Differentiation of high-grade and low-grade diffuse gliomas by intravoxel incoherent motion MR imaging

Osamu Togao, Akio Hiwatashi, Koji Yamashita, Kazufumi Kikuchi, Masahiro Mizoguchi, Koji Yoshimoto, Satoshi O. Suzuki, Toru Iwaki, Makoto Obara, Marc Van Cauteren, Hiroshi Honda

Research output: Contribution to journalArticlepeer-review

93 Citations (Scopus)

Abstract

Background Our aim was to assess the diagnostic performance of intravoxel incoherent motion (IVIM) MR imaging for differentiating high-grade gliomas (HGGs) from low-grade gliomas (LGGs). Methods Forty-five patients with diffuse glioma (age 50.9 ± 20.4 y; 26 males, 19 females) were assessed with IVIM imaging using 13 b-values (0-1000 s/mm2) at 3T. The perfusion fraction (f), true diffusion coefficient (D), and pseudo-diffusion coefficient (D∗) were calculated by fitting the bi-exponential model. The apparent diffusion coefficient (ADC) was obtained with 2 b-values (0 and 1000 s/mm2). Relative cerebral blood volume was measured by the dynamic susceptibility contrast method. Two observers independently measured D, ADC, D∗, and f, and these measurements were compared between the LGG group (n = 16) and the HGG group (n = 29). Results Both D (1.26 ± 0.37 mm2/s in LGG, 0.94 ± 0.19 mm2/s in HGG; P <. 001) and ADC (1.28 ± 0.35 mm2/s in LGG, 1.03 ± 0.19 mm2/s in HGG; P <. 01) were lower in the HGG group. D was lower than ADC in the LGG (P <. 05) and HGG groups (P <. 0001). D∗ was not different between the groups. The f-values were significantly larger in HGG (17.5 ± 6.3%) than in LGG (5.8 ± 3.8%; P <. 0001) and correlated with relative cerebral blood volume (r = 0.85; P <. 0001). Receiver operating characteristic analyses showed areas under curve of 0.95 with f, 0.78 with D, 0.73 with ADC, and 0.60 with D∗. Conclusion IVIM imaging is useful in differentiating HGGs from LGGs.

Original languageEnglish
Pages (from-to)132-141
Number of pages10
JournalNeuro-Oncology
Volume18
Issue number1
DOIs
Publication statusPublished - Jan 1 2016

All Science Journal Classification (ASJC) codes

  • Oncology
  • Clinical Neurology
  • Cancer Research

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