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Validation of a DIXON-based fat quantification technique for the measurement of visceral fat using a CT-based reference standard

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Abstract

Purpose

The purpose of the study is to determine whether a novel semi-automated DIXON-based fat quantification algorithm can reliably quantify visceral fat using a CT-based reference standard.

Methods

This was an IRB-approved retrospective cohort study of 27 subjects who underwent abdominopelvic CT within 7 days of proton density fat fraction (PDFF) mapping on a 1.5T MRI. Cross-sectional visceral fat area per slice (cm2) was measured in blinded fashion in each modality at intervertebral disc levels from T12 to L4. CT estimates were obtained using a previously published semi-automated computational image processing system that sums pixels with attenuation − 205 to − 51 HU. MR estimates were obtained using two novel semi-automated DIXON-based fat quantification algorithms that measure visceral fat area by spatially regularizing non-uniform fat-only signal intensity or de-speckling PDFF 2D images and summing pixels with PDFF ≥ 50%. Pearson’s correlations and Bland–Altman analyses were performed.

Results

Visceral fat area per slice ranged from 9.2 to 429.8 cm2 for MR and from 1.6 to 405.5 cm2 for CT. There was a strong correlation between CT and MR methods in measured visceral fat area across all studied vertebral body levels (r = 0.97; n = 101 observations); the least (r = 0.93) correlation was at T12. Bland–Altman analysis revealed a bias of 31.7 cm2 (95% CI [− 27.1]–90.4 cm2), indicating modestly higher visceral fat assessed by MR.

Conclusion

MR- and CT-based visceral fat quantification are highly correlated and have good cross-modality reliability, indicating that visceral fat quantification by either method can yield a stable and reliable biomarker.

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Authors and Affiliations

  1. University of Michigan Medical School, Ann Arbor, MI, USA

    Katherine M. Heckman & Bamidele Otemuyiwa

  2. Department of Radiology, Michigan Medicine, Ann Arbor, MI, USA

    Thomas L. Chenevert, Dariya Malyarenko & Matthew S. Davenport

  3. Morphomics Analysis Group, Michigan Medicine, Ann Arbor, MI, USA

    Brian A. Derstine & Stewart C. Wang

  4. Department of Surgery, Michigan Medicine, Ann Arbor, MI, USA

    Stewart C. Wang

  5. Michigan Radiology Quality Collaborative, Ann Arbor, MI, USA

    Matthew S. Davenport

  6. Department of Urology, Michigan Medicine, Ann Arbor, MI, USA

    Matthew S. Davenport

  7. 1500 E Medical Center Dr B2-A209P, Ann Arbor, MI, 48109, USA

    Matthew S. Davenport

Authors
  1. Katherine M. Heckman
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  2. Bamidele Otemuyiwa
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  3. Thomas L. Chenevert
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  4. Dariya Malyarenko
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  5. Brian A. Derstine
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  6. Stewart C. Wang
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  7. Matthew S. Davenport
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Corresponding author

Correspondence to Matthew S. Davenport.

Ethics declarations

No funding was solicited or used for this work. Institutional review board approval was obtained. The requirement for informed consent was waived by the IRB. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Financial disclosure

Matthew Davenport—Royalties from Wolters Kluwer, Katherine M. Heckman—No conflict of interest, Bamidele Otemuyiwa—No conflict of interest, Thomas L. Chenevert—No conflict of interest, Dariya Malyarenko—No conflict of interest, Brian A. Derstine—No conflict of interest, Stewart C Wang—No conflict of interest.

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Heckman, K.M., Otemuyiwa, B., Chenevert, T.L. et al. Validation of a DIXON-based fat quantification technique for the measurement of visceral fat using a CT-based reference standard. Abdom Radiol 44, 346–354 (2019). https://doi.org/10.1007/s00261-018-1678-x

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  • DOI: https://doi.org/10.1007/s00261-018-1678-x

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