The rising prevalence of infectious diseases and a growing geriatric population with increased susceptibility are major drivers for the ever-growing number of patient samples to be assessed by clinical microbiology laboratories. At the same time healthcare professionals face increasing cost pressures and dwindling workforces. This conflict can be resolved by streamlined workflow automation and digitization.
One area with high potential for automation is light microscopy, particularly the reading of Gram stains. Here is also, where the implementation of automated slide scanning and sample digitization is highly beneficial, both from a quality-control perspective as well as given the necessity for higher cost-efficiency in hospital and laboratory settings.
Automated reading of Gram stains is done with the Metafer slide scanning platform*. The walk-away system scans, digitizes and archives up to 800 Gram slides automatically in one batch. Instead of spending time in slide scanning can technicians focus on Gram stain assessment and flexibly organize their work. Moreover, all Gram stain reads can be consolidated on one workstation. Seamless integration into the existing laboratory environment facilitates the exchange of images and data with external systems via LIMs to upload pre-defined procedures for reading and assessment to store Gram information with patient files.
Evaluation of digitized images is faster because data can be accessed from anywhere in the hospital / laboratory network. Now experts can access images anywhere and any time, allowing more timely therapy decisions and sharper focus on interdisciplinary collaborations and optimizing patient results.
Automated imaging improves quality management because
Gram staining is the rapid, easy, and inexpensive method for the assessment of specimen quality, providing early information regarding potential pathogens present in patient samples. Implementation of the Gram Scanner into the laboratory workflow will revolutionize one`s daily routine. The system scans, digitizes and archives – where requested – up to 800 slides in one batch.
Deep learning techniques can potentially support interpretation of digital Gram images. To match the growing demand for workload reduction and efficiency increase in the review process of Gram stained slides we have integrated deep learning-based object classification using convolutional neural networks (CNN) with our automated scanning platform Metafer to create a unique Gram slide screening environment.
Even with escalating expenditures and a dwindling workforce, microbiology laboratories are still expected to meet the demand for prompt and accurate test results at low costs. To meet this challenge, MetaSystems developed the GramScanner, a fully automated walk-away microscope scanning and imaging system. Using the GramScanner, microbiology lab directors can significantly reduce the time their MTs spend at the microscope, increasing the overall efficiency of the lab through more cost-effective use of technicians’ time. This new advanced strategy can even have a direct, positive impact on MT’s health.
MetaSystems, a worldwide leader in microscopic imaging innovation, presented proof of concept results for Deep Learning - based pathogen classification on Gram stain slides.
The congress will take place from 21 to 24 September 2020 in Via Festa del Perdono at the ancient "Spedale di Poveri", built by Francesco Sforza and Bianca Maria Visconti from 1456 on a project by Antonio Averlino, known as Filarete.
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