Automated motion analysis of bony joint structures from dynamic computer tomography images: A multi-atlas approach

Dynamic computer tomography (CT) is an emerging modality to analyze in-vivo joint kinematics at the bone level, but it requires manual bone segmentation and, in some instances, landmark identification. The objective of this study is to present an automated workflow for the assessment of three-dimensional in vivo joint kinematics from dynamic musculoskeletal CT images. The proposed method relies on a multi-atlas, multi-label segmentation and landmark propagation framework to extract bony structures and detect anatomical landmarks on the CT dataset. The segmented structures serve as regions of interest for the subsequent motion estimation across the dynamic sequence. The landmarks are propagated across the dynamic sequence for the construction of bone embedded reference frames from which kinematic parameters are estimated. We applied our workflow on dynamic CT images obtained from 15 healthy subjects on two different joints: thumb base (n = 5) and knee (n = 10). The proposed method resulted in segmentation accuracies of 0.90 ± 0.01 for the thumb dataset and 0.94 ± 0.02 for the knee as measured by the Dice score coefficient. In terms of motion estimation, mean differences in cardan angles between the automated algorithm and manual segmentation, and landmark identification performed by an expert were below 1◦. Intraclass correlation (ICC) between cardan angles from the algorithm and results from expert manual landmarks ranged from 0.72 to 0.99 for all joints across all axes. The proposed automated method resulted in reproducible and reliable measurements, enabling the assessment of joint kinematics using 4DCT in clinical routine

Simultaneous detection of bluetongue virus RNA, internal control GAPDH mRNA, and external control synthetic RNA by multiplex real-time PCR.

&lt;p&gt;Bluetongue is an insect-borne disease of domestic and wild ruminants that requires strict monitoring by sensitive, reproducible and robust methods. Real-time reverse transcription polymerase chain reaction (RT-qPCR) analysis has become the method of choice for routine viral diagnosis. As false-negative test results can have serious implications; an internal/external control system should be incorporated in each analysis to detect RT-qPCR failure due to poor sample quality, improper nucleic acid extraction and/or PCR inhibition. To increase the diagnostic capacity and reduce costs, it is recommended to use a multiplex strategy which enables the amplification of multiple targets in a single reaction. This chapter describes the application of a triplex RT-qPCR for the simultaneous detection of bluetongue viral RNA, an internal control and an external control. The primer and probe sequences of the BTV RT-qPCR were taken from Toussaint et al. (J Virol Methods 140:115-123, 2007), whereas the internal and external RT-qPCRs were specifically designed to detect endogenous glyceraldehyde-3-phosphate dehydrogenase mRNA and a synthetic RNA, respectively. To maximize the sensitivity of the assay, the primer concentrations of the internal/external control reactions were limited and the amount of Taq DNA polymerase was increased. A comparison of the singleplex versus triplex RT-qPCR indicated that the triplex RT-qPCR exhibits a higher analytical sensitivity. Due to the incorporation of the internal/external control system, the triplex RT-qPCR allows an even more reliable and rapid diagnosis of bluetongue than the previously described singleplex RT-qPCR (J Virol Methods 140:115-123, 2007).&lt;/p&gt;</p

Infection expérimentale de veaux par le virus de la fièvre catarrhale ovine de sérotype 8

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Emergence of bluetongue serotypes in Europe, part 1: description and validation of four real-time RT-PCR assays for the serotyping of bluetongue viruses BTV-1, BTV-6, BTV-8 and BTV-11.

&lt;p&gt;The control of bluetongue virus (BTV) in Central-Western Europe is greatly complicated by the coexistence of several BTV serotypes. Rapid, sensitive and specific assays are therefore needed to correctly identify the currently circulating BTV serotypes in field samples. In the present study, four serotype-specific real-time RT-PCR assays (RT-qPCR) are described for the detection of the BTV-1, BTV-6, BTV-8 and BTV-11 serotypes. The analytical sensitivity of the BTV-1/S2, BTV-6/S2, BTV-8/S2 and BTV-11/S2 serotype-specific RT-qPCR assays is comparable to the earlier described serogroup-specific pan-BTV/S5 RT-qPCR assay. In silico and in vitro analyses indicated that none of the assays cross-react with viruses which are symptomatically or genetically related to BTV and only detect the intended BTV serotypes. All assays exhibited a linear range of at least 0.05-3.80 log(10) TCID(50) ml(-1) and a PCR-efficiency approaching the ideal amplification factor of two per PCR cycle. Both intra- and inter-run variations were found to be low with a total coefficient of variation of 1-2% for clear positive samples and &lt;10% for very weak positive samples. Finally, the performance of the described assays was compared with commercially available kits for the detection of BTV-1, BTV-6 and BTV-8. Three in-house assays gave exactly the same diagnostic result (positive/negative) as the commercial assays and can thus be used interchangeably. Together with the earlier described serogroup-specific pan-BTV/S5, the serotype-specific RT-qPCR assays form a flexible and properly validated set of tools to detect and differentiate the BTV serotypes currently circulating in Central-Western Europe.&lt;/p&gt;</p

Emergence of Bluetongue Virus Serotypes in Europe. Part I. Description and Validation of Four Real-Time RT-PCR Assays

Resumen en inglès, ver archivo PD

A proposed validation method for automated nucleic acid extraction and RT-qPCR analysis: an example using Bluetongue virus.

&lt;p&gt;This study proposes a validation strategy for an automated extraction procedure, followed by RT-qPCR analysis. To avoid false-negative results, a triplex RT-qPCR was used which detects the target viral RNA, an internal and an external control. The methods to determine the validation parameters such as linearity, efficiency, analytical sensitivity, analytical specificity and intra- and interrun variability are described in detail. Special attention is given to the analytical sensitivity, which is determined by probit analysis. The limit of detection was set at the input concentration resulting in a positive result in 95% of the repeats. The intra- and interrun variability was analysed profoundly by testing samples covering a broad range of viral loads, from strong positive to weak positive. To increase the diagnostic capacity, the extraction protocol was automated with a JANUS Automated Workstation (PerkinElmer, Waltham, MA), which can extract 186 samples in 2h and 30 min. The automation of the extraction protocol implied some additional validation parameters to be determined such as position-effect, absence of cross-contamination and comparison with the manual protocol. These parameters give essential information about the performance of the robot and are of great importance when the automated assay is used in an accreditation system.&lt;/p&gt;</p