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Retina  |   June 2012
Positioning of Electronic Subretinal Implants in Blind Retinitis Pigmentosa Patients Through Multimodal Assessment of Retinal Structures
Author Affiliations & Notes
  • Akos Kusnyerik
    University of Tübingen, Centre for Ophthalmology, Tübingen, Germany;
    Department of Ophthalmology, Semmelweis University, Budapest, Hungary;
  • Udo Greppmaier
    Retina Implant AG, Reutlingen, Germany;
  • Robert Wilke
    University of Tübingen, Centre for Ophthalmology, Tübingen, Germany;
  • Florian Gekeler
    University of Tübingen, Centre for Ophthalmology, Tübingen, Germany;
  • Barbara Wilhelm
    University of Tübingen, Centre for Ophthalmology, Tübingen, Germany;
  • Helmut G. Sachs
    Klinikum Friedrichstadt, Dresden, Germany;
  • Karl Ulrich Bartz-Schmidt
    University of Tübingen, Centre for Ophthalmology, Tübingen, Germany;
  • Uwe Klose
    University of Tübingen, Section Experimental MRI of the CNS, Tübingen, Germany; and
  • Katarina Stingl
    University of Tübingen, Centre for Ophthalmology, Tübingen, Germany;
  • Miklos D. Resch
    Department of Ophthalmology, Semmelweis University, Budapest, Hungary;
  • Anusch Hekmat
    Retina Implant AG, Reutlingen, Germany;
  • Anna Bruckmann
    University of Tübingen, Centre for Ophthalmology, Tübingen, Germany;
  • Kristof Karacs
    Faculty of Information Technology, Pazmany Peter Catholic University, Budapest, Hungary.
  • Janos Nemeth
    Department of Ophthalmology, Semmelweis University, Budapest, Hungary;
  • Ildiko Suveges
    Department of Ophthalmology, Semmelweis University, Budapest, Hungary;
  • Eberhart Zrenner
    University of Tübingen, Centre for Ophthalmology, Tübingen, Germany;
Investigative Ophthalmology & Visual Science June 2012, Vol.53, 3748-3755. doi:https://doi.org/10.1167/iovs.11-9409
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      Akos Kusnyerik, Udo Greppmaier, Robert Wilke, Florian Gekeler, Barbara Wilhelm, Helmut G. Sachs, Karl Ulrich Bartz-Schmidt, Uwe Klose, Katarina Stingl, Miklos D. Resch, Anusch Hekmat, Anna Bruckmann, Kristof Karacs, Janos Nemeth, Ildiko Suveges, Eberhart Zrenner; Positioning of Electronic Subretinal Implants in Blind Retinitis Pigmentosa Patients Through Multimodal Assessment of Retinal Structures. Invest. Ophthalmol. Vis. Sci. 2012;53(7):3748-3755. https://doi.org/10.1167/iovs.11-9409.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose.: To optimize methods for positioning subretinal visual implants, customizing their cable length, guiding them to the predetermined retinal position, and evaluating their performance.

Methods.: Ten eyes of 10 patients (6 male, 4 female, mean age 46.4 years) were investigated before implantation of a subretinal visual implant. The structural characteristics of the retina as well as the ocular dimensions were determined. Topographic images of the prospective implantation site were subdivided into grids of squares. Each square received a weighted score for suitability. The sum of the scores was calculated, and the region with the highest score was chosen for the implant. In each case, the implant's power supply cable length was calculated by means of magnetic resonance imaging. The planned and achieved positions before and after implantation were compared.

Results.: The mean light sensitivity ratio between the area actually covered by the chip and that of the planned position was 90.8% with an SD of 11.4%. In two cases with almost perfect positioning, the computed ratio was 100%. Measurements showed that to achieve a 95% sensitivity rate the difference between the planned and achieved chip position must be less than 1.7 mm. Preoperative calculations of the intraocular cable length proved accurate in all cases.

Conclusions.: Preoperative evaluation of retinal structures and eye morphology is useful for guiding a retinal implant to the designated area. It is a meaningful tool for planning and performing retinal chip implantation, and it optimizes personalized implantation. (ClinicalTrials.gov numbers, NCT00515814, NCT01024803.)

Introduction
According to a recent World Health Organization estimate, more than 37 million people suffer from blindness worldwide. 1 Although cataract and trachoma are the main causes of blindness in developing countries, age-related macular degeneration (AMD) and hereditary retinal dystrophy (HRD) significantly contribute to the respective number in developed countries. (HRD is the collective term for a large, heterogeneous group of genetically determined diseases that lead to a progressive loss of photoreceptors.) 
In both AMD and HRD, however, it has been found that the inner retina remains intact for a long time, 2,3 and for this reason, retinal implants have been proposed as a means of treating blindness in patients suffering from AMD and HRD. 414 Recent studies with electronic retinal implants have clearly demonstrated their feasibility in principle. 
Although other investigators have proposed and tested epiretinal and suprachoroidal implants in clinical trials in humans, our group has developed and tested a multiphotodiode array (MPDA) that, after implantation in the subretinal space, transforms visual scenes into corresponding spatial patterns of electrical stimuli. 15,16  
However, significant differences in outcome have been observed among all the previously mentioned devices and patients. 8,9,1722 Most of these observations were attributed to the patchy patterns and highly variable individual courses of retinal degeneration. Consequently, it is essential when planning implantation to carefully define the most suitable location of the retina (i.e., the site where the highest density of remaining excitable cells and adequate vision- processing capabilities can be assumed). 
We describe here a method for doing so that combines information on the structural and functional features of the diseased retina with suitability map scores. We also present a method for calculating the distance from the scleral incision to the implantation site and for proper insertion orientation of a retinal implant so as to arrive at the best-suited location on the retina. The latter information is essential, as the length of the control cable from the sclera to the site of implantation differs from patient to patient, and intraocular visibility is limited during the insertion of intraocular devices. 23  
Methods
Patients
Ten patients (P1–10: four females, six males) with typical signs of end-stage retinitis pigmentosa (RP), rod-cone dystrophy, and choroideremia (age range: 26–57 years; mean 48 years) participated in the study (Table 1). All participants had a visual acuity of less than hand movement detection but could detect bright light without, however, being able to localize the light source. The inclusion criteria for the study were RP and HRD without any residual vision. The inclusion criteria for successful implantation were acceptable general health and an absence of severe cardiovascular disease and unstable diabetes mellitus. Patients suffering from other eye diseases or with sufficient residual visual function for crude orientation or navigation (e.g., localization of light) were excluded. All patients underwent cataract surgery and implantation of a posterior chamber IOL before the beginning of the study. Transcorneal electrical stimulation with Dawson-Trick-Litzkow electrodes was carried out to test the electrical excitability of the retina by measuring the perception threshold for single 25-ms impulses. 24 The study period was limited to 126 days in P1 to P3 by the service life of the retroauricular transdermal power source and the signal cable of the pilot study. These were subsequently replaced in the main study by a wireless inductive power supply for unlimited use (P4 to P10). All participants gave written consent according to the Code of Ethics of the World Medical Association (Declaration of Helsinki), and the study protocols were approved by the Ethics Committee of the University of Tübingen.  
Table 1.  
 
The 10 Patients, with Sex, Age, Underlying Ophthalmological Diagnoses, and Preoperative Visual Functions
Table 1.  
 
The 10 Patients, with Sex, Age, Underlying Ophthalmological Diagnoses, and Preoperative Visual Functions
Subject ID P1 P2 P3 P4 P5 P6 P7 P8 P9 P10
Sex Female Male Male Female Female Male Male Female Male Male
Age 40 38 44 52 48 62 45 46 45 44
Diagnosis RP CHM RP RP RP RP RP RP RP RP
VA nlp nlp nlp nlp nlp/ lp nlp nlp/lp nlp nlp nlp
Phosphenes mA (25 ms) 1.85 0.4 0.6 2.7 2.8 1.2 1.2 2.7 1.7 2.9
The Retinal Implant
The intraocular part of the subretinal implant is a silicon-based active microchip with 1500 individual units serving as pixels. Each pixel consists of a photodiode that can sense local light intensity along with amplifying circuitry, which is connected to a local stimulation electrode made of titanium nitride (P1 to P3) or iridium (P4 to P10). The stimulus current provided by the electrode is dependent on the brightness at each photodiode. The carrier substrate for this chip is a piece of polyamide film, which also carries leads for connecting the chip to a separate power supply 17 (Fig. 1). For more details on the chip and visual performance in first clinical trials, see Zrenner et al. 17  
Figure 1. 
 
The subretinal implant. (1) Ceramic housing of the power source with the connecting cable. (2) MPDA. (3) Pixel of the MPDA.
Figure 1. 
 
The subretinal implant. (1) Ceramic housing of the power source with the connecting cable. (2) MPDA. (3) Pixel of the MPDA.
Surgical Technique
The implant is inserted ab externo through a scleral flap 9 mm posterior to the limbus in the upper temporal quadrant. After cauterization of the choroid, a guiding tool is inserted between the choroid and retina and advanced to the desired position determined preoperatively. In the first three operations (P1 to P3) the eyeball was rotated for entry of the tool at the point of insertion, so that the posterior pole could not be seen through the pupil during implantation. According to the present procedure, the guiding foil is implanted before the implantation of the subretinal chip. During insertion of the guiding foil, the exact position can be visualized with the system applied during vitrectomy. Reposition or refinement of the guiding foil localization can be easily performed. After proper positioning of the guiding foil, implant is positioned also under visual control. During and after implantation, the eyeball can be rotated to the neutral position again, and the position of the chip can be checked visually. 23,25 To avoid unnecessary repositioning of the guiding tool, the latter should be advanced in the correct direction and to the proper depth right from the start. The distance and the angle of the implant must be carefully considered during insertion of the device, because the cable of the implant must be inserted and fixed in place at the site of insertion. The most critical part of implantation is entering the subretinal space in the periphery. Once the guiding foil is in the subretinal space, forming of macular hole has not been a problem before, because in the macular area, adhesion of pigment epithelium and neuroretina has turned out in most cases to be weaker than the potential force necessary to penetrate the retina. 
To facilitate insertion, we added additional landmark points from P4 on. We calculated the optimum angle of insertion and also marked reference point “P” (Figure 2) on the limbus with a corneal marker (Markeur, Geuder, Germany) and surgical ink. A line connecting the point of insertion (“I”) and reference point “P” indicates the correct orientation of the implant during surgery. This line intersects the vertical reference plane at an angle α of 45° (Fig. 2). During surgery, this line was marked with a thread fixed on the opposite side of the limbus and aligned with the landmarks according to a procedure used by Gonin (1934). 26 The flexible tool used to prepare a subretinal channel for advancing the implant while protecting the neuroretina was inserted a few millimeters and adjusted according to the previously created landmark points on the surface of the eyeball. Calibration marks on the guiding tool helped ensure an adequate subretinal channel length for the intraocular part of the chip and its cable. 
Figure 2. 
 
Landmarks on the cornea, designated with the flexible guiding tool. Reference point “P” was marked on the limbus with a corneal marker (Markeur) using surgical ink. A line connecting the point of insertion “I” and the reference point “P” indicates the correct orientation for the implant during surgery. d1 indicates the distance between the limbus and the incision; d2 is the depth of insertion for the flexible guiding tool.
Figure 2. 
 
Landmarks on the cornea, designated with the flexible guiding tool. Reference point “P” was marked on the limbus with a corneal marker (Markeur) using surgical ink. A line connecting the point of insertion “I” and the reference point “P” indicates the correct orientation for the implant during surgery. d1 indicates the distance between the limbus and the incision; d2 is the depth of insertion for the flexible guiding tool.
The surgeon performing the procedure also received a fundus image showing the planned implant position in each case before surgery. He was also informed about relevant distances, such as the length of the cable and the distance between the scleral incision and the chip position, as well as about the direction of insertion. 
Preoperative Examinations
Ophthalmic assessment included slit lamp biomicroscopy, funduscopy, IOP measurement, and careful assessment of the papilla. Magnetic resonance imaging (MRI), ultrasound, and optical measurement of the axial length were performed to obtain geometric eye data. Various imaging techniques and a set of tests to assess visual functions were also carried out as described earlier. 17,27  
Digital fundus photography was performed using a Zeiss FF 450 (Carl Zeiss Meditec AG, Jena, Germany) camera. Full-color 35° images of the posterior pole followed the 7-standard Fields and ETDRS standards. Fluorescein angiography images were taken using the above-mentioned protocols and equipment. 
Optical coherence tomography (OCT) scans were performed using a Zeiss Stratus OCT (Cirrus HD-OCT, Model 4000, Carl Zeiss Meditec AG), Topcon 3D OCT (Topcon Medical Systems, Inc., Oakland, CA), or Heidelberg Engineering Spectralis (Spectralis; Heidelberg Engineering, Heidelberg, Germany). Multiple scans were obtained to calculate retinal thickness at various regions of the posterior pole. Scans were analyzed with the built-in software developed and offered by the manufacturers of these OCT units. 
Image contrasting can be tailored to the specific clinical application to highlight specific types of morphology. MRI is generally regarded as an effective and important tool for imaging soft tissues (i.e., those in the human eye). It makes it possible to generate a segmented three-dimensional model of the eye with a resolution tolerance of less than 700 μm voxels. MRI seems to be one of the best tools available for measuring the geometry of the eye and is therefore regarded by us as indispensable for assessment of the eye's dimensions. 
Planning by Biometry
The shape of the human eye is approximately ellipsoid, with three parameters: axial length and the horizontal and vertical diameters. 28 To estimate the individual geometry and dimensions of the eyeball, we obtained 3-Tesla MRI (Siemens MAGNETOM Trio, A Tim System, Erlangen, Germany) scans and optical measurements. We developed new MRI sequences to establish high-resolution scans even under conditions of severe nystagmus. The measurements were performed with closed eyes. A turbo spin-echo sequence (repetition time 10 s, echo time 21 ms, and spatial resolution 0.7*0.7*0.7 mm3) was applied with breaks of some seconds to allow the patients to open their eyes every 10 seconds. 29 By carefully explaining and instructing the patients how to fixate and open their eyes with regular blinking intervals during scan acquisition we could significantly reduce the amount of motion artifacts. The details of these procedures have been worked out by our team and will be published elsewhere. In addition to axial length measurements, the vertical and horizontal equatorial dimensions of the eyeball were defined with a semiautomatic software using Matlab (Mathworks, Natick, MA). We used partial coherence interferometry (IOL Master; Carl Zeiss Meditec, version 5.02, Dublin, CA), a well-established tool, for measuring the axial length of the eyeball. This noncontact method measures the distance between the corneal vertex and the retinal pigment epithelium. Ten repeated measurements of the axial length were carried out, and the average result was determined in each patient. These data were used to estimate the axes of the eyeball and to calculate the length of the path of insertion from the site of implantation to the desired location of the chip in the macular region (Figure 3).  
Figure 3. 
 
Schematic drawing of the eyeball. AMD, optical axis; I, site of incision; AB, plane of the iris; CM, equatorial diameter; l, first axis of this ellipse; r, second axis of the 45° ellipse; h, height of the eyeball; b, width of the eyeball. (See Supplementary Material.)
Figure 3. 
 
Schematic drawing of the eyeball. AMD, optical axis; I, site of incision; AB, plane of the iris; CM, equatorial diameter; l, first axis of this ellipse; r, second axis of the 45° ellipse; h, height of the eyeball; b, width of the eyeball. (See Supplementary Material.)
Scoring System
Our recently developed scoring system for the assessment of the best site of implantation consists of superimposing a rectangular grid with 8 × 8 squares onto images of the 30° of the posterior pole around the fovea (compare Figs. 4a–d). Each grid covered roughly 1000 × 1000 μm of retinal surface. If there was a difficulty in localizing the fovea on fundus images, its position was determined using OCT scans and/or fluorescein angiography. Based on our experiences, the fovea can be determined even in end-stage RP. The human fovea has a unique structural organization. In the fovea, the peripherally displaced ganglion cell, inner plexiform, and nuclear layer form a thick rim. 30 The foveal depression is preserved in RP presumed by Witkin et al. 31 To compensate for distortion, we defined an individual factor for each type of fundus camera. Thus, both the camera type (brand name, magnification level) and known fundus features (e.g., disc size, capillaries) were included in our calculations. The image resolution was determined, and the number of pixels per mm ratio was calculated. We found that the ratio was invariably 90 to 100 pixels per mm. Based on earlier findings, we developed a numerical scoring system for the grid according to the specific features extracted from each modality, as detailed in the next paragraph. 
Figure 4. 
 
(a) Sample fundus image with the superimposed scoring grid. (b) OCT-B-scans of the foveal region (Spectralis; Heidelberg Engineering). (c) Schematic presentation of the fundus image with scoring grid and chip. Individual scores assigned to each area of P10. The green areas are most suitable for the chip location, yellow areas less so but still appropriate. Red areas are to be avoided during chip implantation. The chip is positioned according to the scores. (d) OCT thickness scan of the foveal region mapped onto the scoring grid on the posterior pole of the retina of P5.
Figure 4. 
 
(a) Sample fundus image with the superimposed scoring grid. (b) OCT-B-scans of the foveal region (Spectralis; Heidelberg Engineering). (c) Schematic presentation of the fundus image with scoring grid and chip. Individual scores assigned to each area of P10. The green areas are most suitable for the chip location, yellow areas less so but still appropriate. Red areas are to be avoided during chip implantation. The chip is positioned according to the scores. (d) OCT thickness scan of the foveal region mapped onto the scoring grid on the posterior pole of the retina of P5.
Evaluation and comparison of the retinal fields were carried out by means of the above-mentioned grid. The measurement values of the ocular fundus of the patients are listed in Figures 4a and 4b. 
The grid system consisted of square fields displayed graphically by means of software developed by the study team (U.G., A.K.). These fields were overlaid on fundus color photos. As a result, the photos simultaneously displayed the pathologic features of the fundus and the optimum position for the chip as calculated by the software. The software also allowed the clinician to classify the status of the fundus according to four categories, which included the distance to the fovea, the state of scars and the vessels, and thickness of the retina. The features of each category were evaluated on a scale of 1 to 10, as shown in Table 2
Table 2.  
 
Explanation and Classification of the Preoperative Scoring System
Table 2.  
 
Explanation and Classification of the Preoperative Scoring System
Score Category I Distance from the Fovea (mm) Category II Lesions, Pigment, Scars/ Area Unit (%) Category III Vessels (Number and Diameter) (Area Unit) Category IV (Thickness)
Foveal Area (μm) Extrafoveal Areas (μm)
1 ≥4.2 ≥80 Not detectable 220 ± 45 250 ± 45
2–3 3.4–4.2 60–80 1 thin v.* 220 ± 35 250 ± 35
4–5 2.6–3.4 40–60 2 thin v.s 220 ± 25 250 ± 25
6–7 1.8–2.6 20–40 >2 thin v.s 220 ± 20 250 ± 20
8–9 1.0–1.8 5–20 1 thick v.† 220 ± 15 250 ± 15
10 0–1.0 (Perifoveal area) No pigments, scars 1 thick v. and 1 thin v. 220 ± 0 250 ± 0
Category I represented the distance of each cell of the superimposed grid from the fovea, with values of 1 to 10 (10 = a position directly under the fovea). The area of each square was approx. 1 mm2. This category was important for the evaluation of retinal receptor density. 
Category II scored scars, pigments, and RPE status, again on a scale of 1 to 10, with 10 being the least pigmented area with preserved RPE structures. Retinal structure was evaluated based on the color fundus photos and OCT. The progression of retinal disease was assessed on the basis of pigment density. 
Category III scored retinal vasculature from 1 to 10, where 10 meant at least one thick vessel with a minimum diameter of 100 μm. The vasculature, including the length of the vessels, was assessed by fluorescein angiography. This category was helpful in assessing the vitality of specific retinal areas. 
Category IV scored the thickness of the retina on a scale of 1 to 10 in the reference areas, with 10 for optimum thickness for function. The thickness was assessed by OCT. 32 This was a meaningful indicator of retinal function. 
In carrying out scoring, we added weighted average values to the different categories as follows: 
  •  
    Category I Distance from the fovea: 37.5%
  •  
    Category II Scars, pigments: 25%
  •  
    Category III Vessels: 25%
  •  
    Category IV Thickness (OCT): 12.5 %
The above-mentioned categories and weighted values were chosen on the basis of clinical experience regarding the pathognomonic features and progression of RP and choroideremia respectively and taking into account previous results of retinal implant surgery. 
To further evaluate the suitability of an implant position, we quantified sensitivity values at both the planned and subsequently achieved positions. The overall suitability of a position was determined by integrating a suitability function for the chip area at the chosen position (see below). That is, suitability values were determined by visual inspection for discrete areas defined by the square grid, and the integral was calculated by means of the following weighted sum:  where fi is the sensitivity value of field element i and wi is the weight assigned proportional to the area covered by the chip. The weights for both the planned position and that achieved after implantation were estimated by inspection and discretized to a set of values, resulting in the following:    
The following ratio was used to relate the sensitivity of the area actually covered by the chip to the sensitivity of the planned position:  The error introduced by this discretization scheme for a given square touched by the chip was 1/16 mm2. Because the areas covered by the squares were identical, the error in these cases was zero and overall no more than 0.5 mm2 (i.e., less than 6%, as the maximum number of squares for a 3 × 3 chip was 8). It is important to note, however, that the error of suitability values for any position was smaller because of correlation with the values of the neighboring cells.  
Results
Processing of the data included a comparison of both the imaging data and the results of ophthalmologic examinations before each operation. 
Chip Position
The planned site of implantation was defined by an assessment of retinal morphology (see the Methods section above). Figure 5 shows a comparison between the site of implantation as planned according to the scoring system and the actual site of implantation. 
Figure 5. 
 
Planning and results of subretinal chip implantations in P1 to P10. Red squares show the planned positions; black squares mark the achieved position of the implants.
Figure 5. 
 
Planning and results of subretinal chip implantations in P1 to P10. Red squares show the planned positions; black squares mark the achieved position of the implants.
Biometric Dimensions
The axial length and the equatorial horizontal and vertical diameters of the eyeball were measured in all cases. Table 3 lists the projected suitability for each of the three main axes of the ellipsoid model of the globe for each patient of this study. The distance from the point of insertion to the desired location of the MPDA and the required intraocular length of the cable were determined. (For equations, see Supplementary Material.) 
Table 3.  
 
Mean Eye Dimensions of Individual Patients Scheduled for Implantation (mm)
Table 3.  
 
Mean Eye Dimensions of Individual Patients Scheduled for Implantation (mm)
Subject ID P1 P2 P3 P4 P5 P6 P7 P8 P9 P10
Axial length 24.1 24.98 23.12 20.78 25.95 24.50 19.85 23.76 20.90 24.78
Horizontal diameter 22.9 23.70 24.34 21.75 24.30 24.10 20.00 23.00 21.40 24.16
Vertical diameter 22.9 23.00 24.31 21.08 25.42 25.10 16.80 22.90 20.10 22.78
The pre- and postoperative periods of all patients were carefully observed and followed as published by Zrenner et al. 17 No severe complications occurred. Mild inflammation of the conjunctiva was found in four cases. Limited transient postoperative pain was observed. 
Light Sensitivity Ratio
The ratio between the area actually covered by the chip and that of the planned position was 90.79% on the average, with an SD of 11.39%. In two cases, the actual position had an evaluation ratio of more than 1 due to the calculation technique, meaning that the sensitivity of the position achieved for these two patients was equal to that of the planned positions (Fig. 5). In two cases (P2 and P4), evaluation was not possible because the final chip position was outside the 8 × 8 grid fields. 
Accuracy of Planning
Although the number of procedures was small, Figure 6 shows that the q value is a nonlinear function of the distance of the chip-center from the fovea. In one patient, the offset was so small that the achieved sensitivity can be regarded as equal to the planned value, as both were within the limit of error. Based on the results of our 10 patients, we found that to achieve a 95% sensitivity, the offset between the planned and actually achieved chip position had to be less than 1.7 mm. More precise conclusions will require further data. 
Figure 6. 
 
Ratio of the light sensitivity of the actual area covered by the chip and that of the planned position.
Figure 6. 
 
Ratio of the light sensitivity of the actual area covered by the chip and that of the planned position.
Discussion
In all patients, the previously described evaluation method provided essential information for the surgeon and the technical specialists who prepared the intraocular cables individually for each patient. Correct positioning of the chip at the entry point was found to play an important role for arriving at the presumed optimum site of implantation in each individual. 
Significantly better vision results are to be expected in the future when higher-resolution implants will be used at different chip locations on the posterior pole. The specific distance of the chip from the fovea was an important part of our calculations, as the foveal area in our patients had the highest number of residual photoreceptors with remaining nerve fibers. 33 The fact that AMD and HRD usually affect the central macular region with patchy patterns must also be taken into account during the planning procedure. 
OCT is important for visualizing intraocular structures in vivo with a resolution approaching that of histopathological analysis. 34 It provides valuable quantitative information concerning retinal degenerative processes such as HRD. 35,36  
Selective outer retinal degeneration of photoreceptor cells leads to visual loss in AMD and HRD, and the thickness of the retina in RP is subject to change during the course of the disease. Hood et al. 36 in 2009 confirmed histopathologically that some patients had slightly thicker retinal ganglion cell (RGC) layers, whereas the inner nuclear layer and RGC layers in these patients were comparable to those of healthy subjects. In most patients, however, the retinal nerve fiber layer (RNFL) was thicker in both horizontal midline and peripapillary scans. It can therefore be assumed that visual function is correlative to some extent with retinal thickness. 31,32 Patients in our study had advanced degeneration, with central retinal thicknesses ranging from 125 to 205 μm. In the patient selection process, systemic analysis of different retinal layers was performed. Ganglion cell, photoreceptor, and retinal pigment epithelium layers were evaluated on the magnified images. 
Ultra-high resolution OCT (UHR-OCT) is capable of visualization and quantification of microstructural changes in the photoreceptor and RPE layer. In one study, foveal outer segment/pigment epithelial thickness was defined, measured, and compared between patients with the diagnosis of RP or related diseases and a series of normal eyes. The thickness measurement in RP patients was correlated with visual acuity as well. RP patients' visual acuity showed an excellent correlation with UHR-OCT quantified photoreceptor loss. 31 Another article investigated the potential of OCT and focal electroretinogram for monitoring macular function in RP patients. Although there is a clear correlation between the number of photoreceptors and visual function, another study supports the notion that RNFL thickness in patients with RP is relatively retained despite the profound loss of photoreceptors. 37 With the ability of adaptive optics (AO), previous studies have demonstrated photoreceptor degeneration with progression of the retinal dystrophies. The AO imaging of the retina is a powerful tool to assess and monitor functional versus nonfunctional photoreceptor cells in the living human eye in retinal dystrophies. Choi et al. 38 demonstrated a clear correlation between functional vision loss and the extent of cone density decline, and confirmed earlier histological data by showing apoptotic death of the photoreceptors in diseased retinas in vivo. 
Evidence is very limited concerning predictive factors for the outcome of the retinal implants; however, parameters, such as retinal thickness, retinal scarring, pigment clumping, and the rarefaction of retinal microvasculature as an indication of inner retinal layer degeneration, are likely to be associated with reduced local excitability of the retina. We therefore chose these parameters for our preimplant scoring system. 
Retinal thickness as measured with OCT can be expected to correlate positively with the number of preserved inner retinal neurons and with an expected favorable outcome. In some cases, however, OCT thickness does not correlate with a prevalence of inner retinal neurons; these are, for example, a thickened internal limiting membrane (ILM), cystoid macular edema, and even RPE65-mutations in which normal nerve fiber layers have also been reported. 36,39  
A typical symptom of end-stage RP is the thinning and constriction of retinal vessels. The disease is also characterized by atrophy of the pigmented retinal epithelium and the formation of bone spicule lesions. Fluorescein angiography provides a method for assessing retinal microvasculature; this is normally difficult in RP due to high choroidal fluorescence. The latter was very scarce in patient 1, for example, but was well preserved in patient 3. 
Degeneration frequently causes patchy lesions on the retina, with midperipheral rings or islands. Kinetic perimetry, in particular Goldman perimetry, is well suited for identifying the functional state of the preserved retina in such cases. This is important for a comprehensive evaluation of residual retinal function and eventually for adequate evaluation of the effectiveness of a retinal implant. In our cohort of patients, however, no useful perimetric examination results could be obtained due to the lack of vision before implantation. Nevertheless, we believe that perimetry will play a crucial role when we include patients with better visual function in future studies. 
A member of our team (R.W.) evaluated the method of fundus autofluorescent imaging (FAF) in RP. It was established that FAF represents a transition zone from relatively well-preserved to abnormal retinal morphology. FAF imaging was found to be a clinically significant tool for assessing the severity and progression of dysfunction in RP patients. 40 To guide the evaluation of patchy areas of preserved RPE and photoreceptors, autofluorescence and/or hyperfluorescence imaging can be helpful in some cases as a means of marking areas with preserved retinal tissue and showing the state of degenerated areas. 41,42 As autofluorescence mainly originates from deposits in RPE cells, this marker is useful only in areas with preserved RPE cells. Advanced degeneration renders the identification of retinal layers by high-resolution OCT difficult. Involuntary eye movements and nystagmus often interrupt data acquisition. Different degrees of improvement regarding these pathologic changes were found in our patients after implantation. 15 Initially, the implants were not positioned beneath the macula but rather in the mid-periphery. Visual performance was seen to improve (Stingl et al., manuscript in preparation), however, when the implants were deliberately placed under the fovea after patient 8. 17  
In any case, the device must always be placed precisely on a retinal area containing living bipolar ganglion cells. Our experience has shown that the location of the implant must be determined according to the site of the patient's individual retinal and/or choroidal lesions. 
We also determined the cable length from the site of the insertion to the planned position on the retina. Providing the manufacturer with the length of the intraocular cable is critical for the production of custom-made implants. 
When implanting the retinal implant, it is very important to place the active part of the implant, the chip, at the best possible location under the retina. Our results confirm that preoperative evaluation of the eyeball shape is important for precise calculation of the distance from the incision site to the designated area of the implant. 
Conclusion
In summary, preoperative planning proved to be a valuable support for the operating surgeon. Preoperative assessment of retinal structures is always essential in patients considered for retinal implantation, as retinal degeneration is usually very patchy, and the success of the implant depends on exploiting residual retinal function. Standard functional tests, such as perimetry, fail in these patients; however, multimodal approaches, such as described in this article, may help to determine the best retinal site for implantation. The resulting data, in combination with morphological measurement of the dimensions of the eyeball, can be used to customize implants. Such evaluation provides a meaningful tool for planning surgical implantation in the case of other approaches (e.g., epiretinal and suprachoroidal prostheses) as well. 
To the best of our knowledge, this is the first article published about the importance of guidelines for and preoperative planning of subretinal implantation, together with the results of chip implantations in patients and a report on methods for the customization of implants and for guiding them to the predefined position during surgery. 
Supplementary Materials
Acknowledgment
The authors are grateful for the technical assistance of Matthias Roeger of the University of Tübingen's Section on Experimental MRI of the CNS in Tübingen, Germany. 
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Footnotes
 Preliminary data of this study were presented in part at the annual meeting of the Association for Research in Vision and Ophthalmology, Fort Lauderdale, Florida, May 2-6, 2010. (Kusnyerik et al., IOVS 2010, E-Abstract 3024).
Footnotes
 Supported by the Kerstan Foundation, ProRetina Deutschland e.V.
Footnotes
 Disclosure: A. Kusnyerik, None; U. Greppmaier, Retina Implant AG (E); R. Wilke, None; F. Gekeler, Retina Implant AG (I, C); B. Wilhelm, None; H.G. Sachs, None; K.U. Bartz-Schmidt, None; U. Klose, None; K. Stingl, Retina Implant AG (F); M.D. Resch, None; A. Hekmat, Retina Implant AG (E); A. Bruckmann, None; K. Karacs, None; J. Nemeth, None; I. Suveges, None; E. Zrenner, Retina Implant AG (I, C, R), P
Figure 1. 
 
The subretinal implant. (1) Ceramic housing of the power source with the connecting cable. (2) MPDA. (3) Pixel of the MPDA.
Figure 1. 
 
The subretinal implant. (1) Ceramic housing of the power source with the connecting cable. (2) MPDA. (3) Pixel of the MPDA.
Figure 2. 
 
Landmarks on the cornea, designated with the flexible guiding tool. Reference point “P” was marked on the limbus with a corneal marker (Markeur) using surgical ink. A line connecting the point of insertion “I” and the reference point “P” indicates the correct orientation for the implant during surgery. d1 indicates the distance between the limbus and the incision; d2 is the depth of insertion for the flexible guiding tool.
Figure 2. 
 
Landmarks on the cornea, designated with the flexible guiding tool. Reference point “P” was marked on the limbus with a corneal marker (Markeur) using surgical ink. A line connecting the point of insertion “I” and the reference point “P” indicates the correct orientation for the implant during surgery. d1 indicates the distance between the limbus and the incision; d2 is the depth of insertion for the flexible guiding tool.
Figure 3. 
 
Schematic drawing of the eyeball. AMD, optical axis; I, site of incision; AB, plane of the iris; CM, equatorial diameter; l, first axis of this ellipse; r, second axis of the 45° ellipse; h, height of the eyeball; b, width of the eyeball. (See Supplementary Material.)
Figure 3. 
 
Schematic drawing of the eyeball. AMD, optical axis; I, site of incision; AB, plane of the iris; CM, equatorial diameter; l, first axis of this ellipse; r, second axis of the 45° ellipse; h, height of the eyeball; b, width of the eyeball. (See Supplementary Material.)
Figure 4. 
 
(a) Sample fundus image with the superimposed scoring grid. (b) OCT-B-scans of the foveal region (Spectralis; Heidelberg Engineering). (c) Schematic presentation of the fundus image with scoring grid and chip. Individual scores assigned to each area of P10. The green areas are most suitable for the chip location, yellow areas less so but still appropriate. Red areas are to be avoided during chip implantation. The chip is positioned according to the scores. (d) OCT thickness scan of the foveal region mapped onto the scoring grid on the posterior pole of the retina of P5.
Figure 4. 
 
(a) Sample fundus image with the superimposed scoring grid. (b) OCT-B-scans of the foveal region (Spectralis; Heidelberg Engineering). (c) Schematic presentation of the fundus image with scoring grid and chip. Individual scores assigned to each area of P10. The green areas are most suitable for the chip location, yellow areas less so but still appropriate. Red areas are to be avoided during chip implantation. The chip is positioned according to the scores. (d) OCT thickness scan of the foveal region mapped onto the scoring grid on the posterior pole of the retina of P5.
Figure 5. 
 
Planning and results of subretinal chip implantations in P1 to P10. Red squares show the planned positions; black squares mark the achieved position of the implants.
Figure 5. 
 
Planning and results of subretinal chip implantations in P1 to P10. Red squares show the planned positions; black squares mark the achieved position of the implants.
Figure 6. 
 
Ratio of the light sensitivity of the actual area covered by the chip and that of the planned position.
Figure 6. 
 
Ratio of the light sensitivity of the actual area covered by the chip and that of the planned position.
Table 1.  
 
The 10 Patients, with Sex, Age, Underlying Ophthalmological Diagnoses, and Preoperative Visual Functions
Table 1.  
 
The 10 Patients, with Sex, Age, Underlying Ophthalmological Diagnoses, and Preoperative Visual Functions
Subject ID P1 P2 P3 P4 P5 P6 P7 P8 P9 P10
Sex Female Male Male Female Female Male Male Female Male Male
Age 40 38 44 52 48 62 45 46 45 44
Diagnosis RP CHM RP RP RP RP RP RP RP RP
VA nlp nlp nlp nlp nlp/ lp nlp nlp/lp nlp nlp nlp
Phosphenes mA (25 ms) 1.85 0.4 0.6 2.7 2.8 1.2 1.2 2.7 1.7 2.9
Table 2.  
 
Explanation and Classification of the Preoperative Scoring System
Table 2.  
 
Explanation and Classification of the Preoperative Scoring System
Score Category I Distance from the Fovea (mm) Category II Lesions, Pigment, Scars/ Area Unit (%) Category III Vessels (Number and Diameter) (Area Unit) Category IV (Thickness)
Foveal Area (μm) Extrafoveal Areas (μm)
1 ≥4.2 ≥80 Not detectable 220 ± 45 250 ± 45
2–3 3.4–4.2 60–80 1 thin v.* 220 ± 35 250 ± 35
4–5 2.6–3.4 40–60 2 thin v.s 220 ± 25 250 ± 25
6–7 1.8–2.6 20–40 >2 thin v.s 220 ± 20 250 ± 20
8–9 1.0–1.8 5–20 1 thick v.† 220 ± 15 250 ± 15
10 0–1.0 (Perifoveal area) No pigments, scars 1 thick v. and 1 thin v. 220 ± 0 250 ± 0
Table 3.  
 
Mean Eye Dimensions of Individual Patients Scheduled for Implantation (mm)
Table 3.  
 
Mean Eye Dimensions of Individual Patients Scheduled for Implantation (mm)
Subject ID P1 P2 P3 P4 P5 P6 P7 P8 P9 P10
Axial length 24.1 24.98 23.12 20.78 25.95 24.50 19.85 23.76 20.90 24.78
Horizontal diameter 22.9 23.70 24.34 21.75 24.30 24.10 20.00 23.00 21.40 24.16
Vertical diameter 22.9 23.00 24.31 21.08 25.42 25.10 16.80 22.90 20.10 22.78
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