ESCRS 2026: Beyond LOCS III: An autofluorescence-based approach to objective cataract grading

Cataract is a leading cause of visual impairment worldwide, and cataract surgery is among the most frequently performed procedures in medicine. Yet preoperative grading still relies largely on the Lens Opacities Classification System III (LOCS III), a subjective slit lamp–based system whose scores can differ between graders.¹ That variability carries more weight as patient expectations rise and optically complex IOLs demand more precise preoperative assessment.

Ahead of the 44th Congress of the European Society of Cataract and Refractive Surgeons, held September 11-15, 2026, in London, Alessandro Arrigo, MD, spoke with Ophthalmology Times Europe.² Arrigo is with the Department of Ophthalmology at IRCCS San Raffaele Scientific Institute and Vita-Salute San Raffaele University in Milan, Italy. He discussed a quantitative cataract grading method that he and colleagues developed using blue light autofluorescence confocal imaging, a modality better known from medical retina.³

The approach builds on the crystalline lens's role as the eye's main blue light filter. It generates three metrics: a morphological index and bright and dark energy indexes. The study included approximately 40 patients across cataract stages, with young, cataract-free patients as reference cases. The metrics correlated with LOCS III grades from a single expert grader and with the signal-to-noise ratio of retinal imaging. A manuscript describing the work is under review.

The Q&A

Note: Transcript lightly edited for clarity.

Why does preoperative cataract grading need a new, objective approach?

Alessandro Arrigo, MD: During the…ESCRS meeting, I [presented] a new way to perform objective, quantitative cataract grading based on blue light autofluorescence confocal imaging technology. That is something that came from medical retinal diagnostics, because blue light autofluorescence is very important when we speak about retinal diseases such as age-related macular degeneration.

We know that cataract is a leading global cause of visual impairment, and it is also probably the most performed surgery all over the world. It is even more fundamental to perform the correct presurgical planning before the surgery, for several reasons. First of all, to try to understand how difficult your surgery is, meaning how advanced the cataract is. And this is fundamental, especially to avoid intraoperative and postoperative complications that may derive from a challenging or difficult cataract.

Presurgical planning is also important to try to optimize the visual and refractive targets and outcomes, because nowadays the expectations of patients are growing. The patient wants to have the best visual acuity possible and also the best visual quality possible. Not only the acuity, but also the quality.

The problem in this field is that there are several cataract grading systems. Some are based on slit lamp examination, others on color images, and also OCT [optical coherence tomography]. But at the end of the story, we know that the most used one is still the LOCS III [Lens Opacities Classification System III] approach. It is a slit lamp, so a subjective approach that tries to understand the [severity] of the cataract based on the color of the cataract and also the size of the opacities, whether it's nuclear, cortical, or mixed. The limitation of the LOCS III system is the fact that it is subjective, because if two or more ophthalmologists test the grade of the cataract, they can answer with different scores. So it's something that is not as reproducible as we want.

Why use blue light autofluorescence to assess the crystalline lens?

Arrigo: We know from physiology that the most important filter of blue light is the crystalline lens. The filtering process of blue light is very important, especially to preserve the retina, because we know that blue light is a potential damage for the retina. On this biological assumption, our main hypothesis was that the blue light filtering properties of the crystalline lens decrease over time and that this is strongly associated with the grading of the cataract and the stage of the cataract.

We know that blue light technology is still used in ocular diagnostics, in blue light autofluorescence. So, based on these assumptions, we hypothesized that blue light autofluorescence technology may be useful to provide an objective way to measure the cataract-related degenerative processes and to develop an objective way to grade the cataract.

How was the quantitative autofluorescence grading approach developed and tested?

Arrigo: Because it was completely innovative research (indeed, it was also the object of a patent), we needed to develop a quantitative pipeline. The target is to try to standardize the way of analyzing the cataracts coming from different patients, because the size, the intensity of the signal, and a lot of parameters may be different among a patient cohort. So we needed to develop a precise quantitative pipeline to standardize the approach for obtaining our final output.

We also developed three quantitative metrics that we named the morphological index and the bright and dark energy indexes. These parameters were an attempt to obtain numbers, some values that could be correlated with the grading of the cataract.

To try to compare our quantitative output with something that is universally accepted in the scientific community, we also included the LOCS III grading system, performed by an expert grader. That let us test the agreement and the correlation between the numbers coming from these parameters, this objective, quantitative way to grade the cataract, and the subjective LOCS III grading system.

Moreover, as an additional analysis of this research, we know well, unfortunately, that cataracts are directly related to the loss of quality of retinal imaging. The denser and the more advanced the cataract is, the worse the quality of the OCT and autofluorescence of the fundus. So we also tried to test the correlation between our quantitative grading system of the cataract and the signal-to-noise ratio, that is, the amount of signal that is lost because of the increasing opacity of the cataract.

What did the autofluorescence grading study find, and what comes next?

Arrigo: On this basis, we produced this research, including, I think, 40 patients with different stages of cataract and also young patients without cataracts as reference cases. We found that our approach was able to provide numbers that are objective, easily reproducible numbers that are directly correlated with the LOCS III grading system performed by this expert. So only one [grader], without heterogeneous findings. It also provided a quantitative way that correlated with the amount of retinal signal that was lost because of the presence of the cataract. We introduce this new quantitative grading system in the literature with a paper that is currently under second review, so we hope it will be published soon.

The final take-home message of this study was that we need a new objective classification system. We propose this as a promising way to reach an objective classification system. It may provide a lot of advantages for optimizing the preoperative, intraoperative, and postoperative phases of cataract surgery in the present time and for the future, after further optimization of this approach and larger analyses. It may also favor the inclusion of artificial intelligence–based algorithms that may help us improve the quantitative output that we can obtain from these autofluorescence images of the lens and the cataract.

What can an objective cataract grade offer surgeons that a slit lamp grade cannot?

Arrigo: There are a lot of answers. The first one is to avoid the human factor and the subjective factor. I see a cataract on a slit lamp, but what can be easy for me as an expert surgeon is difficult for a less trained, less expert surgeon. The point is that we don't know how difficult the surgery is until the instruments are inside the eye. So, in my personal opinion, an objective classification system may help, first of all, to optimize the choice of the surgeon. If I have an objectively difficult cataract, I can choose an expert surgeon. If I have an easy cataract, I can also choose a resident.

The second point is that the IOL [intraocular lens] power formulas are good, especially the next-generation ones, but they are not perfect. There are a lot of strange cases where the final refractive output does not correspond to what we calculated before. One of the main reasons is that the ocular media may interfere with the proper acquisition of all the parameters during the preoperative assessment: the topography and the biometry. So, in my mind, by introducing a quantitative way to grade the cataract, I can have a number, a score, that I can use as a corrective factor during my IOL power calculation. In my mind, I can reduce (maybe not avoid, but reduce) the amount of artifacts and [interferences] that are produced by the media opacities, and I can optimize the final calculation. These are, in my opinion, the two most important contributions of an objective system.

How does autofluorescence-based grading differ from OCT-based cataract grading?

Arrigo: As I told you, there are several attempts to perform quantitative cataract grading, especially looking at optical coherence tomography technology. But all these attempts are based on the morphology of the lens and of the cataract. My approach was the first one, considering the biochemical properties of the lens and of the cataract, because by using the autofluorescence technique, I can measure how good the function of the lens as a filter is. The function is related to the biological order of the components of the lens. So I can measure the biochemical degeneration and the amount of molecular and biochemical disorganization of the lens.

Comparing this approach and its biological assumption to the other approaches that exist in the literature, I am convinced that this approach may outperform all the others, because we speak about the molecular properties of the lens and of the cataract, not the morphology.

"I don't know if my approach is better than OCT-based or other approaches, but I am sure that my approach is focused on some changes occurring before morphology."

How significant is disagreement between graders using subjective cataract grading?

Arrigo: If I have 100 cataracts, 100 patients, and I have two expert surgeons, I can have a good agreement in at least 80 or 90 cataracts, 80 or 90 persons, and this is demonstrated by several papers. If I think about the published papers, the rate of agreement is around 80% to 90%. The problem is the remaining 10% of cases. Consider that this is the most performed surgery in the world, not only in ophthalmology but across all the medical specialties. So this 10%, this apparently small number of mistakes or disagreements, is very, very big.

We are in a setting where the expectations of the patients are growing, and today it is very difficult to manage our capabilities to solve a problem against the expectations of the patients. So it is important to try to overcome this kind of limitation and to optimize the way of understanding the type of cataract that I have in front of me.

How does lens opacity affect retinal imaging and quantification?

Arrigo: Working together with the retinal assessment is fundamental because of my background. I am responsible for the imaging unit of my hospital, and imaging covers a lot of things, starting from the ocular surface and reaching the optic nerve. But the most important application of imaging techniques is in the retinal field. So my background is mainly on retinal imaging, because it's the most used one: fundus autofluorescence, OCT, or OCT angiography.

We know that there are hundreds of artifacts and factors that interfere with the proper acquisition of retinal imaging and also with proper quantification. In medical retina, quantification is very, very important, with or without artificial intelligence, which is a second problem. If we speak about retinal thickness or vessel density, there are thousands of quantitative metrics in medical retina, and all these metrics are prone to artifacts. The first source of artifacts is media opacities. Ocular surface alterations, such as dry eye and corneal opacities, are less frequent than the others. The main reason is cataract, or also lens opacity that is not yet cataract, the step before.

So if I am aware, through a quantitative assessment, of the degree of lens opacity, I can correct my quantitative approach to all the other retinal metrics. We speak about two different chapters of ophthalmology: one is anterior segment surgery, and the other one is medical retina. Despite that, I think they must work together to optimize the overall diagnostics of the eye.

What is the key message of the ESCRS presentation?

Arrigo: I can give two points. The first point: as a surgeon, I am aware that we need new ways to optimize presurgical planning. We must take care of the growing expectations of the patients and also of growing technologies, because there are new-generation IOLs that are optically more complex than a monofocal IOL. We can't treat the preoperative assessment of these very complex IOLs like a monofocal one, so we need some steps forward for the preoperative assessment. This can be a way, because the first step forward is an objective and quantitative approach that can be easily reproducible over the world, so I have perfect agreement in every part of the world.

The second point is for the question of why your approach is beautiful, or more beautiful than the other ones. We know, again from physiology, that biochemical changes, the functional changes, always precede the morphological ones. I don't know if my approach is better than OCT-based or other approaches, but I am sure that my approach is focused on some changes occurring before morphology. I can detect the functional way of filtering blue light, and I can probably detect earlier and more detailed alterations than other approaches. So I don't know if it's better than the others, but the theoretical assumption is biologically plausible, and it may make sense.

What is needed to bring autofluorescence-based cataract grading into clinical practice?

Arrigo: We can add an additional point, which is a difficulty that I am addressing at the moment. I am a humble ophthalmologist, not an engineer, not a [physicist]. I had a good idea. Because I have imaging skills, I was able to develop and propose a first step. Not the final one; a first step. What is fundamental now, and what is challenging for me at the moment, is to involve companies and obtain the help of companies that have the technical skills, the resources, and all that is needed to translate and transform this first good idea (if I can say this) into something that can be really clinically relevant. Without the support of the companies that are dedicated to this kind of approach, it's a pity, but I think that we can move on in the right way.

References

1. Arrigo A, Aragona E, Bandello F. Quantitative cataract grading based on blue-light autofluorescence confocal imaging. Presented at: EVER 2025 Congress; October 10, 2025; London, United Kingdom.

2. Arrigo A. Objective, in-vivo cataract grading from blue-light autofluorescence imaging. Presented at: 44th Congress of the European Society of Cataract and Refractive Surgeons; September 11-15, 2026; London, United Kingdom.

3. Chylack LT Jr, Wolfe JK, Singer DM, et al. The Lens Opacities Classification System III. Arch Ophthalmol. 1993;111(6):831-836. doi:10.1001/archopht.1993.01090060119035