- •Foreword
- •Preface
- •Contents
- •1.1 Introduction
- •1.2 Method
- •1.2.1 Databases
- •1.2.2 Dates
- •1.2.3 Keywords
- •1.2.4 Criteria for Inclusion
- •1.2.5 Criteria for Exclusion
- •1.2.6 Selection of Papers
- •1.3 Results
- •1.3.1 Subspecialty
- •1.3.2 Type of Telemedicine
- •1.3.3 Study Design
- •1.3.4 Final Conclusions of Papers
- •1.4 Discussion
- •References
- •2.1 Introduction
- •2.2 The Need for Diabetic Retinopathy Screening Programs
- •2.4 Guidelines for Referring Patients
- •2.7 Program Models for Diabetic Retinopathy Screening
- •2.9 Program Personnel and Operations
- •2.9.1 Primary Care Providers
- •2.9.2 Photographers
- •2.9.3 Clinical Consultants
- •2.9.4 Administrators
- •2.9.5 A Note to CEOs, Operations Directors, and Clinic Managers
- •2.10 Policies and Procedures
- •2.10.1 Sample Protocol 1
- •2.10.1.1 Diabetic Retinopathy Screening Services
- •Policy
- •Background
- •Procedure
- •2.10.2 Sample Protocol 2
- •2.10.2.1 Pupil Dilation Before Diabetic Retinopathy Photography
- •Policy
- •Background
- •Procedure
- •2.10.3 Sample Protocol 3
- •2.10.3.1 Diabetic Retinopathy Photography Review
- •Policy
- •Background
- •Procedure
- •2.11 Technical Requirements
- •2.11.1 Connectivity
- •2.11.2 Resolution
- •2.11.3 Color
- •2.11.4 Stereopsis
- •2.11.5 Compression
- •2.11.6 Enhancement
- •2.11.7 Pupil Dilation
- •2.11.8 Early California Telemedicine Initiatives Diabetic Retinopathy Screening
- •2.11.9 The American Indian Diabetes Teleophthalmology Grant Program
- •2.11.10 Central Valley EyePACS Diabetic Retinopathy Screening Project
- •2.12.1 Diabetic Retinopathy
- •2.12.1.1 ADA Guidelines Terms
- •2.12.1.2 Vitrectomy
- •References
- •3: Stereopsis and Teleophthalmology
- •3.1 Introduction
- •3.2 History of Stereopsis and Stereopsis in Ophthalmology
- •3.3 Technology and Photography
- •3.3.3 Imaging Fields
- •3.3.4 Image Viewing Techniques
- •3.3.5 Image Compression
- •3.4 Stereoscopic Teleophthalmology Systems
- •3.4.1 University of Alberta
- •3.4.4 Joslin Vision Network
- •3.5 Conclusion
- •References
- •4.1 Introduction
- •4.2 Methods
- •4.2.1 Main Outcome Measures
- •4.3 Results
- •4.3.1 Retinal Video Recording Versus Retinal Still Photography
- •4.3.2 Video Compression Analysis
- •4.4 Discussion
- •References
- •5.1 Introduction
- •5.1.1 Automated, Remote Image Analysis of Retinal Diseases
- •5.1.2 Telehealth
- •5.2 Design Requirements
- •5.2.1 Telehealth Network Architecture
- •5.2.2 Work Flow
- •5.2.3 Performance Evaluation of the Network
- •5.3 Automated Image Analysis Overview
- •5.3.1 Quality Assessment Module
- •5.3.2 Vascular Tree Segmentation
- •5.3.3 Quality Evaluation
- •5.4 Anatomic Structure Segmentation
- •5.4.1 Optic Nerve Detection
- •5.4.2 Macula
- •5.4.3 Lesion Segmentation
- •5.4.4 Lesion Population Description
- •5.4.5 Image Query
- •5.5 Summary
- •References
- •6.1 Introduction
- •6.3 Optical Coherence Tomography to Detect Leakage
- •References
- •7.1 Introduction
- •7.2 Patients and Methods
- •7.2.1 Participants
- •7.2.2 Methods
- •7.2.3 Statistics
- •7.3 Results
- •7.3.1 Reliability of Image Evaluation
- •7.3.2 Prevalence of Glaucomatous Optic Nerve Atrophy
- •7.4 Discussion
- •7.5 Perspectives
- •References
- •8.1 Introduction
- •8.1.2 Homology Between Retinal and Systemic Microvasculature
- •8.1.3 Need for More Precise CVD Risk Prediction
- •8.2.1 Retinal Microvascular Signs
- •8.2.2 Retinal Vessel Biometry
- •8.2.3 Newer Retinal Imaging for Morphologic Features of Retinal Vasculature
- •8.3 Associations of Retinal Imaging and CVD Risk
- •8.3.1.1 Risk of Pre-clinical CVD
- •8.3.1.2 Risk of Stroke
- •8.3.1.3 Risk of Coronary Heart Disease
- •8.3.2.1 Risk of Hypertension
- •8.3.2.2 Risk of Stroke
- •8.3.2.3 Risk of Coronary Heart Disease
- •8.3.2.4 Risk of Peripheral Artery Disease
- •8.3.3 Newer Morphologic Features of Retinal Vasculature
- •8.4 Retinal Imaging and Its Potential as a Tool for CVD Risk Prediction
- •References
- •9.1 Alzheimer’s Disease
- •9.2 Treatments
- •9.3 Diagnosis
- •9.6 Conclusions
- •References
- •10.1 Introduction
- •10.1.1 Stroke
- •10.1.2 Heart Disease
- •10.1.3 Arteriovenous Ratio
- •10.2 Purpose
- •10.3 Method
- •10.3.1 Medical Approach
- •10.3.2 Technical Approach
- •10.3.3 Output of Medical Data
- •10.4 Patients
- •10.5 Results
- •10.5.1 Medical History
- •10.5.2 Telemedical Evaluation of Retinal Vessels
- •10.5.2.1 Prevalence of Retinal Microangiopathy
- •10.5.2.2 Arteriovenous Ratio
- •10.5.2.3 PROCAM-Index
- •10.6 Discussion and Perceptive
- •10.6.1 Estimation of “Stroke Risk” Estimated by the Stage of Retinal Microangiopathy
- •References
- •11.1 Introduction
- •11.2 System Requirements
- •11.3 Fundus Camera
- •11.4 Imaging Procedure
- •11.4.1 Reading Center Procedure
- •11.5 Detection of Macular Edema
- •11.6 Implementation
- •11.7 Unreadable Images
- •11.7.1 Impact on Overall Diabetic Retinopathy Assessment Rates
- •11.7.2 Compliance with Recommendations
- •11.7.3 Challenges
- •11.7.4 Summary
- •References
- •12.1 Screening
- •12.2 Background
- •12.3 Historical Perspective in England
- •12.4 Methodology
- •12.4.1 The Aim of the Programme
- •12.5 Systematic DR Screening
- •12.6 Cameras for Use in the English Screening Programme
- •12.7 Software for Use in the English Screening Programme
- •12.9 Implementation in England
- •12.11 Quality Assurance
- •12.12 The Development of External Quality Assurance in the English Screening Programme
- •12.13 Information Technology (IT) Developments for the English Screening Programme
- •12.14 Dataset Development
- •12.15 The Development of External Quality Assurance Test Set for the English Screening Programme
- •12.16 Failsafe
- •12.17 The Epidemic of Diabetes
- •References
- •13.1 Introduction
- •13.2 Burden of Diabetes and Diabetic Retinopathy in India
- •13.3 Diabetic Retinopathy Screening Models
- •13.4 Need for Telescreening
- •13.5 Guidelines for Telescreening
- •13.6 ATA Categories of DR Telescreening Validation
- •13.7 Yield of Diabetic Retinopathy in a Telescreening Model
- •13.8 How Are Images Transferred
- •13.10 How Many Fields Are Enough for Diabetic Retinopathy Screening
- •13.11 Is Mydriasis Needed While Using Nonmydriatic Camera?
- •13.12 Validation Studies on Telescreening
- •13.12.1 Accuracy of Telescreening
- •13.12.2 Patient Satisfaction in Telescreening
- •13.12.3 Cost Effectivity
- •13.12.4 Telescreening for Diabetic Retinopathy: Our Experience
- •13.13 Future of Diabetic Retinopathy Screening
- •References
- •14.1 Introduction
- •14.2 Methods
- •14.3 Discussion
- •14.4 Conclusion
- •References
- •15.1 Introduction
- •15.1.1 Description of the EADRSI
- •15.5 State Support of Screening in the Safety Net
- •15.7 Screening Economics for Providers
- •15.8 Patient Sensitivity to Fees
- •15.9 Conclusion
- •References
- •16.1 Introduction
- •16.2 Setting Up the New Screening Model
- •16.2.1 Phase 1: Training
- •16.2.2 Phase 2: Evaluation of Agreement
- •16.2.3 Phase 3: Implementation of the Screening Model
- •16.3 Technologic Requirements
- •16.3.1 Data Management
- •16.3.2 Data Models
- •16.3.2.1 Data Scheme for Patient-Related Information
- •16.3.2.2 Data Scheme for Images
- •Fundus Camera VISUCAM Pro NM
- •PACS Server
- •ClearCanvas DICOM Visualizer
- •16.4 Results
- •16.4.1 Phase 2: Agreement Evaluation
- •16.4.2 Phase 3: Implementation of the Screening Model
- •16.5 Discussion
- •16.5.1 Evaluation of the Screening Model
- •16.5.2 Prevalence of DR
- •16.5.3 Quality Evaluation
- •16.6 Conclusion
- •References
- •17.1.3 Examination and Treatment
- •17.1.4 Limitations of Current Care
- •17.2 Telemedicine and ROP
- •17.2.2 Accuracy and Reliability of Telemedicine for ROP Diagnosis
- •17.2.3 Operational ROP Telemedicine Systems
- •17.2.4 Potential Barriers
- •17.3 Closing Remarks
- •17.3.1 Future Directions
- •References
- •18.1 Introduction
- •18.2 Neonatal Stress and Pain
- •18.3 ROP Screening Technique
- •18.4 Effect of Different Examination Techniques on Stress
- •18.5 Future of Retinal Imaging in Babies
- •References
- •19.1 Introduction
- •19.2 History of the Program
- •19.3 Telehealth Technologies
- •19.4 Impact of the Program
- •Selected References
- •Preamble
- •Introduction
- •Background
- •The Diabetic Retinopathy Study (DRS)
- •Mission
- •Vision
- •Goals
- •Guiding Principles
- •Ethics
- •Clinical Validation
- •Category 1
- •Category 2
- •Category 3
- •Category 4
- •Communication
- •Medical Care Supervision
- •Patient Care Coordinator
- •Image Acquisition
- •Image Review and Evaluation
- •Information Systems
- •Interoperability
- •Image Acquisition
- •Compression
- •Data Communication and Transmission
- •Computer Display
- •Archiving and Retrieval
- •Security
- •Reliability and Redundancy
- •Documentation
- •Image Analysis
- •Legal Requirements
- •Facility Accreditation
- •Privileging and Credentialing
- •Stark Act and Self-referrals
- •State Medical Practice Acts/Licensure
- •Tort Liability
- •Duty
- •Standards of Care
- •Consent
- •Quality Control
- •Operations
- •Customer Support
- •Originating Site
- •Transmission
- •Distant Site
- •Financial Factors
- •Reimbursement
- •Grants
- •Federal Programs
- •Other Financial Factors
- •Equipment Cost
- •Summary
- •Abbreviations
- •Appendices
- •Appendix A: Interoperability
- •Appendix B: DICOM Metadata
- •Appendix C: Computer-Aided Detection
- •Appendix D: Health Insurance Portability and Accountability Act (HIPAA)
- •Appendix F: Quality Control
- •Appendix H: Customer Support
- •Level 1
- •Level 2
- •Level 3
- •Appendix I: Reimbursement
- •Medicare
- •Medicaid
- •Commercial Insurance Carrier Reimbursement
- •Other Financial Factors
- •Disease Prevention
- •Resource Utilization
- •American Telemedicine Association’s Telehealth Practice Recommendations for Diabetic Retinopathy
- •Conclusion
- •References
- •Contributors
- •Second Edition
- •First Edition
- •Index
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The technical failure rates for retinal videos and retinal still photography were 7.5% versus 7%, respectively (p > 0.05). Of the failed videos, 47% (n = 7) had cataracts, 13% (n = 2) had dark fundi, and 40% (n = 6) were intolerant to bright light, whereas for retinal images, they were due to presence of cataracts (36%, n = 5), intolerance to bright flash (36%, n = 5), and poor fixation of eyes (28%, n = 4).
4.4Discussion
Our study has shown that the retinal video recording technique is a potential alternative novel technique to screen for DR due to its high diagnostic accuracy, as compared to the retinal still photography and slit lamp examination. The diagnostic sensitivity and specificity were more than 90% for both imaging methods graded by both consultant ophthalmologists for detection of any grade of DR, increasing to 100% sensitivity and specificity for sight-threatening DR. The efficacy of the retinal video recording technique has also been reanalyzed using Kappa statistics which were found to be more than 0.8 for DR grading and lesions such as microaneurysms, retinal hemorrhages, cotton wool spots, intraretinal microvascular abnormalities, new vessels, vitreous hemorrhage, and hard exudates.
To evaluate the user-friendliness of retinal video recording, we recruited a medical officer who did not possess any previous ophthalmic imaging experience in performing this technique, with comparison to the retinal still photography performed by an extremely experienced orthoptist who had 10 years experience in DR screening and imaging. Our results showed not only that the diagnostic accuracy for both imaging methods were comparable to the slit lamp examination, but also the technical failure between retinal video recording and retinal still photography were not statistically significant (7.5% vs. 7%, chi-square = 0.04; d.f. = 1, p = 0.85).
This technique is easy to use with minimal training by inexperienced personnel. Moreover, a 1-min retinal video recording can be readily compressed down from 1 GB to 20 MB for a 1-min video, using a video software converter. The con-
version time was approximately 20 s per video. In other words, a 15to 20-s video will take up 5–7 MB. This file size is comparable to the 3-field retinal color fundus photos downloaded in Tagged Image File Format (TIFF) or bitmap format. Given that the retinal video recording had high sensitivity, specificity, and short conversion timing, this novel technique could be potentially implemented in a routine, mobile, and teleophthalmology setting. Nevertheless, more research will be required to evaluate the use of retinal video recording with a teleophthalmology software in order to assess cost-effectiveness of implementation of this technique and its data transmission speed. The usability of this study could also be conducted by recruiting various allied health-care professionals to utilize this technique and evaluate the technical difficulties and diagnostic accuracy as the main outcome measure of the study.
We utilized the International Clinical Diabetic Retinopathy Severity Scales in our study due to its simplicity. Compared to Early Treatment Diabetic Retinopathy Study, this photographic grading system carries less severity scales and DR lesions. Hence, it enables the specialist and nonspecialist personnel to communicate in a common language. By making easier to grade and screen DR, the primary eye care providers such as the general practitioners and optometrists will be more interested and proactive in participating in DR screening services in the community levels instead of referring every diabetic patient including the ones with normal or mild DR. By reducing the waiting list in a tertiary DR screening service, this could shorten the specialist appointment time and, hence, fast track the patients with sight-threatening DR changes (severe NPDR, PDR, and diabetic macular edema) to receive prompt laser treatment.
In order to prevent any screen size or color resolution related diagnostic error, our study chose the 27-in. iMac (Apple, USA) as the reading monitor for the ophthalmologists and medical officer. Given that the results arose from this study were favorable, further research should be directed toward the usage of various screen sizes and less expensive computer brands to interpret the retinal videos in order to reduce
4 Video Imaging Technology: A Novel Method for Diabetic Retinopathy Screening |
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the costs of implementation and maintenance of a diabetic screening service, especially in areas with financial limitations (e.g., rural areas and developing countries).
The strength of this study is that this is one of the first few large-scale studies worldwide to evaluate the efficacy of using retinal video recording and compression technique as an alternative way to screen for DR. This technique offers slightly greater fields and better continuity of retinal views within a shorter period of time, compared to the standard retinal still photography. One of the weaknesses of this study was that all patients underwent both retinal video recording and retinal still photography within a short period of time, and hence, the technical failure rate may be affected by patients’ prolonged exposure to bright light. In order to further justify the usage of this technique, this study will need to be expanded to multiple centers around the world. Most of the patients enrolled in this study were Caucasians who have brighter fundi as compared to the pigmented races such as Chinese and Indians. Therefore, one will need to evaluate the technical failure rate of this technique among the pigmented population with dark fundi. The retinal video recording also did not possess a built-in video compression software. Further research will be of great value to refine the current version of retinal video cameras or invent other new retinal video cameras which come with a built-in video compression software.
In conclusion, retinal video recording is a novel technique to screen for DR. Although it may not substitute the gold standard slit lamp examination
by the clinicians, it is another potential alternative to retinal still photography in screening for patients with diabetes. It offers an excellent continuity of retinal views within a short period of time. Given that it does not offer a three-dimensional view of the retina, patients with suspicious of diabetic macular edema, the commonest cause for visual impairment in patients with diabetes, should be referred promptly to an ophthalmologist. It will be of great significance if further research could focus on its clinical and cost-effectiveness in mass screening the patients in a routine, mobile, and teleophthalmology setting across different ethnicities.
References
1.McKay R, McCarty CA, Taylor HR (2000) Diabetic retinopathy in Victoria, Australia: the visual impair-
ment project. Br J Ophthalmol 84:865–870
2. Klein R, Klein BE, Moss SE, Davis MD, DeMets DL (1984) The Wisconsin epidemiologic study of diabetic retinopathy. III. Prevalence and risk of diabetic retinopathy when age at diagnosis is 30 or more years. Arch Ophthalmol 102:527–532
3. Ting DSW, Tay-Kearney ML, Constable IJ, Liam L, Yogesan K (2011) Retinal video recording: a new way to image and diagnose diabetic retinopathy. Ophthalmology 118(8):1588–1593
4.Early Treatment Diabetic Retinopathy Study Research Group (1991) Grading diabetic retinopathy from stereoscopic color fundus photographs – an extension of the modified Airlie house classification. ETDRS report number 10. Early Treatment Diabetic Retinopathy Study Research Group. Ophthalmology 98:786–806
5. Wilkinson CP, Ferris FL 3rd, Klein RE, Lee PP, Agardh CD, Davis M et al (2003) Proposed international clinical diabetic retinopathy and diabetic macular edema disease severity scales. Ophthalmology 110:1677–1682
