Korean J Radiol.  2019 Mar;20(3):438-448. 10.3348/kjr.2018.0310.

High Acceleration Three-Dimensional T1-Weighted Dual Echo Dixon Hepatobiliary Phase Imaging Using Compressed Sensing-Sensitivity Encoding: Comparison of Image Quality and Solid Lesion Detectability with the Standard T1-Weighted Sequence

• Nam JG
• Lee JM
• Lee SM
• Kang HJ
• Lee ES
• Hur BY
• Yoon JH
• Kim E
• Doneva M

• KMID: 2438274
• DOI: http://doi.org/10.3348/kjr.2018.0310

Abstract

OBJECTIVE
To compare a high acceleration three-dimensional (3D) T1-weighted gradient-recalled-echo (GRE) sequence using the combined compressed sensing (CS)-sensitivity encoding (SENSE) method with a conventional 3D GRE sequence using SENSE, with respect to image quality and detectability of solid focal liver lesions (FLLs) in the hepatobiliary phase (HBP) of gadoxetic acid-enhanced liver MRI.
MATERIALS AND METHODS
A total of 217 patients with gadoxetic acid-enhanced liver MRI at 3T (54 in the preliminary study and 163 in the main study) were retrospectively included. In the main study, HBP imaging was done twice using the standard mDixon-3D-GRE technique with SENSE (acceleration factor [AF]: 2.8, standard mDixon-GRE) and the high acceleration mDixon-3D GRE technique using the combined CS-SENSE technique (CS-SENSE mDixon-GRE). Two abdominal radiologists assessed the two MRI data sets for image quality in consensus. Three other abdominal radiologists independently assessed the diagnostic performance of each data set and its ability to detect solid FLLs in 117 patients with 193 solid nodules and compared them using jackknife alternative free-response receiver operating characteristics (JAFROC).
RESULTS
There was no significant difference in the overall image quality. CS-SENSE mDixon-GRE showed higher image noise, but lesser motion artifact levels compared with the standard mDixon-GRE (all p < 0.05). In terms of lesion detection, reader-averaged figures-of-merit estimated with JAFROC was 0.918 for standard mDixon-GRE, and 0.953 for CS-SENSE mDixon-GRE (p = 0.142). The non-inferiority of CS-SENSE mDixon-GRE over standard mDixon-GRE was confirmed (difference: 0.064 [−0.012, 0.081]).
CONCLUSION
The CS-SENSE mDixon-GRE HBP sequence provided comparable overall image quality and non-inferior solid FFL detectability compared with the standard mDixon-GRE sequence, with reduced acquisition time.

Keyword

Liver MRI; Compressed sensing; Sparse reconstruction; Parallel imaging; CS-SENSE; T1-weighted sequence

MeSH Terms

Acceleration*
Artifacts
Consensus
Dataset
Humans
Liver
Magnetic Resonance Imaging
Methods
Noise
Retrospective Studies
ROC Curve

Figure

• 

  Fig. 1 Flowchart of inclusion and exclusion criteria of our main study population.CS = compressed sensing, GRE = gradient-recalled-echo, HBP = hepatobiliary phase, SENSE = sensitivity coding, 3D = three-dimensional

• 

  Fig. 2 59-year-old male patient who had undergone liver segmentectomy due to HCC underwent gadoxetic acid-enhanced MRI for surveillance of recurrence of HCC.HBP standard mDixon-GRE image (A) shows severe motion artifacts (score 2) resulting in image blurring, and similar level of motion artifacts is also seen on other phases of standard mDixon-GRE images (C). Motion artifact level was significantly decreased to score of 4 on HBP CS-SENSE mDixon-GRE image (B) although image noise is more prominent than on standard mDixon-GRE image. HCC = hepatocellular carcinoma

• 

  Fig. 3 75-year-old female patient with multiple lesions of HCC.Standard mDixon-GRE image obtained during HBP (A) shows severe motion artifacts (score 2). Contrarily, motion artifacts are significantly decreased to score of 4 on HBP CS-SENSE mDixon-GRE image (B). Note that CS-SENSE mDixon-GRE image demonstrates better lesion conspicuity as well as depiction of intrahepatic vessels and intrahepatic bile ducts. Similar level of motion artifacts was also demonstrated on portal venous phase image with standard mDixon-GRE images (C), representing limited breath-holding capacity of patient.

• 

  Fig. 4 65-year-old male patient with multiple HCCs.Standard mDixon-GRE image (A) and CS-SENSE mDixon-GRE image (B) obtained during HBP showed similar level of motion artifact (both score 3). However, aliasing artifact was more prominent in CS-SENSE mDixon-GRE image (B, arrowheads).

Reference

1. Bangiyev L, Raz E, Block TK, Hagiwara M, Wu X, Yu E, et al. Evaluation of the orbit using contrast-enhanced radial 3D fat-suppressed T-1 weighted gradient echo (radial-VIBE) sequence. Br J Radiol. 2015; 88:20140863. PMID: 26194589.

2. Breuer FA, Blaimer M, Heidemann RM, Mueller MF, Griswold MA, Jakob PM. Controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA) for multi-slice imaging. Magn Reson Med. 2005; 53:684–691. PMID: 15723404.

3. Breuer FA, Blaimer M, Mueller MF, Seiberlich N, Heidemann RM, Griswold MA, et al. Controlled aliasing in volumetric parallel imaging (2D CAIPIRINHA). Magn Reson Med. 2006; 55:549–556. PMID: 16408271.

4. Runge VM, Richter JK, Heverhagen JT. Speed in clinical magnetic resonance. Invest Radiol. 2017; 52:1–17. PMID: 27828787.

5. Bruix J, Sherman M. American Association for the Study of Liver Disease. Management of hepatocellular carcinoma: an update. Hepatology. 2011; 53:1020–1022. PMID: 21374666.

6. European Association for the Study of the Liver, European Organisation for Research and Treatment of Cancer. EASL-EORTC clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol. 2012; 56:908–943. PMID: 22424438.

7. Liver imaging reporting and data system (LI-RADS). Acr.org Web site. Published July 2018. Accessed August 29, 2018. https://www.acr.org/Clinical-Resources/Reporting-and-Data-Systems/LI-RADS.

8. Yoon JH, Park JW, Lee JM. Noninvasive diagnosis of hepatocellular carcinoma: elaboration on Korean Liver Cancer Study Group-National Cancer Center Korea practice guidelines compared with other guidelines and remaining issues. Korean J Radiol. 2016; 17:7–24. PMID: 26798212.

9. Jaspan ON, Fleysher R, Lipton ML. Compressed sensing MRI: a review of the clinical literature. Br J Radiol. 2015; 88:20150487. PMID: 26402216.

10. Feng L, Benkert T, Block KT, Sodickson DK, Otazo R, Chandarana H. Compressed sensing for body MRI. J Magn Reson Imaging. 2017; 45:966–987. PMID: 27981664.

11. Yang AC, Kretzler M, Sudarski S, Gulani V, Seiberlich N. Sparse reconstruction techniques in magnetic resonance imaging: methods, applications, and challenges to clinical adoption. Invest Radiol. 2016; 51:349–364. PMID: 27003227.

12. McGibney G, Smith MR, Nichols ST, Crawley A. Quantitative-evaluation of several partial Fourier reconstruction algorithms used in MRI. Magn Reson Med. 1993; 30:51–59. PMID: 8371675.

13. Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P. SENSE: sensitivity encoding for fast MRI. Magn Reson Med. 1999; 42:952–962. PMID: 10542355.

14. Griswold MA, Jakob PM, Heidemann RM, Nittka M, Jellus V, Wang JM, et al. Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magn Reson Med. 2002; 47:1202–1210. PMID: 12111967.

15. Liang D, Liu B, Wang J, Ying L. Accelerating SENSE using compressed sensing. Magn Reson Med. 2009; 62:1574–1584. PMID: 19785017.

16. Lustig M, Donoho D, Pauly JM. Sparse MRI: the application of compressed sensing for rapid MR imaging. Magn Reson Med. 2007; 58:1182–1195. PMID: 17969013.

17. Glockner JF, Hu HH, Stanley DW, Angelos L, King K. Parallel MR imaging: a user's guide. Radiographics. 2005; 25:1279–1297. PMID: 16160112.

18. Wright KL, Harrell MW, Jesberger JA, Landeras L, Nakamoto DA, Thomas S, et al. Clinical evaluation of CAIPIRINHA: comparison against a GRAPPA standard. J Magn Reson Imaging. 2014; 39:189–194. PMID: 24123420.

19. Sodickson DK, Manning WJ. Simultaneous acquisition of spatial harmonics (SMASH): fast imaging with radiofrequency coil arrays. Magn Reson Med. 1997; 38:591–603. PMID: 9324327.

20. Liu F, Duan Y, Peterson BS, Kangarlu A. Compressed sensing MRI combined with SENSE in partial k-space. Phys Med Biol. 2012; 57:N391–N403. PMID: 23073235.

21. Vasanawala SS, Alley MT, Hargreaves BA, Barth RA, Pauly JM, Lustig M. Improved pediatric MR imaging with compressed sensing. Radiology. 2010; 256:607–616. PMID: 20529991.

22. Candès EJ, Romberg J, Tao T. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Trans Inf Theory. 2006; 52:489–509.

23. Donoho DL. Compressed sensing. IEEE Trans Inf Theory. 2006; 52:1289–1306.

24. Lustig M, Donoho DL, Santos JM, Pauly JM. Compressed sensing MRI. IEEE Signal Process Mag. 2008; 25:72–82.

25. Hollingsworth KG. Reducing acquisition time in clinical MRI by data undersampling and compressed sensing reconstruction. Phys Med Biol. 2015; 60:R297–R322. PMID: 26448064.

26. Chandarana H, Feng L, Block TK, Rosenkrantz AB, Lim RP, Babb JS, et al. Free-breathing contrast-enhanced multiphase MRI of the liver using a combination of compressed sensing, parallel imaging, and golden-angle radial sampling. Invest Radiol. 2013; 48:10–16. PMID: 23192165.

27. Runge VM. Current technological advances in magnetic resonance with critical impact for clinical diagnosis and therapy. Invest Radiol. 2013; 48:869–877. PMID: 24126386.

28. Chandarana H, Feng L, Ream J, Wang A, Babb JS, Block KT, et al. Respiratory motion-resolved compressed sensing reconstruction of free-breathing radial acquisition for dynamic liver MRI. Invest Radiol. 2015; 50:749–756. PMID: 26146869.

29. Lee YJ, Lee JM, Lee JS, Lee HY, Park BH, Kim YH, et al. Hepatocellular carcinoma: diagnostic performance of multidetector CT and MR imaging-a systematic review and meta-analysis. Radiology. 2015; 275:97–109. PMID: 25559230.

30. Niekel MC, Bipat S, Stoker J. Diagnostic imaging of colorectal liver metastases with CT, MR imaging, FDG PET, and/or FDG PET/CT: a meta-analysis of prospective studies including patients who have not previously undergone treatment. Radiology. 2010; 257:674–684. PMID: 20829538.

31. Guo J, Seo Y, Ren S, Hong S, Lee D, Kim S, et al. Diagnostic performance of contrast-enhanced multidetector computed tomography and gadoxetic acid disodium-enhanced magnetic resonance imaging in detecting hepatocellular carcinoma: direct comparison and a meta-analysis. Abdom Radiol (NY). 2016; 41:1960–1197. PMID: 27318936.

32. Yoon JH, Lee JM, Yu MH, Kim EJ, Han JK, Choi BI. High-resolution T1-weighted gradient echo imaging for liver MRI using parallel imaging at high-acceleration factors. Abdom Imaging. 2014; 39:711–721. PMID: 24557640.

33. Takayama Y, Nishie A, Asayama Y, Ishigami K, Kakihara D, Nakayama T, et al. Image quality of Gd-EOB-DTPA-enhanced magnetic resonance imaging of the liver using dual-source parallel radiofrequency transmission technology: comparison with the post-processing correction method for B1 inhomogeneity-induced signal loss. Eur J Radiol. 2012; 81:3035–3040. PMID: 22578836.

34. Rahbar H, Partridge SC, DeMartini WB, Gutierrez RL, Parsian S, Lehman CD. Improved B1 homogeneity of 3 tesla breast MRI using dual-source parallel radiofrequency excitation. J Magn Reson Imaging. 2012; 35:1222–1226. PMID: 22282269.

35. Lum DP, Busse RF, Francois CJ, Brau AC, Beatty PJ, Huff J, et al. Increased volume of coverage for abdominal contrast-enhanced MR angiography with two-dimensional autocalibrating parallel imaging: initial experience at 3.0 tesla. J Magn Reson Imaging. 2009; 30:1093–1110. PMID: 19856443.

36. Mostardi PM, Glockner JF, Young PM, Riederer SJ. Contrast-enhanced MR angiography of the abdomen with highly accelerated acquisition techniques. Radiology. 2011; 261:587–597. PMID: 21900616.

37. Nael K, Ruehm SG, Michaely HJ, Pope W, Laub G, Finn JP, et al. High spatial-resolution CE-MRA of the carotid circulation with parallel imaging: comparison of image quality between 2 different acceleration factors at 3.0 tesla. Invest Radiol. 2006; 41:391–339. PMID: 16523022.

38. Morakkabati-Spitz N, Gieseke J, Kuhl C, Lutterbey G, von Falkenhausen M, Träber F, et al. MRI of the pelvis at 3T: very high spatial resolution with sensitivity encoding and flip-angle sweep technique in clinically acceptable scan time. Eur Radiol. 2006; 16:634–641. PMID: 16228214.

39. McClellan TR, Motosugi U, Middleton MS, Allen BC, Jaffe TA, Miller CM, et al. Intravenous gadoxetate disodium administration reduces breath-holding capacity in the hepatic arterial phase: a multi-center randomized placebo-controlled trial. Radiology. 2016; 282:361–368. PMID: 27509544.

40. Fletcher JG, Yu L, Li Z, Manduca A, Blezek DJ, Hough DM, et al. Observer performance in the detection and classification of malignant hepatic nodules and masses with CT image-space denoising and iterative reconstruction. Radiology. 2015; 276:465–478. PMID: 26020436.

41. Lee SJ, Park SH, Kim AY, Yang SK, Yun SC, Lee SS, et al. A prospective comparison of standard-dose CT enterography and 50% reduced-dose CT enterography with and without noise reduction for evaluating Crohn disease. AJR Am J Roentgenol. 2011; 197:50–57. PMID: 21701010.

42. Zhang T, Chowdhury S, Lustig M, Barth RA, Alley MT, Grafendorfer T, et al. Clinical performance of contrast enhanced abdominal pediatric MRI with fast combined parallel imaging compressed sensing reconstruction. J Magn Reson Imaging. 2014; 40:13–25. PMID: 24127123.

43. Sharma SD, Fong CL, Tzung BS, Law M, Nayak KS. Clinical quality assessment of accelerated magnetic resonance neuroimaging using compressed sensing. Invest Radiol. 2013; 48:638–645. PMID: 23538890.

44. Worters PW, Sung K, Stevens KJ, Koch KM, Hargreaves BA. Compressed-sensing multispectral imaging of the postoperative spine. J Magn Reson Imaging. 2013; 37:243–248. PMID: 22791572.

45. Park YS, Lee CH, Kim IS, Kiefer B, Woo ST, Kim KA, et al. Usefulness of controlled aliasing in parallel imaging results in higher acceleration in gadoxetic acid-enhanced liver magnetic resonance imaging to clarify the hepatic arterial phase. Invest Radiol. 2014; 49:183–188. PMID: 24276676.

46. Zhang T, Cheng JY, Potnick AG, Barth RA, Alley MT, Uecker M, et al. Fast pediatric 3D free-breathing abdominal dynamic contrast enhanced MRI with high spatiotemporal resolution. J Magn Reson Imaging. 2015; 41:460–473. PMID: 24375859.