Magnetic Resonance Insights

Kenneth L. Weiss¹, Dongmei Sun^1,2, Rebecca S. Cornelius¹ and Jane L. Weiss³

¹University of Cincinnati, Department of Radiology, Cincinnati, Ohio, U.S.A. ²Beijing Jiaotong University, Institute of Information Science, Beijing, P.R. China. ³WestImage, Division of Research, Cincinnati, Ohio, U.S.A.

Abstract

Background and Purpose: Multi-parametric MRI of the entire spine is technologist-dependent, time consuming, and often limited by inhomogeneous fat suppression. We tested a technique to provide rapid automated total spine MRI screening with improved tissue contrast through optimized fat-water separation.

Methods: The entire spine was auto-imaged in two contiguous 35 cm field of view (FOV) sagittal stations, utilizing out-of-phase fast gradient echo (FGRE) and T1 and/or T2 weighted fast spin echo (FSE) IDEAL (Iterative Decomposition of Water and Fat with Echo Asymmetric and Least-squares Estimation) sequences. 18 subjects were studied, one twice at 3.0T (pre and post contrast) and one at both 1.5 T and 3.0T for a total of 20 spine examinations (8 at 1.5 T and 12 at 3.0T). Images were independently evaluated by two neuroradiologists and run through Automated Spine Survey Iterative Scan Technique (ASSIST) analysis software for automated vertebral numbering.

Results: In all 20 total spine studies, neuroradiologist and computer ASSIST labeling were concordant. In all cases, IDEAL provided uniform fat and water separation throughout the entire 70 cm FOV imaged. Two subjects demonstrated breast metastases and one had a large presumptive schwannoma. 14 subjects demonstrated degenerative disc disease with associated Modic Type I or II changes at one or more levels. FGRE ASSIST afforded subminute submillimeter in-plane resolution of the entire spine with high contrast between discs and vertebrae at both 1.5 and 3.0T. Marrow signal abnormalities could be particularly well characterized with IDEAL derived images and parametric maps.

Conclusion: IDEAL ASSIST is a promising MRI technique affording a rapid automated high resolution, high contrast survey of the entire spine with optimized tissue characterization.

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