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Assessing Study Reproducibility through MMRI: A Novel Approach for Large-scale High-throughput Association Studies

Jiao, Z.; Lai, Y.; Kang, J.; Gong, W.; Ma, L.; Jia, T.; Xie, C.; Cheng, W.; Heinz, A.; Desrivieres, S.; Schumann, G.; Sun, F.; Feng, J.

2020-08-24 neuroscience
10.1101/2020.08.18.253740 bioRxiv
Show abstract

Magnetic Resonance Imaging (MRI) technology has been increasingly used in large-scale association studies. Reproducibility of statistically significant findings generated by MRI-based association studies, especially structural MRI (sMRI) and functional MRI (fMRI), has been recently heavily debated. However, there is still a lack of overall reproducibility assessment for MRI-based association studies. It is also crucial to elucidate the relationship between overall reproducibility and sample size in an experimental design. In this study, we proposed an overall reproducibility index for large-scale high-throughput MRI-based association studies. We performed the overall reproducibility assessments for several recent large sMRI/fMRI databases and observed satisfactory overall reproducibility. Furthermore, we performed the sample size evaluation for the purpose of achieving a desirable overall reproducibility. Additionally, we evaluated the overall reproducibility of GMV changes for UKB vs. PPMI and UKB vs. HCP. We demonstrated that both sample size and some experimental factors play important roles in the overall reproducibility for different experiments. In summary, a systematic assessment of overall reproducibility is fundamental and crucial in the current large-scale high-throughput MRI-based research.

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