Automated quantitative pupillometry for the prognostication of coma after cardiac arrest.

BACKGROUND: Sedation and therapeutic hypothermia (TH) delay neurological responses and might reduce the accuracy of clinical examination to predict outcome after cardiac arrest (CA). We examined the accuracy of quantitative pupillary light reactivity (PLR), using an automated infrared pupillometry, to predict outcome of post-CA coma in comparison to standard PLR, EEG, and somato-sensory evoked potentials (SSEP). METHODS: We prospectively studied over a 1-year period (June 2012-June 2013) 50 consecutive comatose CA patients treated with TH (33 °C, 24 h). Quantitative PLR (expressed as the % of pupillary response to a calibrated light stimulus) and standard PLR were measured at day 1 (TH and sedation; on average 16 h after CA) and day 2 (normothermia, off sedation: on average 46 h after CA). Neurological outcome was assessed at 90 days with Cerebral Performance Categories (CPC), dichotomized as good (CPC 1-2) versus poor (CPC 3-5). Predictive performance was analyzed using area under the ROC curves (AUC). RESULTS: Patients with good outcome [n = 23 (46 %)] had higher quantitative PLR than those with poor outcome [n = 27; 16 (range 9-23) vs. 10 (1-30) % at day 1, and 20 (13-39) vs. 11 (1-55) % at day 2, both p < 0.001]. Best cut-off for outcome prediction of quantitative PLR was <13 %. The AUC to predict poor outcome was higher for quantitative than for standard PLR at both time points (day 1, 0.79 vs. 0.56, p = 0.005; day 2, 0.81 vs. 0.64, p = 0.006). Prognostic accuracy of quantitative PLR was comparable to that of EEG and SSEP (0.81 vs. 0.80 and 0.73, respectively, both p > 0.20). CONCLUSIONS: Quantitative PLR is more accurate than standard PLR in predicting outcome of post-anoxic coma, irrespective of temperature and sedation, and has comparable prognostic accuracy than EEG and SSEP.

Analysis of acute brain slices by electron microscopy: A correlative light-electron microscopy workflow based on Tokuyasu cryo-sectioning.

Acute brain slices are slices of brain tissue that are kept vital in vitro for further recordings and analyses. This tool is of major importance in neurobiology and allows the study of brain cells such as microglia, astrocytes, neurons and their inter/intracellular communications via ion channels or transporters. In combination with light/fluorescence microscopies, acute brain slices enable the ex vivo analysis of specific cells or groups of cells inside the slice, e.g. astrocytes. To bridge ex vivo knowledge of a cell with its ultrastructure, we developed a correlative microscopy approach for acute brain slices. The workflow begins with sampling of the tissue and precise trimming of a region of interest, which contains GFP-tagged astrocytes that can be visualised by fluorescence microscopy of ultrathin sections. The astrocytes and their surroundings are then analysed by high resolution scanning transmission electron microscopy (STEM). An important aspect of this workflow is the modification of a commercial cryo-ultramicrotome to observe the fluorescent GFP signal during the trimming process. It ensured that sections contained at least one GFP astrocyte. After cryo-sectioning, a map of the GFP-expressing astrocytes is established and transferred to correlation software installed on a focused ion beam scanning electron microscope equipped with a STEM detector. Next, the areas displaying fluorescence are selected for high resolution STEM imaging. An overview area (e.g. a whole mesh of the grid) is imaged with an automated tiling and stitching process. In the final stitched image, the local organisation of the brain tissue can be surveyed or areas of interest can be magnified to observe fine details, e.g. vesicles or gold labels on specific proteins. The robustness of this workflow is contingent on the quality of sample preparation, based on Tokuyasu's protocol. This method results in a reasonable compromise between preservation of morphology and maintenance of antigenicity. Finally, an important feature of this approach is that the fluorescence of the GFP signal is preserved throughout the entire preparation process until the last step before electron microscopy.

AWSum-Combining Classification with Knowledge Aquisition

Many classifiers achieve high levels of accuracy but have limited applicability in real world situations because they do not lead to a greater understanding or insight into the^way features influence the classification. In areas such as health informatics a classifier that clearly identifies the influences on classification can be used to direct research and formulate interventions. This research investigates the practical applications of Automated Weighted Sum, (AWSum), a classifier that provides accuracy comparable to other techniques whilst providing insight into the data. This is achieved by calculating a weight for each feature value that represents its influence on the class value. The merits of this approach in classification and insight are evaluated on a Cystic Fibrosis and Diabetes datasets with positive results.

Automated analysis of background EEG and reactivity during therapeutic hypothermia in comatose patients after cardiac arrest.

Visual analysis of electroencephalography (EEG) background and reactivity during therapeutic hypothermia provides important outcome information, but is time-consuming and not always consistent between reviewers. Automated EEG analysis may help quantify the brain damage. Forty-six comatose patients in therapeutic hypothermia, after cardiac arrest, were included in the study. EEG background was quantified with burst-suppression ratio (BSR) and approximate entropy, both used to monitor anesthesia. Reactivity was detected through change in the power spectrum of signal before and after stimulation. Automatic results obtained almost perfect agreement (discontinuity) to substantial agreement (background reactivity) with a visual score from EEG-certified neurologists. Burst-suppression ratio was more suited to distinguish continuous EEG background from burst-suppression than approximate entropy in this specific population. Automatic EEG background and reactivity measures were significantly related to good and poor outcome. We conclude that quantitative EEG measurements can provide promising information regarding current state of the patient and clinical outcome, but further work is needed before routine application in a clinical setting.

AssociationViewer: a scalable and integrated software tool for visualization of large-scale variation data in genomic context.

SUMMARY: We present a tool designed for visualization of large-scale genetic and genomic data exemplified by results from genome-wide association studies. This software provides an integrated framework to facilitate the interpretation of SNP association studies in genomic context. Gene annotations can be retrieved from Ensembl, linkage disequilibrium data downloaded from HapMap and custom data imported in BED or WIG format. AssociationViewer integrates functionalities that enable the aggregation or intersection of data tracks. It implements an efficient cache system and allows the display of several, very large-scale genomic datasets. AVAILABILITY: The Java code for AssociationViewer is distributed under the GNU General Public Licence and has been tested on Microsoft Windows XP, MacOSX and GNU/Linux operating systems. It is available from the SourceForge repository. This also includes Java webstart, documentation and example datafiles.

Reproducibility of 3D free-breathing magnetic resonance coronary vessel wall imaging.

AIMS: Although the coronary artery vessel wall can be imaged non-invasively using magnetic resonance imaging (MRI), the in vivo reproducibility of wall thickness measures has not been previously investigated. Using a refined magnetization preparation scheme, we sought to assess the reproducibility of three-dimensional (3D) free-breathing black-blood coronary MRI in vivo. METHODS AND RESULTS: MRI vessel wall scans parallel to the right coronary artery (RCA) were obtained in 18 healthy individuals (age range 25-43, six women), with no known history of coronary artery disease, using a 3D dual-inversion navigator-gated black-blood spiral imaging sequence. Vessel wall scans were repeated 1 month later in eight subjects. The visible vessel wall segment and the wall thickness were quantitatively assessed using a semi-automatic tool and the intra-observer, inter-observer, and inter-scan reproducibilities were determined. The average imaged length of the RCA vessel wall was 44.5+/-7 mm. The average wall thickness was 1.6+/-0.2 mm. There was a highly significant intra-observer (r=0.97), inter-observer (r=0.94), and inter-scan (r=0.90) correlation for wall thickness (all P<0.001). There was also a significant agreement for intra-observer, inter-observer, and inter-scan measurements on Bland-Altman analysis. The intra-class correlation coefficients for intra-observer (r=0.97), inter-observer (r=0.92), and inter-scan (r=0.86) analyses were also excellent. CONCLUSION: The use of black-blood free-breathing 3D MRI in conjunction with semi-automated analysis software allows for reproducible measurements of right coronary arterial vessel-wall thickness. This technique may be well-suited for non-invasive longitudinal studies of coronary atherosclerosis.

Performance of an automated multiplex immunofluorescence assay for detection of Chlamydia trachomatis immunoglobulin G.

Chlamydia serology is indicated to investigate etiology of miscarriage, infertility, pelvic inflammatory disease, and ectopic pregnancy. Here, we assessed the reliability of a new automated-multiplex immunofluorescence assay (InoDiag test) to detect specific anti-C. trachomatis immunoglobulin G. Considering immunofluorescence assay (IF) as gold standard, InoDiag tests exhibited similar sensitivities (65.5%) but better specificities (95.1%-98%) than enzyme-linked immunosorbent assays (ELISAs). InoDiag tests demonstrated similar or lower cross-reactivity rates when compared to ELISA or IF.

Discordant prevalence of hypertension using two different automated blood pressure measurement devices: a population-based study in Dar es Salaam (Tanzania).

OBJECTIVE: The estimation of blood pressure is dependent on the accuracy of the measurement devices. We compared blood pressure readings obtained with an automated oscillometric arm-cuff device and with an automated oscillometric wrist-cuff device and then assessed the prevalence of defined blood pressure categories. METHODS: Within a population-based survey in Dar es Salaam (Tanzania), we selected all participants with a blood pressure >/= 160/95 mmHg (n=653) and a random sample of participants with blood pressure <160/95 mmHg (n=662), based on the first blood pressure reading. Blood pressure was reassessed 2 years later for 464 and 410 of the participants, respectively. In these 874 subjects, we compared the prevalence of blood pressure categories as estimated with each device. RESULTS: Overall, the wrist device gave higher blood pressure readings than the arm device (difference in systolic/diastolic blood pressure: 6.3 +/- 17.3/3.7 +/- 11.8 mmHg, P<0.001). However, the arm device tended to give lower readings than the wrist device for high blood pressure values. The prevalence of blood pressure categories differed substantially depending on which device was used, 29% and 14% for blood pressure <120/80 mmHg (arm device versus wrist device, respectively), 30% and 33% for blood pressure 120-139/80-89 mmHg, 17% and 26% for blood pressure 140-159/90-99 mmHg, 12% and 13% for blood pressure 160-179/100-109 mmHg and 13% and 14% for blood pressure >/= 180/110 mmHg. CONCLUSIONS: A large discrepancy in the estimated prevalence of blood pressure categories was observed using two different automatic measurement devices. This emphasizes that prevalence estimates based on automatic devices should be considered with caution.

Transient Ischemic Dilation (TID) ratio measurement during Rb-82 cardiac PET: Comparison between three different software packages.

Background: TIDratio indirectly reflects myocardial ischemia and is correlated with cardiacprognosis. We aimed at comparing the influence of three different softwarepackages for the assessment of TID using Rb-82 cardiac PET/CT. Methods: Intotal, data of 30 patients were used based on normal myocardial perfusion(SSS<3 and SRS<3) and stress myocardial blood flow 2mL/min/g)assessed by Rb-82 cardiac PET/CT. After reconstruction using 2D OSEM (2Iterations, 28 subsets), 3-D filtering (Butterworth, order=10, ωc=0.5), data were automatically processed, and then manually processed fordefining identical basal and apical limits on both stress and rest images.TIDratio were determined with Myometrix®, ECToolbox® and QGS®software packages. Comparisons used ANOVA, Student t-tests and Lin concordancetest (ρc). Results: All of the 90 processings were successfullyperformed. TID ratio were not statistically different between software packageswhen data were processed automatically (P=0.2) or manually (P=0.17). There was a slight, butsignificant relative overestimation of TID with automatic processing incomparison to manual processing using ECToolbox® (1.07 ± 0.13 vs 1.0± 0.13, P=0.001)and Myometrix® (1.07 ± 0.15 vs 1.01 ± 0.11, P=0.003) but not using QGS®(1.02 ±0.12 vs 1.05 ± 0.11, P=0.16). The best concordance was achieved between ECToolbox®and Myometrix® manual (ρc=0.67) processing.Conclusion: Using automatic or manual mode TID estimation was not significantlyinfluenced by software type. Using Myometrix® or ECToolbox®TID was significantly different between automatic and manual processing, butnot using QGS®. Software package should be account for when definingTID normal reference limits, as well as when used in multicenter studies. QGS®software seemed to be the most operator-independent software package, whileECToolbox® and Myometrix® produced the closest results.

Automated DNA extraction using the QIAsymphony platform: Estimation of DNA recovery from simulated forensic stains

The aim of this study was to evaluate the forensic protocol recently developed by Qiagen for the QIAsymphony automated DNA extraction platform. Samples containing low amounts of DNA were specifically considered, since they represent the majority of samples processed in our laboratory. The analysis of simulated blood and saliva traces showed that the highest DNA yields were obtained with the maximal elution volume available for the forensic protocol, that is 200 ml. Resulting DNA extracts were too diluted for successful DNA profiling and required a concentration. This additional step is time consuming and potentially increases inversion and contamination risks. The 200 ml DNA extracts were concentrated to 25 ml, and the DNA recovery estimated with real-time PCR as well as with the percentage of SGM Plus alleles detected. Results using our manual protocol, based on the QIAamp DNA mini kit, and the automated protocol were comparable. Further tests will be conducted to determine more precisely DNA recovery, contamination risk and PCR inhibitors removal, once a definitive procedure, allowing the concentration of DNA extracts from low yield samples, will be available for the QIAsymphony.

TCRep 3D: an automated in silico approach to study the structural properties of TCR repertoires.

TCRep 3D is an automated systematic approach for TCR-peptide-MHC class I structure prediction, based on homology and ab initio modeling. It has been considerably generalized from former studies to be applicable to large repertoires of TCR. First, the location of the complementary determining regions of the target sequences are automatically identified by a sequence alignment strategy against a database of TCR Vα and Vβ chains. A structure-based alignment ensures automated identification of CDR3 loops. The CDR are then modeled in the environment of the complex, in an ab initio approach based on a simulated annealing protocol. During this step, dihedral restraints are applied to drive the CDR1 and CDR2 loops towards their canonical conformations, described by Al-Lazikani et. al. We developed a new automated algorithm that determines additional restraints to iteratively converge towards TCR conformations making frequent hydrogen bonds with the pMHC. We demonstrated that our approach outperforms popular scoring methods (Anolea, Dope and Modeller) in predicting relevant CDR conformations. Finally, this modeling approach has been successfully applied to experimentally determined sequences of TCR that recognize the NY-ESO-1 cancer testis antigen. This analysis revealed a mechanism of selection of TCR through the presence of a single conserved amino acid in all CDR3β sequences. The important structural modifications predicted in silico and the associated dramatic loss of experimental binding affinity upon mutation of this amino acid show the good correspondence between the predicted structures and their biological activities. To our knowledge, this is the first systematic approach that was developed for large TCR repertoire structural modeling.

A post-processing pipeline to reconstruct the developing fetal brain using low-resolution MRI

Introduction. Development of the fetal brain surfacewith concomitant gyrification is one of the majormaturational processes of the human brain. Firstdelineated by postmortem studies or by ultrasound, MRIhas recently become a powerful tool for studying in vivothe structural correlates of brain maturation. However,the quantitative measurement of fetal brain developmentis a major challenge because of the movement of the fetusinside the amniotic cavity, the poor spatial resolution,the partial volume effect and the changing appearance ofthe developing brain. Today extensive efforts are made todeal with the âeurooepost-acquisitionâeuro reconstruction ofhigh-resolution 3D fetal volumes based on severalacquisitions with lower resolution (Rousseau, F., 2006;Jiang, S., 2007). We here propose a framework devoted tothe segmentation of the basal ganglia, the gray-whitetissue segmentation, and in turn the 3D corticalreconstruction of the fetal brain. Method. Prenatal MRimaging was performed with a 1-T system (GE MedicalSystems, Milwaukee) using single shot fast spin echo(ssFSE) sequences in fetuses aged from 29 to 32gestational weeks (slice thickness 5.4mm, in planespatial resolution 1.09mm). For each fetus, 6 axialvolumes shifted by 1 mm were acquired (about 1 min pervolume). First, each volume is manually segmented toextract fetal brain from surrounding fetal and maternaltissues. Inhomogeneity intensity correction and linearintensity normalization are then performed. A highspatial resolution image of isotropic voxel size of 1.09mm is created for each fetus as previously published byothers (Rousseau, F., 2006). B-splines are used for thescattered data interpolation (Lee, 1997). Then, basalganglia segmentation is performed on this superreconstructed volume using active contour framework witha Level Set implementation (Bach Cuadra, M., 2010). Oncebasal ganglia are removed from the image, brain tissuesegmentation is performed (Bach Cuadra, M., 2009). Theresulting white matter image is then binarized andfurther given as an input in the Freesurfer software(http://surfer.nmr.mgh.harvard.edu/) to provide accuratethree-dimensional reconstructions of the fetal brain.Results. High-resolution images of the cerebral fetalbrain, as obtained from the low-resolution acquired MRI,are presented for 4 subjects of age ranging from 29 to 32GA. An example is depicted in Figure 1. Accuracy in theautomated basal ganglia segmentation is compared withmanual segmentation using measurement of Dice similarity(DSI), with values above 0.7 considering to be a verygood agreement. In our sample we observed DSI valuesbetween 0.785 and 0.856. We further show the results ofgray-white matter segmentation overlaid on thehigh-resolution gray-scale images. The results arevisually checked for accuracy using the same principlesas commonly accepted in adult neuroimaging. Preliminary3D cortical reconstructions of the fetal brain are shownin Figure 2. Conclusion. We hereby present a completepipeline for the automated extraction of accuratethree-dimensional cortical surface of the fetal brain.These results are preliminary but promising, with theultimate goal to provide âeurooemovieâeuro of the normal gyraldevelopment. In turn, a precise knowledge of the normalfetal brain development will allow the quantification ofsubtle and early but clinically relevant deviations.Moreover, a precise understanding of the gyraldevelopment process may help to build hypotheses tounderstand the pathogenesis of several neurodevelopmentalconditions in which gyrification have been shown to bealtered (e.g. schizophrenia, autismâeuro¦). References.Rousseau, F. (2006), 'Registration-Based Approach forReconstruction of High-Resolution In Utero Fetal MR Brainimages', IEEE Transactions on Medical Imaging, vol. 13,no. 9, pp. 1072-1081. Jiang, S. (2007), 'MRI of MovingSubjects Using Multislice Snapshot Images With VolumeReconstruction (SVR): Application to Fetal, Neonatal, andAdult Brain Studies', IEEE Transactions on MedicalImaging, vol. 26, no. 7, pp. 967-980. Lee, S. (1997),'Scattered data interpolation with multilevel B-splines',IEEE Transactions on Visualization and Computer Graphics,vol. 3, no. 3, pp. 228-244. Bach Cuadra, M. (2010),'Central and Cortical Gray Mater Segmentation of MagneticResonance Images of the Fetal Brain', ISMRM Conference.Bach Cuadra, M. (2009), 'Brain tissue segmentation offetal MR images', MICCAI.

How to measure cortical folding from MR images: a step-by-step tutorial to compute local gyrification index.

Cortical folding (gyrification) is determined during the first months of life, so that adverse events occurring during this period leave traces that will be identifiable at any age. As recently reviewed by Mangin and colleagues(2), several methods exist to quantify different characteristics of gyrification. For instance, sulcal morphometry can be used to measure shape descriptors such as the depth, length or indices of inter-hemispheric asymmetry(3). These geometrical properties have the advantage of being easy to interpret. However, sulcal morphometry tightly relies on the accurate identification of a given set of sulci and hence provides a fragmented description of gyrification. A more fine-grained quantification of gyrification can be achieved with curvature-based measurements, where smoothed absolute mean curvature is typically computed at thousands of points over the cortical surface(4). The curvature is however not straightforward to comprehend, as it remains unclear if there is any direct relationship between the curvedness and a biologically meaningful correlate such as cortical volume or surface. To address the diverse issues raised by the measurement of cortical folding, we previously developed an algorithm to quantify local gyrification with an exquisite spatial resolution and of simple interpretation. Our method is inspired of the Gyrification Index(5), a method originally used in comparative neuroanatomy to evaluate the cortical folding differences across species. In our implementation, which we name local Gyrification Index (lGI(1)), we measure the amount of cortex buried within the sulcal folds as compared with the amount of visible cortex in circular regions of interest. Given that the cortex grows primarily through radial expansion(6), our method was specifically designed to identify early defects of cortical development. In this article, we detail the computation of local Gyrification Index, which is now freely distributed as a part of the FreeSurfer Software (http://surfer.nmr.mgh.harvard.edu/, Martinos Center for Biomedical Imaging, Massachusetts General Hospital). FreeSurfer provides a set of automated reconstruction tools of the brain's cortical surface from structural MRI data. The cortical surface extracted in the native space of the images with sub-millimeter accuracy is then further used for the creation of an outer surface, which will serve as a basis for the lGI calculation. A circular region of interest is then delineated on the outer surface, and its corresponding region of interest on the cortical surface is identified using a matching algorithm as described in our validation study(1). This process is repeatedly iterated with largely overlapping regions of interest, resulting in cortical maps of gyrification for subsequent statistical comparisons (Fig. 1). Of note, another measurement of local gyrification with a similar inspiration was proposed by Toro and colleagues(7), where the folding index at each point is computed as the ratio of the cortical area contained in a sphere divided by the area of a disc with the same radius. The two implementations differ in that the one by Toro et al. is based on Euclidian distances and thus considers discontinuous patches of cortical area, whereas ours uses a strict geodesic algorithm and include only the continuous patch of cortical area opening at the brain surface in a circular region of interest.