Comparing smartphone camera adapters in imaging post-operative cataract patients

Area of Science:

• Ophthalmology
• Medical Imaging
• Mobile Health Technology

Background:

• Smartphone-based anterior segment imaging is emerging as a tool for ophthalmological assessments.
• Evaluating image quality and clinical utility of different smartphone adapters is crucial for real-world application.

Purpose of the Study:

• To compare image quality and clinical confidence using four smartphone anterior segment imaging adapters: macro lens (ML), ML with LED illumination (ML-LED), no adapter (NA), and slit lamp (SL).

Main Methods:

• Anterior segment images were captured from 190 post-cataract surgery eyes using an iPhone 6 with ML, ML-LED, NA, and SL adapters.
• Ophthalmologists subjectively rated images for quality and clinical management confidence.

Main Results:

• No adapter (NA), ML-LED, and SL adapters achieved high image quality acceptability (100%, 93.7%, 86.3%).
• NA, SL, and ML-LED demonstrated high clinical confidence (100%, 98%, 93.2%).
• The macro lens (ML) adapter showed the lowest acceptability for both image quality (61.1%) and clinical confidence (37.4%).

Conclusions:

• ML-LED, NA, and SL adapters are suitable for visualizing anterior segment structures, achieving 86-100% acceptability.
• These smartphone imaging methods, combined with clinical data, offer 93-100% acceptable clinical confidence for managing post-operative cataract patients.