Harmonization of pipeline for preclinical multicenter MRI biomarker discovery in a rat model of post-traumatic epileptogenesis.

Preclinical imaging studies of posttraumatic epileptogenesis (PTE) have largely been proof-of-concept studies with limited animal numbers, and thus lack the statistical power for biomarker discovery. Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) is a pioneering multicenter trial investigating preclinical imaging biomarkers of PTE. EpiBios4Rx faced the issue of harmonizing the magnetic resonance imaging (MRI) procedures and imaging data metrics prior to its execution. We present here the harmonization process between three preclinical MRI facilities at the University of Eastern Finland (UEF), the University of Melbourne (Melbourne), and the University of California, Los Angeles (UCLA), and evaluate the uniformity of the obtained MRI data. Adult, male rats underwent a lateral fluid percussion injury (FPI) and were followed by MRI 2 days, 9 days, 1 month, and 5 months post-injury. Ex vivo scans of fixed brains were conducted 7 months post-injury as an end point follow-up. Four MRI modalities were used: T2-weighted imaging, multi-gradient-echo imaging, diffusion-weighted imaging, and magnetization transfer imaging, and acquisition parameters for each modality were tailored to account for the different field strengths (4.7 T and 7 T) and different MR hardwares used at the three participating centers. Pilot data collection resulted in comparable image quality across sites. In interim analysis (of data obtained by April 30, 2018), the within-site variation of the quantified signal properties was low, while some differences between sites remained. In T2-weighted images the signal-to-noise ratios were high at each site, being 35 at UEF, 48 at Melbourne, and 32 at UCLA (p < 0.05). The contrast-to-noise ratios were similar between the sites (9, 10, and 8, respectively). Magnetization transfer ratio maps had identical white matter/ gray matter contrast between the sites, with white matter showing 15% higher MTR than gray matter despite different absolute MTR values (MTR both in white and gray matter was 3% lower in Melbourne than at UEF, p < 0.05). Diffusion-weighting yielded different degrees of signal attenuation across sites, being 83% at UEF, 76% in Melbourne, and 80% at UCLA (p < 0.05). Fractional anisotropy values differed as well, being 0.81 at UEF, 0.73 in Melbourne, and 0.84 at UCLA (p < 0.05). The obtained values in sham animals showed low variation within each site and no change over time, suggesting high repeatability of the measurements. Quality control scans with phantoms demonstrated stable hardware performance over time. Timing of post-TBI scans was designed to target specific phases of the dynamic pathology, and the execution at different centers was highly accurate. Besides a few outliers, the 2-day scans were done within an hour from the target time point. At day 9, most animals were scanned within an hour from the target time point, and all but 2 outliers within 24 h from the target. The 1-month post-TBI scans were done within 31 ± 3 days. MRI procedures and animal physiology during scans were similar between the sites. Taken together, the 10% inter-site difference in FA and 3% difference in MTR values should be included into analysis as a covariate or balanced out in post-processing in order to detect disease-related effects on brain structure at the same scale. However, for a MRI biomarker for post-traumatic epileptogenesis to have realistic chance of being successfully translated to validation in clinical trials, it would need to be a robust TBI-induced structural change which tolerates the inter-site methodological variability described here.

Informatics tools to assess the success of procedural harmonization in preclinical multicenter biomarker discovery study on post-traumatic epileptogenesis.

The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) is a National Institutes for Neurological Diseases and Stoke funded Centers-Without-Walls international multidisciplinary study aimed at preventing epileptogenesis. The preclinical biomarker discovery in EpiBios4Rx applies a multicenter study design to allow the number of animals that are required for adequate statistical power for the analysis to be studied in an efficient manner. Further, the use of multiple centers mimics the clinical trial situation, and therefore potentially the chance of successful clinical translation of the outcomes of the study. Its successful implementation requires harmonization of procedures and data analyses between the three contributing centers in Finland, Australia, and USA. The objective of the present analysis was to develop metrics for analysis of the success of harmonization of procedures to guide further data analyses and plan the future multicenter preclinical studies. The interim analysis of data is based on the analysis of data from 212 rats with lateral fluid-percussion injury or sham-operation included in the biomarker discovery by April 30, 2018. The details of protocols, including production of injury, post-injury follow-up, blood sampling, electroencephalogram recording, and magnetic resonance imaging have been presented in the accompanying manuscripts in this Supplement. Implementation of protocols in EpiBios4Rx project participant centers was visualized in 2D using t-distributed stochastic neighborhood embedding (t-SNE). The protocols applied to each rat were presented as feature vectors of procedure related variables (e.g., impact pressure, anesthesia time). The total number of protocol features linked to each rat was 112. The missing data was accounted in visualization by utilizing imputation and adding the number of missing values as a third dimension to 2D t-SNE plot, resulting in a 3D overview of protocol data. Intraclass correlation coefficient (ICC) using Euclidean distances and area under receiver operating characteristic curve (AUC) of k-nearest neighbor classifier (KNN) were utilized to quantify the degree of clustering by center. Both subsets of data with incomplete protocol vectors omitted and missing protocol data imputed were assessed. Our data show that a visible clustering by center was observed in all t-SNE plots, except for day 7 neuroscores. Both ICC and AUC indicated clustering by center in all protocol variable subsets, excluding unimputed day 7 neuroscores (ICC 0.04 and AUC 0.6). ICC for imputed set of all protocol related variables was 0.1 and KNN AUC 0.92. In conclusion, both ICC and AUC indicated differences in protocol between EpiBios4Rx participating centers, which needs to be taken into account in data analysis. Importantly, the majority of observed differences are recoverable as they relate to insufficient updates in record keeping. While AUC score of KNN is a more sensitive measure for protocol harmonization than ICC for data that displays complex splintered clustering, ICC and AUC provide complementary measures to assess the degree of procedural harmonization. This experience should be helpful for other groups planning such multicenter post-traumatic epileptogenesis studies in the future.