Predicting Meningioma Consistency on Preoperative Neuroimaging Studies

Mark S. Shiroishi, Steven Y. Cen, Benita Tamrazi, Francesco D'Amore, Alexander Lerner, Kevin S. King, Paul E. Kim, Meng Law, Darryl H. Hwang, Orest B. Boyko, Chia Shang J. Liu

Research output: Contribution to journalReview articlepeer-review

15 Scopus citations


This article provides an overview of the neuroimaging literature focused on preoperative prediction of meningioma consistency. A validated, noninvasive neuroimaging method to predict tumor consistency can provide valuable information regarding neurosurgical planning and patient counseling. Most of the neuroimaging literature indicates conventional MRI using T2-weighted imaging may be helpful to predict meningioma consistency; however, further rigorous validation is necessary. Much less is known about advanced MRI techniques, such as diffusion MRI, MR elastography (MRE), and MR spectroscopy. Of these methods, MRE and diffusion tensor imaging appear particularly promising.

Original languageEnglish (US)
Pages (from-to)145-154
Number of pages10
JournalNeurosurgery Clinics of North America
Issue number2
StatePublished - Apr 1 2016


  • Consistency
  • Firmness
  • MRI
  • Meningioma
  • Minimally invasive neurosurgery
  • Neurosurgical planning
  • Prediction
  • Texture

ASJC Scopus subject areas

  • Surgery
  • Clinical Neurology

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