DOI QR코드

DOI QR Code

Findings Regarding an Intracranial Hemorrhage on the Phase Image of a Susceptibility-Weighted Image (SWI), According to the Stage, Location, and Size

  • Lee, Yoon Jung (Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Lee, Song (Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Jang, Jinhee (Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Choi, Hyun Seok (Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Jung, So Lyung (Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Ahn, Kook-Jin (Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Kim, Bum-soo (Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Lee, Kang Hoon (Department of Radiology, St. Paul's Hospital, College of Medicine, The Catholic University of Korea)
  • 투고 : 2015.05.18
  • 심사 : 2015.06.15
  • 발행 : 2015.06.30

초록

Purpose: Susceptibility weighted imaging (SWI) is a new magnetic resonance technique that can exploit the magnetic susceptibility differences of various tissues. Intracranial hemorrhage (ICH) looks a dark blooming on the magnitude images of SWI. However, the pattern of ICH on phase images is not well known. The purpose of this study is to characterize hemorrhagic lesions on the phase images of SWI. Materials and Methods: We retrospectively enrolled patients with ICH, who underwent both SWI and precontrast CT, between 2012 and 2013 (n = 95). An SWI was taken, using the 3-tesla system. A phase map was generated after postprocessing. Cases with an intracranial hemorrhage were reviewed by an experienced neuroradiologist and a trainee radiologist, with 10 years and 3 years of experience, respectively. The types and stages of the hemorrhages were determined in correlation with the precontrast CT, the T1- and T2-weighted images, and the FLAIR images. The size of the hemorrhage was measured by a one- directional axis on a magnitude image of SWI. The phase values of the ICH were qualitatively evaluated: hypo-, iso-, and hyper-intensity. We summarized the imaging features of the intracranial hemorrhage on the phase map of the SWI. Results: Four types of hemorrhage are observed: subdural and epidural; subarachnoid; parenchymal hemorrhage; and microbleed. The stages of the ICH were classified into 4 groups: acute (n = 34); early subacute (n = 11); late subacute (n = 15); chronic (n = 8); stage-unknown microbleeds (n = 27). The acute and early subacute hemorrhage showed heterogeneous mixed hyper-, iso-, and hypo-signal intensity; the late subacute hemorrhage showed homogeneous hyper-intensity, and the chronic hemorrhage showed a shrunken iso-signal intensity with the hyper-signal rim. All acute subarachnoid hemorrhages showed a homogeneous hyper-signal intensity. All parenchymal hemorrhages (> 3 mm) showed a dipole artifact on the phase images; however, microbleeds of less than 3 mm showed no dipole artifact. Larger hematomas showed a heterogeneous mixture of hyper-, iso-, and hypo-signal intensities. Conclusion: The pattern of the phase value of the SWI showed difference, according to the type, stage, and size.

키워드

참고문헌

  1. Parizel PM, Makkat S, Van Miert E, Van Goethem JW, van den Hauwe L, De Schepper AM. Intracranial hemorrhage: principles of CT and MRI interpretation. Eur Radiol 2001;11:1770-1783 https://doi.org/10.1007/s003300000800
  2. Bradley WG Jr. MR appearance of hemorrhage in the brain. Radiology 1993;189:15-26 https://doi.org/10.1148/radiology.189.1.8372185
  3. Allkemper T, Tombach B, Schwindt W, et al. Acute and subacute intracerebral hemorrhages: comparison of MR imaging at 1.5 and 3.0 T--initial experience. Radiology 2004;232:874-881 https://doi.org/10.1148/radiol.2323030322
  4. Nandigam RN, Viswanathan A, Delgado P, et al. MR imaging detection of cerebral microbleeds: effect of susceptibility-weighted imaging, section thickness, and field strength. AJNR Am J Neuroradiol 2009;30:338-343 https://doi.org/10.3174/ajnr.A1355
  5. Gupta RK, Rao SB, Jain R, et al. Differentiation of calcification from chronic hemorrhage with corrected gradient echo phase imaging. J Comput Assist Tomogr 2001;25:698-704 https://doi.org/10.1097/00004728-200109000-00006
  6. Haacke EM, Mittal S, Wu Z, Neelavalli J, Cheng YC. Susceptibility-weighted imaging: technical aspects and clinical applications, part 1. AJNR Am J Neuroradiol 2009;30:19-30 https://doi.org/10.3174/ajnr.A1400
  7. Mittal S, Wu Z, Neelavalli J, Haacke EM. Susceptibilityweighted imaging: technical aspects and clinical applications, part 2. AJNR Am J Neuroradiol 2009;30:232-252 https://doi.org/10.3174/ajnr.A1461
  8. Gomori JM, Grossman RI. Mechanisms responsible for the MR appearance and evolution of intracranial hemorrhage. Radiographics 1988;8:427-440 https://doi.org/10.1148/radiographics.8.3.3380989
  9. Deistung A, Rauscher A, Sedlacik J, Witoszynskyj S, Reichenbach JR. Informatics in Radiology: GUIBOLD: a graphical user interface for image reconstruction and data analysis in susceptibility-weighted MR imaging. Radiographics 2008;28:639-651 https://doi.org/10.1148/rg.283075715
  10. Wu Z, Li S, Lei J, An D, Haacke EM. Evaluation of traumatic subarachnoid hemorrhage using susceptibility-weighted imaging. AJNR Am J Neuroradiol 2010;31:1302-1310 https://doi.org/10.3174/ajnr.A2022
  11. Liu J, Liu T, de Rochefort L, et al. Morphology enabled dipole inversion for quantitative susceptibility mapping using structural consistency between the magnitude image and the susceptibility map. Neuroimage 2012;59:2560-2568 https://doi.org/10.1016/j.neuroimage.2011.08.082
  12. Schelhorn J, Gramsch C, Deuschl C, et al. Intracranial hemorrhage detection over time using susceptibilityweighted magnetic resonance imaging. Acta Radiol 2014 [Epub ahead of print]
  13. Liu T, Xu W, Spincemaille P, Avestimehr AS, Wang Y. Accuracy of the morphology enabled dipole inversion (MEDI) algorithm for quantitative susceptibility mapping in MRI. IEEE Trans Med Imaging 2012;31:816-824 https://doi.org/10.1109/TMI.2011.2182523
  14. McAuley G, Schrag M, Sipos P, et al. Quantification of punctate iron sources using magnetic resonance phase. Magn Reson Med 2010;63:106-115