No. In the new Ikaros, the DNN capabilities facilitate the segregation of chromosomes and their categorization into the appropriate karyogram classes. This process yields a preliminary suggestion that requires further assessment and potential modification by a skilled user. Ultimately, the cytogeneticist is responsible for creating the final karyogram and conducting its analysis.
Yes, once Ikaros generates a karyogram proposal via its DNN features, users have the possibility and the responsibility to review and, if needed, amend this proposal. They have access to the same respective tools that have been present in earlier versions of Ikaros. Nevertheless, when an appropriate DNN is utilized, it is anticipated that the need for manual adjustments will be considerably reduced compared to the machine learning algorithms used in prior versions.
The response to this inquiry is contingent on various elements. Factors such as the nature of preparations, working methods employed, and the time allocated for result verification and reporting all play crucial roles in determining processing time. Nonetheless, insights from laboratories that have adopted the new feature indicate a noticeable decrease in case processing times, attributed to the diminished requirement for manual intervention in contrast to the algorithms previously in use.
No, there is no need for a replacement. Starting with version 6.3, every new version of Ikaros comes ready for DNN-based chromosome separation and classification and can be upgraded to include this feature. For efficient handling of DNN operations, an additional graphics card is needed to facilitate the computations. This card can be installed directly in the workstation or in a distinct system. For further information on the technical options available, please feel free to get in touch with us.
Once the Metafer Platform Software is installed in your lab, you can configure workflows to detect metaphases on slides automatically. Metafer offers two object detection methods. The first is based on classic machine learning algorithms, which quickly identify metaphases and display them as gallery images after the search. This method is fast and commonly used by many customers. More recently, the platform has also incorporated Deep Neural Networks (DNN), which can be trained to identify metaphases from images classified by the users. Although this method is a bit slower than the traditional algorithms, our customers report that it provides more accurate and specific results. The choice between these two methods depends on various factors, and during the customization process, our application specialists will assist you in developing the most appropriate workflow for your laboratory.
Yes, Metafer saves the positions of the detected objects and associates them with the respective gallery image. The coordinates are transferred to the high-resolution images, allowing them to be viewed in Ikaros. Additionally, if needed, other coordinate systems, such as the verniers from different manual microscopes, can be stored in Metafer. Metafer can convert all coordinates into the new system upon request, enabling objects to be located manually on external microscopes.
Users can customize their workflow using the Metafer Platform Software toolbox, allowing them to decide which steps to automate and which to leave manual. For instance, the search and image acquisition processes can be linked, eliminating the need for manual intervention between them. Installing an automatic immersion oil dispenser (AutoOiler) ensures the preparations receive the correct amount of immersion oil when switching to a high-resolution objective.
Additionally, a barcode reader can automate the management of preparations, either fully or partially, including the creation of automatically generated search protocols that track and document the entire process.
As case volumes grow, Metafer can be upgraded with the automatic SlideFeeder x80, which feeds slides into the microscope. The search capacity can be expanded from 8 slides (without the SlideFeeder x80) to 80, 160, 240, or up to 800 slides. Depending on the automation settings, these slides can be scanned automatically with no need for manual intervention.
Yes, that is possible. Metafer, together with Neon, offers extensive options for exchanging case data, scan tasks, and other information with external databases. This data exchange can be highly automated to minimize unnecessary interactions and reduce the risk of human error. For example, if your LIMS supports it, barcode labels can be generated upon case creation; Metafer and Neon can then read and interpret these barcodes. Combined with a file generated by the LIMS that defines the search parameters, the barcode can automatically trigger the metaphase search and image capture process. When case data is imported simultaneously, evaluators at their workstations receive all relevant information alongside the images to facilitate case assessment.
Chromosome analysis with the help of karyograms is central to cytogenetics, and Ikaros enhances this process, allowing the users to set up a versatile digital workflow. The software supports various banding techniques, specimen types, and advanced image processing tools, all within an intuitive, customizable interface.
The latest versions of Ikaros offer the option of implementing Deep Neural Networks (DNN) in user workflows, which help reduce segmentation errors, minimize manual corrections, and save time in metaphase processing. The DNN technology optimizes chromosome segmentation and classification and provides an initial karyogram draft as a basis for expert review. Delivering these innovative features while maintaining backward compatibility, Ikaros ensures that long-time users can seamlessly transition to the latest version and decide how much of this functionality they want to implement in their workflows.
The traditional manual FISH spot evaluation method is time-consuming, repetitive, error-prone, and often conducted under poor lighting conditions, leading to fatigue and decreased accuracy. Additionally, it lacks comprehensive image documentation and the necessary checks required by the dual control principle. MetaSystems enables users to establish a method that integrates imaging automation with human expertise to streamline FISH spot counting. The Customization Package for Spot Counting facilitates the creation of a flexible workflow that adapts to various locus-specific probes and supports different probe layouts, preparation methods, and color channels. This approach allows users to leverage the benefits of digital image processing while ensuring quick and easy confirmation of results, along with complete documentation in the form of images and process data.
RapidScore is a crucial step in the workflow that allows experts to efficiently evaluate data by focusing on areas of interest and identifying anomalies. This process combines automation and human insight to draw well-informed conclusions from the data. The RapidScore keyboard displays anticipated spot patterns specific to the probe layout on its keys, allowing experts to swiftly confirm or modify these suggestions with a keystroke.
After data collection is finalized and cytogenetics experts have completed their review, there are various options for presenting the results. The general data management software, Neon, which is installed with every Metafer Platform Software installation, includes a built-in Reporting Interface specifically designed for this purpose. Customizable report templates simplify the creation of personalized and visually engaging result summaries. Additionally, data can be easily exported from Neon - such as transferring it back to the LIMS - or aggregated into detailed statistical queries for streamlined summarization.
Sure, one case study involved a U.S. laboratory conducting analyses on probe panels for various conditions. The use case showed significant time savings using the Metafer-based workflow with RapidScore compared to manual, paper-based analysis. Read more here!
The Customization Package TissueFISH is a service to set up a proposed workflow that utilizes the various tools of the Metafer Platform Software to provide a comprehensive solution for analyzing fluorescence signals in tissue sections. It integrates advanced software with automated image acquisition and processing tools, simplifying the analysis of FISH spots and other fluorescence signals in tissue samples. Our TissueFISH Customization Package offers a service to assist customers in designing, implementing, and validating their workflows, with support from a MetaSystems application specialist. Final workflow validation is the responsibility of the customer.
Each tissue sample is unique, making it ineffective to configure scanning software like Metafer to always digitize the same region. Instead, Metafer provides flexible options for creating intelligent autofocus algorithms that adapt to the dimensions and characteristics of tissue sections on the specimen. To prepare for the main scan, a pre-scan at the lowest possible magnification can be configured and conducted before the main scan. This pre-scan automatically generates an optimized position list for the main scan, allowing users to define criteria for selecting optimal regions, such as cell density, signal presence, tissue thickness, and more. Additionally, through a tissue-matching process, pre-scans can be applied to differently stained adjacent sections. Regions captured automatically or marked manually can then be transferred to another tissue section for further analysis.
In an ideal, customized TissueFISH workflow, results for each nucleus are displayed alongside a gallery image, enabling immediate verification and correction. The software dynamically updates a configurable data histogram to summarize the findings in real-time. For final review, it provides a comprehensive overview, including the cell gallery, a virtual DAPI slide, and the corresponding H&E virtual slide. Results can be exported either as raw data or in customizable report formats.
Metafer is widely used by institutions around the world to analyze routine forensic samples stained with common methods like Christmas Tree stain, Baecchi stain, and H&E. If your laboratory uses any of these staining techniques, the workflow can typically be implemented with minimal modifications. For samples prepared with alternative methods, we offer services to tailor Deep Neural Networks (DNN) to meet your specific requirements.
The answer to this question depends on your workflow and the extent of time and effort you have already dedicated to manual microscopy. With Metafer, sperm searches can be automated and run unattended, even overnight or on weekends. However, a forensic expert still has to review, verify, and assess the results afterward. Informal feedback from users indicates that implementing automatic sperm detection has significantly helped to reduce the backlog of unresolved cases.
Systems operated with our Metafer software can be configured to meet the requirements of laboratories of different sizes. Various add-ons are available for small, medium, and large laboratories. If capacity requires 24/7 microscopy operation with the ability to prioritize urgent slides, an automated slide feeder can be added to the scanning system. This allows for unattended slide scanning overnight or on weekends. With a scalable capacity from 8 up to 800 slides being automatically scanned, we support our customers in high-throughput applications.
Negative cases can be challenging to confirm, as there is always a chance that one or more sperm cells were missed. This concern applies to both manual microscopy and automated sperm detection. Many of our customers consider this factor when validating their workflow. Metafer helps by automatically sorting the object gallery after scanning, prioritizing potential matches based on the probability delivered by the DNN. For the final mandatory review of results by a forensic expert, it may be helpful to specify in your SOP the number of gallery pages that must be examined before classifying a case as negative. Each laboratory should determine this number individually based on its specific circumstances.