Diagnostic Accuracy of CT for the Detection of Hepatic Steatosis: A Systematic Review and Meta-Analysis

  • Deputy Editor: Kathryn Fowler
  • Scientific Editor: Shannyn Wolfe
Published Online:https://doi.org/10.1148/radiol.241171

Noncontrast CT was a reliable method for detection of at least moderate hepatic steatosis (over 20%–33% fat at biopsy), with a pooled sensitivity and specificity of 82% and 94%, respectively.

Background

CT plays an important role in the opportunistic identification of hepatic steatosis. CT performance for steatosis detection has been inconsistent across various studies, and no clear guidelines on optimum thresholds have been established.

Purpose

To conduct a systematic review and meta-analysis to assess CT diagnostic accuracy in hepatic steatosis detection and to determine reliable cutoffs for the commonly mentioned measures in the literature.

Materials and Methods

A systematic search of the PubMed, Embase, and Scopus databases (English-language studies published from September 1977 to January 2024) was performed. Studies evaluating the diagnostic accuracy of noncontrast CT (NCCT), contrast-enhanced (CECT), and dual-energy CT (DECT) for hepatic steatosis detection were included. Reference standards included biopsy, MRI proton density fat fraction (PDFF), or NCCT. In several CECT and DECT studies, NCCT was used as the reference standard, necessitating subgroup analysis. Statistical analysis included a random-effects meta-analysis, assessment of heterogeneity with use of the I2 statistic, and meta-regression to explore potential sources of heterogeneity. When available, mean liver attenuation, liver-spleen attenuation difference, liver to spleen attenuation ratio, and the DECT-derived fat fraction for hepatic steatosis diagnosis were assessed.

Results

Forty-two studies (14 186 participants) were included. NCCT had a sensitivity and specificity of 72% and 88%, respectively, for steatosis (>5% fat at biopsy) detection and 82% and 94% for at least moderate steatosis (over 20%–33% fat at biopsy) detection. CECT had a sensitivity and specificity of 66% and 90% for steatosis detection and 68% and 93% for at least moderate steatosis detection. DECT had a sensitivity and specificity of 85% and 88% for steatosis detection. In the subgroup analysis, the sensitivity and specificity for detecting steatosis were 80% and 99% for CECT and 84% and 93% for DECT. There was heterogeneity among studies focusing on CECT and DECT. Liver attenuation less than 40–45 HU, liver-spleen attenuation difference less than −5 to 0 HU, and liver to spleen attenuation ratio less than 0.9–1 achieved high specificity for detection of at least moderate steatosis.

Conclusion

NCCT showed high performance for detection of at least moderate steatosis.

© RSNA, 2024

Supplemental material is available for this article.

References

  • 1. Browning JD, Horton JD. Molecular mediators of hepatic steatosis and liver injury. J Clin Invest 2004;114(2):147–152.
  • 2. Mazhar SM, Shiehmorteza M, Sirlin CB. Noninvasive assessment of hepatic steatosis. Clin Gastroenterol Hepatol 2009;7(2):135–140.
  • 3. Bellentani S, Saccoccio G, Masutti F, et al. Prevalence of and risk factors for hepatic steatosis in Northern Italy. Ann Intern Med 2000;132(2):112–117.
  • 4. Browning JD, Szczepaniak LS, Dobbins R, et al. Prevalence of hepatic steatosis in an urban population in the United States: impact of ethnicity. Hepatology 2004;40(6):1387–1395.
  • 5. Szczepaniak LS, Nurenberg P, Leonard D, et al. Magnetic resonance spectroscopy to measure hepatic triglyceride content: prevalence of hepatic steatosis in the general population. Am J Physiol Endocrinol Metab 2005;288(2):E462–E468.
  • 6. Clark JM. The epidemiology of nonalcoholic fatty liver disease in adults. J Clin Gastroenterol 2006;40(Suppl 1):S5–S10.
  • 7. Murag S, Ahmed A, Kim D. Recent epidemiology of nonalcoholic fatty liver disease. Gut Liver 2021;15(2):206–216.
  • 8. Hashimoto E, Tokushige K. Prevalence, gender, ethnic variations, and prognosis of NASH. J Gastroenterol 2011;46(Suppl 1):63–69.
  • 9. Rinella ME. Nonalcoholic fatty liver disease: a systematic review. JAMA 2015;313(22):2263–2273.
  • 10. Williams CD, Stengel J, Asike MI, et al. Prevalence of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis among a largely middle-aged population utilizing ultrasound and liver biopsy: a prospective study. Gastroenterology 2011;140(1):124–131.
  • 11. Harrison SA, Torgerson S, Hayashi PH. The natural history of nonalcoholic fatty liver disease: a clinical histopathological study. Am J Gastroenterol 2003;98(9):2042–2047.
  • 12. Clark JM, Diehl AM. Nonalcoholic fatty liver disease: an underrecognized cause of cryptogenic cirrhosis. JAMA 2003;289(22):3000–3004.
  • 13. Ascha MS, Hanouneh IA, Lopez R, Tamimi TAR, Feldstein AF, Zein NN. The incidence and risk factors of hepatocellular carcinoma in patients with nonalcoholic steatohepatitis. Hepatology 2010;51(6):1972–1978.
  • 14. Charlton M. Cirrhosis and liver failure in nonalcoholic fatty liver disease: molehill or mountain? Hepatology 2008;47(5):1431–1433.
  • 15. Younossi ZM, Stepanova M, Ong J, et al. Nonalcoholic steatohepatitis is the most rapidly increasing indication for liver transplantation in the United States. Clin Gastroenterol Hepatol 2021;19(3):580–589.e5, e5.
  • 16. Adams LA, Lymp JF, St Sauver J, et al. The natural history of nonalcoholic fatty liver disease: a population-based cohort study. Gastroenterology 2005;129(1):113–121.
  • 17. Levene AP, Goldin RD. The epidemiology, pathogenesis and histopathology of fatty liver disease. Histopathology 2012;61(2):141–152.
  • 18. 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(1):108–118.
  • 19. Idilman IS, Aniktar H, Idilman R, et al. Hepatic steatosis: quantification by proton density fat fraction with MR imaging versus liver biopsy. Radiology 2013;267(3):767–775.
  • 20. Ballestri S, Nascimbeni F, Lugari S, Lonardo A, Francica G. A critical appraisal of the use of ultrasound in hepatic steatosis. Expert Rev Gastroenterol Hepatol 2019;13(7):667–681.
  • 21. Boyce CJ, Pickhardt PJ, Kim DH, et al. Hepatic steatosis (fatty liver disease) in asymptomatic adults identified by unenhanced low-dose CT. AJR Am J Roentgenol 2010;194(3):623–628.
  • 22. Mergo PJ, Ros PR, Buetow PC, Buck JL. Diffuse disease of the liver: radiologic-pathologic correlation. RadioGraphics 1994;14(6):1291–1307.
  • 23. DenOtter TD, Schubert J. Hounsfield unit. 2019. https://www.ncbi.nlm.nih.gov/books/NBK547721/.
  • 24. Bohte AE, van Werven JR, Bipat S, Stoker J. The diagnostic accuracy of US, CT, MRI and 1H-MRS for the evaluation of hepatic steatosis compared with liver biopsy: a meta-analysis. Eur Radiol 2011;21(1):87–97.
  • 25. Tsurusaki M, Sofue K, Hori M, et al. Dual-energy computed tomography of the liver: uses in clinical practices and applications. Diagnostics (Basel) 2021;11(2):161.
  • 26. McGrath TA, Bossuyt PM, Cronin P, et al. Best practices for MRI systematic reviews and meta-analyses. J Magn Reson Imaging 2019;49(7):e51–e64.
  • 27. Leeflang MM, Deeks JJ, Gatsonis C, Bossuyt PM; Cochrane Diagnostic Test Accuracy Working Group. Systematic reviews of diagnostic test accuracy. Ann Intern Med 2008;149(12):889–897.
  • 28. McInnes MD, Bossuyt PM. Pitfalls of systematic reviews and meta-analyses in imaging research. Radiology 2015;277(1):13–21.
  • 29. McGrath TA, Alabousi M, Skidmore B, et al. Recommendations for reporting of systematic reviews and meta-analyses of diagnostic test accuracy: a systematic review. Syst Rev 2017;6(1):194.
  • 30. Stewart LA, Clarke M, Rovers M, et al. Preferred Reporting Items for Systematic Review and Meta-Analyses of individual participant data: the PRISMA-IPD Statement. JAMA 2015;313(16):1657–1665.
  • 31. Salameh JP, Bossuyt PM, McGrath TA, et al. Preferred reporting items for systematic review and meta-analysis of diagnostic test accuracy studies (PRISMA-DTA): explanation, elaboration, and checklist. BMJ 2020;370:m2632.
  • 32. McInnes MDF, Moher D, Thombs BD, et al. Preferred Reporting Items for a Systematic Review and Meta-Analysis of Diagnostic Test Accuracy Studies: the PRISMA-DTA statement. JAMA 2018;319(4):388–396.
  • 33. Brunt EM, Janney CG, Di Bisceglie AM, Neuschwander-Tetri BA, Bacon BR. Nonalcoholic steatohepatitis: a proposal for grading and staging the histological lesions. Am J Gastroenterol 1999;94(9):2467–2474.
  • 34. Jia S, Zhao Y, Liu J, et al. Magnetic resonance imaging-proton density fat fraction vs. transient elastography-controlled attenuation parameter in diagnosing non-alcoholic fatty liver disease in children and adolescents: a meta-analysis of diagnostic accuracy. Front Pediatr 2022;9:784221.
  • 35. Caussy C, Reeder SB, Sirlin CB, Loomba R. Noninvasive, quantitative assessment of liver fat by MRI‐PDFF as an endpoint in NASH trials. Hepatology 2018;68(2):763–772.
  • 36. Choi Y, Kim DK, Youn SY, Kim H, Choi JI. Unenhanced computed tomography for non-invasive diagnosis of hepatic steatosis with low tube potential protocol. Quant Imaging Med Surg 2022;12(2):1348–1358.
  • 37. Kim HN, Jeon HJ, Choi HG, et al. CT-based Hounsfield unit values reflect the degree of steatohepatitis in patients with low-grade fatty liver disease. BMC Gastroenterol 2023;23(1):77.
  • 38. Shim SR, Kim SJ, Lee J. Diagnostic test accuracy: application and practice using R software. Epidemiol Health 2019;41:e2019007.
  • 39. Migliavaca CB, Stein C, Colpani V, et al. Meta-analysis of prevalence: I2 statistic and how to deal with heterogeneity. Res Synth Methods 2022;13(3):363–367.
  • 40. Shim S, Shin I, Bae J. Meta-analysis of diagnostic tests accuracy using STATA software. J Health Info Stat 2015;40(3):190–199.
  • 41. Walter SD. Properties of the summary receiver operating characteristic (SROC) curve for diagnostic test data. Stat Med 2002;21(9):1237–1256.
  • 42. Haberal KM, Turnaoğlu H, Haberal Reyhan AN. Is unenhanced computed tomography reliable in the assessment of macrovesicular steatosis in living liver donors? Exp Clin Transplant 2019;17(6):749–752.
  • 43. Limanond P, Raman SS, Lassman C, et al. Macrovesicular hepatic steatosis in living related liver donors: correlation between CT and histologic findings. Radiology 2004;230(1):276–280.
  • 44. Adalı G, Bozkurt B, Ceyhan Ö, et al. Body mass index and unenhanced CT as a predictor of hepatic steatosis in potential liver donors. Transplant Proc 2019;51(7):2373–2378.
  • 45. Lee SS, Park SH, Kim HJ, et al. Non-invasive assessment of hepatic steatosis: prospective comparison of the accuracy of imaging examinations. J Hepatol 2010;52(4):579–585.
  • 46. Park SH, Kim PN, Kim KW, et al. Macrovesicular hepatic steatosis in living liver donors: use of CT for quantitative and qualitative assessment. Radiology 2006;239(1):105–112.
  • 47. Rogier J, Roullet S, Cornélis F, et al. Noninvasive assessment of macrovesicular liver steatosis in cadaveric donors based on computed tomography liver-to-spleen attenuation ratio. Liver Transpl 2015;21(5):690–695.
  • 48. Saba L, di Martino M, Bosco S, et al. MDCT classification of steatotic liver: a multicentric analysis. Eur J Gastroenterol Hepatol 2015;27(3):290–297.
  • 49. Pickhardt PJ, Park SH, Hahn L, Lee SG, Bae KT, Yu ES. Specificity of unenhanced CT for non-invasive diagnosis of hepatic steatosis: implications for the investigation of the natural history of incidental steatosis. Eur Radiol 2012;22(5):1075–1082.
  • 50. van Werven JR, Marsman HA, Nederveen AJ, et al. Assessment of hepatic steatosis in patients undergoing liver resection: comparison of US, CT, T1-weighted dual-echo MR imaging, and point-resolved 1H MR spectroscopy. Radiology 2010;256(1):159–168.
  • 51. Şeker M, Erol C, Sevmiş Ş, Saka B, Durur Karakaya A. Comparison of CT methods for determining graft steatosis in living donor liver transplantation. Abdom Radiol (NY) 2019;44(7):2418–2429.
  • 52. Kuzu U, Gökcan H, Suna N, et al. Predictive value of unenhanced computerized tomography for detecting hepatosteatosis in living liver donors. Transplant Proc 2015;47(6):1854–1859.
  • 53. Marsman HA, van der Pool AE, Verheij J, et al. Hepatic steatosis assessment with CT or MRI in patients with colorectal liver metastases after neoadjuvant chemotherapy. J Surg Oncol 2011;104(1):10–16.
  • 54. Bae JS, Lee DH, Suh KS, et al. Noninvasive assessment of hepatic steatosis using a pathologic reference standard: comparison of CT, MRI, and US-based techniques. Ultrasonography 2022;41(2):344–354. [Published correction appears in Ultrasonography 2023;42(2):356.]
  • 55. Kan H, Kimura Y, Hyogo H, et al. Non-invasive assessment of liver steatosis in non-alcoholic fatty liver disease. Hepatol Res 2014;44(14):E420–E427.
  • 56. Chaudhary A, Sood G, Kumar N, et al. Validation of accuracy of non-invasive imaging methods (magnetic resonance imaging (MRI) fat fraction calculation and computed tomography (CT) liver attenuation index) for hepatic graft fat quantification in living liver transplant donors. Ann Transplant 2021;26:e933801.
  • 57. Cho CS, Curran S, Schwartz LH, et al. Preoperative radiographic assessment of hepatic steatosis with histologic correlation. J Am Coll Surg 2008;206(3):480–488.
  • 58. Jirapatnakul A, Reeves AP, Lewis S, et al. Automated measurement of liver attenuation to identify moderate-to-severe hepatic steatosis from chest CT scans. Eur J Radiol 2020;122:108723.
  • 59. Pickhardt PJ, Graffy PM, Reeder SB, Hernando D, Li K. Quantification of liver fat content with unenhanced MDCT: phantom and clinical correlation with MRI proton density fat fraction. AJR Am J Roentgenol 2018;211(3):W151–W157.
  • 60. Ahn Y, Yun SC, Lee SS, et al. Development and validation of a simple index based on non-enhanced CT and clinical factors for prediction of non-alcoholic fatty liver disease. Korean J Radiol 2020;21(4):413–421.
  • 61. Atef HM, Korayem EM, Ahmed NA, Houseni MM, El-Refaie AM, Gomaa MI. Assessment of hepatic steatosis of potential living donor before liver transplantation using liver/spleen CT attenuation ratio compared to liver biopsy. Egypt J Radiol Nucl Med 2023;54(1):212.
  • 62. Byun J, Lee SS, Sung YS, et al. CT indices for the diagnosis of hepatic steatosis using non-enhanced CT images: development and validation of diagnostic cut-off values in a large cohort with pathological reference standard. Eur Radiol 2019;29(8):4427–4435.
  • 63. Kim DY, Park SH, Lee SS, et al. Contrast-enhanced computed tomography for the diagnosis of fatty liver: prospective study with same-day biopsy used as the reference standard. Eur Radiol 2010;20(2):359–366.
  • 64. Sagir Kahraman A, Karakas HM, Kirimlioglu H, Kahraman B, Yilmaz S, Kirimlioglu V. The assessment of hepatosteatosis in living-donor liver transplant: comparison of liver attenuation index and histopathologic results. Exp Clin Transplant 2017;15(1):69–77.
  • 65. Jacobs JE, Birnbaum BA, Shapiro MA, et al. Diagnostic criteria for fatty infiltration of the liver on contrast-enhanced helical CT. AJR Am J Roentgenol 1998;171(3):659–664.
  • 66. Lawrence DA, Oliva IB, Israel GM. Detection of hepatic steatosis on contrast-enhanced CT images: diagnostic accuracy of identification of areas of presumed focal fatty sparing. AJR Am J Roentgenol 2012;199(1):44–47.
  • 67. da Fonseca Monjardim R, Cerqueira Costa DM, Tavares Romano RF, et al. Diagnosis of hepatic steatosis by contrast-enhanced abdominal computed tomography. Radiol Bras 2013;46(3):134–138.
  • 68. Pickhardt PJ, Blake GM, Kimmel Y, et al. Detection of moderate hepatic steatosis on portal venous phase contrast-enhanced CT: evaluation using an automated artificial intelligence tool. AJR Am J Roentgenol 2023;221(6):748–758.
  • 69. Panicek DM, Giess CS, Schwartz LH. Qualitative assessment of liver for fatty infiltration on contrast-enhanced CT: is muscle a better standard of reference than spleen? J Comput Assist Tomogr 1997;21(5):699–705.
  • 70. Zhang PP, Choi HH, Ohliger MA. Detection of fatty liver using virtual non-contrast dual-energy CT. Abdom Radiol (NY) 2022;47(6):2046–2056.
  • 71. Kang HJ, Lee DH, Park SJ, Han JK. Virtual noncontrast images derived from dual-energy CT for assessment of hepatic steatosis in living liver donors. Eur J Radiol 2021;139:109687.
  • 72. Choi MH, Lee YJ, Choi YJ, Pak S. Dual-energy CT of the liver: true noncontrast vs. virtual noncontrast images derived from multiple phases for the diagnosis of fatty liver. Eur J Radiol 2021;140:109741.
  • 73. Hong SB, Lee NK, Kim S, Um K, Kim K, Kim IJ. Hepatic fat quantification with the multi-material decomposition algorithm by using low-dose non-contrast material-enhanced dual-energy computed tomography in a prospectively enrolled cohort. Medicina (Kaunas) 2022;58(10):1459.
  • 74. Corrias G, Erta M, Sini M, et al. Comparison of multimaterial decomposition fat fraction with DECT and proton density fat fraction with IDEAL IQ MRI for quantification of liver steatosis in a population exposed to chemotherapy. Dose Response 2021;19(2):1559325820984938.
  • 75. Demondion E, Ernst O, Louvet A, et al. Hepatic fat quantification in dual-layer computed tomography using a three-material decomposition algorithm. Eur Radiol 2024;34(6):3708–3718.
  • 76. Niehoff JH, Woeltjen MM, Saeed S, et al. Assessment of hepatic steatosis based on virtual non-contrast computed tomography: initial experiences with a photon counting scanner approved for clinical use. Eur J Radiol 2022;149:110185.
  • 77. Catania R, Jia L, Haghshomar M, Miller FH, Borhani AA. Detection of moderate hepatic steatosis on contrast-enhanced dual-source dual-energy CT: role and accuracy of virtual non-contrast CT. Eur J Radiol 2024;172:111328.
  • 78. Beck S, Jahn L, Deniffel D, et al. Iodine images in dual-energy CT: detection of hepatic steatosis by quantitative iodine concentration values. J Digit Imaging 2022;35(6):1738–1747.
  • 79. Kardashian A, Serper M, Terrault N, Nephew LD. Health disparities in chronic liver disease. Hepatology 2023;77(4):1382–1403.
  • 80. Mahesh M, Ansari AJ, Mettler FA Jr. Patient exposure from radiologic and nuclear medicine procedures in the United States and worldwide: 2009-2018. Radiology 2023;307(1):e221263.
  • 81. Ajmera V, Park CC, Caussy C, et al. Magnetic resonance imaging proton density fat fraction associates with progression of fibrosis in patients with nonalcoholic fatty liver disease. Gastroenterology 2018;155(2):307–310.e2, e2.
  • 82. Hernaez R, Lazo M, Bonekamp S, et al. Diagnostic accuracy and reliability of ultrasonography for the detection of fatty liver: a meta-analysis. Hepatology 2011;54(3):1082–1090.
  • 83. Neuschwander-Tetri BA, Clark JM, Bass NM, et al. Clinical, laboratory and histological associations in adults with nonalcoholic fatty liver disease. Hepatology 2010;52(3):913–924.
  • 84. Pearce SG, Thosani NC, Pan JJ. Noninvasive biomarkers for the diagnosis of steatohepatitis and advanced fibrosis in NAFLD. Biomark Res 2013;1(1):7.

Article History

Received: Apr 23 2024
Revision requested: May 31 2024
Revision received: Aug 29 2024
Accepted: Sept 3 2024
Published online: Nov 05 2024