Identifying and reverting the adverse effects of white matter hyperintensities on cortical surface analyses
Yuki Oi,
Masakazu Hirose,
Hiroki Togo,
Kenji Yoshinaga,
Thai Akasaka,
Tomohisa Okada,
Toshihiko Aso,
Ryosuke Takahashi,
Matthew F. Glasser,
Takuya Hayashi,
Takashi Hanakawa
Affiliations
Yuki Oi
Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan; Department of Integrated Neuroanatomy and Neuroimaging, Kyoto University Graduate School of Medicine, Kyoto, Japan; Laboratory for Brain Connectomics Imaging, Center for Biosystems Dynamics Research, RIKEN, Kobe, Japan
Masakazu Hirose
Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan; Department of Integrated Neuroanatomy and Neuroimaging, Kyoto University Graduate School of Medicine, Kyoto, Japan
Hiroki Togo
Department of Integrated Neuroanatomy and Neuroimaging, Kyoto University Graduate School of Medicine, Kyoto, Japan; Laboratory for Brain Connectomics Imaging, Center for Biosystems Dynamics Research, RIKEN, Kobe, Japan; Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Kodaira, Japan
Kenji Yoshinaga
Department of Integrated Neuroanatomy and Neuroimaging, Kyoto University Graduate School of Medicine, Kyoto, Japan
Thai Akasaka
Human Brain Research Center, Kyoto University Graduate School of Medicine, Kyoto, Japan
Tomohisa Okada
Human Brain Research Center, Kyoto University Graduate School of Medicine, Kyoto, Japan
Toshihiko Aso
Laboratory for Brain Connectomics Imaging, Center for Biosystems Dynamics Research, RIKEN, Kobe, Japan
Ryosuke Takahashi
Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan
Matthew F. Glasser
Departments of Radiology and Neuroscience, Washington University School of Medicine, St. Louis, MO, United States
Takuya Hayashi
Laboratory for Brain Connectomics Imaging, Center for Biosystems Dynamics Research, RIKEN, Kobe, Japan; Department of Brain Connectomics, Kyoto University Graduate School of Medicine, Kyoto, Japan
Takashi Hanakawa
Department of Integrated Neuroanatomy and Neuroimaging, Kyoto University Graduate School of Medicine, Kyoto, Japan; Laboratory for Brain Connectomics Imaging, Center for Biosystems Dynamics Research, RIKEN, Kobe, Japan; Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Kodaira, Japan; Human Brain Research Center, Kyoto University Graduate School of Medicine, Kyoto, Japan; Corresponding author at: Integrated Neuroanatomy and Neuroimaging, Director, Human Brain Research Center, Kyoto University Graduate School of Medicine, Yoshida Konoe-cho, Sakyo-ku, Kyoto 606-8501, Japan.
The Human Connectome Project (HCP)-style surface-based brain MRI analysis is a powerful technique that allows precise mapping of the cerebral cortex. However, the strength of its surface-based analysis has not yet been tested in the older population that often presents with white matter hyperintensities (WMHs) on T2-weighted (T2w) MRI (hypointensities on T1w MRI). We investigated T1-weighted (T1w) and T2w structural MRI in 43 healthy middle-aged to old participants. Juxtacortical WMHs were often misclassified by the default HCP pipeline as parts of the gray matter in T1w MRI, leading to incorrect estimation of the cortical surfaces and cortical metrics. To revert the adverse effects of juxtacortical WMHs, we incorporated the Brain Intensity AbNormality Classification Algorithm into the HCP pipeline (proposed pipeline). Blinded radiologists performed stereological quality control (QC) and found a decrease in the estimation errors in the proposed pipeline. The superior performance of the proposed pipeline was confirmed using an originally-developed automated surface QC based on a large database. Here we showed the detrimental effects of juxtacortical WMHs for estimating cortical surfaces and related metrics and proposed a possible solution for this problem. The present knowledge and methodology should help researchers identify adequate cortical surface biomarkers for aging and age-related neuropsychiatric disorders.