Automation in the clinical microbiology laboratory

The Impact of Laboratory Automation on the Time to Urine Microbiological Results: A Five-Year Retrospective Study

Total laboratory automation (TLA) is a valuable component of microbiology laboratories and a growing number of publications suggest the potential impact of automation in terms of analysis standardization, streaking quality, and the turnaround time (TAT). The aim of this project was to perform a detailed investigation of the impact of TLA on the workflow of commonly treated specimens such as urine. This is a retrospective observational study comparing two time periods (pre TLA versus post TLA) for urine specimen culture processing. A total of 35,864 urine specimens were plated during the pre-TLA period and 47,283 were plated during the post-TLA period. The median time from streaking to identification decreased from 22.3 h pre TLA to 21.4 h post TLA (p < 0.001), and the median time from streaking to final validation of the report decreased from 24.3 h pre TLA to 23 h post TLA (p < 0.001). Further analysis revealed that the observed differences in TAT were mainly driven by the contaminated and positive samples. Our findings demonstrate that TLA has the potential to decrease turnaround times of samples in a laboratory. Nevertheless, changes in laboratory workflow (such as extended opening hours for plate reading and antibiotic susceptibility testing or decreased incubation times) might further maximize the efficiency of TLA and optimize TATs.

Promising potential of machine learning-assisted MALDI-TOF MS as an effective detector for Streptococcus suis serotype 2 and virulence thereof

IMPORTANCE

To the best of our knowledge, this study reveals a strong correlation between mass spectra pattern and virulence phenotype among S. suis for the first time. In order to make the findings applicable and to excavate the intrinsic information in the spectra, the classifiers based on the machine learning algorithms were established, and RF (Random Forest)-based models have achieved an accuracy of over 90%. Overall, this study will pave the way for virulent SS2 (Streptococcus suis serotype 2) rapid detection, and the important findings on the association between genotype and mass spectrum may provide a new idea for the genotype-dependent detection of specific pathogens.

Current State of Laboratory Automation in Clinical Microbiology Laboratory

BACKGROUND

Although it has been 30 years since the first automation systems were introduced in the microbiology laboratory, total laboratory automation (TLA) has only recently been recognized as a valuable component of the laboratory. A growing number of publications illustrate the potential impact of automation. TLA can improve standardization, increase laboratory efficiency, increase workplace safety, and reduce long-term costs.

CONTENT

This review provides a preview of the current state of automation in clinical microbiology and covers the main developments during the last years. We describe the available hardware systems (that range from single function devices to multifunction workstations) and the challenging alterations on workflow and organization of the laboratory that have to be implemented to optimize automation.

SUMMARY

Despite the many advantages in efficiency, productivity, and timeliness that automation offers, it is not without new and unique challenges. For every advantage that laboratory automation provides, there are similar challenges that a laboratory must face. Change management strategies should be used to lead to a successful implementation. TLA represents, moreover, a substantial initial investment. Nevertheless, if properly approached, there are a number of important benefits that can be achieved through implementation of automation in the clinical microbiology laboratory. Future developments in the field of automation will likely focus on image analysis and artificial intelligence improvements. Patient care, however, should remain the epicenter of all future directions and there will always be a need for clinical microbiology expertise to interpret the complex clinical and laboratory information.

Behind Every Great Infection Prevention Program is a Great Microbiology Laboratory: Key Components and Strategies for an Effective Partnership

A great clinical microbiology laboratory supporting a great infection prevention program requires focusing on the following services: rapid and accurate identification of pathogens associated with health care-associated infections; asymptomatic surveillance for health care-acquired pathogens before infections arise; routine use of broad and flexible antimicrobial susceptibility testing to direct optimal therapy; implementation of epidemiologic tracking tools to identify outbreaks; development of clear result communication with interpretative comments for clinicians. These goals are best realized in a collaborative relationship with the infection prevention program so that both can benefit from the shared priorities of providing the best patient care.

Clinical Utility of Advanced Microbiology Testing Tools

Advanced microbiology technologies are rapidly changing our ability to diagnose infections, improve patient care, and enhance clinical workflow. These tools are increasing the breadth, depth, and speed of diagnostic data generated per patient, and testing is being moved closer to the patient through rapid diagnostic technologies, including point-of-care (POC) technologies.

Advanced microbiology technologies are rapidly changing our ability to diagnose infections, improve patient care, and enhance clinical workflow. These tools are increasing the breadth, depth, and speed of diagnostic data generated per patient, and testing is being moved closer to the patient through rapid diagnostic technologies, including point-of-care (POC) technologies. While select stakeholders have an appreciation of the value/importance of improvements in the microbial diagnostic field, there remains a disconnect between clinicians and some payers and hospital administrators in terms of understanding the potential clinical utility of these novel technologies. Therefore, a key challenge for the clinical microbiology community is to clearly articulate the value proposition of these technologies to encourage payers to cover and hospitals to adopt advanced microbiology tests. Specific guidance on how to define and demonstrate clinical utility would be valuable. Addressing this challenge will require alignment on this topic, not just by microbiologists but also by primary care and emergency room (ER) physicians, infectious disease specialists, pharmacists, hospital administrators, and government entities with an interest in public health. In this article, we discuss how to best conduct clinical studies to demonstrate and communicate clinical utility to payers and to set reasonable expectations for what diagnostic manufacturers should be required to demonstrate to support reimbursement from commercial payers and utilization by hospital systems.

Anaerobes and laboratory automation: Like oil and water?

Diagnostic laboratories are urged to take advantage of novel technological advancements to provide standardized and high-throughput information for clinicians; however, total laboratory automation (TLA) has only recently been introduced in clinical microbiology in the last 10-12 years. The introduction of total laboratory automation comes with certain advantages and drawbacks that need to be assessed before the introduction of such systems in the diagnostic workflow that includes the detection of anaerobic bacteria. For several reasons, there is yet to be a manufacturer to fully address the issue of anaerobes in the setting of laboratory automation; the aim of the present paper is to address some of the issues associated with anaerobes in lab automation.

Automation and artificial intelligence in the clinical laboratory

The daily operation of clinical laboratories will be drastically impacted by two disruptive technologies: automation and artificial intelligence (the development and use of computer systems able to perform tasks that normally require human intelligence). These technologies will also expand the scope of laboratory medicine. Automation will result in increased efficiency but will require changes to laboratory infrastructure and a shift in workforce training requirements. The application of artificial intelligence to large clinical datasets generated through increased automation will lead to the development of new diagnostic and prognostic models. Together, automation and artificial intelligence will support the move to personalized medicine. Changes in pathology and clinical doctoral scientist training will be necessary to fully participate in these changes. KEYWORDS: Automation; artificial intelligence; deep learning; laboratory medicine.

Clinical Microbiology Is Growing Up: The Total Laboratory Automation Revolution

BACKGROUND

Historically, culture-based microbiology laboratory testing has relied on manual methods, and automated methods (such as those that have revolutionized clinical chemistry and hematology over the past several decades) were largely absent from the clinical microbiology laboratory. However, an increased demand for microbiology testing and standardization of sample-collection devices for microbiology culture, as well as a dwindling supply of microbiology technologists, has driven the adoption of automated methods for culture-based laboratory testing in clinical microbiology.

CONTENT

We describe systems currently enabling total laboratory automation (TLA) for culture-based microbiology testing. We describe the general components of a microbiology automation system and the various functions of these instruments. We then introduce the 2 most widely used systems currently on the market: Becton Dickinson's Kiestra TLA and Copan's WASPLab. We discuss the impact of TLA on metrics such as turnaround time and recovery of microorganisms, providing a review of the current literature and perspectives from laboratory directors, managers, and technical staff. Finally, we provide an outlook for future advances in TLA for microbiology with a focus on artificial intelligence for automated culture interpretation.

SUMMARY

TLA is playing an increasingly important role in clinical microbiology. Although challenges remain, TLA has great potential to affect laboratory efficiency, turnaround time, and the overall quality of culture-based microbiology testing.

MVO Automation Platform: Addressing Unmet Needs in Clinical Laboratories with Microcontrollers, 3D Printing, and Open-Source Hardware/Software

Laboratory automation improves test reproducibility, which is vital to patient care in clinical laboratories. Many small and specialty laboratories are excluded from the benefits of automation due to low sample number, cost, space, and/or lack of automation expertise. The Minimum Viable Option (MVO) automation platform was developed to address these hurdles and fulfill an unmet need. Consumer 3D printing enabled rapid iterative prototyping to allow for a variety of instrumentation and assay setups and procedures. Three MVO versions have been produced. MVOv1.1 successfully performed part of a clinical assay, and results were comparable to those of commercial automation. Raspberry Pi 3 Model B (RPI3) single-board computers with Sense Hardware Attached on Top (HAT) and Raspberry Pi Camera Module V2 hardware were remotely accessed and evaluated for their suitability to qualify the latest MVOv1.2 platform. Sense HAT temperature, barometric pressure, and relative humidity sensors were stable in climate-controlled environments and are useful in identifying appropriate laboratory spaces for automation placement. The RPI3 with camera plus digital dial indicator logged axis travel experiments. RPI3 with camera and Sense HAT as a light source showed promise when used for photometric dispensing tests. Individual well standard curves were necessary for well-to-well light and path length compensations.

Experimental fusion of different versions of the total laboratory automation system and improvement of laboratory turnaround time

BACKGROUND

Use of total laboratory automation (TLA) system has expanded to microbiology and hemostasis and upgraded to second and third generations. We herein report the first successful upgrades and fusion of different versions of the TLA system, thus improving laboratory turnaround time (TAT).

METHODS

A 21-day schedule was planned from the time of pre-meeting to installation and clinical sample application. We analyzed the monthly TAT in each menu, distribution of the "out of range for acceptable TAT" samples, and "prolonged time out of acceptable TAT," before and after the upgrade and fusion.

RESULTS

We installed and customized hardware, middleware, and software. The one-way CliniLog 2.0 version track, 50.0-m long, was changed to a 23.2-m long one-way 2.0 version and an 18.7-m long two-way 4.0 version. The monthly TAT in the outpatient samples, before and after upgrading the TLA system, were uniformly satisfactory in the chemistry and viral marker menus. However, in the tumor marker menu, the target TAT (98.0% of samples ≤60 minutes) was not satisfied during the familiarization period. There was no significant difference in the proportion of "out of acceptable TAT" samples, before and after the TLA system upgrades (7.4‰ and 8.5‰). However, the mean "prolonged time out of acceptable TAT" in the chemistry samples was significantly shortened to 17.4 (±24.0) minutes after the fusion, from 34.5 (±43.4) minutes.

CONCLUSIONS

Despite experimental challenges, a fusion of the TLA system shortened the "prolonged time out of acceptable TAT," indicating a distribution change in overall TAT.

Effect of Electrode Geometry on the Classification Performance of Rapid Evaporative Ionization Mass Spectrometric (REIMS) Bacterial Identification

The recently developed automated, high-throughput monopolar REIMS platform is suited for the identification of clinically important microorganisms. Although already comparable to the previously reported bipolar forceps method, optimization of the geometry of monopolar electrodes, at the heart of the system, holds the most scope for further improvements to be made. For this, sharp tip and round shaped electrodes were optimized to maximize species-level classification accuracy. Following optimization of the distance between the sample contact point and tube inlet with the sharp tip electrodes, the overall cross-validation accuracy improved from 77% to 93% in negative and from 33% to 63% in positive ion detection modes, compared with the original 4 mm distance electrode. As an alternative geometry, round tube shaped electrodes were developed. Geometry optimization of these included hole size, number, and position, which were also required to prevent plate pick-up due to vacuum formation. Additional features, namely a metal "X"-shaped insert and a pin in the middle were included to increase the contact surface with a microbial biomass to maximize aerosol production. Following optimization, cross-validation scores showed improvement in classification accuracy from 77% to 93% in negative and from 33% to 91% in positive ion detection modes. Supervised models were also built, and after the leave 20% out cross-validation, the overall classification accuracy was 98.5% in negative and 99% in positive ion detection modes. This suggests that the new generation of monopolar REIMS electrodes could provide substantially improved species level identification accuracies in both polarity detection modes. Graphical abstract.

The cobas® 6800/8800 System: a new era of automation in molecular diagnostics

INTRODUCTION

Molecular diagnostics is a key component of laboratory medicine. Here, the authors review key triggers of ever-increasing automation in nucleic acid amplification testing (NAAT) with a focus on specific automated Polymerase Chain Reaction (PCR) testing and platforms such as the recently launched cobas® 6800 and cobas® 8800 Systems. The benefits of such automation for different stakeholders including patients, clinicians, laboratory personnel, hospital administrators, payers, and manufacturers are described. Areas Covered: The authors describe how molecular diagnostics has achieved total laboratory automation over time, rivaling clinical chemistry to significantly improve testing efficiency. Finally, the authors discuss how advances in automation decrease the development time for new tests enabling clinicians to more readily provide test results. Expert Commentary: The advancements described enable complete diagnostic solutions whereby specific test results can be combined with relevant patient data sets to allow healthcare providers to deliver comprehensive clinical recommendations in multiple fields ranging from infectious disease to outbreak management and blood safety solutions.

Hyperspectral image analysis for rapid and accurate discrimination of bacterial infections: A benchmark study

With the rapid diffusion of Full Laboratory Automation systems, Clinical Microbiology is currently experiencing a new digital revolution. The ability to capture and process large amounts of visual data from microbiological specimen processing enables the definition of completely new objectives. These include the direct identification of pathogens growing on culturing plates, with expected improvements in rapid definition of the right treatment for patients affected by bacterial infections. In this framework, the synergies between light spectroscopy and image analysis, offered by hyperspectral imaging, are of prominent interest. This leads us to assess the feasibility of a reliable and rapid discrimination of pathogens through the classification of their spectral signatures extracted from hyperspectral image acquisitions of bacteria colonies growing on blood agar plates. We designed and implemented the whole data acquisition and processing pipeline and performed a comprehensive comparison among 40 combinations of different data preprocessing and classification techniques. High discrimination performance has been achieved also thanks to improved colony segmentation and spectral signature extraction. Experimental results reveal the high accuracy and suitability of the proposed approach, driving the selection of most suitable and scalable classification pipelines and stimulating clinical validations.

Dielectrophoresis for Biomedical Sciences Applications: A Review

Dielectrophoresis (DEP) is a label-free, accurate, fast, low-cost diagnostic technique that uses the principles of polarization and the motion of bioparticles in applied electric fields. This technique has been proven to be beneficial in various fields, including environmental research, polymer research, biosensors, microfluidics, medicine and diagnostics. Biomedical science research is one of the major research areas that could potentially benefit from DEP technology for diverse applications. Nevertheless, many medical science research investigations have yet to benefit from the possibilities offered by DEP. This paper critically reviews the fundamentals, recent progress, current challenges, future directions and potential applications of research investigations in the medical sciences utilizing DEP technique. This review will also act as a guide and reference for medical researchers and scientists to explore and utilize the DEP technique in their research fields.

High diversity of airborne fungi in the hospital environment as revealed by meta-sequencing-based microbiome analysis

Invasive fungal infections acquired in the hospital have progressively emerged as an important cause of life-threatening infection. In particular, airborne fungi in hospitals are considered critical pathogens of hospital-associated infections. To identify the causative airborne microorganisms, high-volume air samplers were utilized for collection, and species identification was performed using a culture-based method and DNA sequencing analysis with the Illumina MiSeq and HiSeq 2000 sequencing systems. Few bacteria were grown after cultivation in blood agar. However, using microbiome sequencing, the relative abundance of fungi, Archaea species, bacteria and viruses was determined. The distribution characteristics of fungi were investigated using heat map analysis of four departments, including the Respiratory Intensive Care Unit, Intensive Care Unit, Emergency Room and Outpatient Department. The prevalence of Aspergillus among fungi was the highest at the species level, approximately 17% to 61%, and the prevalence of Aspergillus fumigatus among Aspergillus species was from 34% to 50% in the four departments. Draft genomes of microorganisms isolated from the hospital environment were obtained by sequence analysis, indicating that investigation into the diversity of airborne fungi may provide reliable results for hospital infection control and surveillance.

Utilization Management in a Large Community Hospital

The utilization management of laboratory tests in a large community hospital is similar to academic and smaller community hospitals. There are numerous factors that influence laboratory utilization. Outside influences like hospitals buying physician practices, increasing numbers of hospitalists, and hospital consolidation will influence the number and complexity of the test menu that will need to be monitored for over and/or under utilization in the central laboratory and reference laboratory. CLIA’88 outlines the four test categories including point-of-care testing (waived) and provider-performed microscopy that need laboratory test utilization management. Incremental cost analysis is the most efficient method for evaluating utilization reduction cost savings. Economies of scale define reduced unit cost per test as test volume increases. Outreach programs in large community hospitals provide additional laboratory tests from non-patients in physician offices, nursing homes, and other hospitals. Disruptive innovations are changing the present paradigms in clinical diagnostics, like wearable sensors, MALDI-TOF, multiplex infectious disease panels, cell-free DNA, and others. Obsolete tests need to be universally defined and accepted by manufacturers, physicians, laboratories, and hospitals, to eliminate access to their reagents and testing platforms.

Bacterial culture detection and identification in blood agar plates with an optoelectronic nose

Clinical microbiology automation is currently limited by the lack of an in-plate culture identification system. Using an inexpensive, printed, disposable colorimetric sensor array (CSA) responsive to the volatiles emitted into plate headspace by microorganisms during growth, we report here that not only the presence but the species of bacteria growing in plate was identified before colonies are visible. In 1894 trials, 15 pathogenic bacterial species cultured on blood agar were identified with 91.0% sensitivity and 99.4% specificity within 3 hours of detection. The results indicate CSAs integrated into Petri dish lids present a novel paradigm to speciate microorganisms, well-suited to integration into automated plate handling systems.

Emerging technologies for the clinical microbiology laboratory

In this review we examine the literature related to emerging technologies that will help to reshape the clinical microbiology laboratory. These topics include nucleic acid amplification tests such as isothermal and point-of-care molecular diagnostics, multiplexed panels for syndromic diagnosis, digital PCR, next-generation sequencing, and automation of molecular tests. We also review matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) and electrospray ionization (ESI) mass spectrometry methods and their role in identification of microorganisms. Lastly, we review the shift to liquid-based microbiology and the integration of partial and full laboratory automation that are beginning to impact the clinical microbiology laboratory.

A review of the current state of digital plate reading of cultures in clinical microbiology

Digital plate reading (DPR) is increasingly being adopted as a means to facilitate the analysis and improve the quality and efficiency within the clinical microbiology laboratory. This review discusses the role of DPR in the context of total laboratory automation and explores some of the platforms currently available or in development for digital image capturing of microbial growth on media. The review focuses on the advantages and challenges of DPR. Peer-reviewed studies describing the utility and quality of these novel DPR systems are largely lacking, and professional guidelines for DPR implementation and quality management are needed. Further development and more widespread adoption of DPR is anticipated.

On the application of optical forward-scattering to bacterial identification in an automated clinical analysis perspective

The Optical Forward Scattering (OFS) technique can be used to identify pathogens by direct observation of bacteria colonies growing on a culture plate. The identification is based on the acquisition of scattering images from isolated colonies and their subsequent comparison with reference images acquired from known bacteria. The technique has been mainly studied for the identification of pathogens in the food-safety field. This paper focuses on the possibility of extending the applicability of the technique to the field of clinical laboratory automation. This scenario requires that the paradigm of image acquisition at fixed colony-dimension, well established in the food-safety applications, should be substituted by an acquisition at fixed incubation time. As a consequence, the scatterometer must be adjustable in real-time for adapting to the actual features of the bacterial colony. The paper describes an OFS system prototype qualified by the possibility to tune both the laser beam diameter and the acquisition camera field of view. Preliminary experiments on bacteria cultures from pathogens causing infections of the urinary tract show that the proposed approach is promising for the development of an automated bacteria identification station. The new OFS approach also involves an alternative method for building a reference image database for subsequent image analysis.

Bacterial colony counting by Convolutional Neural Networks

Counting bacterial colonies on microbiological culture plates is a time-consuming, error-prone, nevertheless fundamental task in microbiology. Computer vision based approaches can increase the efficiency and the reliability of the process, but accurate counting is challenging, due to the high degree of variability of agglomerated colonies. In this paper, we propose a solution which adopts Convolutional Neural Networks (CNN) for counting the number of colonies contained in confluent agglomerates, that scored an overall accuracy of the 92.8% on a large challenging dataset. The proposed CNN-based technique for estimating the cardinality of colony aggregates outperforms traditional image processing approaches, becoming a promising approach to many related applications.

Clinical microbiology informatics

The clinical microbiology laboratory has responsibilities ranging from characterizing the causative agent in a patient's infection to helping detect global disease outbreaks. All of these processes are increasingly becoming partnered more intimately with informatics. Effective application of informatics tools can increase the accuracy, timeliness, and completeness of microbiology testing while decreasing the laboratory workload, which can lead to optimized laboratory workflow and decreased costs. Informatics is poised to be increasingly relevant in clinical microbiology, with the advent of total laboratory automation, complex instrument interfaces, electronic health records, clinical decision support tools, and the clinical implementation of microbial genome sequencing. This review discusses the diverse informatics aspects that are relevant to the clinical microbiology laboratory, including the following: the microbiology laboratory information system, decision support tools, expert systems, instrument interfaces, total laboratory automation, telemicrobiology, automated image analysis, nucleic acid sequence databases, electronic reporting of infectious agents to public health agencies, and disease outbreak surveillance. The breadth and utility of informatics tools used in clinical microbiology have made them indispensable to contemporary clinical and laboratory practice. Continued advances in technology and development of these informatics tools will further improve patient and public health care in the future.

The automated clinical microbiology laboratory: fact or fantasy?

Automated chemistry laboratories dependent on robotic processes are the standard in both academic and large community hospital settings. Diagnostic microbiology manufacturers are betting that robotics will be used for specimen processing, plate reading, and organism identification in the near future. These systems are highly complex and have large footprints and hefty price tags. However, they are touted as being more efficient, rapid, and accurate than standard processes. Certain features, such as image collection, are highly innovative. Hospital administrators may be swayed to institute these new systems because of the promise of the need for fewer skilled workers, higher throughput, and greater efficiency. They also may be swayed by the fact that workers with the requisite clinical microbiology skills are becoming more difficult to find, and this technology should allow fewer skilled workers to handle larger numbers of cultures. In this Point-Counterpoint, Nate Ledeboer, Medical Director, Clinical Microbiology and Molecular Diagnostics, Dynacare Laboratories, and Froedtert Hospital, Milwaukee, WI, will explain why he believes that this approach will become widespread, while Steve Dallas of the University of Texas Health Science Center San Antonio explains why he thinks that this automation may not become widely used.