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Intraaxial Brain Masses: MR Imaging–based Diagnostic Strategy—Initial Experience¹

¹ From the Departments of Radiology (R.N.A., J.K., J.H.W., R.L.W., H.P., E.R.M.) and Neurosurgery (D.M.O., K.D.J.), University of Pennsylvania School of Medicine, 3400 Spruce St, Dulles 2, Philadelphia, PA 19104; and Department of Nuclear Medicine, Medical University of Gdansk, Gdansk, Poland (J.K.). Received March 17, 2006; revision requested May 17; revision received July 31; accepted August 29; final version accepted November 1. Address correspondence to E.R.M. (e-mail: Elias.Melhem{at}uphs.upenn.edu).

Purpose: To develop and retrospectively determine the accuracy of a magnetic resonance (MR) imaging strategy to differentiate intraaxial brain masses, with histologic findings or clinical diagnosis as the reference standard.

Materials and Methods: The study was HIPAA compliant and was approved by the institutional review board. A waiver of informed consent was obtained. A strategy was developed on the basis of conventional MR imaging, diffusion-weighted MR imaging, perfusion MR imaging, and proton MR spectroscopy to classify intraaxial masses as low-grade primary neoplasms, high-grade primary neoplasms, metastatic neoplasms, abscesses, lymphomas, tumefactive demyelinating lesions (TDLs), or encephalitis. The strategy was evaluated by using data from 111 patients (46 women, 65 men; mean age, 48.9 years) with imaging results available on a departmental picture archiving and communication system from a 5-year search period. Bayesian statistics of the strategy elements and three clinical tasks were calculated.

Results: Search results identified 44 patients with high-grade and 14 with low-grade primary neoplasms, 24 with abscesses, 12 with lymphoma, 11 with TDLs, five with metastases, and one with encephalitis who had undergone conventional and advanced MR imaging. However, only 40 patients (25 women, 15 men; mean age, 45 years) had undergone all studies and had data to allow completion of the entire strategy. Accuracy, sensitivity, and specificity of the strategy, respectively, were 90%, 97%, and 67% for discrimination of neoplastic from nonneoplastic diseases, 90%, 88%, and 100% for discrimination of high-grade from low-grade neoplasms, and 85%, 84%, and 87% for discrimination of high-grade neoplasms and lymphoma from low-grade neoplasms and nonneoplastic diseases.

Conclusion: An integrated MR imaging–based strategy, which is accurate in differentiation of several intraaxial brain masses, was proposed.

© RSNA, 2007

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