Assessing post-analytical phase harmonization in European laboratories: a survey promoted by the EFLM Working Group on Harmonization.

OBJECTIVES: Harmonization of the laboratory total testing process (TTP) is critical to improving patient outcome. In 2016, an EFLM survey on the harmonization of TTP underlined the serious shortcomings pertaining to the post-analytical phase. In 2023, the WG-H conducted a new survey aiming to update information in the 2016 harmonization report in order to ascertain whether countries that had declared they were keen to adopt SI units had continued with this program, the aim being to verify the state-of art in harmonization units in areas of laboratory medicine not included in the previous survey. METHODS: Questionnaires were distributed to the Presidents and National Representatives of EFLM Full Member Societies and EFLM affiliate Members. The survey questions were grouped into three categories: measurement units, reference intervals, and nomenclature/terminology, and results were evaluated using Survey Monkey software and Excel. RESULTS: A total of 123 questionnaires from 31 countries were analyzed. A trend (+19.3 %) was observed toward a wider use of SI units for general clinical biochemistry parameters. The results for tests not included in the 2016 survey (i.e., endocrinology diagnostics and coagulation panels), demonstrated that for reports on hormones, responses were satisfactory, 70-90 % of the responders adopting the recommended units, whereas for coagulation test panels, a serious lack of harmonization was found, "seconds", which are inaccurate and not recommended, being widely used units (91 %). CONCLUSIONS: The findings made in the 2023 survey demonstrated a progressive, albeit slow, improvement in harmonization reports. However, further efforts at improvement are mandatory.

Deep conditional generative model for longitudinal single-slice abdominal computed tomography harmonization.

Purpose: Two-dimensional single-slice abdominal computed tomography (CT) provides a detailed tissue map with high resolution allowing quantitative characterization of relationships between health conditions and aging. However, longitudinal analysis of body composition changes using these scans is difficult due to positional variation between slices acquired in different years, which leads to different organs/tissues being captured. Approach: To address this issue, we propose C-SliceGen, which takes an arbitrary axial slice in the abdominal region as a condition and generates a pre-defined vertebral level slice by estimating structural changes in the latent space. Results: Our experiments on 2608 volumetric CT data from two in-house datasets and 50 subjects from the 2015 Multi-Atlas Abdomen Labeling Challenge Beyond the Cranial Vault (BTCV) dataset demonstrate that our model can generate high-quality images that are realistic and similar. We further evaluate our method's capability to harmonize longitudinal positional variation on 1033 subjects from the Baltimore longitudinal study of aging dataset, which contains longitudinal single abdominal slices, and confirmed that our method can harmonize the slice positional variance in terms of visceral fat area. Conclusion: This approach provides a promising direction for mapping slices from different vertebral levels to a target slice and reducing positional variance for single-slice longitudinal analysis. The source code is available at: https://github.com/MASILab/C-SliceGen.

The effect of harmonization on the variability of PET radiomic features extracted using various segmentation methods.

PURPOSE: This study aimed to examine the robustness of positron emission tomography (PET) radiomic features extracted via different segmentation methods before and after ComBat harmonization in patients with non-small cell lung cancer (NSCLC). METHODS: We included 120 patients (positive recurrence = 46 and negative recurrence = 74) referred for PET scanning as a routine part of their care. All patients had a biopsy-proven NSCLC. Nine segmentation methods were applied to each image, including manual delineation, K-means (KM), watershed, fuzzy-C-mean, region-growing, local active contour (LAC), and iterative thresholding (IT) with 40, 45, and 50% thresholds. Diverse image discretizations, both without a filter and with different wavelet decompositions, were applied to PET images. Overall, 6741 radiomic features were extracted from each image (749 radiomic features from each segmented area). Non-parametric empirical Bayes (NPEB) ComBat harmonization was used to harmonize the features. Linear Support Vector Classifier (LinearSVC) with L1 regularization For feature selection and Support Vector Machine classifier (SVM) with fivefold nested cross-validation was performed using StratifiedKFold with 'n_splits' set to 5 to predict recurrence in NSCLC patients and assess the impact of ComBat harmonization on the outcome. RESULTS: From 749 extracted radiomic features, 206 (27%) and 389 (51%) features showed excellent reliability (ICC ≥ 0.90) against segmentation method variation before and after NPEB ComBat harmonization, respectively. Among all, 39 features demonstrated poor reliability, which declined to 10 after ComBat harmonization. The 64 fixed bin widths (without any filter) and wavelets (LLL)-based radiomic features set achieved the best performance in terms of robustness against diverse segmentation techniques before and after ComBat harmonization. The first-order and GLRLM and also first-order and NGTDM feature families showed the largest number of robust features before and after ComBat harmonization, respectively. In terms of predicting recurrence in NSCLC, our findings indicate that using ComBat harmonization can significantly enhance machine learning outcomes, particularly improving the accuracy of watershed segmentation, which initially had fewer reliable features than manual contouring. Following the application of ComBat harmonization, the majority of cases saw substantial increase in sensitivity and specificity. CONCLUSION: Radiomic features are vulnerable to different segmentation methods. ComBat harmonization might be considered a solution to overcome the poor reliability of radiomic features.

Reflections on the Saudi FDA Regulatory Experience with Smart GxP Inspections.

Smart GxP inspections have gained increasing attention due to the COVID-19 pandemic, which, understandably, made it challenging for regulatory authorities to conduct on-site inspections. Smart GxP inspections are an oversight approach developed by the SFDA to enable remote compliance assessments of establishments. In this type of inspection, appropriate technical methods and tools (such as livestreaming video) are used without requiring the presence of inspectors onsite, ensuring efficient utilization of resources and the efficiency of inspection process. The objective of this research is to examine and document the shared encounters involving remote inspections and evaluations carried out by SFDA from 2020 to 2022. This will be achieved through the evaluation of the accuracy of document evaluation and the extent to which the objectives of smart GxP inspections were met. Data were collected from local and international smart inspections reports conducted by SFDA between 2020 and 2022, covering medical device manufacturers, pharmaceutical manufacturing sites, warehouses, accreditation offices, scientific offices, and food manufacturing facilities. The results indicate that smart GxP inspections were effective in achieving visit objectives, showing a high degree of document evaluation accuracy. The findings of this study support the use of smart GxP inspections as a valuable alternative to on-site inspections, offering a practical solution to regulatory compliance during the pandemic and beyond. Although the SFDA recognizes the usefulness of smart inspections in upholding regulatory oversight in the face of various challenges, it does not endorse the complete replacement of conventional on-site inspection methods. The SFDA acknowledges significant limitations associated with the current technological resources used in remote regulatory assessments, and these limitations will be explored in the relevant sections.

Diet patterns associated with cognitive decline: methods to harmonize data from European and US cohort studies.

The impact of dietary intake on cognitive outcomes and dementia prevention is a topic of increasing interest. Meta-analyses of observational studies, mostly conducted within US and European populations, have reported benefits of healthy diet patterns on cognitive performance, but results from individual studies have been inconsistent. These inconsistencies are likely due to the diverse methodology used in studies, including different diet and cognitive function assessment instruments, follow-up periods, and analytical methods, which make drawing conclusions relevant to dietary guidance challenging. The objective of this project is to describe a protocol to conduct a retrospective harmonization study on dietary intake and cognitive health using data from European and US studies. The recommendations resulting from the project can be used to support evidence-based synthesis for future iterations of the Dietary Guidelines for Americans or other population-based dietary guidance. Additionally, this study will serve as a harmonization guide for future research on the relationship between diet patterns and cognition. The approach outlined ultimately aims to optimize resources and expedite research efforts for dementia prevention.

Corrigendum: Cancer data quality and harmonization in Europe: The experience of the BENCHISTA Project - International Benchmarking of Childhood Cancer Survival by Stage.

[This corrects the article DOI: 10.3389/fonc.2023.1232451.].

Microbiological acceptance criteria, specifications of herbal drugs and herbal drug preparations in various pharmacopoeias: a global scenario.

PURPOSE: A pharmacopoeia is a compendium of guidelines and criteria for drug quality. It was established by a national or regional entity and has legal significance. This applies to administration of drugs in a particular nation or region. METHOD: In this study, the differences and similarities of microbiological acceptance criteria, specifications for microbial enumeration of herbal drugs and herbal drug preparations in 14 national and international pharmacopeias were investigated. RESULTS: It was found that 12 pharmacopeias have given separate microbial limits for total aerobic microbial count (TAMC) and total yeast and mold count (TYMC), and a list of specified microorganisms for which acceptance criteria are defined. However, similarities were noticed in Ph.Eur, Ph. Helv and, BP. Salmonella, and Escherichia coli are the most common pathogens specified for herbal preparations in which boiling water is added prior to use and for internal use in all Pharmacopoeias because they serve as indicators of potential contamination. CONCLUSION: From this study, it can be concluded that the differences in microbial limit tests and their acceptance criteria as specified in the various pharmacopoeias need to be harmonized. It will become a more convenient option for global drug manufacturers to import/export herbal drugs, and this would also eliminate the burden of performing various analytical methods and comply with different microbial acceptance criteria set by various pharmacopoeias. The comparative data obtained from this study will be used to develop strategies for revisions of pharmacopoeias in a harmonized manner with respect to microbiological acceptance criteria, specifications for microbial enumeration of herbal drugs and herbal drug preparations.

Agreement between routinely used immunoassays for thyroid function testing in non-pregnant and pregnant adults.

OBJECTIVE: Thyroid function tests are common biochemical analyses, and agreement between the routinely used immunoassays is important for diagnosis and monitoring of thyroid disease. Efforts are continuously made to align the biochemical assays, and we aimed to evaluate the agreement between immunoassays used in a clinical laboratory setting among non-pregnant and pregnant adults. DESIGN: Cross-sectional study. PARTICIPANTS: Serum samples were obtained from 192 blood donors (non-pregnant adults) and from 86 pregnant women in the North Denmark Region with no known thyroid disease. MEASUREMENTS: Each sample was used for measurement of thyroid-stimulating hormone (TSH) with the routinely used automatic immunoassays in the regional Departments of Clinical Biochemistry (Alinity, Abbott Laboratories, Cobas, Roche Diagnostics, and Atellica, Siemens Healthineers) and reported as the median with 95% confidence interval (95% CI). RESULTS: In nonpregnant adults, the level of TSH was higher with Cobas and Atellica than with Alinity as reflected by median (Alinity: 1.39 mIU/L (95% CI: 1.30-1.51 mIU/L); Cobas: 1.57 mIU/L (95% CI: 1.48-1.75 mIU/L); Atellica: 1.74 mIU/L (95% CI: 1.61-1.83 mIU/L)). Similarly, a trend was seen towards higher median TSH with Cobas than with Alinity among pregnant women (Alinity: 1.90 mIU/L (95% CI: 1.37-2.82 mIU/L); Cobas: 2.33 mIU/L (95% CI: 1.69-3.62 mIU/L)). CONCLUSION: Results of thyroid function tests obtained with different immunoassays were not interchangeable when evaluated among pregnant and non-pregnant adults. The distinct differences are relevant for clinical decision making and emphasize the necessity of clinical laboratory information when different assays are used for diagnosis and monitoring of patients with thyroid disease.

Geographic And Taxonomic Occurrence R-based Scrubbing (gatoRs): An R package and workflow for processing biodiversity data.

Premise: Digitized biodiversity data offer extensive information; however, obtaining and processing biodiversity data can be daunting. Complexities arise during data cleaning, such as identifying and removing problematic records. To address these issues, we created the R package Geographic And Taxonomic Occurrence R-based Scrubbing (gatoRs). Methods and Results: The gatoRs workflow includes functions that streamline downloading records from the Global Biodiversity Information Facility (GBIF) and Integrated Digitized Biocollections (iDigBio). We also created functions to clean downloaded specimen records. Unlike previous R packages, gatoRs accounts for differences in download structure between GBIF and iDigBio and allows for user control via interactive cleaning steps. Conclusions: Our pipeline enables the scientific community to process biodiversity data efficiently and is accessible to the R coding novice. We anticipate that gatoRs will be useful for both established and beginning users. Furthermore, we expect our package will facilitate the introduction of biodiversity-related concepts into the classroom via the use of herbarium specimens.

Empirical assessment of the assumptions of ComBat with diffusion tensor imaging.

Purpose: Diffusion tensor imaging (DTI) is a magnetic resonance imaging technique that provides unique information about white matter microstructure in the brain but is susceptible to confounding effects introduced by scanner or acquisition differences. ComBat is a leading approach for addressing these site biases. However, despite its frequent use for harmonization, ComBat's robustness toward site dissimilarities and overall cohort size have not yet been evaluated in terms of DTI. Approach: As a baseline, we match N=358 participants from two sites to create a "silver standard" that simulates a cohort for multi-site harmonization. Across sites, we harmonize mean fractional anisotropy and mean diffusivity, calculated using participant DTI data, for the regions of interest defined by the JHU EVE-Type III atlas. We bootstrap 10 iterations at 19 levels of total sample size, 10 levels of sample size imbalance between sites, and 6 levels of mean age difference between sites to quantify (i) ßAGE, the linear regression coefficient of the relationship between FA and age; (ii) Î³/f*, the ComBat-estimated site-shift; and (iii) Î´/f*, the ComBat-estimated site-scaling. We characterize the reliability of ComBat by evaluating the root mean squared error in these three metrics and examine if there is a correlation between the reliability of ComBat and a violation of assumptions. Results: ComBat remains well behaved for ßAGE when N>162 and when the mean age difference is less than 4 years. The assumptions of the ComBat model regarding the normality of residual distributions are not violated as the model becomes unstable. Conclusion: Prior to harmonization of DTI data with ComBat, the input cohort should be examined for size and covariate distributions of each site. Direct assessment of residual distributions is less informative on stability than bootstrap analysis. We caution use ComBat of in situations that do not conform to the above thresholds.

Lung CT harmonization of paired reconstruction kernel images using generative adversarial networks.

BACKGROUND: The kernel used in CT image reconstruction is an important factor that determines the texture of the CT image. Consistency of reconstruction kernel choice is important for quantitative CT-based assessment as kernel differences can lead to substantial shifts in measurements unrelated to underlying anatomical structures. PURPOSE: In this study, we investigate kernel harmonization in a multi-vendor low-dose CT lung cancer screening cohort and evaluate our approach's validity in quantitative CT-based assessments. METHODS: Using the National Lung Screening Trial, we identified CT scan pairs of the same sessions with one reconstructed from a soft tissue kernel and one from a hard kernel. In total, 1000 pairs of five different paired kernel types (200 each) were identified. We adopt the pix2pix architecture to train models for kernel conversion. Each model was trained on 100 pairs and evaluated on 100 withheld pairs. A total of 10 models were implemented. We evaluated the efficacy of kernel conversion based on image similarity metrics including root mean squared error (RMSE), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM) as well as the capability of the models to reduce measurement shifts in quantitative emphysema and body composition measurements. Additionally, we study the reproducibility of standard radiomic features for all kernel pairs before and after harmonization. RESULTS: Our approach effectively converts CT images from one kernel to another in all paired kernel types, as indicated by the reduction in RMSE (p < 0.05) and an increase in the PSNR (p < 0.05) and SSIM (p < 0.05) for both directions of conversion for all pair types. In addition, there is an increase in the agreement for percent emphysema, skeletal muscle area, and subcutaneous adipose tissue (SAT) area for both directions of conversion. Furthermore, radiomic features were reproducible when compared with the ground truth features. CONCLUSIONS: Kernel conversion using deep learning reduces measurement variation in percent emphysema, muscle area, and SAT area.

Impact of harmonization on the reproducibility of MRI radiomic features when using different scanners, acquisition parameters, and image pre-processing techniques: a phantom study.

This study investigated the impact of ComBat harmonization on the reproducibility of radiomic features extracted from magnetic resonance images (MRI) acquired on different scanners, using various data acquisition parameters and multiple image pre-processing techniques using a dedicated MRI phantom. Four scanners were used to acquire an MRI of a nonanatomic phantom as part of the TCIA RIDER database. In fast spin-echo inversion recovery (IR) sequences, several inversion durations were employed, including 50, 100, 250, 500, 750, 1000, 1500, 2000, 2500, and 3000 ms. In addition, a 3D fast spoiled gradient recalled echo (FSPGR) sequence was used to investigate several flip angles (FA): 2, 5, 10, 15, 20, 25, and 30 degrees. Nineteen phantom compartments were manually segmented. Different approaches were used to pre-process each image: Bin discretization, Wavelet filter, Laplacian of Gaussian, logarithm, square, square root, and gradient. Overall, 92 first-, second-, and higher-order statistical radiomic features were extracted. ComBat harmonization was also applied to the extracted radiomic features. Finally, the Intraclass Correlation Coefficient (ICC) and Kruskal-Wallis's (KW) tests were implemented to assess the robustness of radiomic features. The number of non-significant features in the KW test ranged between 0-5 and 29-74 for various scanners, 31-91 and 37-92 for three times tests, 0-33 to 34-90 for FAs, and 3-68 to 65-89 for IRs before and after ComBat harmonization, with different image pre-processing techniques, respectively. The number of features with ICC over 90% ranged between 0-8 and 6-60 for various scanners, 11-75 and 17-80 for three times tests, 3-83 to 9-84 for FAs, and 3-49 to 3-63 for IRs before and after ComBat harmonization, with different image pre-processing techniques, respectively. The use of various scanners, IRs, and FAs has a great impact on radiomic features. However, the majority of scanner-robust features is also robust to IR and FA. Among the effective parameters in MR images, several tests in one scanner have a negligible impact on radiomic features. Different scanners and acquisition parameters using various image pre-processing might affect radiomic features to a large extent. ComBat harmonization might significantly impact the reproducibility of MRI radiomic features.

Dementias Platform UK: Bringing genetics into life.

INTRODUCTION: The Dementias Platform UK (DPUK) Data Portal is a data repository bringing together a wide range of cohorts. Neurodegenerative dementias are a group of diseases with highly heterogeneous pathology and an overlapping genetic component that is poorly understood. The DPUK collection of independent cohorts can facilitate research in neurodegeneration by combining their genetic and phenotypic data. METHODS: For genetic data processing, pipelines were generated to perform quality control analysis, genetic imputation, and polygenic risk score (PRS) derivation with six genome-wide association studies of neurodegenerative diseases. Pipelines were applied to five cohorts. DISCUSSION: The data processing pipelines, research-ready imputed genetic data, and PRS scores are now available on the DPUK platform and can be accessed upon request though the DPUK application process. Harmonizing genome-wide data for multiple datasets increases scientific opportunity and allows the wider research community to access and process data at scale and pace.

World Endometriosis Research Foundation Endometriosis Phenome and Biobanking Harmonization Project: V. physical examination standards in endometriosis research.

OBJECTIVE: The World Endometriosis Research Foundation (WERF) established the Endometriosis Phenome and Biobanking Harmonisation Project (EPHect) to create standardized documentation tools (with common data elements) to facilitate the comparison and combination of data across different research sites and studies. In 2014, four data research standards were published: clinician-reported surgical data, patient-reported clinical data, and fluid and tissue biospecimen collection. Our current objective is to create an EPHect standard for the clinician-reported physical examination (EPHect-PE) for research studies. DESIGN: An international consortium involving 26 clinical and academic experts and patient partners from 11 countries representing 25 institutions and organizations. Two virtual workshops, followed by the development of the physical examination standards that underwent multiple rounds of iterations and revisions. SUBJECTS: N/A MAIN OUTCOME MEASURE(S): N/A RESULT(S): The EPHect physical examination (EPHect-PE) tool provides standardised assessment of physical examination characteristics and pain phenotyping. Data elements involve examination of a) back and pelvic girdle; b) abdomen including allodynia and trigger points; c) vulva including provoked vestibulodynia; d) pelvic floor muscle tone and tenderness; e) tenderness on unidigital pelvic exam; f) presence of pelvic nodularity; g) uterine size and mobility; h) presence of adnexal masses; i) presence of incisional masses; j) speculum examination; k) tenderness and allodynia at an extra-pelvic site (e.g. forearm); and l) recording of anthropometrics. CONCLUSION(S): The EPHect physical examination standards (EPHect-PE) will facilitate the standardised documentation of the physical examination, including the assessment and documentation of examination phenotyping of endometriosis-associated pelvic pain.

Harmonization of Zika serological assays and comparative evaluation of two commercial ZIKA IgG ELISA kits.

The interpretation for Zika virus serology results is challenging due to high antibody cross reactivity with other flaviviruses. This limits availability of reliable and accurate methods for serosurveillance studies to understand the disease burden. Therefore, we conducted study to harmonize anti-Zika IgG antibody detection assays with 1st WHO International Standard (16/352) and working standard (16/320) for anti-Zika virus antibody.Additionally, evaluated NuGenTMZIKA-IgG and NovaLisa®ZIKA virus IgG-Capture ELISA using a panel of 278 seraFurther, 106 samples positive for other-flavi viruses were taken for assessing cross-reactivity of the assay, all serums were further tested by Zika-PRNT. The results of this study indicates satisfactory performance of both the assays. Serological and neutralization assays were calibrated according to the international standards. This will help in understanding antibody dynamics in serosurveillance and vaccine studies. However the performance of the kits with possibilities of cross-reactivity will have to be verified by coupling ZIKV and DENV specific ELISA.

Harmonizing regulatory market approval of products with high safety requirements: Evidence from the European pharmaceutical market.

We causally analyzed whether being a member of the European Union (EU) and having access to a centralized marketing authorization procedure (centralized procedure [CP]) affects availability and time to launch of new pharmaceuticals. We employed multiple difference-in-differences models, exploiting the eastern enlargement of the EU as well as changes in the indications that fall within the compulsory or voluntary scope of the CP. Results showed that countries experienced a mean decrease in launch delay of 10.9 months (p = 0.004) after joining the EU. Effects were higher among pharmaceuticals that belong to indications that might voluntarily participate in the CP but are not obliged to. These are often financially less attractive to manufacturers than pharmaceuticals within the compulsory scope. Availability of new pharmaceuticals launched remained unaffected. We found signs that the magnitude of the country-specific effect of centralized marketing authorization on launch delay may be influenced by strategic decisions of manufacturers at the national level (e.g., parallel trade or reference pricing).

MidRISH: Unbiased harmonization of rotationally invariant harmonics of the diffusion signal.

Data harmonization is necessary for removing confounding effects in multi-site diffusion image analysis. One such harmonization method, LinearRISH, scales rotationally invariant spherical harmonic (RISH) features from one site ("target") to the second ("reference") to reduce confounding scanner effects. However, reference and target site designations are not arbitrary and resultant diffusion metrics (fractional anisotropy, mean diffusivity) are biased by this choice. In this work we propose MidRISH: rather than scaling reference RISH features to target RISH features, we project both sites to a mid-space. We validate MidRISH with the following experiments: harmonizing scanner differences from 37 matched patients free of cognitive impairment, and harmonizing acquisition and study differences on 117 matched patients free of cognitive impairment. We find that MidRISH reduces bias of reference selection while preserving harmonization efficacy of LinearRISH. Users should be cautious when performing LinearRISH harmonization. To select a reference site is to choose diffusion metric effect-size. Our proposed method eliminates the bias-inducing site selection step.

Diffusion MRI harmonization via personalized template mapping.

One fundamental challenge in diffusion magnetic resonance imaging (dMRI) harmonization is to disentangle the contributions of scanner-related effects from the variable brain anatomy for the observed imaging signals. Conventional harmonization methods rely on establishing an atlas space to resolve anatomical variability and generate a unified inter-site mapping function. However, this approach is limited in accounting for the misalignment of neuroanatomy that still widely persists even after registration, especially in regions close to cortical boundaries. To overcome this challenge, we propose a personalized framework in this paper to more effectively address the confounding from the misalignment of neuroanatomy in dMRI harmonization. Instead of using a common template representing site-effects for all subjects, the main novelty of our method is the adaptive computation of personalized templates for both source and target scanning sites to estimate the inter-site mapping function. We integrate our method with the rotation invariant spherical harmonics (RISH) features to achieve the harmonization of dMRI signals between sites. In our experiments, the proposed approach is applied to harmonize the dMRI data acquired from two scanning platforms: Siemens Prisma and GE MR750 from the Adolescent Brain Cognitive Development dataset and compared with a state-of-the-art method based on RISH features. Our results indicate that the proposed harmonization framework achieves superior performance not only in reducing inter-site variations due to scanner differences but also in preserving sex-related biological variability in original cohorts. Moreover, we assess the impact of harmonization on the estimation of fiber orientation distributions and show the robustness of the personalized harmonization procedure in preserving the fiber orientation of original dMRI signals.