Technology-Driven Fitting: Enhancing Contact Lens Success with AI and Advanced Metrics

Overview

Recent technological advances, including AI and precise ocular measurements like sagittal depth and axial length, are transforming contact lens fitting and myopia management. Incorporating these innovations allows eyecare practitioners to personalize lens selection and better monitor disease progression, improving patient outcomes.

Background

Over the past two decades, optometry has seen significant growth in technology that enhances patient care, especially in specialty contact lens fitting. Traditional lens parameters such as base curve and diameter do not fully capture lens fit variability, as unmarked factors like sagittal depth and modulus also influence fit. Measuring sagittal depth and axial length has become increasingly important for customizing lens fits and managing myopia progression. Artificial intelligence (AI) can integrate these data points to guide practitioners in selecting optimal lenses and monitoring treatment efficacy.

Data Highlights

Studies have found the average total sagittal height of the anterior eye surface to be approximately 3,740 microns (range 3,140–4,040 microns) and 3,735 microns (range 3,290–4,170 microns). Axial length changes correlate variably with refractive changes: one study reported 1 mm axial length increase corresponds to 1.44–1.63 D change, while another found 2.50–3.00 D change per 1 mm. These metrics are critical for fitting and myopia management.

Key Findings

• Soft contact lenses with identical labeled parameters (base curve, diameter) can fit differently due to unmarked factors like sagittal depth and modulus.
• Measuring sagittal depth using devices such as scleral profilometers or OCT enhances fitting success, especially for specialty lenses.
• AI can be customized to incorporate patient-specific data (refractive error, sagittal depth, lens material preferences) to recommend optimal lens options.
• Axial length measurement is a vital parameter for quantifying myopia progression and assessing risk for ocular pathologies.
• Visual data displays and AI tracking improve communication with patients and parents regarding myopia control effectiveness.
• Future integration of AI with interoperable electronic health records and diagnostic instruments promises streamlined, personalized lens fitting and disease management.

Clinical Implications

Practitioners should incorporate sagittal depth and axial length measurements into routine assessments to improve contact lens fitting and myopia management. Utilizing AI-driven tools can personalize lens selection and enhance patient communication by visually demonstrating treatment progress. Embracing these technologies may lead to better patient adherence and outcomes.

Conclusion

Technology-driven fitting, supported by AI and advanced ocular measurements, represents a significant advancement in optometric care. Integrating these innovations enables more precise lens fitting and effective myopia management, ultimately improving patient success.

References

1. Various Authors/Studies (2024) -- Technology-Driven Fitting and AI in Optometry