Multi-measurements of meibomian glands (MGs) — which consist of area ratio, diameter deformation, tortuosity, and signal intensity — could serve as promising biomarkers for meibomian gland dysfunction (MGD) diagnosis and unbiased grading, according to study results published in The Lancet

The report found that most prior studies on examining MGs were deemed as relatively subjective and likely influenced by interobserver variability. Due to insufficient quantitative analysis tools, the development of diagnosis, grading, and treatment of MGD remains a considerable challenge, according to the research.

Between January 1, 2019 and December 31, 2020, researchers in China collected 256 participants who had experienced symptoms associated with dry eye and 56 healthy volunteers who underwent complete ocular surface examination. 


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The investigators utilized an automatic MG analyser to obtain the following multi-parametric measurements in meibography images: MGs area ratio (GA), MGs diameter deformation index (DI), MGs tortuosity index (TI), and MGs signal index (SI). In this cross-sectional study, adjusted odds ratios (ORs) of the multi-parametric measurements of MGs for MGD, and area under the receiver operating characteristic (AUC-ROC) curves of multi-parametric measurements for MGD diagnosing and grading were performed.  

Researchers noted that age and sex did not significantly differ within each pair of participant groups. When age, sex, and ocular surface condition were combined together, the estimated ORs for DI was 1.62 (95% CI, 1.29-2.56), low-level SI was 24.34 (95% CI, 2.73-217.3), TI was 0.76 (95% CI, 0.54-0.90), and GA was 0.86 (95% CI, 0.74-0.92) for MGD. 

The combination of DI-TI-GA-SI demonstrated an AUC=0.82 (P < .001) for identifying MGD patients from symptomatic subjects. The performance of single variables revealed that DI had the highest AUC in identifying early-stage MGD (grade 1-2). TI and GA had higher AUCs with regard to identifying moderate and advanced stages of MGD (grade 3-5). The Combination of DI-TI-GA demonstrated the highest AUCs in differentiating MGD severities. 

“With the automated multiparametric quantitative analysis of MGs in meibography images, our study found that morphological features including an increased DI (cross-sectionally uneven gland dilation) and a slightly increased GA (thickened and dilated glands) are common in the early stage of MGD, while a decreased GA (greatly influenced by incomplete atrophy) together with a decreased TI (decreased axial distortion) are signs of severe MGD, and revealed that glands with a low-level SI showed a high risk for the presence of MGD,” investigators report. 

“A combination of DI-TI-GA-SI has good differentiation power in identifying MGD patients from symptomatic subjects, and the merge of morphological parameters DI-TI-GA showed excellent accuracy in distinguishing MGD severities.”

Reference

Deng Y, Wang Q, Luo Z, et al. Quantitative analysis of morphological and functional features in Meibography for Meibomian Gland Dysfunction: Diagnosis and Grading. Lancet. Published online September 10, 2021. doi:10.1016/j.eclinm.2021.101132