BACKGROUND: An objective, non-invasive method for redness detection during acute allograft rejection in face transplantation (FT) is lacking. METHODS: A retrospective cohort study was performed with 688 images of 7 patients with face transplant (range, 1 to 108 months post-transplant). Healthy controls were matched to donor age, sex, and had no prior facial procedures. Rejection state was confirmed via tissue biopsy. An image-analysis software developed alongside VicarVision (Amsterdam, Netherlands) was used to produce R, a measure of differences between detectable color and absolute red. R is inversely proportional to redness, where lower R values correspond to increased redness. Linear mixed models were used to study fixed effect of rejection state on R values. Estimated marginal means of fitted models were calculated for pairwise comparisons. RESULTS: Of 688 images, 175, 170, 202, and 141 images were attributable to Banff Grade 0,1,2, and 3, respectively. Estimated change in R value of facial allografts decreased with increasing Banff Grade (p = 0.0001). The mean R value of clinical rejection (Banff Grade 2⁄3) (16.67, 95% Confidence Interval [CI] 14.79-18.58) was lower (p = 0.005) than non-rejection (Banff Grade 0/1) (19.38, 95%CI 17.43-21.33). Both clinical and non-rejection mean R values were lower (p = 0.0001) than healthy controls (24.12, 95%CI 20.96-27.28). CONCLUSION: This proof-of-concept study demonstrates that software-based analysis can detect and monitor acute rejection changes in FT. Future studies should expand on this tool's potential application in telehealth and as a screening tool for allograft rejection.
- MeSH
- Allografts MeSH
- Biopsy MeSH
- Humans MeSH
- Graft Rejection MeSH
- Retrospective Studies MeSH
- Software MeSH
- Kidney Transplantation * MeSH
- Facial Transplantation * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Intravascular optical coherence tomography (IVOCT) is used to assess stent tissue coverage and malapposition in stent evaluation trials. We developed the OCT Image Visualization and Analysis Toolkit for Stent (OCTivat-Stent), for highly automated analysis of IVOCT pullbacks. Algorithms automatically detected the guidewire, lumen boundary, and stent struts; determined the presence of tissue coverage for each strut; and estimated the stent contour for comparison of stent and lumen area. Strut-level tissue thickness, tissue coverage area, and malapposition area were automatically quantified. The software was used to analyze 292 stent pullbacks. The concordance-correlation-coefficients of automatically measured stent and lumen areas and independent manual measurements were 0.97 and 0.99, respectively. Eleven percent of struts were missed by the software and some artifacts were miscalled as struts giving 1% false-positive strut detection. Eighty-two percent of uncovered struts and 99% of covered struts were labeled correctly, as compared to manual analysis. Using the highly automated software, analysis was harmonized, leading to a reduction of inter-observer variability by 30%. With software assistance, analysis time for a full stent analysis was reduced to less than 30 minutes. Application of this software to stent evaluation trials should enable faster, more reliable analysis with improved statistical power for comparing designs.
- MeSH
- Endovascular Procedures instrumentation methods MeSH
- Humans MeSH
- Tomography, Optical Coherence instrumentation methods MeSH
- Sensitivity and Specificity MeSH
- Software standards MeSH
- Stents adverse effects standards MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Evaluation Study MeSH
- Research Support, N.I.H., Extramural MeSH
Super-resolution optical fluctuation imaging (SOFI) allows one to perform sub-diffraction fluorescence microscopy of living cells. By analyzing the acquired image sequence with an advanced correlation method, i.e. a high-order cross-cumulant analysis, super-resolution in all three spatial dimensions can be achieved. Here we introduce a software tool for a simple qualitative comparison of SOFI images under simulated conditions considering parameters of the microscope setup and essential properties of the biological sample. This tool incorporates SOFI and STORM algorithms, displays and describes the SOFI image processing steps in a tutorial-like fashion. Fast testing of various parameters simplifies the parameter optimization prior to experimental work. The performance of the simulation tool is demonstrated by comparing simulated results with experimentally acquired data.
- MeSH
- Algorithms MeSH
- Microscopy, Fluorescence * MeSH
- HeLa Cells MeSH
- Humans MeSH
- Image Processing, Computer-Assisted methods MeSH
- Software * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Účel studie: Mw\Pharm software (MEDI\WARE, Prague, Czech Republic / Groningen, Netherlands) je dlouhodobě používán pro PK/PD modelování pro terapeutické monitorování hladin léčiv (TDM). Cílem práce bylo najít nejvhodnější model pro kontinuální aplikaci vankomycinu v novější Windows verzi Mw\Pharm++ 1.3.5.558 (WIN). Pacienti: 20 dospělých pacientů (průměrný věk 66 ± 12 let, hmotnost 85 ± 16kg), bylo opakovaně vyšetřeno na hladinu vankomycinu. Medián dávky byl 1625g/24h. Koncentrace vankomycinu predikované pomocí WIN modelů "#vancomycin_adult_k_C2", "#vancomycin_adult_C2", "vancomycin_adult_C2", "vancomycin_C1" a DOS modelů "vancomycin (cont.inf.) %ahz" (DOS1) a "vancomycin adult" byly porovnány s naměřenou hodnotou a DOS1 modelem. Statistika: Průměrná procentuální chyba predikce (% PE) vypočtená jako (predikovaná - změřená)/změřená, příp. (predikovaná-DOS1)/DOS1, RMSE, Bland-Altmanova bias, Pearsonův korelační koeficient (R), Studentův t-test. Statistická analýza byla provedena pomocí GraphPad Prism version 5.00 pro Windows. Výsledky: % PE se pohybovala mezi -3,2 ± 33,0 % a -7,4 ± 36,7%, s výjimkou jednokompartmentového modelu "vancomycin_C1", kde byla -20,8 ± 39,4%. Nejlepší výsledky byly dosaženy modelem "vancomycin adult". Model "#vancomycin_adult_k_C2" produkoval nejnižší % PE, RMSE and Bland-Altman bias mezi WIN modely, ale korelace byla slabší. Korelace byla mírně lepší u modelu "vancomycin_adult_C2" RMSE byl stejný, % PE a Bland-Altmanova bias byly obdobné jako u modelu "#vancomycin_adult_k_C2". % PE mezi oběma DOS modely byla 4,1 ± 13,9% (NS); "vancomycin adult" měl mírně lepší výsledky než DOS1. Závěr: Z WIN modelů byly nejlepší výsledky dosaženy modely "vancomycin_adult_C2" a "#vancomycin_adult_k_C2". Oba DOS modely produkovaly nízkou bias a jejich predikce byly srovnatelné.
Objective: For a long time, the Mw\Pharm software suite (MEDI\WARE, Prague, Czech Republic/Groningen, Netherlands) has been used for PK/PD modelling in therapeutic drug monitoring (TDM). The aim of this study was to find the best model in the newer Windows version of Mw\Pharm++ 1.3.5.558 (WIN) for continuous administration of vancomycin. Patients: Twenty adult patients with a mean age of 66 ± 12 years, body weight 85 ± 16kg, and median dose 1,625g/24h were repeatedly examined for vancomycin. Methods: Concentrations predicted by "#vancomycin_adult_k_C2", "#vancomycin_adult_C2", "vancomycin_adult_C2", "vancomycin_C1" WIN models and "vancomycin (cont.inf.) %ahz" (DOS1) and "vancomycin adult" DOS models were compared with the measured values and with the DOS1 model. Statistics: Percentage prediction error (%PE) calculated as (predicted-measured)/measured or (predicted-DOS1)/DOS1, RMSE, Bland-Altman bias, Pearson's coefficient of rank correlation (R), Student's t-test. Statistical analysis was performed using the GraphPad Prism version 5.00 for Windows. Results: %PE values varied between -3.2 ± 33.0% and -7.4 ± 36.7%, with the exception of "vancomycin_C1", the only one-compartment model, where it was -20.8 ± 39.4%. The best outcomes were achieved with "vancomycin adult". The "#vancomycin_adult_k_C2" model produced the lowest %PE, RMSE, and Bland-Altman bias among the WIN models, but its correlation (Pearson's R) was less tight. RMSE was the same in "vancomycin_adult_C2" while %PE and Bland-Altman bias were similar, with slightly better correlation when compared to "#vancomycin_adult_k_C2". The %PE value between the two DOS models was 4.1 ± 13.9% (NS); "vancomycin adult" produced slightly better outcomes than DOS1. Conclusion: "vancomycin_adult_C2" and "#vancomycin_adult_k_C2" produced the best outcomes between WIN models. Both DOS models produced lower bias and their prediction was comparable.
- MeSH
- Anti-Bacterial Agents therapeutic use MeSH
- Middle Aged MeSH
- Humans MeSH
- Drug Monitoring * MeSH
- Drug Design MeSH
- Aged MeSH
- Software MeSH
- Vancomycin * administration & dosage pharmacokinetics blood MeSH
- Check Tag
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Research Support, Non-U.S. Gov't MeSH
PURPOSE: Neuroimaging pipelines have long been known to generate mildly differing results depending on various factors, including software version. While considered generally acceptable and within the margin of reasonable error, little is known about their effect in common research scenarios such as inter-group comparisons between healthy controls and various pathological conditions. The aim of the presented study was to explore the differences in the inferences and statistical significances in a model situation comparing volumetric parameters between healthy controls and type 1 diabetes patients using various FreeSurfer versions. METHODS: T1- and T2-weighted structural scans of healthy controls and type 1 diabetes patients were processed with FreeSurfer 5.3, FreeSurfer 5.3 HCP, FreeSurfer 6.0 and FreeSurfer 7.1, followed by inter-group statistical comparison using outputs of individual FreeSurfer versions. RESULTS: Worryingly, FreeSurfer 5.3 detected both cortical and subcortical volume differences out of the preselected regions of interest, but newer versions such as FreeSurfer 5.3 HCP and FreeSurfer 6.0 reported only subcortical differences of lower magnitude and FreeSurfer 7.1 failed to find any statistically significant inter-group differences. CONCLUSION: Since group averages of individual FreeSurfer versions closely matched, in keeping with previous literature, the main origin of this disparity seemed to lie in substantially higher within-group variability in the model pathological condition. Ergo, until validation in common research scenarios as case-control comparison studies is included into the development process of new software suites, confirmatory analyses utilising a similar software based on analogous, but not fully equivalent principles, might be considered as supplement to careful quality control.
The recent discoveries of regulatory non-coding RNAs changed our view of RNA as a simple information transfer molecule. Understanding the architecture and function of active RNA molecules requires methods for comparing and analyzing their 3D structures. While structural alignment of short RNAs is achievable in a reasonable amount of time, large structures represent much bigger challenge. Here, we present the SETTER web server for the RNA structure pairwise comparison utilizing the SETTER (SEcondary sTructure-based TERtiary Structure Similarity Algorithm) algorithm. The SETTER method divides an RNA structure into the set of non-overlapping structural elements called generalized secondary structure units (GSSUs). The SETTER algorithm scales as O(n(2)) with the size of a GSSUs and as O(n) with the number of GSSUs in the structure. This scaling gives SETTER its high speed as the average size of the GSSU remains constant irrespective of the size of the structure. However, the favorable speed of the algorithm does not compromise its accuracy. The SETTER web server together with the stand-alone implementation of the SETTER algorithm are freely accessible at http://siret.cz/setter.
- MeSH
- Algorithms MeSH
- Internet MeSH
- Nucleic Acid Conformation MeSH
- RNA chemistry MeSH
- Software MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
MOTIVATION: Understanding the architecture and function of RNA molecules requires methods for comparing and analyzing their 3D structures. Although a structural alignment of short RNAs is achievable in a reasonable amount of time, large structures represent much bigger challenge. However, the growth of the number of large RNAs deposited in the PDB database calls for the development of fast and accurate methods for analyzing their structures, as well as for rapid similarity searches in databases. RESULTS: In this article a novel algorithm for an RNA structural comparison SETTER (SEcondary sTructure-based TERtiary Structure Similarity Algorithm) is introduced. SETTER uses a pairwise comparison method based on 3D similarity of the so-called generalized secondary structure units. For each pair of structures, SETTER produces a distance score and an indication of its statistical significance. SETTER can be used both for the structural alignments of structures that are already known to be homologous, as well as for 3D structure similarity searches and functional annotation. The algorithm presented is both accurate and fast and does not impose limits on the size of aligned RNA structures. AVAILABILITY: The SETTER program, as well as all datasets, is freely available from http://siret.cz/hoksza/projects/setter/.
- MeSH
- Chemotherapy, Cancer, Regional Perfusion MeSH
- Diagnostic Imaging methods MeSH
- Adult MeSH
- Ventricular Function, Left MeSH
- Myocardial Infarction diagnosis pathology MeSH
- Humans MeSH
- Nuclear Medicine methods MeSH
- Image Processing, Computer-Assisted MeSH
- Radionuclide Ventriculography methods MeSH
- Check Tag
- Adult MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Comparative Study MeSH
BACKGROUND:Analysis of ciliary function for assessment of patients suspected of primary ciliary dyskinesia (PCD) and for research studies of respiratory and ependymal cilia requires assessment of both ciliary beat pattern and beat frequency. While direct measurement of beat frequency from high-speed video recordings is the most accurate and reproducible technique it is extremely time consuming. The aim of this study was to develop a freely available automated method of ciliary beat frequency analysis from digital video (AVI) files that runs on open-source software (ImageJ) coupled to Microsoft Excel, and to validate this by comparison to the direct measuring high-speed video recordings of respiratory and ependymal cilia. These models allowed comparison to cilia beating between 3 and 52 Hz. METHODS:Digital video files of motile ciliated ependymal (frequency range 34 to 52 Hz) and respiratory epithelial cells (frequency 3 to 18 Hz) were captured using a high-speed digital video recorder. To cover the range above between 18 and 37 Hz the frequency of ependymal cilia were slowed by the addition of the pneumococcal toxin pneumolysin. Measurements made directly by timing a given number of individual ciliary beat cycles were compared with those obtained using the automated ciliaFA system. RESULTS:The overall mean difference (± SD) between the ciliaFA and direct measurement high-speed digital imaging methods was -0.05 ± 1.25 Hz, the correlation coefficient was shown to be 0.991 and the Bland-Altman limits of agreement were from -1.99 to 1.49 Hz for respiratory and from -2.55 to 3.25 Hz for ependymal cilia. CONCLUSIONS:A plugin for ImageJ was developed that extracts pixel intensities and performs fast Fourier transformation (FFT) using Microsoft Excel. The ciliaFA software allowed automated, high throughput measurement of respiratory and ependymal ciliary beat frequency (range 3 to 52 Hz) and avoids operator error due to selection bias. We have included free access to the ciliaFA plugin and installation instructions in Additional file 1 accompanying this manuscript that other researchers may use.
