Literature DB >> 27109485

Application of histogram analysis for the evaluation of vascular permeability in glioma by the K2 parameter obtained with the dynamic susceptibility contrast method: Comparisons with Ktrans obtained with the dynamic contrast enhance method and cerebral blood volume.

Toshiaki Taoka1, Hisashi Kawai2, Toshiki Nakane2, Saeka Hori3, Tomoko Ochi3, Toshiteru Miyasaka3, Masahiko Sakamoto3, Kimihiko Kichikawa3, Shinji Naganawa2.   

Abstract

PURPOSE: The "K2" value is a factor that represents the vascular permeability of tumors and can be calculated from datasets obtained with the dynamic susceptibility contrast (DSC) method. The purpose of the current study was to correlate K2 with Ktrans, which is a well-established permeability parameter obtained with the dynamic contrast enhance (DCE) method, and determine the usefulness of K2 for glioma grading with histogram analysis.
METHODS: The subjects were 22 glioma patients (Grade II: 5, III: 6, IV: 11) who underwent DSC studies, including eight patients in which both DSC and DCE studies were performed on separate days within 10days. We performed histogram analysis of regions of interest of the tumors and acquired 20th percentile values for leakage-corrected cerebral blood volume (rCBV20%ile), K2 (K220%ile), and for patients who underwent a DCE study, Ktrans (Ktrans20%ile). We evaluated the correlation between K220%ile and Ktrans20%ile and the statistical difference between rCBV20%ile and K220%ile.
RESULTS: We found a statistically significant correlation between K220%ile and Ktrans20%ile (r=0.717, p<0.05). rCBV20%ile showed a significant difference between Grades II and III and between Grades II and IV, whereas K220%ile showed a statistically significant (p<0.05) difference between Grades II and IV and between Grades III and IV.
CONCLUSIONS: The K2 value calculated from the DSC dataset, which can be obtained with a short acquisition time, showed a correlation with Ktrans obtained with the DCE method and may be useful for glioma grading when analyzed with histogram analysis.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Glioma; K2; MRI; Perfusion imaging; Permeability imaging

Mesh:

Substances:

Year:  2016        PMID: 27109485     DOI: 10.1016/j.mri.2016.04.020

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  5 in total

1.  Texture features and pharmacokinetic parameters in differentiating benign and malignant breast lesions by dynamic contrast enhanced magnetic resonance imaging.

Authors:  Qingliang Niu; Xiaomei Jiang; Qin Li; Zhaolong Zheng; Hanwang Du; Shasha Wu; Xuexi Zhang
Journal:  Oncol Lett       Date:  2018-07-23       Impact factor: 2.967

2.  Dynamic susceptibility-contrast magnetic resonance imaging with contrast agent leakage correction aids in predicting grade in pediatric brain tumours: a multicenter study.

Authors:  Stephanie B Withey; Lesley MacPherson; Adam Oates; Stephen Powell; Jan Novak; Laurence Abernethy; Barry Pizer; Richard Grundy; Paul S Morgan; Simon Bailey; Dipayan Mitra; Theodoros N Arvanitis; Dorothee P Auer; Shivaram Avula; Andrew C Peet
Journal:  Pediatr Radiol       Date:  2022-03-15

3.  Deep-learned time-signal intensity pattern analysis using an autoencoder captures magnetic resonance perfusion heterogeneity for brain tumor differentiation.

Authors:  Ji Eun Park; Ho Sung Kim; Junkyu Lee; E-Nae Cheong; Ilah Shin; Sung Soo Ahn; Woo Hyun Shim
Journal:  Sci Rep       Date:  2020-12-08       Impact factor: 4.379

4.  Radiotherapy Target Volume Definition in Newly Diagnosed High-Grade Glioma Using 18F-FET PET Imaging and Multiparametric MRI: An Inter Observer Agreement Study.

Authors:  Brieg Dissaux; Doria Mazouz Fatmi; Julien Ognard; Bastien Allard; Nathalie Keromnes; Amina Latreche; Amandine Lepeuve; Ulrike Schick; Vincent Bourbonne; Douraied Ben Salem; Gurvan Dissaux; Solène Querellou
Journal:  Tomography       Date:  2022-08-16

5.  Differentiating between Central Nervous System Lymphoma and High-grade Glioma Using Dynamic Susceptibility Contrast and Dynamic Contrast-enhanced MR Imaging with Histogram Analysis.

Authors:  Kazuhiro Murayama; Yuya Nishiyama; Yuichi Hirose; Masato Abe; Shigeharu Ohyu; Ayako Ninomiya; Takashi Fukuba; Kazuhiro Katada; Hiroshi Toyama
Journal:  Magn Reson Med Sci       Date:  2017-05-18       Impact factor: 2.471

  5 in total

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