Michael Glantz, Urvashi Upadhyay, Dana T. Timek, Martin T. Pavelic, Richard P. Moser, Charles S. Specht, John M. Varlotto, Sangam Kanekar, Shakeeb Yunus, Christopher Dimaio, Matthew Tangel, John C. Flickinger, Jonas M. Sheehan, Steven Sogge, Thomas J. Fitzgerald, Paul Rava, and Aaron N. Yao
// John Varlotto 1 , John Flickinger 2 , Martin T. Pavelic 3 , Charles S. Specht 4 , Jonas M. Sheehan 5, 6 , Dana T. Timek 4 , Michael J. Glantz 5, 6 , Steven Sogge 7 , Christopher Dimaio 8 , Richard Moser 9 , Shakeeb Yunus 10 , Thomas J. Fitzgerald 1 , Urvashi Upadhyay 9 , Paul Rava 1 , Matthew Tangel 11 , Aaron Yao 12 , Sangam Kanekar 7 1 University of Massachusetts Medical Center, Department of Radiation Oncology, Worcester, MA, USA 2 University of Pittsburgh Medical Center, Department of Radiation Oncology, Pittsburgh, PA, USA 3 Columbia University Medical Center, Department of Anesthesia, New York, NY, USA 4 Penn State Hershey Medical Center, Department of Pathology, Hershey, PA, USA 5 Penn State Hershey Medical Center, Department of Neurosurgery, Hershey, PA, USA 6 Penn State Hershey Neuroscience Institute, Hershey, PA, USA 7 Penn State Hershey Medical Center, Department of Radiology, Hershey, PA, USA 8 Penn State Hershey Medical Center, Department of Neurology, Hershey, PA, USA 9 University of Massachusetts Medical Center, Division of Neurosurgery, Worcester, MA, USA 10 University of Massachusetts Medical Center, Department of Medical Oncology, Worcester, MA, USA 11 Penn State College of Medicine, Hershey, PA, USA 12 Department of Healthcare Policy and Research, Virginia Commonwealth University, Richmond, VA, USA Correspondence to: John M. Varlotto, e-mail: john.varlotto@umassmemorial.org Keywords: meningioma, MRI, cerebrovascular accident, tumor vascularity Received: July 08, 2015 Accepted: September 28, 2015 Published: October 09, 2015 ABSTRACT Background: Many meningiomas are identified by imaging and followed, with an assumption that they are WHO Grade I tumors. The purpose of our investigation is to find clinical or imaging predictors of WHO Grade II/III tumors to distinguish them from Grade I meningiomas. Methods: Patients with a pathologic diagnosis of meningioma from 2002–2009 were included if they had pre-operative MRI studies and pathology for review. A Neuro-Pathologist reviewed and classified all tumors by WHO 2007. All Brain MRI imaging was reviewed by a Neuro-radiologist. Pathology and Radiology reviews were blinded from each other and clinical course. Recursive partitioning was used to create predictive models for identifying meningioma grades. Results: Factors significantly correlating with a diagnosis of WHO Grade II-III tumors in univariate analysis: prior CVA ( p = 0.005), CABG ( p = 0.010), paresis ( p = 0.008), vascularity index = 4/4: ( p = 0.009), convexity vs other ( p = 0.014), metabolic syndrome ( p = 0.025), non-skull base ( p = 0.041) and non-postmenopausal female ( p = 0.045). Recursive partitioning analysis identified four categories: 1. prior CVA, 2. vascular index (vi) = 4 (no CVA), 3. premenopausal or male, vi < 4, no CVA. 4. Postmenopausal, vi < 4, no CVA with corresponding rates of 73, 54, 35 and 10% of being Grade II-III meningiomas. Conclusions: Meningioma patients with prior CVA and those grade 4/4 vascularity are the most likely to have WHO Grade II-III tumors while post-menopausal women without these features are the most likely to have Grade I meningiomas. Further study of the associations of clinical and imaging factors with grade and clinical behavior are needed to better predict behavior of these tumors without biopsy.