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Liu Z, Tan K, Zhang H, Sun J, Li Y, Fang S, Li J, Song X, Zhou H, Zhai G. CT-based artificial intelligence prediction model for ocular motility score of thyroid eye disease. Endocrine 2024; 86:1055-1064. [PMID: 39046593 DOI: 10.1007/s12020-024-03906-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 05/29/2024] [Indexed: 07/25/2024]
Abstract
PURPOSE Thyroid eye disease (TED) is the most common orbital disease in adults. Ocular motility restriction is the primary complaint of patients, while its evaluation is quite difficult. The present study aimed to introduce an artificial intelligence (AI) model based on orbital computed tomography (CT) images for ocular motility score. METHODS A total of 410 sets of CT images and clinical data were obtained from the hospital. To build a triple classification predictive model for ocular motility score, multiple deep learning models were employed to extract features of images and clinical data. Subgroup analyses based on pertinent clinical features were performed to test the efficacy of models. RESULTS The ResNet-34 network outperformed Alex-Net and VGG16-Net in prediction of ocular motility score, with the optimal accuracy (ACC) of 0.907, 0.870, and 0.890, respectively. Subgroup analyses indicated no significant difference in ACC between active or inactive phase, functional visual field diplopia or peripheral visual field diplopia (p > 0.05). However, in the gender subgroup, the prediction model performed more accurately in female patients than males (p = 0.02). CONCLUSION In conclusion, the AI model based on CT images and clinical data successfully realized automatic scoring of ocular motility in TED patients. This approach potentially enhanced the efficiency and accuracy of ocular motility evaluation, thus facilitating clinical application.
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Affiliation(s)
- Zijia Liu
- Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University, Shanghai, 200040, China
| | - Kexin Tan
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, and Center for Basic Medical Research and Innovation in Visual System Diseases of Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Haiyang Zhang
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, and Center for Basic Medical Research and Innovation in Visual System Diseases of Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Jing Sun
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, and Center for Basic Medical Research and Innovation in Visual System Diseases of Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Yinwei Li
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, and Center for Basic Medical Research and Innovation in Visual System Diseases of Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Sijie Fang
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, and Center for Basic Medical Research and Innovation in Visual System Diseases of Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Jipeng Li
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, and Center for Basic Medical Research and Innovation in Visual System Diseases of Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China
| | - Xuefei Song
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, and Center for Basic Medical Research and Innovation in Visual System Diseases of Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China.
| | - Huifang Zhou
- Department of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology, and Center for Basic Medical Research and Innovation in Visual System Diseases of Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China.
| | - Guangtao Zhai
- Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University, Shanghai, 200040, China.
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Hankinson J, Shuaib A. Surgical management of oculomotor nerve palsy - a review of the literature. Eur J Ophthalmol 2024; 34:1667-1674. [PMID: 38303488 DOI: 10.1177/11206721241229758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2024]
Abstract
We aim to review the surgical management techniques available for patients with oculomotor nerve (OMN) palsy, compare and contrast the approaches and subsequent outcomes. A search of the literature was carried out to yield all papers relevant to the topic, and a wide spectrum of surgical techniques were identified. These included: muscle shortening and lengthening procedures, muscle transposition, globe fixation and ptosis surgery. Patients often require a synergistic combination of these techniques. Strabismus surgery for OMN palsy can be approached through a variety of different techniques to improve the quality of life, independence and aesthetics for the patient.
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Affiliation(s)
- Jake Hankinson
- Barts and The London School of Medicine and Dentistry, London, UK
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