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Quantitative assessment of global hepatic glycolysis in patients with cirrhosis and normal controls using 18F-FDG-PET/CT: a pilot study

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Abstract

Objective

To compare differences in global measures of hepatic metabolism between control subjects and subjects with cirrhosis.

Materials and methods

FDG-PET/CT scans of 33 subjects either without or with cirrhosis were analyzed retrospectively and classified as follows: group 1 includes subjects without cirrhosis or extrahepatic malignancy (1a) (n = 11) and subjects without cirrhosis but with history of extrahepatic malignancy (1b) (n = 10); group 2 includes subjects with cirrhosis and history of extrahepatic malignancy (n = 12). Subjects with focal hepatic lesions, prior hepatic surgery, co-existing liver pathology, or who received chemotherapy or radiation therapy within the last 6 months were excluded. The hepatic volumes, hepatic mean standardized uptake value (SUVmean), and global hepatic glycolysis (GHG) were compared between groups.

Results

Subjects with cirrhosis showed a lower average hepatic SUVmean as compared to non-cirrhotic patients (1.55 ± 0.29 for group 2 versus 1.81 ± 0.23 for group 1; p value = 0.009) and lower average values for GHG (2238.29 ± 903.60 for group 2 versus 2974.67 ± 829.16 for group 1; p value = 0.024). No differences were noted between the non-cirrhotic subgroups (i.e., between the groups 1a and 1b) without and with associated extrahepatic malignancy, respectively.

Conclusions

We hypothesize that presence of fibrosis, reduction of active inflammation, and decreased hepatic metabolism and function are potential causes of the lower FDG uptake in cirrhotic livers. Our results also indicate that extrahepatic cancer status does not influence FDG uptake in the non-cirrhotic liver in subjects without hepatic metastases.

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References

  1. Hansen L, Sasaki A, Zucker B. End-stage liver disease: challenges and practice implications. Nurs Clin North Am. 2010;45(3):411–26.

    Article  PubMed  Google Scholar 

  2. Schuppan D, Afdhal NH. Liver cirrhosis. Lancet. 2008;371(9615):838–51.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  3. Udell JA, Wang CS, Tinmouth J, FitzGerald JM, Ayas NT, Simel DL, et al. Does this patient with liver disease have cirrhosis? JAMA. 2012;307(8):832–42.

    Article  CAS  PubMed  Google Scholar 

  4. Riley TR, Taheri M, Schreibman IR. Does weight history affect fibrosis in the setting of chronic liver disease? J Gastrointestin Liver Dis. 2009;18(3):299–302.

    PubMed  Google Scholar 

  5. Wanless IR, Nakashima E, Sherman M. Regression of human cirrhosis. Morphologic features and the genesis of incomplete septal cirrhosis. Arch Pathol Lab Med. 2000;124(11):1599–607.

    CAS  PubMed  Google Scholar 

  6. Desmet VJ, Roskams T. Cirrhosis reversal: a duel between dogma and myth. J Hepatol. 2004;40(5):860–7.

    Article  PubMed  Google Scholar 

  7. de Graaf W, Bennink RJ, Vetelainen R, van Gulik TM. Nuclear imaging techniques for the assessment of hepatic function in liver surgery and transplantation. J Nucl Med. 2010;51(5):742–52.

    Article  PubMed  Google Scholar 

  8. Fierbinteanu-Braticevici C, Purcarea M. Non-biopsy methods to determine hepatic fibrosis. J Med Life. 2009;2(4):401–6.

    PubMed Central  PubMed  Google Scholar 

  9. Wang Y, Ganger DR, Levitsky J, Sternick LA, McCarthy RJ, Chen ZE, et al. Assessment of chronic hepatitis and fibrosis: comparison of MR elastography and diffusion-weighted imaging. AJR Am J Roentgenol. 2011;196(3):553–61.

    Article  PubMed Central  PubMed  Google Scholar 

  10. Sohail S. Hepatic fibrosis imaging: trends and feasibility. J Coll Physicians Surg Pak. 2012;22(2):73–4.

    PubMed  Google Scholar 

  11. Brancatelli G, Baron RL, Federle MP, Sparacia G, Pealer K. Focal confluent fibrosis in cirrhotic liver: natural history studied with serial CT. AJR Am J Roentgenol. 2009;192(5):1341–7.

    Article  PubMed  Google Scholar 

  12. Lenhart M, Feuerbach S. Role of computed tomography and magnetic resonance imaging in the diagnosis of hepatitis and liver cirrhosis. Praxis (Bern 1994). 2005;94(16):635–8.

    Article  CAS  Google Scholar 

  13. Yoshida M, Shiraishi S, Sakaguchi F, Utsunomiya D, Tashiro K, Tomiguchi S, et al. A quantitative index measured on (9)(9)mTc GSA SPECT/CT 3D fused images to evaluate severe fibrosis in patients with chronic liver disease. Jpn J Radiol. 2012;30(5):435–41.

    Article  PubMed  Google Scholar 

  14. Yoshida M, Shiraishi S, Sakaguchi F, Utsunomiya D, Tashiro K, Tomiguchi S, et al. Fused 99m-Tc-GSA SPECT/CT imaging for the preoperative evaluation of postoperative liver function: can the liver uptake index predict postoperative hepatic functional reserve? Jpn J Radiol. 2012;30(3):255–62.

    Article  PubMed  Google Scholar 

  15. Kwon AH, Matsui Y, Ha-Kawa SK, Kamiyama Y. Functional hepatic volume measured by technetium-99m-galactosyl-human serum albumin liver scintigraphy: comparison between hepatocyte volume and liver volume by computed tomography. Am J Gastroenterol. 2001;96(2):541–6.

    Article  CAS  PubMed  Google Scholar 

  16. Onodera Y, Takahashi K, Togashi T, Sugai Y, Tamaki N, Miyasaka K. Clinical assessment of hepatic functional reserve using 99mTc DTPA galactosyl human serum albumin SPECT to prognosticate chronic hepatic diseases—validation of the use of SPECT and a new indicator. Ann Nucl Med. 2003;17(3):181–8.

    Article  PubMed  Google Scholar 

  17. Kaibori M, Ha-Kawa SK, Maehara M, Ishizaki M, Matsui K, Sawada S, et al. Usefulness of Tc-99m-GSA scintigraphy for liver surgery. Ann Nucl Med. 2011;25(9):593–602.

    Article  PubMed  Google Scholar 

  18. Alavi A, Kung JW, Zhuang H. Implications of PET based molecular imaging on the current and future practice of medicine. Semin Nucl Med. 2004;34(1):56–69.

    Article  PubMed  Google Scholar 

  19. Musiek ES, Chen Y, Korczykowski M, Saboury B, Martinez PM, Reddin JS, et al. Direct comparison of fluorodeoxyglucose positron emission tomography and arterial spin labeling magnetic resonance imaging in Alzheimer’s disease. Alzheimers Dement. 2012;8(1):51–9. doi:10.1016/j.jalz.2011.06.003.

    Article  PubMed Central  PubMed  Google Scholar 

  20. Ewers M, Insel PS, Stern Y, Weiner MW. Cognitive reserve associated with FDG-PET in preclinical Alzheimer disease. Neurology. 2013;80(13):1194–201. doi:10.1212/WNL.0b013e31828970c2.

    Article  CAS  PubMed  Google Scholar 

  21. Kuker RA, Mesoloras G, Gulec SA. Optimization of FDG-PET/CT imaging protocol for evaluation of patients with primary and metastatic liver disease. Int Semin Surg Oncol. 2007;4:17.

    Article  PubMed Central  PubMed  Google Scholar 

  22. Lin CY, Ding HJ, Lin CC, Chen CC, Sun SS, Kao CH. Impact of age on FDG uptake in the liver on PET scan. Clin Imaging. 2010;34(5):348–50.

    Article  PubMed  Google Scholar 

  23. Alavi A, Newberg AB, Souder E, Berlin JA. Quantitative analysis of PET and MRI data in normal aging and Alzheimer’s disease: atrophy weighted total brain metabolism and absolute whole brain metabolism as reliable discriminators. J Nucl Med. 1993;34(10):1681–7.

    CAS  PubMed  Google Scholar 

  24. Abdulla S, Salavati A, Saboury B, Basu S, Torigian DA, Alavi A. Quantitative assessment of global lung inflammation following radiation therapy using FDG PET/CT: a pilot study. Eur J Nucl Med Mol Imaging. 2013. doi:10.1007/s00259-013-2579-4.

  25. Fonti R, Larobina M, Del Vecchio S, De Luca S, Fabbricini R, Catalano L, et al. Metabolic tumor volume assessed by 18F-FDG PET/CT for the prediction of outcome in patients with multiple myeloma. J Nucl Med. 2012;53(12):1829–35. doi:10.2967/jnumed.112.106500.

    Article  CAS  PubMed  Google Scholar 

  26. Lim R, Eaton A, Lee NY, Setton J, Ohri N, Rao S, et al. 18F-FDG PET/CT metabolic tumor volume and total lesion glycolysis predict outcome in oropharyngeal squamous cell carcinoma. J Nucl Med. 2012;53(10):1506–13. doi:10.2967/jnumed.111.101402.

    Article  CAS  PubMed  Google Scholar 

  27. Berkowitz A, Basu S, Srinivas S, Sankaran S, Schuster S, Alavi A. Determination of whole-body metabolic burden as a quantitative measure of disease activity in lymphoma: a novel approach with fluorodeoxyglucose-PET. Nucl Med Commun. 2008;29(6):521–6. doi:10.1097/MNM.0b013e3282f813a4.

    Article  CAS  PubMed  Google Scholar 

  28. Chen HH, Chiu NT, Su WC, Guo HR, Lee BF. Prognostic value of whole-body total lesion glycolysis at pretreatment FDG PET/CT in non-small cell lung cancer. Radiology. 2012;264(2):559–66. doi:10.1148/radiol.12111148.

    Article  PubMed  Google Scholar 

  29. Liao S, Penney BC, Wroblewski K, Zhang H, Simon CA, Kampalath R, et al. Prognostic value of metabolic tumor burden on 18F-FDG PET in nonsurgical patients with non-small cell lung cancer. Eur J Nucl Med Mol Imaging. 2012;39(1):27–38. doi:10.1007/s00259-011-1934-6.

    Article  CAS  PubMed  Google Scholar 

  30. Francis RJ, Byrne MJ, van der Schaaf AA, Boucek JA, Nowak AK, Phillips M, et al. Early prediction of response to chemotherapy and survival in malignant pleural mesothelioma using a novel semiautomated 3-dimensional volume-based analysis of serial 18F-FDG PET scans. J Nucl Med. 2007;48(9):1449–58. doi:10.2967/jnumed.107.042333.

    Article  PubMed  Google Scholar 

  31. Dibble EH, Alvarez AC, Truong MT, Mercier G, Cook EF, Subramaniam RM. 18F-FDG metabolic tumor volume and total glycolytic activity of oral cavity and oropharyngeal squamous cell cancer: adding value to clinical staging. J Nucl Med. 2012;53(5):709–15. doi:10.2967/jnumed.111.099531.

    Article  CAS  PubMed  Google Scholar 

  32. Basu S, Zaidi H, Houseni M, Bural G, Udupa J, Acton P, et al. Novel quantitative techniques for assessing regional and global function and structure based on modern imaging modalities: implications for normal variation, aging and diseased states. Semin Nucl Med. 2007;37(3):223–39.

    Article  PubMed  Google Scholar 

  33. Bural GG, Torigian DA, Burke A, Houseni M, Alkhawaldeh K, Cucchiara A, et al. Quantitative assessment of the hepatic metabolic volume product in patients with diffuse hepatic steatosis and normal controls through use of FDG-PET and MR imaging: a novel concept. Mol Imaging Biol. 2010;12(3):233–9.

    Article  PubMed  Google Scholar 

  34. Abele JT, Fung CI. Effect of hepatic steatosis on liver FDG uptake measured in mean standard uptake values. Radiology. 2010;254(3):917–24.

    Article  PubMed  Google Scholar 

  35. Dostbil Z, Varoglu E, Serdengecti M, Kaya B, Onder H, Sari O. Evaluation of hepatic metabolic activity in non-alcoholic fatty livers on (18)FDG PET/CT. Rev Esp Med Nucl Imagen Mol. 2013;32(3):156–61. doi:10.1016/j.remn.2012.04.006.

    CAS  PubMed  Google Scholar 

  36. Geraghty EM, Boone JM, McGahan JP, Jain K. Normal organ volume assessment from abdominal CT. Abdom Imaging. 2004;29(4):482–90.

    Article  CAS  PubMed  Google Scholar 

  37. Kamimura K, Nagamachi S, Wakamatsu H, Higashi R, Ogita M, Ueno S, et al. Associations between liver (18)F fluoro-2-deoxy-d-glucose accumulation and various clinical parameters in a Japanese population: influence of the metabolic syndrome. Ann Nucl Med. 2010;24(3):157–61. doi:10.1007/s12149-009-0338-1.

    Article  PubMed  Google Scholar 

  38. Meier JM, Alavi A, Iruvuri S, Alzeair S, Parker R, Houseni M, et al. Assessment of age-related changes in abdominal organ structure and function with computed tomography and positron emission tomography. Semin Nucl Med. 2007;37(3):154–72.

    Article  PubMed  Google Scholar 

  39. Bural GG, Torigian DA, Chen W, Houseni M, Basu S, Alavi A. Increased 18F-FDG uptake within the reticuloendothelial system in patients with active lung cancer on PET imaging may indicate activation of the systemic immune response. Hell J Nucl Med. 2010;13(1):23–5.

    PubMed  Google Scholar 

  40. Nicoll A. Surgical risk in patients with cirrhosis. J Gastroenterol Hepatol. 2012;27(10):1569–75. doi:10.1111/j.1440-1746.2012.07205.x.

    Article  PubMed  Google Scholar 

  41. Kamath PS, Kim WR. The model for end-stage liver disease (MELD). Hepatology. 2007;45(3):797–805. doi:10.1002/hep.21563.

    Article  PubMed  Google Scholar 

  42. Asrani SK, Kim WR. Model for end-stage liver disease: end of the first decade. Clin Liver Dis. 2011;15(4):685–98. doi:10.1016/j.cld.2011.08.009.

    Article  PubMed Central  PubMed  Google Scholar 

  43. Sorensen M, Mikkelsen KS, Frisch K, Villadsen GE, Keiding S. Regional metabolic liver function measured by 2-[(18)F]fluoro-2-deoxy-d-galactose PET/CT in patients with cirrhosis. J Hepatol. 2013; 8278(13). doi: 10.1016/j.jhep.2013.01.012.

  44. Chopra A. 18F-labeled neogalactosylalbumin. Molecular Imaging and Contrast Agent Database (MICAD). National Center for Biotechnology Information (US); 2009. pp. 2004–13.

  45. Slimani L, Kudomi N, Oikonen V, Jarvisalo M, Kiss J, Naum A, et al. Quantification of liver perfusion with [(15)O]H(2)O-PET and its relationship with glucose metabolism and substrate levels. J Hepatol. 2008;48(6):974–82.

    Article  CAS  PubMed  Google Scholar 

  46. Nishiguchi S, Shiomi S, Kawamura E, Ishizu H, Habu D, Torii K, et al. Evaluation of ammonia metabolism in the skeletal muscles of patients with cirrhosis using N-13 ammonia PET. Ann Nucl Med. 2003;17(5):417–9.

    Article  CAS  PubMed  Google Scholar 

  47. Dam G, Keiding S, Munk OL, Ott P, Buhl M, Vilstrup H, et al. Branched-chain amino acids increase arterial blood ammonia in spite of enhanced intrinsic muscle ammonia metabolism in patients with cirrhosis and healthy subjects. Am J Physiol Gastrointest Liver Physiol. 2011;301(2):G269–77.

    Article  CAS  PubMed  Google Scholar 

  48. Matusch A, Meyer PT, Bier D, Holschbach MH, Woitalla D, Elmenhorst D, et al. Metabolism of the A1 adenosine receptor PET ligand [18F]CPFPX by CYP1A2: implications for bolus/infusion PET studies. Nucl Med Biol. 2006;33(7):891–8.

    Article  CAS  PubMed  Google Scholar 

  49. Sorensen M, Mikkelsen KS, Frisch K, Bass L, Bibby BM, Keiding S. Hepatic galactose metabolism quantified in humans using 2-18F-fluoro-2-deoxy-d-galactose PET/CT. J Nucl Med. 2011;52(10):1566–72.

    Article  PubMed Central  PubMed  Google Scholar 

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The authors declare no conflict of interest.

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Correspondence to Abass Alavi.

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A. Hernandez-Martinez, V. A. Marin-Oyaga, and A. Salavati contributed equally to this study.

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Hernandez-Martinez, A., Marin-Oyaga, V.A., Salavati, A. et al. Quantitative assessment of global hepatic glycolysis in patients with cirrhosis and normal controls using 18F-FDG-PET/CT: a pilot study. Ann Nucl Med 28, 53–59 (2014). https://doi.org/10.1007/s12149-013-0780-y

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  • DOI: https://doi.org/10.1007/s12149-013-0780-y

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