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MR Fingerprinting for Rapid Quantitative Abdominal Imaging.

Publication ,  Journal Article
Chen, Y; Jiang, Y; Pahwa, S; Ma, D; Lu, L; Twieg, MD; Wright, KL; Seiberlich, N; Griswold, MA; Gulani, V
Published in: Radiology
April 2016

PURPOSE: To develop a magnetic resonance (MR) "fingerprinting" technique for quantitative abdominal imaging. MATERIALS AND METHODS: This HIPAA-compliant study had institutional review board approval, and informed consent was obtained from all subjects. To achieve accurate quantification in the presence of marked B0 and B1 field inhomogeneities, the MR fingerprinting framework was extended by using a two-dimensional fast imaging with steady-state free precession, or FISP, acquisition and a Bloch-Siegert B1 mapping method. The accuracy of the proposed technique was validated by using agarose phantoms. Quantitative measurements were performed in eight asymptomatic subjects and in six patients with 20 focal liver lesions. A two-tailed Student t test was used to compare the T1 and T2 results in metastatic adenocarcinoma with those in surrounding liver parenchyma and healthy subjects. RESULTS: Phantom experiments showed good agreement with standard methods in T1 and T2 after B1 correction. In vivo studies demonstrated that quantitative T1, T2, and B1 maps can be acquired within a breath hold of approximately 19 seconds. T1 and T2 measurements were compatible with those in the literature. Representative values included the following: liver, 745 msec ± 65 (standard deviation) and 31 msec ± 6; renal medulla, 1702 msec ± 205 and 60 msec ± 21; renal cortex, 1314 msec ± 77 and 47 msec ± 10; spleen, 1232 msec ± 92 and 60 msec ± 19; skeletal muscle, 1100 msec ± 59 and 44 msec ± 9; and fat, 253 msec ± 42 and 77 msec ± 16, respectively. T1 and T2 in metastatic adenocarcinoma were 1673 msec ± 331 and 43 msec ± 13, respectively, significantly different from surrounding liver parenchyma relaxation times of 840 msec ± 113 and 28 msec ± 3 (P < .0001 and P < .01) and those in hepatic parenchyma in healthy volunteers (745 msec ± 65 and 31 msec ± 6, P < .0001 and P = .021, respectively). CONCLUSION: A rapid technique for quantitative abdominal imaging was developed that allows simultaneous quantification of multiple tissue properties within one 19-second breath hold, with measurements comparable to those in published literature.

Duke Scholars

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Published In

Radiology

DOI

EISSN

1527-1315

Publication Date

April 2016

Volume

279

Issue

1

Start / End Page

278 / 286

Location

United States

Related Subject Headings

  • Phantoms, Imaging
  • Nuclear Medicine & Medical Imaging
  • Middle Aged
  • Male
  • Magnetic Resonance Imaging
  • Image Interpretation, Computer-Assisted
  • Humans
  • Female
  • Algorithms
  • Aged
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Chen, Y., Jiang, Y., Pahwa, S., Ma, D., Lu, L., Twieg, M. D., … Gulani, V. (2016). MR Fingerprinting for Rapid Quantitative Abdominal Imaging. Radiology, 279(1), 278–286. https://doi.org/10.1148/radiol.2016152037
Chen, Yong, Yun Jiang, Shivani Pahwa, Dan Ma, Lan Lu, Michael D. Twieg, Katherine L. Wright, Nicole Seiberlich, Mark A. Griswold, and Vikas Gulani. “MR Fingerprinting for Rapid Quantitative Abdominal Imaging.Radiology 279, no. 1 (April 2016): 278–86. https://doi.org/10.1148/radiol.2016152037.
Chen Y, Jiang Y, Pahwa S, Ma D, Lu L, Twieg MD, et al. MR Fingerprinting for Rapid Quantitative Abdominal Imaging. Radiology. 2016 Apr;279(1):278–86.
Chen, Yong, et al. “MR Fingerprinting for Rapid Quantitative Abdominal Imaging.Radiology, vol. 279, no. 1, Apr. 2016, pp. 278–86. Pubmed, doi:10.1148/radiol.2016152037.
Chen Y, Jiang Y, Pahwa S, Ma D, Lu L, Twieg MD, Wright KL, Seiberlich N, Griswold MA, Gulani V. MR Fingerprinting for Rapid Quantitative Abdominal Imaging. Radiology. 2016 Apr;279(1):278–286.

Published In

Radiology

DOI

EISSN

1527-1315

Publication Date

April 2016

Volume

279

Issue

1

Start / End Page

278 / 286

Location

United States

Related Subject Headings

  • Phantoms, Imaging
  • Nuclear Medicine & Medical Imaging
  • Middle Aged
  • Male
  • Magnetic Resonance Imaging
  • Image Interpretation, Computer-Assisted
  • Humans
  • Female
  • Algorithms
  • Aged