The online version of this article (doi:10.1007/s00330-016-4451-y) contains supplementary material, which is available to authorized users.
To investigate the value of local image variance (LIV) as a new technique for quantification of hypointense microvascular susceptibility-weighted imaging (SWI) structures at 7 Tesla for preoperative glioma characterization.
Adult patients with neuroradiologically suspected diffusely infiltrating gliomas were prospectively recruited and 7 Tesla SWI was performed in addition to standard imaging. After tumour segmentation, quantification of intratumoural SWI hypointensities was conducted by the SWI-LIV technique. Following surgery, the histopathological tumour grade and isocitrate dehydrogenase 1 (IDH1)-R132H mutational status was determined and SWI-LIV values were compared between low-grade gliomas (LGG) and high-grade gliomas (HGG), IDH1-R132H negative and positive tumours, as well as gliomas with significant and non-significant contrast-enhancement (CE) on MRI.
In 30 patients, 9 LGG and 21 HGG were diagnosed. The calculation of SWI-LIV values was feasible in all tumours. Significantly higher mean SWI-LIV values were found in HGG compared to LGG (92.7 versus 30.8; p < 0.0001), IDH1-R132H negative compared to IDH1-R132H positive gliomas (109.9 versus 38.3; p < 0.0001) and tumours with significant CE compared to non-significant CE (120.1 versus 39.0; p < 0.0001).
Our data indicate that 7 Tesla SWI-LIV might improve preoperative characterization of diffusely infiltrating gliomas and thus optimize patient management by quantification of hypointense microvascular structures.
• 7 Tesla local image variance helps to quantify hypointense susceptibility-weighted imaging structures.
• SWI-LIV is significantly increased in high-grade and IDH1-R132H negative gliomas.
• SWI-LIV is a promising technique for improved preoperative glioma characterization.
• Preoperative management of diffusely infiltrating gliomas will be optimized.
High resolution image (TIFF 2663 kb)330_2016_4451_MOESM1_ESM.tiff
Burger PC, Scheithauer BW, Vogel FS (2002) Surgical Pathology of the Nervous System and Its Coverings, 4 ed. Churchill Livingstone
Louis DN, Cavenee WK, Ohgaki H, Wiestler OD (2007) WHO Classification of Tumours of the Central Nervous System. WHO Regional Office Europe
Cancer Genome Atlas Research Network (2015) Comprehensive integrative genomic analysis of diffuse lower-grade gliomas. N Engl J Med. doi: 10.1056/NEJMoa1402121
Wang Q, Zhang H, Zhang J et al (2015) The diagnostic performance of magnetic resonance spectroscopy in differentiating high-from low-grade gliomas: a systematic review and meta-analysis. Eur Radiol 1–15. doi: 10.1007/s00330-015-4046-z
Pinker K, Stavrou I, Szomolanyi P et al (2007) Improved preoperative evaluation of cerebral cavernomas by high-field, high-resolution susceptibility-weighted magnetic resonance imaging at 3 Tesla: comparison with standard (1.5 T) magnetic resonance imaging and correlation with histopathological findings--preliminary results. Invest Radiol 42:346–351 CrossRefPubMed
Park MJ, Kim HS, Jahng G-H et al (2009) Semiquantitative assessment of intratumoral susceptibility signals using non-contrast-enhanced high-field high-resolution susceptibility-weighted imaging in patients with gliomas: comparison with MR perfusion imaging. AJNR Am J Neuroradiol 30:1402–1408 CrossRefPubMed
Vincent RD, Janke A, Sled JG et al (2004) A modality independent format for multidimensional medical images. Proceedings of the 10th Annual Meeting of the Organization for Human Brain Mapping
Christoph G, Hackel H (2002) Starthilfe Stochastik: Studium, 1st ed. Vieweg + Teubner Verlag
Yamashita K, Hiwatashi A, Togao O et al (2015) MR Imaging-Based Analysis of Glioblastoma Multiforme: Estimation of IDH1 Mutation Status. AJNR Am J Neuroradiol. doi: 10.3174/ajnr.A4491
- Local image variance of 7 Tesla SWI is a new technique for preoperative characterization of diffusely infiltrating gliomas: correlation with tumour grade and IDH1 mutational status
- Springer Berlin Heidelberg
Neu im Fachgebiet Radiologie
Meistgelesene Bücher aus der Radiologie
e.Med Kampagnen-Visual, Mail Icon II