Application and research progress of magnetic resonance imaging lipid detection techniques in abdomen and pelvis_CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Authors：

CAO Likun , CHU Lei , HUANG Zixing ,  SONG Bin

Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;

Corresponding author：

SONG Bin, Email: anicesong@vip.sina.com

Keywords：

adipose tissue; magnetic resonance imaging; magnetic resonance spectroscopy; abdominal and pelvic disease

DOI：

10.7507/1007-9424.201707083

Video：

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Objective To summarize applications and research progress of common magnetic resonance imaging lipid detection techniques in abdomen and pelvis. Method The latest domestic and foreign research literatures related to the applications and research progress of common magnetic resonance imaging lipid detection techniques in the abdomen and pelvis in recent years were collected and reviewed. Results The fat-selective spectral-spatial imaging, ¹H-magnetic resonance spectroscopy (¹H-MRS), and Dixon & IDEAL are three main magnetic resonance imaging lipid detection techniques, and they can estimate the fat content in the normal tissues and lesions noninvasively and longitudinally, which make the ectopic fat-induced diseases’ early diagnosis, treatment and follow-up possible. Conclusion Magnetic resonance imaging lipid detection techniques have obvious clinical values in quantitative measurement of fat content, and each method gets its own advantage, especially modified Dixon, which is more convenient and accurate and shows an enormous potential in clinical practice.

Citation： CAO Likun, CHU Lei, HUANG Zixing, SONG Bin. Application and research progress of magnetic resonance imaging lipid detection techniques in abdomen and pelvis. CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY, 2017, 24(10): 1269-1274. doi: 10.7507/1007-9424.201707083 Copy

1.	Springer F, Ehehalt S, Sommer J, et al. Assessment of relevant hepatic steatosis in obese adolescents by rapid fat-selective GRE imaging with spatial-spectral excitation: a quantitative comparison with spectroscopic findings. Eur Radiol, 2011, 21(4): 816-822.
2.	Reeder SB, Cruite I, Hamilton G, et al. Quantitative assessment of liver fat with magnetic resonance imaging and spectroscopy. J Magn Reson Imaging, 2011, 34(4): spcone.
3.	赵黎明, 宋彬, 陈光文, 等. 肝脏脂肪含量MRI定量诊断与病理对照研究. 中国普外基础与临床杂志, 2011, 18(6): 666-671.0.
4.	Thomas EL, Hamilton G, Patel N, et al. Hepatic triglyceride content and its relation to body adiposity: a magnetic resonance imaging and proton magnetic resonance spectroscopy study. Gut, 2005, 54(1): 122-127.
5.	Dixon WT. Simple proton spectroscopic imaging. Radiology, 1984, 153(1): 189-194.
6.	Glover GH, Schneider E. Three-point Dixon technique for true water/fat decomposition with B0 inhomogeneity correction. Magn Reson Med, 1991, 18(2): 371-383.
7.	Reeder SB, Pineda AR, Wen Z, et al. Iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL): application with fast spin-echo imaging. Magn Reson Med, 2005, 54(3): 636-644.
8.	范建高, 曾民德. 脂肪肝的研究进展. 胃肠病学和肝病学杂志, 1999, 8(2): 149-160.0.
9.	Leiber LM, Boursier J, Michalak S, et al. MRI versus histological methods for time course monitoring of steatosis amount in a murine model of NAFLD. Diagn Interv Imaging, 2015, 96(9): 915-922.
10.	Tang A, Tan J, Sun M, et al. Nonalcoholic fatty liver disease: MR imaging of liver proton density fat fraction to assess hepatic steatosis. Radiology, 2013, 267(2): 422-431.
11.	Noureddin M, Lam J, Peterson MR, et al. Utility of magnetic resonance imaging versus histology for quantifying changes in liver fat in nonalcoholic fatty liver disease trials. Hepatology, 2013, 58(6): 1930-1940.
12.	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.
13.	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.
14.	Sumida Y, Nakajima A, Itoh Y. Limitations of liver biopsy and non-invasive diagnostic tests for the diagnosis of nonalcoholic fatty liver disease/nonalcoholic steatohepatitis. World J Gastroenterol, 2014, 20(2): 475-485.
15.	Siripongsakun S, Lee JK, Raman SS, et al. MRI detection of intratumoral fat in hepatocellular carcinoma: potential biomarker for a more favorable prognosis. AJR Am J Roentgenol, 2012, 199(5): 1018-1025.
16.	Barth BK, Fischer MA, Kambakamba P, et al. Liver-fat and liver-function indices derived from Gd-EOB-DTPA-enhanced liver MRI for prediction of future liver remnant growth after portal vein occlusion. Eur J Radiol, 2016, 85(4): 843-849.
17.	Hu HH, Kim HW, Nayak KS, et al. Comparison of fat-water MRI and single-voxel MRS in the assessment of hepatic and pancreatic fat fractions in humans. Obesity (Silver Spring), 2010, 18(4): 841-847.
18.	Li J, Xie Y, Yuan F, et al. Noninvasive quantification of pancreatic fat in healthy male population using chemical shift magnetic resonance imaging: effect of aging on pancreatic fat content. Pancreas, 2011, 40(2): 295-299.
19.	Kühn JP, Berthold F, Mayerle J, et al. Pancreatic steatosis demonstrated at MR imaging in the general population: clinical relevance. Radiology, 2015, 276(1): 129-136.
20.	Idilman IS, Tuzun A, Savas B, et al. Quantification of liver, pancreas, kidney, and vertebral body MRI-PDFF in non-alcoholic fatty liver disease. Abdom Imaging, 2015, 40(6): 1512-1519.
21.	Kim HJ, Byun JH, Park SH, et al. Focal fatty replacement of the pancreas: usefulness of chemical shift MRI. AJR Am J Roentgenol, 2007, 188(2): 429-432.
22.	Heni M, Machann J, Staiger H, et al. Pancreatic fat is negatively associated with insulin secretion in individuals with impaired fasting glucose and/or impaired glucose tolerance: a nuclear magnetic resonance study. Diabetes Metab Res Rev, 2010, 26(3): 200-205.
23.	Maggio AB1, Mueller P, Wacker J, et al. Increased pancreatic fat fraction is present in obese adolescents with metabolic syndrome. J Pediatr Gastroenterol Nutr, 2012, 54(6): 720-726.
24.	Cohen M, Syme C, Deforest M, et al. Ectopic fat in youth: the contribution of hepatic and pancreatic fat to metabolic disturbances. Obesity (Silver Spring), 2014, 22(5): 1280-1286.
25.	Dong Z, Luo Y, Cai H, et al. Noninvasive fat quantification of the liver and pancreas may provide potential biomarkers of impaired glucose tolerance and type 2 diabetes. Medicine (Baltimore), 2016, 95(23): e3858.
26.	Lee Y, Lingvay I, Szczepaniak LS, et al. Pancreatic steatosis: harbinger of type 2 diabetes in obese rodents. Int J Obes (Lond), 2010, 34(2): 396-400.
27.	Pacifico L, Di Martino M, Anania C, et al. Pancreatic fat and β-cell function in overweight/obese children with nonalcoholic fatty liver disease. World J Gastroenterol, 2015, 21(15): 4688-4695.
28.	van der Zijl NJ, Goossens GH, Moors CC, et al. Ectopic fat storage in the pancreas, liver, and abdominal fat depots: impact on β-cell function in individuals with impaired glucose metabolism. J Clin Endocrinol Metab, 2011, 96(2): 459-467.
29.	Saisho Y, Butler AE, Meier JJ, et al. Pancreas volumes in humans from birth to age one hundred taking into account sex, obesity, and presence of type-2 diabetes. Clin Anat, 2007, 20(8): 933-942.
30.	Murakami R, Saisho Y, Watanabe Y, et al. Pancreas fat and beta cell mass in humans with and without diabetes: An analysis in the Japanese population. J Clin Endocrinol Metab, 2017 Jun 14. doi: 10.1210/jc.2017-00828.[Epub ahead of print].
31.	Lee SE, Jang JY, Lim CS, et al. Measurement of pancreatic fat by magnetic resonance imaging: predicting the occurrence of pancreatic fistula after pancreatoduodenectomy. Ann Surg, 2010, 251(5): 932-936.
32.	Marin D, Soher BJ, Dale BM, et al. Characterization of adrenal lesions: comparison of 2D and 3D dual gradient-echo MR imaging at 3 T—preliminary results. Radiology, 2010, 254(1): 179-187.
33.	Ramalho M, de Campos RO, Heredia V, et al. Characterization of adrenal lesions with 1.5-T MRI: preliminary observations on comparison of three in-phase and out-of-phase gradient-echo techniques. AJR Am J Roentgenol, 2011, 197(2): 415-423.
34.	Meng X, Chen X, Shen Y, et al. Proton-density fat fraction measurement: A viable quantitative biomarker for differentiating adrenal adenomas from nonadenomas. Eur J Radiol, 2017, 86: 112-118.
35.	Woo S, Cho JY, Kim SY, et al. Adrenal adenoma and metastasis from clear cell renal cell carcinoma: can they be differentiated using standard MR techniques? Acta Radiol, 2014, 55(9): 1120-1128.
36.	Kim JK, Kim SH, Jang YJ, et al. Renal angiomyolipoma with minimal fat: differentiation from other neoplasms at double-echo chemical shift FLASH MR imaging. Radiology, 2006, 239(1): 174-180.
37.	Sasiwimonphan K, Takahashi N, Leibovich BC, et al. Small (<4 cm) renal mass: differentiation of angiomyolipoma without visible fat from renal cell carcinoma utilizing MR imaging. Radiology, 2012, 263(1): 160-168.
38.	Dillon RC, Friedman AC, Miller FH. MR signal intensity calculations are not reliable for differentiating renal cell carcinoma from lipid poor angiomyolipoma. Radiology, 2010, 257(1): 299-300.
39.	Jeong CJ, Park BK, Park JJ, et al. Unenhanced CT and MRI parameters that can be used to reliably predict fat-invisible angiomyolipoma. AJR Am J Roentgenol, 2016, 206(2): 340-347.
40.	Song S, Park BK, Park JJ. New radiologic classification of renal angiomyolipomas. Eur J Radiol, 2016, 85(10): 1835-1842.

1. Springer F, Ehehalt S, Sommer J, et al. Assessment of relevant hepatic steatosis in obese adolescents by rapid fat-selective GRE imaging with spatial-spectral excitation: a quantitative comparison with spectroscopic findings. Eur Radiol, 2011, 21(4): 816-822.
2. Reeder SB, Cruite I, Hamilton G, et al. Quantitative assessment of liver fat with magnetic resonance imaging and spectroscopy. J Magn Reson Imaging, 2011, 34(4): spcone.
3. 赵黎明, 宋彬, 陈光文, 等. 肝脏脂肪含量MRI定量诊断与病理对照研究. 中国普外基础与临床杂志, 2011, 18(6): 666-671.0.
4. Thomas EL, Hamilton G, Patel N, et al. Hepatic triglyceride content and its relation to body adiposity: a magnetic resonance imaging and proton magnetic resonance spectroscopy study. Gut, 2005, 54(1): 122-127.
5. Dixon WT. Simple proton spectroscopic imaging. Radiology, 1984, 153(1): 189-194.
6. Glover GH, Schneider E. Three-point Dixon technique for true water/fat decomposition with B0 inhomogeneity correction. Magn Reson Med, 1991, 18(2): 371-383.
7. Reeder SB, Pineda AR, Wen Z, et al. Iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL): application with fast spin-echo imaging. Magn Reson Med, 2005, 54(3): 636-644.
8. 范建高, 曾民德. 脂肪肝的研究进展. 胃肠病学和肝病学杂志, 1999, 8(2): 149-160.0.
9. Leiber LM, Boursier J, Michalak S, et al. MRI versus histological methods for time course monitoring of steatosis amount in a murine model of NAFLD. Diagn Interv Imaging, 2015, 96(9): 915-922.
10. Tang A, Tan J, Sun M, et al. Nonalcoholic fatty liver disease: MR imaging of liver proton density fat fraction to assess hepatic steatosis. Radiology, 2013, 267(2): 422-431.
11. Noureddin M, Lam J, Peterson MR, et al. Utility of magnetic resonance imaging versus histology for quantifying changes in liver fat in nonalcoholic fatty liver disease trials. Hepatology, 2013, 58(6): 1930-1940.
12. 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.
13. 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.
14. Sumida Y, Nakajima A, Itoh Y. Limitations of liver biopsy and non-invasive diagnostic tests for the diagnosis of nonalcoholic fatty liver disease/nonalcoholic steatohepatitis. World J Gastroenterol, 2014, 20(2): 475-485.
15. Siripongsakun S, Lee JK, Raman SS, et al. MRI detection of intratumoral fat in hepatocellular carcinoma: potential biomarker for a more favorable prognosis. AJR Am J Roentgenol, 2012, 199(5): 1018-1025.
16. Barth BK, Fischer MA, Kambakamba P, et al. Liver-fat and liver-function indices derived from Gd-EOB-DTPA-enhanced liver MRI for prediction of future liver remnant growth after portal vein occlusion. Eur J Radiol, 2016, 85(4): 843-849.
17. Hu HH, Kim HW, Nayak KS, et al. Comparison of fat-water MRI and single-voxel MRS in the assessment of hepatic and pancreatic fat fractions in humans. Obesity (Silver Spring), 2010, 18(4): 841-847.
18. Li J, Xie Y, Yuan F, et al. Noninvasive quantification of pancreatic fat in healthy male population using chemical shift magnetic resonance imaging: effect of aging on pancreatic fat content. Pancreas, 2011, 40(2): 295-299.
19. Kühn JP, Berthold F, Mayerle J, et al. Pancreatic steatosis demonstrated at MR imaging in the general population: clinical relevance. Radiology, 2015, 276(1): 129-136.
20. Idilman IS, Tuzun A, Savas B, et al. Quantification of liver, pancreas, kidney, and vertebral body MRI-PDFF in non-alcoholic fatty liver disease. Abdom Imaging, 2015, 40(6): 1512-1519.
21. Kim HJ, Byun JH, Park SH, et al. Focal fatty replacement of the pancreas: usefulness of chemical shift MRI. AJR Am J Roentgenol, 2007, 188(2): 429-432.
22. Heni M, Machann J, Staiger H, et al. Pancreatic fat is negatively associated with insulin secretion in individuals with impaired fasting glucose and/or impaired glucose tolerance: a nuclear magnetic resonance study. Diabetes Metab Res Rev, 2010, 26(3): 200-205.
23. Maggio AB1, Mueller P, Wacker J, et al. Increased pancreatic fat fraction is present in obese adolescents with metabolic syndrome. J Pediatr Gastroenterol Nutr, 2012, 54(6): 720-726.
24. Cohen M, Syme C, Deforest M, et al. Ectopic fat in youth: the contribution of hepatic and pancreatic fat to metabolic disturbances. Obesity (Silver Spring), 2014, 22(5): 1280-1286.
25. Dong Z, Luo Y, Cai H, et al. Noninvasive fat quantification of the liver and pancreas may provide potential biomarkers of impaired glucose tolerance and type 2 diabetes. Medicine (Baltimore), 2016, 95(23): e3858.
26. Lee Y, Lingvay I, Szczepaniak LS, et al. Pancreatic steatosis: harbinger of type 2 diabetes in obese rodents. Int J Obes (Lond), 2010, 34(2): 396-400.
27. Pacifico L, Di Martino M, Anania C, et al. Pancreatic fat and β-cell function in overweight/obese children with nonalcoholic fatty liver disease. World J Gastroenterol, 2015, 21(15): 4688-4695.
28. van der Zijl NJ, Goossens GH, Moors CC, et al. Ectopic fat storage in the pancreas, liver, and abdominal fat depots: impact on β-cell function in individuals with impaired glucose metabolism. J Clin Endocrinol Metab, 2011, 96(2): 459-467.
29. Saisho Y, Butler AE, Meier JJ, et al. Pancreas volumes in humans from birth to age one hundred taking into account sex, obesity, and presence of type-2 diabetes. Clin Anat, 2007, 20(8): 933-942.
30. Murakami R, Saisho Y, Watanabe Y, et al. Pancreas fat and beta cell mass in humans with and without diabetes: An analysis in the Japanese population. J Clin Endocrinol Metab, 2017 Jun 14. doi: 10.1210/jc.2017-00828.[Epub ahead of print].
31. Lee SE, Jang JY, Lim CS, et al. Measurement of pancreatic fat by magnetic resonance imaging: predicting the occurrence of pancreatic fistula after pancreatoduodenectomy. Ann Surg, 2010, 251(5): 932-936.
32. Marin D, Soher BJ, Dale BM, et al. Characterization of adrenal lesions: comparison of 2D and 3D dual gradient-echo MR imaging at 3 T—preliminary results. Radiology, 2010, 254(1): 179-187.
33. Ramalho M, de Campos RO, Heredia V, et al. Characterization of adrenal lesions with 1.5-T MRI: preliminary observations on comparison of three in-phase and out-of-phase gradient-echo techniques. AJR Am J Roentgenol, 2011, 197(2): 415-423.
34. Meng X, Chen X, Shen Y, et al. Proton-density fat fraction measurement: A viable quantitative biomarker for differentiating adrenal adenomas from nonadenomas. Eur J Radiol, 2017, 86: 112-118.
35. Woo S, Cho JY, Kim SY, et al. Adrenal adenoma and metastasis from clear cell renal cell carcinoma: can they be differentiated using standard MR techniques? Acta Radiol, 2014, 55(9): 1120-1128.
36. Kim JK, Kim SH, Jang YJ, et al. Renal angiomyolipoma with minimal fat: differentiation from other neoplasms at double-echo chemical shift FLASH MR imaging. Radiology, 2006, 239(1): 174-180.
37. Sasiwimonphan K, Takahashi N, Leibovich BC, et al. Small (<4 cm) renal mass: differentiation of angiomyolipoma without visible fat from renal cell carcinoma utilizing MR imaging. Radiology, 2012, 263(1): 160-168.
38. Dillon RC, Friedman AC, Miller FH. MR signal intensity calculations are not reliable for differentiating renal cell carcinoma from lipid poor angiomyolipoma. Radiology, 2010, 257(1): 299-300.
39. Jeong CJ, Park BK, Park JJ, et al. Unenhanced CT and MRI parameters that can be used to reliably predict fat-invisible angiomyolipoma. AJR Am J Roentgenol, 2016, 206(2): 340-347.
40. Song S, Park BK, Park JJ. New radiologic classification of renal angiomyolipomas. Eur J Radiol, 2016, 85(10): 1835-1842.

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Application and research progress of magnetic resonance imaging lipid detection techniques in abdomen and pelvis

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