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01.11.2010 | Diagnostic Neuroradiology

Brain surface motion imaging to predict adhesions between meningiomas and the brain surface

Erschienen in: Neuroradiology | Ausgabe 11/2010

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Abstract

Introduction

“Brain surface motion imaging” (BSMI) is the subtraction of pulse-gated, 3D, heavily T2-weighted image of two different phases of cerebrospinal fluid (CSF) pulsation, which enables the assessment of the dynamics of brain surface pulsatile motion. The purpose of this study was to evaluate the feasibility of this imaging method for providing presurgical information about adhesions between meningiomas and the brain surface.

Methods

Eighteen cases with surgically resected meningioma in whom BSMI was presurgically obtained were studied. BSMI consisted of two sets of pulse-gated, 3D, heavily T2-weighted, fast spin echo scans. Images of the systolic phase and the diastolic phase were obtained, and subtraction was performed with 3D motion correction. We analyzed the presence of band-like texture surrounding the tumor and judged the degree of motion discrepancy as “total,” “partial,” or “none.” The correlation between BSMI and surgical findings was evaluated. For cases with partial adhesions, agreements in the locations of the adhesions were also evaluated.

Results

On presurgical BSMI, no motion discrepancy was seen in eight cases, partial in six cases, and total in four cases. These presurgical predictions about adhesions and surgical findings agreed in 13 cases (72.2%). The locations of adhesions agreed in five of six cases with partial adhesions.

Conclusion

In the current study, BSMI could predict brain and meningioma adhesions correctly in 72.2% of cases, and adhesion location could also be predicted. This imaging method appears to provide presurgical information about brain/meningioma adhesions.
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Metadaten
Titel
Brain surface motion imaging to predict adhesions between meningiomas and the brain surface
Publikationsdatum
01.11.2010
Erschienen in
Neuroradiology / Ausgabe 11/2010
Print ISSN: 0028-3940
Elektronische ISSN: 1432-1920
DOI
https://doi.org/10.1007/s00234-010-0671-z

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