Pancreatic adenocarcinoma: a pilot study of quantitative perfusion and diffusion-weighted breath-hold magnetic resonance imaging
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To confirm the feasibility of breath-hold DCE-MRI and DWI at 3T to obtain the intra-abdominal quantitative physiologic parameters, K trans, k ep, and ADC, in patients with untreated pancreatic ductal adenocarcinomas.
Diffusion-weighted single-shot echo-planar imaging (DW-SS-EPI) and dynamic contrast-enhanced (DCE) MRI were used for 16 patients with newly diagnosed biopsy-proven pancreatic ductal adenocarcinomas. K trans, k ep, and apparent diffusion coefficient (ADC) values of pancreatic tumors, non-tumor adjacent pancreatic parenchyma (NAP), liver metastases, and normal liver tissues were quantitated and statistically compared.
Fourteen patients were able to adequately hold their breath for DCE-MRI, and 15 patients for DW-SS-EPI. Four patients had liver metastases within the 6 cm of Z axis coverage centered on the pancreatic primary tumors. K trans values (10−3 min−1) of primary pancreatic tumors, NAP, liver metastases, and normal liver tissues were 7.3 ± 4.2 (mean ± SD), 25.8 ± 14.9, 8.1 ± 5.9, and 45.1 ± 15.6, respectively, k ep values (10−2 min−1) were 3.0 ± 0.9, 7.4 ± 3.1, 5.2 ± 2.0, and 12.1 ± 2.8, respectively, and ADC values (10−3 mm2/s) were 1.3 ± 0.2, 1.6 ± 0.3, 1.1 ± 0.1, and 1.3 ± 0.1, respectively. K trans, k ep, and ADC values of primary pancreatic tumors were significantly lower than those of NAP (p < 0.05), while K trans and k ep values of liver metastases were significantly lower than those of normal liver tissues (p < 0.05).
3T breath-hold quantitative physiologic MRI is a feasible technique that can be applied to a majority of patients with pancreatic adenocarcinomas.
KeywordsDCE-MRI DWI Pancreatic adenocarcinoma
Research Initiative Pilot Award from the Department of Radiology at UAB and NIH grant 2P30CA013148.
- 16.Dougherty G (2009) Digital image processing for medical applications. New York: Cambridge University PressGoogle Scholar
- 17.Tofts PS, Brix G, Buckley DL, et al. (1999) Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusible tracer: standardized quantities and symbols. J Magn Reson Imaging 10(3):223–232. doi:101002/(SICI)1522-2586(199909)10:3<223::AID-JMRI2>3.0.CO;2-SPubMedCrossRefGoogle Scholar
- 19.Neter J, Kutner MH, Nachtsheim JC, Wasserman W (1996) Applied linear statistical models, 4th edn. Columbus: The McGraw-Hill Companies Inc.Google Scholar
- 21.Heye T, Davenport MS, Horvath JJ, et al. (2013) Reproducibility of dynamic contrast-enhanced MR imaging. Part I. Perfusion characteristics in the female pelvis by using multiple computer-aided diagnosis perfusion analysis solutions. Radiology 266(3):801–811. doi: 10.1148/radiol.12120278 PubMedCrossRefGoogle Scholar
- 32.Chopra S, Verma A, Kundu S, et al. (2012) Evaluation of diffusion-weighted imaging as a predictive marker for tumor response in patients undergoing chemoradiation for postoperative recurrences of cervical cancer. J Cancer Res Ther 8(1):68–73. doi: 10.4103/0973-1482.95177 PubMedCrossRefGoogle Scholar