Klaus-Martin Reichert

Mosaicking the subbasal nerve plexus by guided eye movements.

PURPOSE A growing number of studies provide evidence that the morphology of the corneal subbasal nerve plexus (SNP), examined by corneal confocal microscopy (CCM), is a sensitive marker for diabetic peripheral neuropathy. However, it has been established that the field of view of a single CCM image (≈0.16 mm(2)) is insufficient for reliable assessment of corneal nerve fiber morphology. The present work proposes a highly automated technique for imaging an extended area of the SNP and creating large-scale montages. METHODS A moving fixation target is presented on a small display in front of the nonexamined eye. By guiding the viewing direction of the subject in an expanding spiral pattern, the scanned corneal area is continuously expanded. Specialized software algorithms subsequently assemble a mosaic image from the acquired CCM image data. The proposed technique was applied in 12 healthy subjects. RESULTS Montage images of the SNP were successfully created from all examinations performed. The mean imaged SNP area was 9.86 mm(2) (range, 1.62-18.31 mm(2)). The mean CCM duration was 65.33 seconds (range, 14.58-142.58 seconds). CONCLUSIONS The key advances embodied in the proposed technique are its high degree of integration and automation (both for image acquisition and image processing) and the resulting short duration of CCM. By providing an easy-to-use tool for obtaining large-scale mosaic images of the SNP, this technique has the potential to facilitate larger clinical trials where SNP morphology is used as a surrogate marker for peripheral neuropathy.

A Novel Approach to Analyze the Progression of Measured Corneal Sub-Basal Nerve Fiber Length in Continuously Expanding Mosaic Images

ABSTRACT Purpose/Aim of the study: A recently proposed technique enables the generation of continuously increasing mosaic images of the corneal sub-basal nerve plexus (SNP) using in vivo corneal confocal microscopy (CCM). The aim of the present study was to investigate the progression of the corneal nerve fiber length (CNFL) measured in the growing mosaic images with regard to their increasing area. Materials and Methods: Five large datasets from three healthy volunteers were examined using the proposed CCM technique. Intermediate mosaic images were created and assessed for CNFL. Results: The measured CNFL progression shows both over- and underestimation of the CNFL for small observed areas. Increasing the mosaic image area stabilizes the CNFL values and reduces the moving variance in all five datasets. The relative deviation of means from values of first and second examination of two of the subjects shows high differences for an observed area of <1.5 mm2. Conclusions: The present examination provides two measures to quantify different area-dependent aspects of the CNFL measured in an expanding mosaic image. The moving variance measures how stable the CNFL can be considered at a certain mosaic size. The relative deviation of means from two repeated CCM examinations on the other hand gives some indication on the level of reliability that can be expected from the measured CNFL. The progression of CNFL in the examined datasets manifests a potentially very high variability for mosaic sizes of less than about 1.5 mm2. Above that size, CNFL progression and the intra-patient relative deviations both stabilize significantly in all five datasets. The results of the present examination suggest a recommendation for a minimum sampled area of the central SNP of 1.5 mm2 for reliable and meaningful measurement of CNFL.

EyeGuidance - a computer controlled system to guide eye movements

Abstract The densely innervated human cornea is the only superficial tissue of the human body in which nerve fibres are accessible in vivo by corneal confocal microscopy (CCM). Morphological parameters of the corneal sub-basal nerve plexus (SNP) derived from CCM images can potentially serve as a sensitive biomarker for early diagnosis of various neurodegenerative diseases. The evaluation of a single image with a typical field of view of 0.16 mm2 is insufficient for robust morphometric assessment. Mosaicking approaches have therefore been proposed to examine the SNP on a larger scale. Here we present a highly automated technique that significantly facilitates the generation of mosaic images of the SNP and is suitable for clinical tests.

Generating extended images of the corneal nerve plexus by guided eye movements

Confocal laser scanning microscopy (CLSM) provides a technique for in vivo imaging the sub-basal nerve plexus (SNP) of the cornea. For mapping an extended area of the SNP, currently the objective of the CLSM is manually moved laterally across the corneal surface during acquisition of overlapping images. This work presents a proof of concept for a new method that realizes the movements during the mapping process by guiding the eye movements with a computercontrolled fixation target on a display in front of the contralateral eye. The purpose is to generate a maximized and completely covered scan area with an overlapping area of adjacent images of more than 50%.

3D confocal laser-scanning microscopy for large-area imaging of the corneal subbasal nerve plexus

The capability of corneal confocal microscopy (CCM) to acquire high-resolution in vivo images of the densely innervated human cornea has gained considerable interest in using this non-invasive technique as an objective diagnostic tool for staging peripheral neuropathies. Morphological alterations of the corneal subbasal nerve plexus (SNP) assessed by CCM have been shown to correlate well with the progression of neuropathic diseases and even predict future-incident neuropathy. Since the field of view of single CCM images is insufficient for reliable characterisation of nerve morphology, several image mosaicking techniques have been developed to facilitate the assessment of the SNP in large-area visualisations. Due to the limited depth of field of confocal microscopy, these approaches are highly sensitive to small deviations of the focus plane from the SNP layer. Our contribution proposes a new automated solution, combining guided eye movements for rapid expansion of the acquired SNP area and axial focus plane oscillations to guarantee complete imaging of the SNP. We present results of a feasibility study using the proposed setup to evaluate different oscillation settings. By comparing different image selection approaches, we show that automatic tissue classification algorithms are essential to create high-quality mosaic images from the acquired 3D datasets.

Iterative Algorithms to Generate Large Scale Mosaic Images

The process of creating mosaic images from non-linear registration image sequences consists of various complex subtasks. The two most time consuming and hardware resource intensive operations are the image registration process and the solution of an equation system in order to determine image positions in the mosaic. This work presents methods that allow quick calculation of image positions while reducing the necessary hardware resources. A novel graph-based method to determine promising image pairs for the registration process was developed, resulting in a reduction of runtime by 87.5%.