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Accumulated Hepatic Steatosis Grades Predicted by T2*-IDEAL Fat Fraction

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Abstract

Purpose

1H Magnetic resonance spectroscopy (MRS) is currently considered to be the standard for MR-based fat quantification without the need of histopathologic correlation. The purpose of this prospective study was to examine whether T2*-iterative decomposition of water and fat with echo asymmetry and least squares estimation (T2*-IDEAL) technique accurately predicts different hepatic steatosis grades.

Methods

Hepatic fat fraction was quantified by 1H MRS and T2*-IDEAL methods. Geometric homogeneity, intraobserver reliability, and interobserver agreement were examined for T2*-IDEAL method. The relationship between fat fraction measured by T2*I-DEAL (FFIDEAL) and that measured by 1H MRS (FFMRS) was examined by linear regression analysis. Based on 1H MRS, accumulated hepatic steatosis grade including HSF5, HSF15, HSF30, and HSF60, representing hepatic steatosis with fat fraction no less than 5%, 15%, 30%, and 60%, respectively, were calculated. Body mass index and FFIDEAL were used to predict the accumulated hepatic steatosis grade, respectively.

Results

FFMRS and FFIDEAL were 16.36% ± 12.96 and 15.57% ± 11.13, respectively. Linear regression analysis showed that the FFIDEAL was significantly and positively associated with FFMRS (y = 0.8226x + 2.1068, R2 = 0.9181, p < 0.001). The percentage error of FFIDEAL was − 5.2% ± 22.2% for HSF5. FFIDEAL and BMI predicted hepatic steatosis grade HSF5, HSF15, and HSF30 with an AUC of 0.988, 0.967, and 0.996 (all p = 0.0001) for FFIDEAL and 0.742, 0.836, and 0.883 (all p < 0.01) for BMI, respectively.

Conclusion

T2*-IDEAL method accurately predicts the accumulated hepatic steatosis grades with high intraobserver reliability, interobserver agreement, and geometric homogeneity.

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Acknowledgements

The authors thank Yan-Chang Chen for his assistance in performing MRI experiments.

Funding

No funding was received for this research.

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Authors and Affiliations

  1. Department of Medical Imaging, China Medical University Hsinchu Hospital and China Medical University, Hsinchu, Taiwan

    Chang-Hsien Liu, Chi-Feng Hsieh & Chun-Jung Juan

  2. Department of Radiology, Tri-Service General Hospital and National Defense Medical Center, Taipei, Taiwan

    Chang-Hsien Liu

  3. Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong, China

    Hing-Chiu Chang

  4. Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan

    Yi-Jui Liu & Cheng-Hsuan Juan

  5. Department of Medical Imaging, China Medical University Hospital, Taichung, Taiwan

    Wei-Ching Lin & Chun-Jung Juan

  6. Department of Biomedical Imaging and Radiological Science, China Medical University, Taichung, Taiwan

    Wei-Ching Lin

  7. Department of Radiology, Armed Forces General Hospital, Kaohsiung, Taiwan

    Te-Pao Lin

  8. 6-year English Language Program, Department of Medicine, Medical University of Lublin, Lublin, Poland

    Cheng-Hsuan Juan

  9. Department of Surgery, School of Medicine, China Medical University, Taichung, Taiwan

    William Tzu-Liang

  10. Department of Surgery, China Medical University Hsinchu Hospital, Hsinchu, Taiwan

    William Tzu-Liang

  11. Department of Radiology, School of Medicine, China Medical University, Taichung, Taiwan

    Chun-Jung Juan

  12. Department of Biomedical Engineering, National Defense Medical Center, Taipei, Taiwan

    Chun-Jung Juan

  13. Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan

    Chun-Jung Juan

  14. Department of Medical Imaging, China Medical University Hsinchu Hospital, No. 199, Sec. 1, Xinglong Rd., Hsinchu County, Zhubei City, 302, Taiwan

    Chun-Jung Juan

  15. Institute of Nuclear Engineering and Science, National Tsing Hua University, Hsinchu, Taiwan

    Chang-Hsien Liu

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Contributions

Conception and design—C-HL and C-JJ; collection and assembly of data—C-HL, H-CC, W-CL, T-PL, and C-HJ; data analysis and interpretation—C-HL, C-JJ, H-CC, and Y-JL; manuscript writing—All authors; final approval of manuscript—All authors.

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Correspondence to Chun-Jung Juan.

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This study was approved by the institutional review board of Tri-Service General Hospital (TSGHIRB 099-05-265).

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Liu, CH., Chang, HC., Liu, YJ. et al. Accumulated Hepatic Steatosis Grades Predicted by T2*-IDEAL Fat Fraction. J. Med. Biol. Eng. 43, 706–714 (2023). https://doi.org/10.1007/s40846-023-00819-7

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