Meet the 2025 Roger Mann Award Winner: Enhancing the Progressive Collapsing Foot Deformity Classification System

Summary

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Podcast Summary: Meet the 2025 Roger Mann Award Winner – Enhancing the Progressive Collapsing Foot Deformity Classification System

Podcast: The AOFAS Orthopod-Cast
Episode Date: December 10, 2025
Host/Moderator: Dr. Scott (AOFAS Podcast Committee)
Guests: Dr. Rebecca Blonde (HSS, lead researcher), Dr. De Cesar Netto (Contributing researcher)

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Episode Overview

This episode highlights the cutting-edge advancements in the classification and treatment of Progressive Collapsing Foot Deformity (PCFD), featuring Dr. Rebecca Blonde and Dr. De Cesar Netto, winners of the 2025 Roger Mann Award. The discussion centers on improving the PCFD classification system by introducing objective, imaging-based measures, and explores the clinical and research impact of these refinements. Listeners gain insights into the practical consequences for both diagnosis and surgical intervention.

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Key Discussion Points & Insights

1. Motivation and Background for the Project

• Development of PCFD Classification Improvement ([01:01]):

  • Dr. Blonde describes how the work builds upon a consensus meeting at HSS in 2020, with the aim to give objective, measurable parameters to PCFD’s broad classification classes.
  • “Basically, it's to further characterize the classification system by giving it objective measures for each class…that would help tailor what our treatment options would be.”
    — Dr. Rebecca Blonde, [01:25]

• Need for Standardization ([02:33]):

  • Dr. Scott notes the clinical difficulty posed by flatfoot deformity and the variability in both assessment and surgical decisions.
  • “First of all, I think we got to be speaking the same language...that's step one because we can't speak the same language, we don't know if we're getting the same outcomes on the same patients.”
    — Dr. Scott, [03:09]

2. Imaging Requirements and Clinical Application

• Reliance on Weight Bearing CT ([03:09]–[04:45]):

  • The new objective measures for PCFD are based on parameters derived from weight bearing CT scans, which offer superior accuracy compared to weight bearing x-rays.
  • Dr. Blonde clarifies: “To objectively classify it in this way, you need a weight bearing CT, but I think you can use weight bearing radiographs...CT is more accurate.”
    — Dr. Blonde, [03:40]
  • Dr. De Cesar Netto emphasizes that while the study uses CT, many parameters do correlate to those on plain x-ray; certain features (like Class C’s forefoot arch angle) truly require CT.

• Discussion on Imaging Quality and Accessibility ([05:07]–[06:08]):

  • Dr. Scott raises practical concerns about image quality and radiologist acceptance.
  • De Cesar Netto responds: “The resolution is probably a little bit less, but it's gotten way better as we get different iterations...you can actually make an x-ray from it.”
    — Dr. De Cesar Netto, [05:42], [06:07]
  • Future direction: Potential to digitally reconstruct x-rays from CT data for better comparison and broader accessibility.

3. Research & Clinical Impact

• Linking Classification to Surgical Decision-Making ([06:46]):

  • The authors see the revised classification as a way to guide treatment planning and post-operative assessment.
  • “Each class usually drives with it a certain surgical treatment…so we can use the classification then to drive the specific surgical treatments, the amount of each of those osteotomies that you might do.”
    — Dr. De Cesar Netto, [07:08]

• Opportunities for Algorithmic and AI Integration ([07:37]):

  • Dr. Scott envisions integrating AI for imaging interpretation, classification, and even surgical recommendations.

  • “Maybe there's help from AI here—basically, I put my X ray, my weight bearing CT scan into AI, it does a whole classification, and then...develop what is the algorithm, steps do I need to do.”
    — Dr. Scott, [07:37]

  • Dr. De Cesar Netto highlights ongoing work on a “smart flat foot” tool for patient-specific, algorithm-driven surgical planning ([09:05]).

  • “If you plug in a CT scan for a patient and it can tell you using these thresholds how much you need to correct…all the options for that particular person.”
    — Dr. Blonde, [09:15]

• Personalization and Correction Accuracy ([09:30]):

  • There is a clinical need to move from subjective to objective intraoperative decisions.

  • “I'd like to know, oh, you need to put in an eight and a half millimeter wedge. Okay, can do. Right...”
    — Dr. Scott, [09:30]

  • Dr. Scott lauds the significance: “Step one is we have to all agree on what we're talking about, and I think this is going to help that.”
    — Dr. Scott, [09:45]

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Memorable Quotes

• On the challenge of flatfoot:
  “I think every foot and ankle surgeon sees people with flat feet, both symptomatic and asymptomatic, which is also fascinating...It's like going to the heart doctor and telling them you have chest pain. And they're like, yeah, we have really no idea what caused this...”
  — Dr. Scott, [02:33]

• On imaging advances:
  “You can actually make an x-ray from [weight bearing CT data]...It's gotten way better.”
  — Dr. De Cesar Netto, [06:07]

• On future directions:
  “We're developing a smart... patient specific...the smart flat foot.”
  — Dr. De Cesar Netto, [09:05]

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Timestamps of Key Segments

• [01:01] – Project background and motivation (Dr. Blonde)
• [02:33] – The frustration and ubiquity of flatfoot problems (Dr. Scott)
• [03:09] – Importance of a shared language in classification; specificity of new system
• [03:30] – Discussion about imaging requirements: weight bearing CT vs. x-ray
• [04:08] – Crosswalk between measurement parameters on x-ray and CT (Dr. De Cesar Netto)
• [05:07] – Practical imaging limitations and advancements (all)
• [06:46] – Application of classification to surgical outcomes (Dr. Blonde, Dr. De Cesar Netto)
• [07:37] – Dr. Scott’s vision for algorithmic/AI-assisted decision-making
• [09:05] – AI and smart flatfoot tools (Dr. De Cesar Netto, Dr. Blonde)
• [09:30] – Objective targets for surgical correction (Dr. Scott)

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Conclusion

The episode delivers a detailed exploration of how precise, imaging-driven categorization of PCFD can enable improved patient outcomes and advances in surgical planning. The conversation covered the technical and practical aspects of implementing the new classification, the promise of AI assistance, and the next research steps in personalizing flatfoot treatment. The guests were celebrated for their important work that lays the foundation for clearer communication, better research, and ultimately higher quality care for patients with complex foot deformities.

Final Thanks:
“Congrats on a major award and thanks for spending some time talking with us about it. Really appreciate it.”
— Dr. Scott, [10:00]

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Transcript

[Podcast Host]

Welcome to AOFAS Ortho Podcast, where leaders in foot and ankle orthopedic surgery discuss the issues that affect you and your practice. Please note that the views expressed on this podcast do not necessarily represent the views of the AOFAS or its members.

[Dr. Scott]

So we're here at the annual meeting and we have the real pleasure of now actually going to have discussion with our Roger Mann Award winners. We have Dr. Balana here and Dr. Ellis, and they also have a lengthy title project. I think that may be one of the secrets of winning an award. I found that with the Gold Award and the Mann Award, if your title is over 25 words, you're a shoe in to win it. So I'm going to sort of summarize. So basically, they're looking at PCFD classification system and a threshold for radiographic cutoff to decide who is in what classification system. Hopefully I summarized that. Well, Dr. Blonde, tell me all about the project and basically why you came up with the idea and then what you've learned from your research.

[Dr. Rebecca Blonde]

So I did my fellowship at HSS and in October of 2020, there was a consensus meeting there to basically define and come up with a nomenclature for the PCFD classification system. And so this is kind of like a continuation of the work that has been done there, but also at a different institution with Dr. De Cesar Netto as well, because he has a huge collection of PCFD patients as well. He was able to obtain controls as well. So that kind of helped. But basically it's to further characterize the classification system by giving it objective measures for each class. Because, you know, if you just look at the classification system, basically it's pretty broad for each class and it doesn't have like, for example, class A. We're looking at hindfoot moment, arm. And that can range depending on if you're asymptomatic flat foot or if you're a normal foot or if you're cable various foot or if you are asymptomatic flat foot. Basically, the goal was to come up with objective measures for a broadly defined class. And that would help basically tailor what our treatment options would be and hopefully in the future would help us dial in correction in a sense too, because a flat foot is a complex, I think, clinical problem. It's hard to solve and there's so many angles that you can tackle flat foot. And this is basically a means to further characterize it, to objectify it even further so that we can treat it better.

[Dr. Scott]

Yeah, no, I think it is a frustratingly difficult, yet common problem. Right. I think every foot and ankle surgeon sees people with flat feet, both symptomatic and asymptomatic, which is also fascinating. People ask me, well, is it okay that my child has flat feet or is it okay that I have flat feet or just because I'm flat foot in this idea to do surgery on, are you going to do surgery on the other side? And my answer is always, I don't know. And I sort of feel like that's like going to the heart doctor and telling them you have chest pain. And they're like, yeah, we have really no idea what caused us and we have no idea what makes it better. I mean. Right. It's not quite that bad, but it's. It sort of feels that way. So obviously I definitely appreciate Yalls efforts because first of all, I think we got to be speaking the same language, which I think what this study is trying to do.

[Dr. Rebecca Blonde]

Yeah.

[Dr. Scott]

Then we know is an A, B, C, D, E. When we're writing papers and I'm writing a paper and you're writing a paper, we know exactly what we're saying. Which I think is super helpful. That's step one because we can't speak the same language. We don't know if we're getting the same outcomes on the same patients. And so I think it's fantastic. So one question I have about this is, does this require you to get a weight bearing CT scan in order to be able to do this classification?

[Dr. Rebecca Blonde]

It seems so, yeah, it does.

[Dr. Scott]

So you think just based on your study or you just think in general, in order to really classify this, you need a weight bearing CT scan.

[Dr. Rebecca Blonde]

Well, to object to objectively classify it in this way, you need a weight bearing ct, but I think you can use weight bearing radiographs. It's just, I think there are studies that have shown that weight bearing CT is more accurate than weight bearing.

[Dr. Scott]

Sure.

[Dr. Rebecca Blonde]

But in classifying, you know, pcfd, but specifically for these objective measures, we wanted to come up with values that, that were as accurate as possible and can only do that with weight bearing ct.

[Dr. De Cesar Netto]

And that's a critique that we've had this study in general because not that many people have a weight bearing CAT scan, but all the data that Rebecca looked at was weight bearing CAT scan parameters. But the truth is for many of these things there are equivalents on a plain X ray too. So. And we've looked at similar of those in the past and you can almost take the same cohort she gave the example of hypovolgus we looked at that on a weight bearing CAT scan, but that's something you would easily measure on a weight bearing X ray. There's a few parameters that we had that were much easier and actually you could only see on weight bearing CAT scan, for example, the class C which, which is the forefoot supination. One of the majors she looked at was called four foot arch angle. And that's really a. On a coronal view of a weight bearing CAT scan.

[Dr. Scott]

Yeah, I mean obviously a three dimensional analysis is going to be better than two dimensional and there are going to be some angles that can and should be measured in three dimensions. Right. That you just can't do in two.

[Dr. De Cesar Netto]

But I will say one of the things we've done studies also to compare parameters on X ray and how they might correlate to findings on CAT scans. So there's going to be like a crosswalk for people so that you to your question, really can tackle these problems without a wavering. Cassie. And it's just a very helpful research tool.

[Dr. Scott]

Yeah, for sure. We have one. It's fascinating. I use it some. I use it not as often as my partner does. Our radiologists seem to hate it, like really hate it because they think the quality of the image is not very good. I think the quality of the image is okay, but like if one of our lead muscle skeletal radiologists had their choice that they would get rid of the machine tomorrow. Do you guys have any trouble with, I don't know if quality is the best word but I mean it's obviously they're trying to use low amount of radiation so there are going to be differences in that and a sort of quote unquote standard CT scan. Do you think that causes any difficulty with your interpretation of it versus a regular ct?

[Dr. De Cesar Netto]

I, I can comment. I mean the resolution is probably a little bit less, but it's gotten way better as we get different iterations and now actually the wavelength CAT scans come up to the hip. The resolution at the hip is probably a little bit less, but it's still excellent. And actually one other thing they're working on and getting better at is what's called a digitally reconstructed X ray. So you can take the wave brain CAT scan data and it's not a true CAT scan, it's tomogram. You're just seeing things in different planes and you can actually make an X ray from it.

[Dr. Scott]

I think that's fascinating.

[Dr. De Cesar Netto]

It's gotten way better.

[Dr. Scott]

So I think we're gonna get to.

[Dr. De Cesar Netto]

The point where you probably don't even need an X ray.

[Dr. Scott]

Right? Yeah. Because I mean, as you guys, you know, it probably mentioned most people are going to follow people with a weight bearing CT scan. Right. But if you had to able to sort of take that data set and turn that into an X ray, which I've seen before, I mean they were doing this 15 years ago when I was in medical school with CT scans and re engineering them to look like X rays, I think that could be helpful. And that way you may be able to take the information you got and correlate that even better with a plain X ray because it's in the same patient, you can measure the same angles on those two different study types, which. Fascinating. So yeah, again it's a great project. So what do you think the next steps are on this project?

[Dr. Rebecca Blonde]

That's a good question.

Well, I mean, I think what's helpful for this is now that we can kind of compare or look at severity of PCFD and look at treatment and how the changes in those objective measures may contribute to patient reported outcomes. Okay, yeah, no, if you dial in, you know, a certain amount of correction, does that help?

[Dr. De Cesar Netto]

Yeah, that's a great idea. So one thought would be to get a weight bearing CAT scan at six months afterwards and see are we correcting each of those classes? Rebecca in her presentation this morning was saying, and we believe it's like each class usually drives with it a certain surgical treatment. The class A for example, is usually you're medializing heel slide. The class B is a lateral column lengthening. So we can use the classification then to drive the specific surgical treatments, the amount of each of those osteotomies that you might do and then see what it looks like after to see if we got it back to a normal range.

[Dr. Scott]

That's really what I'd like. I mean I'd like. And maybe there's help from AI here. You know, basically I put my X ray my way. Brings CT scan into AI. It not only says, okay, you got class ABCD 1, 2, whatever, it does a whole classification and then we as researchers with you guys develop what is the algorithm steps do I need to do. And then, and maybe it's you do some and I do another because I can tell you for most of my flat feed I'm pretty algorithmic. It's a gastroc session, medial space of calciotomy, cotton osteotomy, FDL transfer, posterior tubal tenotomy. I probably do an Evans in 1 in 10 to maybe 1 in 20 patients. And I mean I Check promise scores. I publish my results. My patients do pretty well. I mean, of course, nobody has perfect results. I certainly don't. I have people that still hurt it nine months and I'm not happy with it. But I would say overall, I think my rate's pretty good. And Scott, you may recall, I think we did an interview, maybe it was five years ago now. And I think your algorithm has changed of how you were taking your own flat foot from five years ago. I think we had one of these podcasts, even as Caesar on maybe a couple of years ago, I said, you know, a lot of the focus has been on the angle of the subtalar joint. Well, actually makes some sense to me. The angle's off and that allows maybe the subtle joint to kind of spin and rotate. That causes a flat foot. Because we really don't know. Chicken or the egg. Is it the posterior templal tendon spring ligament? This angle, we don't know. Again, this is like going to the heart doctor saying, I have chest pain. We have no idea what caused it. It's great. So, but like with surgery, we're not addressing the angle of the subtalar joint. Nothing we do is addressing the angle of subtalar joints. Like, so you're doing subtalar joint osteotomies. I don't know. Right. But I'd love to know that.

[Dr. De Cesar Netto]

Well, it's a workaround. I think AI is right on too, because one other thing we're looking at right now independently, is we're developing a smart, like a patient specific. The smart flat foot.

[Dr. Rebecca Blonde]

I was going to bring that up too, as when you brought up AI Just, you know, if you plug in a CT scan for a patient and it can tell you using these thresholds how much you need to correct and you can have like a patient specific treatment options or all the options for that particular person.

[Dr. Scott]

Yeah. Because I mean, right now when I do my cotton, I just feel the front of the foot. I mean, it's subjective. I mean, I do this a lot. I think I have a good idea. I've had people, I've overcooked it. I've definitely had people have undercooked it. I'd like to know, oh, you need to put in eight and a half millimeter wedge. Okay, can do. Right. But I think all of us want to treat our patients better and give them the exact correction they need. And I just don't know that we have that yet. But anyway, I really appreciate yalls work. I think this is step one. Step one is we have to all agree on what we're talking about and I think this is going to help that. So I get really appreciate Yalls work on this. I think it's fantastic work. Congrats on a major award and thanks for spending some time talking with us about it. Really appreciate it.

[Dr. Rebecca Blonde]

Thank you.

[Dr. De Cesar Netto]

Thank you. It's an honor.

[Podcast Host]

Thank you for listening to the AOFAS Ortho Podcast, a Convey Med production. To learn more about joining our dynamic community of highly skilled orthopedic specialists, visit aofas.org.