title: Tools for multiple granularity analysis of brain MRI data for individualized image analysis.
abstract: Voxel-based analysis is widely used for quantitative analysis of brain MRI. While this type of analysis provides the highest granularity level of spatial information (i.e., each voxel), the sheer number of voxels and noisy information from each voxel often lead to low sensitivity for detection of abnormalities. To ameliorate this issue, granularity reduction is commonly performed by applying isotropic spatial filtering. This study proposes a systematic reduction of the spatial information using ontology-based hierarchical structural relationships. The 254 brain structures were first defined in multiple (n=29) geriatric atlases. The multiple atlases were then applied to T1-weighted MR images of each subject's data for automated brain parcellation and five levels of ontological relationships were established, which further reduced the spatial dimension to as few as 11 structures. At each ontology level, the amount of atrophy was evaluated, providing a unique view of low-granularity analysis. This reduction of spatial information allowed us to investigate the anatomical features of each patient, demonstrated in an Alzheimer's disease group.
authors: Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors: Aigerim
authors: A
authors: Djamanakova
authors: Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors: Xiaoying
authors: X
authors: Tang
authors: The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors: Xin
authors: X
authors: Li
authors: The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors: Andreia V
authors: AV
authors: Faria
authors: Center for Imaging Science, Johns Hopkins University, Baltimore, MD, USA.
authors: Can
authors: C
authors: Ceritoglu
authors: The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors: Kenichi
authors: K
authors: Oishi
authors: Department of Neurology, Johns Hopkins University, Baltimore, MD, USA; Department of Physical Medicine and Rehabilitation, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Cognitive Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors: Argye E
authors: AE
authors: Hillis
authors: Department of Neurology, Johns Hopkins University, Baltimore, MD, USA; The Johns Hopkins Alzheimer's Disease Research Center, Baltimore, MD, USA.
authors: Marilyn
authors: M
authors: Albert
authors: The Johns Hopkins Alzheimer's Disease Research Center, Baltimore, MD, USA; Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, USA.
authors: Constantine
authors: C
authors: Lyketsos
authors: Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Center for Imaging Science, Johns Hopkins University, Baltimore, MD, USA.
authors: Michael I
authors: MI
authors: Miller
authors: The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA. Electronic address: susumu@mri.jhu.edu.
authors: Susumu
authors: S
authors: Mori
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000473:pathology*; D000544:Alzheimer Disease / Q000473:pathology*; D001921:Brain / Q000033:anatomy & histology* / Q000473:pathology; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods* / Q000592:standards; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000592:standards; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D055815:Young Adult