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A portable single-sided magnetic-resonance sensor for the grading of liver steatosis and fibrosis

Nature Biomedical Engineering volume 5, pages 240–251 (2021)Cite this article

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Abstract

Low-cost non-invasive diagnostic tools for staging the progression of non-alcoholic chronic liver failure from fatty liver disease to steatohepatitis are unavailable. Here, we describe the development and performance of a portable single-sided magnetic-resonance sensor for grading liver steatosis and fibrosis using diffusion-weighted multicomponent T2 relaxometry. In a diet-induced mouse model of non-alcoholic fatty liver disease, the sensor achieved overall accuracies of 92% (Cohen’s kappa, κ = 0.89) and 86% (κ = 0.78) in the ex vivo grading of steatosis and fibrosis, respectively. Localization of the measurements in living mice through frequency-dependent spatial encoding led to an overall accuracy of 87% (κ = 0.81) for the grading of steatosis. In human liver samples, the sensor graded steatosis with an overall accuracy of 93% (κ = 0.88). The use of T2 relaxometry as a sensitive measure in fully automated low-cost magnetic-resonance devices at the point of care would alleviate the accessibility and cost limits of magnetic-resonance imaging for diagnosing liver disease and assessing liver health before liver transplantation.

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Fig. 1: A portable MR sensor can accurately quantify fat content.
Fig. 2: A diet-induced model of NAFLD/NASH leads to progressive steatosis followed by fibrosis in mouse livers.
Fig. 3: The portable MR sensor accurately stages steatosis and fibrosis using multicomponent T2 relaxometry analysis of excised livers.
Fig. 4: The portable MR sensor accurately stages steatosis from excised human livers.
Fig. 5: The portable MR sensor accurately stages steatosis in vivo using multicomponent T2 relaxometry.

Data availability

The main data supporting the results in this study are available within the paper and its Supplementary Information. The raw and analysed datasets generated during the study are too large to be publicly shared, yet they are available for research purposes from the corresponding author on reasonable request.

Code availability

All code used for the analysis of data generated during the study is available from the corresponding author on reasonable request.

References

  1. Younossi, Z. et al. Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nat. Rev. Gastroenterol. Hepatol. 15, 11–20 (2018).

    Article  PubMed  Google Scholar 

  2. Shetty, A. & Syn, W.-K. Health and economic burden of nonalcoholic fatty liver disease in the United States and its impact on veterans. Fed. Pract. 36, 14–19 (2019).

    PubMed  PubMed Central  Google Scholar 

  3. Spengler, E. K. & Loomba, R. Recommendations for diagnosis, referral for liver biopsy, and treatment of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis. Mayo Clin. Proc. 90, 1233–1246 (2015).

    Article  PubMed  Google Scholar 

  4. Brunt, E. M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 7, 195–203 (2010).

    Article  PubMed  Google Scholar 

  5. Vernon, G., Baranova, A. & Younossi, Z. M. Systematic review: the epidemiology and natural history of non-alcoholic fatty liver disease and non-alcoholic steatohepatitis in adults. Aliment. Pharmacol. Ther. 34, 274–285 (2011).

    Article  CAS  PubMed  Google Scholar 

  6. Takahashi, Y. & Fukusato, T. Histopathology of nonalcoholic fatty liver disease/nonalcoholic steatohepatitis. World J. Gastroenterol. 20, 15539–15548 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Wattacheril, J., Issa, D. & Sanyal, A. Nonalcoholic steatohepatitis (NASH) and hepatic fibrosis: emerging therapies. Annu. Rev. Pharmacol. Toxicol. 58, 649–662 (2018).

    Article  CAS  PubMed  Google Scholar 

  8. Zhang, E. et al. Cost-utility analysis of nonalcoholic steatohepatitis screening. Eur. Radiol. 25, 3282–3294 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Tanaka, N. et al. Current status, problems, and perspectives of non-alcoholic fatty liver disease research. World J. Gastroenterol. 25, 163–177 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Wong, V. W.-S., Adams, L. A., de Lédinghen, V., Wong, G. L.-H. & Sookoian, S. Noninvasive biomarkers in NAFLD and NASH—current progress and future promise. Nat. Rev. Gastroenterol. Hepatol. 15, 461–478 (2018).

    Article  CAS  PubMed  Google Scholar 

  11. Strauss, S., Gavish, E., Gottlieb, P. & Katsnelson, L. Interobserver and intraobserver variability in the sonographic assessment of fatty liver. Am. J. Roentgenol. 189, W320–W323 (2007).

    Article  Google Scholar 

  12. Liang, W. et al. Establishment of a general NAFLD scoring system for rodent models and comparison to human liver pathology. PLoS ONE 9, e115922 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. Shen, J. et al. Non-invasive diagnosis of non-alcoholic steatohepatitis by combined serum biomarkers. J. Hepatol. 56, 1363–1370 (2012).

    Article  CAS  PubMed  Google Scholar 

  14. Krawczyk, K. et al. Adipohormones as prognostic markers in patients with nonalcoholic steatohepatitis (NASH). J. Physiol. Pharmacol. 60, 71–75 (2009).

    PubMed  Google Scholar 

  15. Loomba, R. et al. Magnetic resonance elastography predicts advanced fibrosis in patients with nonalcoholic fatty liver disease: a prospective study. Hepatology 60, 1920–1928 (2014).

    Article  CAS  PubMed  Google Scholar 

  16. Akkaya, H. E., Erden, A., Öz, D. K., Ünal, S. & Erden, I. Magnetic resonance elastography: basic principles, technique, and clinical applications in the liver. Diagn. Interv. Radiol. 24, 328–335 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Fishbein, M. et al. Hepatic MRI for fat quantitation: its relationship to fat morphology, diagnosis, and ultrasound. J. Clin. Gastroenterol. 39, 619–625 (2005).

    Article  PubMed  Google Scholar 

  18. Taouli, B. et al. Diffusion-weighted MRI for quantification of liver fibrosis: preliminary experience. Am. J. Roentgenol. 189, 799–806 (2007).

    Article  Google Scholar 

  19. Petitclerc, L., Sebastiani, G., Gilbert, G., Cloutier, G. & Tang, A. Liver fibrosis: review of current imaging and MRI quantification techniques. J. Magn. Reson. Imaging 45, 1276–1295 (2017).

    Article  PubMed  Google Scholar 

  20. Dulai, P. S., Sirlin, C. B. & Loomba, R. MRI and MRE for non-invasive quantitative assessment of hepatic steatosis and fibrosis in NAFLD and NASH: clinical trials to clinical practice. J. Hepatol. 65, 1006–1016 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Bohte, A. E., van Werven, J. R., 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. 21, 87–97 (2011).

    Article  PubMed  Google Scholar 

  22. Schultz, J. F., Bell, J. D., Goldstein, R. M., Kuhn, J. A. & McCarty, T. M. Hepatic tumor imaging using iron oxide MRI: comparison with computed tomography, clinical impact, and cost analysis. Ann. Surg. Oncol. 6, 691–698 (1999).

    Article  CAS  PubMed  Google Scholar 

  23. Evens, R. G. & Evens, R. G. Economic and utilization analysis of MR imaging units in the United States in 1987. Radiology 166, 27–30 (1988).

    Article  CAS  PubMed  Google Scholar 

  24. Schroeder, S. A. Magnetic resonance imaging: present costs and potential gains. Ann. Intern. Med. 102, 551–553 (1985).

    Article  CAS  PubMed  Google Scholar 

  25. Bashyam, A., Frangieh, C., Li, M. & Cima, M. J. Dehydration assessment via a non-invasive, miniature, portable magnetic resonance sensor using multicomponent T2 relaxometry. Magn. Reson. Med. 83, 1390–1404 (2020).

    Article  CAS  PubMed  Google Scholar 

  26. Bashyam, A., Li, M. & Cima, M. J. Design and experimental validation of unilateral linear Halbach magnet arrays for single-sided magnetic resonance. J. Magn. Reson. 292, 36–43 (2018).

    Article  CAS  PubMed  Google Scholar 

  27. Bush, E. C. et al. Fat-water phantoms for magnetic resonance imaging validation: a flexible and scalable protocol. J. Vis. Exp. 139, e57704 (2018).

    Google Scholar 

  28. Hines, C. D. G. et al. T1 independent, T2* corrected MRI with accurate spectral modeling for quantification of fat: validation in a fat-water-SPIO phantom. J. Magn. Reson. Imaging 30, 1215–1222 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Bernard, C. P., Liney, G. P., Manton, D. J., Turnbull, L. W. & Langton, C. M. Comparison of fat quantification methods: a phantom study at 3.0T. J. Magn. Reson. Imaging 27, 192–197 (2008).

    Article  PubMed  Google Scholar 

  30. Whitaker, C. & Casarella, J. Multiple NMR T2 relaxation values in human liver tissue. Am. J. Roentgenol. 141, 1203–1208 (1983).

    Article  Google Scholar 

  31. Cole, W. C., Leblanc, A. D. & Jhingran, S. G. The origin of biexponential T2 relaxation in muscle water. Magn. Reson. Med. 29, 19–24 (1993).

    Article  CAS  PubMed  Google Scholar 

  32. Clapper, J. R. et al. Diet-induced mouse model of fatty liver disease and nonalcoholic steatohepatitis reflecting clinical disease progression and methods of assessment. Am. J. Physiol. Gastrointest. Liver Physiol. 305, G483–G495 (2013).

    Article  CAS  PubMed  Google Scholar 

  33. Nakamura, A. & Terauchi, Y. Lessons from mouse models of high-fat diet-induced NAFLD. Int. J. Mol. Sci. 14, 21240–21257 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Matsumoto, M. et al. An improved mouse model that rapidly develops fibrosis in non-alcoholic steatohepatitis. Int. J. Exp. Pathol. 94, 93–103 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Ikawa-Yoshida, A. et al. Hepatocellular carcinoma in a mouse model fed a choline-deficient, l-amino acid-defined, high-fat diet. Int. J. Exp. Pathol. 98, 221–233 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. van Werven, J. R. 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 256, 159–168 (2010).

    Article  PubMed  Google Scholar 

  37. Charlton, M. et al. Fast food diet mouse: novel small animal model of NASH with ballooning, progressive fibrosis, and high physiological fidelity to the human condition. Am. J. Physiol. Gastrointest. Liver Physiol. 301, G825–G834 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Kleiner, D. E. et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology 41, 1313–1321 (2005).

    Article  PubMed  Google Scholar 

  39. Bonekamp, S., Torbenson, M. S. & Kamel, I. R. Diffusion-weighted magnetic resonance imaging for the staging of liver fibrosis. J. Clin. Gastroenterol. 45, 885–892 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Casanova, F., Perlo, J. & Blümich, B. Single-Sided NMR (Springer, 2011).

  41. Casieri, C., Bubici, S. & De Luca, F. Self-diffusion coefficient by single-sided NMR. J. Magn. Reson. 162, 348–355 (2003).

    Article  CAS  PubMed  Google Scholar 

  42. Rata, D. G., Casanova, F., Perlo, J., Demco, D. E. & Blümich, B. Self-diffusion measurements by a mobile single-sided NMR sensor with improved magnetic field gradient. J. Magn. Reson. 180, 229–235 (2006).

    Article  CAS  PubMed  Google Scholar 

  43. Perlo, J., Casanova, F. & Blümich, B. Profiles with microscopic resolution by single-sided NMR. J. Magn. Reson. 176, 64–70 (2005).

    Article  CAS  PubMed  Google Scholar 

  44. Koinuma, M., Ohashi, I., Hanafusa, K. & Shibuya, H. Apparent diffusion coefficient measurements with diffusion-weighted magnetic resonance imaging for evaluation of hepatic fibrosis. J. Magn. Reson. Imaging 22, 80–85 (2005).

    Article  PubMed  Google Scholar 

  45. Eddowes, P. J. et al. Utility and cost evaluation of multiparametric magnetic resonance imaging for the assessment of non-alcoholic fatty liver disease. Aliment. Pharmacol. Ther. 47, 631–644 (2018).

    Article  CAS  PubMed  Google Scholar 

  46. Skoien, R. et al. Heterogeneity of fibrosis patterns in non-alcoholic fatty liver disease supports the presence of multiple fibrogenic pathways. Liver Int. 33, 624–632 (2013).

    Article  CAS  PubMed  Google Scholar 

  47. Howlett, D. C., Drinkwater, K. J., Lawrence, D., Barter, S. & Nicholson, T. Findings of the UK national audit evaluating image-guided or image-assisted liver biopsy. Part II. Minor and major complications and procedure-related mortality. Radiology 266, 226–235 (2013).

    Article  PubMed  Google Scholar 

  48. Castéra, L., Nègre, I., Samii, K. & Buffet, C. Patient-administered nitrous oxide/oxygen inhalation provides safe and effective analgesia for percutaneous liver biopsy: a randomized placebo-controlled trial. Am. J. Gastroenterol. 96, 1553–1557 (2001).

    Article  PubMed  Google Scholar 

  49. Piccinino, F. et al. Complications following percutaneous liver biopsy: a multicentre retrospective study on 68,276 biopsies. J. Hepatol. 2, 165–173 (1986).

    Article  CAS  PubMed  Google Scholar 

  50. Seeff, L. B. et al. Complication rate of percutaneous liver biopsies among persons with advanced chronic liver disease in the HALT-C trial. Clin. Gastroenterol. Hepatol. 8, 877–883 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  51. Rockey, D. C., Caldwell, S. H., Goodman, Z. D., Nelson, R. C. & Smith, A. D. Liver biopsy. Hepatology 49, 1017–1044 (2009).

    Article  PubMed  Google Scholar 

  52. Foster, G. R. et al. Management of chronic hepatitis C: clinical audit of biopsy based management algorithm. Brit. Med. J. 315, 453–458 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Clark, J. M., Brancati, F. L. & Diehl, A. M. Nonalcoholic fatty liver disease. Gastroenterology 122, 1649–1657 (2002).

    Article  PubMed  Google Scholar 

  54. Yano, E., Tagawa, K., Yamaoka, K. & Mori, M. Test validity of periodic liver function tests in a population of Japanese male bank employees. J. Clin. Epidemiol. 54, 945–951 (2001).

    Article  CAS  PubMed  Google Scholar 

  55. Stanković, M. N. et al. Time-dependent changes and association between liver free fatty acids, serum lipid profile and histological features in mice model of nonalcoholic fatty liver disease. Arch. Med. Res. 45, 116–124 (2014).

    Article  PubMed  CAS  Google Scholar 

  56. Linares, I., Hamar, M., Selzner, N. & Selzner, M. Steatosis in liver transplantation: current limitations and future strategies. Transplantation 103, 78–90 (2019).

    Article  PubMed  Google Scholar 

  57. Croome, K. P. et al. The impact of post-reperfusion syndrome during liver transplantation using livers with significant macrosteatosis. Am. J. Transplant. https://doi.org/10.1111/ajt.15330 (2019).

  58. Gabrielli, M. et al. Steatotic livers. Can we use them in OLTX? Outcome data from a prospective baseline liver biopsy study. Ann. Hepatol. 11, 891–898 (2012).

    Article  PubMed  Google Scholar 

  59. Croome, K. P., Lee, D. D. & Taner, C. B. The “skinny” on assessment and utilization of steatotic liver grafts: a systematic review. Liver Transpl. 25, 488–499 (2019).

    Article  PubMed  Google Scholar 

  60. Selzner, M. & Clavien, P. A. Fatty liver in liver transplantation and surgery. Semin. Liver Dis. 21, 105–113 (2001).

  61. Rehorn, C. & Blümich, B. Cultural heritage studies with mobile NMR. Angew. Chem. Int. Ed. Engl. 57, 7304–7312 (2018).

    Article  CAS  PubMed  Google Scholar 

  62. Dabaghyan, M. et al. A portable single-sided magnet system for remote NMR measurements of pulmonary function. NMR Biomed. 27, 1479–1489 (2014).

    Article  PubMed  Google Scholar 

  63. Colucci, L. A. et al. Fluid assessment in dialysis patients by point-of-care magnetic relaxometry. Sci. Transl. Med. 11, eaau1749 (2019).

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  64. Bruinsma, B. G. et al. Subnormothermic machine perfusion for ex vivo preservation and recovery of the human liver for transplantation. Am. J. Transplant. 14, 1400–1409 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Karimian, N. et al. Ex situ normothermic machine perfusion of donor livers. J. Vis. Exp. 2015, e52688 (2015).

    Google Scholar 

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Acknowledgements

We thank staff at the Koch Institute Swanson Biotechnology Center for technical support, specifically W. Huang and V. Spanoudaki at Animal Imaging and Preclinical Testing and K. Cormier at Histology; A. Warren, K. Nayak, M. Rosen, E. Adalsteinsson, S. Carrasco, K. Subramanyam, M. Cotler, E. Rousseau and K. Ramadi for discussions; staff at the New England Donor Services and the patients and families that made this study possible. This work was supported in part by the Koch Institute Support (core) grant no. P30-CA14051 from the National Cancer Institute, the National Institutes of Health grant nos. R01DK096075 and R01DK107875, and National Science Foundation (ATP-Bio 1941543). A.B. was supported by a Fannie & John Hertz Foundation Graduate Fellowship and a National Science Foundation Graduate Fellowship.

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Author notes

  1. These authors contributed equally: Ashvin Bashyam, Chris J. Frangieh.

Authors and Affiliations

  1. David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA

    Ashvin Bashyam, Chris J. Frangieh, Jeremy Sogo & Michael J. Cima

  2. Electrical Engineering & Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA

    Ashvin Bashyam, Chris J. Frangieh & Jeremy Sogo

  3. Division of Transplantation, Department of Surgery, Massachusetts General Hospital, Boston, MA, USA

    Siavash Raigani & Heidi Yeh

  4. Department of Microbiology and Immunobiology, Division of Immunology, Harvard Medical School, Boston, MA, USA

    Roderick T. Bronson

  5. Center for Engineering in Medicine and Surgery, Massachusetts General Hospital, Boston, MA, USA

    Korkut Uygun

  6. Division of Nephrology, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA

    Dennis A. Ausiello

  7. Center for Assessment Technology and Continuous Health, Massachusetts General Hospital, Boston, MA, USA

    Dennis A. Ausiello

  8. Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Michael J. Cima

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Contributions

A.B. constructed the portable MR sensor. A.B. and C.J.F. characterized the portable MR sensor, performed all of the experiments and wrote the manuscript. J.S. performed ex vivo experiments. A.B. prepared figures. A.B., C.J.F. and M.J.C. designed the experiments and interpreted results. A.B., C.J.F., S.R. and M.J.C. edited the manuscript. R.T.B. conducted pathology analysis of all tissues. M.J.C., D.A.A., H.Y. and K.U. supervised the research.

Corresponding author

Correspondence to Michael J. Cima.

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Competing interests

A.B. and M.J.C. are inventors on a patent application (US20180306879) submitted by MIT that describes the design of the permanent magnet array within the portable MR sensor. K.U. has a financial interest in Organ Solutions, a company that is focused on developing organ preservation technology. These interests are managed by the Mass General Brigham in accordance with their conflict of interest policies.

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Supplementary Figs. 1–15, Table 1, discussion, methods and references.

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Bashyam, A., Frangieh, C.J., Raigani, S. et al. A portable single-sided magnetic-resonance sensor for the grading of liver steatosis and fibrosis. Nat Biomed Eng 5, 240–251 (2021). https://doi.org/10.1038/s41551-020-00638-0

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