crashs=Cruise+ASHS

CRASHS is a surface-based modeling and groupwise registration pipeline for the human medial temporal lobe (MTL). It is used to postprocess the results of ASHS segmentation with ASHS atlases that contain a white matter label. CRASHS uses the CRUISE technique implemented in the NighRes software to fit the white matter segmentation with a surface of spherical topology, and find a series of surfaces spanning between the gray/white boundary and the pial surface. The middle surface is inflated and registered to a population template, allowing surface-based analysis of MTL cortical thickness and other measures such as functional MRI and diffusion MRI.

Inputs

The main input to the package is the ASHS-T1 output folder. ASHS should be run using the new ASHS-T1 atlas with the white matter label.

Outputs

The program generates many outputs, but the most useful ones are:

• fitting/[ID]_fitted_omt_hw_target.vtk: the grey/white and grey/csf boundaries estimated by the cruise_cortex_extraction module of NighRes. These meshes are in physical (RAS) coordinate space, not in voxel (IJK) space output by Nighres. If you extract meshes from the T1-ASHS segmentation in ITK-SNAP, those should like up with these meshes.

• fitting/[ID]_fitted_omt_hw_target.vtk: the mid-surface of the gray matter estimated by the volumetric_layering module of NighRes. Also in RAS space.

• fitting/[ID]_fitted_omt_match_to_hw.vtk: the template mesh projected onto the mid-surface surface, also in RAS space. This should have the same geometry as the mid-surface, but the same number of vertices/faces as the template. This mesh will also have scalar arrays for the anatomical label and other features from the template, such as template curvature (useful for visualization). This mesh can be used to map data from subject space (thickness, fMRI, NODDI, etc) into template space for group analysis

The following files can be used to check how well the fitting between the inflated template mid-surface and the inflated subject mid-surface worked.

• fitting/[ID]_fit_target_reduced: this is the inflated and sub-sampled mid-surface mesh of the subject, affine transformed into the space of the inflated template. Each triangle is associated with an anatomical label.

• fitting/[ID]_fitted_lddmm_template: this is the inflated template warped to optimally match the mesh above. The fit is not perfect but should be close.

• fitting/[ID]_fitted_dist_stat.json: distance statistics of the fitting, including average, max, and 95th percentile of the distance. Useful to check for poor fitting results.

Docker

This repository includes the CRASHS scripts and a Dockerfile. The official container on DockerHub is labeled pyushkevich/crashs:latest

docker run -v your_data_directory:/data -it pyushkevich/crashs:latest /bin/bash
./crashs.py --help

A sample dataset is also provided and can be processed as follows (also see run_sample.sh)

docker run -v your_data_directory:/data -it pyushkevich/crashs:latest /bin/bash
./crashs.py -s right -r 0.1 sample_data/035_S_4082_2011-06-28 templates/crashs_template_01 /data/test

Citation

• PA Yushkevich, L Xie, LEM Wisse, M Dong, S Ravikumar, R Ittyerah, R de Flores, SR Das, DA Wolk for the Alzheimer’s Disease Neuroimaging Initiative (ADNI), Mapping Medial Temporal Lobe Longitudinal Change in Preclinical Alzheimer’s Disease, 2023 Alzheimer's Association International Conference (AAIC 2023).