RESUMEN
The sub-basal nerve plexus (SNP) of the cornea provides the possibility of in vivo and non-invasive examination of peripheral nerve structures by corneal confocal microscopy (CCM). Thus morphological alterations of the SNP can be directly detected and quantified. A single CCM image is insufficient for a well-founded diagnosis because of the inhomogeneous distribution of the nerve fibers; therefore, there is a demand for techniques for large area imaging of the SNP. This article provides an overview of published approaches to the problem. Current developmental work at the Karlsruhe Institute of Technology and the University of Rostock Eye Clinic is expected to lead to a simplified handling of the technology and a further improvement in the image quality.
Asunto(s)
Córnea/inervación , Microscopía Intravital/instrumentación , Microscopía Confocal/instrumentación , Fibras Nerviosas/patología , Enfermedades del Sistema Nervioso Periférico/diagnóstico , Enfermedades del Sistema Nervioso Periférico/patología , Diagnóstico Precoz , Movimientos Oculares/fisiología , Humanos , Interpretación de Imagen Asistida por Computador/instrumentación , Interpretación de Imagen Asistida por Computador/métodos , Microscopía Intravital/métodos , Microscopía Confocal/métodos , Fibras Nerviosas/clasificación , Programas InformáticosRESUMEN
BACKGROUND: The high resolution of corneal confocal microscopy (CCM) allows in vivo imaging of the corneal sub-basal nerve plexus (SNP). The field of view of a single CCM image (0.16 mm²) is not sufficient for the reliable morphometric characterisation of the SNP. Therefore we are developing a highly automated mosaicking technique for large-area imaging of the SNP using CCM image sequences. METHODS: In order to acquire an image sequence of a larger area of the SNP, the view direction of the patient is guided by a computer-controlled moving fixation target on a display in front of the non-examined eye. The CCM image sequence is recorded with 30 fps. An online calculated mosaic image allows the medical operator to observe the acquisition process and assess the quality and size of the resulting image during the CCM recording process. Remaining image artefacts are corrected in an automated post-processing step. RESULTS: Using a first prototype system and an appropriate fixation target trajectory, a mean growth of the covered SNP area of 0.18 mm²/s could be achieved. CONCLUSION: Using the presented technology, large-area images of the SNP can be generated. The technology is characterized by a high degree of automation and short examination times.