Korean J Radiol.  2019 Jan;20(1):126-133. 10.3348/kjr.2018.0174.

Fat Quantification in the Vertebral Body: Comparison of Modified Dixon Technique with Single-Voxel Magnetic Resonance Spectroscopy

Affiliations
  • 1Department of Radiology, Seoul National University Hospital, Seoul, Korea. dalnara3@gmail.com
  • 2Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.
  • 3Department of Radiological Science, College of Health Science, Gimcheon University, Gimcheon, Korea.
  • 4Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea.

Abstract


OBJECTIVE
To compare the lumbar vertebral bone marrow fat-signal fractions obtained from six-echo modified Dixon sequence (6-echo m-Dixon) with those from single-voxel magnetic resonance spectroscopy (MRS) in patients with low back pain.
MATERIALS AND METHODS
Vertebral bone marrow fat-signal fractions were quantified by 6-echo m-Dixon (repetition time [TR] = 7.2 ms, echo time (TE) = 1.21 ms, echo spacing = 1.1 ms, total imaging time = 50 seconds) and single-voxel MRS measurements in 25 targets (23 normal bone marrows, two focal lesions) from 24 patients. The point-resolved spectroscopy sequence was used for localized single-voxel MRS (TR = 3000 ms, TE = 35 ms, total scan time = 1 minute 42 seconds). A 2 × 2 × 1.5 cm³ voxel was placed within the normal L2 or L3 vertebral body, or other lesions including a compression fracture or metastasis. The bone marrow fat spectrum was characterized on the basis of the magnitude of measurable fat peaks and a priori knowledge of the chemical structure of triglycerides. The imaging-based fat-signal fraction results were then compared to the MRS-based results.
RESULTS
There was a strong correlation between m-Dixon and MRS-based fat-signal fractions (slope = 0.86, R² = 0.88, p < 0.001). In Bland-Altman analysis, 92.0% (23/25) of the data points were within the limits of agreement. Bland-Altman plots revealed a slight but systematic error in the m-Dixon based fat-signal fraction, which showed a prevailing overestimation of small fat-signal fractions (< 20%) and underestimation of high fat-signal fractions (> 20%).
CONCLUSION
Given its excellent agreement with single-voxel-MRS, 6-echo m-Dixon can be used for visual and quantitative evaluation of vertebral bone marrow fat in daily practice.

Keyword

Vertebra; Fat quantification; Modified Dixon; MR spectroscopy

MeSH Terms

Bone Marrow
Evaluation Studies as Topic
Fractures, Compression
Humans
Low Back Pain
Magnetic Resonance Spectroscopy*
Neoplasm Metastasis
Spectrum Analysis
Spine
Triglycerides
Triglycerides

Figure

  • Fig. 1 79-year-old man with acute osteoporotic compression fracture at L3 vertebral body.Median plane from sagittal T1-weighted image (A) shows acute compression fracture of L3 vertebral body with decreased bone marrow signals. Sagittal FF image derived from six-echo modified Dixon sequence method (B) shows decreased FF at affected L3 vertebra, with normal high FFs at other lumbar vertebral bodies. Two 2 × 1.5-cm2 regions-of-interest are shown on affected L3 vertebral body and normal L2 vertebral body. Sagittal (C) image showing 2 × 2 × 1.5-cm2 VOI placed on normal L2 vertebral body for MRS analysis. Another VOI of same size was placed at L3 vertebra (D). FF = fat fraction, MRS = magnetic resonance spectroscopy, VOI = volume of interest

  • Fig. 2 Typical MRS spectrum from normal L3 vertebral body of 42-year-old woman with nonspecific low back pain.Various peaks are indicated for fat at 0.90, 1.30, 1.59, 2.00, 2.25, 2.77, 4.20, and 5.31 ppm, and water peak is indicated at 4.65 ppm.

  • Fig. 3 Graph showing linear regression model for FFmrs versus FFdix measurements.Correlation coefficient R2 = 0.88, with p < 0.001. FFdix = magnetic resonance image-based FF, FFmrs = spectroscopy-based FF

  • Fig. 4 Bland-Altman plot showing mean measurement bias of 3.6% (FFmrs > FFdix), and limits of agreement ranging from −11% to 18%.Small systematic error is present with FFdix, which showed slight overestimation of small FF (< 20%) and underestimation of high FF (> 20%). Subject with smallest mean FF (arrow) shows overestimation of FFdix, whereas subject with second smallest mean FF (arrowhead) shows underestimation. SD = standard deviation


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