Accuracy of proton magnetic resonance for diagnosing non-alcoholic steatohepatitis: a meta-analysis.
Tae-Hoon KimChang Won JeongHong Young JunChungSub LeeSiHyeong NohJi Eon KimSeungJin KimKwon Ha YoonPublished in: Scientific reports (2019)
Liver biopsy is the reference standard test to differentiate between non-alcoholic steatohepatitis (NASH) and simple steatosis (SS) in non-alcoholic fatty liver disease (NAFLD), but noninvasive diagnostics are warranted. The diagnostic accuracy in NASH using MR imaging modality have not yet been clearly identified. This study was assessed the accuracy of magnetic resonance imaging (MRI) method for diagnosing NASH. Data were extracted from research articles obtained after a literature search from multiple electronic databases. Random-effects meta-analyses were performed to obtain overall effect size of the area under the receiver operating characteristic(ROC) curve, sensitivity, specificity, likelihood ratios(LR), diagnostic odds ratio(DOR) of MRI method in detecting histopathologically-proven SS(or non-NASH) and NASH. Seven studies were analyzed 485 patients, which included 207 SS and 278 NASH. The pooled sensitivity was 87.4% (95% CI, 76.4-95.3) and specificity was 74.3% (95% CI, 62.4-84.6). Pooled positive LR was 2.59 (95% CI, 1.96-3.42) and negative LR was 0.17 (95% CI, 0.07-0.38). DOR was 21.57 (95% CI, 7.27-63.99). The area under the curve of summary ROC was 0.89. Our meta-analysis shows that the MRI-based diagnostic methods are valuable additions in detecting NASH.
Keyphrases
- contrast enhanced
- magnetic resonance imaging
- systematic review
- magnetic resonance
- meta analyses
- diffusion weighted imaging
- computed tomography
- end stage renal disease
- newly diagnosed
- ejection fraction
- insulin resistance
- big data
- randomized controlled trial
- high fat diet
- liver injury
- prognostic factors
- liver fibrosis
- skeletal muscle
- patient reported outcomes
- deep learning
- machine learning
- drug induced
- ultrasound guided
- high fat diet induced
- study protocol