Prediction of Postoperative Visual Acuity in Cataract Patients Using a Macular Optical Coherence Tomography-based Deep Learning Method

Launched by SECOND AFFILIATED HOSPITAL, SCHOOL OF MEDICINE, ZHEJIANG UNIVERSITY · May 13, 2021

Keywords

ClinConnect Summary

This clinical trial aims to develop a new method for predicting how well cataract patients will see after their surgery, using advanced technology called deep learning. Researchers will collect images of the patients' eyes and their vision measurements before and after the surgery at the Second Affiliated Hospital of Zhejiang University Medical College. The goal is to create a model that can help doctors better understand how a patient's vision might improve after cataract surgery.

To participate in this study, patients need to have age-related cataracts that are affecting their daily life, whether or not they also have other eye conditions. However, individuals who can significantly improve their vision with glasses or have other serious eye issues will not be eligible. The study is not yet recruiting participants, but once it starts, those who qualify can expect to have their eye images taken and their vision measured as part of the research process. This could ultimately lead to better outcomes for future cataract patients by helping doctors predict and improve their vision after surgery.

Gender

ALL

Eligibility criteria

• Inclusion Criteria:
• • Senile cataract patients, with or without macular disease, the impact of cataract on vision has affected the daily life of patients.
• Exclusion Criteria:
• • Glasses can obviously improve eyesight
• • In addition to macular disease, combined with other eye diseases that seriously affect vision, resulting in no significant improvement in postoperative vision
• • Complicated cataract surgery due to trauma and other reasons
• • Combined with other eye diseases not suitable for intraocular lens implantation
• • Patients with systemic diseases who cannot tolerate surgery