Intravoxel incoherent motion diffusion weighted imaging for the evaluation of pancreatic fibrosis: a preliminary study
LIU Yan-qing1, LIU Ying1, SHI Kai-ning2, WANG Xiao-qi2, WANG Min1, SHI Yu1, GUO Qi-yong1
1. Department of Radiology, Shengjing Hospital, China Medical University, Shenyang 110004, China;
2. Imaging Systems Clinical Science Philips Healthcare, Beijing 100600, China
Abstract：Objective: To evaluate the diagnostic performance of intravoxel incoherent motion diffusion weighted imaging(IVIM-DWI) for the evaluation of pancreatic fibrosis. Methods: A total of 15 healthy volunteers and 45 patients(F0: 15, F1: 10, F2: 11, F3: 9) with pancreatic or ampullary masses and subsequent pancreaticoduodenectomy underwent preoperative 3.0T MR IVIM imaging within less than one week. IVIM-DWI parameters(true diffusion coefficient(D), pseudo-diffusion coefficient(D*), and perfusion fraction(f)) were measured independently by two radiologists with more than 5 years of experience in abdominal imaging diagnosis. Spearman rank correlation coefficient was used to analyze the correlation between D, D*, f values and pancreatic fibrosis. Receiver operating characteristic curve(ROC) analysis was to determine the diagnostic performance of IVIM parameters for staging of pancreatic fibrosis(F0～F3). Results: The D, D* and f values measured by the two subjects were excellent(ICC: 0.925, 0.907, 0.823). f values showed a better negative correlation with fibrosis stages(r=-0.651, P<0.001) than D(r=-0.392, P=0.002) and D*(r=-0.523, P<0.001). f values had higher area under the curve(AUC) than that of D and D*(F0 vs (F1～F3): AUC=0.822, 0.662, 0.764, respectively; (F0, F1) vs (F2, F3): AUC=0.876, 0.772, 0.799, respectively), though without statistical significance(all P>0.05). Conclusion: IVIM-DWI is a promising method for staging of pancreatic fibrosis.
刘艳清1，刘 莹1，史凯宁2，王小奇2，王 敏1，石 喻1，郭启勇1. 体素内不相干运动扩散加权成像评价胰腺纤维化的初步研究[J]. 中国临床医学影像杂志, 2017, 28(10): 736-741.
LIU Yan-qing1, LIU Ying1, SHI Kai-ning2, WANG Xiao-qi2, WANG Min1, SHI Yu1, GUO Qi-yong1. Intravoxel incoherent motion diffusion weighted imaging for the evaluation of pancreatic fibrosis: a preliminary study. JOURNAL OF CHINA MEDICAL IMAGING, 2017, 28(10): 736-741.
[1]Ceyhan GO, Friess H. Pancreatic disease in 2014: Pancreatic fibrosis and standard diagnostics[J]. Nat Rev Gastroenterol Hepatol, 2015, 12(2): 68-70.
[2]Kang KM, Lee JM, Yoon JH, et al. Intravoxel incoherent motion diffusion-weighted MR imaging for characterization of focal pancreatic lesions[J]. Radiology, 2014, 270(2): 444-453.
[3]Ma C, Li Y, Wang L, et al. Intravoxel incoherent motion DWI of the pancreatic adenocarcinomas: monoexponential and biexponential apparent diffusion parameters and histopathological correlations[J]. Cancer Imaging, 2017, 17(1): 12.
[4]Witt H, Apte M V, Keim V, et al. Chronic pancreatitis: challenges and advances in pathogenesis, genetics, diagnosis, and therapy[J]. Gastroenterology, 2007, 132(4): 1557-1573.
[5]Apte M, Pirola R, Wilson J. The fibrosis of chronic pancreatitis: new insights into the role of pancreatic stellate cells[J]. Antioxid Redox Signal, 2011, 15(10): 2711-2722.
[6]Kelly KA, Hollingsworth MA, Brand RE, et al. Advances in Biomedical Imaging, Bioengineering, and Related Technologies for the Development of Biomarkers of Pancreatic Disease: Summary of a National Institute of Diabetes and Digestive and Kidney Diseases and National Institute of Biomedical Imaging and Bioengineering Workshop[J]. Pancreas, 2015, 44(8): 1185-1194.
[7]Watanabe H, Kanematsu M, Tanaka K, et al. Fibrosis and postoperative fistula of the pancreas: correlation with MR imaging findings-preliminary results[J]. Radiology, 2014, 270(3): 791-799.
[8]Yoon JH, Lee JM, Lee KB, et al. Pancreatic steatosis and fibrosis: quantitative assessment with preoperative multiparametric MR imaging[J]. Radiology, 2015, 279(1): 140-150.
[9]Garcia-Carracedo D, Yu CC, Akhavan N, et al. Smad4 loss synergizes with TGFα overexpression in promoting pancreatic metaplasia, PanIN development, and fibrosis[J]. PLoS one, 2015, 10(3): e0120851.
[10]Wellner UF, Kayser G, Lapshyn H, et al. A simple scoring system based on clinical factors related to pancreatic texture predicts postoperative pancreatic fistula preoperatively[J]. HPB(Oxford), 2010, 12(10): 696-702.
[11]Ichikawa S, Motosugi U, Morisaka H, et al. MRI-based staging of hepatic fibrosis: Comparison of intravoxel incoherent motion diffusion-weighted imaging with magnetic resonance elastography[J]. J Magn Reson Imaging, 2015, 42(1): 204-210.
[12]Sugimoto M, Takahashi S, Kobayashi T, et al. Pancreatic perfusion data and post-pancreaticoduodenectomy outcomes[J]. J Surg Res, 2015, 194(2): 441-449.
[13]Tanaka K, Tomita H, Osada S, et al. Significance of histopathological evaluation of pancreatic fibrosis to predict postoperative course after pancreatic surgery[J]. Anticancer Res, 2015, 35(3): 1749-1756.
[14]Klau M, Gaida MM, Lemke A, et al. Fibrosis and Pancreatic Lesions: Counterintuitive Behavior of the Diffusion Imaging-Derived Structural Diffusion Coefficient D[J]. Invest Radiol, 2013, 48(3): 129-133.
[15]Kuwahara T, Hirooka Y, Kawashima H, et al. Quantitative evaluation of pancreatic tumor fibrosis using shear wave elastography[J]. Pancreatology, 2016, 16(6): 1063-1068.
[16]Harada N, Ishizawa T, Inoue Y, et al. Acoustic radiation force impulse imaging of the pancreas for estimation of pathologic fibrosis and risk of postoperative pancreatic fistula[J]. J Am Coll Surg, 2014, 219(5): 887-894.
