Computational protocol: The Virtual Brain: Modeling Biological Correlates of Recovery after Chronic Stroke

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Protocol publication

[…] Resting state fMRI (rsfMRI) preprocessing analysis was performed using AFNI functions () and included the following steps: Motion correction using a six-parameter 3D registration of functional and anatomical data sets ().Three-dimensional spatial registration to a reference acquisition from the first fMRI run.Registration of functional images to the anatomical volume.Despiking of the time series.Mean normalization of the time series.Inspection and censoring of time points occurring during excessive motion (>1 mm) ().Regression of cerebrospinal fluid and white matter signals to remove slow drifts in the fMRI signal.Motion correction using a six-parameter 3D registration of functional and anatomical data sets ().Three-dimensional spatial registration to a reference acquisition from the first fMRI run.Registration of functional images to the anatomical volume.Despiking of the time series.Mean normalization of the time series.Inspection and censoring of time points occurring during excessive motion (>1 mm) ().Regression of cerebrospinal fluid and white matter signals to remove slow drifts in the fMRI signal. [...] Parcellating image data that contain lesions with the use of semiautomated schemes produce inaccurate results due to the absence of tissue and consequent mechanical deformation. We therefore developed The Virtual Brain transplant (VBT). This method effectively replaces the lesion produced by the cortical stroke with T1-w images of brain tissue from the contralesional hemisphere from the same subject (). This method allows us to use a semiautomated parcelation scheme subsequent to the transplant. The VBT process consisted of the following steps (Figure ): Lesion segmentation by hand.The high-resolution anatomical T1-w brain images and lesion masks were uploaded to a transplantation pipeline, which dissected the MRI brain tissue from the non-lesioned hemisphere homologous to the lesion, and transplanted it into the lesioned hemisphere at the site of the lesion, filling in the missing portions of the brain.After the initial transplant was done, manual corrections in the interface between the native and transplanted T1-w images were performed.The brain was segmented into 83 cortical and subcortical regions using the Lausanne 2008 (Freesurfer) parcelation scheme within the Connectome Mapper Toolkit (, ).Lesion segmentation by hand.The high-resolution anatomical T1-w brain images and lesion masks were uploaded to a transplantation pipeline, which dissected the MRI brain tissue from the non-lesioned hemisphere homologous to the lesion, and transplanted it into the lesioned hemisphere at the site of the lesion, filling in the missing portions of the brain.After the initial transplant was done, manual corrections in the interface between the native and transplanted T1-w images were performed.The brain was segmented into 83 cortical and subcortical regions using the Lausanne 2008 (Freesurfer) parcelation scheme within the Connectome Mapper Toolkit (, ). [...] We performed the following steps: DWI was aligned to the same reference b = 0 s/mm2 image used to align the corrected T1-w via VBT to DTI. Distortions caused by eddy currents and head motion were corrected using the FSL eddy current correction (12 degrees of freedom linear transformation), and the diffusion gradient vectors rotated accordingly (). That is, the T1-w images with the “transplanted masks” are used to supply the region of interest landmarks for tractography but do not directly impact the tractography algorithm as the transplant is not performed in the DWI space.The diffusion-weighted images were resampled to 2mm isotropic resolution ().White matter deterministic tractography of DTI data was performed in Trackvis software () using the FACT algorithm (). Threshold values of a maximum of 60° turning angle and a minimum of 0.20 fractional anisotropy (FA) were used as stopping criteria for the tracking algorithm. These thresholds take into account the decrease in signal in regions with the lesion. The FA threshold is particularly useful in terminating tracks before they enter regions containing the lesion. These regions, filled with CSF, have FA values close to zero. Therefore white matter pathways ordinarily connecting two ROIs will not be tracked if the ROI is completely lesioned, despite appearing intact in the transplanted T1-w image from which the parcelation is made. If a parcelation is partially compromised by the lesion then white matter pathways will also be partially tracked as reflected by a lesser number of streamlines.DWI was aligned to the same reference b = 0 s/mm2 image used to align the corrected T1-w via VBT to DTI. Distortions caused by eddy currents and head motion were corrected using the FSL eddy current correction (12 degrees of freedom linear transformation), and the diffusion gradient vectors rotated accordingly (). That is, the T1-w images with the “transplanted masks” are used to supply the region of interest landmarks for tractography but do not directly impact the tractography algorithm as the transplant is not performed in the DWI space.The diffusion-weighted images were resampled to 2mm isotropic resolution ().White matter deterministic tractography of DTI data was performed in Trackvis software () using the FACT algorithm (). Threshold values of a maximum of 60° turning angle and a minimum of 0.20 fractional anisotropy (FA) were used as stopping criteria for the tracking algorithm. These thresholds take into account the decrease in signal in regions with the lesion. The FA threshold is particularly useful in terminating tracks before they enter regions containing the lesion. These regions, filled with CSF, have FA values close to zero. Therefore white matter pathways ordinarily connecting two ROIs will not be tracked if the ROI is completely lesioned, despite appearing intact in the transplanted T1-w image from which the parcelation is made. If a parcelation is partially compromised by the lesion then white matter pathways will also be partially tracked as reflected by a lesser number of streamlines. […]

Pipeline specifications

Software tools The Virtual Brain, TrackVis
Applications Magnetic resonance imaging, Diffusion magnetic resonance imaging analysis
Organisms Homo sapiens
Diseases Stroke