Evaluation of Corneal Nerves Morphology for Diabetic Peripheral Neuropathy Assessment

Susana F. Silva1,2, Custódio F.M. Loureiro1,2, Hugo Almeida1,2, Iulian Otel1,3, José Paulo Domingues1,3, José Silvestre Silva2,4, Maria João Quadrado3,5 and António Miguel Morgado1,3

1Department of Physics, Faculty of Sciences and Technology, University of Coimbra, Portugal 2Instrumentation Center, Faculty of Sciences and Technology, University of Coimbra, Portugal

3IBILI – Institute of Biomedical Research in Light and Image, Faculty of Medicine, University of Coimbra, Portugal 4School of Technology and Management, Polytechnic Institute of Portalegre, Portugal

5Ophtalmology Departament, Coimbra University Hospitals, Portugalmiguel@fis.uc.pt (PI)

Abstract—The evaluation of corneal nerve morphology by optical methods may form the basis of a simple, non-invasive technique for early diagnosis and accurate assessment of peripheral diabetic neuropathy. Currently, corneal nerves can be imaged in vivo using corneal confocal microscopy, an expensive technique that is only available at large medical units. Our goal is to develop an optical technique for peripheral neuropathy assessment, through corneal nerves imaging, based on simple, easy to operate and widespread instrumentation. This technique will be built upon automatic algorithms for corneal nerves segmentation and morphometric analysis and an optical confocal module for recording corneal nerves images using a standard slit-lamp, the most commonly used instrument in ophthalmic practice to observe the anterior eye. Here we present the current status and results of this ongoing project.

Diabetic neuropathy; Corneal nerves; Corneal confocal imaging; Automatic image segmentation.

I. CONTEXT

Peripheral diabetic neuropathy is the major cause of chronic disability in diabetic patients, being implicated in 50-75% of non-traumatic amputations [1]. The present approach to reduce diabetic neuropathy complications is based on its early diagnosis and accurate assessment [2], a difficult task due to the non-availability of a simple non-invasive method for early diagnosis [3].

The cornea, is one of the most densely innervated tissues in the human body [4] and is accessible to inspection through optical methods. In the past 15 years, several researchers proposed the use of morphologic parameters extracted from images of the corneal sub-basal nerve plexus, acquired in vivo,on conscious patients, using corneal confocal microscopy (CCM), a technique that outputs high resolution images of thin corneal layers allowing the identification of structures without using histology techniques [5]. It is established that diabetic neuropathy patients have lower nerve density [6], a feature present even for short diabetes duration [7;8]. It is also demonstrated that CCM can report accurately the extent of corneal nerve damage and repair, using measurements of fiber

density and branching [9], and that nerve tortuosity is related to the severity of neuropathy [10].

More recent works focus on the development of accurate methods for automatic segmentation and morphometric analysis of corneal nerves [11-16]. Currently, the automatic analysis of nerve images obtained through CCM microscopy produces equivalent results to manual analysis when classifying neuropathy as absent, mild, moderate or severe.

The issue of having a simple, low cost device for imaging corneal nerves for neuropathy assessment is crucial in what concerns the use of such technique at primary or secondary healthcare. A corneal confocal microscope is an expensive device used only in central hospitals and large clinics. Currently, there is no other instrument capable of imaging in vivo the corneal nerves. Our purpose is to develop such instrument, as an add-on module to a standard slit-lamp, the most commonly used instrument in ophthalmic practice to observe the anterior eye.

II. GOALS

The project goal is to develop a method for early diagnosis and follow-up of diabetic neuropathy based on the automatic analysis of morphometric parameters from cornea sub-basal nerve plexus, imaged through a slit-lamp equipped with an optical add-on module.

III. TEAM AND INSTITUTIONS

The project is a joint effort by IBILI - Institute of Biomedical Research on Light and Image, from the Faculty of Medicine, University of Coimbra, and the Instrumentation Center, from the Physics Department of the Faculty of Science and Technology, University of Coimbra. Images from patients and healthy volunteers are obtained at the Ophthalmology Department of Coimbra University Hospitals.

The team includes researchers with expertise on optical and electronic instrumentation, medical image processing and an experienced ophthalmologist. One PhD student and two MSc

students are currently enrolled, with their thesis covering different aspects of the project.

IV. IMPLEMENTATION Current work addresses the development of automatic

segmentation methods for extracting corneal nerves morphology from CCM images, the development of an optical confocal module meant to be installed on a standard slit-lamp for corneal imaging and the selection and assessment of diabetic neuropathy patients at Coimbra University Hospitals.

So far we used two different approaches to solve the problem of having an automatic tool for accurate and reproducible segmentation of corneal nerves. An automatic method based on phase symmetry and morphological operations was developed [16]. It starts by normalizing the image contrast and reducing the noise, using contrast equalization, a phase symmetry-based method and a histogram procedure. Then a fast search is done to locate candidate regions that are expanded to identify each corneal nerve. The final nerve structure is obtained by discarding false positives and merging all remaining nerves results. The second approach for automatic nerve segmentation was based on nerve tracking from seed points.

Both algorithms were implemented in Matlab and applied to a set of 47 images (36 healthy controls and 11 diabetic patients) captured by a ConfoScan 4 corneal confocal microscope (Nidek Technologies, Padova, Italy) with a 460×350 µm field of view, using a 40X objective. The images came from a database available online [11], containing 90 images (768×576 pixels, stored in JPEG format) from which we discarded a group of images with extremely low quality as well as a set of repeated images. Images with stromal nerves and images whose en face section traverses several corneal layers were also not considered. The processing time was approximately 1 minute on an Intel Centrino Core 2 at 2.4 GHz computer. The algorithms were used to evaluate the tortuosity coefficient (TC), a parameter that quantifies if a structure is curved or winding, according to the expression proposed by Kallinikos et al. [10]. More recently, the algorithms were adapted for images obtained at Coimbra University Hospitals. These images were captured with a Heidelberg Retinal Tomograph equipped with a Cornea Rostock Module (HRT-CRM: Heidelberg Engineering, Heidelberg, Germany). The 384 x 384 pixels images correspond to a 400 �m x 400 �m area and were saved as JPEG images. One example can be viewed in Fig. 1.

For imaging corneal nerves on a slit-lamp biomicroscope, we are developing an optical unit configured as an add-on module. So far, we designed, simulated on optical CAD (Oslo, Lambda Research Corporation, USA) and built a system comprising three modules to be installed on a standard slit-lamp (Nidek SL-1600): an illumination module based on a Quartz-tungsten lamp (Oriel Radiometric Fiber Optic Source 77501) coupled through a fiber optic bundle (Oriel Glass Fiber Optic Bundle 77524) and a purpose built adapter to a lateral slit-lamp port; an optical head, placed in front of the slit lamp objective, fitted with a standard microscope objective (Zeiss

Achroplan water immersion 40X 0.75 NA) and precision adjustable double prisms for separating the illumination and the detection paths (one half of the objective’s numerical aperture is used for illumination while the other half is used for detection); and a detection module, placed on the second lateral port of the slit-lamp based on a monochromatic CCD camera (Cohu 1100 series) and a set of dedicated optics for image formation on the CCD plan.

Figure 1. Corneal sub-basal nerves from a diabetic patient. The image was captured using a laser-scanning corneal confocal microscope (HRT-CRM).

The viewed area is a 400 �m square.

Confocal imaging will be implemented using a scanning-slit arrangement. The optical unit will be controlled by microcontroller (Microchip PIC32 family) based electronics. Depending on the used camera, video signal conversion can be done through a dedicated frame grabber or using the microcontroller hardware. In this case, the hardware will interface the data to a PC computer via USB.

In order to identify the best nerve morphometric parameters for neuropathy assessment, CCM exams will be performed on patients selected from the diabetic population followed at Coimbra University Hospitals and on age-matched healthy volunteers. The severity of neuropathy will be evaluated according to the Michigan Neuropathy Screening Instrument [17] and will require physical tests. The clinical measurements will be supervised by an experienced ophthalmologist and will be conducted according to guidelines of the Declaration of Helsinki and submitted to approval by the Medical Ethics Committee of the Coimbra University Hospitals.

V. RESULTS Examples of corneal nerves segmentation results are shown

in Fig. 2. Both algorithms were evaluated comparing their results with manually traced nerves by an experienced ophthalmologist using a commercial program. The percentage of nerve length correctly and falsely detected was calculated. Best results, which were obtained with the phase symmetry algorithm, are shown in Table I.

Simulation showed that the optical unit has an adequate performance in what concerns spatial resolution, contrast and optical aberrations (see Fig. 3). Ray-trace analysis reports very

low limit values for astigmatism aberration (below 0.2 mm) and spherical aberration (below 0.7 mm). The distortion is less than 0.01% for the intended field of view, a value well below those reported for commercial CCMs [19]. The Point Spread Function (PSF) analysis shows a perfect intensity distribution in three positions of the field, with a slight decrease in peak value when considering the full field of view. Therefore, light intensity will be slightly lower for objects near the field margins but lateral resolution will be almost uniform. The lateral resolution in the object plane, given by the distance between the PSF maximum and its first minimum (Airy’s disk radius), divided by the system magnification is 1.9 �m, a value three times higher than Abbe’s resolution limit but adequate for corneal nerve imaging [20]. The Modulation Transfer Function (MTF) for points in the optical axis is close to the ideal response. If we consider the full field, the MTF is above 0.4 for frequencies up to 56 cycles/mm. This means that the contrast is good and suitable for the application.

Figure 2. Examples of the results obtained with the automatic segmentation algorithms. The four images on the left were obtained using the phase

symmetry algorithm. Starting top left and going clockwise: original image, after local equalization, after phase symmetry and final segmentation. The

four images on the right are segmentation results using the tracking algorithm. On this set, there are images with good and inadequate segmentation results.

TABLE I. EVALUATION OF THE SEGMENTATION ALGORITHM PERFORMANCE: PHASE SYMMETRY ALGORITHM

Parameter Results

Average Std. Dev. Minimum Maximum

Nerve length correctly detected 89.8% 12.0% 72.0% 99.0%

Nerve length falsely detected 5.3% 8.9% 0% 43.1%

The detection side of the optical unit was installed in a Nidek SL-1600 slit-lamp and tested using a trans-illumination arrangement (see Fig. 4). All measurements were done with the slit-lamp’s Galilean telescope on the 16x position, which corresponds to no additional magnification. The field of view was measured with a Melles-Griot USAF 1951 test target. The result was 304 �m x 354 �m. Distortion was measured by comparing the image size of different squares diagonal with their actual value, given by the USAF 1951 test target specifications. The measured values (average 6.7%) were quite above those predicted by simulation, a difference that is related with optical misalignments on the optics mounting that will be corrected on the final optical unit which will be installed on a precision adapter.

The USAF 951 target was also used to estimate the spatial resolution of the system. Since all the elements present on the target were resolved by the system, we can conclude, from the specifications of the target, that the resolution is better than 228 lines per millimeter, a value that corresponds to about 4μm.

Figure 3. Simulation results for the optical unit. From top left, in clockwise direction: Ray-Trace analysis with aberrations values; Point Spread Function

analysis; MTF curves and Distortion.

Figure 4. Testing of the detection optics. The optics were installed Nidek SL-1600 slit-lamp and tested using a trans-illumination arrangement.

The system’s MTF was measured using a sinusoidal target (Edmund Optics model NT54-804). For target’s limit value (12 cycles/mm), the MTF response is around 50% again a value that, although adequate for the application, is well below the simulation results and will surely be improved in the final design.

VI. CONCLUSIONS So far, automatic corneal nerve segmentation algorithms

and an optical unit configured as an add-on module to a slit-lamp biomicroscope, were developed and tested. The algorithms identify the corneal nerves without user intervention and have good results, in terms of percentage of nerves detected, except on images with a high number of nerve branches. The results are still not adequate for diabetic

neuropathy assessment. Therefore further developments are required adequate segmentation of corneal nerves.

The simulation tests on the optical unit provided results that allow us to claim that it will meet the specifications required for corneal nerve imaging. Testing on the detection optics produced worst results that expected from simulation. However, these are due to alignment and placement issues that will be corrected when the optics are mounted in their final mounts and adapters.

VII. PLANNED DEVELOPMENTS Currently, we are developing an automatic algorithm for

corneal nerves segmentation based on dynamic programming and we are manufacturing the final optics mounts and adapters that will integrate both illumination and detection optics.

We also finished an exploratory phase that comprised the in vivo examination by CCM of corneal nerves from a small group of diabetic patients and healthy volunteers. Now we are setting up a clinical study based on CCM exams of diabetic patients and age-matched healthy volunteers to evaluate the value of different morphometric parameters of corneal nerves for documenting nerve damage and repair. Diabetic patients will be selected from the diabetic population followed at the Coimbra University Hospital and will be subjected to physical tests to score their diabetic neuropathy.

ACKNOWLEDGMENT This work was supported by FCT - Portuguese Foundation

for the Science and Technology through grant PTDC/SAU-BEB/104183/2008.

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