SamuROI, a Python-Based Software Tool for Visualization and Analysis of Dynamic Time Series Imaging at Multiple Spatial Scales

The measurement of activity in vivo and in vitro has shifted from electrical to optical methods. While the indicators for imaging activity have improved significantly over the last decade, tools for analysing optical data have not kept pace. Most available analysis tools are limited in their flexibility and applicability to datasets obtained at different spatial scales. Here, we present SamuROI (Structured analysis of multiple user-defined ROIs), an open source Python-based analysis environment for imaging data. SamuROI simplifies exploratory analysis and visualization of image series of fluorescence changes in complex structures over time and is readily applicable at different spatial scales. In this paper, we show the utility of SamuROI in Ca2+-imaging based applications at three spatial scales: the micro-scale (i.e., sub-cellular compartments including cell bodies, dendrites and spines); the meso-scale, (i.e., whole cell and population imaging with single-cell resolution); and the macro-scale (i.e., imaging of changes in bulk fluorescence in large brain areas, without cellular resolution). The software described here provides a graphical user interface for intuitive data exploration and region of interest (ROI) management that can be used interactively within Jupyter Notebook: a publicly available interactive Python platform that allows simple integration of our software with existing tools for automated ROI generation and post-processing, as well as custom analysis pipelines. SamuROI software, source code and installation instructions are publicly available on GitHub and documentation is available online. SamuROI reduces the energy barrier for manual exploration and semi-automated analysis of spatially complex Ca2+ imaging datasets, particularly when these have been acquired at different spatial scales.Peer Reviewe

Comparison of elution characteristics and compressive strength of biantibiotic-loaded PMMA bone cement for spacers: Copal^® spacem with gentamicin and vancomycin versus Palacos^® R+G with vancomycin

Purpose. Copal^® spacem is a new PMMA bone cement for fabricating spacers. This study compares elution of gentamicin, elution of vancomycin, and compressive strength of Copal^® spacem and of Palacos^® R+G at different vancomycin loadings in the powder of the cements. We hypothesized that antibiotic elution of Copal^® spacem is superior at comparable compressive strength. Methods. Compression test specimens were fabricated using Copal^® spacem manually loaded with 0.5 g gentamicin and additionally 2 g, 4 g, and 6 g of vancomycin per 40 g of cement powder (COP specimens) and using 0.5 g gentamicin premixed Palacos^® R+G manually loaded with 2 g, 4 g, and 6 g of vancomycin per 40 g of cement powder (PAL specimens). These specimens were used for determination of gentamicin and vancomycin elution (in fetal calf serum, at 22°C) and for determination of compressive strength both prior and following the elution tests. Results. Cumulative gentamicin concentrations (p < 0.005) and gentamicin concentration after 28 days (p ≤ 0.043) were significantly lower for COP specimens compared to PAL specimens. Cumulative vancomycin concentrations were significantly higher (p ≤ 0.043) for COP specimens after the second day. Vancomycin concentrations after 28 days were not significantly higher for the Copal specimens loaded with 2 g and 4 g of vancomycin. Compressive strength was not significantly different between COP specimens and PAL specimens before elution tests. Compressive strength after the elution tests was significantly lower (p = 0.005) for COP specimens loaded with 2 g of vancomycin. Conclusion. We could not demonstrate consistent superior antibiotic elution from Copal^® spacem compared to Palacos^® R+G for fabricating gentamicin and vancomycin loaded spacers. The results do not favor Copal^® spacem over Palacos^® R+G for the use as a gentamicin and vancomycin biantibiotic-loaded spacer

The posterior-anterior-flexed view is essential for the evaluation of valgus osteoarthritis. A prospective study on 134 valgus knees

Background Radiographic imaging is an important tool to assess osteoarthritis (OA). Lateral compartment osteoarthritis (valgus OA) usually starts with cartilage degeneration along the posterior aspect of the lateral femoral condyle. There is evidence that the posterior-anterior (PA)-flexed view is more sensitive when diagnosing early stages of valgus OA compared to the anterior-posterior (AP) view. The current paper analyzes the value of the PA-flexed view for patients scheduled for total knee arthroplasty (TKA). Methods Radiographs of 134 valgus knees were assessed prior to TKA. The minimal joint space width (minJSW) was measured on AP and PA-flexed views. The extent of mechanical deformity was measured on hip to ankle standing films. Results 49 (36.6%) AP views showed Kellgren and Lawrence (K/L)-grade 4 osteoarthritis in the lateral compartment, 82 (63.4%) showed grade 3 or less. The PA-flexed view resulted in an increased K/L-grading to grade 4 for 53 knees (62.4%) that were considered grade 3 or less on standard AP-radiographs. There was a significant differences between lateral minJSW on AP and PA-flexed view for patients with up to 10 degrees of mechanical valgus deformity (p < 0.001), as well as 11 to 15 degrees of mechanical deformity (p = 0.021). Only knees with severe deformity of more than 15 degrees did not show a difference in minJSW between PA-flexed view and AP view (p = 0.345). Conclusions The PA-flexed view is superior to the standard AP view in quantifying the extent of valgus OA in patients with zero to fifteen degrees of valgus deformity. It is recommended for the initial assessment of patients with valgus osteoarthritis and better documents the extent of osteoarthritis prior to TKA

SamuROI, a Python-Based Software Tool for Visualization and Analysis of Dynamic Time Series Imaging at Multiple Spatial Scales

The measurement of activity in vivo and in vitro has shifted from electrical to optical methods. While the indicators for imaging activity have improved significantly over the last decade, tools for analysing optical data have not kept pace. Most available analysis tools are limited in their flexibility and applicability to datasets obtained at different spatial scales. Here, we present SamuROI (Structured analysis of multiple user-defined ROIs), an open source Python-based analysis environment for imaging data. SamuROI simplifies exploratory analysis and visualization of image series of fluorescence changes in complex structures over time and is readily applicable at different spatial scales. In this paper, we show the utility of SamuROI in Ca2+-imaging based applications at three spatial scales: the micro-scale (i.e., sub-cellular compartments including cell bodies, dendrites and spines); the meso-scale, (i.e., whole cell and population imaging with single-cell resolution); and the macro-scale (i.e., imaging of changes in bulk fluorescence in large brain areas, without cellular resolution). The software described here provides a graphical user interface for intuitive data exploration and region of interest (ROI) management that can be used interactively within Jupyter Notebook: a publicly available interactive Python platform that allows simple integration of our software with existing tools for automated ROI generation and post-processing, as well as custom analysis pipelines. SamuROI software, source code and installation instructions are publicly available on GitHub and documentation is available online. SamuROI reduces the energy barrier for manual exploration and semi-automated analysis of spatially complex Ca2+ imaging datasets, particularly when these have been acquired at different spatial scales