Literature DB >> 24925770

Detection of infragenual arterial disease using non-contrast-enhanced MR angiography in patients with diabetes.

Xin Liu1, Na Zhang, Zhaoyang Fan, Fei Feng, Qi Yang, Hairong Zheng, Pengcheng Liu, Debiao Li.   

Abstract

PURPOSE: To evaluate the diagnostic performance of a newly developed non-contrast-enhanced MR angiography (NCE-MRA) technique using flow-sensitive dephasing (FSD) prepared steady-state free precession (SSFP) for detecting calf arterial disease in patients with diabetes.
MATERIALS AND METHODS: Forty-five patients with diabetes who underwent routine contrast-enhanced MR angiography (CE-MRA) of lower extremities were recruited for NCE-MRA at the calf on a 1.5 Tesla MR system. Image quality evaluated on a 4-point scale and diagnostic performance for detecting more than 50% arterial stenosis were statistically analyzed, using CE-MRA as the standard of reference.
RESULTS: A total of 264 calf arterial segments were obtained in the 45 patients with 88 legs. The percentage of diagnostic arterial segments was all 98% for NCE- and CE-MRA. The image quality, SNR, CNR was 3.3, 177, 138, and 3.5, 103, 99, for NCE-MRA and CE-MRA, respectively. The average sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of NCE-MRA were 97%, 96%, 90%, 99%, and 96%, respectively on a per-segment basis and 90%, 84%, 82%, 91%, and 87%, respectively, on a per-patients basis.
CONCLUSION: The NCE-MRA technique demonstrates adequate image quality in the delineation of calf arteries and consistent diagnostic performance for detecting significant stenosis with CE-MRA in patients with diabetes.
© 2013 Wiley Periodicals, Inc.

Entities:  

Keywords:  diabetes; flow-sensitive dephasing; non-contrast-enhanced MR angiography; peripheral vascular disease; steady-state free precession

Mesh:

Substances:

Year:  2013        PMID: 24925770      PMCID: PMC4059779          DOI: 10.1002/jmri.24477

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


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