Published March 2021 | Version v1
Journal article

Differentiation of recurrent diffuse glioma from treatment-induced change using amide proton transfer imaging. Incremental value to diffusion and perfusion parameters

  • 1. Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seodaemun-gu, Seoul (Korea, Republic of)
  • 2. Department of Neurosurgery, Yonsei University College of Medicine, Seoul (Korea, Republic of)
  • 3. Department of Pathology, Yonsei University College of Medicine, Seoul (Korea, Republic of)
  • 4. Division of MRI Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD (United States)

Description

To evaluate the incremental value of amide proton transfer (APT) imaging to diffusion tensor imaging (DTI), dynamic susceptibility contrast (DSC) imaging, and dynamic contrast-enhanced (DCE) imaging in differentiating recurrent diffuse gliomas (World Health Organization grade II-IV) from treatment-induced change after concurrent chemoradiotherapy or radiotherapy. This study included 36 patients (25 patients with recurrent gliomas and 11 with treatment-induced changes) with post-treatment gliomas. The mean values of apparent diffusion coefficient (ADC), fractional anisotropy (FA), normalized cerebral blood volume (nCBV), normalized cerebral blood flow, volume transfer constant, rate transfer coefficient, extravascular extracellular volume fraction, plasma volume fraction, and APT asymmetry index were assessed. Independent quantitative parameters were investigated to predict recurrent glioma using multivariable logistic regression. The incremental value of APT signal to other parameters was assessed by the increase of the area under the curve, net reclassification index, and integrated discrimination improvement. Univariable analysis showed that lower ADC (p = 0.018), higher FA (p = 0.031), higher nCBV (p = 0.021), and higher APT signal (p = 0.009) were associated with recurrent gliomas. In multivariable logistic regression, the diagnostic performance of the model with ADC, FA, and nCBV significantly increased when APT signal was added, with areas under the curve of 0.87 and 0.92, respectively (net reclassification index of 0.77 and integrated discrimination improvement of 0.13). APT imaging may be a useful imaging biomarker that adds value to DTI, DCE, and DSC parameters for distinguishing between recurrent gliomas and treatment-induced changes.

Availability note (English)

Available from: http://dx.doi.org/10.1007/s00234-020-02542-5

Additional details

Identifiers

Publishing Information

Journal Title
Neuroradiology
Journal Volume
63
Journal Issue
3
Journal Page Range
p. 363-372
ISSN
0028-3940
CODEN
NRDYAB