Applications of a dual-input pharmacokinetic model of dynamic contrast-enhanced MRI for evaluating tumorous microvascular properties in advanced hepatocellular carcinoma
ZHAO Zhigang, ZHAO Zhenhua, YANG Jianfeng, ZHANG Yu, ZHAO Li, YANG Liming, WANG Ting, LU Zengxin.
Department of Radiology, Shaoxing People’s Hospital, Shaoxing Hospital of Zhejiang University, Shaoxing, 312000
ZHAO Zhigang,ZHAO Zhenhua,YANG Jianfeng, et al. Applications of a dual-input pharmacokinetic model of dynamic contrast-enhanced MRI for evaluating tumorous microvascular properties in advanced hepatocellular carcinoma[J]. JOURNAL OF WEZHOU MEDICAL UNIVERSITY, 2017, 47(2): 96-103.
Abstract:Objective: To investigate the feasibility of a dual-input two-compartment tracer kinetic model for evaluating tumorous microvascular properties in advanced hepatocellular carcinoma (HCC). Methods: From January 2014 to April 2015, pharmacokinetic parameters included transfer constant (Ktrans), plasma flow (Fp), permeability surface area product (PS), efflux rate constant (Kep), extravascular extracellular space volume ratio (ve), blood plasma volume ratio (vp), and hepatic perfusion index (HPI) were prospectively measured and analyzed using dual-input two-compartment tracer kinetic models included a dual-input extended Tofts model and a dual-input 2-compartment exchange model (2CXM) in 28 consecutive HCC patients. A paired Student’s t-test and a nonparametric paired Wilcoxon rank sum test were used to compare the equivalent pharmacokinetic parameters derived from the two models, and pearson correlation analysis was applied to observe the correlations among all equivalent parameters. The tumor size and pharmacokinetic parameters were tested by pearson correlation analysis, while correlations among stage, tumor size and all pharmacokinetic parameters were assessed by spearman correlation analysis. Results: The Fp value was greater than the PS value (Fp=1.07 mL/(mL•min), PS= 0.19 mL/(mL•min) in the dual-input 2CXM. HPI was 0.66 and 0.63 in the dual-input extended Tofts model and the dual-input 2CXM, respectively. There were no significant differences in the Kep, Vp, and HPI between the dual-input extended Tofts model and the dual-input 2CXM (P=0.524, P=0.569, P=0.622, respectively). Except for Ve, other equivalent pharmacokinetic parameters were correlated in the two dual-input two-compartment pharmacokinetic models; both Fp and PS in the dual-input 2CXM were correlated with Ktrans derived from the dual-input extended Tofts model (r=0.566, P=0.002; r=0.570, P=0.002); Kep, Vp, and HPI between the two kinetic models were positive correlated (r=0.594, P=0.001; r=0.686, P=0.0001; r=0.391, P=0.004, respectively). In the dual input extended Tofts model, Ve was significantly less than in the dual input 2CXM (P=0.004), and no significant correlation was seen between the two tracer kinetic models (r=0.276, P=0.156). Neither tumor size nor tumor stage was significantly correlated with any of the pharmacokinetic parameters obtained from the two models (P>0.05). Conclusion: A dual-input two-compartment pharmacokinetic model can be used in assessing the microvascular physiopathological properties in the pretreatment of advanced HCC. The dual-input extended Tofts model may be more stable in measuring the Ve. However, the dual-input 2CXM may be more detailed and accurate in measuring microvascular permeability.
[1] Corona-Villalobos C P, Halappa V G, Geschwind J F, et al. Volumetric assessment of tumour response using functional MR imaging in patients with hepatocellular carcinoma treated with a combination of doxorubicin-eluting beads and sorafenib[J]. Eur Radiol, 2015, 25(2): 380-390.
[2] O’Connor J P, Rose C J, Jackson A, et al. DCE-MRI biomarkers of tumour heterogeneity predict CRC liver metastasis shrinkage following bevacizumab and FOLFOX-6[J]. Br J Cancer, 2011, 105(1): 139-145.
[3] Teo Q Q, Thng C H, Koh T S, et al. Dynamic contrast-enhanced magnetic resonance imaging: applications in oncology[J]. Clin Oncol, 2014, 26(10): e9-20.
[4] Hirashima Y, Yamada Y, Tateishi U, et al. Pharmacokinetic parameters from 3-Tesla DCE-MRI as surrogate biomarkers of antitumor effects of bevacizumab plus FOLFIRI in colorectal cancer with liver metastasis[J]. Int J Cancer, 2012, 130(10): 2359-2365.
[5] De Bruyne S, Van Damme N, Smeets P, et al. Value of DCE-MRI and FDG-PET/CT in the prediction of response to preoperative chemotherapy with bevacizumab for colorectal liver metastases[J]. Br J Cancer, 2012, 106(12): 1926-1933.
[6] Jarnagin W R, Schwartz L H, Gultekin D H, et al. Regional chemotherapy for unresectable primary liver cancer: results of a phase II clinical trial and assessment of DCE-MRI as a biomarker of survival[J]. Ann Oncol, 2009, 20(9):1589-1595.
[7] Sahani D V, Jiang T, Hayano K, et al. Magnetic resonance imaging biomarkers in hepatocellular carcinoma: association with response and circulating biomarkers after sunitinib therapy[J]. J Hematol Oncol, 2013, 6: 51.
[8] Khalifa F, Soliman A, El-Baz A, et al. Models and methods for analyzing DCE-MRI: A review[J]. Med Phys, 2014, 41(12): 124301.
[9] Sourbron S P, Buckley D L. Tracer kinetic modelling in MRI: estimating perfusion and capillary permeability[J].Phys Med Biol, 2012, 57(2): R1-R33.
[10] Thng C H, Koh T S, Collins D J, et al. Perfusion magnetic resonance imaging of the liver[J]. World J Gastroenterol, 2010, 16(13): 1598-609.
[11] Van Beers B E, Daire J L, Garteiser P. New imaging techniques for liver diseases[J]. J Hepatol, 2015, 62(3):690-700.
[12] European Association For The Study Of The Liver, European Organisation For Research And Treatment Of Cancer. EASLEORTC clinical practice guidelines: management of hepatocellular carcinoma[J]. J Hepatol, 2012, 56(4): 908-943.
[13] Donaldson S B, West C M, Davidson S E, et al. A comparison of tracer kinetic models for T1-weighted dynamic contrast-enhanced MRI: application in carcinoma of the cervix[J]. Magn Reson Med, 2010, 63(3): 691-700.
[14] Tofts P S. Modeling tracer kinetics in dynamic Gd-DTPA MR imaging[J]. J Magn Reson Imaging, 1997, 7(1): 91-101.
[15] Bruix J, Sherman M, Llovet J M, et al. Clinical management of hepatocellular carcinoma. Conclusions of the Barcelona-2000 EASL conference[J]. J Hepatol, 2001, 35(3):421-430.
[16] Llovet J M, Di Bisceglie A M, Bruix J, et al. Design and endpoints of clinical trials in hepatocellular carcinoma[J]. J Natl Cancer Inst, 2008, 100(10): 698-711.
[17] Lee S H, Hayano K, Zhu A X, et al. Dynamic contrast-enhanced MRI kinetic parameters as prognostic biomarkers for prediction of survival of patient with advanced hepatocellular carcinoma: A pilot comparative study[J]. Acad Radiol, 2015, 22(11): 1344-1360.
[18] Chiandussi L, Greco F, Sardi G, et al. Estimation of hepatic arterial and portal venous blood flow by direct catheterization of the vena porta through the umbilical cord in man. Preliminary results[J]. Acta Hepatosplenol, 1968, 15 (3): 166-171.
[19] Hayashi M, Matsui O, Ueda K, et al. Progression to hypervascular hepatocellular carcinoma: correlation with intranodular blood supply evaluated with CT during intraarterial injection of contrast material[J]. Radiology, 2002, 225 (1): 143-149.
[20] Tofts P S, Brix G, Buckley D L, et al. Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusable tracer: standardized quantities and symbols[J]. J Magn Reson Imaging, 1999, 10(3): 223-232.
[21] Bergamino M, Bonzano L, Levrero F, et al. A review of technical aspects of T1-weighted dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in human brain tumors[J]. Phys Med, 2014, 30(6): 635-643.
[22] Michoux N, Huwart L, Abarca-Quinones J, et al. Transvascular and interstitial transport in rat hepatocellular carcinomas: dynamic contrast-enhanced MRI assessment with low- and high-molecular weight agents[J]. J Magn Reson Imaging, 2008, 28(4): 906-914.