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Methods of Analysis
Published in Andrei I. Holodny, Functional Neuroimaging, 2019
After spatial smoothing, spatial normalization (35,36) can be employed if necessary. This method transforms (stretching or shrinkage) an individual brain image onto a template space defined by a template image and then minimizes the difference between these two images. This procedure is required for intersubject averaging and statistical comparison between different groups and when standard coordinates are required to specify regions of activation. One drawback of this procedure is that as the template is typically derived from normal brains, transformations for a patient’s brain with a tumor, for example, can lead to image distortion at the site of the tumor where the brains to be normalized have areas of signal intensity that are very different compared with the corresponding area of the template brain. In other words, this procedure may distort the location of intact tissue to diminish the contribution of the lesion. If fMRI is performed for presurgical planning, for example, spatial normalization should not be used since keeping intact anatomical and functional information essential and the possibility of adding confounding effects must be eliminated.
Beyond DVH
Published in Tiziana Rancati, Claudio Fiorino, Modelling Radiotherapy Side Effects, 2019
Oscar Acosta, Renaud de Crevoisier
Spatial normalization is the process of obtaining a transformation between the native coordinate system and a single common coordinate system leading to meaningful correspondences across the population. This is a key step in pixel/voxel wise analysis since dose comparison results rely on anatomical alignment accuracy. In the case of DSMs, the mapping is generated by the direct relationship between a 3D coordinate system and the 2D map. As mentioned before, there are several ways for defining such a relationship. DSMs were obtained in different works (Sanchez-Nieto et al. 2001; Munbodh et al. 2008; Tucker et al. 2006; Hoogeman et al. 2004). The general idea is depicted in Figure 17.3 with a rectal DSM, where a direct relationship exists between the cylindrical coordinates and the 2D space in the O (ϴ,L) space. Thus, the mapping between the 3D organ and the 2D map is performed through the link between coordinates O (R,ϴ,L) of the organ wall and the cylindrical space counterpart O (R,ϴ,L). After the 3D–2D relationships are obtained, the dose is propagated and interpolated, yielding a 2D image of dose on the unfolded organ.
Neurobiology of Dyspnea: An Overview
Published in Donald A. Mahler, Denis E. O’Donnell, Dyspnea, 2014
Karleyton C. Evans, Robert B. Banzett
To help the reader recognize the various steps at which errors may be introduced, we will briefly review the common steps in image preprocessing as well as common analytic strategies. Because brains vary in size and shape, and because it is essentially impossible for subjects to remain motionless during the scans, image data are subjected to substantial spatial preprocessing steps before analyses are performed. Both PET and fMRI data undergo within-subject alignment (referred to as realignment or motion correction) to correct for small head movements during the experiment, and subsequently undergo three-dimensional warping to a common stereotactic space (referred to as spatial normalization).72 Neuroimaging data may also undergo “tissue segmentation,” a process that differentiates and separates gray matter from white matter and CSF components.73 The resultant segmented gray matter image can serve as an explicit mask to constrain image analysis to gray matter only. Examples of segmented and normalized gray matter images are presented in Figure 2.1. Finally, prior to statistical analyses, images are spatially smoothed with a three-dimensional Gaussian filter.
Influence of the hypothalamus–pituitary–gonadal axis reactivation and pubertal hormones on gray matter volume in early pubertal girls
Published in International Journal of Neuroscience, 2021
Lu Zhou, Tao Chen, Yu Wang, Yuchuan Fu, Xiaoling Xie, Xiaozheng Liu, Wei Chen, Zhihan Yan, Peining Liu
T1-weighted images were analyzed using the voxel-based morphometry toolbox (VBM8, http://dbm.neuro.uni-jena.de/) in SPM8 (http://www.fil.ion.ucl.ac.uk/spm). T1-weighted images were segmented into gray matter, white matter, and cerebrospinal fluid using the unified segmentation model in SPM8 [30]. After an initial affine registration of segmented images into the Montreal Neurological Institute space, the images were nonlinearly warped using diffeomorphic anatomical registration with exponentiated Lie algebra and were resampled to 3-mm cubic voxels [31]. Finally, spatially normalized images were modulated to ensure that the overall amount of each tissue class was not altered by the spatial normalization procedure, and smoothed with an 8 mm full-width at half-maximum Gaussian kernel. Voxel-based comparisons of GMV were performed between groups using two-sample t tests, with age at scan and total intracranial volume as covariates. The significance threshold was set at p < 0.001 at voxel level and cluster extent > 13 voxels with AlphaSim correction based on Monte Carlo simulations at cluster level which corresponded to a corrected p < 0.01. This AlphaSim correction was conducted using the AlphaSim program embedded into the REST Software (http://www.restfmri.net/forum/REST_V1.8). To verify the reliability of the results, the same processing steps were performed with the child template.
MRI evaluation of motor function recovery by rTMS and intensive occupational therapy and changes in the activity of motor cortex
Published in International Journal of Neuroscience, 2020
Ryo Ueda, Naoki Yamada, Masahiro Abo, Pradeepa Wanniarachchi Ruwan, Atsushi Senoo
The fMRI images were realigned, and the structural images were co-registered to the fMRI images using Statistical Parametric Mapping (SPM) 12 (Wellcome Trust Centre for Neuroimaging, London, United Kingdom). Image processing included spatial realignment and spatial normalization of a template brain image created by the Montreal Neurological Institute using 12-parameter affine transformation with 16 nonlinear iterations. We then applied 3 D smoothing after spatial normalization, and the Gaussian kernel full-width at half-maximum was set to 8 mm. To investigate the brain activity region responsible for the movement of paralyzed fingers, the estimates were compared using linear contrast associated with the motor and rest conditions. We used LI-toolbox [12] to calculate LI the precentral gyrus. Activation of lesional and non-lesional hemispheres were represented by LI values of–1 and +1, respectively, where LI = [(activation area in the lesional hemisphere–activation area in the non-lesional hemisphere)/(activation area in the lesional hemisphere + activation area in the non-lesional hemisphere)].
Cortical Alterations by the Abnormal Visual Experience beyond the Critical Period: A Resting-state fMRI Study on Constant Exotropia
Published in Current Eye Research, 2019
Hongmei Shi, Yanming Wang, Xuemei Liu, Lin Xia, Yao Chen, Qinlin Lu, Benedictor Alexander Nguchu, Huijuan Wang, Bensheng Qiu, Xiaoxiao Wang, Lixia Feng
MRI image preprocessing was performed using statistical parametric mapping (SPM8, https://www.fil.ion.ucl.ac.uk/spm/) and Data Processing Assistant for Resting-State fMRI (DPARSF 4.3) – a convenient plug-in software within Data Processing & Analysis for Brain Imaging (DPABI 3.0, http://rfmri.org/dpabi). The following series of steps were entailed in the preprocessing: First, to absolve from the inadaptability of participants and initial instability of the magnetic field, the first ten time points were discarded. Next, correction in slice timing and head motion was performed based on estimated parameters. Certainly, the participant with motion shift >2 mm and angular shift >2° in any direction was excluded from further processing. Finally, the spatial normalization to Montreal Neurological Institute space with resolution of 3 × 3 × 3 mm3 was achieved using DARTEL. Additionally, covariates, including head motion parameters, WM, and cerebrospinal fluid signal, were removed.