Advertisement

European Radiology

, Volume 26, Issue 11, pp 3949–3956 | Cite as

Feasibility of test-bolus DCE-MRI using CAIPIRINHA-VIBE for the evaluation of pancreatic malignancies

  • Jimi Huh
  • Yoonseok Choi
  • Dong-Cheol Woo
  • Nieun Seo
  • Bohyun Kim
  • Chang Kyung Lee
  • In Seong Kim
  • Dominik Nickel
  • Kyung Won KimEmail author
Magnetic Resonance

Abstract

Objectives

To evaluate the feasibility of test-bolus dynamic contrast-enhanced (DCE) MRI with CAIPIRINHA-VIBE for pancreatic malignancies.

Methods

Thirty-two patients underwent DCE-MRI with CAIPIRINHA-VIBE after injection of 2 mL gadolinium. From the resulting time–intensity curve (TIC), we estimated the arterial (AP) and portal venous phase (PVP) scan timing for subsequent multiphasic MRI. DCE-MRI perfusion maps were generated, and perfusion parameters were calculated. The image quality was rated on a 5-point scale (1: poor, 5: excellent). Goodness-of-fit of the TIC was evaluated by Pearson’s χ2 test.

Results

Test-bolus DCE-MRIs with high temporal (3 s) and spatial resolution (1 × 1 × 4 mm3) were acquired with good-quality perfusion maps of Ktrans and iAUC (mean score 4.313 ± 0.535 and 4.125 ± 0.554, respectively). The mean χ2 values for fitted TICs were 0.115 ± 0.082 for the pancreatic parenchyma and 0.784 ± 0.074 for pancreatic malignancies, indicating an acceptable goodness-of-fit. Test-bolus DCE-MRI was highly accurate in estimating the proper timing of AP (90.6 %) and PVP (100 %) of subsequent multiphasic MRI. Between pancreatic adenocarcinomas and neuroendocrine tumours, there were significant differences in the Ktrans (0.073 ± 0.058 vs. 0.308 ± 0.062, respectively; p = 0.007) and iAUC (1.501 ± 0.828 vs. 3.378 ± 0.378, respectively; p = 0.045).

Conclusions

Test-bolus DCE-MRI using CAIPIRINHA-VIBE is feasible for incorporating perfusion analysis of pancreatic tumours into routine multiphasic MRI.

Key Points

Test-bolus DCE-MRI using CAIPIRINHA-VIBE is feasible for perfusion analysis of pancreatic tumours.

CAIPIRINHA-VIBE enables DCE-MRI with high temporal and spatial resolution.

Test-bolus DCE-MRI is highly accurate in estimating the proper timing of multiphasic MRI.

Keywords

Magnetic resonance imaging Pancreas Neoplasms Perfusion imaging Feasibility studies 

Abbreviations

DCE

Dynamic contrast-enhanced

AP

Arterial phase

PVP

Portal venous phase

CAIPIRINHA

Controlled aliasing in parallel imaging results in higher acceleration

VIBE

Volume interpolated breath-hold examination

TIC

Time-intensity curve

TPEAK

Time to peak aorta enhancement

Ktrans

Volume transfer constant

iAUC

Initial area under the concentration curve in 60 s

Radial-VIBE

Radial T1-weighted gradient-echo sequence

KWIC

K-space-weighted image contrast

Notes

Acknowledgments

The scientific guarantor of this publication is Kyung Won Kim. Two authors (In Seong Kim, Dominik Nickel) are employees of Siemens Healthcare. They provided us technical advice. However, they did not control or access the patients’ data. Only authors from academic institution handled the patients’ data. This study was supported by a grant (No. 2015-0636) from the Asan Institute for Life Sciences of Asan Medical Center and a grant (No. 2014R1A1A1006823) from the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT, & Future Planning. This study did not require a statistical expertise, because it is a study to evaluate technical feasibility. Institutional Review Board approval was obtained. Informed consent was waived because of the retrospective nature of this study. Methodology: retrospective, observational, performed at one institution.

References

  1. 1.
    Kim JH, Lee JM, Park JH et al (2013) Solid pancreatic lesions: characterization by using timing bolus dynamic contrast-enhanced MR imaging assessment--a preliminary study. Radiology 266:185–196CrossRefPubMedGoogle Scholar
  2. 2.
    Ueno M, Niwa T, Ohkawa S et al (2009) The usefulness of perfusion-weighted magnetic resonance imaging in advanced pancreatic cancer. Pancreas 38:644–648CrossRefPubMedGoogle Scholar
  3. 3.
    Akisik MF, Sandrasegaran K, Bu G, Lin C, Hutchins GD, Chiorean EG (2010) Pancreatic cancer: utility of dynamic contrast-enhanced MR imaging in assessment of antiangiogenic therapy. Radiology 256:441–449CrossRefPubMedGoogle Scholar
  4. 4.
    Baxter S, Wang ZJ, Joe BN, Qayyum A, Taouli B, Yeh BM (2009) Timing bolus dynamic contrast-enhanced (DCE) MRI assessment of hepatic perfusion: Initial experience. J Magn Reson Imaging 29:1317–1322CrossRefPubMedGoogle Scholar
  5. 5.
    Kim BS, Lee KR, Goh MJ (2014) New imaging strategies using a motion-resistant liver sequence in uncooperative patients. Biomed Res Int 2014:142658PubMedPubMedCentralGoogle Scholar
  6. 6.
    Committee. DMT (2012) DCE MRI Quantification Profile, Quantitative Imaging Biomarkers Alliance. Version 1.0. Reviewed DraftGoogle Scholar
  7. 7.
    Tofts PS, Brix G, Buckley DL et al (1999) Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusable tracer: standardized quantities and symbols. J Magn Reson Imaging 10:223–232CrossRefPubMedGoogle Scholar
  8. 8.
    Chefd'hotel C, Hermosillo G, Faugeras O (2002) Flows of diffeomorphisms for Multimodal Image Registration. Proceedings of the IEEE International Symposium on Biomedical Imaging, Washington DC, USA, pp 753–756Google Scholar
  9. 9.
    Chefd'hotel C, Hermosillo G, Faugeras O (2001) A Variational Approach to Multimodal Image Matching. Proceedings of the IEEE workshop on Variational and Level Set Methods in Computer Vision, Vancouver BC, Canada, pp 21–28Google Scholar
  10. 10.
    Kim KW, Lee JM, Jeon YS et al (2013) Free-breathing dynamic contrast-enhanced MRI of the abdomen and chest using a radial gradient echo sequence with K-space weighted image contrast (KWIC). Eur Radiol 23:1352–1360CrossRefPubMedGoogle Scholar
  11. 11.
    Tokuda J, Mamata H, Gill RR et al (2011) Impact of nonrigid motion correction technique on pixel-wise pharmacokinetic analysis of free-breathing pulmonary dynamic contrast-enhanced MR imaging. J Magn Reson Imaging 33:968–973CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Chandarana H, Block KT, Winfeld MJ et al (2014) Free-breathing contrast-enhanced T1-weighted gradient-echo imaging with radial k-space sampling for paediatric abdominopelvic MRI. Eur Radiol 24:320–326CrossRefPubMedGoogle Scholar
  13. 13.
    Fujinaga Y, Ohya A, Tokoro H et al (2014) Radial volumetric imaging breath-hold examination (VIBE) with k-space weighted image contrast (KWIC) for dynamic gadoxetic acid (Gd-EOB-DTPA)-enhanced MRI of the liver: advantages over Cartesian VIBE in the arterial phase. Eur Radiol 24:1290–1299CrossRefPubMedGoogle Scholar
  14. 14.
    Reiner CS, Neville AM, Nazeer HK et al (2013) Contrast-enhanced free-breathing 3D T1-weighted gradient-echo sequence for hepatobiliary MRI in patients with breath-holding difficulties. Eur Radiol 23:3087–3093CrossRefPubMedGoogle Scholar
  15. 15.
    Walker-Samuel S, Leach MO, Collins DJ (2006) Evaluation of response to treatment using DCE-MRI: the relationship between initial area under the gadolinium curve (IAUGC) and quantitative pharmacokinetic analysis. Phys Med Biol 51:3593–3602CrossRefPubMedGoogle Scholar
  16. 16.
    Leach MO, Brindle KM, Evelhoch JL et al (2003) Assessment of antiangiogenic and antivascular therapeutics using MRI: recommendations for appropriate methodology for clinical trials. Br J Radiol 76:S87–S91CrossRefPubMedGoogle Scholar
  17. 17.
    Naish JH, Hutchinson CE, Caunce A et al (2010) Multiple-bolus dynamic contrast-enhanced MRI in the pancreas during a glucose challenge. J Magn Reson Imaging 32:622–628CrossRefPubMedGoogle Scholar
  18. 18.
    Coenegrachts K, Van Steenbergen W, De Keyzer F et al (2004) Dynamic contrast-enhanced MRI of the pancreas: initial results in healthy volunteers and patients with chronic pancreatitis. J Magn Reson Imaging 20:990–997CrossRefPubMedGoogle Scholar

Copyright information

© European Society of Radiology 2016

Authors and Affiliations

  • Jimi Huh
    • 1
  • Yoonseok Choi
    • 2
  • Dong-Cheol Woo
    • 2
  • Nieun Seo
    • 1
  • Bohyun Kim
    • 1
  • Chang Kyung Lee
    • 2
  • In Seong Kim
    • 3
  • Dominik Nickel
    • 4
  • Kyung Won Kim
    • 1
    • 2
    Email author
  1. 1.Department of Radiology and Research Institute of Radiology, Asan Medical CenterUniversity of Ulsan College of MedicineSeoulKorea
  2. 2.Bioimaging Center, Asan Institute for Life SciencesAsan Medical CenterSeoulKorea
  3. 3.Siemens HealthcareSeoulKorea
  4. 4.Siemens HealthcareErlangenGermany

Personalised recommendations