Magnetic Resonance Imaging Parameters on Lacrimal Gland in Thyroid Eye Disease: a Systematic Review and Meta-analysis

Abstract

Abstract Background: Thyroid eye disease (TED) is an extrathyroidal manifestation of Graves’ disease and is associated with dry eye disease. This is the first systematic review and meta-analysis to evaluate the role of magnetic resonance imaging (MRI) lacrimal gland (LG) parameters in TED diagnosis, activity grading, and therapeutic responses prediction. Methods: Up to 23 August, 2022, 504 studies from PubMed and Cochrane Library were analyzed. After removing duplicates and imposing selection criteria, nine eligible studies were included. Risk of bias assessment was done. Meta-analyses were performed using random-effect model if heterogeneity was significant. Otherwise, fixed-effect model was used. Main outcome measures include seven structural MRI parameters (LG herniation (LGH), maximum axial area (MAA), maximum coronal area (MCA), maximum axial length (MAL), maximum coronal length (MCL), maximum axial width (MAW), maximum coronal width (MCW)), and three functional MRI parameters (diffusion tensor imaging (DTI)-fractional anisotropy (FA), DTI-apparent diffusion coefficient (ADC) or mean diffusivity (MD), diffusion-weighted imaging (DWI)-ADC). Results: TED showed larger MAA, MCA, MAL, MAW, MCW, DTI-ADC/MD, and lower DTI-FA than controls. Active TED showed larger LGH, MCA, DWI-ADC than inactive. LG dimensional (MAA, MCA, MAL, MAW, MCW) and functional parameters (DTI-FA, DTA-ADC/MD) could be used for diagnosing TED; LGH, MCA, and DWI-ADC for differentiating active from inactive TED; DTI parameters (DTI-FA, DTI-MD) and LGH for helping grading and therapeutic responses prediction respectively. Conclusions: MRI LG parameters can detect active TED and differentiate TED from controls. MCA is the most effective indicator for TED diagnosis and activity grading. There are inconclusive results showing whether structural or functional LG parameters have diagnostic superiority. Future studies are warranted to determine the use of MRI LG parameters in TED.