Fat fraction and R2 * values of various liver masses: Initial experience with 6-point Dixon method on a 3T MRI system

Taichi Kitagawa, Kazuto Kozaka, Takashi Matsubara, Tetsuya Wakayama, Atsushi Takamatsu, Tomohiro Kobayashi, Kenichiro Okumura, Kotaro Yoshida, Norihide Yoneda, Azusa Kitao, Satoshi Kobayashi, Toshifumi Gabata, Osamu Matsui, Jay P. Heiken

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: To assess the feasibility of the 6-point Dixon method for evaluating liver masses. We also report our initial experience with the quantitative values in various liver masses on a 3T system. Materials and methods: Of 251 consecutive patients for whom 6-point Dixon was employed in abdominal magnetic resonance imaging scans between October 2020 and October 2021, 117 nodules in 117 patients with a mass diameter of more than 1 cm were included in the study. Images for measuring the proton density fat fraction (PDFF) and R2 * values were obtained using the iterative decomposition of water and fat with echo asymmetry and least-squares estimation-quantitative technique for liver imaging. Two radiologists independently measured PDFF (%) and R2 * (Hz). Inter-reader agreement and the differences between readers were examined using intra-class correlation coefficient (ICC) and the Bland-Altman method, respectively. PDFF and R2 * values in differentiating liver masses were examined. Results: The masses included hepatocellular carcinoma (n = 59), cyst (n = 20), metastasis (n = 14), hemangioma (n = 8), and others (n = 16). The ICCs for the region of interest (mm2), PDFF, and R2 * were 0.988 (95 % confidence interval (CI): 0.983, 0.992), 0.964 (95 % CI: 0.949, 0.975), and 0.962 (95 % CI: 0.941, 0.975), respectively. The differences of measurements between the readers showed that 5.1 % (6/117) and 6.0% (7/117) for PDFF and R2 *, respectively, were outside the 95 % CI. Conclusion: Our observation indicates that the 6-point Dixon method is applicable to liver masses.

Original languageEnglish (US)
Article number100519
JournalEuropean Journal of Radiology Open
Volume11
DOIs
StatePublished - Dec 2023

Keywords

  • Chemical shift imaging
  • Chemotherapy
  • Image enhancement
  • Lipid droplets
  • Liver neoplasms

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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