Correlation of manual semi-quantitative and automated quantitative Ki-67 proliferative index with OncotypeDXTM recurrence score in invasive breast carcinoma.

BACKGROUND: Ki-67 immunohistochemistry (IHC) staining is a widely used cancer proliferation assay; however, its limitations could be improved with automated scoring. The OncotypeDXTM Recurrence Score (ORS), which primarily evaluates cancer proliferation genes, is a prognostic indicator for breast cancer chemotherapy response; however, it is more expensive and slower than Ki-67. OBJECTIVE: To compare manual Ki-67 (mKi-67) with automated Ki-67 (aKi-67) algorithm results based on manually selected Ki-67 "hot spots" in breast cancer, and correlate both with ORS. METHODS: 105 invasive breast carcinoma cases from 100 patients at our institution (2011-2013) with available ORS were evaluated. Concordance was assessed via Cohen's Kappa (κ). RESULTS: 57/105 cases showed agreement between mKi-67 and aKi-67 (κ 0.31, 95% CI 0.18-0.45), with 41 cases overestimated by aKi-67. Concordance was higher when estimated on the same image (κ 0.53, 95% CI 0.37-0.69). Concordance between mKi-67 score and ORS was fair (κ 0.27, 95% CI 0.11-0.42), and concordance between aKi-67 and ORS was poor (κ 0.10, 95% CI -0.03-0.23). CONCLUSIONS: These results highlight the limits of Ki-67 algorithms that use manual "hot spot" selection. Due to suboptimal concordance, Ki-67 is likely most useful as a complement to, rather than a surrogate for ORS, regardless of scoring method.

How Reliable Is Automated Urinalysis in Acute Kidney Injury?

OBJECTIVE: Examination of urine sediment is crucial in acute kidney injury (AKI). In such renal injury, tubular epithelial cells, epithelial cell casts, and dysmorphic red cells may provide clues to etiology. The aim of this study was to compare automated urinalysis findings with manual microscopic analysis in AKI. METHODS: Samples from patients diagnosed with AKI and control patients were included in the study. Red blood cells, white blood cells, renal tubular epithelial cells/small round cells, casts, and pathologic (path) cast counts obtained microscopically and by a UF1000i cytometer were compared by Spearman test. Logistic regression analysis was used to assess the ability to predict AKI from parameters obtained from the UF1000i. RESULTS: There was poor correlation between manual and automated analysis in AKI. None of the parameters could predict AKI using logistic regression analysis. However, the increment in the automated path cast count increased the odds of AKI 93 times. CONCLUSION: Automated urinalysis parameters are poor predictors of AKI, and there is no agreement with manual microscopy.

[Digital morphology analyzers in hematology: a French survey]. / État des lieux des pratiques d'utilisation du microscope automatisé en hématologie en France.

Digital morphology hematology analyzers are becoming more prevalent in laboratories Aims: investigate practices and assess the benefits and limits of digital automated microscopy in hematology. METHODS: questionnaire sent by e-mail in 2018 to French public and private laboratories. RESULTS: out of 118 responses (56 private, 62 public), 117 participants had a CellaVision® microscope, 1 had a West Medica®. Practices were sometimes different, especially in the choice of smears to be digitized or for quality controls (16.1% had internal quality controls, 48.3% external quality controls); 62.1% never used the red blood cell (RBC) characterization tool; the number of cells counted varied from 100 to 400. The study reported a high rate of agreement for these benefits: traceability (95.7%), staff training (94.1%), eye strain (91.4%), risk of error (87.2%), time saving (83.6%). Among the disadvantages, apart from the inadequate search for platelets clumps (93.2%), the agreement rates were often lower: adaptation to digital images (61.2%), difficult assessment of atypical morphologies (49.6%) or RBC morphology (49.6%). CONCLUSION: despite well-established benefits, standardization of practices and technical improvement are still needed.

Inter-laboratory comparison of Ki-67 proliferating index detected by visual assessment and automated digital image analysis.

BACKGROUND: Proliferation rate is a major determinant of the biologic behavior of the tumor and provides information that can be used to guide treatment decisions. METHODS: This ring study included 27 pathologists from 14 Institutions, in order to assess inter-observer concordance between pathologists in Croatia. We analyzed Ki-67 proliferative index on ten randomly selected breast cancer samples comparing consistency between visual assessment using light microscopy compared to digital image analyses results from one central laboratory as a referral value. RESULTS: When we analyzed Ki-67 as numeric value high concordance rate was found between Ki-67 score visually assessed in all participating Institutions compared to referral value assessed by digital image analysis (ICC 0.76, 95% CI 0.58-0.91), and Krippendorff's alpha was 0.79 (95% CI 0.58-1.00). Concordance was better in slides with higher Ki-67 values. When we categorized Ki-67 values according to generally accepted 20% cut-off value we noticed the lower concordance rate among participants in our study. CONCLUSION: Proliferation remains one of the most important parameters for tumor characterization helpful in making clinical decisions, but it should be used with great caution. Standardization of the Ki-67 assessment is essential and proliferating index should be expressed as exact numeric value. For patients with proliferative index near the cut-off value, other factors must be considered in making clinical decisions.

Implementation of total laboratory automation at a tertiary care hospital in Saudi Arabia: effect on turnaround time and cost efficiency.

BACKGROUND: Total laboratory automation (TLA) is a relatively new way of improving the management of high volume clinical laboratories. TLA may reduce staff, reduce operating costs, decrease testing time and provide enhanced process control. OBJECTIVES: Establish a cost efficient TLA that is less labor intensive, improves productivity and reduces turnaround time (TAT). DESIGN: Implementation of TLA for random glucose and troponin-T as sentinel tests to compare change in TAT. SETTING: Tertiary hospital with high volume of laboratory tests. METHODS: Routine patient samples for random glucose and troponin-T were used to capture TAT. Information on staff grades and schedules before and after implementing the TLA, and cost of contracts to deliver the service were collected. MAIN OUTCOME MEASURES: TAT, cost efficiency, and reduction in labor. RESULTS: The consolidation of contracts resulted in a reduction of 28.8 million SAR in direct costs. Staffing cost was reduced by 1.14 million SAR with less senior staff required; there were reductions in staff at both senior and junior level. The overall TAT for all tests was reduced by 32% in 2016 (after TLA implementation) compared to 2012 (before TLA implementation). The median TAT for random glucose tests was reduced by 21% (to 55.7 minutes in 2016 from 70.1 minutes in 2012). Evidence of test optimization by exploring the impact of stat tests, auto-dilutions and reruns on the overall TAT of the TLA is shown by comparing troponin T TATs after reclassifying stat tests (in 2016) to routine (in 2017). At the 75th percentile, there was a 27% reduction in TAT when comparing August 2016 to March 2017 with a 19% reduction in median TAT. CONCLUSION: By moving from stat to routine assays, the TAT was reduced, which is counter-intuitive. The use of stat assays slowed down the performance of the TLA. A careful review of the mix of assays should be conducted to maximize performance and to ensure that the system delivers what is required. LIMITATIONS: Room for improvement by systematically analyzing and reviewing the impact of making minor changes that could have significant impact on TAT. CONFLICT OF INTEREST: None.

Blood Culture Turnaround Time in U.S. Acute Care Hospitals and Implications for Laboratory Process Optimization.

The rapid identification of blood culture isolates and antimicrobial susceptibility test (AST) results play critical roles for the optimal treatment of patients with bloodstream infections. Whereas others have looked at the time to detection in automated culture systems, we examined the overall time from specimen collection to actionable test results. We examined four points of time, namely, blood specimen collection, Gram stain, organism identification (ID), and AST reports, from electronic data from 13 U.S. hospitals for the 11 most common, clinically significant organisms in septic patients. We compared the differences in turnaround times and the times from when specimens were collected and the results were reported in the 24-h spectrum. From January 2015 to June 2016, 165,593 blood specimens were collected, of which, 9.5% gave positive cultures. No matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry was used during the study period. Across the 10 common bacterial isolates (n = 6,412), the overall median (interquartile range) turnaround times were 0.80 (0.64 to 1.08), 1.81 (1.34 to 2.46), and 2.71 (2.46 to 2.99) days for Gram stain, organism ID, and AST, respectively. For all positive cultures, approximately 25% of the specimens were collected between 6:00 a.m. and 11:59 a.m. In contrast, more of the laboratory reporting times were concentrated between 6:00 a.m. and 11:59 a.m. for Gram stain (43%), organism ID (78%), and AST (82%), respectively (P < 0.001). The overall average turnaround times from specimen collection for Gram stain, organism ID, and AST were approximately 1, 2, and 3 days, respectively. The laboratory results were reported predominantly in the morning hours. Laboratory automation and work flow optimization may play important roles in reducing the microbiology result turnaround time.

Effectiveness of the International Consensus Group criteria for manual peripheral smear review.

CONTEXT: The International Consensus Group for Hematology Review (ICGHR) are essentially review criteria designed to reduce the number of manual smear reviews following analysis in automated hematology analyzers (AHAs). Although AHAs are an indispensable part of the present-day clinical laboratory, manual smear reviews still play an integral role in identifying morphological abnormalities and to confirm the results of the analyzers. AIMS: The aim of this study is to evaluate the efficacy of the ICGHR criteria and our laboratory criteria using the Sysmex XN-1000 for manual peripheral smear review (MSR). STUDY DESIGN: A prospective cross-sectional comparative study between the two sets of criteria for MSR was performed. MATERIAL AND METHODS: A total of 860 whole blood samples sent over a period of 19 months for complete blood count testing to our laboratory were collected using systematic random sampling. Truth tables were prepared for each set of criteria. Tests of proportion were used to compare performance specifications between both sets of criteria. RESULTS: Using ICGHR criteria, sensitivity was 81.58%, specificity was 84.61%, 83.38% positive predictive value, and 82.92% negative predictive value. The microscopic smear review rate was 47.56% and efficiency was 83.14%. Using our laboratory criteria, sensitivity was 98.80%, specificity was 41.40%, positive predictive value of 61.46%, and negative predictive value of 97.34%. The microscopic smear review rate was 78.14% and efficiency 69.30%. CONCLUSIONS: There was a significant reduction in the microscopic smear review rates using the ICGHR criteria compared to our laboratory criteria. The ICGHR criteria can thus be adapted to daily laboratory practice provided they are first optimized and locally validated before use.

Request Pattern, Pre-Analytical and Analytical Conditions of Urinalysis in Primary Care: Lessons from a One-Year Large-Scale Multicenter Study.

BACKGROUND: To study the urinalysis request, pre-analytical sample conditions, and analytical procedures. METHODS: Laboratories were asked to provide the number of primary care urinalyses requested, and to fill out a questionnaire regarding pre-analytical conditions and analytical procedures. RESULTS: 110 laboratories participated in the study. 232.5 urinalyses/1,000 inhabitants were reported. 75.4% used the first morning urine. The sample reached the laboratory in less than 2 hours in 18.8%, between 2 - 4 hours in 78.3%, and between 4 - 6 hours in the remaining 2.9%. 92.5% combined the use of test strip and particle analysis, and only 7.5% used the strip exclusively. All participants except one performed automated particle analysis depending on strip results; in 16.2% the procedure was only manual. CONCLUSIONS: Urinalysis was highly requested. There was a lack of compliance with guidelines regarding time between micturition and analysis that usually involved the combination of strip followed by particle analysis.

The use of automated Ki67 analysis to predict Oncotype DX risk-of-recurrence categories in early-stage breast cancer.

Ki67 is a commonly used marker of cancer cell proliferation, and has significant prognostic value in breast cancer. In spite of its clinical importance, assessment of Ki67 remains a challenge, as current manual scoring methods have high inter- and intra-user variability. A major reason for this variability is selection bias, in that different observers will score different regions of the same tumor. Here, we developed an automated Ki67 scoring method that eliminates selection bias, by using whole-slide analysis to identify and score the tumor regions with the highest proliferative rates. The Ki67 indices calculated using this method were highly concordant with manual scoring by a pathologist (Pearson's r = 0.909) and between users (Pearson's r = 0.984). We assessed the clinical validity of this method by scoring Ki67 from 328 whole-slide sections of resected early-stage, hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer. All patients had Oncotype DX testing performed (Genomic Health) and available Recurrence Scores. High Ki67 indices correlated significantly with several clinico-pathological correlates, including higher tumor grade (1 versus 3, P<0.001), higher mitotic score (1 versus 3, P<0.001), and lower Allred scores for estrogen and progesterone receptors (P = 0.002, 0.008). High Ki67 indices were also significantly correlated with higher Oncotype DX risk-of-recurrence group (low versus high, P<0.001). Ki67 index was the major contributor to a machine learning model which, when trained solely on clinico-pathological data and Ki67 scores, identified Oncotype DX high- and low-risk patients with 97% accuracy, 98% sensitivity and 80% specificity. Automated scoring of Ki67 can thus successfully address issues of consistency, reproducibility and accuracy, in a manner that integrates readily into the workflow of a pathology laboratory. Furthermore, automated Ki67 scores contribute significantly to models that predict risk of recurrence in breast cancer.

Wet Lab Accelerator: A Web-Based Application Democratizing Laboratory Automation for Synthetic Biology.

Wet Lab Accelerator (WLA) is a cloud-based tool that allows a scientist to conduct biology via robotic control without the need for any programming knowledge. A drag and drop interface provides a convenient and user-friendly method of generating biological protocols. Graphically developed protocols are turned into programmatic instruction lists required to conduct experiments at the cloud laboratory Transcriptic. Prior to the development of WLA, biologists were required to write in a programming language called "Autoprotocol" in order to work with Transcriptic. WLA relies on a new abstraction layer we call "Omniprotocol" to convert the graphical experimental description into lower level Autoprotocol language, which then directs robots at Transcriptic. While WLA has only been tested at Transcriptic, the conversion of graphically laid out experimental steps into Autoprotocol is generic, allowing extension of WLA into other cloud laboratories in the future. WLA hopes to democratize biology by bringing automation to general biologists.

Percentage of hyperdense cells: Automated parameter to hereditary spherocytosis screening.

BACKGROUND: The hereditary spherocytosis (HS) is a common cause of inherited hemolytic anemia that is difficult to identify in many cases. Currently, there are new economic parameters for red cell disorder evaluation, such as hyperdense cell percentage (%Hyper) obtained from automated analyzers. OBJECTIVE: In this study we determined the %Hyper efficacy and compared its accuracy with a flow cytometry method in HS, hemoglobinopathy and healthy individuals, in order to allow the use of %Hyper in HS screening. METHODS: Patients treated at the outpatient clinic at the Hospital de Clínicas de Porto Alegre (HCPA) were allocated into three groups according to their clinical condition: HS, hemoglobinopathy or healthy groups. Flow-cytometric osmotic fragility test (FCM OF) method was used as reference to compare with %Hyper, both performed from K2EDTA samples. RESULTS: Fifty-eight individuals were included in this study. We found that the %Hyper cut-off point of 6.4% showed an excellent sensitivity (92.3%) and specificity (90.7%) to detect HS. Besides, %Hyper presented a significant negative correlation with FCM OF in identifying HS (Rs=-0.525; P<0.001). CONCLUSIONS: %Hyper could be a tool for screening HS, before requesting additional tests. It is a fast and cost-effective test, which is easily obtained in complete blood count, favoring its use in clinical laboratories. However, this test does not replace flow cytometric methods for confirmation of atypical cases.

The association of eGFR reporting with the timing of dialysis initiation.

Automated reporting of eGFR by laboratories has been widely implemented during the last decade. Over this same period, a steady increase in eGFR at dialysis initiation has been reported. This study examined trends in eGFR at dialysis initiation over time among incident dialysis patient populations before and after eGFR reporting. All patients who initiated dialysis between January of 2001 and December of 2010 in four Canadian provinces that implemented province-wide automated eGFR reporting and had an eGFR measure at dialysis initiation were included in the study (n=22,208). The primary outcome was change over time in eGFR among patients at dialysis initiation. An interrupted time series and adjusted multilevel regression models were used to determine the differences in eGFR at dialysis initiation before and after reporting. We observed a linear increase in the mean eGFR at dialysis initiation from 9.1 to 10.8 ml/min per m(2) during the study period. There was no change in the trajectory of the eGFR at dialysis initiation before or after eGFR reporting in crude or adjusted models accounting for case mix and facility characteristics. These findings were consistent among age and sex strata and when the proportions of patients with an eGFR≥10.5 or ≥12 ml/min per m(2) were examined. In conclusion, automated laboratory-based eGFR reporting did not influence eGFR at dialysis initiation among incident dialysis patient populations. Concerns that widespread eGFR reporting leads to earlier dialysis initiation are not supported by this study.

Time-Motion Analysis of Four Automated Systems for the Detection of Chlamydia trachomatis and Neisseria gonorrhoeae by Nucleic Acid Amplification Testing.

Next-generation diagnostics for Chlamydia trachomatis and Neisseria gonorrhoeae are available on semi- or fully-automated platforms. These systems require less hands-on time than older platforms and are user friendly. Four automated systems, the ABBOTT m2000 system, Becton Dickinson Viper System with XTR Technology, Gen-Probe Tigris DTS system, and Roche cobas 4800 system, were evaluated for total run time, hands-on time, and walk-away time. All of the systems evaluated in this time-motion study were able to complete a diagnostic test run within an 8-h work shift, instrument setup and operation were straightforward and uncomplicated, and walk-away time ranged from approximately 90 to 270 min in a head-to-head comparison of each system. All of the automated systems provide technical staff with increased time to perform other tasks during the run, offer easy expansion of the diagnostic test menu, and have the ability to increase specimen throughput.

Development of a prediction model on the acceptance of electronic laboratory notebooks in academic environments.

Documentation of research data plays a key role in the biomedical engineering innovation processes. It makes an important contribution to the protection of intellectual property, the traceability of results and fulfilling the regulatory requirement. Because of the increasing digitalization in laboratories, an electronic alternative to the commonly-used paper-bound notebooks could contribute to the production of sophisticated documentation. However, compared to in an industrial environment, the use of electronic laboratory notebooks is not widespread in academic laboratories. Little is known about the acceptance of an electronic documentation system and the underlying reasons for this. Thus, this paper aims to establish a prediction model on the potential preference and acceptance of scientists either for paper-based or electronic documentation. The underlying data for the analysis originate from an online survey of 101 scientists in industrial, academic and clinical environments. Various parameters were analyzed to identify crucial factors for the system preference using binary logistic regression. The analysis showed significant dependency between the documentation system preference and the supposed workload associated with the documentation system (p<0.006; odds ratio=58.543) and an additional personal component. Because of the dependency of system choice on specific parameters it is possible to predict the acceptance of an electronic laboratory notebook before implementation.

Pathology laboratories productivity evaluation in Turkey.

OBJECTIVE: Efficiency criteria and automation in pathology laboratories have been set in a limited number of studies usually originated from the United States. A questionnaire has been prepared to determine the situation and define the criteria for adaptation in our country. MATERIAL AND METHOD: The survey was sent to all pathology laboratories and, 302 responded. The survey questionned of pathology laboratories efficiencies, staff workloads, methods applied, devices used, and physical conditions. Work flow productivity was obtained by dividing the annual number of blocks to working hours multiplied by the number of technicians. The hospitals were categorized to 3 groups according to providing training or not and privacy, and to 4 groups according to the annual biopsy numbers. The data entered through the SPSS 16.0 statistical package program, analysis of distribution criteria, significance of the difference between means tests were used. RESULTS: The annual biopsy numbers were significantly higher in education units, but below the limit of productivity levels for all laboratories. The device hardware and automation correlated with annual biopsy numbers. However, the laboratories of limited capacity have redundant automation. Histochemical and immunohistochemical staining numbers were high. Liquid-based cytology techniques were used more significantly in private hospitals. Archiving times were not standard. A serious shortage of working space in service hospitals was noted. Work flow productivity in education units was at the border, and low in other units. CONCLUSION: All pathology laboratories in our country should define and improve their productivities. Formalizing of archiving times is very important for future malpractice lawsuits.