Voxel-Based Texture Analysis of the Brain

Maani, Rouzbeh; Yang, Yee Hong; Kalra, Sanjay

doi:10.1371/journal.pone.0117759

Cited by 50 publications

(58 citation statements)

References 36 publications

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“…Similar to previously reported 3D TA studies, this study used default parameters to produce the texture maps. Maani et al suggests that the parameters for neighborhood radius ( N ) and offset distance ( D ) should be 1 to 3 for optimal results in single‐center studies . However, an increase in N and D would incur significantly higher computation costs and may not necessarily improve results, as the nearest neighbor information would not be accounted for.…”

Section: Discussionmentioning

confidence: 99%

“…However, voxelwise 3D TA instead computes the statistical differences in texture values. This technique has shown to be highly sensitive and specific in both Alzheimer's disease and ALS, supporting its potential as an imaging biomarker and diagnostic tool …”

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confidence: 88%

“…TA has potential for clinical use, providing information on many neurological disorders. Indeed, it has been used to study intracranial brain tumors, epilepsy, multiple sclerosis, Alzheimer's disease, and amyotrophic lateral sclerosis (ALS) …”

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confidence: 99%

“…Previous methods of using TA have been limited to 2D region‐of‐interest (ROI)‐based approaches. To address this limitation, a novel 3D TA technique based on the popular gray‐level co‐occurrence matrix (GLCM) method was previously developed . Using this method, texture features are computed at each voxel, subsequently producing 3D maps.…”

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confidence: 99%

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Reliability of 3D texture analysis: A multicenter MRI study of the brain

Khan

Ishaque

et al. 2019

Magnetic Resonance Imaging

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Background Texture analysis (TA) is an image‐analysis technique that detects complex intervoxel statistical patterns. 3D TA has shown potential in detecting cerebral degeneration not perceptible to the human eye in many neurological disorders. The reliability of this method's application in a multicenter study is unknown. Purpose To assess the intrasite and intersite reliability of a novel 3D TA method from data acquired systematically from the Canadian ALS Neuroimaging Consortium (CALSNIC). Study Type Prospective multicenter data with harmonized MR sequence parameters acquired from five sites. Population Six healthy subjects. Field Strength 3T 3D‐MPRAGE and 3D‐SPGR T1‐weighted MRI of the brain. Assessment Voxel‐based 3D TA was performed on the whole brain to produce texture maps. Statistical Tests Intra‐ and intersite reliability of texture features was assessed using a two‐way mixed‐effects model for intraclass correlation coefficients (ICC). ICCs were calculated in a region‐of‐interest (ROI) analysis of predetermined anatomically relevant areas. A voxelwise approach was used to assess the whole brain. Results In the ROI analyses, intrasite reliability was excellent (ICC > 0.75) across most regions and texture features (autocorrelation [autoc], contrast [contr], energy [energ]). Intersite reliability was excellent for most regions with autoc, ranging from fair to excellent for contr, and ICCs ranging from poor to good (<0.40–0.75) for energ. Voxelwise analyses revealed a large range in ICC across the brain for both intrasite and intersite ICCs (0.0–0.90), with higher reliability in the cortical gray matter compared with deeper subcortical structures. Data Conclusion Overall, the reliability of 3D TA was highly dependent on texture feature, region studied, and method of analysis (ROI or voxelwise). Intrasite reproducibility was good to excellent, and better than intersite. ROI‐based analyses present higher reliability in comparison with voxelwise analyses. Autoc has overall excellent reliability. These factors might be considered when designing future 3D TA studies. Level of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;51:1200–1209.

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Reliability of 3D texture analysis: A multicenter MRI study of the brain

Khan

Ishaque

et al. 2019

Magnetic Resonance Imaging

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“…normal control) and 26 images have CDR  1 (i.e. Alzheimer disease) as in [20]. The attribute of included subjects are summarized in …”

Section: A Experimental Datamentioning

confidence: 99%

Classification of Alzheimer Disease using Gabor Texture Feature of Hippocampus Region

Keserwani¹,

Pammi²,

Prakash³

et al. 2016

IJIGSP

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Abstract-The aim of this research is to propose a methodology to classify the subjects into Alzheimer disease and normal control on the basis of visual features from hippocampus region. All three dimensional MRI images were spatially normalized to the MNI/ICBM atlas space. Then, hippocampus region was extracted from brain structural MRI images, followed by application of two dimensional Gabor filter in three scales and eight orientations for texture computation. Texture features were represented on slice by slice basis by mean and standard deviation of magnitude of Gabor response. Classification between Alzheimer disease and normal control was performed with linear support vector machine. This study analyzes the performance of Gabor texture feature along each projection (axial, coronal and sagittal) separately as well as combination of all projections. The experimental results from both single projection (axial) as well as combination of all projections (axial, coronal and sagittal), demonstrated better classification performance over other existing method. Hence, this methodology could be used as diagnostic measure for the detection of Alzheimer disease.

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Evaluating the cerebral correlates of survival in amyotrophic lateral sclerosis

Ishaque

Mah

Seres

et al. 2018

Ann Clin Transl Neurol

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ObjectiveTo evaluate cerebral degenerative changes in ALS and their correlates with survival using 3D texture analysis.MethodsA total of 157 participants were included in this analysis from four neuroimaging studies. Voxel‐wise texture analysis on T1‐weighted brain magnetic resonance images (MRIs) was conducted between patients and controls. Patients were divided into long‐ and short‐survivors using the median survival of the cohort. Neuroanatomical differences between the two survival groups were also investigated.ResultsWhole‐brain analysis revealed significant changes in image texture (FDR P < 0.05) bilaterally in the motor cortex, corticospinal tract (CST), insula, basal ganglia, hippocampus, and frontal regions including subcortical white matter. The texture of the CST correlated (P < 0.05) with finger‐ and foot‐tapping rate, measures of upper motor neuron function. Patients with a survival below the media of 19.5 months demonstrated texture change (FDR P < 0.05) in the motor cortex, CST, basal ganglia, and the hippocampus, a distribution which corresponds to stage 4 of the distribution TDP‐43 pathology in ALS. Patients with longer survival exhibited texture changes restricted to motor regions, including the motor cortex and the CST.InterpretationWidespread gray and white matter pathology is evident in ALS, as revealed by texture analysis of conventional T1‐weighted MRI. Length of survival in patients with ALS is associated with the spatial extent of cerebral degeneration.

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Voxel-Based Texture Analysis of the Brain

Cited by 50 publications

References 36 publications

Reliability of 3D texture analysis: A multicenter MRI study of the brain

Reliability of 3D texture analysis: A multicenter MRI study of the brain

Classification of Alzheimer Disease using Gabor Texture Feature of Hippocampus Region

Evaluating the cerebral correlates of survival in amyotrophic lateral sclerosis

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