Extended diffusion weighted magnetic resonance imaging with two-compartment and anomalous diffusion models for differentiation of low-grade and high-grade brain tumors in pediatric patients.

Purpose: The purpose of this study was to examine advanced diffusion-weighted magnetic resonance imaging (DW-MRI) models for differentiation of low- and high-grade tumors in the diagnosis of pediatric brain neoplasms. Methods: Sixty-two pediatric patients with various types and grades of brain tumor...

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Publicado en:Neuroradiology Vol. 59; no. 8; pp. 803 - 812
Autores principales: Burrowes, Delilah, Fangusaro, Jason, Nelson, Paige, Zhang, Bin, Wadhwani, Nitin, Rozenfeld, Michael, Deng, Jie
Formato: diagnostic images equations & formulas research tables/charts Journal Article
Publicado: Springer Nature Aug2017
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Aug2017
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s00234-017-1865-4
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        atl: Extended diffusion weighted magnetic resonance imaging with two-compartment and anomalous diffusion models for differentiation of low-grade and high-grade brain tumors in pediatric patients.
      aug:
        au:
          Burrowes, Delilah
          Fangusaro, Jason
          Nelson, Paige
          Zhang, Bin
          Wadhwani, Nitin
          Rozenfeld, Michael
          Deng, Jie
        affil: Department of Medical Imaging , Ann and Robert H. Lurie Children's Hospital of Chicago , 225 E. Chicago Ave Chicago 60611 USA
      sug:
        subj:
          Magnetic Resonance Imaging
          Brain Neoplasms Diagnosis
          Brain Neoplasms
          World Health Organization
          ROC Curve
          Logistic Regression
          Sensitivity and Specificity
          Data Collection
          Regression
      ab: Purpose: The purpose of this study was to examine advanced diffusion-weighted magnetic resonance imaging (DW-MRI) models for differentiation of low- and high-grade tumors in the diagnosis of pediatric brain neoplasms. Methods: Sixty-two pediatric patients with various types and grades of brain tumors were evaluated in a retrospective study. Tumor type and grade were classified using the World Health Organization classification (WHO I-IV) and confirmed by pathological analysis. Patients underwent DW-MRI before treatment. Diffusion-weighted images with 16 b-values (0-3500 s/mm) were acquired. Averaged signal intensity decay within solid tumor regions was fitted using two-compartment and anomalous diffusion models. Intracellular and extracellular diffusion coefficients (D and D), fractional volumes (V and V), generalized diffusion coefficient ( D), spatial constant (μ), heterogeneity index (β), and a diffusion index (index_diff = μ × V/β) were calculated. Multivariate logistic regression models with stepwise model selection algorithm and receiver operating characteristic (ROC) analyses were performed to evaluate the ability of each diffusion parameter to distinguish tumor grade. Results: Among all parameter combinations, D and index_diff jointly provided the best predictor for tumor grades, where lower D ( p = 0.03) and higher index_diff ( p = 0.009) were significantly associated with higher tumor grades. In ROC analyses of differentiating low-grade (I-II) and high-grade (III-IV) tumors, index_diff provided the highest specificity of 0.97 and D provided the highest sensitivity of 0.96. Conclusions: Multi-parametric diffusion measurements using two-compartment and anomalous diffusion models were found to be significant discriminants of tumor grading in pediatric brain neoplasms.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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