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Automatic measurement of choroidal thickness and vasculature in optical coherence tomography images of eyes with retinitis pigmentosa

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Abstract

Retinitis pigmentosa (RP) is a group of genetic disorders, characterized by degeneration of photoreceptor cells which is the main cause of choroidal thinning. It is one of the leading causes of blindness worldwide. Thus, an investigation of choroidal changes is required for a better understanding of disease and diagnosis of RP. In this paper, we propose an automatic technique for measuring the choroidal parameters in optical coherence tomography (OCT) images of eyes with RP. The parameters include the total choroidal area (TCA), luminal area (LA), stromal area (SA), and choroidal thickness (CT). We applied our recently proposed, dense dilated U-Net segmentation model, called ChoroidNET, for segmenting the choroid layer and choroidal vessels for our RP dataset. Choroid segmentation is an important task since the measurement results depend on it. Comparison with other state-of-the-art models shows that ChoroidNET provides a better quantitative and qualitative segmentation of the choroid layer and choroidal vessels. Next, we measure the choroidal parameters based on the segmentation results of ChoroidNET. The proposed method achieves high reliability with an intraclass correlation coefficient (0.961, 0.940, 0.826, 0.916) for TCA, LA, SA, and CT, respectively.

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Acknowledgements

The authors would like to acknowledge the financial support provided by the KAKENHI under the Grant-in-Aid for Scientific Research (A) (Grant number 19H01172), the Japan Society for the Promotion of Science (JSPS) Core-to-Core Program (JPJSCCA20170004), the Thai Government Research Fund (contract numbers 33/2560 and 24/2561), the National Research Council of Thailand (NRCT) (Grant number NRCT5-RSA63010-05), and the Center of Excellence in Biomedical Engineering of Thammasat University.

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Authors and Affiliations

  1. Graduate School of Science and Engineering, Chiba University, Chiba, 263-8522, Japan

    Tin Tin Khaing & Takayuki Okamoto

  2. Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani, 12000, Thailand

    Tin Tin Khaing, Pakinee Aimmanee & Stanislav S. Makhanov

  3. Center for Frontier Medical Engineering, Chiba University, Chiba, 263-8522, Japan

    Chen Ye, Md. Abdul Mannan & Hideaki Haneishi

  4. Department of Ophthalmology and Visual Science, Graduate School of Medicine, Chiba University, Chiba, 260-8670, Japan

    Gen Miura & Hirotaka Yokouchi

  5. Institute for Tenure Track Promotion, University of Miyazaki, Miyazaki, 889-2192, Japan

    Kazuya Nakano

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  1. Tin Tin Khaing
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  2. Takayuki Okamoto
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  3. Chen Ye
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  5. Gen Miura
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Correspondence to Takayuki Okamoto.

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Khaing, T.T., Okamoto, T., Ye, C. et al. Automatic measurement of choroidal thickness and vasculature in optical coherence tomography images of eyes with retinitis pigmentosa. Artif Life Robotics 27, 70–79 (2022). https://doi.org/10.1007/s10015-022-00737-y

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  • DOI: https://doi.org/10.1007/s10015-022-00737-y

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