MR imaging of soft-tissue vascular malformations: Diagnosis, classification, and therapy follow-up

Lucía Flors, Carlos Leiva-Salinas, Ismaeel M. Maged, Patrick T. Norton, Alan H. Matsumoto, John F. Angle, Hugo Bonatti, Auh Whan Park, Ehab Ali Ahmad, Ugur Bozlar, Ahmed M. Housseini, Thomas E. Huerta, Klaus D. Hagspiel

Research output: Contribution to journalArticlepeer-review

197 Scopus citations

Abstract

Vascular malformations and tumors comprise a wide, heterogeneous spectrum of lesions that often represent a diagnostic and therapeutic challenge. Frequent use of an inaccurate nomenclature has led to considerable confusion. Since the treatment strategy depends on the type of vascular anomaly, correct diagnosis and classification are crucial. Magnetic resonance (MR) imaging is the most valuable modality for classification of vascular anomalies because it accurately demonstrates their extension and their anatomic relationship to adjacent structures. A comprehensive assessment of vascular anomalies requires functional analysis of the involved vessels. Dynamic time-resolved contrast material-enhanced MR angiography provides information about the hemodynamics of vascular anomalies and allows differentiation of high-flow and low-flow vascular malformations. Furthermore, MR imaging is useful in assessment of treatment success and establishment of a long-term management strategy. Radiologists should be familiar with the clinical and MR imaging features that aid in diagnosis of vascular anomalies and their proper classification. Furthermore, they should be familiar with MR imaging protocols optimized for evaluation of vascular anomalies and with their posttreatment appearances. Supplemental material available at http://radiographics.rsna.org/lookup/suppl/doi:10.1148/rg.315105213/-/DC1.

Original languageEnglish (US)
Pages (from-to)1321-1340
Number of pages20
JournalRadiographics
Volume31
Issue number5
DOIs
StatePublished - Sep 2011
Externally publishedYes

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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