Addressing the Challenges Faced by Modern Cytogenetics Labs
The traditional method of manually analyzing metaphase spreads for karyotyping or manually counting FISH signals can lead to potential bottlenecks in workflow. To address these challenges, laboratories worldwide are increasingly turning to automation. At MetaSystems, we have worked closely with users for nearly 40 years to develop software solutions that can be adapted to meet the evolving needs of modern cytogenetics laboratories.
MetaSystems installations are not simply a collection of individual workstations, but represent scalable multi-user environments that fit seamlessly into existing structures, structure entire laboratory workflows, manage cases and images securely, and provide a variety of tools for routine and standardized image analysis and reporting. Whether for human genetics, oncology or prenatal diagnostics, our customizable software can support a wide range of workflows and help reduce manual workload.
Metaphase Detection
Users have successfully implemented the Metafer Platform Software with our assistance to detect metaphases in various preparation techniques, including G-banding, R-banding, Q-banding, and DAPI banding. With support from MetaSystems application specialists, users can tailor their installations to include Deep Neural Networks (DNNs) to address challenging preparations. Automated image capture is scalable to process up to 800 slides in a single run.
Spot Counting
Imaging installations operated by the Metafer Platform Software can be customized to automatically acquire interphase nuclei and fluorescent signals, with focus stacking possible. This workflow is adaptable to diverse FISH DNA probes, preparation techniques, and color channels. With the intuitive RapidScore keyboard, users can quickly confirm or adjust software-generated spot pattern suggestions.
TissueFISH
Users can perform pre-scans on H&E-stained samples to identify regions of interest and match these to adjacent tissue sections for analysis. Tissue Micro Array (TMA) patterns can also be edited with a convenient tool for high-throughput applications. Optionally, users can incorporate custom workflows for automated cell segmentation with user-trained Deep Neural Networks (DNNs). The software provides real-time signal suggestions, dynamic data histograms, and image enhancement options.