Efficient, Unbiased Quality Assurance Of Automated Tissue Analysis Applicable To Daily Pathology Practice

Introduction/ Background Quantification of tissue biomarkers is increasingly demanded for diagnosis and is commonly performed by expert pathologists using microscopy of stained tissue at high magnification. This manual scoring is a reasonably fast, supervised procedure, but it suffers from inter- and intra-observer differences due to a) differences in selection of regions of interest, b) differences in quantity estimation, c) intra-tissue variability of biomarker expression. Computers and whole slide microscopy scanners have made it feasible to perform high-capacity analysis of high resolution images of tissue. Image analysis (IA) enables better reproducibility, but conversely, the unsupervised analysis introduces challenges regarding accuracy. Furthermore, borderline cases will always have to be rigorously inspected by pathologists. Many IA evaluation methods exist, but for pathology, a supervised comparison of experimental segmentation to an appropriately obtained standard criterion is the optimal strategy. The production of standard criterion necessitates evaluation of whole slide images to eliminate any possible region sampling bias while inter- and intra- observer bias can only be minimized by replacing any manual estimates by objective measurements. A logical step is thus to change the task of the pathologist from quantity estimation to verifying the output an automated procedure reports. Still, verification of entire tissue slides is in daily pathology practice too time-consuming. To minimize the workload pathology is turning to stereological methods which aim to efficiently quantify matter unbiasedly and have been proved useful for supervised validation of automated analysis for Ki67 scoring of breast cancer. However, the workload still needs to be reduced to a level comparable to the manual scoring procedure. Aims We aim to enable high accuracy, objective evaluation of automated image analysis with a workload and workflow feasible for daily pathology practice. This regards both production of reference data for image analysis tool calibration and continuous quality control inspection of borderline cases. Methods This study investigates proportionate sampling, a very efficient stereological sampling scheme utilizing weighted sampling of regions of automated image analysis for manual evaluation of automated IA. The sampling of regions to be inspected by a pathologist draws upon the IA to assign probability weights to all regions. This results in a highly efficient, unbiased sampling and quality assurance estimate for the automated image analysis. Results Presented here is proof-of-concept of an efficient, unbiased image analysis evaluation methodology. The task of the pathologist is changed from quantity estimation to instead annotate discrepancies between the output from the IA and the tissue in a few sampled regions. From the annotations an unbiased quality assurance estimate of the IA can be estimated including levels of accuracy obtainable and expected workloads. This confirms that the stereological proportionate sampling enables manual verification of automated whole slide image analysis for unbiased reference dataset creation and quality control inspection in borderline cases. Furthermore, the methodology is easily integrated into both image analysis platforms for production of reference data sets and laboratory information systems for daily pathology practices.

Human Herpesvirus 8, Southern Siberia

International audienceLette

Impact of HIV Infection and Kaposi Sarcoma on Human Herpesvirus-8 Mucosal Replication and Dissemination in Uganda

Kaposi sarcoma (KS) is the leading cause of cancer in Uganda and occurs in people with and without HIV. Human herpesvirus-8 (HHV-8) replication is important both in transmission of HHV-8 and progression to KS. We characterized the sites and frequency of HHV-8 detection in Ugandans with and without HIV and KS.Participants were enrolled into one of four groups on the basis of HIV and KS status (HIV negative/KS negative, HIV positive/KS negative, HIV negative/KS positive, and HIV positive/KS positive). Participants collected oral swabs daily and clinicians collected oral swabs, anogenital swabs, and plasma samples weekly over 4 weeks. HHV-8 DNA at each site was quantified by polymerase chain reaction (PCR).78 participants collected a total of 2063 orals swabs and 358 plasma samples. Of these, 428 (21%) oral swabs and 96 (27%) plasma samples had detectable HHV-8 DNA. HHV-8 was detected more frequently in both the oropharynx of persons with KS (24 (57%) of 42 persons with KS vs. 8 (22%) of 36 persons without, p = 0.002) and the peripheral blood (30 (71%) of 42 persons with KS vs. 8 (22%) of 36 persons without, p<0.001). In a multivariate model, HHV-8 viremia was more frequent among men (IRR = 3.3, 95% CI = 1.7-6.2, p<0.001), persons with KS (IRR = 3.9, 95% CI = 1.7-9.0, p = 0.001) and persons with HIV infection (IRR = 1.7, 95% CI = 1.0-2.7, p = 0.03). Importantly, oral HHV-8 detection predicted the subsequent HHV-8 viremia. HHV-8 viremia was significantly more common when HHV-8 DNA was detected from the oropharynx during the week prior than when oral HHV-8 was not detected (RR = 3.3, 95% CI = 1.8-5.9 p<0.001). Genital HHV-8 detection was rare (9 (3%) of 272 swabs).HHV-8 detection is frequent in the oropharynx and peripheral blood of Ugandans with endemic and epidemic KS. Replication at these sites is highly correlated, and viremia is increased in men and those with HIV. The high incidence of HHV-8 replication at multiple anatomic sites may be an important factor leading to and sustaining the high prevalence of KS in Uganda

Seroprevalence of HHV-8, CMV, and EBV among the general population in Ghana, West Africa

<p>Abstract</p> <p>Background</p> <p>Human herpesvirus 8 (HHV-8), cytomegalovirus (CMV) and Epstein-Barr virus (EBV) are prevalent in Africa, but less common elsewhere and the modes of transmission are still subject to debate. Generally, they rarely cause disease in the immunocompetent host but are highly oncogenic when associated with immunosuppression. Although the high prevalence of HHV-8, CMV and EBV has been well documented in Africa, such data are sparse from Ghana.</p> <p>Methods</p> <p>Serum samples from 3275 HIV-seronegative healthy blood donors and 250 HIV-AIDS patients were tested for antibodies specific for HHV-8, CMV and EBV by IgG ELISA assays. Differences in seropositivity rates by gender and age were evaluated using the Chi-square test with Yates correction.</p> <p>Results</p> <p>Of the 3275 HIV-seronegative healthy blood donors tested, 2573 (78.6%) were males and 702 (21.4%) were females, with ages ranging from 18 to 65 years (median 32.6; mean 31.2; mode 30). Of the 250 HIV-AIDS patients tested, 140 (56%) were males and 110 (44%) were females, with ages ranging from 17 to 64 years (median 30.8; mean 30.3; mode 28). Among the HIV-seronegative healthy blood donors, overall seroprevalence of HHV-8, CMV and EBV was 23.7%, 77.6% and 20.0%, respectively. Among the HIV-AIDS patients, overall seroprevalence of HHV-8, CMV and EBV was 65.6%, 59.2% and 87.2%, respectively. The seroprevalence of HHV-8 (p < 0.005) and EBV (p < 0.001) was statistically significantly higher in HIV-AIDS patients compared to HIV-seronegative healthy blood donors. There was no statistically significant difference (p = 0.24) between CMV seroprevalence in HIV-AIDS patients and HIV-seronegative healthy blood donors. Age and gender were not independent determinants (p > 0.05) for all three infections among HIV-seronegative healthy blood donors and HIV-AIDS patients in Ghana.</p> <p>Conclusion</p> <p>The results presented herein indicate that HHV-8, CMV and EBV infections are hyperendemic in both HIV-seronegative and HIV-seropositive Ghanaians, and suggest primarily a horizontal route of transmission of these three viral infections in Ghana.</p

The LifeCycle Project-EU Child Cohort Network : a federated analysis infrastructure and harmonized data of more than 250,000 children and parents

Early life is an important window of opportunity to improve health across the full lifecycle. An accumulating body of evidence suggests that exposure to adverse stressors during early life leads to developmental adaptations, which subsequently affect disease risk in later life. Also, geographical, socio-economic, and ethnic differences are related to health inequalities from early life onwards. To address these important public health challenges, many European pregnancy and childhood cohorts have been established over the last 30 years. The enormous wealth of data of these cohorts has led to important new biological insights and important impact for health from early life onwards. The impact of these cohorts and their data could be further increased by combining data from different cohorts. Combining data will lead to the possibility of identifying smaller effect estimates, and the opportunity to better identify risk groups and risk factors leading to disease across the lifecycle across countries. Also, it enables research on better causal understanding and modelling of life course health trajectories. The EU Child Cohort Network, established by the Horizon2020-funded LifeCycle Project, brings together nineteen pregnancy and childhood cohorts, together including more than 250,000 children and their parents. A large set of variables has been harmonised and standardized across these cohorts. The harmonized data are kept within each institution and can be accessed by external researchers through a shared federated data analysis platform using the R-based platform DataSHIELD, which takes relevant national and international data regulations into account. The EU Child Cohort Network has an open character. All protocols for data harmonization and setting up the data analysis platform are available online. The EU Child Cohort Network creates great opportunities for researchers to use data from different cohorts, during and beyond the LifeCycle Project duration. It also provides a novel model for collaborative research in large research infrastructures with individual-level data. The LifeCycle Project will translate results from research using the EU Child Cohort Network into recommendations for targeted prevention strategies to improve health trajectories for current and future generations by optimizing their earliest phases of life.Peer reviewe

Using Digital Image Analysis Algorithms to quantify Hypoxia Inducible Factors labelling index in glioma samples

CERVOXYNational audienc