Artificial intelligence in ophthalmology
| ISRCTN | ISRCTN13860301 |
|---|---|
| DOI | https://doi.org/10.1186/ISRCTN13860301 |
| Secondary identifying numbers | 81971697 |
- Submission date
- 03/11/2021
- Registration date
- 08/11/2021
- Last edited
- 08/11/2021
- Recruitment status
- No longer recruiting
- Overall study status
- Completed
- Condition category
- Eye Diseases
Plain English Summary
Background and study aims
A cataract is a clouding of the lens of the eye. Cataract surgery to replace the lens is popular, especially refractive cataract surgery, where the surgeon uses advanced multifocal intraocular lenses (IOLs) to restore vision. Both surgical skills and the IOL power calculation are important factors for surgical outcomes. Currently, optical biometers are popular instruments in ophthalmology. Many related eye parameters have an influence on the IOL power calculation. Age-related macular degeneration (AMD) is the leading cause of severe and permanent vision loss in people over age 50 years. A precise diagnosis is very important. Compared with the traditional IOL power calculation and expert diagnosis system, deep learning provides the possibility of a more accurate IOL power calculation and an efficient diagnostic method. The aim of this study is to find a more precise and efficient deep learning algorithm for IOL power calculation and AMD diagnosis.
Who can participate?
Patients undergoing cataract surgery in the Shanxi Eye Hospital Affiliated to Shanxi Medical University (Taiyuan, Shanxi, China) and patients with AMD
What does the study involve?
All patients undergo non-invasive eye tests at the start of the study and after 1 week, 1 month, and 3 months.
What are the possible benefits and risks of participating?
Participants may benefit from a basic evaluation of their eye structure. As this is an observational study, no risks are involved.
Where is the study run from?
Shanxi Eye Hospital (China)
When is the study starting and how long is it expected to run for?
November 2019 to December 2023
Who is funding the study?
1. National Natural Science Foundation of China
2. Shanxi Eye Hospital
3. Shanxi Scholarship Council of China
Who is the main contact?
Dr Xiaogang Wang
movie6521@163.com
Contact information
Scientific
No. 100 Fudong Street
Taiyuan
030002
China
| Phone | +86 (0)13834246830 |
|---|---|
| movie6521@163.com |
Study information
| Study design | Single-center prospective cross-sectional study |
|---|---|
| Primary study design | Observational |
| Secondary study design | Cross sectional study |
| Study setting(s) | Hospital |
| Study type | Diagnostic |
| Participant information sheet | Not applicable in web format, please use contact details to request a participant information sheet |
| Scientific title | Establishment of an accurate anterior and posterior segment data analysis and diagnostic system with the combination of multimodal optical coherence tomography imaging and deep learning |
| Study hypothesis | 1. The intraocular lens (IOL) power of various structures could be accurately calculated using deep learning and the swept source optical coherence tomography (OCT) system 2. An intelligent age-related macular degeneration (AMD) grading diagnosis system could be established with the combination of deep learning and the spectral-domain OCT system |
| Ethics approval(s) | Approved 03/11/2019, Shanxi Eye Hospital Affiliated to Shanxi Medical University (No. 100 Fudong Street, Taiyuan, China; +86 (0)351 4131791; SXYYLLWYH@163.com), ref: 2019LL130 |
| Condition | Cataract, age-related macular degeneration |
| Intervention | All patients undergo biometric data capture (non-contact) with the sequence of ANTERION and then with that of IOLMaster 700 in the mesopic condition without pupil dilation. The researchers collect previous retinal disease OCT images and add new available captured retinal disease images using the Optovue XR and Heiderberg OCT systems. |
| Intervention type | Device |
| Pharmaceutical study type(s) | |
| Phase | Not Applicable |
| Drug / device / biological / vaccine name(s) | ANTERION, IOLMaster 700, Optovue XR and Heiderberg OCT systems |
| Primary outcome measure | Automatically measured using the SS-OCT device at baseline, 1 week, 1 month, and 3 months: 1. Axial length 2. Keratometry 3. Astigmatism 4. Anterior chamber depth 5. Lens thickness values Automatically measured using the OCT device at baseline, 1 week, 1 month, 3 months: 1. Retinal thickness 2. Macular edema 3. Choroidal neovascularization (CNV) images |
| Secondary outcome measures | 1. IOL power calculated using a free Barrett online calculator at baseline, 1 week, 1 month, and 3 months 2. Visual acuity measured using a Snellen visual chart at baseline, 1 week, 1 month, and 3 months 3. Intraocular pressure measured using a non-contact tonometer at 1 week, 1 month, and 3 months |
| Overall study start date | 03/11/2019 |
| Overall study end date | 31/12/2023 |
Eligibility
| Participant type(s) | Patient |
|---|---|
| Age group | All |
| Sex | Both |
| Target number of participants | At least 73 patients for the IOL power study and 100 patients for the AMD study group |
| Participant inclusion criteria | 1. Patients undergoing cataract surgery in the Shanxi Eye Hospital Affiliated to Shanxi Medical University (Taiyuan, Shanxi, China) 2. No systemic disease 3. No pathological alteration of the anterior segment (such as keratoconus, zonular dialysis, pseudoexfoliation syndrome, corneal opacity) 4. No retinal diseases impairing visual function 5. No previous anterior or posterior segment surgery 6. If patients are diagnosed with AMD disease, the captured image can be included in the AMD and deep learning study |
| Participant exclusion criteria | Patients who cannot cooperate with the data capturing procedure and fail to pass the image quality check |
| Recruitment start date | 01/09/2020 |
| Recruitment end date | 31/12/2022 |
Locations
Countries of recruitment
- China
Study participating centre
Taiyuan
030002
China
Sponsor information
Hospital/treatment centre
No. 100 Fudong Street
Taiyuan
030002
China
| Phone | +86 (0)351 8286886 |
|---|---|
| SXYYLLWYH@163.com | |
| Website | http://www.sxsyk.com/web/index |
"ROR" |
https://ror.org/02wh8xm70 |
Funders
Funder type
Government
Government organisation / National government
- Alternative name(s)
- Chinese National Science Foundation, Natural Science Foundation of China, National Science Foundation of China, NNSF of China, NSF of China, 国家自然科学基金委员会, National Nature Science Foundation of China, Guójiā Zìrán Kēxué Jījīn Wěiyuánhuì, NSFC, NNSF, NNSFC
- Location
- China
No information available
Government organisation / Local government
- Alternative name(s)
- SSCC, SXSCC, SSCC
- Location
- China
Results and Publications
| Intention to publish date | 12/05/2023 |
|---|---|
| Individual participant data (IPD) Intention to share | Yes |
| IPD sharing plan summary | Available on request |
| Publication and dissemination plan | Planned publication in a high-impact peer-reviewed journal. Additional documents (such as study protocol, statistical analysis plan etc) will be available on proper request. |
| IPD sharing plan | The related data can be acquired by contacting Dr Xiaogang Wang (movie6521@163.com). Type of data: quantitative data, imaging data. The data will be available after the related paper is published for 1 year. A written form has to be submitted to the institution investigator and evaluated by the ethics committee. |
Editorial Notes
08/11/2021: Trial's existence confirmed by the Medical Ethics Committee of Shanxi Medical University.
