1
|
Kwon YD, Ko KO, Lim JW, Cheon EJ, Song YH, Yoon JM. Usefulness of Transient Elastography for Non-Invasive Diagnosis of Liver Fibrosis in Pediatric Non-Alcoholic Steatohepatitis. J Korean Med Sci 2019; 34:e165. [PMID: 31197983 PMCID: PMC6565925 DOI: 10.3346/jkms.2019.34.e165] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Accepted: 05/27/2019] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Transient elastography (FibroScan®) is a non-invasive and rapid method for assessing liver fibrosis. While the feasibility and usefulness of FibroScan® have been proven in adults, few studies have focused on pediatric populations. We aimed to determine the feasibility and usefulness of FibroScan® in Korean children. METHODS FibroScan® examinations were performed in 106 children (age, 5-15 years) who visited the Konyang University Hospital between June and September 2018. Liver steatosis was measured in terms of the controlled attenuation parameter (CAP), while hepatic fibrosis was evaluated in terms of the liver stiffness measurement (LSM). Children were stratified into obese and non-obese controls, according to body mass index (≥ or < 95th percentile, respectively). RESULTS The obese group was characterized by significantly higher levels of aspartate aminotransferase (AST, 57.00 ± 48.47 vs. 26.40 ± 11.80 IU/L; P < 0.001) and alanine aminotransferase (ALT, 91.27 ± 97.67 vs. 16.28 ± 9.78 IU/L; P < 0.001), frequency of hypertension and abdominal obesity (abdominal circumference > 95% percentile) (P < 0.001), CAP (244.4-340.98 dB/m), and LSM (3.85-7.77 kPa) (P < 0.001). On FibroScan®, 30 of 59 obese children had fibrosis (LSM > 5.5 kPa), whereas the remaining 29 did not (LSM < 5.5 kPa). Obese children with fibrosis had higher levels of AST (73.57 ± 56.00 vs. 39.86 ± 31.93 IU/L; P = 0.009), ALT (132.47 ± 113.88 vs. 48.66 ± 51.29 IU/L; P = 0.001), and gamma-glutamyl transferase (106.67 ± 69.31 vs. 28.80 ± 24.26 IU/L; P = 0.042) compared to obese children without fibrosis. LSM had high and significant correlation (P < 0.05) with AST, ALT, homeostasis model assessment for insulin resistance, and AST-to-platelet ratio index. CONCLUSION FibroScan® is clinically feasible and facilitates non-invasive, rapid, reproducible, and reliable detection of hepatic steatosis and liver fibrosis in the Korean pediatric population.
Collapse
Affiliation(s)
- Young Dai Kwon
- Department of Pediatrics, Konyang University Hospital, Konyang University College of Medicine, Daejeon, Korea
| | - Kyung Ok Ko
- Department of Pediatrics, Konyang University Hospital, Konyang University College of Medicine, Daejeon, Korea
| | - Jae Woo Lim
- Department of Pediatrics, Konyang University Hospital, Konyang University College of Medicine, Daejeon, Korea
| | - Eun Jung Cheon
- Department of Pediatrics, Konyang University Hospital, Konyang University College of Medicine, Daejeon, Korea
| | - Young Hwa Song
- Department of Pediatrics, Konyang University Hospital, Konyang University College of Medicine, Daejeon, Korea
| | - Jung Min Yoon
- Department of Pediatrics, Konyang University Hospital, Konyang University College of Medicine, Daejeon, Korea.
| |
Collapse
|
2
|
Yin Z, Murphy MC, Li J, Glaser KJ, Mauer AS, Mounajjed T, Therneau TM, Liu H, Malhi H, Manduca A, Ehman RL, Yin M. Prediction of nonalcoholic fatty liver disease (NAFLD) activity score (NAS) with multiparametric hepatic magnetic resonance imaging and elastography. Eur Radiol 2019; 29:5823-5831. [PMID: 30887196 DOI: 10.1007/s00330-019-06076-0] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 01/17/2019] [Accepted: 02/06/2019] [Indexed: 12/17/2022]
Abstract
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.
Collapse
Affiliation(s)
- Ziying Yin
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Matthew C Murphy
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Jiahui Li
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Kevin J Glaser
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Amy S Mauer
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA
| | | | - Terry M Therneau
- Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | - Heshan Liu
- Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA
| | - Harmeet Malhi
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA
| | - Armando Manduca
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA.,Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA
| | - Richard L Ehman
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA
| | - Meng Yin
- Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA.
| |
Collapse
|