J Neurol Surg B Skull Base 2015; 76(03): 225-229
DOI: 10.1055/s-0034-1543965
Original Article
Georg Thieme Verlag KG Stuttgart · New York

Predicting Consistency of Meningioma by Magnetic Resonance Imaging

Kyle A. Smith
1   Department of Neurosurgery, University of Kansas Medical Center, Kansas City, Kansas, United States
,
John D. Leever
2   Department of Radiology, University of Kansas Medical Center, Kansas City, Kansas, United States
,
Roukoz B. Chamoun
1   Department of Neurosurgery, University of Kansas Medical Center, Kansas City, Kansas, United States
› Author Affiliations
Further Information

Publication History

16 March 2014

31 October 2014

Publication Date:
21 January 2015 (online)

Abstract

Objective Meningioma consistency is important because it affects the difficulty of surgery. To predict preoperative consistency, several methods have been proposed; however, they lack objectivity and reproducibility. We propose a new method for prediction based on tumor to cerebellar peduncle T2-weighted imaging intensity (TCTI) ratios.

Design The magnetic resonance (MR) images of 20 consecutive patients were evaluated preoperatively. An intraoperative consistency scale was applied to these lesions prospectively by the operating surgeon based on Cavitron Ultrasonic Surgical Aspirator (Valleylab, Boulder, Colorado, United States) intensity. Tumors were classified as A, very soft; B, soft/intermediate; or C, fibrous. Using T2-weighted MR sequence, the TCTI ratio was calculated. Tumor consistency grades and TCTI ratios were then correlated.

Results Of the 20 tumors evaluated prospectively, 7 were classified as very soft, 9 as soft/intermediate, and 4 as fibrous. TCTI ratios for fibrous tumors were all ≤ 1; very soft tumors were ≥ 1.8, except for one outlier of 1.66; and soft/intermediate tumors were > 1 to < 1.8.

Conclusion We propose a method using quantifiable region-of-interest TCTIs as a uniform and reproducible way to predict tumor consistency. The intraoperative consistency was graded in an objective and clinically significant way and could lead to more efficient tumor resection.

 
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