Ординатура / Офтальмология / Английские материалы / Diabetes and Ocular Disease Past, Present, and Future Therapies 2nd edition_Scott, Flynn, Smiddy_2009

Brown and associates [39] compared the sensitivity of optical coherence tomography (OCT) to CLBM in the identification of macular edema from diabetic retinopathy. Ninety-five patients (172 eyes) were enrolled consecutively. Excellent agreement was found between the two methods when foveal thickness was within normal limits (<200 microns) or moderately increased (>300 microns). Agreement was poor when retinal thickness was minimal (201–300 microns), suggesting that OCT is more sensitive than clinical examination at identifying mild macular edema. Sanchez-Tocino and associates [40] found that OCT was able to identify early macular edema prior to the development of CSME. OCT might be a useful supplementary tool in a telemedicine program for evaluating macular edema.

Neubauer and colleagues [41] compared routine ophthalmologic examinations to tele-screening images captured with a retinal thickness analyzer (RTA) in 31 consecutive eyes with diabetic retinopathy. The RTA images were graded by three independent and masked graders. RTA images were found to be sensitive (mean = 93%) in the identification of macular edema but less specific (58–96%) than clinical examination. Although the results of this study show promise in the identification of macular edema, further validation is needed if a RTA is to be used as part of a telemedicine system.

PRACTICE RECOMMENDATIONS

The American Telemedicine Association (ATA), the ATA Ocular Telehealth Special Interest Group, and the United States National Institute of Standards and Technology Working Group met in 2003 to discuss current diabetic retinopathy telehealth clinical and administrative issues. Their work culminated with the publication of Telehealth Practice Recommendations for Diabetic Retinopathy [42].

The document provides recommendations for designing and implementing a diabetic retinopathy ocular telehealth program. Because of the diverse nature of health care at diabetic patient points of care, the Recommendations advise telemedicine programs to clearly define goals. Available resources may vary from one setting to another. Building a telemedicine program should match economics, human resources, and telecommunication infrastructures with community needs.

The Recommendations also advocate that every telemedicine program validate and define performance. It is recommended that programs compare kappa values for agreement of diagnosis, false positive and false negative readings, positive predictive value, negative predictive value, sensitivity and specificity of diagnosing levels of retinopathy and macular edema to ETDRS film photography. The Recommendations describe four categories of validation ranging from Category 1 (distinguishing between no or minimal DR and more than minimal DR) to Category 4 (distinguishing retinopathy levels equivalent to or exceeding ETDRS) (Table 19.2). The performance of a telemedicine program should be assessed as an integrated system, from image capture to image review—not as a series of individual processes or components. For example, the performance of two teleophthalmology systems based on identical fundus cameras equipped with identical 1280 × 1024 pixel resolution digital backs may not be the same if one system uses a 800 × 600 pixel video monitor for review while the other uses a 1280 × 1024 monitor.

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Table 19.2. American Telemedicine Association’s Recommended Validation

Categories

* category able to detect clinically significant macula edema.

ETDRS = Early Treatment Diabetic Retinopathy Study; DR = diabetic retinopathy

The Telehealth Practice Recommendations for Diabetic Retinopathy also specifies qualifications and responsibilities for personnel and recommends that programs include quality assurance policies and procedures to monitor system performance. The Recommendations acknowledge that diabetic patients be aware that teleophthalmology examination of the retina, while substituting for a traditional face-to-face dilated retinal evaluation, is not a replacement for a comprehensive eye examination. The document notes, A comprehensive eye examination by a qualified provider continues to be essential . . . . A licensed eye care provider with expertise in evaluation and management of diabetic retinopathy should oversee image evaluation and ultimately be responsible for diagnoses.

CONSIDERATIONS IN IMPLEMENTING A TELEMEDICINE PROGRAM

Resources that societies have or are willing to devote to medical care vary by community and by country. Implementing a telemedicine system may be hindered by legal issues, limited acceptance of telemedicine by local health care professionals and payers, lack of funding for new technology and equipment, limited training of associated health care personnel, physician remuneration, computer network charges and maintenance, and other factors. The cost of implementing a telemedicine program to detect retinopathy should consider all resources needed to build and run the program, including resources to manage diabetic retinopathy once identified.

A number of factors should be considered when initially planning a diabetic retinopathy telemedicine program. Among these are [43]:

•The number of diabetic patients in the population being considered for the program

•The percentage of patients evaluated for retinopathy without teleophthalmology

•The percentage of patients who would be evaluated if teleophthalmology was implemented

Careful consideration of technology should precede implementation of any telemedicine system. Technological considerations include:

•System compliance with relevant health information guidelines and requirements such as HIPPA (Health Insurance Portability and Accountability Act)

•Archiving health information and images

•Expected lifespan of the archival media

•DICOM (Digital Imaging and Communications in Medicine) compliance

•HL7 (Health Level 7) compliance

•Network and/or Web access security such as two-factor authentication, encryption and/or passwords

Once a diabetic retinopathy telemedicine system is up and running, general factors to consider in administering and sustaining the program include:

•Patient convenience

•Appropriate referral of patients evaluated by telemedicine

•Assessment quality

•Quality control

Not all diabetic retinopathy telemedicine systems require sensitivity in detecting all levels of retinopathy. Sensitivity requirements can vary depending on resources available to clinicians and patients. For example, a diabetic patient living in a remote location without access to eye care may need a highly sensitive evaluation to screen for retinopathy requiring treatment. This telemedicine system should be able to identify levels of retinopathy including severe nonproliferative, proliferative, and clinically significant macular edema stages. In addition, the system should be sensitive and specific enough to allow follow-up after treatment. In an urban environment, where distance to specialist care is not a barrier, a community may be better served by a system with only enough sensitivity to identify patients without diabetic retinopathy. Each program should define goals and set clinically acceptable operating points.

Networked telemedicine systems offer potential advantages over stand-alone systems. New software can be downloaded and installed and network servers updated. Web, intranets, and private networks allow use of inexpensive, browser-compliant computers to access telemedicine systems instead of expensive, dedicated workstations. Hardware independence also allows various cameras, operating systems, and other technologies to coexist, providing maximum flexibility to customize systems to local needs. Web-based systems allow instant and simultaneous access to registered

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users almost anywhere in the world. The development of DICOM standards for ophthalmology will facilitate the transfer of electronic information between different medical devices and components while maintaining data integrity [44].

EMERGING TECHNOLOGY

The use of digital imaging and the growing availability of clinical information in digital form are spurring the development of computer-aided detection and diagnosis for various medical conditions. Potential advantages of automated image analysis and detection include increased efficiency, improved consistency and reliability of interpretation, enhanced accuracy and objective quantification of pathology, and reduction of inter-observer variability [45]. Mammography computer-aided diagnosis (CAD) received FDA approval in 2002 [46]. Studies have shown a 19% increase in cancer detection using CAD [47]. Computer-aided diagnosis for multidetector computed tomography (MDCT) of pulmonary nodules received approval in July, 2004 [48]. CAD is also being developed in other areas of radiology including detection of polyps in virtual colonoscopy scans, pulmonary nodules and other lung interstitial diseases on chest radiographs, brain lesions on CT and MRI brain scans, and prostate lesions.

Diabetic retinopathy’s distinct characteristics can be used by computer algorithms to detect and analyze disease. Microaneurysms’ circular features or the high intensity and edge sharpness of hard exudates are relatively easy for computers to identify. Hard exudates in the macula and their proximity to the central macula serve as surrogate markers for macular edema. Microaneurysm quantity is a surrogate measure of diabetic retinopathy severity [49,50]. For these reasons, microaneurysms and hard exudates are logical diabetic retinal lesions for automatic analysis investigation. Neovascularization, unfortunately, is not. Because neovascularization is less frequent, appears in various forms, and has borders that are often indistinct, neovascularization is harder to detect automatically.

Hipewell investigated automated detection of microaneurysms in digital red-free photographs as a diabetic retinopathy screening tool. The study of 925 subjects achieved a sensitivity of 85% and specificity of 76% in the detection of subjects with retinopathy. Two EURODIAB 50-degree fields per eye were analyzed per subject using 1024 × 1024 pixel, 8-bit images [51].

Another group investigated automated detection of red lesions (microaneurysm and retinal hemorrhage) in photos [52]. This 2003 study analyzed 35 mm slides, 60-degree images digitized at 1350 dpi and 12 bits per color channel. The 137patient photograph study correctly identified 90% of patients with retinopathy and 81% without retinopathy. By adjusting visibility threshold, their algorithm adapts to different screening priorities: high-sensitivity identification for diabetic retinopathy or high-specificity identification for absence of retinopathy [53]. White lesion detection algorithms for hard exudates have also been studied. [54,55]

A recent intelligent image analysis study to detect retinopathy by looking for exudates, hemorrhages and/or microaneurysms showed 84% sensitivity and 64%

specificity [56]. Another study found 90.5% sensitivity and 67.4% specificity in the detection of technical failures or diabetic retinopathy [57].

Another promising image analysis approach applied to the automated diagnosis of diabetic retinopathy is content-based image retrieval. Investigators have used pictorial content to retrieve related images from large database collections to predict disease presence and severity [58].

In general, automated detection processes include:

Image Processing

1.Pre-processing of images to enhance contrast

2.Identification of optic disc, retinal vessels, and fovea

3.Identification of bright pathology lesions (hard exudates) and dark pathology lesions (hemorrhages/microaneurysms)

4.Extraction of pathology features via size, shape, hue, and intensity

Classification

1.Identification of each lesion as a true lesion or noise (using an artificial neural network)

2.Identification of each image and patient as without retinopathy or with retinopathy according to the presence or absence of lesions (based on mathematical rules)

Although no automated detection of diabetic retinopathy program is yet approved by the FDA, substantial progress is being made. It is likely that using computers to semi-automatically distinguish images with pathology will eventually become an integral part of evaluating diabetic retinopathy.

Investigations of other computer-assisted tools are also underway. Image enhancement algorithms to maximize suboptimal contrast from uneven illumination or retinal pigmentation variation among individuals are being developed. These algorithms are designed to maximize image quality, decreasing the number of unreadable images. Computer tools for annotating and quantifying pathology are also increasingly available. Digital images embedded with metadata such as patient information, eye/retina characteristics, and digital image specifications offer new possibilities in specialist monitoring and managing diabetic retinopathy through telemedicine.

IMAGINING THE FUTURE

Today’s telemedicine technological requirements are being developed and limitations studied through investigative applications and validation research. New standards and protocols for telemedicine technology will accelerate the future use of telemedicine, as will scientific evidence supporting clinical and cost effectiveness.

Diabetic retinopathy is a leading cause of blindness worldwide. Telemedicine offers new methods of health care delivery that can facilitate the goal of all diabetic patients having access to eye care. It may also prove to be the most cost-effective and efficacious solution for mass screening people with diabetes. In countries with

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socialized medicine programs or single health care payers, cost savings associated with telemedicine have allowed the early development and implementation of telemedicine programs. In other countries, the introduction of diabetic retinopathy telemedicine fee codes or other remuneration for physicians should provide further incentives for expansion.

Within the next 10 years, we expect diabetic retinopathy telemedicine systems to be in place throughout the United States and most of the developed world. Systems will utilize multi-field, digital retinal photography, with or without pupil dilation. Images will be graded utilizing ETDRS, modified ETDRS, or entirely new standards specific to digital imagery.

Technology, of course, does not stand still. Within 20 years, we expect systems will detect diabetic retinopathy more accurately than current seven-field, stereoscopic, film photography. Telemedicine technology will be portable, inexpensive, accurate, and widely available. It will rely on computer algorithms to detect and identify treatable diabetic retinopathy. And if a cure for diabetes is found, telemedicine may play the pivotal role in eliminating the last vestiges of this blinding disease.

SUMMARY FOR THE CLINICIAN

•Telemedicine is being integrated into many aspects of health care

•Telemedicine for diabetic retinopathy protocols and equipment may vary, but all are targeted to early identification of the disease

•An eye care specialist continues to be responsible for diabetic retinopathy identified through telemedicine

Telemedicine Pros

•Patient convenience

•Extends health care resources and specialists

•Potential increase in quality consistency

•Potential increase in patient referral efficiency

Telemedicine Cons

•Not a substitute for comprehensive eye examination

•Technology investment required

•Specialized training and/or new support personnel required

•New compliance protocols associated with computer systems sharing patient information

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