Longitudinal Screening for Diabetic Retinopathy in a Nationwide Screening Program: Comparing Deep Learning and Human Graders

المؤلفون المشاركون

Soonthornworasiri, Ngamphol
Limwattanayingyong, Jirawut
Nganthavee, Variya
Seresirikachorn, Kasem
Singalavanija, Tassapol
Ruamviboonsuk, Varis
Rao, Chetan
Raman, Rajiv
Grzybowski, Andrzej
Schaekermann, Mike
Peng, Lily H.
Webster, Dale R.
Semturs, Christopher
Krause, Jonathan
Sayres, Rory
Hersch, Fred
Liu, Yun
Ruamviboonsuk, Paisan
Tiwari, Richa

المصدر

Journal of Diabetes Research

العدد

المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-8، 8ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2020-12-16

دولة النشر

مصر

عدد الصفحات

8

التخصصات الرئيسية

الأمراض
الطب البشري

الملخص EN

Objective.

To evaluate diabetic retinopathy (DR) screening via deep learning (DL) and trained human graders (HG) in a longitudinal cohort, as case spectrum shifts based on treatment referral and new-onset DR.

Methods.

We randomly selected patients with diabetes screened twice, two years apart within a nationwide screening program.

The reference standard was established via adjudication by retina specialists.

Each patient’s color fundus photographs were graded, and a patient was considered as having sight-threatening DR (STDR) if the worse eye had severe nonproliferative DR, proliferative DR, or diabetic macular edema.

We compared DR screening via two modalities: DL and HG.

For each modality, we simulated treatment referral by excluding patients with detected STDR from the second screening using that modality.

Results.

There were 5,738 patients (12.3% STDR) in the first screening.

DL and HG captured different numbers of STDR cases, and after simulated referral and excluding ungradable cases, 4,148 and 4,263 patients remained in the second screening, respectively.

The STDR prevalence at the second screening was 5.1% and 6.8% for DL- and HG-based screening, respectively.

Along with the prevalence decrease, the sensitivity for both modalities decreased from the first to the second screening (DL: from 95% to 90%, p=0.008; HG: from 74% to 57%, p<0.001).

At both the first and second screenings, the rate of false negatives for the DL was a fifth that of HG (0.5-0.6% vs.

2.9-3.2%).

Conclusion.

On 2-year longitudinal follow-up of a DR screening cohort, STDR prevalence decreased for both DL- and HG-based screening.

Follow-up screenings in longitudinal DR screening can be more difficult and induce lower sensitivity for both DL and HG, though the false negative rate was substantially lower for DL.

Our data may be useful for health-economics analyses of longitudinal screening settings.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Limwattanayingyong, Jirawut& Nganthavee, Variya& Seresirikachorn, Kasem& Singalavanija, Tassapol& Soonthornworasiri, Ngamphol& Ruamviboonsuk, Varis…[et al.]. 2020. Longitudinal Screening for Diabetic Retinopathy in a Nationwide Screening Program: Comparing Deep Learning and Human Graders. Journal of Diabetes Research،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1183482

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Limwattanayingyong, Jirawut…[et al.]. Longitudinal Screening for Diabetic Retinopathy in a Nationwide Screening Program: Comparing Deep Learning and Human Graders. Journal of Diabetes Research No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1183482

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Limwattanayingyong, Jirawut& Nganthavee, Variya& Seresirikachorn, Kasem& Singalavanija, Tassapol& Soonthornworasiri, Ngamphol& Ruamviboonsuk, Varis…[et al.]. Longitudinal Screening for Diabetic Retinopathy in a Nationwide Screening Program: Comparing Deep Learning and Human Graders. Journal of Diabetes Research. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1183482

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1183482