Prediction of high-grade meningioma by preoperative MRI assessment

High-grade (World Health Organization grades II and III) meningiomas grow aggressively and recur frequently, resulting in a poor prognosis. Assessment of tumor malignancy before treatment initiation is important. We attempted to determine predictive factors for high-grade meningioma on magnetic resonance (MR) imaging before surgery. We reviewed 65 meningiomas (39 cases, benign; 26 cases, high-grade) and assessed four factors: (1) tumor–brain interface (TBI) on T1-weighted imaging (T1WI), (2) capsular enhancement (CapE), i.e., the layer of the tumor–brain interface on gadolinium-enhanced T1WI (T1Gd), (3) heterogeneity on T1Gd, and (4) tumoral margin on T1Gd. All four factors were useful in distinguishing high-grade from benign meningiomas, according to univariate analysis. On multivariate regression analysis, unclear TBI and heterogeneous enhancement were independent predictive factors for high-grade meningioma. In meningiomas with an unclear TBI and heterogeneous enhancement, the probability of high-grade meningioma was 98%. Our data suggest that this combination of factors obtained from conventional sequences on MR imaging may be useful to predict high-grade meningioma.

[1]  S. Nakasu,et al.  Meningioma: proliferating potential and clinicoradiological features. , 1995, Neurosurgery.

[2]  S. Ng,et al.  Differentiation Between Classic and Atypical Meningiomas with Use of Diffusion Tensor Imaging , 2008, American Journal of Neuroradiology.

[3]  A. Jouvet,et al.  WHO grade II and III meningiomas: a study of prognostic factors , 2009, Journal of Neuro-Oncology.

[4]  B. Guthrie,et al.  Hitting a moving target: evolution of a treatment paradigm for atypical meningiomas amid changing diagnostic criteria. , 2008, Neurosurgical focus.

[5]  S. Nakasu,et al.  Interface between the meningioma and the brain on magnetic resonance imaging. , 1990, Surgical neurology.

[6]  M. Bondy,et al.  Epidemiology and etiology of intracranial meningiomas: A review , 1996, Journal of Neuro-Oncology.

[7]  J. Kuratsu,et al.  Incidence and clinical features of asymptomatic meningiomas. , 2000, Journal of neurosurgery.

[8]  T. Yoshimine,et al.  Scoring radiologic characteristics to predict proliferative potential in meningiomas , 2006, Brain Tumor Pathology.

[9]  R. Alday,et al.  Risk Factors Predicting Recurrence in Patients Operated on for Intracranial Meningioma. A Multivariate Analysis , 1999, Acta Neurochirurgica.

[10]  S. Nakasu,et al.  Preoperative identification of meningiomas that are highly likely to recur. , 1999, Journal of neurosurgery.

[11]  H. Mehdorn,et al.  MR spectroscopy in patients with intracranial meningiomas , 2007, Neurological research.

[12]  S. Nakasu,et al.  Interface between the meningioma and the brain. , 1989, Surgical neurology.

[13]  R. Grossman,et al.  Intracranial meningiomas: high-field MR imaging. , 1986, Radiology.

[14]  T. Mochizuki,et al.  Evaluation of the tumor-brain interface of intracranial meningiomas on MR imaging including FLAIR images. , 2003, Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine.

[15]  Madjid Samii,et al.  The Natural History of Incidental Meningiomas , 2003, Neurosurgery.

[16]  J. Ambrose,et al.  Computerized tomography scanning appearances of intracranial meningiomas. An attempt to predict the histological features. , 1979, Journal of neurosurgery.

[17]  Akira Matsumura,et al.  New observations concerning the interpretation of magnetic resonance spectroscopy of meningioma , 2008, European Radiology.

[18]  I. Whittle,et al.  The accuracy of meningioma grading: a 10‐year retrospective audit , 2005, Neuropathology and applied neurobiology.

[19]  J. Dietemann,et al.  CT findings in malignant meningiomas , 2004, Neuroradiology.

[20]  D. Louis WHO classification of tumours of the central nervous system , 2007 .

[21]  T. Mochizuki,et al.  Prediction of tumor-brain adhesion in intracranial meningiomas by MR imaging and DSA. , 2003, Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine.

[22]  T. Kawase,et al.  Lateral ventricular meningioma encapsulated by the dura‐like membrane , 2000, Neuropathology : official journal of the Japanese Society of Neuropathology.

[23]  D. Hosmer,et al.  A comparison of goodness-of-fit tests for the logistic regression model. , 1997, Statistics in medicine.

[24]  A. Göçer,et al.  Correlation of the relationships of brain-tumor interfaces, magnetic resonance imaging, and angiographic findings to predict cleavage of meningiomas. , 1999, Journal of neurosurgery.

[25]  T. Hori,et al.  Clinical and radiological features related to the growth potential of meningioma , 2006, Neurosurgical Review.

[26]  R. Burgut,et al.  Predicting the probability of meningioma recurrence in the preoperative and early postoperative period: a multivariate analysis in the midterm follow-up. , 2007, Skull base : official journal of North American Skull Base Society ... [et al.].