Electrochemical simulation of phase I metabolism for 21 drugs using four different working electrodes in an automated screening setup with MS detection.

BACKGROUND Electrochemical conversion of xenobiotics has been shown to mimic human phase I metabolism for a few compounds. MATERIALS & METHODS Twenty-one compounds were analyzed with a semiautomated electrochemical setup and mass spectrometry detection. RESULTS The system was able to mimic some metabolic pathways, such as oxygen gain, dealkylation and deiodination, but many of the expected and known metabolites were not produced. CONCLUSION Electrochemical conversion is a useful approach for the preparative synthesis of some types of metabolites, but as a screening method for unknown phase I metabolites, the method is, in our opinion, inferior to incubation with human liver microsomes and in vivo experiments with laboratory animals, for example.

Image registration for triggered and non-triggered DTI of the human kidney: Reduced variability of diffusion parameter estimation

BACKGROUND: To investigate if non-rigid image-registration reduces motion artifacts in triggered and non-triggered diffusion tensor imaging (DTI) of native kidneys. A secondary aim was to determine, if improvements through registration allow for omitting respiratory-triggering. METHODS: Twenty volunteers underwent coronal DTI of the kidneys with nine b-values (10-700 s/mm2 ) at 3 Tesla. Image-registration was performed using a multimodal nonrigid registration algorithm. Data processing yielded the apparent diffusion coefficient (ADC), the contribution of perfusion (FP ), and the fractional anisotropy (FA). For comparison of the data stability, the root mean square error (RMSE) of the fitting and the standard deviations within the regions of interest (SDROI ) were evaluated. RESULTS: RMSEs decreased significantly after registration for triggered and also for non-triggered scans (P < 0.05). SDROI for ADC, FA, and FP were significantly lower after registration in both medulla and cortex of triggered scans (P < 0.01). Similarly the SDROI of FA and FP decreased significantly in non-triggered scans after registration (P < 0.05). RMSEs were significantly lower in triggered than in non-triggered scans, both with and without registration (P < 0.05). CONCLUSION: Respiratory motion correction by registration of individual echo-planar images leads to clearly reduced signal variations in renal DTI for both triggered and particularly non-triggered scans. Secondarily, the results suggest that respiratory-triggering still seems advantageous.J. Magn. Reson. Imaging 2014. (c) 2014 Wiley Periodicals, Inc.

Feasibility of automated slope III and Scond analysis in children.

BACKGROUND Multiple breath washout (MBW) derived Scond is an established index of ventilation inhomogeneity. Time-consuming post hoc calculations of the expirogram's slope of alveolar phase III (SIII) and the lack of available software hampered widespread application of Scond. METHODS Seventy-two school-aged children (45 with cystic fibrosis; CF) performed 3 nitrogen MBW. We tested a new automated algorithm for Scond analysis (Scondauto ) which comprised breath selection for SIII detection, calculation and reporting of test quality. We compared Scondauto to (i) standard Scond analysis (Scondmanual ) with manual breath selection and to (ii) pragmatic Scond analysis including all breaths (Scondall ). Primary outcomes were success rate and agreement between different Scond protocols, and Scond fitting quality (linear regression R(2) ). RESULTS Average Scondauto (0.06 for CF and 0.01 for controls) was not different from Scondmanual (0.06 for CF and 0.01 for controls) and showed comparable fitting quality (R(2) 0.53 for CF and 0.13 for controls vs. R(2) 0.54 for CF and 0.13 for controls). Scondall was similar in CF and controls but with inferior fitting quality compared to Scondauto and Scondmanual . CONCLUSIONS Automated Scond calculation is feasible and produces robust results comparable to the standard manual way of Scond calculation. This algorithm provides a valid, fast and objective tool for regular use, even in children. Pediatr Pulmonol. © 2014 Wiley Periodicals, Inc.

Semiautomatic Cochleostomy Target and Insertion Trajectory Planning for Minimally Invasive Cochlear Implantation

A major component of minimally invasive cochlear implantation is atraumatic scala tympani (ST) placement of the electrode array. This work reports on a semiautomatic planning paradigm that uses anatomical landmarks and cochlear surface models for cochleostomy target and insertion trajectory computation. The method was validated in a human whole head cadaver model (n = 10 ears). Cochleostomy targets were generated from an automated script and used for consecutive planning of a direct cochlear access (DCA) drill trajectory from the mastoid surface to the inner ear. An image-guided robotic system was used to perform both, DCA and cochleostomy drilling. Nine of 10 implanted specimens showed complete ST placement. One case of scala vestibuli insertion occurred due to a registration/drilling error of 0.79 mm. The presented approach indicates that a safe cochleostomy target and insertion trajectory can be planned using conventional clinical imaging modalities, which lack sufficient resolution to identify the basilar membrane.

Late cardiac sodium current can be assessed using automated patch-clamp

The cardiac late Na (+) current is generated by a small fraction of voltage-dependent Na (+) channels that undergo a conformational change to a burst-gating mode, with repeated openings and closures during the action potential (AP) plateau. Its magnitude can be augmented by inactivation-defective mutations, myocardial ischemia, or prolonged exposure to chemical compounds leading to drug-induced (di)-long QT syndrome, and results in an increased susceptibility to cardiac arrhythmias. Using CytoPatch™ 2 automated patch-clamp equipment, we performed whole-cell recordings in HEK293 cells stably expressing human Nav1.5, and measured the late Na (+) component as average current over the last 100 ms of 300 ms depolarizing pulses to -10 mV from a holding potential of -100 mV, with a repetition frequency of 0.33 Hz. Averaged values in different steady-state experimental conditions were further corrected by the subtraction of current average during the application of tetrodotoxin (TTX) 30 μM. We show that ranolazine at 10 and 30 μM in 3 min applications reduced the late Na (+) current to 75.0 ± 2.7% (mean ± SEM, n = 17) and 58.4 ± 3.5% ( n = 18) of initial levels, respectively, while a 5 min application of veratridine 1 μM resulted in a reversible current increase to 269.1 ± 16.1% ( n = 28) of initial values. Using fluctuation analysis, we observed that ranolazine 30 μM decreased mean open probability p from 0.6 to 0.38 without modifying the number of active channels n, while veratridine 1 μM increased n 2.5-fold without changing p. In human iPSC-derived cardiomyocytes, veratridine 1 μM reversibly increased APD90 2.12 ± 0.41-fold (mean ± SEM, n = 6). This effect is attributable to inactivation removal in Nav1.5 channels, since significant inhibitory effects on hERG current were detected at higher concentrations in hERG-expressing HEK293 cells, with a 28.9 ± 6.0% inhibition (mean ± SD, n = 10) with 50 μM veratridine.

Individual Video Training iVT - Development of a National Infrastructure for Video-Supported Learning

Introduction: Video‐Supported Learning is particularly effective when it comes to skills and behaviors. Video registration of patient‐physician interviews, class room instruction or practical skills allow it to learners themselves, their peers, and their tutors to assess the quality of the learner's performance, to give specific feedback, and to make suggestions for improvement. Methods: In Switzerland, four pedagogical universities and two medical faculties joined to initiate the development of a national infrastructure for Video Supported Learning. The goal was to have a system that is simple to use, has most steps automated, provides the videos over the Internet, and has a sophisticated access control. Together with SWITCH, the national IT‐Support‐Organisation for Swiss Universities, the program iVT (Individual Video Training) was developed by integrating two preexisting technologies. The first technology is SWITCHcast, a podcast system. With SWITCHcast, videos are automatically uploaded to a server as soon as the registration is over. There the videos are processed and converted to different formats. The second technology is the national Single Logon System AAI (Authentification and Authorization Infrastructure) that enables iVT to link each video with the corresponding learner. The learner starts the registration with his Single Logon. Thus, the video can unambiguously be assigned. Via his institution's Learning Management System (LMS), the learner can access his video and give access to his video to peers and tutors. Results: iVT is now used at all involved institutions. The system works flawlessly. In Bern, we use iVT for the communications skills training in the forth and sixth year. Since students meet with patient actors alone, iVT is also used to certify attendance. Students are encouraged to watch the videos of the interview and the feedback of the patient actor. The offer to discuss a video with a tutor was not used by the students. Discussion: We plan to expand the use of iVT by making peer assessment compulsory. To support this, annotation capabilities are currently added to iVT. We also want to use iVT in training of practical skills, again for self as well as for peer assessment.  At present, we use iVT for quality control of patient actor's performance.

3D morphometry using automated aortic segmentation in native MR angiography: an alternative to contrast enhanced MRA?

INTRODUCTION Native-MR angiography (N-MRA) is considered an imaging alternative to contrast enhanced MR angiography (CE-MRA) for patients with renal insufficiency. Lower intraluminal contrast in N-MRA often leads to failure of the segmentation process in commercial algorithms. This study introduces an in-house 3D model-based segmentation approach used to compare both sequences by automatic 3D lumen segmentation, allowing for evaluation of differences of aortic lumen diameters as well as differences in length comparing both acquisition techniques at every possible location. METHODS AND MATERIALS Sixteen healthy volunteers underwent 1.5-T-MR Angiography (MRA). For each volunteer, two different MR sequences were performed, CE-MRA: gradient echo Turbo FLASH sequence and N-MRA: respiratory-and-cardiac-gated, T2-weighted 3D SSFP. Datasets were segmented using a 3D model-based ellipse-fitting approach with a single seed point placed manually above the celiac trunk. The segmented volumes were manually cropped from left subclavian artery to celiac trunk to avoid error due to side branches. Diameters, volumes and centerline length were computed for intraindividual comparison. For statistical analysis the Wilcoxon-Signed-Ranked-Test was used. RESULTS Average centerline length obtained based on N-MRA was 239.0±23.4 mm compared to 238.6±23.5 mm for CE-MRA without significant difference (P=0.877). Average maximum diameter obtained based on N-MRA was 25.7±3.3 mm compared to 24.1±3.2 mm for CE-MRA (P<0.001). In agreement with the difference in diameters, volumes obtained based on N-MRA (100.1±35.4 cm(3)) were consistently and significantly larger compared to CE-MRA (89.2±30.0 cm(3)) (P<0.001). CONCLUSIONS 3D morphometry shows highly similar centerline lengths for N-MRA and CE-MRA, but systematically higher diameters and volumes for N-MRA.

Volumetric analysis of lung nodules in computed tomography (CT): comparison of two different segmentation algorithm softwares and two different reconstruction filters on automated volume calculation.

BACKGROUND A precise detection of volume change allows for better estimating the biological behavior of the lung nodules. Postprocessing tools with automated detection, segmentation, and volumetric analysis of lung nodules may expedite radiological processes and give additional confidence to the radiologists. PURPOSE To compare two different postprocessing software algorithms (LMS Lung, Median Technologies; LungCARE®, Siemens) in CT volumetric measurement and to analyze the effect of soft (B30) and hard reconstruction filter (B70) on automated volume measurement. MATERIAL AND METHODS Between January 2010 and April 2010, 45 patients with a total of 113 pulmonary nodules were included. The CT exam was performed on a 64-row multidetector CT scanner (Somatom Sensation, Siemens, Erlangen, Germany) with the following parameters: collimation, 24x1.2 mm; pitch, 1.15; voltage, 120 kVp; reference tube current-time, 100 mAs. Automated volumetric measurement of each lung nodule was performed with the two different postprocessing algorithms based on two reconstruction filters (B30 and B70). The average relative volume measurement difference (VME%) and the limits of agreement between two methods were used for comparison. RESULTS At soft reconstruction filters the LMS system produced mean nodule volumes that were 34.1% (P < 0.0001) larger than those by LungCARE® system. The VME% was 42.2% with a limit of agreement between -53.9% and 138.4%.The volume measurement with soft filters (B30) was significantly larger than with hard filters (B70); 11.2% for LMS and 1.6% for LungCARE®, respectively (both with P < 0.05). LMS measured greater volumes with both filters, 13.6% for soft and 3.8% for hard filters, respectively (P < 0.01 and P > 0.05). CONCLUSION There is a substantial inter-software (LMS/LungCARE®) as well as intra-software variability (B30/B70) in lung nodule volume measurement; therefore, it is mandatory to use the same equipment with the same reconstruction filter for the follow-up of lung nodule volume.

Graphical Model-Based Vertebra Identification from X-Ray Image(s)

Automated identification of vertebrae from X-ray image(s) is an important step for various medical image computing tasks such as 2D/3D rigid and non-rigid registration. In this chapter we present a graphical model-based solution for automated vertebra identification from X-ray image(s). Our solution does not ask for a training process using training data and has the capability to automatically determine the number of vertebrae visible in the image(s). This is achieved by combining a graphical model-based maximum a posterior probability (MAP) estimate with a mean-shift based clustering. Experiments conducted on simulated X-ray images as well as on a low-dose low quality X-ray spinal image of a scoliotic patient verified its performance.