Ep 384 - Is Ultrasound Lying About Your Gains?

Summary

Iron Culture Ep 384 - Is Ultrasound Lying About Your Gains?

Hosts: Eric Helms & Eric Trexler
Date: July 29, 2026
Main Theme:
This episode dives deep into the reliability and interpretation of ultrasound (specifically muscle thickness) and DEXA measurements in muscle growth/hypertrophy research. The hosts critically review a new study making waves in the field, discuss methodological concerns, and draw out implications for both research and practical lifting culture. The conversation blends technical analysis with their signature banter and historical perspective.

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Main Topic Overview

Purpose:
To assess whether recent research truly undermines the use of ultrasound muscle thickness for measuring muscle growth, and to explore the nuances and limitations of DEXA for assessing body composition—particularly in the context of interpreting the last decade of physique science.

“If this conclusion statement has veracity [...] think of all the hypertrophy literature you love from the last 10 years and then throw out 60% of it, basically is what this conclusion is saying.”
— Eric Trexler, 07:01

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Key Segments & Discussion Points

1. The “Splashy” Paper: Insights & Critique

[05:00–14:24]

• Study in Question:
  Balshaw et al. (2026)—claims ultrasound muscle thickness is a poor and potentially invalid indicator of muscle growth compared to gold-standard MRI.

• Methods Recap:

  • Reanalyzed secondary data from a 15-week resistance training/collagen study.
  • Compared B-mode ultrasound (muscle thickness) vs. MRI (cross-sectional area & volume) of the quadriceps.
  • Measurements taken pre/post in controlled conditions.

• Helms’s Critique:

  • Strongly worded conclusion is not as well supported by the actual data.
  • Three main concerns:
    • Measurement positions differed (seated ultrasound vs. supine MRI).
    • Compared different anatomical sites (matching up ultrasound thickness with MRI slices is imprecise).
    • MRI (3D/2D) and ultrasound (1D) measure related, but not identical, constructs.
  • Variance and error: Muscle thickness changes measured were very small relative to the method’s noise.

“Noise being defined as how much variability was there between people relative to the average change. So you had some very large changes, relatively, some very small changes, but the absolute values aren’t much. So it’s just this pretty noisy measurement.”
— Eric Helms, 28:54

[Summary points at 30:58]

• Their findings:
  • Practically no statistically significant relationship between changes in ultrasound muscle thickness and MRI-measured muscle changes.
  • But: These may be more about the limitations of the study design (small changes, differing sites, device skill requirements) than wholesale invalidity of ultrasound.

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2. What Does This Mean for Hypertrophy Research?

[30:39–38:10]

• Contextualizing the Results:
  • Past research does show cross-sectional relationships between thickness, area, volume.
  • This study looks at correlations in change at the individual level—a much noisier signal.
  • Most studies, especially with muscle thickness via ultrasound, observe very small average changes (sometimes <1mm)—which can disappear into measurement error.

“When you have this tiny, tiny signal relative to the fairly unavoidable noise of a muscle thickness measurement with ultrasound, even with a very skilled technician, that's going to make it extremely difficult to correlate that measure at the individual level...”
— Eric Trexler, 24:25

• Implication for the Field:
  • Directionally, muscle thickness should relate to hypertrophy, but confidently detecting small changes requires large samples or longer interventions.
  • Throwing out 10–15 years of research based on this study is unwarranted.

“The narrative that this is evidence that we need to throw out all ultrasound measurements of muscle thickness, I think is objectively wrong based upon what we have, or at least not supported by this data.”
— Eric Helms, 36:01

• Meta-Analysis Comparison:
  • Trexler helped author an enormous new meta-analysis (Roberts et al., 2026, preprint) showing—contrary to Balshaw et al.—that, across hundreds of studies, muscle thickness tends to show greater change than MRI area, not less.
  • Discrepancy highlights the outlier status of the Balshaw paper.

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3. Bigger Picture: How to Use Muscle Thickness Data

[37:52–42:49]

• Practical Research Design:

  • If using muscle thickness, ensure adequate training stimulus/length to get sizeable change.
  • Consider multiple measurements and robust technique to minimize noise.
  • Interpret studies with small sample sizes and tiny mean changes with caution—regardless of measurement technique.

• Nuanced Take:

  • Thickness, area, and volume changes all have validity but differing reliability and face value.
  • Instead of “throw out muscle thickness,” use it more carefully: larger sample sizes, longer time frames, and/or as one piece to triangulate.

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4. DEXA: What Are You Actually Measuring?

[48:04–76:48]

• Listener Q&A Origin:

  • Why do the “energy values” for 1kg of fat/lean mass lost differ from textbook numbers? (E.g., 9400 kcal of body fat loss in research settings vs. the “7700 kcal per kg” rule.)

• DEXA’s Compartment Model:

  • DEXA separates body into bone, fat mass (lipid), and lean soft tissue (includes water, glycogen, protein).
  • DEXA fat mass = lipid only—not all adipose tissue, which contains water and protein too.
  • DEXA lean mass = contractile proteins + water + glycogen.
    – “Because water inside of fat tissue is lost, that fat tissue looks smaller because the adipocyte is smaller. Right? So you're going to see a similar visual change whether or not you're losing triglyceride, lipids, or water from that fat cell. But on a DEXA scanner, that's not the case.”
    — Eric Helms, 53:19

• Body Composition Tech Evolution

  • DEXA: Now the field’s mainstay for practical, noninvasive, repeated whole-body body comp.
  • Other tech (BodPod, underwater weighing) has largely been abandoned due to inconvenience or unreliable participant experience.

• What Changes DEXA Can Miss:

  • DEXA cannot distinguish water/glycogen/protein in “lean mass.”
  • Lean mass changes can reflect water shifts—think glycogen/water loss, edema, even dehydration.
  • DEXA “fat mass” does not track subcellular or structural changes in adipose (e.g., increased water in shrinking adipocytes).
  • “Squishy fat” and the “whoosh” effect: Adipocytes may temporarily hold extra water as lipids are lost, delaying actual tissue shrinkage on imaging—and potentially leading to sudden drops (the “whoosh”) once the water is expelled.

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5. Notable Quotes & Concepts

• On Interpretation:

  “This paper is a really cool demonstration of [signal-to-noise issues]. I don't think ... the last 15 years of hypertrophy research is a lie. So that's really not the case. We've always had to be cognizant of ... small signal relative to big noise in small groups of people...”
  — Eric Trexler, 41:26

• On DEXA vs. MRI for Muscle Loss (e.g., in GLP-1 drugs literature):

  “You decide, which one am I more concerned about? And I would say when it comes to that particular topic, I put a little more weight in the MRI data than I do the DEXA data. For some of these reasons we talked about.”
  — Eric Trexler, 78:43

• On Current Best Practices:

  “If you looked at this study and you were like, okay, I don't have access to MRI and I want to do research with the ultrasound unit that I have ... You wouldn't say, ah, screw it, I might as well sell this on the street for a dollar. Instead ... I probably need a larger sample than I would need, or multiple measurements at pre and post, because that can also improve your precision.”
  — Eric Helms, 35:01

• On Banter and Legal Rights:

  “If you only have one or two Ds, you're missing a critical D. The real money would be ... Ds that are greater than 3 ... my statement for the record did not state that 1D and 2D, 3D, and 4D are different. And I'm not stating that now. Legally.”
  — Eric Helms, 80:10

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Timestamps for Key Segments

• [05:05] – Main topic intro: Why ultrasound thickness and DEXA matter for the lifting world
• [08:53] – The “controversial” Balshaw paper walk-through
• [15:50] – Muscle imaging methods explained (ultrasound vs. MRI: 1D, 2D, 3D)
• [23:00] – Main limitation: Tiny changes in muscle, swamped by measurement error
• [30:39] – Should we trust 10+ years of muscle thickness studies?
• [36:01] – Why “throw out ultrasound” is the wrong take
• [43:44] – New meta-analysis data confirm: changes in muscle thickness valid at scale
• [48:04] – DEXA deep dive: What do the numbers really mean?
• [57:45] – Evolution of body composition measurement—why DEXA took over
• [62:43] – “Squishy fat” and water in adipocytes
• [73:14] – Edema & water’s role in lean mass measures
• [76:48] – Practical ties: GLP-1 drugs, “muscle loss,” and the DEXA/MRI disconnect
• [80:09] – Legal banter: The “muscle journey” pyramid/triangle “Ds” joke

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Key Takeaways

For Evidence-Based Lifting & Physique Research

• Ultrasound muscle thickness isn’t a scam—but its utility depends on magnitude of gains, measurement reliability, and research design. Small studies with tiny changes = major caution required.
• MRI remains the reference standard for precise muscle volume/area, but is expensive and labor-intensive.
• DEXA is excellent tech, but not infallible:
  • DEXA “fat mass” ≠ all tissue in fat depots; “lean mass” includes water/glycogen/protein.
  • Useful for trends and large changes, but beware over-interpreting small shifts or applying textbook kcal/kg values uncritically.
• Biological reality is messy:
  • Adipocyte (fat cell) water and lipid dynamics don’t always match “expected” textbook models.
• Meta-analyses > single outlier studies: Always situate splashy findings in the wider evidence landscape.
• Be methodologically literate:
  • Know what your chosen measurement technique does and doesn’t capture—whether lab vet, coach, or keen lifter.

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Notable Moments & Humor

• Trexler’s “Come into my van for an MRI” riff [18:12]
• Methods nerd humor about PhD students manually segmenting MRI slices [12:51–13:35]
• Triangle scheme, “Ds” legal banter [80:09]
• Ongoing ribbing about social media natty/not “expert analysis” [01:16–02:50]

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Conclusion

[Summary by Eric Helms at 73:14 & 76:48]

• “1D isn’t 2D isn’t 3D”—different muscle imaging methods capture different aspects, with variability in reliability/validity.
• Signal-to-noise matters: interpret muscle changes, especially with ultrasound, with caution when changes are small.
• DEXA’s three-compartment model is a huge advance, but don’t conflate DEXA fat mass/lean mass with pure adipose/muscle tissue.
• Be a savvy consumer of physique research—methods matter, context is king.

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If you’re a coach, lifter, or research enthusiast, this episode arms you with a skeptical, informed lens for interpreting “cutting edge” body composition science and for making the most of the tools available—without falling for headline hype.

Transcript

[A]

Foreign.

[B]

What's up, everybody? Welcome back to Iron Culture presented by the Mass Research Review. I am Eric Trexler, joined as always by Dr. Eric Helms. Helms, how are we doing today?

[A]

You know what? I am doing pretty well. I tried to do single leg leg press last night and I was surprised at the level of pain sensitivity and range of motion differences between legs. And I was like, oh, what's going on here? And then I just kept warming up and it was fine. I learned again. I'm just, you know, so we don't broken old man.

[B]

So we don't need to go in for the double hip surgery. Round two.

[A]

Well, I saw some. It was more around the knee. I did see some pretty convincing reels about Conor McGregor's injury that if I followed certain protocols which would have obviously prevented that. Maybe that's what I need to be doing. I just need to hire a movement guru.

[B]

It's amazing. In America, healthcare is so expensive. If I could just film all my injuries and put them on Twitter, I'd have all the answers in two seconds. Free of charge.

[A]

100%. Yeah, it's crazy. I've also thought about natural bodybuilding. It's something that it seems like the Internet is quite good at. Is instead of investing in trained polygraphers and time consuming processes of going over a banned substance list before, you then take a 30 minute to one hour polygraph. And then if you do happen to win or get prize money as a pro, taking an expensive blood test or urine test, we could just ask those guys. Most of the time they're guys in YouTube, like, hey, which one of these folks are natty or not?

[B]

You know what, that'd be really interesting to see exactly how far if we did just leave it up to like YouTube commenter committee, where would we set the kind of natural limit for like, that is as muscular as a person can be. With our committee endorsing their natural status, I'd be really, I'd be really interested to see exactly how far low that that gets pushed. You know what I mean? Oh.

[A]

It's an entirely dependent thing upon what people have been normalized to and habituated on the Internet. So like in like 2005, when we started, it was like, of course that guy's natty. He's only like 220@6foot. Because we were. We hadn't been disabused. And then sometime in 2013, you're like, that guy has a full six pack. No way. No way.

[B]

Yeah.

[A]

How do you do that with and

[B]

like I feel like back then, because natural bodybuilding was so niche and if you followed bodybuilding, you followed ifbb bodybuilding. So yeah, like if you looked at somebody who was on stage and they were 5 foot 7 and they weren't 260 lean, you're like, what's this guy's a twig? You know, he's hardly pushing 200. And then you realize like, wait a minute, 700 natural 200, that's 5 foot 7, 205% body fat. I don't know. So all that is to say, yes, our minds were very warped. Now I think they're warped in the other direction. But anyway, not related to the point of the podcast. But before we get into the actual point of the podcast, Helms yes, we should probably do some business. So folks, as always, you know, if you like the show, many ways to support it. Make sure you like rate, subscribe, review, post, post the episode, share it with friends. Let people know you like it. Maybe they'll like it too if they have good taste like yourself. If you do leave a review, we prefer good ones over bad ones. Generally five stars is what people leave. If you want to dig even deeper into the mass universe, you know where to do it. You go to massresearchreview.com we put out every single month a research review. And by the way folks, I know most of the audience cannot read. Nothing wrong with that whatsoever. All the articles, there are multiple ways to listen to them. We have video lectures that go up every month, so it is a multimedia experience delivering you every month the newest, freshest, hottest, most useful research related to your training, nutrition and coaching. So make sure you check out massresearchreview.com also if you want to submit questions for the show, massresearchreview.com Ironclass culture We would definitely love to load up more questions for our next Q and A episode time. TBD on that. And then finally, if you want to support our friends, which is a good thing, our dear friends over at elite FTs make extremely high quality lifting gear and apparel. So if you want to save 10% on your next order, go to EliteFTS.com and use the discount code MRR10. That stands for Mass Research Review 10. Helms, what did I miss?

[A]

God, you didn't miss anything. You just shot on target after target.

[B]

The guy can't miss. All right, so Helms, we have an episode today that I think is going to cover a couple things that are extremely relevant to anyone who follows the research, right? So we are in this evidence based fitness online space. And every now and then a paper comes out and it may be about some flashy topic, you know, you name it. Lengthen partials, reverse dieting, insert any hot topic. And in many cases those papers are going to, if they're listen, if they're looking at muscle growth hypertrophy, a huge percentage of them are going to be reporting muscle thickness measured via B mode ultrasound. If they're looking at, you know, whole body composition, body fat percentage, and maybe even looking at hypertrophy, fat loss, things of that nature at the whole body level rather than the muscle level, they're going to be reporting in many cases values from dexas. And so in this episode we're going to talk a little bit about some nuances that may get missed when you're looking at some of those muscle thickness measurements from ultrasound or looking at those whole body DEXA measurements. And these nuances actually become pretty important sometimes when you're interpreting the broader literature, especially a literature that combines papers using measurements from all different sorts of methods trying to quantify the same exact thing. So we'll get to DXA toward the end of the episode. But to start out with the real main meat of the episode all relates to a paper that just came out. It actually didn't even really come out yet. It's published ahead of print, which means the manuscript is ugly and unformatted and all that stuff. But you can still find it on the Internet. And this is by Balshaw and colleagues and the paper, the title is Ultrasound Muscle Thickness is a Poor Index of Criterion. Magnetic Resonance Imaging Measures of Resistance Training Induced Muscle Growth. And if I may read just the conclusion from the abstract, which is pretty much how I do things these days, a lot of people will tell you to read the whole paper. I strongly advise against that. If you want to do science at a high level, go to the abstract, don't read the whole abstract, just go to the conclusion. So the conclusion says overall change in muscle thickness measured via ultrasound was not an accurate or valid index of resistance training induced muscle growth. And it is recommended to exercise substantial caution in the use and interpretation of ultrasound muscle thickness in the context of resistance training adaptation. Now, Helms, I'm gonna let people look behind the curtain here, some inside baseball, how we make the show. But basically before we recorded, I think last week or the week before, I basically mentioned, hey, I just came across this abstract and I can't download the paper yet, but this is kind of a big deal if I am to believe this conclusion Sentence. Right. I mean, basically think of all the hypertrophy literature you love from the last 10 years and then throw out 60% of it, basically is what this conclusion is saying. Right. So most of what we've all been arguing about, and to the extent that there's any online consensus, most of what's informing that consensus, I think probably most, if not much, is using B mode ultrasound to look at muscle thickness measurements. So, Helms, I'm going to let you kind of take it from here in terms of basically, I basically said, hey, we need to look into this because again, if this conclusion statement has veracity and is, you know, it's a bold statement. So unless there's all sorts of caveats that we can attach to this, this is going to be a pretty huge splash. So I don't know, let's walk through it and see if this is as big a splash as the one sentence from the abstract would indicate.

[A]

Yeah, so this, this was definitely a splashy title, a splashy abstract. And I will be honest, I'm not going to bury the lead. When I actually read the paper, I was far less convinced that the data were representative by those statements. And I think there's maybe three reasons for that. And then we can get into why we don't think this paper supports its conclusions quite as strongly as they're made and then what we want to do and find out in the future. So for a bit of background, they're like, what do they actually do? Well, they did a secondary data analysis of another study where they compared, I think they're using like, I think bioactive collagen peptides over like a 15 week training study.

[B]

Yeah. And by the way, if I may, one thing that I'm going to give them some credit here because, man, I don't know if you've noticed this, Helms. It's kind of uncomfortable to talk about. I feel like I've been reading a lot of randomized controlled trials these days with longitudinal resistance training programs and I guess people don't drop out of studies anymore. That wasn't really how it worked when I was a grad student. People love to drop out of studies. So in this study they start with 52 healthy people. Healthy people, right. So it's not like a clinical population. And they had 13 withdrawal. And so I want to give them a tip of the cap for just good reporting because I don't know if we have a reporting issue or an honesty issue these days, but we should have people dropping out of 15 week resistance training Study. So we are going to be critical of the paper, but I wanted to find an opportunity to give a tip of the hat.

[A]

No, that's always good to see. And I think a lot of that comes down to if you look at the wording, they're ambiguous as to enrollment versus completed.

[B]

Yes.

[A]

And sometimes they'll just get straight into we measured, Right? Yes. Which doesn't tell you anything. Right. Yeah. And it's very important it's measured baseline but not the post test.

[B]

Because if you've ever done a meta analysis and you do like a risk of bias assessment, there's all these detailed questions about how many people dropped out, how do you know that many people dropped out? And yeah, a lot of times you have to just say, I don't know. And it. You literally have to then ding the paper with a probable, you know, at least moderate risk of bias from. From that vantage point. Yeah. But anyway, go on.

[A]

Yeah, yeah. So I think at face value, what it looks like they did was they got ultrasound muscle thickness. For those who don't know. Ultrasound probe, same thing that you would use to, you know, check out your, your baby's health and potentially sex at a certain number of weeks into the pregnancy, which I don't know. And it can give you a thickness you can do that of depending upon the muscle and what you can actually see. Individual heads of muscles or a composite measure like quadricep thickness versus say rectus femoris vastus lateralis, vastus medialis. So this was a quadricep based study. They got all four heads, they looked at thickness as well as the composite measure. And what you're simply doing is, is you're identifying the border of that muscle and then drawing a line between the thickest point you have certain standardized places you'd put it. And for the overall quadricep thickness, basically you're going from femur up to the section right below the subcutaneous fat interface. Right. And then they've also got ultrasound, sorry, mri. So magnetic resonance imaging. This is often considered the gold standard for measuring changes in hypertrophy over time. You can take an individual slice of it and then you can trace it and you can look at a individual cross sectional area slice, or you can take multiple slices and you can try to calculate a volume. So that's essentially what they did here.

[B]

And if I may, Helms, if I may, that process sucks. At least when I did it. I don't know if they found with AI and leveraging the power of computing back in my day, I can't believe I'm old enough to be saying this, but you had to just go through manually section by section, because basically you're taking a bunch of 2D images to construct a 3D volume. It was a harrowing experience, Helms, as I was going through slide by slide by slide by slide to basically facilitate the quantification of different tissues. So my hope is for all the young people out there who are pursuing Master's degrees and PhDs, that that process has gotten a lot easier.

[A]

There are. I have now, I have a student currently using MRI, but not in our labs. He's overseas with Dr. Mao, who you've probably heard of, Dear Listener, if you've been paying attention to the research on comparing, say, seated versus lying, hamstring curls, overhead tricep extensions versus pushdowns. And they do a lot of really great work with MRI using volume. So my PhD student, Takahiro, as well as one of our research associates, Ricardo Padovan, and my prior master's student, Kai Homer, are all out there currently with Mao doing a bunch of cool stuff. So. But I have never personally used an mri, except for as a patient in a doctor's office. So a little different.

[B]

Yeah, that part is easy, to the best of my. The way I recollect it. You just lay down, correct?

[A]

Yeah. And then you get headphones and you listen to music while you hear some really weird noises in the background. And then hopefully you're not claustrophobic. So, yeah, two different measurements, and not only two different devices, but also measuring different dimensionalities of muscle. So we have a 1D comparison, a 2D comparison, and a 3D comparison. And I think it's important just to talk through what they did. So they looked at each individual muscle segmented every 15 millimeters along its length to get a slice. Okay. And then what they took was, was looking at the maximum anatomical cross sectional area of one of those slices, and then they looked at seven contiguous slices around the suspected maximum anatomical cross sectional area to try to get the single image with the highest anatomical cross sectional area. Now, importantly, this was done as we discussed, lying down in an mri while the ultrasound measurements, they were done based upon specific locations to try to get a reliable thickness measurement in a seated position on an isokinetic dynamometer, which in this case, just think of like a lab grade, like, extension, but it can be transformed into a bunch of other stuff.

[B]

And the reason they do that, I assume, is so you can fix the knee at a particular angle. Is that right? The knee and the.

[A]

Yes. Yeah. Okay. I think so. It might have also just been for convenience during the training and testing and being faster. So multiple benefits there. You could argue you might have them seated. You go through getting your gel together, talking them through the participant characteristics. Sign this, do this, because you generally want someone just chilling for a while off their feet to kind of get a resting, if you will, ultrasound measurement so that it's not confounded by having just walked up the stairs, being led around, doing a warmup, all those other things. Right. Because those can alter the muscle thickness.

[B]

Yeah, because we used to always check, even if we had them laid down, laying down with something under their knee, we would always check with a goniometer to make sure that our little thing was placed properly. So, yeah, a lot of benefit. It's a lot easier if you just throw them on a dynamometer because you can literally lock it in position with it with a goniometer. So, yeah, a lot of benefit there.

[A]

Yeah, correct. Because isochemic dynamometers are basically like transformers. They can measure most joints in the body that are, you know, appendicular, and then be able to test them at various joint angles, quite individualized. And then you'll have an electronic record of it because it's isokinetic, because it is a fixed movement thing or, you know, speed, or even fixed in place, if you're doing the isometric option. So just people know, because I know this is something. Swelling is a big concern around hypertrophy measurements. They took the measurements five to seven days before and three to five days after this resistance training intervention. And another thing to point out, just a bit of an anatomy lesson here. So we got the quadriceps, the rectus femoris is biarticular. So that means that it attaches at the hip and the knee. So its resting thickness and length and how taut it is is going to change not just from knee position, but also hip position. So when you're in a seated position, not only is your knee different, but also your hip. So that's impacting specifically the rectus femoris, but also when you're lying down, your knees are straight. So what we're looking at is two different positions which probably are going to impact muscle morphology to some degree. And I think that's a critical thing to understand. And then the other thing to understand is that we're potentially comparing two different sites in that different position on the quadricep with where the ultrasound was and where the comparative slice that was cross sectional area was. And then, of course, muscle volume is taking into account all of those composites of cross sectional area. So that's a bit of the methodology of what they did in this study. Now I think we should probably think about the actual construct that they are measuring. Okay, we got 1D, 2D, 3D. What does that mean? So we are looking at the total area of a slice like you're looking at a scan, and you would actually trace it and you would do math to determine the area. The thickness measurement, that's really easy. That's just the millimeters from border to border or bone to fat interface, depending upon the measurement, or they might just be added together. Sometimes those composite measures are not just actually one measurement, which I think they were in this study, which is important to note. And then, yeah, the volume is then calculated for the 3D space of that estimated muscle volume. So the first thing we have to ask is what relationship between these measurements should we expect? And just because MRI is considered the gold standard, because it can measure cross sectional area and volume, it's looking at, I mean, obviously muscle adapts in more than one, one dimension, right? So it is, it has what you would describe as more face validity. This is probably the thing we're actually truly interested in, or closer to it, because we're not going to actually dissect the person and say, weigh the muscle like they actually do in animal studies. So we're trying to get the best non invasive measurement. And there are invasive measurements. You can do a biopsy and you can look at individual fibers and how they grow. But in this case, when we're looking at imaging, we're comparing 1D to 2D to 3D. And you could make an argument that one is probably closer in terms of face validity to the construct you're interested in. But in terms of mathematical validity, they are what they are. Right? And the question is, do they agree? What is the agreement or the relationship to how they change? And I think it's important to understand that we maybe shouldn't expect thickness, area and volume to change in exactly the same way. And that's going to be muddied even more by one point that I already made, and I'll have pitch it to you to make the other different positions which change morphology, such as knee and hip position, as well as maybe not measuring over the same location in this specific instance of area versus thickness. But I think it's also important to point out what kind of changes were we looking at in the first place? Because you can measure something cross sectionally, and I don't mean the cross sectional area but at one time point, right, we can just pick somebody off the street and say, hey, how would you like to come into my van? I've got an MRI there, an ultrasound, they spray you with mace, you change your wording, you ask someone who's not a child and then you're good to go. This was what I did last week, so that is one way to do it. Or you can say, hey, I need you to come into this van with me for eight weeks and we're going to get really sweaty together. And then again, you get sprayed with mace, you go to someone, you say, okay, we're going to do resistance training in this, in this van and you have someone with you, you let them know it's a legitimate university study. And then you can actually see not just a comparison of one time point, but the actual change. And there's going to be a given degree of variability that is associated with the actual change, normal day to day variability, as well as the inherent variability of the device, which for some of these measurements is going to be impacted by the user. Ultrasound measurements are a skill, right? How much do you compress it, how much gel do you use, how steady is your hand? Do you have the probe at a slight angle or not? Mri, not so much. Although there is something to be said for how it's traced, whether you or an AI did that. But for the most part you're looking at just measurement error related to the device rather than measurement error of the user plus the device and variation. When you're looking at changes over time and hoping that the actual change is substantially more than that unavoidable error so that you can get the signal for the noise. So in this case, Trex, what was your main critique, or I'd say main limitation of looking at some of these relationships?

[B]

Yeah, I think one limitation that you have to keep in mind with this paper is there's a lot of focus on. So, for example, Helms, I'm pretty certain that there are plenty of previous cross sectional studies where they say, hey, it looks like a thicker muscle tends to be a muscle with larger area, which tends to be a muscle with larger volume, right? Like those correlations have been done and they seem fine, but with this study they were looking at correlations in the change, you know, how much hypertrophy occurred as measured by this measurement method versus that method versus the other method. And so one of the challenges there is when you're doing how much does my change in muscle thickness at an individual level correlate with my change in muscle volume, again, we're thinking with volume we have opportunities for the muscle to expand in three dimensions. We're not going to miss it by taking the wrong cross section because we're looking at this huge stretch of the muscle. We have a really good feeling that if that muscle grew, we're going to get plenty of signal amidst the modest amount of noise there. But when we look at this study with the changes in muscle thickness, so just for example, the average change in thickness for the vastus lateralis was less than a millimeter, so 26.3 to 27.2 millimeters thickness. For the vastus intermedius it was 1.1 millimeters. For the vastus medialis it was just over half a millimeter. And for the rectus femoris, I think my table formatting is a little weird there, so I'll punt on that one because I'm very confused by the number I'm seeing. But in any case, you get the idea. We're looking at very, very small changes in muscle thickness relative to, to the error we would expect even with a very skilled technician. Okay. And so when you have this tiny, tiny signal relative to the fairly unavoidable noise of a muscle thickness measurement with ultrasound, even with a very skilled technician, that's going to make it extremely difficult to correlate that measure at the individual level with these other metrics of hypertrophy, which do have, like you said, greater face validity and we have a better opportunity to capture that two dimensional or three dimensional growth relative to this kind of crude one dimensional snapshot. And so for that reason, that was actually the first thing I mentioned to you, Helms is when I said Helms, oh my God. This paper makes a very bold claim in the conclusion, but I can't find the full text. And I said, I wonder if they just didn't grow much. And what I meant by that was not, and you actually corrected me on this kind of off the air, it's not that they didn't grow much, it's that as measured by muscle thickness, they didn't grow much relative to the error of that method. And therefore every individual measure you get is going to be this tiny bit of growth or shrinkage, you know, hopefully growth if you're lifting for 15 weeks, but lost in this C, I don't want to overstate it, but lost in this, this mixture of measurement error as well, which is very likely to distort those correlations. And so I think that's just a huge, huge factor to keep in Mind here.

[A]

Yeah. And I think there's. I've been thinking of how to discuss this in a way that wouldn't get too into the weeds or be confusing, especially if you're just listening. But. So when they present the data in this paper, they did their analysis on the percentage changes. So while these are very small absolute changes, the percentage changes make them look a little more normal, and they're not an abnormal level of change. This would be probably among the lower total changes that you would observe in the typical distribution of resistance training studies from pre to post. But you can also see the relative variability. So how much variation there is in these different measures. And they are higher for thickness. And that's exactly going back to what I said earlier. It's not just that there's more face validity. MRI does have greater precision because, like I said, there's fewer sources of error. The image is typically cleaner, and you are not necessarily just limited to one dimension. And there's more standardization. You know, if someone shifts a little bit or whatever, or you're up or down like that, those things don't occur in an mri. So, like, just as an example, if you look at the Vastus medialis in the figure, you see the change for muscle thickness is way lower. It's like an eighth of the height of the bar compared to the anatomical cross sectional area as well as the volume from mri. But then if you look at the error bar, the error bars are actually quite similar height for all three. So that means the error is like almost 10 times the size of the actual change. So what we're looking at for that vastus medialis muscle thickness change is a very, very, very noisy measurement. And noise being defined as how much variability was there between people relative to the average change. So you had some very large changes, relatively, some very small changes, but the absolute values aren't much. So it's just this pretty noisy measurement. And you could look at that and say, well, okay, hey, muscle thickness is therefore crap. And you're. And what you would. Your response would be, no, it has a quantifiable known degree of variability, and that has to be accounted for when we're looking for observing true changes that we are confident are not just variability. Right. So percentage changes, they do put everything on the same scale relative to itself, but they don't account for that, that error bar, that variability. We've talked about meta analysis on this podcast before. We often talk about trivial or small or moderate or large changes. These are different variations of effect sizes are often called standardized Mean differences, and those just simply take into account that baseline degree of variability, and then they look at how much change was there, often based upon the standard deviation of that measurement and the mean change relative to it. So it builds in some acknowledgment mathematically for what the variability is around the mean. A percentage doesn't do that. So one thing that I think would be really interesting, and I'll leave it to people better at stats than I to figure out what the best approach would be, is I would love to see a comparison where these values were standardized in some way, if it would change them meaningfully. But there's almost no way to get around the fact that you had not a whole lot of change. If we were to say, well, hold on, what is your, your reliability here? Am I confident that's an actual change, or is it probably within the measurement error that we're seeing here, at least for muscle thickness? So I think depending upon how you spin that, you could say, yeah, muscle thickness is trash. I don't even need to see the comparison to MRI or volume. Or you could say, well, hold on, it's not trash. It is a noisier measurement. That's been known, but that just means that we need to be accounting for that when we're looking at changes over time. Would you say that's a fair description that didn't get too down the rabbit hole?

[B]

Yeah, I think that's fair. And I think that's probably a good time for us to kind of just give a quick summary of basically what they found and then kind of transition to, practically speaking, what do we do with, with the last 10 years of hypertrophy research that largely focuses on muscle thickness.

[A]

Yep. Yeah. So, I mean, I won't try to try to sugarcoat it. What they found was essentially no real relationship between muscle thickness and anatomical cross sectional area or volume. And I think it's important to mention that we're not just comparing different dimensions, but also different devices. And the first thing that popped into my head, and I've actually had this thought before and I forgot about it, was, you know, you can get muscle thickness from an mri. You know, you can see the whole thing. It's just an image. It's a better image. Right. You don't even. And oh, by the way, just for anyone curious, you can actually get anatomical cross sectional area from an ultrasound, but it depends upon how much you can get into the field of view. So if you're assessing an untrained person's arm with the right probe you might be able to get it. If you're measuring a large trained person's quadricep, you're probably going to need a probe that has an extended field of view and then you get the snapshot and then you actually will trace it in the same way as an mri.

[B]

Right. Or you can, if you have a little bit of skill, you can shift it into panoramic mode and do the sliding image. That's what we used to do and it was a pain in the butt.

[A]

It is, it is hard to do the panoramic. And there's another dimension of skill there as well, because you need a contiguous image and depending upon the software you might use, it can try to line things up and fix it.

[B]

Yeah. Just to be clear, I think that there are plenty of people on this planet, wonderful people who I would trust their muscle thickness images, but if they told me, hey, I measured cross sectional area in panoramic mode with these sweeping images, I would say, no, thanks. I've seen you with the Ultrasound Pro, but I'm not interested. So what I'm saying is it's a very dramatic change in skill level.

[A]

Yes. And certain muscles are much easier to measure than others. And let's be frank, thickness is one of the easiest things you can measure with an ultrasound. You can get decent, reliable, and this is something you can quantify. Not just how good do I feel about it, but you can look at your inter rater reliability within day, between day. And if you're talking, you know, quadricep measurements, give me a few weeks of actually training someone like an hour a day and, and they'll be good to go. You start playing with the triceps, you know, now it's a little harder right now. You start like going, I want individual heads. Now we're getting a little more challenging. Biceps is also kind of hard. The pec isn't too bad. But then when you start doing mixed sex studies, you have to figure an anatomical location that works for everybody. There is a lot that does go into this that I don't think a lot of people appreciate. But nonetheless, I would love to just be able to discriminate between the device versus the D and say, hey, well how do we even see a change or sorry, a relationship between thickness and cross sectional area and thickness and volume just within mri. Because I think the kind of the brain dead take on this has been several people going like, throw out ultrasound. And I'm just saying, hold on, hold on. I just don't think there's going to be A consistent and strong relationship even between thickness, volume and cross sectional area. Because you're not going to see a perfectly uniform growth that expands the circumference of these non circle shaped objects. Right. That's just not the way math works. And even more so, the thickness changes are going to differ across the whole muscle. That's why we do anatomical locations. We'll often hand a permanent marker to the participant if they're getting serial measurements or pre mid post, especially to remark, especially in like repeated measures, short term ish studies, because we don't want to have to remark the thing. And I've seen people also use like pieces of paper or other measurements. There's a lot of tools to try to replicate the same location on someone's body. And we often like to give people an ISAC course. So they're really good at identifying bony landmarks. And you're measuring, you should be in the same spot. But I think a key critical point here is that if the thickness can vary because you're not measuring the same point on the muscle, that means that also that probably means the cross sectional area will. And that's why you take multiple cross sectional areas to get a volume. So if you're comparing a slice where you're getting cross sectional area to not even the same place where you get a thickness, and if the thickness would differ, you're probably seeing some type of multiplicative error going from 1D to 2D, where even if you had the same 1D measurement or the same location from the 2D versus the 1D measurement, that they would, you know, maybe be slightly better because the thickness would be the same. So anyway, all that is to say different location on the thigh, different body position and different dimension and different device. So I wouldn't have expected these to line up. But I also don't think that that means that none of them or only certain of these measurements are valid for measuring change over time. I think they are probably valid within themselves. And then in terms of the reliability and the precision, they have a known quantifiable degree of reliability. And if you looked at this study and you were like, okay, I don't have access to MRI and I want to do research with the ultrasound unit that I have and I don't have extended view of field of view, I got to do thickness, you wouldn't say, ah, screw it, I might as well, you know, sell this on the street for a dollar. Instead what you would do is go, oh, I probably need a larger sample than I would need, or multiple Measurements at pre and post, because that can also improve your precision. There's a lot of things one can do to actually have confidence in my measurements and my change or have a higher probability of being able to detect a smaller change over time. And if I don't think I can detect that, then I need to keep recruiting or I need to measure over a longer period. Like, these are the same problem we have in all studies, no matter what the measurement is. And it's just a game of math to figure out how to do it. So the narrative that this is evidence that we need to throw out all ultrasound measurements of muscle thickness, I think is objectively wrong based upon what we have, or at least not supported by this data. Yeah. Now, I have ideas on what we could do in the future, but I want to pass it over to you because I've been monologuing a bit.

[B]

No, yeah, I agree. I think one of the big takeaways, you hit the big stuff. But I think when we are doing this hypertrophy research and we are going to use muscle thickness via ultrasound as a measurement, we have to be cognizant of the fact that it kind of does take a pretty substantial increase in muscle volume, AKA hypertrophy, to actually induce a substantial measurable change in thickness. Right. And so, like you said, you know, we could do larger sample sizes, multiple measurements, but also, I think even just at the study design level, to the extent that it's feasible, you know, I mean, the best thing we can do for ourselves as researchers, like, help yourself out a little bit, try to make sure there's some very appreciable growth board going on before you go in for the post measurement. Right. So maybe it does mean that we have to, you know, crank up the dose of resistance training our studies. Maybe it means we have to make them twice as long as we thought. But I do worry that if we get too bogged down in the kind of standard paradigm of small samples, very modest hypertrophy measured via thickness, again, in the long run, directionally, it should be able to give us signals of what's going on in terms of growth. But I think we just have to be careful of how we interpret directional results when changes in total are very small relative to error. And so, Helms, if I can make that a little more concrete, and I'm going to just be as controversial as possible, when someone makes content about how sleeping absolutely destroys muscle growth, almost always they cite the same study. We actually have surprisingly minimal research on how sleep restriction, how much it really matters for hypertrophy, we know it makes you feel like shit. We see different measures of performance that decreases decrease. But, but there's this one study From I think 2010 and they had 10 individuals who were not resistance training and they underwent calorie restriction and they either slept for eight and a half hours a night or five and a half hours per night. So 14 days, no resistance training, 10 people. And the headline that everybody runs with is sleep restriction decreased the proportion of weight loss as fat by 55% helms and increased the loss of fat free mass by 60%. So this is killing your gains by 60%. Can you believe it? And what we're looking at there is we're looking at a measure of whole body body composition. I believe they use DEXA if I'm not mistaken. And basically in the minimal sleep group. So again we're talking about slashing three hours a night from your sleep. So this is a very substantial sleep restriction intervention. We're talking about how much fat they lost being a difference of 1.4kg versus 0.6kg. So we're talking about less than a kilogram of difference measured on a DEXA for changes that happened over 14 days. And as we know DEXA day to day volatility, it's not. You really don't want to build much of your worldview on 1 kg in either direction. On Adexa and again that 60%, 10 people and in 10 people and that 60% plummeting of gains. Basically what we're looking at is the loss of fat free mass of 1.5 versus 2.4 kilograms. And again that's showing up dehydrated. That, that'll explain the whole thing for you, you know, 1 kg of lean mass on a DEXA. So all that is to say what we're talking about in this study about muscle thickness with ultrasound. This is not new. We've always known that you have to be really cautious about how you interpret studies where we know there's measurement error. We're looking at very small signal relative to that noise and we have relatively small sample size. We know that we have to be really cautious about how this gets interpreted. So I do think like here's what I want to say and therefore I will say it because I'm allowed to. I think this paper is a really cool demonstration of that. So I'm glad they published it. I don't think it's like, I don't think there's nothing we can glean from this paper. But I do think that the conclusion statement came on very, very strong and has led a lot of people who maybe haven't dug into the full text to say, oh my God, the last 15 years of hypertrophy research is a lie. So that's really not the case. We've always had to be cognizant of. When you're looking at small signal relative to big noise in small groups of people, you better be cautious and you better triangulate that finding with the rest of the research.

[A]

Very well said. And I think there's almost some proof to at least the hypothesis that we're seeing some error involved in this. If you look at actually a recent preprint of a meta analysis that included a similar comparison to this but over a much larger scale by Roberts, which I believe you were one of the co authors on.

[B]

Yeah, that was a painful meta analysis to do. There's a lot of studies.

[A]

Yeah, I mean I was looking at the list of authors on it. There's many and several with a lot of statistical chops. And I'm like, oh, they must have had to divvy up the work on this because it was something like 400 studies that you guys included or something like that. Something crazy. 480 or some shit.

[B]

I don't know off the top of my head. But it was a lot. It was the biggest meta that I've ever been involved with and hopefully, God willing, the largest one I'll ever be involved with.

[A]

I mean, you guys covered almost like all resistance training data because this is a cool paper that people should read. It's pre printed, but it's essentially modeling hypertrophy, right? Yes. And looking at over time. And it has some really cool data. And this is a much larger version using more data and more muscle groups than a supplementary part of a 2023 meta analysis on effect size and resistance training that Steel did using just an arm cross sectional area model. So it's kind of cool to see that then replicated larger scale, more precision and more confidence. One of the other things that you guys did, and this is what I wanted to point out, relevant to this is there were so many studies included that you had a fair amount looking at MRI and a fair amount looking at ultrasound. And there was a specific comparison between the magnitude, just magnitude, not necessarily like reliability or agreement of MRI cross sectional area and ultrasound muscle thickness. And the opposite was shown in this study again on what 39 people that we're talking about versus 10 times that many studies, at least not study groups even. Right. And the cross sectional area measured by MRI tended to show smaller changes compared to ultrasound muscle thickness, which is the exact opposite of what we're seeing in this study, which is much larger changes substantially if you're looking at the means at least for certain muscles in terms of the changes in volume or cross sectional area. And those two were more related to another than ultrasound thickness. So just like that sleep study kind of seemed to indicate, if you don't think about the standard error or potential sources of error in ADEXA, you know, in 10 people over a short term time period, if we're looking at not much of a change in noisy measurements and comparing them and you go, oh, look at that. Muscle thickness shows no change in cross sectional area shows, you know, much larger changes relatively. And that goes against the largest meta analysis that I've ever seen in resistance training. Which one do you think is the outlier in terms of perhaps not being representative the actual change? So I will leave the critiques and the considerations there and I will say I also think this is a very easy to solve or I'd say easy to improve data set. Again, we can just simply look at within MRI itself, looking at the relationship between these three dimensions. We can do that at scale with multiple studies and do some type of actual meta analysis. I don't think there's enough probably for volume, but certainly as you guys demonstrated, there are enough for thickness versus thickness. I mean you'd have to get these people to actually send you raw data because people almost never, I don't think ever have I seen someone calculate MRI muscle thickness. Maybe there's a study out there, but I have never seen it. But that would be a really interesting comparison, MRI cross sectional area versus MRI thickness and then also compare it to ultrasound thickness. Then also potentially just doing a slightly different analysis, not using percentage change, using some standardized stuff. And this is something that we can get far more data behind. So like you said, I'm glad this is published. I think people are going to look at it like me and go, oh man, I really like would like it if we could answer this question a little bit better and hopefully it spurs that. So you know, shout out to the authors for, for resulting in that this is actually the way science is supposed to work. And also you did a great job talking about DEXA because I think that is our next topic of interest because yeah, this one actually stemmed from someone being confused by the energetic content of fat mass not tracking with the rough quote unquote 3500 calorie rule, which is actually about adipose tissue, not fat mass. And then I think most people don't understand how DEXA works, why it works that way and what it's actually telling you in terms of say lean soft tissue or lean body mass versus fat mass and bone. Because it's a unique three compartment model, right?

[B]

Yeah, yeah. I mean like all good podcast segments, this started with someone accusing us of being wrong. Helms, can you imagine the gall, the temerity, the boldness on the Internet? So someone who obviously was very cordial and polite, but they did say, helms, you fool, you wrote an article for Mass where you did all these hand wavy calculations about body recomposition and you had attributed the energetic value of losing 1kg of fat. You attributed it as a loss of about 9,400 calories from the body. And they were like, well, why not 7,700 calories? Because they had heard that number elsewhere. And so I dove into the comments. This is an interesting reversal. I dove in to defend you against your words. So normally what happens with mass is Mike Zordos or Lauren Clenzo Semple or I will write something and then someone will say something very nasty to Helms as if he wrote it. And then he will lose several afternoons of his life and a lot of stress as he defends himself for things he didn't say. But this was a nice role reversal, but it was a little easier.

[A]

The only reason I got away with it is because I live in New Zealand. So it happened while I was asleep. I woke up and it, you know, Mike had already basically said, hey, I'm pretty sure this is the deal, but can someone who's maybe a little more on the body comp side jump in?

[B]

I'm.

[A]

It's 3:00am for me, but Trek's to the rescue. Because imagine if I wasn't on New Zealand time. This would just be a continuation of the same pattern. I'm attacked for my words and I must defend myself. I'm attacked for your words and I must defend myself. I'm attacked for Lauren's words and I must defend myself or Mike. So this, it was, I wouldn't say it was a role reversal. I'll say it was a break from the typical thank you New Zealand time.

[B]

And what I also want to point out though is I want to do a little bit of victim blaming. And you often, when you are somehow defending yourself for what Lauren said, it usually involves you getting, like I said, grip, you know, pulled into these multi day, several dozen comment back and forth Wars. I'm starting to think that you're just not very skilled, that you lack the tact and precision, because I resolved it in one comment and then the response was, oh, makes sense. Thank you very much. Have a good day. So maybe there's something to be learned from that, Helms. Maybe you need to. Maybe you're just too mean on the Internet. Maybe that's what's happening, is that you're bullying people and then they get very defensive.

[A]

That's been the typical refrain is that I am a total jerk. I always take the low road. And I also have not changed my behavior over time, nor do I learn from my mistakes. So the good news is you're right, which I know you like. The bad news is I'm never going to change. It's going to keep happening, and I'm only going to get worse over time.

[B]

Nice. But anyway, so this whole discrepancy, 9,400 calories. I don't want to split hairs. The paper I usually cite by Kevin hall is, I think 9441. You don't want to forget those extra 41 calories. But no, I've seen it rounded several different ways. I've seen it 9,300, 9,400, 9,500, but in that ballpark. But this 7,700, if you just want to talk through what is that discrepancy and kind of how does that relate to essentially what we're talking about with recomposition and how we measure it using different techniques.

[A]

Yes. Yeah. So in the real world, what we see and care about is actually the loss of adipose tissue. Right. And when we say body fat, in a real world physiological sense, we do mean adipose tissue. And adipose tissue is not pure lipids. Right. It is a given proportion of structural stuff that contains some proteins and then a notable amount of water, but certainly not the primary amount. And then a large amount of lipids. It is predominantly lipid. Now, as I'll plant a seed here, the way that body composition estimation works many times depending upon the device, is based upon some assumptions about that water composition, not just within adipose tissue, but across tissues. And I think the DEXA equations operate off of it being like 87% or 85 or 90%, probably depending upon the year, the black box, like what goes into it. So there is an assumed hydration constant on the device you're working with for when that's an appropriate thing to have that is fixed seed planted. Okay. Now, in the real world, we sort of don't care about that. You know, if water inside of fat tissue is lost, that fat tissue looks smaller because the adipocyte is smaller. Right. So you're going to see a similar visual change whether or not you're losing triglyceride, lipids or water from that fat cell. But on a DEXA scanner that's not the case. And the DEXA does not measure adipose tissue. This is a dual X ray that is actually shooting X ray beams at you. And the things that are going to dictate how that reflects is tissue thickness and depth. And actually at a more like chemical level where the actual hydrogen and oxygen are and depending upon how they actually refract and reflect X rays. And an interesting thing is that water, glycogen and protein look really, really similar to a DEXA machine and they're going to have a similar ability to reflect that those X rays. And that's why dexa's measure three compartments. They can accurately discriminate between bone, adipose tissue and then what they call fat free mass or lean soft tissue if you want to also take out the bone. So it's kind of a unique three compartment model. Some of the other three compartment models out there don't separate it out into bone. They'll be looking at say water and then lean tissue and fat tissue. But for adexa, because of the similarities between how X rays impact water, glycogen and proteins, lean tissue includes water, including the water that is in fat mass. So when you see a fat mass calculation on a DEXA scan, which by the way, like I would say the amounts that we quoted in terms of how many hypertrophy papers use ultrasound muscle thickness at this stage of the game, with more and more publications happening at a faster and faster rate since the invention of dexa, a similar or even larger proportion of whole body changes in body composition are now being done with dexa. So fat mass changes are actually reporting the lipid losses and lean mass changes are including any change in body water, regardless of its location. And I think that's, that's a kind of the key thing that a lot of people miss. Would you say Trex?

[B]

Yeah, now that you mention it, it's actually really been a while since I saw a paper, not, I wouldn't say since the last time, but you just don't see a lot of papers that use BOD pod anymore. You don't see a lot of papers that use skinfold calipers anymore. These days, pretty much everything I'm seeing in Terms of whole body composition is predominantly either going to be DEXA or BIS or bia, you know, some kind of like in body device or something like that, which give very different. I have a lot more confidence in the DEXA stuff than the BIA BIS stuff. But yeah, it's been interesting to see. Like when I was coming up, you saw a lot more bod, pod air displacement, plethysmography. But that stuff has really fallen by the wayside and we've really. Underwater weighing. You don't see that ever anymore and helps. Here's the secret nobody tells you about underwater wing. The reason you don't see it anymore, in my opinion, number one, because no lab wants to maintain basically a small pool because it's annoying. Equipment wise, it's a huge pain. But also you basically have to simulate drowning to get a decent number. You have to have a person go underwater and get as much air out of their lungs as they possibly can and then hold it. And then they come up for air and they look distressed because they just simulated drowning themselves. And you say, I have great news. We're 5% done. I want you to do 19 more of those. So it's just a horrible tech like to get a decent number. You end up repeating it, you know, 15, 20 times in a lot of cases. So all that is to say people don't. People never liked that. They do not like it. If you had any air bubbles that got stuck in your bathing suit, it would throw off the whole measurement. Air bubbles stuck in your hair. It was a pain in the butt. So thank God that we've kind of moved toward DEXA as being this, you know, major measurement tool. But yeah, having said that, even though it gives really good data and it is very easy to do and we can look past the small radiation dose because it's really negligible in the long run. We still had to deal with some of these nuances of exactly how it's measuring and what it's measuring.

[A]

Well said. Yeah, it's interesting. I've been to multiple labs that actually do have BIA or BIS devices. Research grade. So substantially better than the top, even commercial grade in body. And they don't use them in isolation. They typically use them as part of getting a 4C or 5C or if you're Grant Tinsley and you want to show off a 6C model. Right. And that's because they measure different things. And the same variation in water can produce different directional errors in different devices, which I find fascinating. So, for example, BIS and bia bioelectrical impedance. If you're using high grade stuff, it's typically multiple frequencies. So you can differentiate between different body compartments of water, but it's assuming a conduction speed based upon the different tissue. The two compartment model it's measuring, or I guess three, and it is basically impacted by dehydration, impacting the speed of the electrical signals, right? And then displacement, which is what you're measuring, whether you're getting dunked in the water and simulated drowning or just getting to sit in the BOD pod. How much you displace air, how much you displace water is a comparison of weight and density and area. So if you are reducing the water content, you are decreasing your weight, but potentially having not the same impact on the space you take up. And it can make you seem like higher density. Right? So you can get different directions of either increasing or decreasing body fat due to either a decrease or increase in lean body mass or the fat compartment. Based upon those assumptions and when used together, this is where you can get an estimation of your body water, your bone, your lean soft tissue mass, the basically everything that's not bone, adipose tissue, and you can even start breaking it down into glycogen, minerals and all the fun stuff if you want to get fancy. So one of the things that always confused me until I actually dug under the hood to understand what DEXA did, was why it measures fat mass, not adipose tissue, but it actually measures lean mass, including water. And I didn't understand why. And that's actually really due to the chemical structure of water relative to glycogen and lean mass. And it just can't differentiate those things. So that is also why when you look at the energetic value of lean tissue in a dexa, it is way, way lower. Because if you take muscle, it's about depending upon the study you're looking at and the person and the state, on average, maybe 70% water, just like on average we talked about maybe 85, 87, 90% of adipose tissue is not water. So we're looking at a pretty large difference. And if you were to go, well, hold on, I don't care about that, I want to know the actual kilogram change in contractile tissue and the actual kilogram change in lipid. Now you'd be looking at something much closer to how we count our macros. You know, 4kcals per gram versus 9kcal per gram of fat. And that's because we're actually thinking about only the metabolizable energy, not the tissue itself. When we're counting macros, and unless we can actually only measure the metabolizable energy in the tissue, we're not going to get that. So when we look at the lean mass values, again, there's different ones. But we'll use Kevin Hall's paper, 1800 calories ish. That is important because that data by Kevin hall was based upon and is in the era of and is used for informing DEXA based studies that assess body composition change while doing other things to assess energy expenditure, whether that's doubly labeled water or being in a metabolic ward or using, you know, basically a bunch of measures to try to get some estimation of that and looking at their relationship over time. So that means then that's why body recomposition is something that is you have to define the energetic value of these tissues and what you're looking at. And I would think that actually your experiences in the real world might not perfectly mirror what you're seeing in DEXA because of those different ways of assessing what you're actually measuring versus what you might see. And the seed I planted earlier, Trex and I found this interesting and we had to kind of revisit some of this data when we were talking about it is that maybe a constant hydration value for adipose tissue being assumed is not appropriate. So why don't you talk to me about that a little bit?

[B]

Well, yeah, I don't have a huge speech to give on this, but one of the things we were talking about is, well, if we, we were kind of talking through, if somebody's losing lipid content from their adipocytes, they're not losing the cell wall, right? They're not losing the organelles within it. But then the question was, well, what happens to the water? And a kind of natural assumption would be it stays the same. But there's actually some research to suggest it might actually increase a little bit, especially in the short term. And you've heard, you know, the lore Helms and the kind of, you know, people talk about squishy fat and the whoosh effect, you know, these types of things. Kind of informally talking about this idea of as you're acutely losing fat, especially if it's happening at a pretty rapid clip, maybe we see a little bit of extra water enter the adipocyte, at least in the short term, and then maybe it, you know, maybe that normalizes or stabilizes a little bit. Some of that extra water that came in leaves giving us that kind of whoosh. Effect. But there have been some studies where they look at the relative water content of adipocytes in leaner people versus people with obesity or people who used to have much more body fat and have since lost it. And it does look like that water content may go up just a tiny bit in those scenarios, which is fascinating. I'm not sure how actionable it is. I still don't have a good grip on how much it would really tangibly affect whole level estimates of body composition. But it is just kind of an interesting thing we were talking through as you start to think through, and that's really what it comes down to with these methods discussions is number one, you have to boil down what exactly is this method doing? Number two, what exact physiology is actually occurring that we're trying to capture. And number three, where are the gaps between them or where are the weird anomalies or unexpected behaviors when you put how the method actually does its work versus what physiology is actually occurring?

[A]

No, well said. And I don't know that this is necessarily representative of all people leaner versus higher in body weight, but one of the studies you referred me to was long term differences in people who'd lost a lot of weight. Looking at the water content of abdominal adipose tissue, and I want to say it was closer to 70% being lipids versus the like 85, 90 kind of range that is assumed. And of course it's still predominantly lipid, but that's a notable change, right?

[B]

Yeah. And it's interesting because then you have to also consider, well, if the lipid is going down, then by default the percentage water is going up. But it's interesting that they're not going down in the same proportion relative to each other.

[A]

Yeah, correct.

[B]

So I don't want to give the impression that, I don't want to give the impression that if you lose fat, your fat cells are just going to stay exactly the same size and fill up with water. But what we do see, you know, this acute kind of transient. And do you want to give a little background on like what people are talking about with squishy fat and the whoosh effect? Those are things you see especially back in like the fitness forum days, people would talk about that. It became kind of accepted among people who are interested in, you know, this kind of body composition, physiology. Do you want to give a, just like a very brief background on that?

[A]

Yeah, yeah, yeah. I think there was some studies that were done on relatively rapid weight loss and looking at what is going on in terms of the fat cell and it seems to be that there, in, at least in this one study, a delayed loss in the, a delayed reduction in the overall size of it and a proportional change where as the lipid content was going down, the water content was going up. And then hypothetically, and this is kind of more like the area that you love now, evolutionary biology thinking, well, listen, like short term losses of fat and you know, then getting access to food kind of characterized by what we see and perhaps having a massive change in a cell size would not be ideal for our long term storage of energy. I think there's even some speculation that if a fat cell was to change in size that rapidly, it could actually, the tail could die because of structural instability. So that's not what you want.

[B]

Like a terrible metaphor would be like if you ran a business, let's say you're Omar and you're selling a bunch of shirts out of the warehouse, right? You wouldn't really want to sell your warehouse space every time you had a small drawdown in inventory. Because it's going to be a pain in the ass to say, great, now that we have a new, now that we're restocking, I guess we have to find new space and start a new lease at a new warehouse. Like you'd want to. If you expect that there's going to be some more inventory coming in, in this case more lipid to be stored, you're like, why don't we just put a little placeholder there and save ourselves the trouble of having to actually go through literal reconfiguration of the cell size, contracting it and then re expanding it and having to actually build it back out.

[A]

That's actually a really good analogy because if you think about it, if you sit on that, that rent that you're doing, okay, man, I don't have enough shirts, but I probably will in the future. That's kind of the, the survival. It's not thinking, but that's the, the thing that seemed to survive best in our species, right? That's actually really similar to, well, what would happen if you just went, well, I'm just going to continually change warehouses based upon my inventory size. You're breaking leases and incurring penalties and you're paying a whole lot of down payments. And in the body, the physiological parallel would be you might be having some cell death. And then the good news is, yes, your body can create new fat cells. That's not actually good news. None of us like that in fitness, but it's great news for survival. But there's A cost to creating this new tissue. And cost in physiological terms and in evolutionary biology terms. Cost means you need to eat more, which means you need to move more, you need to get more things, which means you probably can't support a baby, or you probably don't have the energy to go out and hunt or forage or mount an immune defense, which means more people with that type of physiology or at a time point when they were maybe people or some other type of ape that walked around on two legs prior to our current version billion point zero or whatever it is, that probably wasn't the best strategy. So I imagine it's not a homogenous thing between people, the degree to which water is maintained and how much squishy fat someone has. And anecdotally, as a coach, you do see some very different things when you look at kind of regional fat loss, visual changes and patterns before you see a dip in body weight. But I think it's just really interesting to think about that, that this was something that was a, I would say, hypothetical hypothesis to why we sometimes see something, sometimes over overnight changes, not only just in the scale after an apparent deficit that should have produced more weight loss more steadily, but also given the visual change where your body finally decides to go. I'm going to let go of this water now. To be honest, I have always questioned in my mind the idea that there is going to be this large loss of water because it doesn't make any more sense than why the cell wouldn't want a large loss of fat struct. And I would think it would be this steady, incremental, slow retransition to whatever body water content is going to have at your new body fat level.

[B]

Yeah, no, I agree. But just to bring the terms home, squishy fat is kind of the colloquial term for these adipocytes that have lost some lipid and are transiently storing maybe a little bit of extra water, and therefore their physical characteristics have changed and they are squishy. The idea of the whoosh effect is this kind of precipitous drop where these squishy fat cells have decided, okay, I guess the extra lipid just isn't going to be around, so we'll go ahead and drop that water and kind of adjust to our new reality. I agree. I do wonder to some extent if people are conflating those initial, those rapid drops. Of course, you know, there's so much to throw you for a loop when you're hyper monitoring your body during a weight loss phase with Shifts in sodium, shifts in carbohydrate. But the biggest, like I had a thing, I, I've talked about it before on a million podcasts, but there's this one point where I was just training my ass off like crazy, very stressed, way overdoing it, and I just took a de load and just didn't go to the gym for four days. And, and just boom. Because the math didn't work. I was like, I know I'm in a deficit. I know that I should be losing fat at this particular rate, but my scale is not budging for weeks. And then all of a sudden every bit of weight that I thought I should have been losing, it was just gone. Right? Because we do know in that kind of hyper stressed out state between psychogenic stress and physiological stress of pushing your training too hard, especially with a lot of interval training, you can ramp up cortisol like crazy, which can lead to some transient kind of temporary fluid. Fluid. What's the term? I'm thinking retention. Yeah, retention. So I do wonder to some, to some extent if people who are in those rapid fat loss phases are also in some of those, like kind of a lot of cortisol volatility. And so what they're seeing as the whoosh effect may be something a little bit more along those lines. But nonetheless, those are the terms that kind of help us colloquially discuss this idea of adipocytes having some flexibility in terms of the water content. And yeah, it may ramp up acutely, it may drop back down, and perhaps it actually stays, in a relative terms, elevated a little bit long after that weight loss has kind of stabilized. I don't claim to be an expert on adipocyte physiology, which is good because I don't know a ton about it, but these are the kind of high level concepts that, that get discussed in the literature, 100%.

[A]

And yeah, I think where you do see much easier to measure and much more conceptually intuitive, I guess you could say water changes is actually in lean and muscle tissue. You know, we see big changes in swelling, edema. And if you just think about what's hydrophobic, what's hydrophilic, which, which types of, you know, molecules. And then if you think about something can be in the muscle cell, but not necessarily, or sorry, it could be in the whole muscle, but not necessarily in the muscle cell and where that, that fluid retention is and how quickly it can come and go, 100%. And there are studies on short term dehydration having very large effects on muscle size because it's not 15% fat or water, it's 70% water. So nonetheless that that is where a large amount of our body water is stored either in the intra or inter intra or inter muscle cell space but but within the whole muscle and of course in the vascular system. But anyway Trex I think we covered a lot. I think the key take homes here are that 1D isn't 2D isn't 3D and there are different sources of error. But we should also between ultrasound and MRI as well as these different dimensions. But they are, they do have face validity. I would like to see my muscles get thicker. I would also like them to see I have more area. I would also like them to see have more volume and I'll take all three and I suspect most of the time when one is changing, the other ones are too. Unless you're seeing really unique regional changes in hypertrophy that really just haven't really panned out when we look at whole muscle volume on MRI. And doesn't mean that any of those three are any less valid than the others. But there may be differences in reliability which may influence the type of change you need to see before you can be confident in that change. And I'm excited for future work but I think the official mass opinion is that this paper by Balshawk demonstrates how variability and signal versus noise can lead to some measurements that should agree, not agreeing. But we need a better assessment of this to try to support maybe the initial claims they made which we would probably feel are a little too strong. And then the second thing we would say is hey, kind of cool if you understand what's going on at least a high level under the hood on DEXA because it's bouncing X rays off you, the things that they actually encounter are going to dictate what compartments you can actually measure. And since water and lean tissue, be it glycogen or contractile proteins, have pretty similar chemistry as far as ADEXA is concerned, can't differentiate. So it's not measuring adipose tissue, it's measuring the actual lipids. So fat mass. But it is measuring kind of the composite of the water content, glycogen content and protein content. And there's some, some error there because they don't all have identical energy values. In fact, water, last time I checked, has no energy value. But nonetheless that's why we use these roughly 1800 and roughly 9400 values when we're trying to talk about back calculating someone's energy status based upon body composition change from dexa yeah.

[B]

And if I may add one more practical note, a place where this comes up a lot, just to tie a bow on our DEXA discussion is people have talked about all these papers about GLP1 agonist drugs indicating that there's this really precipitous muscle loss based on dexa fat free mass. In a previous MASS article, I cited two different reviews that have kind of really gone in depth on this question, and they've pointed out that when you look at MRI measures of muscle volume, you tend to find changes in muscle volume with GLP1 drugs that are basically what we would expect relative to the magnitude of weight loss. And then when you actually look in the muscle at what some people will call muscle quality, what they're finding is an elevator. Even though the volume of muscle is going down, the quality of muscle is going up. Because when we start to add a lot of extra body fat, there's a few places where we store what we might call ectopic fat. So instead of just putting it in that subcutaneous layer between muscle and skin, we'll start storing more fat within the muscle tissue itself, within our organs, in our visceral area, around the organs. And, you know, for a variety of methodological reasons, DEXA doesn't seem to be picking up those nuances with quite the same degree, especially, I would argue, in the abdomen and visceral region. Because at the end of the day, DEXA is a two dimensional technology trying to get through a big, thick mass of tissue with a lot of various tissues with differing densities. It's not just as simple as you look at an arm on a dexa. Oh, bone, muscle, fat, right. It's just right there in a line. You start looking from belly button to the back of the, you know, to a person back, you're going through a lot of different tissue densities. So all that is to say the reason that we would bother to make a podcast about these nuances is so that you understand, oh, there's a reason that we would see discrepant values between DEXA and mri. Now that we know how these technologies work, then you decide, which one am I more concerned about? And I would say when it comes to that particular topic, I put a little more weight in the MRI data than I do the DEXA data. For some of these reasons we talked about. You know, basically a dexa, what you're doing is you're turning a three dimensional human into a two dimensional image. Each pixel gets a value and every pixel that has bone gets counted as Bone, basically. So there's a lot of dimension reduction that's going on in dexa. Even though it's a great technology, we do lose some of the nuance versus the insane amount of information we get from a three dimensional MRI of a human being's whole body. It's pretty remarkable. So just kind of one more note to kind of, again, kind of emphasize the relevance of why we bother to kind of take a moment to understand how these really popular technologies actually work. And then one legal note, actually, I want to add, Helms, in your summary, you mentioned that 1D is not 2D is not 3D, which legally permits anyone listening, and possibly even me, the opportunity to create 1D muscle journey and 2D muscle journey. And so if anyone does that, I've officially come up with the concept and therefore I am an equity owner. So just drop me an email, we'll figure out which Ds we want to drop and we'll get rolling with the paperwork.

[A]

Well, I can tell you that if you only have one or two Ds, you're missing a critical D. The real money would be. And I don't know why I'm giving my future competitors this advantage, Ds that are greater than than 3. But I'll tell you this, my statement for the record did not state that 1D and 2D, 3D and 4D are different. And I'm not stating that now. Yeah, legally. So you can try to come at me with my very real Delaware lawyers if you want to go with a greater than 3D value. But there is substantial risk given the success we've had, maybe even suing large swaths of the world who have dared to even prospectively use similar shapes to what I used in my book. So if you want to actually, you want that smoke, you can have it.

[B]

Now that I think about it, the context of your statement was the D's were dimensions. So if you're acknowledging that one dimension and two dimension are not the same as three dimensions, that also opens up the muscle and strength. Triangles

[A]

A. I would agree that that is a potential interpretation, but I don't think I'm worried about it because triangles simply don't have the same connotation of going up that a pyramid does. Right.

[B]

But they are a great percussive instrument which I was classically trained on, by the way. So lot going for the triangle, but. All right, Helms, I think we've done enough legal deliberation for the day. Anything you want to tell the good people before we sign off? For this episode.

[A]

No, I would just say do not engage in any triangle schemes that Dr. Drexler tries to get you to engage in. And I want to thank the listeners for stomaching this banter at the end, which is typically reserved for the start and be based on the quality of it this time probably is best relegated to the end.

[B]

Probably so. All right folks, appreciate you listening as always. Thanks so much for being a member of the Iron Cult. Thanks for supporting the Mass Research Review if you happen to do so. And if you don't, there's always time. So you can start today. Mass research review.com everyone. Take care. Have a fantastic week and we will be back in seven days with yet another episode.