| 1 |
Goo HW, Goo JM. Dual-Energy CT: New Horizon in Medical Imaging [J]. Korean J Radiol, 2017, 18(4): 555-569.
|
| 2 |
Sellerer T, Noel PB, Patino M, et al. Dual-energy CT: a phantom comparison of different platforms for abdominal imaging [J]. Eur Radiol, 2018, 28(7): 2745-2755.
|
| 3 |
McCollough CH, Leng S, Yu L, et al. Dual- and Multi-Energy CT: Principles, Technical Approaches, and Clinical Applications [J]. Radiology, 2015, 276(3): 637-653.
|
| 4 |
Li W, Li A, Wang B, et al. Automatic spectral imaging protocol and iterative reconstruction for radiation dose reduction in typical hepatic hemangioma computed tomography with reduced iodine load: a preliminary study [J]. Br J Radiol, 2018, 91(1087): 20170978.
|
| 5 |
Durieux P, Gevenois PA, Muylem AV, et al. Abdominal Attenuation Values on Virtual and True Unenhanced Images Obtained With Third-Generation Dual-Source Dual-Energy CT [J]. AJR Am J Roentgenol, 2018, 210(5): 1042-1058.
|
| 6 |
Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries [J]. CA Cancer J Clin, 2021, 71(3): 209-249.
|
| 7 |
Roayaie S, Blume IN, Thung SN, et al. A system of classifying microvascular invasion to predict outcome after resection in patients with hepatocellular carcinoma [J]. Gastroenterology, 2009, 137(3): 850-855.
|
| 8 |
Shah SA, Cleary SP, Wei AC, et al. Recurrence after liver resection for hepatocellular carcinoma: risk factors, treatment, and outcomes [J]. Surgery, 2007, 141(3): 330-339.
|
| 9 |
Yang CB, Zhang S, Jia YJ, et al. Dual energy spectral CT imaging for the evaluation of small hepatocellular carcinoma microvascular invasion [J]. Eur J Radiol, 2017, 95: 222-227.
|
| 10 |
De Cecco CN, Caruso D, Schoepf UJ, et al. A noise-optimized virtual monoenergetic reconstruction algorithm improves the diagnostic accuracy of late hepatic arterial phase dual-energy CT for the detection of hypervascular liver lesions [J]. Eur Radiol, 2018, 28(8): 3393-3404.
|
| 11 |
Matsuda M, Tsuda T, Kido T, et al. Dual-Energy Computed Tomography in Patients With Small Hepatocellular Carcinoma: Utility of Noise-Reduced Monoenergetic Images for the Evaluation of Washout and Image Quality in the Equilibrium Phase [J]. J Comput Assist Tomogr, 2018, 42(6): 937-943.
|
| 12 |
Yoon JH, Chang W, Lee ES, et al. Double Low-Dose Dual-Energy Liver CT in Patients at High-Risk of HCC: A Prospective, Randomized, Single-Center Study [J]. Invest Radiol, 2020, 55(6): 340-348.
|
| 13 |
Caruso D, De Cecco CN, Schoepf UJ, et al. Can dual-energy computed tomography improve visualization of hypoenhancing liver lesions in portal venous phase? Assessment of advanced image-based virtual monoenergetic images [J]. Clin Imaging, 2017, 41: 118-124.
|
| 14 |
Altenbernd J, Forsting M, Lauenstein T, et al. Improved Image Quality and Detectability of Hypovascular Liver Metastases on DECT with Different Adjusted Window Settings [J]. Rofo, 2017, 189(3): 228-232.
|
| 15 |
Lenga L, Lange M, Arendt CT, et al. Can Dual-energy CT-based Virtual Monoenergetic Imaging Improve the Assessment of Hypodense Liver Metastases in Patients With Hepatic Steatosis? [J]. Acad Radiol, 2021, 28(6): 769-777.
|
| 16 |
Schuppan D, Afdhal NH. Liver cirrhosis [J]. Lancet, 2008, 371(9615): 838-851.
|
| 17 |
Guo SL, Su LN, Zhai YN, et al. The clinical value of hepatic extracellular volume fraction using routine multiphasic contrast-enhanced liver CT for staging liver fibrosis [J]. Clin Radiol, 2017, 72(3): 242-246.
|
| 18 |
Bandula S, Punwani S, Rosenberg WM, et al. Equilibrium contrast-enhanced CT imaging to evaluate hepatic fibrosis: initial validation by comparison with histopathologic sampling [J]. Radiology, 2015, 275(1): 136-143.
|
| 19 |
Elbanna KY, Mansoori B, Mileto A, et al. Dual-energy CT in diffuse liver disease: is there a role? [J]. Abdom Radiol (NY), 2020, 45(11): 3413-3424.
|
| 20 |
Bottari A, Silipigni S, Carerj ML, et al. Dual-source dual-energy CT in the evaluation of hepatic fractional extracellular space in cirrhosis [J]. Radiol Med, 2020, 125(1): 7-14.
|
| 21 |
Sofue K, Tsurusaki M, Mileto A, et al. Dual-energy computed tomography for non-invasive staging of liver fibrosis: Accuracy of iodine density measurements from contrast-enhanced data [J]. Hepatol Res, 2018, 48(12): 1008-1019.
|
| 22 |
Bak S, Kim JE, Bae K, et al. Quantification of liver extracellular volume using dual-energy CT: utility for prediction of liver-related events in cirrhosis [J]. Eur Radiol, 2020, 30(10): 5317-5326.
|
| 23 |
Goceri E, Shah ZK, Layman R, et al. Quantification of liver fat: A comprehensive review [J]. Comput Biol Med, 2016, 71: 174-189.
|
| 24 |
Xu MM, Brown RS. Liver transplantation for the referring physician [J]. Clin Liver Dis, 2015, 19(1): 135-153.
|
| 25 |
Abdalla EK, Vauthey JN. Steatosis as a risk factor in liver surgery [J]. Ann Surg, 2007, 246(2): 340-341.
|
| 26 |
Brunt EM, Janney CG, Di Bisceglie AM, et al. Nonalcoholic steatohepatitis: a proposal for grading and staging the histological lesions [J]. Am J Gastroenterol, 1999, 94(9): 2467-2474.
|
| 27 |
Kramer H, Pickhardt PJ, Kliewer MA, et al. Accuracy of Liver Fat Quantification With Advanced CT, MRI, and Ultrasound Techniques: Prospective Comparison With MR Spectroscopy [J]. AJR Am J Roentgenol, 2017, 208(1): 92-100.
|
| 28 |
Hyodo T, Yada N, Hori M, et al. Multimaterial Decomposition Algorithm for the Quantification of Liver Fat Content by Using Fast-Kilovolt-Peak Switching Dual-Energy CT: Clinical Evaluation [J]. Radiology, 2017, 283(1): 108-118.
|
| 29 |
Artz NS, Hines CD, Brunner ST, et al. Quantification of hepatic steatosis with dual-energy computed tomography: comparison with tissue reference standards and quantitative magnetic resonance imaging in the ob/ob mouse [J]. Invest Radiol, 2012, 47(10): 603-610.
|
| 30 |
Patel BN, Kumbla RA, Berland LL, et al. Material density hepatic steatosis quantification on intravenous contrast-enhanced rapid kilovolt (peak)-switching single-source dual-energy computed tomography [J]. J Comput Assist Tomogr, 2013, 37(6): 904-910.
|
| 31 |
Hur BY, Lee JM, Hyunsik W, et al. Quantification of the fat fraction in the liver using dual-energy computed tomography and multimaterial decomposition [J]. J Comput Assist Tomogr, 2014, 38(6): 845-852.
|
| 32 |
Wang B, Gao Z, Zou Q, et al. Quantitative diagnosis of fatty liver with dual-energy CT. An experimental study in rabbits [J]. Acta Radiol, 2003, 44(1): 92-97.
|
| 33 |
Guo Z, Blake GM, Li K, et al. Liver Fat Content Measurement with Quantitative CT Validated against MRI Proton Density Fat Fraction: A Prospective Study of 400 Healthy Volunteers [J]. Radiology, 2020, 294(1): 89-97.
|
| 34 |
Wang Q, Shi G, Qi X, et al. Quantitative analysis of the dual-energy CT virtual spectral curve for focal liver lesions characterization [J]. Eur J Radiol, 2014, 83(10): 1759-1764.
|
| 35 |
Ascenti G, Sofia C, Mazziotti S, et al. Dual-energy CT with iodine quantification in distinguishing between bland and neoplastic portal vein thrombosis in patients with hepatocellular carcinoma [J]. Clin Radiol, 2016, 71(9): 938. e1-e9.
|
| 36 |
Dai X, Schlemmer HP, Schmidt B, et al. Quantitative therapy response assessment by volumetric iodine-uptake measurement: initial experience in patients with advanced hepatocellular carcinoma treated with sorafenib [J]. Eur J Radiol, 2013, 82(2): 327-334.
|
| 37 |
Altenbernd J, Heusner TA, Ringelstein A, et al. Dual-energy-CT of hypervascular liver lesions in patients with HCC: investigation of image quality and sensitivity [J]. Eur Radiol, 2011, 21(4): 738-743.
|
| 38 |
Lee JA, Jeong WK, Kim Y, et al. Dual-energy CT to detect recurrent HCC after TACE: initial experience of color-coded iodine CT imaging [J]. Eur J Radiol, 2013, 82(4): 569-576.
|
| 39 |
Lee SH, Lee JM, Kim KW, et al. Dual-energy computed tomography to assess tumor response to hepatic radiofrequency ablation: potential diagnostic value of virtual noncontrast images and iodine maps [J]. Invest Radiol, 2011, 46(2): 77-84.
|
| 40 |
Greffier J, Frandon J, Hamard A, et al. Impact of iterative reconstructions on image quality and detectability of focal liver lesions in low-energy monochromatic images [J]. Phys Med, 2020, 77: 36-42.
|
| 41 |
Hanson GJ, Michalak GJ, Childs R, et al. Low kV versus dual-energy virtual monoenergetic CT imaging for proven liver lesions: what are the advantages and trade-offs in conspicuity and image quality? A pilot study [J]. Abdom Radiol (NY), 2018, 43(6): 1404-1412.
|
| 42 |
Hur S, Lee JM, Kim SJ, et al. 80-kVp CT using Iterative Reconstruction in Image Space algorithm for the detection of hypervascular hepatocellular carcinoma: phantom and initial clinical experience [J]. Korean J Radiol, 2012, 13(2): 152-164.
|
| 43 |
Javadi S, Elsherif S, Bhosale P, et al. Quantitative attenuation accuracy of virtual non-enhanced imaging compared to that of true non-enhanced imaging on dual-source dual-energy CT [J]. Abdom Radiol (NY), 2020, 45(4): 1100-1109.
|
| 44 |
Kaltenbach B, Wichmann JL, Pfeifer S, et al. Iodine quantification to distinguish hepatic neuroendocrine tumor metastasis from hepatocellular carcinoma at dual-source dual-energy liver CT [J]. Eur J Radiol, 2018, 105: 20-24.
|
| 45 |
Kim JE, Kim HO, Bae K, et al. Differentiation of small intrahepatic mass-forming cholangiocarcinoma from small liver abscess by dual source dual-energy CT quantitative parameters [J]. Eur J Radiol, 2017, 92: 45-52.
|
| 46 |
Kim TM, Lee JM, Yoon JH, et al. Prediction of microvascular invasion of hepatocellular carcinoma: value of volumetric iodine quantification using preoperative dual-energy computed tomography [J]. Cancer Imaging, 2020, 20(1): 60.
|