CFA Shape Template Database
Brain warping techniques have made it possible to compare anatomical structure and function of the brain in large populations. Most of these techniques are template-based approaches that have been successful in describing anatomical variations between a collection of anatomies and a template. The template is often represented by a healthy control subject from the population being studied. The difficulties with this approach are that the template may not be truly representative of the population, particularly when severe neurodegenerate disorders or brain development are studied. Wide variation of the anatomy across subjects relative to the template may cause the failure of the mapping. Thus, one of the fundamental limitations of choosing the anatomy of a single subject as a template is the introduction of a statistical bias based on the arbitrary choice of the template anatomy. In this database, we provide representative shapes of a variety of structures that were constructed from different populations using large deformation diffeomorphic metric template estimation procedure (Qiu, A., et. al., NeuroImage, 2008).
CFA Subcortical Shape Template
The CFA
subcortical shape template includes lateral and inferior lateral ventricles as
well as six subcortical structures (amygdala, hippocampus, thalamus, caudate,
putamen, globus pallidus in both volume and surface representations. This set of
the shapes were generated from manual labeled volumes of forty one subject using
the large deformation diffeomorphic metric template estimation. These subjects
were selected based on demographic information (gender, age, and diagnosis) from
the database of Open Access Series of Imaging Studies (OASIS,
http://www.oasis-brains.org), including ten young adults (4 males and 6
females, age: 21.3 ± 1.57), ten middle aged adults (5 males and 5 females, age:
49.8 ± 5.79), ten elders (5 males and 5 females, age: 73.6 ±7.05), and eleven
patients with dementia (5 males and 6 females, age: 77.2±5.64). All imaging was
conducted at 1.5 T (Siemens Vision scanner, Erlangen -Germany). Head movement
was minimized by cushioning and a thermoplastic face mask. Three or four T1-
weighted MP-RAGE scans were acquired in each subject. MP-RAGE parameters were
empirically optimized for gray–white contrast
REFERENCES:
Methodological Papers:
1. Anqi Qiu, Timothy Brown, Bruce Fischl, Anthony Kolasny, Jun Ma, Randy L. Buckner, Michael I. Miller, “Subcortical Structure Template Generation with its Applications in Shape Analysis”, NeuroImage, in revision.
2. Anqi Qiu, Michael I. Miller, “Multi-Structure Network Shape Analysis via Normal Surface Momentum Maps”, NeuroImage, accepted.
Download : surface and curve
The CFA cortical template includes the left and right cortical hemispheric surfaces and 14 sulcal curves of each side. 14 major sulci are chosen because they are consistently present and are readily identifiable on the cortical surface (Ono, 1990; Sowell et. al., Cereb Cortex, 2002). As illustrated in above Figure, these curves are superior frontal sulcus (SFS), inferior frontal sulcus (IFS), precentral sulcus (PreCeS), central sulcus (CeS), postcentral sulcus (PostCeS), Sylvian fissure (SF), anterior segment of the superior temporal sulcus (aSTS), inferior temporal sulcus (ITS), intraparietal sulcus (IPS), calcarine sulcus (CaS), parieto-occipital fissure (POF), collateral sulcus (CLS), superior callosal sulcus (CC), and olfactory sulcus (OS).
We estimated the template of the cortical surface and the 14 sulcal curves from 40 subjects using multi-manifold large deformation diffeomorphic metric mapping (MM-LDDMM). These subjects with ten youths (5 males and 5 females, age: 23.4±2.55), ten adults (5 males and 5 females, age: 49.3±1.89), ten elders (5 males and 5 females, age:73.9±2.02), and ten patients with dementia (5 males and 5 females, age: 76.4±2.55) were randomly selected based on gender, age, and diagnosis from the public available dataset of Open Access Series of Imaging Studies (OASIS). All imaging was conducted at 1.5 T (Siemens Vision scanner, Erlangen -Germany). Head movement was minimized by cushioning and a thermoplastic face mask. Three or four T1- weighted MP-RAGE scans were acquired in each subject. MP-RAGE parameters were empirically optimized for gray–white contrast [TR =9.7 ms, TE = 4 ms, flip angle = 10 degrees, inversion time (TI) = 20ms, delay time (TD) = 200 ms, 256 X 256 (1 X 1 mm) in-plane resolution, one hundred twenty-eight 1.25-mm slices without gaps]. The MP-RAGE data were averaged offline (with correction for head movement) to increase the contrast to noise ratio in all procedures involving manual tracing, segmentation, and measurement of normalized whole brain volume and were interpolated into isotropic voxels with resolution of 1mm X 1mm X 1mm. The detailed template generation procedure is described in (Zhong and Qiu, A., Medical Image Analysis, 2008).
REFERENCES:
Methodological Papers:
1. Jidan Zhong, Anqi Qiu, “Multi-Manifold Diffeomorphic Metric Mapping for Aligning Cortical Hemispheric Surfaces”, Medical Image Analysis, in submission.
CFA Children Basal Ganglia Shape Template
The CFA children basal ganglia shape template includes the caudate, putamen, and globus pallidus in both volume and surface representations. It was generated from manual labeled masks of thirty five healthy children using the large deformation diffeomorphic metric template estimation. These subjects include 18 males and 17 females at mean age of 10.4 years. Each subject underwent for high-resolution T1 MPRAGE images acquired on a 1.5T Philips Gyroscan NT system (MPRAGE parameters: TR=8ms; TE=3.76ms; flip angle=8°; matrix=256x256; field of view=260; voxel size=1 x 1 x 1.2 mm3). The basal ganglia structures were manually delineated from MR images using the MIPAV (Medical Image Processing and Visualization) program. The manual tracing of the caudate (nucleus accumbens included), putamen, and globus pallidus were examined in the coronal sections based on the criteria established at laboratory (http://www.psychiatry.unc.edu/).
REFERENCES:
Methodological Papers:
1. Anqi Qiu, Timothy Brown, Bruce Fischl, Anthony Kolasny, Jun Ma, Randy L. Buckner, Michael I. Miller, “Subcortical Structure Template Generation with its Applications in Shape Analysis”, NeuroImage, in revision.
2. Anqi Qiu, Michael I. Miller, “Multi-Structure Network Shape Analysis via Normal Surface Momentum Maps”, NeuroImage, accepted.
Applications in Neuropsychiatric and Neurodegenerative Diseases:
1. Anqi Qiu, Deana Crocetti, Marcy Adler, Mark Mahone, Martha Deckla, Michael I. Miller, and Stewart H. Mostofsy, “Basal ganglia volume and shape in children with ADHD”, Am J Psychiatry, accepted.
