based on personal characteristics, and to determine whether its use is associated with the use of other substances among a representative sample of youths in Switzerland. METHODS: A representative sample of 621 youths (308 females) was divided into never users (n=353), experimenters (Only once, n=120) and users (Several times, n=148) of e-cigarettes. Groups were compared on socio-demographic data and current smoking, alcohol misuse and cannabis use. Reasons for e-cigarette use were compared between experimenters and users. A multinomial regression was performed using never users as the reference category. RESULTS: Forty-three percent had ever tried e-cigarettes, and the main reason was curiosity. Compared to never users, experimenters were more likely to be out of school (Relative Risk Ratio [RRR]: 2.68) and to misuse alcohol (RRR: 2.08), while users were more likely to be male (RRR: 2.75), to be vocational students (RRR: 2.30) or out of school (RRR: 3.48) and to use any of the studied substances (tobacco, RRR: 5.26; alcohol misuse, RRR: 2.71; cannabis use, RRR: 30.2). CONCLUSIONS: Although often still part of adolescent experimentation, e-cigarettes are becoming increasingly popular among adolescents and they should become part of health providers' standard substance use screening. As health providers (and especially paediatricians) do not seem to have high levels of knowledge and, consequently, little comfort in discussing e-cigarettes, training in this domain should be available to them.

Implementation of bayesian therapeutic drug monitoring in modern patient care

The variability observed in drug exposure has a direct impact on the overall response to drug. The largest part of variability between dose and drug response resides in the pharmacokinetic phase, i.e. in the dose-concentration relationship. Among possibilities offered to clinicians, Therapeutic Drug Monitoring (TDM; Monitoring of drug concentration measurements) is one of the useful tool to guide pharmacotherapy. TDM aims at optimizing treatments by individualizing dosage regimens based on blood drug concentration measurement. Bayesian calculations, relying on population pharmacokinetic approach, currently represent the gold standard TDM strategy. However, it requires expertise and computational assistance, thus limiting its large implementation in routine patient care. The overall objective of this thesis was to implement robust tools to provide Bayesian TDM to clinician in modern routine patient care. To that endeavour, aims were (i) to elaborate an efficient and ergonomic computer tool for Bayesian TDM: EzeCHieL (ii) to provide algorithms for drug concentration Bayesian forecasting and software validation, relying on population pharmacokinetics (iii) to address some relevant issues encountered in clinical practice with a focus on neonates and drug adherence. First, the current stage of the existing software was reviewed and allows establishing specifications for the development of EzeCHieL. Then, in close collaboration with software engineers a fully integrated software, EzeCHieL, has been elaborated. EzeCHieL provides population-based predictions and Bayesian forecasting and an easy-to-use interface. It enables to assess the expectedness of an observed concentration in a patient compared to the whole population (via percentiles), to assess the suitability of the predicted concentration relative to the targeted concentration and to provide dosing adjustment. It allows thus a priori and a posteriori Bayesian drug dosing individualization. Implementation of Bayesian methods requires drug disposition characterisation and variability quantification trough population approach. Population pharmacokinetic analyses have been performed and Bayesian estimators have been provided for candidate drugs in population of interest: anti-infectious drugs administered to neonates (gentamicin and imipenem). Developed models were implemented in EzeCHieL and also served as validation tool in comparing EzeCHieL concentration predictions against predictions from the reference software (NONMEM®). Models used need to be adequate and reliable. For instance, extrapolation is not possible from adults or children to neonates. Therefore, this work proposes models for neonates based on the developmental pharmacokinetics concept. Patients' adherence is also an important concern for drug models development and for a successful outcome of the pharmacotherapy. A last study attempts to assess impact of routine patient adherence measurement on models definition and TDM interpretation. In conclusion, our results offer solutions to assist clinicians in interpreting blood drug concentrations and to improve the appropriateness of drug dosing in routine clinical practice.

Meeting report of the European mouse complex genetics network SYSGENET.

The second scientific meeting of the European systems genetics network for the study of complex genetic human disease using genetic reference populations (SYSGENET) took place at the Center for Cooperative Research in Biosciences in Bilbao, Spain, December 10-12, 2012. SYSGENET is funded by the European Cooperation in the Field of Scientific and Technological Research (COST) and represents a network of scientists in Europe that use mouse genetic reference populations (GRPs) to identify complex genetic factors influencing disease phenotypes (Schughart, Mamm Genome 21:331-336, 2010). About 50 researchers working in the field of systems genetics attended the meeting, which consisted of 27 oral presentations, a poster session, and a management committee meeting. Participants exchanged results, set up future collaborations, and shared phenotyping and data analysis methodologies. This meeting was particularly instrumental for conveying the current status of the US, Israeli, and Australian Collaborative Cross (CC) mouse GRP. The CC is an open source project initiated nearly a decade ago by members of the Complex Trait Consortium to aid the mapping of multigenetic traits (Threadgill, Mamm Genome 13:175-178, 2002). In addition, representatives of the International Mouse Phenotyping Consortium were invited to exchange ongoing activities between the knockout and complex genetics communities and to discuss and explore potential fields for future interactions.