Why We Built an Axial Length Estimator — And Why It Must Be Used Carefully

Richard Kadri-Langford
1 day ago
3 min read

Axial length is now widely recognised as the gold standard for monitoring myopia progression.

But there’s a problem.

Most patients — especially children — don’t have historic axial length data.

What they do have is:

Spectacle prescriptions
Refraction history
Clinical notes

So the question becomes:

Can we use that existing data to estimate what axial length might have been?

That’s exactly why we’ve developed the Myopia Focus Axial Length Estimator.

Why This Tool Exists

In an ideal world, every child at risk of myopia would have:

Baseline axial length recorded early
Regular follow-up measurements
Longitudinal growth tracked over time

In reality, that’s rarely the case.

Many practitioners are now seeing patients who:

Are already myopic
Have several years of prescription history
But have no axial length baseline

This creates a gap.

Because without that baseline:

You can’t assess how fast the eye has grown
You can’t confidently evaluate past progression
And you can’t fully contextualise where the patient is today

This is where estimation becomes useful.

What the Estimator Can (and Should) Be Used For

Our estimator uses available clinical inputs (such as refractive error) to provide a best-fit estimate of axial length.

Used appropriately, it can help with:

1. Retrospective context

Understanding approximate historical eye size when no measurements were taken.

“If this child was -2.00D two years ago, what might their axial length have been?”

2. Patient and parent communication

Helping explain:

How the eye may have grown over time
Why early intervention matters

3. Clinical storytelling

Supporting discussions such as:

“This is where we think things were”
“This is where we are now”
“This is why we need to act”

But Here’s the Critical Point

This is not a measurement tool.

And it should never be used as one.

What the Latest Research Tells Us

Last year research on axial length centile curves - by Bullimore et al - highlights a broader issue: -

Many commonly used tools in myopia management are not designed for tracking true eye growth.

Key findings include:

Population-based models (including centiles) reflect distributions, not individual growth
Myopic progression can occur without obvious shifts in position or category
Cross-sectional data can give a false sense of stability

The same principle applies here.

The Limitations of Axial Length Estimation

It’s important to be explicit.

1. It is an approximation

The relationship between refractive error and axial length is not fixed.

It is influenced by:

Corneal curvature
Lens power
Individual ocular anatomy

Two patients with the same prescription can have different axial lengths.

2. It cannot detect progression

Because it is derived from indirect inputs:

It cannot measure small changes
It cannot assess treatment efficacy
It cannot replace longitudinal tracking

3. It carries inherent variability

Even under ideal assumptions, estimation introduces uncertainty.

Which means:

It should never be used to make clinical decisions about progression or control.

So Why Use It At All?

Because despite its limitations, i can helpt solve a real problem:

You cannot go back in time and measure axial length.

But you can:

Use existing data intelligently
Reconstruct a likely clinical picture
Improve understanding and engagement

Used correctly, it adds context — not certainty.

Where This Fits in Modern Myopia Management

The direction of travel is clear:

Measure early
Measure regularly
Track actual change over time

Axial length estimation sits before that journey begins.

It helps bridge the gap between:

Historical data (what we have)
Clinical best practice (what we need)

Our Position at Myopia Focus

We made a deliberate decision to include this tool — but with full transparency.

We believe:

It is useful for education and context
It is helpful for retrospective understanding
But it is not suitable for monitoring or decision-making