Diffusion tensor invasive phenotypes can predict progression-free survival in glioblastomas

Mohsen, Laila; Shi, Victoria; Jena, R.; Gillard, Jonathan H.; Price, Stephen J.

doi:10.3109/02688697.2013.771136

Cited by 28 publications

(26 citation statements)

References 14 publications

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“…This measure allows distinction of the tumor core, tumor infiltration, and edema, and a better assessment of tumor extent. Price et al (103) have used this technique to predict the pattern of tumor recurrence, while Mohsen et al (105) recently reported higher survival in patients with a minimally invasive pattern. It can be hypothesized that this finding is correlated with a specific genotype of glioma.…”

Section: Review: Imaging Correlates Of Adult Glioma Genotypesmentioning

confidence: 99%

Imaging Correlates of Adult Glioma Genotypes

2017

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Primary brain tumors, most commonly gliomas, are histopathologically typed and graded as World Health Organization (WHO) grades I-IV according to increasing degrees of malignancy. These grades provide prognostic information and guidance on treatment such as radiation therapy and chemotherapy after surgery. Despite the confirmed value of the WHO grading system, results of a multitude of studies and prospective interventional trials now indicate that tumors with identical morphologic criteria can have highly different outcomes. Molecular markers can allow subtypes of tumors of the same morphologic type and WHO grade to be distinguished and are, therefore, of great interest in personalization of brain tumor treatment. Recent genomic-wide studies have resulted in a far more comprehensive understanding of the genomic alterations in gliomas and provide suggestions for a new molecularly based classification. Magnetic resonance (MR) imaging phenotypes can serve as noninvasive surrogates for tumor genotypes and can provide important information for diagnosis, prognosis, and, eventually, personalized treatment. The newly emerged field of radiogenomics allows specific MR imaging phenotypes to be linked with gene expression profiles. In this article, the authors review the conventional and advanced imaging features of three tumoral genotypes with prognostic and therapeutic consequences: (a) isocitrate dehydrogenase mutation; (b) the combined loss of the short arm of chromosome 1 and the long arm of chromosome 19, or 1p19q codeletion; and (c) methylguanine methyltransferase promoter methylation. RSNA, 2017.

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Section: Review: Imaging Correlates Of Adult Glioma Genotypesmentioning

confidence: 99%

Imaging Correlates of Adult Glioma Genotypes

2017

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“…Another promising application of DTI imaging is the potential to detect and predict the invasive growth patterns of high-grade tumors such as GBM. 6 A multitude of additional variations of diffusion imaging such as diffusion kurtosis imaging, 7 high b value, 8 histogram curve fitting, 9 functional diffusion maps, 10–12 and restriction spectrum imaging 13 are currently under investigation and may provide additional insights into complex tissue environments.…”

Section: Advanced Mri Techniquesmentioning

confidence: 99%

Conventional and advanced magnetic resonance imaging in patients with high-grade glioma

Pope¹,

Brandal²

2018

Q J Nucl Med Mol Imaging

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Magnetic resonance imaging is integral to the care of patients with high-grade gliomas. Anatomic detail can be acquired with conventional structural imaging, but newer approaches also add capabilities to interrogate image-derived physiologic and molecular characteristics of central nervous system neoplasms. These advanced imaging techniques are increasingly employed to generate biomarkers that better reflect tumor burden and therapy response. The following is an overview of current strategies based on advanced magnetic resonance imaging that are used in the assessment of high-grade glioma patients with an emphasis on how novel imaging biomarkers can potentially advance patient care.

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“…To interpret the high-dimensional tensor imaging, a decomposition into isotropic component (p) and anisotropic component (q) was proposed [12]. This method measures the isotropic and anisotropic diffusion of water molecules and has shown its utility in predicting tumor progression [13] and patient survival [14]. More recently, integrating these modalities was considered useful in revealing the intratumoral invasive component [15] and predicting IDH genotype in high-grade gliomas [16].…”

Section: Introductionmentioning

confidence: 99%

Multi-Parametric and Multi-Regional Histogram Analysis of MRI: Revealing Imaging Phenotypes of Glioblastoma Correlated with Patient Survival

Wang

Serra

et al. 2017

Preprint

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IntroductionGlioblastoma is characterized by its remarkable heterogeneity and dismal prognosis. Histogram analysis of quantitative magnetic resonance imaging (MRI) is an important in vivomethod to study intratumoral heterogeneity. With large amounts of histogram features generated, integrating these modalities effectively for clinical decision remains a challenge. MethodsA total of 80 patients with supratentorial primary glioblastoma were recruited. All patients received surgery and standard regimen of temozolomide chemoradiotherapy. Diagnosis was confirmed by pathology. Anatomical T2-weighted, T1-weighted post-contrast and FLAIR images, as well as dynamic susceptibility contrast (DSC), diffusion tensor imaging (DTI) and chemical shift imaging were acquired preoperatively using a 3T MRI scanner. DTI-p, DTI-q, relative cerebral blood volume (rCBV), mean transit time (MTT) and relative cerebral blood flow (rCBF) maps were generated. Contrast-enhancing (CE) and non-enhancing (NE) regions of interest were manually delineated. Voxel intensity histograms were constructed from the CE and NE regions independently. Patient clustering was performed by the Multi-View Biological Data Analysis (MVDA) approach. Kaplan-Meier and Cox proportional hazards regression analyses were performed to evaluate the relevance of the patient clustering to survival. The histogram features selected from MVDA approach were evaluated using receiver operator characteristics (ROC) curve analysis. The metabolic signatures of the patient clusters were analyzed by multivoxel MR spectroscopy (MRS).All rights reserved. No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/235861 doi: bioRxiv preprint first posted online Dec. 18, 2017; ResultsThe MVDA approach yielded two final patient clusters, consisting of 53 and 27 patients respectively. The two patient subgroups showed significance for overall survival (p = 0.007, HR = 0.32) and progression-free survival (p < 0.001, HR = 0.33) in multivariate Cox regression analysis. Among the features selected by MVDA, higher mean value of DTI-q in the non-enhancing region contributed to a worse OS (HR = 1.40, p = 0.020) and worse PFS (HR = 1.36, p = 0.031). Multivoxel MRS showed N-acetylaspartate/creatine (NAA/Cr) ratio between the two clusters, both in the CE region (p < 0.001) and NE region (p = 0.013).Glutamate/Cr (Glu/Cr) ratio and glutamate + glutamine/Cr (Glx/Cr) of the cluster 1 was significantly lower than cluster 2 (p = 0.037, and 0.027 respectively) In the NE region. DiscussionThis study demonstrated that integrating multi-parametric and multi-regional MRI histogram features may help to stratify patients. The histogram features selected from the proposed approach may be used as potential imaging markers in personalized treatment strategy and response determination.Key words: Glioblastoma, heterogeneity, magnetic resonance i...

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Diffusion tensor invasive phenotypes can predict progression-free survival in glioblastomas

Abstract: It is possible to identify three invasive phenotypes in GBMs using Diffusion tensor imaging , and these three phenotypes have different progression free survival. A minimal phenotype (20% of patients) predicts a greater delay to progression.

Cited by 28 publications

References 14 publications

Imaging Correlates of Adult Glioma Genotypes

Imaging Correlates of Adult Glioma Genotypes

Conventional and advanced magnetic resonance imaging in patients with high-grade glioma

Multi-Parametric and Multi-Regional Histogram Analysis of MRI: Revealing Imaging Phenotypes of Glioblastoma Correlated with Patient Survival

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