Machine learning (ML) has a large capacity to learn and analyze a large volume of data. This study aimed to train different algorithms to discriminate between healthy and pathologic corneal images by evaluating digitally processed spectral-domain optical coherence tomography (SD-OCT) corneal images. A set of 22 SD-OCT images belonging to a random set of corneal pathologies was compared to 71 healthy corneas (control group). A binary classification method was applied; three approaches of ML were used. Once all images were analyzed, representative areas from every digital image were also processed and analyzed for a statistical feature comparison between healthy and pathologic corneas. The best performance was obtained from transfer learning - support vector machine (TL-SVM) (AUROC = 0.94, SPE 88%, SEN 100%) and transfer learning – random forest (TL- RF) method (AUROC = 0.92, SPE 84%, SEN 100%), followed by convolutional neural network (CNN) (AUROC = 0.84, SPE 77%, SEN 91%) and random forest (AUROC = 0.77, SPE 60%, SEN 95%). The highest diagnostic accuracy in classifying corneal images was achieved with the TL-SVM and the TL-RF models. In image classification, CNN was a strong predictor. This pilot experimental study developed a systematic mechanized system to discern pathologic from healthy corneas.

We set a feasible method to produce tailored collagen scaffolds and analyzed its potential for corneal engineering. Collagen-vitrigel membranes (CVM) were produced with a 1:1 ratio of Dulbecco’s Modified Eagle’s medium (DMEM), 1% antibiotics and 8% fetal bovine serum, and 5mg/mL collagen type I. Three volumes of collagen were used: 1X (2.8 L/mm2 of collagen), 2X, and 3X. Vitrification was done at 40% relative humidity (RH), 40° C, and 30 rpm using a matryoshka system set with a shaking-oven and a desiccator with a saturated K2CO3 solution. The CVM was characterized for width, microstructure, transparency, and biocompatibility using NIH3T3 cells. Surgical manipulation was assessed in an ex vivo corneal model. Constructs of corneal endothelial cells (CECs) and 2X-CVM were transplanted into five 18-month-old White New Zealand rabbits. CVM exhibited homogeneous surface and laminar organization. Membrane width increased with gel volume from 3.65µm to 7.2µm. 1X and 2X-CVM exhibited a 99% transmittance. NIH3T3 cells concentration increased 3-fold within 48 h with no significant difference among the 3 CVM (p = 0.323). The 2X-CVM was surgically manipulable. Transplantation of corneal endothelial cells (CECs) seeded over 2X-CVM restored corneal endothelium. The matrioshka system is a feasible method that yields CVM suitable for corneal engineering.