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Abstract Brain atrophy as measured from structural MR images, is one of the primary imaging biomarkers used to track neurodegenerative disease progression. In diseases such as frontotemporal dementia or Alzheimer's disease, atrophy can be observed in key brain structures years before any clinical symptoms are present. Atrophy is most commonly captured as volume change of key structures and the shape changes of these structures are typically not analysed despite being potentially more sensitive than summary volume statistics over the entire structure. In this paper we propose a spatiotemporal analysis pipeline based on Large Diffeomorphic Deformation Metric Mapping (LDDMM) to detect shape changes from volumetric MRI scans. We applied our framework to a cohort of individuals with genetic variants of frontotemporal dementia and healthy controls from the Genetic FTD Initiative (GENFI) study. Our method, take full advantage of the LDDMM framework, and relies on the creation of a population specific average spatiotemporal trajectory of a relevant brain structure of interest, the thalamus in our case. The residuals from each patient data to the average spatiotemporal trajectory are then clustered and studied to assess when presymptomatic mutation carriers differ from healthy control subjects. We found statistical differences in shape in the anterior region of the thalamus at least five years before the mutation carrier subjects develop any clinical symptoms. This region of the thalamus has been shown to be predominantly connected to the frontal lobe, consistent with the pattern of cortical atrophy seen in the disease. Graphical abstract Image 1 Highlights • Clustering shape parametrisation allows local shape analysis. • Thalamic shape changes appear 5 years before onset of fronto temporal dementia. • Shape changes seem to occur before volume changes. • Pre-symptomatic shape changes in thalamus are dorsofrontal, where connecting to temporal lobes. [ABSTRACT FROM AUTHOR]

Abstract: Neuroanatomical endophenotypes may reveal insights into the processes by which genetic factors increase the risk of developing schizophrenia. To determine whether patterns of neuroanatomical asymmetries may be useful as schizophrenia-related endophenotypes, we compared patterns of structural asymmetries in patients with schizophrenia, healthy controls, and their respective siblings. The surfaces of the left and right amygdala, hippocampus, thalamus, caudate nucleus, putamen, globus pallidus, and nucleus accumbens were assessed in 40 pairs of healthy comparison controls (CON) and their siblings (CON-SIB) and 25 pairs of patients with schizophrenia (SCZ) and their siblings (SCZ-SIB) in magnetic resonance (MR) images using large deformation diffeomorphic metric mapping (LDDMM) and parallel transport techniques. The within-subject asymmetry deformation of each structure was first measured via LDDMM, and then translated to a global template via parallel transport for evaluation of the patterns of asymmetry both within and across siblings. Our results revealed that asymmetries observed in CON subjects occurred in the amygdala and the anterior segment of the hippocampus with more pronounced expansion deformation in the right-sided structures (R>L asymmetry) but not in the basal ganglia and thalamus. Disturbance in this pattern of asymmetries was observed in both SCZ and SCZ-SIB subjects. More specifically, exaggerations and reductions in the normative pattern of asymmetries were observed in the amygdala–hippocampus formation, basal ganglia, and thalamus. These altered patterns of asymmetries are present in subjects with schizophrenia and their siblings, and therefore may represent a schizophrenia-related endophenotype. [Copyright &y& Elsevier]

Abstract: The thalamus has been considered to be integral to the pathophysiology of schizophrenia. To determine whether its anatomical abnormalities may be associated with cognitive deficits in the onset of schizophrenia, we assessed thalamic volume, shape, white matter integrity, and their correlations with cognition in patients with first-episode schizophrenia. T1-weighted magnetic resonance and diffusion tensor (DT) images were collected in 49 healthy comparison controls (CON) and 32 patients with FES (FES). Large deformation diffeomorphic metric mapping (LDDMM) algorithms were used to delineate and assess the thalamic shape from MRI scans. The thalamic white matter integrity was quantified by fractional anisotropy (FA) and mean diffusivity (MD) averaged over the thalamus using DTI. Our analysis revealed that FES did not differ from CON in FA and MD but did differ markedly from them in the thalamic volume and shape. Patients with FES also performed poorly in spatial working memory and executive tasks. The correlation study found that regional thalamic shapes highly correlate with the two cognitive scores in the entire sample and healthy comparison controls but not in patients with FES even though no correlation was found between the thalamic volumes with the two cognitive scores in any group. Left thalamic FA was correlated with spatial working memory deficits in FES. Our findings suggest that thalamic volume and shape abnormalities are evident at the onset of FES prior to thalamic abnormal white matter integrity. Altered microstructural white matter integrity assessed using DTI may not be apparent in FES but may be observed as the disease progresses. Cognitive deficits related to spatial working memory and executive functioning in FES were observed in the context of loss of their normal relationship with the thalamic shapes, that is, regionally-specific thalamic shape compression is associated with poor performance in executive functioning and spatial working memory. [Copyright &y& Elsevier]

Abstract: Hippocampal surface structure was assessed at twice 2 years apart in 26 nondemented subjects (CDR 0), in 18 subjects with early dementia of Alzheimer type (DAT, CDR 0.5), and in 9 subjects who converted from the nondemented (CDR 0) to the demented (CDR 0.5) state using magnetic resonance (MR) imaging. We used parallel transport in diffeomorphisms under the large deformation diffeomorphic metric mapping framework to translate within-subject deformation of the hippocampal surface as represented in the MR images between the two time points in a global template coordinate system. We then performed hypothesis testing on the longitudinal variation of hippocampal shape in the global template. Both subjects with early DAT and converters showed greater rates of hippocampal deformation across time than nondemented controls within every subfield of the hippocampus. In a random field analysis, inward surface deformation across time occurred in a non-uniform manner across the hippocampal surface in subjects with early DAT relative to the nondemented controls. Also, compared to the controls, the lateral aspect of the left hippocampal tail showed inward surface deformation in the converters. Using surface deformation patterns as features in a linear discriminant analysis, we were able to respectively distinguish converters and patients with early DAT from healthy nondemented controls at classification rates of 0.77 and 0.87, which were obtained in the same training set using the leave-one-out cross validation approach. [Copyright &y& Elsevier]

Abstract: Serial MRI human brain scans have facilitated the detection of brain development and of the earliest signs of neuropsychiatric and neurodegenerative diseases, monitoring disease progression, and resolving drug effects in clinical trials for preventing or slowing the rate of brain degeneration. To track anatomical shape changes in serial images, we introduce new point-based time sequence large deformation diffeomorphic metric mapping (TS-LDDMM) to infer the time flow of within-subject geometric shape changes that carry known observations through a period. Its Euler–Lagrange equation is generalized for anatomies whose shapes are characterized by point sets, such as landmarks, curves, and surfaces. The time-dependent momentum obtained from the TS-LDDMM encodes within-subject shape changes. For the purpose of across-subject shape comparison, we then propose a diffeomorphic analysis framework to translate within-subject deformation in a global template without incorporating across-subject anatomical variations via parallel transport technique. The analysis involves the retraction of the within-subject time-dependent momentum along the TS-LDDMM trajectory from each time to the baseline, the translation of the momentum in a global template, and the reconstruction of the TS-LDDMM trajectory starting from the global template. [Copyright &y& Elsevier]