Nonlinear registration of longitudinal images and measurement of change in regions of interest

Multimodal Imaging Laboratory, The University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92037, USA.
Medical image analysis (Impact Factor: 3.65). 02/2011; 15(4):489-97. DOI: 10.1016/
Source: PubMed


We describe here a method, Quarc, for accurately quantifying structural changes in organs, based on serial MRI scans. The procedure can be used to measure deformations globally or in regions of interest (ROIs), including large-scale changes in the whole organ, and subtle changes in small-scale structures. We validate the method with model studies, and provide an illustrative analysis using the brain. We apply the method to the large, publicly available ADNI database of serial brain scans, and calculate Cohen's d effect sizes for several ROIs. Using publicly available derived-data, we directly compare effect sizes from Quarc with those from four existing methods that quantify cerebral structural change. Quarc produced a slightly improved, though not significantly different, whole brain effect size compared with the standard KN-BSI method, but in all other cases it produced significantly larger effect sizes.

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    • "Rates of whole brain and hippocampal atrophy from longitudinal magnetic resonane imaging (MRI) scans can aid in disease diagnosis and tracking of pathologic progression in neurodegenerative diseases and are increasingly used as outcome measures in trials of potentially disease-modifying therapies (Anderson et al., 2006; Frisoni et al., 2010; Holland et al., 2012; Sharma et al., 2010; Sluimer et al., 2010). Popular methods for brain atrophy measurement in longitudinal studies include Boundary Shift Integral (BSI) (Freeborough and Fox, 1997; Leung et al., 2010b, 2012), Structural Image Evaluation, using Normalization , of Atrophy (SIENA) (Smith et al., 2001), Quantitative Anatomical Regional Change (QUARC) (Holland and Dale, 2011), Tensor-Based Morphometry (TBM) (Hua et al., 2013), and FreeSurfer-longitudinal (FS) (Reuter et al., 2012). BSI and SIENA both use linear registration to align the baseline and repeat images and then track the shift of the brain boundary location, whereas QUARC and TBM both use nonlinear registrations to map between the baseline and repeat images and then measure volume change through analysis of the resulting deformation fields. "
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    Neurobiology of Aging 08/2014; 36(Suppl 1). DOI:10.1016/j.neurobiolaging.2014.04.035 · 5.01 Impact Factor
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    • "A specific category of spatial deformations has spanned the attention of researchers in this field: diffeomorphisms (smooth deformation with a smooth inverse). These were largely used in different registration models (Allassonnière et al., 2005; Beg et al., 2005; Holland and Dale, 2011; Klein et al., 2009) and became a part of the classical deformable template theory – especially after the establishment of the Large Deformation Diffeomorphic Metric Mapping (LDDMM) – pioneered by Dupuis et al. (1998) and Trouvé (1995, 1998). The metamorphosis theory is built upon the LDDMM framework which is based on the idea of a diffeomorphic metric. "
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    Clinical neuroimaging 08/2014; 5:332–340. DOI:10.1016/j.nicl.2014.07.009 · 2.53 Impact Factor
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    • "To additionally investigate neuroanatomic regions that are involved in the later stages of the disease process [37,38], and to minimize multiple comparisons, we averaged longitudinal volume change in the temporal pole, parahippocampal gyrus, inferior temporal gyrus, banks of the superior temporal sulcus, inferior parietal lobule, amygdala, and hippocampus to create an 'AD-vulnerable’ ROI [33,34] (Figure 1). Using an image-analysis method developed within our laboratory [39], we assessed longitudinal sub-regional change in gray matter volume (atrophy) on serial MRI scans (see Additional file 1 for additional details). "
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    ABSTRACT: Epidemiological and molecular findings suggest a relationship between Alzheimer's disease (AD) and dyslipidemia, although the nature of this association is not well understood. Using linear mixed effects models, we investigated the relationship between CSF levels of heart fatty acid binding protein (HFABP), a lipid binding protein involved with fatty acid metabolism and lipid transport, amyloid-beta (Abeta), phospho-tau, and longitudinal MRI-based measures of brain atrophy among 295 non-demented and demented older individuals. Across all participants, we found a significant association of CSF HFABP with longitudinal atrophy of the entorhinal cortex and other AD-vulnerable neuroanatomic regions. However, we found that the relationship between CSF HABP and brain atrophy was significant only among those with low CSF Abeta1--42 and occurred irrespective of phospho-tau181p status. Our findings indicate that Abeta-associated volume loss occurs in the presence of elevated HFABP irrespective of phospho-tau. This implicates a potentially important role for fatty acid binding proteins in Alzheimer's disease neurodegeneration.
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