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Volume 11
Issue 8
10.3390/biomedicines11082238
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Article

Prediction of Visual Acuity in Pathologic Myopia with Myopic Choroidal Neovascularization Treated with Anti-Vascular Endothelial Growth Factor Using a Deep Neural Network Based on Optical Coherence Tomography Images

by
Migyeong Yang
1,†,
Jinyoung Han
1,2,†,
Ji In Park
3,
Joon Seo Hwang
4,
Jeong Mo Han
5,
Jeewoo Yoon
1,6,
Seong Choi
1,6,
Gyudeok Hwang
7 and
Daniel Duck-Jin Hwang
7,8,*
1
Department of Applied Artificial Intelligence, Sungkyunkwan University, Seoul 03603, Republic of Korea
2
Department of Human-Artificial Intelligence Interaction, Sungkyunkwan University, Seoul 03603, Republic of Korea
3
Department of Medicine, Kangwon National University Hospital, Kangwon National University School of Medicine, Chuncheon 24341, Gangwon-do, Republic of Korea
4
Seoul Plus Eye Clinic, Seoul 01751, Republic of Korea
5
Seoul Bombit Eye Clinic, Sejong 30127, Republic of Korea
6
RAONDATA, Seoul 04615, Republic of Korea
7
Department of Ophthalmology, Hangil Eye Hospital, Incheon 21388, Republic of Korea
8
Department of Ophthalmology, Catholic Kwandong University College of Medicine, Incheon 22711, Republic of Korea
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Biomedicines 2023, 11(8), 2238; https://doi.org/10.3390/biomedicines11082238
Submission received: 16 July 2023 / Revised: 3 August 2023 / Accepted: 8 August 2023 / Published: 9 August 2023
(This article belongs to the Special Issue Research and Application of Artificial Intelligence in Assisting Disease Diagnosis and Treatment)
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Abstract

Myopic choroidal neovascularization (mCNV) is a common cause of vision loss in patients with pathological myopia. However, predicting the visual prognosis of patients with mCNV remains challenging. This study aimed to develop an artificial intelligence (AI) model to predict visual acuity (VA) in patients with mCNV. This study included 279 patients with mCNV at baseline; patient data were collected, including optical coherence tomography (OCT) images, VA, and demographic information. Two models were developed: one comprising horizontal/vertical OCT images (H/V cuts) and the second comprising 25 volume scan images. The coefficient of determination (R2) and root mean square error (RMSE) were computed to evaluate the performance of the trained network. The models achieved high performance in predicting VA after 1 (R2 = 0.911, RMSE = 0.151), 2 (R2 = 0.894, RMSE = 0.254), and 3 (R2 = 0.891, RMSE = 0.227) years. Using multiple-volume scanning, OCT images enhanced the performance of the models relative to using only H/V cuts. This study proposes AI models to predict VA in patients with mCNV. The models achieved high performance by incorporating the baseline VA, OCT images, and post-injection data. This model could assist in predicting the visual prognosis and evaluating treatment outcomes in patients with mCNV undergoing intravitreal anti-vascular endothelial growth factor therapy.
Keywords: myopic choroidal neovascularization; optical coherence tomography; visual acuity; anti-vascular endothelial growth factor myopic choroidal neovascularization; optical coherence tomography; visual acuity; anti-vascular endothelial growth factor

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MDPI and ACS Style

Yang, M.; Han, J.; Park, J.I.; Hwang, J.S.; Han, J.M.; Yoon, J.; Choi, S.; Hwang, G.; Hwang, D.D.-J. Prediction of Visual Acuity in Pathologic Myopia with Myopic Choroidal Neovascularization Treated with Anti-Vascular Endothelial Growth Factor Using a Deep Neural Network Based on Optical Coherence Tomography Images. Biomedicines 2023, 11, 2238. https://doi.org/10.3390/biomedicines11082238

AMA Style

Yang M, Han J, Park JI, Hwang JS, Han JM, Yoon J, Choi S, Hwang G, Hwang DD-J. Prediction of Visual Acuity in Pathologic Myopia with Myopic Choroidal Neovascularization Treated with Anti-Vascular Endothelial Growth Factor Using a Deep Neural Network Based on Optical Coherence Tomography Images. Biomedicines. 2023; 11(8):2238. https://doi.org/10.3390/biomedicines11082238

Chicago/Turabian Style

Yang, Migyeong, Jinyoung Han, Ji In Park, Joon Seo Hwang, Jeong Mo Han, Jeewoo Yoon, Seong Choi, Gyudeok Hwang, and Daniel Duck-Jin Hwang. 2023. "Prediction of Visual Acuity in Pathologic Myopia with Myopic Choroidal Neovascularization Treated with Anti-Vascular Endothelial Growth Factor Using a Deep Neural Network Based on Optical Coherence Tomography Images" Biomedicines 11, no. 8: 2238. https://doi.org/10.3390/biomedicines11082238

APA Style

Yang, M., Han, J., Park, J. I., Hwang, J. S., Han, J. M., Yoon, J., Choi, S., Hwang, G., & Hwang, D. D.-J. (2023). Prediction of Visual Acuity in Pathologic Myopia with Myopic Choroidal Neovascularization Treated with Anti-Vascular Endothelial Growth Factor Using a Deep Neural Network Based on Optical Coherence Tomography Images. Biomedicines, 11(8), 2238. https://doi.org/10.3390/biomedicines11082238

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