Skip to main content

Advertisement

Log in

Quantitative dual-energy CT techniques in the abdomen

  • Special Section: Quantitative Imaging
  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

Advances in dual-energy CT (DECT) technology and spectral techniques are catalyzing the widespread implementation of this technology across multiple radiology subspecialties. The inclusion of energy- and material-specific datasets has ushered overall improvements in CT image contrast and noise as well as artifacts reduction, leading to considerable progress in radiologists’ ability to detect and characterize pathologies in the abdomen. The scope of this article is to provide an overview of various quantitative clinical DECT applications in the abdomen and pelvis. Several of the reviewed applications have not reached mainstream clinical use and are considered investigational. Nonetheless awareness of such applications is critical to having a fully comprehensive knowledge base to DECT and fostering future clinical implementation.

Graphic abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. McCollough CH, Leng S, Yu L, Fletcher JG (2015) Dual- and Multi-Energy CT: Principles, Technical Approaches, and Clinical Applications. Radiology 276:637-653

    Article  PubMed  Google Scholar 

  2. Murray N, Darras KE, Walstra FE, Mohammed MF, McLaughlin PD, Nicolaou S (2019) Dual-Energy CT in Evaluation of the Acute Abdomen. Radiographics 39:264-286

    Article  PubMed  Google Scholar 

  3. Mileto A, Marin D, Ramirez-Giraldo JC et al (2014) Accuracy of contrast-enhanced dual-energy MDCT for the assessment of iodine uptake in renal lesions. AJR Am J Roentgenol 202:W466-474

    Article  PubMed  Google Scholar 

  4. De Kock I, Delrue L, Lecluyse C, Hindryckx P, De Vos M, Villeirs G (2019) Feasibility study using iodine quantification on dual-energy CT enterography to distinguish normal small bowel from active inflammatory Crohn's disease. Acta Radiol 60:679-686

    Article  PubMed  Google Scholar 

  5. Toia GV, Kim S, Dighe MK, Mileto A (2018) Dual-Energy Computed Tomography in Body Imaging. Semin Roentgenol 53:132-146

    Article  PubMed  Google Scholar 

  6. Mileto A, Allen BC, Pietryga JA et al (2017) Characterization of Incidental Renal Mass With Dual-Energy CT: Diagnostic Accuracy of Effective Atomic Number Maps for Discriminating Nonenhancing Cysts From Enhancing Masses. AJR Am J Roentgenol. https://doi.org/10.2214/AJR.16.17325:1-10

    Article  PubMed  Google Scholar 

  7. Marin D, Boll DT, Mileto A, Nelson RC (2014) State of the art: dual-energy CT of the abdomen. Radiology 271:327-342

    Article  PubMed  Google Scholar 

  8. Kaza RK, Platt JF, Cohan RH, Caoili EM, Al-Hawary MM, Wasnik A (2012) Dual-energy CT with single- and dual-source scanners: current applications in evaluating the genitourinary tract. Radiographics 32:353-369

    Article  PubMed  Google Scholar 

  9. Runge VM, Marquez H, Andreisek G, Valavanis A, Alkadhi H (2015) Recent technological advances in computed tomography and the clinical impact therein. Invest Radiol 50:119-127

    Article  PubMed  Google Scholar 

  10. Rubin GD (2014) Computed tomography: revolutionizing the practice of medicine for 40 years. Radiology 273:S45-74

    Article  PubMed  Google Scholar 

  11. Flohr TG, McCollough CH, Bruder H et al (2006) First performance evaluation of a dual-source CT (DSCT) system. Eur Radiol 16:256-268

    Article  PubMed  Google Scholar 

  12. McCollough CH, Primak AN, Saba O et al (2007) Dose performance of a 64-channel dual-source CT scanner. Radiology 243:775-784

    Article  PubMed  Google Scholar 

  13. Im AL, Lee YH, Bang DH, Yoon KH, Park SH (2013) Dual energy CT in patients with acute abdomen; is it possible for virtual non-enhanced images to replace true non-enhanced images? Emerg Radiol 20:475-483

    Article  PubMed  Google Scholar 

  14. Ascenti G, Mileto A, Gaeta M, Blandino A, Mazziotti S, Scribano E (2013) Single-phase dual-energy CT urography in the evaluation of haematuria. Clin Radiol 68:e87-94

    Article  CAS  PubMed  Google Scholar 

  15. Fornaro J, Leschka S, Hibbeln D et al (2011) Dual- and multi-energy CT: approach to functional imaging. Insights Imaging 2:149-159

    Article  PubMed  PubMed Central  Google Scholar 

  16. Sodickson AD, Keraliya A, Czakowski B, Primak A, Wortman J, Uyeda JW (2020) Dual energy CT in clinical routine: how it works and how it adds value. Emerg Radiol. https://doi.org/10.1007/s10140-020-01785-2

    Article  PubMed  Google Scholar 

  17. Goo HW, Goo JM (2017) Dual-Energy CT: New Horizon in Medical Imaging. Korean J Radiol 18:555-569

    Article  PubMed  PubMed Central  Google Scholar 

  18. Durieux P, Gevenois PA, Muylem AV, Howarth N, Keyzer C (2018) Abdominal Attenuation Values on Virtual and True Unenhanced Images Obtained With Third-Generation Dual-Source Dual-Energy CT. AJR Am J Roentgenol 210:1042-1058

    Article  PubMed  Google Scholar 

  19. Lennartz S, Parakh A, Cao J, Kambadakone A (2021) Longitudinal reproducibility of attenuation measurements on virtual unenhanced images: multivendor dual-energy CT evaluation. Eur Radiol. https://doi.org/10.1007/s00330-021-08083-6

    Article  PubMed  PubMed Central  Google Scholar 

  20. Lee HA, Lee YH, Yoon KH, Bang DH, Park DE (2016) Comparison of Virtual Unenhanced Images Derived From Dual-Energy CT With True Unenhanced Images in Evaluation of Gallstone Disease. AJR Am J Roentgenol 206:74-80

    Article  PubMed  Google Scholar 

  21. Glazer DI, Maturen KE, Kaza RK et al (2014) Adrenal Incidentaloma triage with single-source (fast-kilovoltage switch) dual-energy CT. AJR Am J Roentgenol 203:329-335

    Article  PubMed  PubMed Central  Google Scholar 

  22. Wong WD, Mohammed MF, Nicolaou S et al (2020) Impact of Dual-Energy CT in the Emergency Department: Increased Radiologist Confidence, Reduced Need for Follow-Up Imaging, and Projected Cost Benefit. AJR Am J Roentgenol 215:1528-1538

    Article  PubMed  Google Scholar 

  23. Grajo JR, Sahani DV (2018) Dual-Energy CT of the Abdomen and Pelvis: Radiation Dose Considerations. J Am Coll Radiol 15:1128-1132

    Article  PubMed  Google Scholar 

  24. Patel BN, Boltyenkov AT, Martinez MG et al (2020) Cost-effectiveness of dual-energy CT versus multiphasic single-energy CT and MRI for characterization of incidental indeterminate renal lesions. Abdom Radiol (NY) 45:1896-1906

    Article  Google Scholar 

  25. Nishino M (2018) Tumor Response Assessment for Precision Cancer Therapy: Response Evaluation Criteria in Solid Tumors and Beyond. Am Soc Clin Oncol Educ Book 38:1019-1029

    Article  PubMed  Google Scholar 

  26. Schramm N, Schlemmer M, Englhart E et al (2011) Dual energy CT for monitoring targeted therapies in patients with advanced gastrointestinal stromal tumor: initial results. Curr Pharm Biotechnol 12:547-557

    Article  CAS  PubMed  Google Scholar 

  27. Uhrig M, Sedlmair M, Schlemmer HP, Hassel JC, Ganten M (2013) Monitoring targeted therapy using dual-energy CT: semi-automatic RECIST plus supplementary functional information by quantifying iodine uptake of melanoma metastases. Cancer Imaging 13:306-313

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Chen LF, Fu GZ, Huang DP et al (2019) [Value of dual-energy CT-based volumetric iodine-uptake in the evaluation of chemotherapy efficacy in advanced gastric cancer]. Zhonghua Wei Chang Wai Ke Za Zhi 22:977-983

    CAS  PubMed  Google Scholar 

  29. Starekova J, Reeder SB (2020) Liver fat quantification: where do we stand? Abdom Radiol (NY) 45:3386-3399

    Article  Google Scholar 

  30. Lurie Y, Webb M, Cytter-Kuint R, Shteingart S, Lederkremer GZ (2015) Non-invasive diagnosis of liver fibrosis and cirrhosis. World J Gastroenterol 21:11567-11583

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Hur BY, Lee JM, Hyunsik W et al (2014) Quantification of the fat fraction in the liver using dual-energy computed tomography and multimaterial decomposition. J Comput Assist Tomogr 38:845-852

    Article  PubMed  Google Scholar 

  32. Kodama Y, Ng CS, Wu TT et al (2007) Comparison of CT methods for determining the fat content of the liver. AJR Am J Roentgenol 188:1307-1312

    Article  PubMed  Google Scholar 

  33. Molwitz I, Leiderer M, Ozden C, Yamamura J (2020) Dual-Energy Computed Tomography for Fat Quantification in the Liver and Bone Marrow: A Literature Review. Rofo 192:1137-1153

    Article  PubMed  Google Scholar 

  34. Hyodo T, Yada N, Hori M et al (2017) Multimaterial Decomposition Algorithm for the Quantification of Liver Fat Content by Using Fast-Kilovolt-Peak Switching Dual-Energy CT: Clinical Evaluation. Radiology. https://doi.org/10.1148/radiol.2017160130:160130

    Article  PubMed  Google Scholar 

  35. Mileto A, Marin D (2017) Dual-Energy Computed Tomography in Genitourinary Imaging. Radiol Clin North Am 55:373-391

    Article  PubMed  Google Scholar 

  36. Mileto A, Marin D, Nelson RC, Ascenti G, Boll DT (2014) Dual energy MDCT assessment of renal lesions: an overview. Eur Radiol 24:353-362

    Article  PubMed  Google Scholar 

  37. Rigiroli F, Marin D, T. GR (2021) Dual-Energy CT Workflow: PACS Versus Servers. In: Bhosale P, Marin D, Morgan DE, (eds) Practical Dual-Energy CT Throughout the Body: A Busy Radiologist’s Primer. ARRS, USA, pp 20-23

    Google Scholar 

  38. Tamm EP, Le O, Liu X, Layman RR, Cody DD, Bhosale PR (2017) "How to" incorporate dual-energy imaging into a high volume abdominal imaging practice. Abdom Radiol (NY) 42:688-701

    Article  Google Scholar 

  39. Johnson TR, Krauss B, Sedlmair M et al (2007) Material differentiation by dual energy CT: initial experience. Eur Radiol 17:1510-1517

    Article  PubMed  Google Scholar 

  40. Karçaaltıncaba M, Aktaş A (2011) Dual-energy CT revisited with multidetector CT: review of principles and clinical applications. Diagn Interv Radiol 17:181-194

    PubMed  Google Scholar 

  41. Firsching M, Nachtrab F, Uhlmann N, Hanke R (2011) Multi-energy X-ray imaging as a quantitative method for materials characterization. Adv Mater 23:2655-2656

    Article  CAS  PubMed  Google Scholar 

  42. Agostini A, Borgheresi A, Mari A et al (2019) Dual-energy CT: theoretical principles and clinical applications. Radiol Med 124:1281-1295

    Article  PubMed  Google Scholar 

  43. Ascenti G, Mileto A, Krauss B et al (2013) Distinguishing enhancing from nonenhancing renal masses with dual-source dual-energy CT: iodine quantification versus standard enhancement measurements. Eur Radiol 23:2288-2295

    Article  PubMed  Google Scholar 

  44. Graser A, Johnson TR, Hecht EM et al (2009) Dual-energy CT in patients suspected of having renal masses: can virtual nonenhanced images replace true nonenhanced images? Radiology 252:433-440

    Article  PubMed  Google Scholar 

  45. Sun H, Hou XY, Xue HD et al (2015) Dual-source dual-energy CT angiography with virtual non-enhanced images and iodine map for active gastrointestinal bleeding: image quality, radiation dose and diagnostic performance. Eur J Radiol 84:884-891

    Article  PubMed  Google Scholar 

  46. Feuerlein S, Heye TJ, Bashir MR, Boll DT (2012) Iodine quantification using dual-energy multidetector computed tomography imaging: phantom study assessing the impact of iterative reconstruction schemes and patient habitus on accuracy. Invest Radiol 47:656-661

    Article  PubMed  Google Scholar 

  47. Mileto A, Nelson RC, Samei E et al (2014) Impact of dual-energy multi-detector row CT with virtual monochromatic imaging on renal cyst pseudoenhancement: in vitro and in vivo study. Radiology 272:767-776

    Article  PubMed  Google Scholar 

  48. Lestra T, Mulé S, Millet I, Carsin-Vu A, Taourel P, Hoeffel C (2016) Applications of dual energy computed tomography in abdominal imaging. Diagn Interv Imaging 97:593-603

    Article  CAS  PubMed  Google Scholar 

  49. Yang CB, Zhang S, Jia YJ et al (2016) Clinical Application of Dual-Energy Spectral Computed Tomography in Detecting Cholesterol Gallstones From Surrounding Bile. Acad Radiol. https://doi.org/10.1016/j.acra.2016.10.006

    Article  PubMed  PubMed Central  Google Scholar 

  50. Mileto A, Ananthakrishnan L, Morgan DE, Yeh BM, Marin D, Kambadakone AR (2020) Clinical Implementation of Dual-Energy CT for Gastrointestinal Imaging. AJR Am J Roentgenol. https://doi.org/10.2214/AJR.20.25093

    Article  PubMed  Google Scholar 

  51. Yu L, Christner JA, Leng S, Wang J, Fletcher JG, McCollough CH (2011) Virtual monochromatic imaging in dual-source dual-energy CT: radiation dose and image quality. Med Phys 38:6371-6379

    Article  PubMed  PubMed Central  Google Scholar 

  52. Yu L, Leng S, McCollough CH (2012) Dual-energy CT-based monochromatic imaging. AJR Am J Roentgenol 199:S9-S15

    Article  PubMed  Google Scholar 

  53. D'Angelo T, Cicero G, Mazziotti S et al (2019) Dual energy computed tomography virtual monoenergetic imaging: technique and clinical applications. Br J Radiol 92:20180546

    Article  PubMed  PubMed Central  Google Scholar 

  54. Leng S, Yu L, Fletcher JG, McCollough CH (2015) Maximizing Iodine Contrast-to-Noise Ratios in Abdominal CT Imaging through Use of Energy Domain Noise Reduction and Virtual Monoenergetic Dual-Energy CT. Radiology 276:562-570

    Article  PubMed  Google Scholar 

  55. Albrecht MH, Vogl TJ, Martin SS et al (2019) Review of Clinical Applications for Virtual Monoenergetic Dual-Energy CT. Radiology 293:260-271

    Article  PubMed  Google Scholar 

  56. Albrecht MH, Scholtz JE, Hüsers K et al (2016) Advanced image-based virtual monoenergetic dual-energy CT angiography of the abdomen: optimization of kiloelectron volt settings to improve image contrast. Eur Radiol 26:1863-1870

    Article  PubMed  Google Scholar 

  57. Apfaltrer P, Sudarski S, Schneider D et al (2014) Value of monoenergetic low-kV dual energy CT datasets for improved image quality of CT pulmonary angiography. Eur J Radiol 83:322-328

    Article  PubMed  Google Scholar 

  58. Meier A, Wurnig M, Desbiolles L, Leschka S, Frauenfelder T, Alkadhi H (2015) Advanced virtual monoenergetic images: improving the contrast of dual-energy CT pulmonary angiography. Clin Radiol 70:1244-1251

    Article  CAS  PubMed  Google Scholar 

  59. Marin D, Ramirez-Giraldo JC, Gupta S et al (2016) Effect of a Noise-Optimized Second-Generation Monoenergetic Algorithm on Image Noise and Conspicuity of Hypervascular Liver Tumors: An In Vitro and In Vivo Study. AJR Am J Roentgenol 206:1222-1232

    Article  PubMed  Google Scholar 

  60. Dam-Larsen S, Franzmann M, Andersen IB et al (2004) Long term prognosis of fatty liver: risk of chronic liver disease and death. Gut 53:750-755

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Kramer H, Pickhardt PJ, Kliewer MA et al (2017) Accuracy of Liver Fat Quantification With Advanced CT, MRI, and Ultrasound Techniques: Prospective Comparison With MR Spectroscopy. AJR Am J Roentgenol 208:92-100

    Article  PubMed  Google Scholar 

  62. Gakis G, Kramer U, Schilling D, Kruck S, Stenzl A, Schlemmer HP (2011) Small renal oncocytomas: differentiation with multiphase CT. Eur J Radiol 80:274-278

    Article  PubMed  Google Scholar 

  63. Pickhardt PJ, Blake GM, Graffy PM et al (2020) Liver Steatosis Categorization on Contrast-Enhanced CT Using a Fully-Automated Deep Learning Volumetric Segmentation Tool: Evaluation in 1,204 Heathy Adults Using Unenhanced CT as Reference Standard. AJR Am J Roentgenol. https://doi.org/10.2214/AJR.20.24415

    Article  PubMed  Google Scholar 

  64. Elbanna KY, Mansoori B, Mileto A, Rogalla P, L SG (2020) Dual-energy CT in diffuse liver disease: is there a role? Abdom Radiol (NY) 45:3413-3424

    Article  Google Scholar 

  65. Zhang YN, Fowler KJ, Hamilton G et al (2018) Liver fat imaging-a clinical overview of ultrasound, CT, and MR imaging. Br J Radiol 91:20170959

    Article  PubMed  PubMed Central  Google Scholar 

  66. Mandler AG, Borhani AA (2021) Dual-Energy CT: Implications in Liver Imaging. In: Bhosale PR, Marin D, Morgan DE, (eds) Practical Dual-Energy CT Throughout the Body: A Busy Radiologist’s Primer. ARRS

  67. Guo Z, Blake GM, Li K et al (2020) Liver Fat Content Measurement with Quantitative CT Validated against MRI Proton Density Fat Fraction: A Prospective Study of 400 Healthy Volunteers. Radiology 294:89-97

    Article  PubMed  Google Scholar 

  68. Itaya S, Matsui T, Kamiyama T, Yoshino H (2016) Evaluation of Fat Quantification in the Liver Using Dual Energy CT. Nihon Hoshasen Gijutsu Gakkai Zasshi 72:1084-1090

    Article  PubMed  Google Scholar 

  69. Sofue K, Tsurusaki M, Kawasaki R, Fujii M, Sugimura K (2011) Evaluation of hypervascular hepatocellular carcinoma in cirrhotic liver: comparison of different concentrations of contrast material with multi-detector row helical CT--a prospective randomized study. Eur J Radiol 80:e237-242

    Article  PubMed  Google Scholar 

  70. Parola M, Pinzani M (2019) Liver fibrosis: Pathophysiology, pathogenetic targets and clinical issues. Mol Aspects Med 65:37-55

    Article  CAS  PubMed  Google Scholar 

  71. Chi H, Hansen BE, Tang WY et al (2017) Multiple biopsy passes and the risk of complications of percutaneous liver biopsy. Eur J Gastroenterol Hepatol 29:36-41

    Article  PubMed  Google Scholar 

  72. Nagayama Y, Kato Y, Inoue T et al (2021) Liver fibrosis assessment with multiphasic dual-energy CT: diagnostic performance of iodine uptake parameters. Eur Radiol. https://doi.org/10.1007/s00330-021-07706-2

    Article  PubMed  Google Scholar 

  73. Marri UK, Das P, Shalimar, Kalaivani M, Srivastava DN, Madhusudhan KS (2021) Noninvasive Staging of Liver Fibrosis Using 5-Minute Delayed Dual-Energy CT: Comparison with US Elastography and Correlation with Histologic Findings. Radiology 298:600-608

    Article  PubMed  Google Scholar 

  74. Sofue K, Tsurusaki M, Mileto A et al (2018) Dual-energy computed tomography for non-invasive staging of liver fibrosis: Accuracy of iodine density measurements from contrast-enhanced data. Hepatol Res 48:1008-1019

    Article  PubMed  Google Scholar 

  75. Ito E, Sato K, Yamamoto R, Sakamoto K, Urakawa H, Yoshimitsu K (2020) Usefulness of iodine-blood material density images in estimating degree of liver fibrosis by calculating extracellular volume fraction obtained from routine dual-energy liver CT protocol equilibrium phase data: preliminary experience. Jpn J Radiol 38:365-373

    Article  CAS  PubMed  Google Scholar 

  76. Tsurusaki M, Sofue K, Hori M et al (2021) Dual-Energy Computed Tomography of the Liver: Uses in Clinical Practices and Applications. Diagnostics (Basel) 11

  77. Li Q, Dhyani M, Grajo JR, Sirlin C, Samir AE (2018) Current status of imaging in nonalcoholic fatty liver disease. World J Hepatol 10:530-542

    Article  PubMed  PubMed Central  Google Scholar 

  78. Mehta KJ, Farnaud SJ, Sharp PA (2019) Iron and liver fibrosis: Mechanistic and clinical aspects. World J Gastroenterol 25:521-538

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Wang W, Knovich MA, Coffman LG, Torti FM, Torti SV (2010) Serum ferritin: Past, present and future. Biochim Biophys Acta 1800:760-769

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. d'Assignies G, Paisant A, Bardou-Jacquet E et al (2018) Non-invasive measurement of liver iron concentration using 3-Tesla magnetic resonance imaging: validation against biopsy. Eur Radiol 28:2022-2030

    Article  PubMed  Google Scholar 

  81. Jiang X, Hintenlang DE, White RD (2021) Lower limit of iron quantification using dual-energy CT - a phantom study. J Appl Clin Med Phys 22:299-307

    Article  PubMed  Google Scholar 

  82. Joe E, Kim SH, Lee KB et al (2012) Feasibility and accuracy of dual-source dual-energy CT for noninvasive determination of hepatic iron accumulation. Radiology 262:126-135

    Article  PubMed  Google Scholar 

  83. Fischer MA, Gnannt R, Raptis D et al (2011) Quantification of liver fat in the presence of iron and iodine: an ex-vivo dual-energy CT study. Invest Radiol 46:351-358

    Article  CAS  PubMed  Google Scholar 

  84. Luo XF, Xie XQ, Cheng S et al (2015) Dual-Energy CT for Patients Suspected of Having Liver Iron Overload: Can Virtual Iron Content Imaging Accurately Quantify Liver Iron Content? Radiology 277:95-103

    Article  PubMed  Google Scholar 

  85. Werner S, Krauss B, Haberland U et al (2019) Dual-energy CT for liver iron quantification in patients with haematological disorders. Eur Radiol 29:2868-2877

    Article  PubMed  Google Scholar 

  86. Ma Q, Hu J, Yang W, Hou Y (2020) Dual-layer detector spectral CT versus magnetic resonance imaging for the assessment of iron overload in myelodysplastic syndromes and aplastic anemia. Jpn J Radiol 38:374-381

    Article  CAS  PubMed  Google Scholar 

  87. Ascenti G, Sofia C, Mazziotti S et al (2016) Dual-energy CT with iodine quantification in distinguishing between bland and neoplastic portal vein thrombosis in patients with hepatocellular carcinoma. Clin Radiol 71:938 e931-939

    Google Scholar 

  88. Catalano OA, Choy G, Zhu A, Hahn PF, Sahani DV (2010) Differentiation of malignant thrombus from bland thrombus of the portal vein in patients with hepatocellular carcinoma: application of diffusion-weighted MR imaging. Radiology 254:154-162

    Article  PubMed  Google Scholar 

  89. Piscaglia F, Gianstefani A, Ravaioli M et al (2010) Criteria for diagnosing benign portal vein thrombosis in the assessment of patients with cirrhosis and hepatocellular carcinoma for liver transplantation. Liver Transpl 16:658-667

    Article  PubMed  Google Scholar 

  90. Shah ZK, McKernan MG, Hahn PF, Sahani DV (2007) Enhancing and expansile portal vein thrombosis: value in the diagnosis of hepatocellular carcinoma in patients with multiple hepatic lesions. AJR Am J Roentgenol 188:1320-1323

    Article  PubMed  Google Scholar 

  91. Tajima T, Honda H, Taguchi K et al (2002) Sequential hemodynamic change in hepatocellular carcinoma and dysplastic nodules: CT angiography and pathologic correlation. AJR Am J Roentgenol 178:885-897

    Article  PubMed  Google Scholar 

  92. Raza SA, Jang HJ, Kim TK (2014) Differentiating malignant from benign thrombosis in hepatocellular carcinoma: contrast-enhanced ultrasound. Abdom Imaging 39:153-161

    Article  PubMed  Google Scholar 

  93. Qian LJ, Zhu J, Zhuang ZG et al (2012) Differentiation of neoplastic from bland macroscopic portal vein thrombi using dual-energy spectral CT imaging: a pilot study. Eur Radiol 22:2178-2185

    Article  PubMed  Google Scholar 

  94. Han X, An W, Cao Q, Liu C, Shang S, Zhao L (2020) Noninvasive evaluation of esophageal varices in cirrhotic patients based on spleen hemodynamics: a dual-energy CT study. Eur Radiol 30:3210-3216

    Article  PubMed  Google Scholar 

  95. Winklhofer S, Lin WC, Lambert JW, Yeh BM (2017) Accessory spleen versus lymph node: Value of iodine quantification with dual-energy computed tomography. Eur J Radiol 87:53-58

    Article  PubMed  Google Scholar 

  96. Herts BR, Silverman SG, Hindman NM et al (2018) Management of the Incidental Renal Mass on CT: A White Paper of the ACR Incidental Findings Committee. J Am Coll Radiol 15:264-273

    Article  PubMed  Google Scholar 

  97. Thiravit S, Brunnquell C, Cai LM, Flemon M, Mileto A (2020) Use of dual-energy CT for renal mass assessment. Eur Radiol. https://doi.org/10.1007/s00330-020-07426-z

    Article  PubMed  Google Scholar 

  98. Wortman JR, Shyu JY, Fulwadhva UP, Sodickson AD (2019) Impact Analysis of the Routine Use of Dual-Energy Computed Tomography for Characterization of Incidental Renal Lesions. J Comput Assist Tomogr 43:176-182

    Article  PubMed  Google Scholar 

  99. Obmann MM, Cosentino A, Cyriac J et al (2020) Quantitative enhancement thresholds and machine learning algorithms for the evaluation of renal lesions using single-phase split-filter dual-energy CT. Abdom Radiol (NY) 45:1922-1928

    Article  Google Scholar 

  100. Kaza RK, Raff EA, Davenport MS, Khalatbari S (2017) Variability of CT Attenuation Measurements in Virtual Unenhanced Images Generated Using Multimaterial Decomposition from Fast Kilovoltage-switching Dual-energy CT. Acad Radiol 24:365-372

    Article  PubMed  Google Scholar 

  101. Xiao JM, Hippe DS, Zecevic M et al (2021) Virtual Unenhanced Dual-Energy CT Images Obtained with a Multimaterial Decomposition Algorithm: Diagnostic Value for Renal Mass and Urinary Stone Evaluation. Radiology 298:611-619

    Article  PubMed  Google Scholar 

  102. Meyer M, Nelson RC, Vernuccio F et al (2019) Virtual Unenhanced Images at Dual-Energy CT: Influence on Renal Lesion Characterization. Radiology 291:381-390

    Article  PubMed  Google Scholar 

  103. Patel BN, Vernuccio F, Meyer M et al (2019) Dual-Energy CT Material Density Iodine Quantification for Distinguishing Vascular From Nonvascular Renal Lesions: Normalization Reduces Intermanufacturer Threshold Variability. AJR Am J Roentgenol 212:366-376

    Article  PubMed  Google Scholar 

  104. Sadoughi N, Krishna S, Macdonald DB et al (2019) Diagnostic Accuracy of Attenuation Difference and Iodine Concentration Thresholds at Rapid-Kilovoltage-Switching Dual-Energy CT for Detection of Enhancement in Renal Masses. AJR Am J Roentgenol 213:619-625

    Article  PubMed  Google Scholar 

  105. Chandarana H, Megibow AJ, Cohen BA et al (2011) Iodine quantification with dual-energy CT: phantom study and preliminary experience with renal masses. AJR Am J Roentgenol 196:W693-700

    Article  PubMed  Google Scholar 

  106. Kaza RK, Caoili EM, Cohan RH, Platt JF (2011) Distinguishing enhancing from nonenhancing renal lesions with fast kilovoltage-switching dual-energy CT. AJR Am J Roentgenol 197:1375-1381

    Article  PubMed  Google Scholar 

  107. Rompsaithong U, Jongjitaree K, Korpraphong P et al (2019) Characterization of renal stone composition by using fast kilovoltage switching dual-energy computed tomography compared to laboratory stone analysis: a pilot study. Abdom Radiol (NY) 44:1027-1032

    Article  Google Scholar 

  108. Boll DT, Patil NA, Paulson EK et al (2009) Renal stone assessment with dual-energy multidetector CT and advanced postprocessing techniques: improved characterization of renal stone composition--pilot study. Radiology 250:813-820

    Article  PubMed  Google Scholar 

  109. Mansouri M, Aran S, Singh A et al (2015) Dual-Energy Computed Tomography Characterization of Urinary Calculi: Basic Principles, Applications and Concerns. Curr Probl Diagn Radiol 44:496-500

    Article  PubMed  Google Scholar 

  110. Bovio S, Cataldi A, Reimondo G et al (2006) Prevalence of adrenal incidentaloma in a contemporary computerized tomography series. J Endocrinol Invest 29:298-302

    Article  CAS  PubMed  Google Scholar 

  111. Song JH, Chaudhry FS, Mayo-Smith WW (2008) The incidental adrenal mass on CT: prevalence of adrenal disease in 1,049 consecutive adrenal masses in patients with no known malignancy. AJR Am J Roentgenol 190:1163-1168

    Article  PubMed  Google Scholar 

  112. Corwin MT, Navarro SM, Malik DG et al (2019) Differences in Growth Rate on CT of Adrenal Adenomas and Malignant Adrenal Nodules. AJR Am J Roentgenol 213:632-636

    Article  PubMed  Google Scholar 

  113. Shi JW, Dai HZ, Shen L, Xu DF (2014) Dual-energy CT: clinical application in differentiating an adrenal adenoma from a metastasis. Acta Radiol 55:505-512

    Article  PubMed  Google Scholar 

  114. Korobkin M, Francis IR, Kloos RT, Dunnick NR (1996) The incidental adrenal mass. Radiol Clin North Am 34:1037-1054

    Article  CAS  PubMed  Google Scholar 

  115. Ng CS, Altinmakas E, Wei W et al (2018) Combining Washout and Noncontrast Data From Adrenal Protocol CT: Improving Diagnostic Performance. Acad Radiol 25:861-868

    Article  PubMed  Google Scholar 

  116. Slebocki K, Kraus B, Chang DH, Hellmich M, Maintz D, Bangard C (2017) Incidental Findings in Abdominal Dual-Energy Computed Tomography: Correlation Between True Noncontrast and Virtual Noncontrast Images Considering Renal and Liver Cysts and Adrenal Masses. J Comput Assist Tomogr 41:294-297

    Article  PubMed  Google Scholar 

  117. Ananthakrishnan L, Duan X, Rajiah P et al (2018) Phantom Validation of Spectral Detector Computed Tomography-Derived Virtual Monoenergetic, Virtual Noncontrast, and Iodine Quantification Images. J Comput Assist Tomogr 42:959-964

    Article  PubMed  Google Scholar 

  118. Kim YK, Park BK, Kim CK, Park SY (2013) Adenoma characterization: adrenal protocol with dual-energy CT. Radiology 267:155-163

    Article  PubMed  Google Scholar 

  119. Connolly MJ, McInnes MDF, El-Khodary M, McGrath TA, Schieda N (2017) Diagnostic accuracy of virtual non-contrast enhanced dual-energy CT for diagnosis of adrenal adenoma: A systematic review and meta-analysis. Eur Radiol 27:4324-4335

    Article  PubMed  Google Scholar 

  120. Martin SS, Weidinger S, Czwikla R et al (2018) Iodine and Fat Quantification for Differentiation of Adrenal Gland Adenomas From Metastases Using Third-Generation Dual-Source Dual-Energy Computed Tomography. Invest Radiol 53:173-178

    Article  CAS  PubMed  Google Scholar 

  121. Botsikas D, Triponez F, Boudabbous S, Hansen C, Becker CD, Montet X (2014) Incidental adrenal lesions detected on enhanced abdominal dual-energy CT: can the diagnostic workup be shortened by the implementation of virtual unenhanced images? Eur J Radiol 83:1746-1751

    Article  PubMed  Google Scholar 

  122. Hindman NM, Megibow AJ (2020) One-Stop Shopping: Dual-Energy CT for the Confident Diagnosis of Adrenal Adenomas. Radiology 296:333-334

    Article  PubMed  Google Scholar 

  123. Nagayama Y, Inoue T, Oda S et al (2020) Adrenal Adenomas versus Metastases: Diagnostic Performance of Dual-Energy Spectral CT Virtual Noncontrast Imaging and Iodine Maps. Radiology 296:324-332

    Article  PubMed  Google Scholar 

  124. Eisenhauer EA, Therasse P, Bogaerts J et al (2009) New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer 45:228-247

    Article  CAS  PubMed  Google Scholar 

  125. Apfaltrer P, Meyer M, Meier C et al (2012) Contrast-enhanced dual-energy CT of gastrointestinal stromal tumors: is iodine-related attenuation a potential indicator of tumor response? Invest Radiol 47:65-70

    Article  CAS  PubMed  Google Scholar 

  126. Jiang T, Kambadakone A, Kulkarni NM, Zhu AX, Sahani DV (2012) Monitoring response to antiangiogenic treatment and predicting outcomes in advanced hepatocellular carcinoma using image biomarkers, CT perfusion, tumor density, and tumor size (RECIST). Invest Radiol 47:11-17

    Article  PubMed  Google Scholar 

  127. Zhang LJ, Wu S, Wang M et al (2012) Quantitative dual energy CT measurements in rabbit VX2 liver tumors: Comparison to perfusion CT measurements and histopathological findings. Eur J Radiol 81:1766-1775

    Article  PubMed  Google Scholar 

  128. De Cecco CN, Darnell A, Rengo M et al (2012) Dual-energy CT: oncologic applications. AJR Am J Roentgenol 199:S98-S105

    Article  PubMed  Google Scholar 

  129. Chandarana H, Shanbhogue K (2021) Noninvasive Staging of Liver Fibrosis with Dual-Energy CT: Close but No Cigar. Radiology 298:609-610

    Article  PubMed  Google Scholar 

  130. Almeida IP, Schyns LE, Ollers MC et al (2017) Dual-energy CT quantitative imaging: a comparison study between twin-beam and dual-source CT scanners. Med Phys 44:171-179

    Article  CAS  PubMed  Google Scholar 

  131. Lennartz S, Parakh A, Cao J, Zopfs D, Grosse Hokamp N, Kambadakone A (2021) Inter-scan and inter-scanner variation of quantitative dual-energy CT: evaluation with three different scanner types. Eur Radiol. https://doi.org/10.1007/s00330-020-07611-0

    Article  PubMed  PubMed Central  Google Scholar 

  132. Euler A, Solomon J, Mazurowski MA, Samei E, Nelson RC (2019) How accurate and precise are CT based measurements of iodine concentration? A comparison of the minimum detectable concentration difference among single source and dual source dual energy CT in a phantom study. Eur Radiol 29:2069-2078

    Article  PubMed  Google Scholar 

  133. Schmidt C, Baessler B, Nakhostin D et al (2020) Dual-Energy CT-Based Iodine Quantification in Liver Tumors - Impact of Scan-, Patient-, and Position-Related Factors. Acad Radiol. https://doi.org/10.1016/j.acra.2020.04.021

    Article  PubMed  Google Scholar 

  134. Willemink MJ, Persson M, Pourmorteza A, Pelc NJ, Fleischmann D (2018) Photon-counting CT: Technical Principles and Clinical Prospects. Radiology 289:293-312

    Article  PubMed  Google Scholar 

  135. Thiravit S, Brunnquell C, Cai LM, Flemon M, Mileto A (2020) Building a dual-energy CT service line in abdominal radiology. Eur Radiol. https://doi.org/10.1007/s00330-020-07441-0

    Article  PubMed  Google Scholar 

  136. Leng S, Bruesewitz M, Tao S et al (2019) Photon-counting Detector CT: System Design and Clinical Applications of an Emerging Technology. Radiographics 39:729-743

    Article  PubMed  Google Scholar 

  137. Gronberg F, Lundberg J, Sjolin M et al (2020) Feasibility of unconstrained three-material decomposition: imaging an excised human heart using a prototype silicon photon-counting CT detector. Eur Radiol 30:5904-5912

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  138. van Timmeren JE, Cester D, Tanadini-Lang S, Alkadhi H, Baessler B (2020) Radiomics in medical imaging-"how-to" guide and critical reflection. Insights Imaging 11:91

    Article  PubMed  PubMed Central  Google Scholar 

  139. Mannil M, von Spiczak J, Manka R, Alkadhi H (2018) Texture Analysis and Machine Learning for Detecting Myocardial Infarction in Noncontrast Low-Dose Computed Tomography: Unveiling the Invisible. Invest Radiol 53:338-343

    Article  PubMed  Google Scholar 

  140. Rizzo S, Botta F, Raimondi S et al (2018) Radiomics: the facts and the challenges of image analysis. Eur Radiol Exp 2:36

    Article  PubMed  PubMed Central  Google Scholar 

  141. Zhou Y, Su GY, Hu H et al (2020) Radiomics analysis of dual-energy CT-derived iodine maps for diagnosing metastatic cervical lymph nodes in patients with papillary thyroid cancer. Eur Radiol 30:6251-6262

    Article  CAS  PubMed  Google Scholar 

  142. Li J, Dong D, Fang M et al (2020) Dual-energy CT-based deep learning radiomics can improve lymph node metastasis risk prediction for gastric cancer. Eur Radiol 30:2324-2333

    Article  PubMed  Google Scholar 

  143. Ji GW, Zhu FP, Zhang YD et al (2019) A radiomics approach to predict lymph node metastasis and clinical outcome of intrahepatic cholangiocarcinoma. Eur Radiol 29:3725-3735

    Article  PubMed  Google Scholar 

  144. Liu Y, Dou Y, Lu F, Liu L (2020) A study of radiomics parameters from dual-energy computed tomography images for lymph node metastasis evaluation in colorectal mucinous adenocarcinoma. Medicine (Baltimore) 99:e19251

  145. Homayounieh F, Singh R, Nitiwarangkul C et al (2020) Semiautomatic Segmentation and Radiomics for Dual-Energy CT: A Pilot Study to Differentiate Benign and Malignant Hepatic Lesions. AJR Am J Roentgenol 215:398-405

    Article  PubMed  Google Scholar 

  146. Doda Khera R, Homayounieh F, Lades F et al (2020) Can Dual-Energy Computed Tomography Quantitative Analysis and Radiomics Differentiate Normal Liver From Hepatic Steatosis and Cirrhosis? J Comput Assist Tomogr 44:223-229

    Article  PubMed  Google Scholar 

Download references

Funding

The authors did not receive support from any organization for the submitted work.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Giuseppe V. Toia.

Ethics declarations

Conflict of interest

Dr. Mileto and Dr. Wang have on-going dual-energy CT research grants from GE Healthcare. Drs. Toia and Sahani have no relevant financial or non-financial interests to disclose.

Ethical approval

This is a review article and thus no institutional ethics approval was required.

Code availability

No code was created.

Consent to participate

This is a review article in which no research subjects were needed.

Consent for publication

This is a review article in which no research subjects were needed.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Toia, G.V., Mileto, A., Wang, C.L. et al. Quantitative dual-energy CT techniques in the abdomen. Abdom Radiol 47, 3003–3018 (2022). https://doi.org/10.1007/s00261-021-03266-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00261-021-03266-7

Keywords

Navigation