Gadolinium effect on thalamus and whole brain tissue segmentation.

PURPOSE: Gadolinium-based contrast agent (GBCA) effect on automated segmentation algorithms of subcortical gray matter (GM) is not fully known. The aim of this study is to determine gadolinium effect on the segmentation of the thalamus and whole brain tissue using different automated segmentation techniques. METHODS: Eighty-four multiple sclerosis (MS) patients underwent an MRI acquisition of two 3DT1-weighted sequences with and without gadolinium injection among which 10 were excluded after image quality check. Manual thalamic segmentation considered as gold standard was performed on unenhanced T1 images. volBrain and FSL-Anat were used to automatically segment the thalamus on both enhanced and unenhanced T1 and the degree of similitude (DICE) values were compared between manual and automatic segmentations. Whole brain tissue segmentation (GM, white matter (WM), and lateral ventricles (LV)) was also performed using SIENAX. A paired samples t test was applied to test the significance of DICE value differences between the thalamic manual and automatic segmentations of both enhanced and unenhanced T1 images. RESULTS: Significant differences (FSL-Anat 1.474% p < 0.001 and volBrain 1.990% p < 0.001) in DICE between thalamic manual and automatic segmentations on both enhanced and unenhanced images were observed. Automatic tissue segmentation showed a mean DICE of 81.5%, with LV having the lowest DICE value (74.2%). When compared to tissue segmentations, automatic thalamic segmentations by FSL-Anat or volBrain demonstrated a higher degree of similitude (FSL-Anat = 91.7% and volBrain = 90.7%). CONCLUSION: Gadolinium has a significant effect on subcortical GM segmentation. Although significant, the observed subtle changes could be considered acceptable when used for region-based analysis in perfusion or diffusion imaging.

Voxel-based Morphometry of Alzheimer's Disease Using a Localizer Image: A Comparative Study with Magnetization Prepared Rapid Acquisition with Gradient Echo.

PURPOSE: Magnetization prepared rapid acquisition with gradient echo (MPRAGE) sequence is a gold-standard technique for voxel-based morphometry (VBM) because of high spatial resolution and excellent tissue contrast, especially between gray matter (GM) and white matter (WM). Despite its benefits, MPRAGE exhibits distinct challenge for VBM in some patients with neurological disease because of long scan time and motion artifacts. Speedily acquired localizer images may alleviate this problem. This study aimed to evaluate the feasibility of VBM using 3D Fast Low Angle Shot image captured for localizer (L3DFLASH). METHODS: Consecutive 13 patients with pathologically confirmed Alzheimer's disease (AD) (82 ± 9 years) and 21 healthy controls (HC) (79 ± 4 years) were included in this study. Whole-brain L3DFLASH and MPRAGE were captured and preprocessed using the Computational Anatomy Toolbox 12 (CAT12). Agreement with MPRAGE was evaluated for L3DFLASH using regional normalized volume for segmented brain areas. In addition to brain volume difference on VBM and Bland-Altman analysis, atrophic pattern of AD on VBM was evaluated using L3DFLASH and MPRAGE. RESULTS: Acquisition time was 18 s for L3DFLASH and 288 s for MPRAGE. There was a slight systematic difference in all regional normalized volumes from L3DFLASH and MPRAGE. For the whole cohort, GM volume measured from MPRAGE was greater than that from L3DFLASH in most of the region on VBM. When AD and HC were compared, AD-related atrophic pattern was demonstrated in both L3DFLASH and MPRAGE on VBM, although the difference was noted in significant clusters between them. CONCLUSION: Although systematic difference was noted in regional brain volume measured from L3DFLASH and MPRAGE, AD-related atrophic pattern was preserved in L3DFLASH on VBM. VBM, using speedily acquired localizer image, may provide limited but useful information for evaluating brain atrophy.

The influence of limbic-predominant age-related TDP-43 encephalopathy on argyrophilic grain disease: A voxel-based morphometry analysis of pathologically confirmed cases.

BACKGROUND: The influence of limbic-predominant age-related TAR DNA-binding protein of 43 kDa encephalopathy neuropathological change (LATE-NC) on structural alterations in argyrophilic grain disease (AGD) have not been documented. This study aimed to investigate the morphological impact of LATE-NC on AGD through voxel-based morphometry (VBM) technique. MATERIALS AND METHODS: Fifteen individuals with pathologically verified AGD, comprising 6 with LATE-NC (comorbid AGD [cAGD]) and 9 without LATE-NC (pure AGD [pAGD]), along with 10 healthy controls (HC) were enrolled. Whole-brain 3D-T1-weighted images were captured and preprocessed utilizing the Computational Anatomy Toolbox 12. VBM was employed to compare gray matter volume among (i) pAGD and HC, (ii) cAGD and HC, and (iii) pAGD and cAGD. RESULTS: In comparison to HC, the pAGD group exhibited slightly asymmetric gray matter volume loss, particularly in the ambient gyrus, amygdala, hippocampus, anterior cingulate gyrus, and insula. Alternatively, the cAGD group exhibited greater gray matter volume loss, with a predominant focus on the inferolateral regions encompassing the ambient gyrus, amygdala, hippocampus, and the inferior temporal area, including the anterior temporal pole. The atrophy of the bilateral anterior temporal pole and right inferior temporal gyrus persisted when contrasting the pAGD and cAGD groups. CONCLUSION: Comorbidity with LATE-NC is linked to different atrophic distribution, particularly affecting the inferolateral regions in AGD. Consequently, the consideration of comorbid LATE-NC is crucial in individuals with AGD exhibiting more widespread temporal atrophy.

Automated Generation of Radiologic Descriptions on Brain Volume Changes From T1-Weighted MR Images: Initial Assessment of Feasibility.

Purpose: To examine the feasibility and potential difficulties of automatically generating radiologic reports (RRs) to articulate the clinically important features of brain magnetic resonance (MR) images. Materials and Methods: We focused on examining brain atrophy by using magnetization-prepared rapid gradient-echo (MPRAGE) images. The technology was based on multi-atlas whole-brain segmentation that identified 283 structures, from which larger superstructures were created to represent the anatomic units most frequently used in RRs. Through two layers of data-reduction filters, based on anatomic and clinical knowledge, raw images (~10 MB) were converted to a few kilobytes of human-readable sentences. The tool was applied to images from 92 patients with memory problems, and the results were compared to RRs independently produced by three experienced radiologists. The mechanisms of disagreement were investigated to understand where machine-human interface succeeded or failed. Results: The automatically generated sentences had low sensitivity (mean: 24.5%) and precision (mean: 24.9%) values; these were significantly lower than the inter-rater sensitivity (mean: 32.7%) and precision (mean: 32.2%) of the radiologists. The causes of disagreement were divided into six error categories: mismatch of anatomic definitions (7.2 ± 9.3%), data-reduction errors (11.4 ± 3.9%), translator errors (3.1 ± 3.1%), difference in the spatial extent of used anatomic terms (8.3 ± 6.7%), segmentation quality (9.8 ± 2.0%), and threshold for sentence-triggering (60.2 ± 16.3%). Conclusion: These error mechanisms raise interesting questions about the potential of automated report generation and the quality of image reading by humans. The most significant discrepancy between the human and automatically generated RRs was caused by the sentence-triggering threshold (the degree of abnormality), which was fixed to z-score >2.0 for the automated generation, while the thresholds by radiologists varied among different anatomical structures.