Prediction of nonalcoholic fatty liver disease (NAFLD) activity score (NAS) with multiparametric hepatic magnetic resonance imaging and elastography.
Objectives: To investigate the use of MR elastography (MRE)-derived mechanical properties (shear stiffness (|G*|) and loss modulus (G″)) and MRI-derived fat fraction (FF) to predict the nonalcoholic fatty liver disease (NAFLD) activity score (NAS) in a NAFLD mouse model.Methods: Eighty-nine male mic...
| Publicado en: | European Radiology Vol. 29; no. 11; pp. 5823 - 5832 |
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| Autores principales: | , , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Nov2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=139163633&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 139163633 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: Nov2019 vid: 29 iid: 11 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 139163633 139163633 143967923 NLM30887196 10.1007/s00330-019-06076-0 NLM30887196 139163633 ppf: 5823 ppct: 9 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Prediction of nonalcoholic fatty liver disease (NAFLD) activity score (NAS) with multiparametric hepatic magnetic resonance imaging and elastography. aug: au: Yin, Ziying Murphy, Matthew C. Li, Jiahui Glaser, Kevin J. Mauer, Amy S. Mounajjed, Taofic Therneau, Terry M. Liu, Heshan Malhi, Harmeet Manduca, Armando Ehman, Richard L. Yin, Meng affil: Department of Radiology, Mayo Clinic, 200 First St SW, 55905, Rochester, MN, USA sug: subj: Ultrasonography Methods Nonalcoholic Fatty Liver Disease Pathology Male Mice Magnetic Resonance Imaging Methods Liver Biopsy Models, Biological Animals Epidemiological Research Male ab: Objectives: To investigate the use of MR elastography (MRE)-derived mechanical properties (shear stiffness (|G*|) and loss modulus (G″)) and MRI-derived fat fraction (FF) to predict the nonalcoholic fatty liver disease (NAFLD) activity score (NAS) in a NAFLD mouse model.Methods: Eighty-nine male mice were studied, including 64 training and 25 independent testing animals. An MRI/MRE exam and histologic evaluation were performed. Pairwise, nonparametric comparisons and multivariate analyses were used to evaluate the relationships between the three imaging parameters (FF, |G*|, and G″) and histologic features. A virtual NAS score (vNAS) was generated by combining three imaging parameters with an ordinal logistic model (OLM) and a generalized linear model (GLM). The prediction accuracy was evaluated by ROC analyses.Results: The combination of FF, |G*|, and G″ predicted NAS > 1 with excellent accuracy in both training and testing sets (AUROC > 0.84). OLM and GLM predictive models misclassified 3/54 and 6/54 mice in the training, and 1/25 and 1/25 in the testing cohort respectively, in distinguishing between "not-NASH" and "definite-NASH." "Borderline-NASH" prediction was poorer in the training set, and no borderline-NASH mice were available in the testing set.Conclusion: This preliminary study shows that multiparametric MRI/MRE can be used to accurately predict the NAS score in a NAFLD animal model, representing a promising alternative to liver biopsy for assessing NASH severity and treatment response.Key Points: • MRE-derived liver stiffness and loss modulus and MRI-assessed fat fraction can be used to predict NAFLD activity score (NAS) in our preclinical mouse model (AUROC > 0.84 for all NAS levels greater than 1). • The overall agreement between the histological-determined NASH diagnosis and the imaging-predicted NASH diagnosis is 80-92%. • The multiparametric hepatic MRI/MRE has great potential for noninvasively assessing liver disease severity and treatment efficacy. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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