A Novel MRI Texture Analysis of Demyelination and Inflammation in Relapsing-Remitting Experimental Allergic Encephalomyelitis

Zhang, Yunyan; Wells, Jennifer; Buist, Richard; Peeling, James; Yong, V. Wee; Mitchell, J. Ross

doi:10.1007/11866565_93

Cited by 12 publications

(9 citation statements)

References 14 publications

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“…In particular, Zhang et al [6] characterized image texture in vivo using the polar S-Transform (pST) of histologically verified multiple sclerosis lesions within T2-weighted MRI. Both high and low frequency components, representing inflammation and demyelination, were significantly elevated in pathological regions compared to normal control tissue.…”

Section: Related Researchmentioning

confidence: 99%

Predicting MGMT Methylation Status of Glioblastomas from MRI Texture

Levner

Drabycz

Roldán

et al. 2009

Lecture Notes in Computer Science

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Abstract. In glioblastoma (GBM), promoter methylation of the DNA repair gene MGMT is associated with benefit from chemotherapy. Because MGMT promoter methylation status can not be determined in all cases, a surrogate for the methylation status would be a useful clinical tool. Correlation between methylation status and magnetic resonance imaging features has been reported suggesting that non-invasive MGMT promoter methylation status detection is possible. In this work, a retrospective analysis of T2, FLAIR and T1-post contrast MR images in patients with newly diagnosed GBM is performed using L1-regularized neural networks. Tumor texture, assessed quantitatively was utilized for predicting the MGMT promoter methylation status of a GBM in 59 patients. The texture features were extracted using a space-frequency texture analysis based on the S-transform and utilized by a neural network to predict the methylation status of a GBM. Blinded classification of MGMT promoter methylation status reached an average accuracy of 87.7%, indicating that the proposed technique is accurate enough for clinical use.

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Section: Related Researchmentioning

confidence: 99%

Predicting MGMT Methylation Status of Glioblastomas from MRI Texture

Levner

Drabycz

Roldán

et al. 2009

Lecture Notes in Computer Science

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“…Assessment of serial T2‐weighted MRI reveals that texture is finer in normal myelin and remyelinated lesions than in demyelinated lesions, and that the time course of MRI texture is concordant with the evolution of myelin integrity in these animals . Similarly, in mice with experimental allergic encephalomyelitis, abnormally increased lesion texture corresponds to greater tissue injury . The pathological substrates of texture measurements in human MS, however, have never been studied.…”

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confidence: 99%

Pathological correlates of magnetic resonance imaging texture heterogeneity in multiple sclerosis

Zhang

Moore²,

Laule³

et al. 2013

Annals of Neurology

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“…By using the Stockwell transform, they have shown that low frequency information can be a useful means to quantify lesion injury and recovery in MS. In an animal model of MS, Zhang et al (2006) have additionally shown that frequency information can be directly related to histopathological changes in lesions. As expected, classifier performance was best for lesion matter, for both global and local analyses of anisotropy.…”

Section: Discussionmentioning

confidence: 96%