Acceleration of chemical shift encoding-based water fat MRI for liver proton density fat fraction and T2* mapping using compressed sensing
Autoři:
Fabian K. Lohöfer aff001; Georgios A. Kaissis aff001; Christina Müller-Leisse aff001; Daniela Franz aff001; Christoph Katemann aff002; Andreas Hock aff002; Johannes M. Peeters aff003; Ernst J. Rummeny aff001; Dimitrios Karampinos aff001; Rickmer F. Braren aff001
Působiště autorů:
Institute for diagnostic and interventional Radiology, Klinikum rechts der Isar der Technischen Universität München, Ismaninger Straße, München, Germany
aff001; Philips Healthcare, Hamburg, Germany
aff002; Philips Healthcare, Best, Netherlands
aff003
Vyšlo v časopise:
PLoS ONE 14(11)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0224988
Souhrn
Objectives
To evaluate proton density fat fraction (PDFF) and T2* measurements of the liver with combined parallel imaging (sensitivity encoding, SENSE) and compressed sensing (CS) accelerated chemical shift encoding-based water-fat separation.
Methods
Six-echo Dixon imaging was performed in the liver of 89 subjects. The first acquisition variant used acceleration based on SENSE with a total acceleration factor equal to 2.64 (acquisition labeled as SENSE). The second acquisition variant used acceleration based on a combination of CS with SENSE with a total acceleration factor equal to 4 (acquisition labeled as CS+SENSE). Acquisition times were compared between acquisitions and proton density fat fraction (PDFF) and T2*-values were measured and compared separately for each liver segment.
Results
Total scan duration was 14.5 sec for the SENSE accelerated image acquisition and 9.3 sec for the CS+SENSE accelerated image acquisition. PDFF and T2* values did not differ significantly between the two acquisitions (paired Mann-Whitney and paired t-test P>0.05 in all cases). CS+SENSE accelerated acquisition showed reduced motion artifacts (1.1%) compared to SENSE acquisition (12.3%).
Conclusion
CS+SENSE accelerates liver PDFF and T2*mapping while retaining the same quantitative values as an acquisition using only SENSE and reduces motion artifacts.
Klíčová slova:
Fats – Fatty liver – Image processing – Imaging techniques – Liver and spleen scan – Magnetic resonance imaging – Steatosis – Compressed sensing
Zdroje
1. Fraser A, Harris R, Sattar N, Ebrahim S, Davey Smith G, Lawlor DA. Alanine aminotransferase, gamma-glutamyltransferase, and incident diabetes: the British Women's Heart and Health Study and meta-analysis. Diabetes Care. 2009;32(4):741–50. doi: 10.2337/dc08-1870 19131466; PubMed Central PMCID: PMCPMC2660465.
2. Zelber-Sagi S, Nitzan-Kaluski D, Halpern Z, Oren R. Prevalence of primary non-alcoholic fatty liver disease in a population-based study and its association with biochemical and anthropometric measures. Liver Int. 2006;26(7):856–63. doi: 10.1111/j.1478-3231.2006.01311.x 16911469.
3. Valenti L, Fracanzani AL, Dongiovanni P, Bugianesi E, Marchesini G, Manzini P, et al. Iron depletion by phlebotomy improves insulin resistance in patients with nonalcoholic fatty liver disease and hyperferritinemia: evidence from a case-control study. Am J Gastroenterol. 2007;102(6):1251–8. Epub 2007/03/30. doi: 10.1111/j.1572-0241.2007.01192.x 17391316.
4. Valenti L, Fracanzani AL, Bugianesi E, Dongiovanni P, Galmozzi E, Vanni E, et al. HFE genotype, parenchymal iron accumulation, and liver fibrosis in patients with nonalcoholic fatty liver disease. Gastroenterology. 2010;138(3):905–12. Epub 2009/11/26. doi: 10.1053/j.gastro.2009.11.013 19931264.
5. Olivieri NF, Brittenham GM. Iron-chelating therapy and the treatment of thalassemia. Blood. 1997;89(3):739–61. 9028304.
6. Adams LA, Angulo P, Lindor KD. Nonalcoholic fatty liver disease. CMAJ. 2005;172(7):899–905. doi: 10.1503/cmaj.045232 15795412; PubMed Central PMCID: PMCPMC554876.
7. Kleiner DE, Brunt EM, Van Natta M, Behling C, Contos MJ, Cummings OW, et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology. 2005;41(6):1313–21. doi: 10.1002/hep.20701 15915461.
8. Sanyal AJ, American Gastroenterological A. AGA technical review on nonalcoholic fatty liver disease. Gastroenterology. 2002;123(5):1705–25. doi: 10.1053/gast.2002.36572 12404245.
9. 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):2467–74. doi: 10.1111/j.1572-0241.1999.01377.x 10484010.
10. Sarigianni M, Liakos A, Vlachaki E, Paschos P, Athanasiadou E, Montori VM, et al. Accuracy of magnetic resonance imaging in diagnosis of liver iron overload: a systematic review and meta-analysis. Clin Gastroenterol Hepatol. 2015;13(1):55–63 e5. Epub 2014/07/06. doi: 10.1016/j.cgh.2014.05.027 24993364.
11. Nash S, Marconi S, Sikorska K, Naeem R, Nash G. Role of liver biopsy in the diagnosis of hepatic iron overload in the era of genetic testing. Am J Clin Pathol. 2002;118(1):73–81. doi: 10.1309/4A4U-N4GL-DRP3-EQPD 12109859.
12. Urru SA, Tandurella I, Capasso M, Usala E, Baronciani D, Giardini C, et al. Reproducibility of liver iron concentration measured on a biopsy sample: a validation study in vivo. Am J Hematol. 2015;90(2):87–90. doi: 10.1002/ajh.23878 25345839.
13. Yokoo T, Bydder M, Hamilton G, Middleton MS, Gamst AC, Wolfson T, et al. Nonalcoholic fatty liver disease: diagnostic and fat-grading accuracy of low-flip-angle multiecho gradient-recalled-echo MR imaging at 1.5 T. Radiology. 2009;251(1):67–76. doi: 10.1148/radiol.2511080666 19221054; PubMed Central PMCID: PMCPMC2663579.
14. Reeder SB, Sirlin CB. Quantification of liver fat with magnetic resonance imaging. Magn Reson Imaging Clin N Am. 2010;18(3):337–57, ix. doi: 10.1016/j.mric.2010.08.013 21094444; PubMed Central PMCID: PMCPMC3002753.
15. Reeder SB, Cruite I, Hamilton G, Sirlin CB. Quantitative assessment of liver fat with magnetic resonance imaging and spectroscopy. J Magn Reson Imaging. 2011;34(4):729–49. doi: 10.1002/jmri.22580 22025886.
16. Reeder SB, Hu HH, Sirlin CB. Proton density fat-fraction: a standardized MR-based biomarker of tissue fat concentration. J Magn Reson Imaging. 2012;36(5):1011–4. doi: 10.1002/jmri.23741 22777847; PubMed Central PMCID: PMCPMC4779595.
17. Hu HH, Kan HE. Quantitative proton MR techniques for measuring fat. NMR Biomed. 2013;26(12):1609–29. doi: 10.1002/nbm.3025 24123229; PubMed Central PMCID: PMCPMC4001818.
18. Zhang Y, Wang C, Duanmu Y, Zhang C, Zhao W, Wang L, et al. Comparison of CT and magnetic resonance mDIXON-Quant sequence in the diagnosis of mild hepatic steatosis. Br J Radiol. 2018;91(1091):20170587. doi: 10.1259/bjr.20170587 30028193.
19. Hernando D, Levin YS, Sirlin CB, Reeder SB. Quantification of liver iron with MRI: state of the art and remaining challenges. J Magn Reson Imaging. 2014;40(5):1003–21. doi: 10.1002/jmri.24584 24585403; PubMed Central PMCID: PMCPMC4308740.
20. Feng L, Benkert T, Block KT, Sodickson DK, Otazo R, Chandarana H. Compressed sensing for body MRI. J Magn Reson Imaging. 2017;45(4):966–87. doi: 10.1002/jmri.25547 27981664; PubMed Central PMCID: PMCPMC5352490.
21. Fushimi Y, Fujimoto K, Okada T, Yamamoto A, Tanaka T, Kikuchi T, et al. Compressed Sensing 3-Dimensional Time-of-Flight Magnetic Resonance Angiography for Cerebral Aneurysms: Optimization and Evaluation. Invest Radiol. 2016;51(4):228–35. doi: 10.1097/RLI.0000000000000226 26606551.
22. Zhu L, Wu X, Sun Z, Jin Z, Weiland E, Raithel E, et al. Compressed-Sensing Accelerated 3-Dimensional Magnetic Resonance Cholangiopancreatography: Application in Suspected Pancreatic Diseases. Invest Radiol. 2018;53(3):150–7. doi: 10.1097/RLI.0000000000000421 28976478.
23. Doneva M, Bornert P, Eggers H, Mertins A, Pauly J, Lustig M. Compressed sensing for chemical shift-based water-fat separation. Magn Reson Med. 2010;64(6):1749–59. doi: 10.1002/mrm.22563 20859998.
24. Sharma SD, Hu HH, Nayak KS. Accelerated T2*-compensated fat fraction quantification using a joint parallel imaging and compressed sensing framework. J Magn Reson Imaging. 2013;38(5):1267–75. doi: 10.1002/jmri.24034 23390111; PubMed Central PMCID: PMCPMC3654015.
25. Wiens CN, McCurdy CM, Willig-Onwuachi JD, McKenzie CA. R2*-corrected water-fat imaging using compressed sensing and parallel imaging. Magn Reson Med. 2014;71(2):608–16. doi: 10.1002/mrm.24699 23475787.
26. Mann LW, Higgins DM, Peters CN, Cassidy S, Hodson KK, Coombs A, et al. Accelerating MR Imaging Liver Steatosis Measurement Using Combined Compressed Sensing and Parallel Imaging: A Quantitative Evaluation. Radiology. 2016;278(1):247–56. doi: 10.1148/radiol.2015150320 26218662.
27. Ren J, Dimitrov I, Sherry AD, Malloy CR. Composition of adipose tissue and marrow fat in humans by 1H NMR at 7 Tesla. J Lipid Res. 2008;49(9):2055–62. doi: 10.1194/jlr.D800010-JLR200 18509197; PubMed Central PMCID: PMCPMC2515528.
28. Hua B, Hakkarainen A, Zhou Y, Lundbom N, Yki-Jarvinen H. Fat accumulates preferentially in the right rather than the left liver lobe in non-diabetic subjects. Dig Liver Dis. 2018;50(2):168–74. doi: 10.1016/j.dld.2017.08.030 28964678.
29. Fazeli Dehkordy S, Fowler KJ, Mamidipalli A, Wolfson T, Hong CW, Covarrubias Y, et al. Hepatic steatosis and reduction in steatosis following bariatric weight loss surgery differs between segments and lobes. European radiology. 2018. doi: 10.1007/s00330-018-5894-0 30547206.
30. Smith-Bindman R, Miglioretti DL, Larson EB. Rising use of diagnostic medical imaging in a large integrated health system. Health Aff (Millwood). 2008;27(6):1491–502. doi: 10.1377/hlthaff.27.6.1491 18997204; PubMed Central PMCID: PMCPMC2765780.
31. Hollingsworth KG, Higgins DM, McCallum M, Ward L, Coombs A, Straub V. Investigating the quantitative fidelity of prospectively undersampled chemical shift imaging in muscular dystrophy with compressed sensing and parallel imaging reconstruction. Magn Reson Med. 2014;72(6):1610–9. doi: 10.1002/mrm.25072 24347306.
32. Tang A, Tan J, Sun M, Hamilton G, Bydder M, Wolfson T, et al. Nonalcoholic fatty liver disease: MR imaging of liver proton density fat fraction to assess hepatic steatosis. Radiology. 2013;267(2):422–31. doi: 10.1148/radiol.12120896 23382291; PubMed Central PMCID: PMCPMC3632805.
33. Idilman IS, Aniktar H, Idilman R, Kabacam G, Savas B, Elhan A, et al. Hepatic steatosis: quantification by proton density fat fraction with MR imaging versus liver biopsy. Radiology. 2013;267(3):767–75. doi: 10.1148/radiol.13121360 23382293.
34. Serai SD, Smith EA, Trout AT, Dillman JR. Agreement between manual relaxometry and semi-automated scanner-based multi-echo Dixon technique for measuring liver T2* in a pediatric and young adult population. Pediatr Radiol. 2018;48(1):94–100. doi: 10.1007/s00247-017-3990-y 29058039.
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PLOS One
2019 Číslo 11
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