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DOI: 10.1055/a-1212-6017
Dual-Energy Computed Tomography for Fat Quantification in the Liver and Bone Marrow: A Literature Review
Article in several languages: English | deutschAbstract
Background With dual-energy computed tomography (DECT) it is possible to quantify certain elements and tissues by their specific attenuation, which is dependent on the X-ray spectrum. This systematic review provides an overview of the suitability of DECT for fat quantification in clinical diagnostics compared to established methods, such as histology, magnetic resonance imaging (MRI) and single-energy computed tomography (SECT).
Method Following a systematic literature search, studies which validated DECT fat quantification by other modalities were included. The methodological heterogeneity of all included studies was processed. The study results are presented and discussed according to the target organ and specifically for each modality of comparison.
Results Heterogeneity of the study methodology was high. The DECT data was generated by sequential CT scans, fast-kVp-switching DECT, or dual-source DECT. All included studies focused on the suitability of DECT for the diagnosis of hepatic steatosis and for the determination of the bone marrow fat percentage and the influence of bone marrow fat on the measurement of bone mineral density. Fat quantification in the liver and bone marrow by DECT showed valid results compared to histology, MRI chemical shift relaxometry, magnetic resonance spectroscopy, and SECT. For determination of hepatic steatosis in contrast-enhanced CT images, DECT was clearly superior to SECT. The measurement of bone marrow fat percentage via DECT enabled the bone mineral density quantification more reliably.
Conclusion DECT is an overall valid method for fat quantification in the liver and bone marrow. In contrast to SECT, it is especially advantageous to diagnose hepatic steatosis in contrast-enhanced CT examinations. In the bone marrow DECT fat quantification allows more valid quantification of bone mineral density than conventional methods. Complementary studies concerning DECT fat quantification by split-filter DECT or dual-layer spectral CT and further studies on other organ systems should be conducted.
Key points:
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DECT fat quantification in the liver and bone marrow is reliable.
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DECT is clearly superior to SECT in contrast-enhanced CT images.
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DECT bone marrow fat quantification enables better bone mineral density determination.
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Complementary studies with split-filter DECT or dual-layer spectral CT as well as studies in other organ systems are recommended.
Citation Format
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Molwitz I, Leiderer M, Özden C et al. Dual-Energy Computed Tomography for Fat Quantification in the Liver and Bone Marrow: A Literature Review. Fortschr Röntgenstr 2020; 192: 1137 – 1152
Key words
CT-quantitative - bone marrow - bone densitometry - dual-energy CT - fat quantification - hepatic steatosisPublication History
Received: 10 April 2020
Accepted: 11 June 2020
Article published online:
10 September 2020
© 2020. Thieme. All rights reserved.
Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany
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References
- 1 Anstee QM, Reeves HL, Kotsiliti E. et al From NASH to HCC: current concepts and future challenges. Nat Rev Gastroenterol Hepatol 2019; 16: 411-428 . doi:10.1038/s41575-019-0145-7
- 2 Wehrli FW, Hopkins JA, Hwang SN. et al Cross-sectional study of osteopenia with quantitative MR imaging and bone densitometry. Radiology 2000; 217: 527-538 . doi:10.1148/radiology.217.2.r00nv20527
- 3 Bolotin HH. DXA in vivo BMD methodology: an erroneous and misleading research and clinical gauge of bone mineral status, bone fragility, and bone remodelling. Bone 2007; 41: 138-154 . doi:10.1016/j.bone.2007.02.022
- 4 Ju Y, Liu A, Dong Y. et al The Value of Nonenhanced Single-Source Dual-Energy CT for Differentiating Metastases From Adenoma in Adrenal Glands. Academic radiology 2015; 22: 834-839 . doi:10.1016/j.acra.2015.03.004
- 5 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. Am J Roentgenol American journal of roentgenology 2017; 208: 92-100 . doi:10.2214/ajr.16.16565
- 6 Ferraioli G, Soares Monteiro LB. Ultrasound-based techniques for the diagnosis of liver steatosis. World J Gastroenterol 2019; 25: 6053-6062 . doi:10.3748/wjg.v25.i40.6053
- 7 Li Q, Dhyani M, Grajo JR. et al Current status of imaging in nonalcoholic fatty liver disease. World J Hepatol 2018; 10: 530-542 . doi:10.4254/wjh.v10.i8.530
- 8 Hounsfield GN. Computerized transverse axial scanning (tomography). 1. Description of system. The British journal of radiology 1973; 46: 1016-1022 . doi:10.1259/0007-1285-46-552-1016
- 9 Marshall Jr WH, Easter W, Zatz LM. Analysis of the dense lesion at computed tomography with dual kVp scans. Radiology 1977; 124: 87-89 . doi:10.1148/124.1.87
- 10 Johnson TR, Krauss B, Sedlmair M. et al Material differentiation by dual energy CT: initial experience. European radiology 2007; 17: 1510-1517 . doi:10.1007/s00330-006-0517-6
- 11 Johnson TR. Dual-energy CT: general principles. Am J Roentgenol American journal of roentgenology 2012; 199: S3-S8
- 12 Flohr TG, McCollough CH, Bruder H. et al First performance evaluation of a dual-source CT (DSCT) system. European radiology 2006; 16: 256-268 . doi:10.1007/s00330-005-2919-2
- 13 Rutt B, Fenster A. Split-filter computed tomography: a simple technique for dual energy scanning. Journal of computer assisted tomography 1980; 4: 501-509 . doi:10.1097/00004728-198008000-00019
- 14 Euler A, Parakh A, Falkowski AL. et al Initial Results of a Single-Source Dual-Energy Computed Tomography Technique Using a Split-Filter: Assessment of Image Quality, Radiation Dose, and Accuracy of Dual-Energy Applications in an In Vitro and In Vivo Study. Investigative radiology 2016; 51: 491-498 . doi:10.1097/RLI.0000000000000257
- 15 Rassouli N, Etesami M, Dhanantwari A. et al Detector-based spectral CT with a novel dual-layer technology: principles and applications. Insights Imaging 2017; 8: 589-598 . doi:10.1007/s13244-017-0571-4
- 16 Zhang YN, Fowler KJ, Hamilton G. et al Liver fat imaging-a clinical overview of ultrasound, CT, and MR imaging. The British journal of radiology 2018; 91: 20170959 . doi:10.1259/bjr.20170959
- 17 Singhal V, Bredella MA. Marrow adipose tissue imaging in humans. Bone 2019; 118: 69-76 . doi:10.1016/j.bone.2018.01.009
- 18 Yang CB, Zhang S, Jia YJ. et al Clinical Application of Dual-Energy Spectral Computed Tomography in Detecting Cholesterol Gallstones From Surrounding Bile. Academic radiology 2017; 24: 478-482 . doi:10.1016/j.acra.2016.10.006
- 19 Zachrisson H, Engstrom E, Engvall J. et al Soft tissue discrimination ex vivo by dual energy computed tomography. European journal of radiology 2010; 75: e124-e128 . doi:10.1016/j.ejrad.2010.02.001
- 20 Ohta Y, Kitao S, Watanabe T. et al Evaluation of image quality of coronary artery plaque with rapid kVp-switching dual-energy CT. Clinical imaging 2017; 43: 42-49 . doi:10.1016/j.clinimag.2017.01.014
- 21 Tang CX, Zhou CS, Zhao YE. et al Detection of pulmonary fat embolism with dual-energy CT: an experimental study in rabbits. European radiology 2017; 27: 1377-1385 . doi:10.1007/s00330-016-4512-2
- 22 Mendler MH, Bouillet P, Le Sidaner A. et al Dual-energy CT in the diagnosis and quantification of fatty liver: limited clinical value in comparison to ultrasound scan and single-energy CT, with special reference to iron overload. J Hepatol 1998; 28: 785-794 . doi:10.1016/s0168-8278(98)80228-6
- 23 Wang B, Gao Z, Zou Q. et al Quantitative diagnosis of fatty liver with dual-energy CT. An experimental study in rabbits. Acta radiologica (Stockholm, Sweden : 1987) 2003; 44: 92-97
- 24 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. Investigative radiology 2012; 47: 603-610 . doi:10.1097/RLI.0b013e318261fad0
- 25 Sun T, Lin X, Chen K. Evaluation of hepatic steatosis using dual-energy CT with MR comparison. Frontiers in bioscience (Landmark edition) 2014; 19: 1377-1385
- 26 Ma J, Song ZQ, Yan FH. Separation of hepatic iron and fat by dual-source dual-energy computed tomography based on material decomposition: an animal study. PLoS One 2014; 9: e110964 . doi:10.1371/journal.pone.0110964
- 27 Hur BY, Lee JM, Hyunsik W. et al Quantification of the fat fraction in the liver using dual-energy computed tomography and multimaterial decomposition. Journal of computer assisted tomography 2014; 38: 845-852 . doi:10.1097/RCT.0000000000000142
- 28 Noh H, Song X, Heo SH. et al. Comparative Study of Ultrasonography, Computed Tomography, Magnetic Resonance Imaging, and Magnetic Resonance Spectroscopy for the Diagnosis of Fatty Liver in a Rat Model. J Korean Soc Radiol 2017; 76: 14-24
- 29 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. Radiology 2017; 283: 108-118 . doi:10.1148/radiol.2017160130
- 30 Cao Q, Shang S, Han X. et al Evaluation on Heterogeneity of Fatty Liver in Rats: A Multiparameter Quantitative Analysis by Dual Energy CT. Academic radiology 2019; 26: e47-e55 . doi:10.1016/j.acra.2018.05.013
- 31 Zheng X, Ren Y, Philips WT. et al. Assessment of hepatic fatty infiltration using spectral computed tomography imaging: a pilot study. J Comput Assist Tomogr 2013; 37: 134-141
- 32 Mendonca PR, Lamb P, Kriston A. et al. Contrast-independent liver-fat quantification from spectral CT exams. Med Image Comput Comput Assist Interv 2013; 16: 324-331
- 33 Mendonca PR, Lamb P, Sahani DV. A Flexible Method for Multi-Material Decomposition of Dual-Energy CT Images. IEEE transactions on medical imaging 2014; 33: 99-116 . doi:10.1109/tmi.2013.2281719
- 34 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. Journal of computer assisted tomography 2013; 37: 904-910 . doi:10.1097/RCT.0000000000000027
- 35 Brunt EM, Janney CG, Di Bisceglie AM. et al Nonalcoholic steatohepatitis: a proposal for grading and staging the histological lesions. Am J Gastroenterol 1999; 94: 2467-2474 . doi:10.1111/j.1572-0241.1999.01377.x
- 36 Hui SK, Arentsen L, Sueblinvong T. et al A phase I feasibility study of multi-modality imaging assessing rapid expansion of marrow fat and decreased bone mineral density in cancer patients. Bone 2015; 73: 90-97 . doi:10.1016/j.bone.2014.12.014
- 37 Arentsen L, Yagi M, Takahashi Y. et al Validation of marrow fat assessment using noninvasive imaging with histologic examination of human bone samples. Bone 2015; 72: 118-122 . doi:10.1016/j.bone.2014.11.002
- 38 Magome T, Froelich J, Takahashi Y. et al Evaluation of Functional Marrow Irradiation Based on Skeletal Marrow Composition Obtained Using Dual-Energy Computed Tomography. Int J Radiat Oncol Biol Phys 2016; 96: 679-687 . doi:10.1016/j.ijrobp.2016.06.2459
- 39 Arentsen L, Hansen KE, Yagi M. et al. Use of dual-energy computed tomography to measure skeletal-wide marrow composition and cancellous bone mineral density. J Bone Miner Metab 2017; 35: 428-436
- 40 Bredella MA, Daley SM, Kalra MK. et al Marrow Adipose Tissue Quantification of the Lumbar Spine by Using Dual-Energy CT and Single-Voxel (1)H MR Spectroscopy: A Feasibility Study. Radiology 2015; 277: 230-235 . doi:10.1148/radiol.2015142876
- 41 Perumpail BJ, Khan MA, Yoo ER. et al Clinical epidemiology and disease burden of nonalcoholic fatty liver disease. World J Gastroenterol 2017; 23: 8263-8276 . doi:10.3748/wjg.v23.i47.8263
- 42 Hyodo T, Hori M, Lamb P. et al Multimaterial Decomposition Algorithm for the Quantification of Liver Fat Content by Using Fast-Kilovolt-Peak Switching Dual-Energy CT: Experimental Validation. Radiology 2017; 282: 381-389 . doi:10.1148/radiol.2016160129
- 43 Fischer MA, Gnannt R, Raptis D. et al Quantification of liver fat in the presence of iron and iodine: an ex-vivo dual-energy CT study. Investigative radiology 2011; 46: 351-358 . doi:10.1097/RLI.0b013e31820e1486
- 44 Xie T, Li Y, He G. et al The influence of liver fat deposition on the quantification of the liver-iron fraction using fast-kilovolt-peak switching dual-energy CT imaging and material decomposition technique: an in vitro experimental study. Quantitative imaging in medicine and surgery 2019; 9: 654-661 . doi:10.21037/qims.2019.04.06
- 45 Fischer MA, Reiner CS, Raptis D. et al Quantification of liver iron content with CT-added value of dual-energy. European radiology 2011; 21: 1727-1732 . doi:10.1007/s00330-011-2119-1
- 46 Oelckers S, Graeff W. In situ measurement of iron overload in liver tissue by dual-energy methods. Physics in medicine and biology 1996; 41: 1149-1165 . doi:10.1088/0031-9155/41/7/006
- 47 Poltronieri TS, de Paula NS, Chaves GV. Assessing skeletal muscle radiodensity by computed tomography: An integrative review of the applied methodologies. Clin Physiol Funct Imaging 2020; DOI: 10.1111/cpf.12629.
- 48 Cruz-Jentoft AJ, Bahat G, Bauer J. et al Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing 2019; 48: 16-31 . doi:10.1093/ageing/afy169