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Neuroradiology

Published in:

01-09-2016

Reliability of cerebral vein volume quantification based on susceptibility-weighted imaging

Authors: K. Egger, A. K. Dempfle, S. Yang, R. Schwarzwald, A. Harloff, H. Urbach

Published in: Neuroradiology | Issue 9/2016

Abstract

Introduction

Susceptibility-weighted imaging (SWI) visualizes even small cerebral veins and might, therefore, be valuable in monitoring neurological diseases affecting cerebral veins. Since it is generally difficult to evaluate individual results of quantitative MRI measurements, an automatic approach would be highly appreciated to assist the diagnostic process. The aim of this study was to evaluate the rescan and reanalysis reliability using an automatic venous volumetric approach based on SWI in healthy controls.

Methods

SWI was performed in ten healthy controls undergoing MRI examinations using a 32-channel head coil at 3 T five times on five different days. To test for rescan and reanalysis variability, the deep cerebral vein volume was quantified using ANTs and SPM8.

Results

Total volumes of cerebral deep veins measured during five MRI scans in ten individuals (n = 50 scans) showed intra-individual volume changes ranging from 0.07 to 1.03 ml (mean variability = 10.2 %). Automatic reanalyses revealed exactly the same results in all scans.

Conclusion

Automatic SWI-based cerebral vein volumetry shows acceptable rescan—and excellent reanalyses—reliability in healthy volunteers. Therefore, this approach might be beneficial in intra-individual follow-up studies of neurological diseases affecting the cerebral venous system.

Ogawa S, Lee TM, Kay AR et al (1990) Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc Natl Acad Sci U S A 87(24):9868–9872CrossRefPubMedPubMedCentral

Reichenbach JR, Barth M, Haacke EM et al (2000) High-resolution MR venography at 3.0 Tesla. J Comput Assist Tomogr 24(6):949–957CrossRefPubMed

Haacke EM, Xu Y, Cheng YN et al (2004) Susceptibility weighted imaging (SWI). Magn Reson Med 52(3):612–618. doi:10.1002/mrm.20198 CrossRefPubMed

Reichenbach JR, Venkatesan R, Schillinger DJ et al (1997) Small vessels in the human brain: MR venography with deoxyhemoglobin as an intrinsic contrast agent. Radiology 204(1):272–277. doi:10.1148/radiology.204.1.9205259 CrossRefPubMed

Sehgal V, Delproposto Z, Haacke EM et al (2005) Clinical applications of neuroimaging with susceptibility-weighted imaging. J Magn Reson Imaging 22(4):439–450. doi:10.1002/jmri.20404 CrossRefPubMed

Thomas B, Somasundaram S, Thamburaj K et al (2008) Clinical applications of susceptibility weighted MR imaging of the brain—a pictorial review. Neuroradiology 50(2):105–116. doi:10.1007/s00234-007-0316-z CrossRefPubMed

Tsui Y, Tsai FY, Hasso AN et al (2009) Susceptibility-weighted imaging for differential diagnosis of cerebral vascular pathology: a pictorial review. J Neurol Sci 287(1-2):7–16. doi:10.1016/j.jns.2009.08.064 CrossRefPubMed

Barnes SRS, Haacke EM (2009) Susceptibility-weighted imaging: clinical angiographic applications. Magn Reson Imaging Clin N Am 17(1):47–61. doi:10.1016/j.mric.2008.12.002 CrossRefPubMedPubMedCentral

Luo S, Yang L, Wang L (2014) Comparison of susceptibility-weighted and perfusion-weighted magnetic resonance imaging in the detection of penumbra in acute ischemic stroke. J Neuroradiol. doi:10.1016/j.neurad.2014.07.002

10.

Hermier M, Nighoghossian N (2004) Contribution of susceptibility-weighted imaging to acute stroke assessment. Stroke 35(8):1989–1994. doi:10.1161/01.STR.0000133341.74387.96 CrossRefPubMed

11.

Mahvash M, Pechlivanis I, Charalampaki P et al (2014) Visualization of small veins with susceptibility-weighted imaging for stereotactic trajectory planning in deep brain stimulation. Clin Neurol Neurosurg 124:151–155. doi:10.1016/j.clineuro.2014.06.041 CrossRefPubMed

12.

Xia X, Tan C (2013) A quantitative study of magnetic susceptibility-weighted imaging of deep cerebral veins. J Neuroradiol 40(5):355–359. doi:10.1016/j.neurad.2013.03.005 CrossRefPubMed

13.

Fushimi Y, Miki Y, Mori N et al (2010) Signal changes in the brain on susceptibility-weighted imaging under reduced cerebral blood flow: a preliminary study. J Neuroimaging 20(3):255–259. doi:10.1111/j.1552-6569.2008.00348.x CrossRefPubMed

14.

Sedlacik J, Helm K, Rauscher A et al (2008) Investigations on the effect of caffeine on cerebral venous vessel contrast by using susceptibility-weighted imaging (SWI) at 1.5, 3 and 7 T. Neuroimage 40(1):11–18. doi:10.1016/j.neuroimage.2007.11.046 CrossRefPubMed

15.

Chang K, Barnes S, Haacke EM et al (2014) Imaging the effects of oxygen saturation changes in voluntary apnea and hyperventilation on susceptibility-weighted imaging. AJNR Am J Neuroradiol 35(6):1091–1095. doi:10.3174/ajnr.A3818 CrossRefPubMed

16.

Tustison NJ, Avants BB, Cook PA et al (2010) N4ITK: improved N3 bias correction. IEEE Trans Med Imaging 29(6):1310–1320. doi:10.1109/TMI.2010.2046908 CrossRefPubMedPubMedCentral

17.

Avants BB, Tustison NJ, Song G et al (2011) A reproducible evaluation of ANTs similarity metric performance in brain image registration. Neuroimage 54(3):2033–2044. doi:10.1016/j.neuroimage.2010.09.025 CrossRefPubMed

18.

Bates D, Mächler M, Bolker B et al (2015) Fitting linear mixed-effects models using lme4. J Stat Softw 67(1):1–48. doi:10.18637/jss.v067.i01 CrossRef

19.

Nowinski WL, Puspitasari F, Volkau I et al (2013) Quantification of the human cerebrovasculature: a 7 Tesla and 320-row CT in vivo study. J Comput Assist Tomogr 37(1):117–122. doi:10.1097/RCT.0b013e3182765906 CrossRefPubMed

20.

Schaller B (2004) Physiology of cerebral venous blood flow: from experimental data in animals to normal function in humans. Brain Res Brain Res Rev 46(3):243–260. doi:10.1016/j.brainresrev.2004.04.005 CrossRefPubMed

21.

Acosta-Cabronero J, Williams GB, Cardenas-Blanco A et al (2013) In vivo quantitative susceptibility mapping (QSM) in Alzheimer’s disease. PLoS ONE 8(11), e81093. doi:10.1371/journal.pone.0081093 CrossRefPubMedPubMedCentral

22.

Zheng W, Nichol H, Liu S et al (2013) Measuring iron in the brain using quantitative susceptibility mapping and X-ray fluorescence imaging. Neuroimage 78:68–74. doi:10.1016/j.neuroimage.2013.04.022 CrossRefPubMed

23.

Einhäupl K, Stam J, Bousser M et al (2010) EFNS guideline on the treatment of cerebral venous and sinus thrombosis in adult patients. Eur J Neurol 17(10):1229–1235. doi:10.1111/j.1468-1331.2010.03011.x CrossRefPubMed

24.

Savoiardo M, Minati L, Farina L et al (2007) Spontaneous intracranial hypotension with deep brain swelling. Brain 130(Pt 7):1884–1893. doi:10.1093/brain/awm101 CrossRefPubMed

25.

Mucke J, Möhlenbruch M, Kickingereder P et al (2015) Asymmetry of deep medullary veins on susceptibility weighted MRI in patients with acute MCA stroke is associated with poor outcome. PLoS ONE 10(4), e0120801. doi:10.1371/journal.pone.0120801 CrossRefPubMedPubMedCentral

Title: Reliability of cerebral vein volume quantification based on susceptibility-weighted imaging
Authors: K. Egger
A. K. Dempfle
S. Yang
R. Schwarzwald
A. Harloff
H. Urbach
Publication date: 01-09-2016
Publisher: Springer Berlin Heidelberg
Published in: Neuroradiology / Issue 9/2016
Print ISSN: 0028-3940
Electronic ISSN: 1432-1920
DOI: https://doi.org/10.1007/s00234-016-1712-z

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Reliability of cerebral vein volume quantification based on susceptibility-weighted imaging

Abstract

Introduction

Methods

Results

Conclusion

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Introduction

Methods

Results

Conclusion

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