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

Riikka Immonen, Gregory Smith, Rhys D. Brady, David Wright, Leigh Johnston, Neil G. Harris, Eppu Manninen, Raimo Salo, Craig Branch, Dominique Duncan, Ryan Cabeen, Xavier Ekolle Ndode-Ekane, Cesar Santana Gomez, Pablo M. Casillas-Espinosa, Idrish Ali, Sandy R. Shultz, Pedro Andrade, Noora Puhakka, Richard J. Staba, Terence J. O'BrienArthur W. Toga, Asla Pitkänen, Olli Gröhn

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)46-57
Number of pages12
JournalEpilepsy Research
Volume150
DOIs
StatePublished - Feb 2019

Keywords

  • Common data element
  • Diffusion tensor imaging
  • Magnetization transfer imaging
  • Multi-site harmonization
  • Post-traumatic epilepsy
  • Traumatic brain injury

ASJC Scopus subject areas

  • Neurology
  • Clinical Neurology

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    Immonen, R., Smith, G., Brady, R. D., Wright, D., Johnston, L., Harris, N. G., Manninen, E., Salo, R., Branch, C., Duncan, D., Cabeen, R., Ndode-Ekane, X. E., Gomez, C. S., Casillas-Espinosa, P. M., Ali, I., Shultz, S. R., Andrade, P., Puhakka, N., Staba, R. J., ... Gröhn, O. (2019). Harmonization of pipeline for preclinical multicenter MRI biomarker discovery in a rat model of post-traumatic epileptogenesis. Epilepsy Research, 150, 46-57. https://doi.org/10.1016/j.eplepsyres.2019.01.001