Aqueous humour cytokine profiles after Descemet’s membrane endothelial keratoplasty

The aim of this study was to compare aqueous humour (AqH) cytokine profiles before and after Descemet’s membrane endothelial keratoplasty (DMEK) in eyes with bullous keratopathy (BK) and age-matched normal eyes. A total of 49 participants (mean age 75.0 ± 13.5 years) were divided into three groups: (1) BK patients scheduled for DMEK (BK group); (2) patients after DMEK (DMEK group; average postoperative time 1,018 ± 460 days); and (3) control participants without corneal endothelial disease scheduled for cataract surgery (control group). AqH (0.2 mL) was collected from all participants, and the levels of various AqH cytokines were simultaneously measured using a multiplex bead immunoassay. The DMEK group exhibited significantly lower concentrations of several pro-inflammatory cytokines, such as IL-1β, IL-5, IL-6, IL-10, and IL-8, and granulocyte colony stimulating factor than the BK group. In addition, the levels of IL-1β and IL-5 were significantly lower in the DMEK group than in the control group. The AqH levels of several pro-inflammatory cytokines were significantly reduced after DMEK, indicating that regeneration of the endothelial pump owing to the transplantation of a healthy endothelium might have a positive effect on anterior chamber inflammation.

Corneal pachymetry by AS-OCT after Descemet’s membrane endothelial keratoplasty

Corneal thickness (pachymetry) maps can be used to monitor restoration of corneal endothelial function, for example after Descemet’s membrane endothelial keratoplasty (DMEK). Automated delineation of the corneal interfaces in anterior segment optical coherence tomography (AS-OCT) can be challenging for corneas that are irregularly shaped due to pathology, or as a consequence of surgery, leading to incorrect thickness measurements. In this research, deep learning is used to automatically delineate the corneal interfaces and measure corneal thickness with high accuracy in post-DMEK AS-OCT B-scans. Three different deep learning strategies were developed based on 960 B-scans from 50 patients. On an independent test set of 320 B-scans, corneal thickness could be measured with an error of 13.98 to 15.50 μm for the central 9 mm range, which is less than 3% of the average corneal thickness. The accurate thickness measurements were used to construct detailed pachymetry maps. Moreover, follow-up scans could be registered based on anatomical landmarks to obtain differential pachymetry maps. These maps may enable a more comprehensive understanding of the restoration of the endothelial function after DMEK, where thickness often varies throughout different regions of the cornea, and subsequently contribute to a standardized postoperative regime.