Dataset Information

Diagnostic test accuracy of diabetic retinopathy screening by physician graders using a hand-held non-mydriatic retinal camera at a tertiary level medical clinic.

ABSTRACT:

Background

The evidence on diagnostic test accuracy (DTA) of diabetic retinopathy (DR) screening utilising photographic studies by non-ophthalmologist personnel in low and middle-income country (LMIC) settings is scarce. We aimed to assess DTA of DR screening using a nonmydriatic hand-held digital camera by trained general physicians in a non-ophthalmic setting.

Methods

This study is a validation of a screening intervention. We selected 700 people with diabetes (PwDM)?>?18?years of age, not previously screened or treated for DR, presenting at a tertiary medical clinic in Sri Lanka. Two-field retinal imaging was used to capture fundus images before and after pupil dilatation, using a hand-held non-mydriatic (Visuscout 100®-Germany) digital retinal camera. The images were captured and graded by two trained, masked independent physician graders. The DTA of different levels of DR was assessed comparing physician's grading with a retinologist's clinical examination by mydriatic bio-microscopy, according to a locally adopted guideline.

Results

Seven hundred eligible PwDM were screened by physician graders. The mean age of participants was 60.8?years (SD ±10.08) and mean duration of DM was 9.9?years (SD ±8.09). Ungradable image proportion in non-mydriatic imaging was 43.4% (either eye-31.3%, both eyes 12.1%). This decreased to 12.8% (either eye-11.6%, both eyes-1.2%) following pupil dilatation. In comparison to detection of any level of DR, a referable level DR (moderate non-proliferative DR and levels above) showed a higher level of DTA. The sensitivity of the defined referable DR was 88.7% (95% CI 81.7-93.8%) for grader 1 (positive predictive value [PPV] 59.1%) and 92.5% (95% CI 86.4-96.5%) for grader 2 (PPV 68%), using mydriatic imaging, after including ungradable images as screen positives. The specificity was 94.9% (95% CI 93.6-96.0%) for grader 1 (negative predictive value [NPV] 99%) and 96.4% (95% CI 95.3-97.3%) for grader 2 (NPV 99.4%).

Conclusions

The Physicians grading of images from a digital hand-held non-mydriatic camera at a medical clinic, with dilatation of pupil of those who have ungradable images, provides a valid modality to identify referable level of DR. This could be a feasible alternative modality to the existing opportunistic screening to improve the access and coverage.

Trial registration

Current Controlled Trials ISRCTN47559703 . Date of Registration 18th March 2019, Retrospectively registered.

SUBMITTER: Piyasena MMPN

PROVIDER: S-EPMC6454614 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Diagnostic test accuracy of diabetic retinopathy screening by physician graders using a hand-held non-mydriatic retinal camera at a tertiary level medical clinic.

Piyasena Mapa Mudiyanselage Prabhath Nishantha MMPN Yip Jennifer L Y JLY MacLeod David D Kim Min M Gudlavalleti Venkata S Murthy VSM

BMC ophthalmology 20190408 1

<h4>Background</h4>The evidence on diagnostic test accuracy (DTA) of diabetic retinopathy (DR) screening utilising photographic studies by non-ophthalmologist personnel in low and middle-income country (LMIC) settings is scarce. We aimed to assess DTA of DR screening using a nonmydriatic hand-held digital camera by trained general physicians in a non-ophthalmic setting.<h4>Methods</h4>This study is a validation of a screening intervention. We selected 700 people with diabetes (PwDM) > 18 years o ...[more]

PMID: 30961576

Similar Datasets

Project description:BackgroundCurrently, hand-held gamma cameras are being developed for 99mTc imaging, mainly for sentinel lymph node detection. These cameras offer advantages, such as mobility and ease of access, and may be useful also for other applications such as biokinetic studies in animals or for imaging of small, superficial structures in patients. In this work, the suitability of a CZT-based hand-held camera for 177Lu imaging is investigated. The energy response of CZT-based detectors combined with the multiple photon emissions of 177Lu poses new challenges compared to 99mTc imaging, and a thorough camera characterisation is thus warranted.MethodsThree collimators (LEHR, LEHS, and MEGP) and three energy windows (55 keV, 113 keV, and 208 keV) are investigated. Characterised camera properties include the system spatial resolution, energy resolution, sensitivity, image uniformity, septal penetration, and temperature dependence. Characterisations are made starting from NEMA guidelines when applicable, with adjustments made when required. The applicability of the camera is demonstrated by imaging of a superficially located tumour in a patient undergoing [177 Lu]Lu-DOTA-TATE therapy.ResultsOverall, the results are encouraging. Compared to a conventional gamma camera, the hand-held camera generally has a higher sensitivity for a given collimator. For source-collimator distances below 3 cm, the spatial resolution FWHM is within 6 mm for the LEHR and MEGP collimators. Before uniformity correction, the central field-of-view integral uniformity shows best results for the 113-keV window, with values obtained between 11 and 14%. The corresponding values after uniformity correction are within 3%. Effects of septal penetration are observed but are manageable with a proper combination of collimator and energy window setting. Septal penetration and collimator scatter not only affect the 208-keV window but also contribute with counts in lower windows due to energy-tailing effects. The patient study revealed non-uniform uptake patterns in a region that appeared uniform in a conventional gamma camera image.ConclusionsThe results show that the hand-held camera can be used for 177Lu imaging. A 113-keV energy window combined with LEHR or MEGP collimators provides the best image system characteristics.

Project description:BackgroundTo evaluate the accuracy and reliability of fundus retinal photos graded by local graders in Bangladesh with those graded by an expert at the Centre for Eye Research Australia (CERA) in the context of mass scale diabetic retinopathy (DR) screening in Bangladesh.MethodsA population-based cross-sectional study of 3,104 adults identified 213 (7.2%) eligible patients with diabetes of age ? 40 years in 2012-2013. Retinal photographs were collected using a non-mydriatic digital fundus retinal camera and a two-field imaging protocol. The photos were graded by two remote graders (G1 and G2) who were trained by a retinal specialist (RS) in Bangladesh, by the RS himself, and by a Centre for Eye Research Australia (CERA) grader. The local graders up skilled their grading ability by comparing 30% of the photos graded by the CERA grader with their own grades. Learning from that exercise was applied to the remaining 70% of photos, which were re-graded. Reliability and accuracy of grading amongst the graders were reported using cross tabulation, inter- and intra-grader reliability, and with sensitivity and specificity.ResultsOf 122 eyes from 61 patients, the mild (R1) DR was estimated to be 14 to 25%, pre-proliferative (R2) DR 4-8%, and proliferative (R3) DR 0.8 to 1.6%, whereas 25%, 8%, 18%, and 15% were found to be ungradable by CERA, RS, G1, and G2, respectively. Of 8 (6.6%) eyes identified as R2 by the CERA grader, 5 (63%), 3 (38%) and 3 (38%) were correctly classified as R2, whereas the rest were classified either as R1 or R3 but none were classified as no DR (R0) or ungradable by the RS, G1 and G2, respectively. After getting experience reviewing the 30% test set graded by the CERA grader, the local graders graded moderate and severe DR with 100% accuracy. After excluding ungradable photos, the sensitivity (specificity) relative to the CERA grader was 82% (88%) before and 80% (93%) after training for G1 and 56% (87%) before and 77% (90%) after training for G2. In case of maculopathy, the CERA grader reported 11.2% eyes with maculopathy, which included 100% of the 4.9% by RS, 6.6% by G1, and 7.4% by G2.ConclusionsLocal graders in Bangladesh are able to grade retinal photos with high accuracy if the DR is at least of a moderate level. With appropriate training and experience, local graders have the ability to contribute significantly to the grading of millions of retinal photos, which required grading in resource- poor countries.

Project description:Topological characterization of the Retinal microvascular nEtwork visualized by portable fuNDus camera (TREND) is a database comprising of 72 color digital retinal images collected from the students of the Faculty of Medicine at the University of Montenegro, in the period from February 18th to March 11th 2020. The database also includes binarized images of manually segmented microvascular networks associated with each raw image. The participant demographic characteristics, health status, and social habits information such as age, sex, body mass index, smoking history, alcohol use, as well as previous medical history was collected. As proof of the concept, a smaller set of 10 color digital fundus images from healthy older participants is also included. Comparison of the microvascular parameters of these two sets of images demonstrate that digital fundus images recorded with a hand-held portable camera are able to capture the changes in patterns of microvascular network associated with aging. The raw images from the TREND database provide a standard that defines normal retinal anatomy and microvascular network geometry in young healthy people in Montenegro as it is seen with the digital hand-held portable non-mydriatic MiiS HORUS Scope DEC 200.This knowledge could facilitate the application of this technology at the primary level of health care for large scale telematic screening for complications of chronic diseases, such as hypertensive and diabetic retinopathy. In addition, it could aid in the development of new methods for early detection of age-related changes in the retina, systemic chronic diseases, as well as eye-specific diseases. The associated manually segmented images of the microvascular networks provide the standard that can be used for development of automatic software for image quality assessment, segmentation of microvascular network, and for computer-aided detection of pathological changes in retina. The TREND database is freely available at https://doi.org/10.5281/zenodo.4521043.

Dataset Information

Diagnostic test accuracy of diabetic retinopathy screening by physician graders using a hand-held non-mydriatic retinal camera at a tertiary level medical clinic.

Background

Methods

Results

Conclusions

Trial registration

Publications

Diagnostic test accuracy of diabetic retinopathy screening by physician graders using a hand-held non-mydriatic retinal camera at a tertiary level medical clinic.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure