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Essay 05 · Writing · Muscle & Programmatics series

Muscle as a vital organ

Sarcopenia, imaging, and the case for measuring what we already see — in three parts

Axial CT at the third lumbar vertebra (L3): skeletal muscle, subcutaneous and visceral fat surrounding the vertebral body
A real CT scan slice through the belly at the L3 level — where muscle and fat are measured. Tap the gold points to see what each one is.

Click a labelled point on the scan ↑

Tap a tissue on the scan

From this one scan slice we can measure how much muscle there is, how good the muscle quality is, and how much fat is stored — usually from a scan the person already had for another reason.

Part I · Measure

The organ we forget to measure

the organ we forget to measure

For a century, radiology has treated skeletal muscle as scenery — the tissue the beam passes through on the way to the organ of interest. That framing is now scientifically and economically obsolete. Skeletal muscle is the largest metabolically active tissue in the body — roughly 40% of body mass — the principal site of insulin-mediated glucose disposal, an endocrine organ in its own right, and one of the most powerful population-level predictors of survival we can extract from imaging we have already acquired. Sarcopenia — its progressive loss — sits at the intersection of ageing, metabolic disease and preventive medicine. For a preventive-imaging practice, it is the clearest available example of value hiding in plain sight.

What sarcopenia actually is

The 2019 European consensus (EWGSOP2) redefined sarcopenia as a muscle disease — “muscle failure” — and made low muscle strength the primary criterion, with low muscle quantity or quality confirming the diagnosis and poor physical performance marking severity [S1]. The 2024 Global Leadership Initiative in Sarcopenia (GLIS) went further: sarcopenia is the concurrent combination of reduced muscle mass, reduced strength, and reduced muscle-specific strength — and, decisively, physical performance is an outcome of sarcopenia, not a defining component [S2]. Both agree it is a generalised muscle disease, increasingly prevalent with age, and at least partly reversible. Australia and New Zealand now have their own consensus guidance, which matters for any locally credible screening claim [S3].

The clinical stakes are not subtle. Low muscle mass — and, in particular, low muscle radiodensity on CT — independently predicts all-cause and one-year mortality, surgical complications, chemotherapy toxicity and loss of independence [S5][S6].

How radiology measures muscle

Click a modality to see what it measures — and where the honesty lives.

The weak point, stated plainly: there is no universal muscle-mass cut-point. Widely used L3 thresholds derive from specific (often oncology) cohorts; a 2025 AJR systematic review confirmed that broadly applicable healthy-population reference values are still lacking, varying by sex, BMI and ethnicity [S4]. DXA “lean mass” is not muscle; muscle quantity is not quality; neither is strength — the very distinction GLIS insists on. Much muscle–mortality data is also observational (reverse causation). Any screening product must be calibrated to a defensible local reference and must not overclaim one number as a diagnosis. Stating these caveats is what makes the case credible.

Read a single slice

Everything that matters on a body-composition CT lives on one axial image at the third lumbar vertebra (L3) — the scan at the top of this essay. Its labelled points are interactive: every tissue that drives the sarcopenia read — paraspinal and anterior abdominal wall muscle, visceral fat, subcutaneous fat and the vertebral (bone) landmark — can be measured off that single slice.

Muscle quality is not one thing

Radiology tends to collapse “muscle quality” into a single number — mean attenuation in Hounsfield units. That is a useful proxy and a poor description. At least four distinct processes lower that number, and they are not interchangeable.

Myosteatosis — fat deposited within and between muscle fibres — is the best characterised: measurable as low CT radiodensity, or directly as proton density fat fraction on Dixon MRI, and it tracks metabolic derangement independently of how much muscle is present. Fibrosis and fatty replacement — scarring — is what remains after injury, chronic overload or repeated tearing: tissue that is architecturally present but mechanically inert. CT cannot reliably separate scar from simple fat infiltration. MRI can begin to, because fat is bright on T1 while fibrous scar is low signal on every sequence — and the distinction matters, because one of them may respond to resistance training and the other will not. Chronic denervation passes through a subacute phase of oedema-like T2 hyperintensity and ends in fatty atrophy in a territorial, nerve-specific distribution; read as generic “poor-quality muscle”, it produces the wrong management, because the lesion is in the nerve and no protein or training programme repairs it. Oedema and inflammation is the fourth — and the only one of the four in which a low attenuation reading can improve within weeks.

This is where MRI has a genuine rather than marginal advantage: it is the only modality that separates these mechanisms in a living patient, and quantitative MRI already delivers muscle volume, intramuscular fat infiltration and ectopic fat from a single acquisition [S13]. The qualification, stated plainly: fat fraction is well validated, but imaging quantification of fibrosis specifically remains largely research-grade, and none of these four measures has an agreed clinical cut-point. Naming a mechanism is not the same as being able to act on it — or bill for it.

Continue to Part II — Interpret →

Part II · Interpret

What the number actually means

A skeletal muscle index is not a diagnosis. It is a number that has to be interpreted — against a reference population, against the metabolic state of the patient, and against the reason the scan was taken in the first place. This part is about what the number carries, and where its predictive power is strongest and weakest.

Why this is a cardiometabolic story, not a geriatric footnote

Skeletal muscle disposes of the majority of post-prandial glucose under insulin stimulation. Less functional muscle means less glucose sink — and worse glycaemic control. The relationship runs both ways: type 2 diabetes accelerates muscle loss through insulin resistance, inflammation, advanced glycation end-products, mitochondrial dysfunction and oxidative stress, while low muscle and intramuscular fat worsen insulin resistance [S8]. Sarcopenic obesity — low muscle wrapped in excess and infiltrating fat — is the most dangerous phenotype, because a normal BMI conceals it. Myosteatosis specifically tracks with metabolic derangement and predicts adverse cardiovascular outcomes, including after emergency PCI for myocardial infarction [S7].

The protective direction of that relationship deserves more weight than it usually receives. In NHANES III (13,644 adults), higher relative muscle mass was associated with better insulin sensitivity and less prediabetes across the entire range — not only at the frail extreme. After adjustment for age, sex, ethnicity and both generalised and central obesity, each 10% increase in skeletal muscle index was associated with an 11% relative reduction in HOMA-IR (95% CI 6–15%) and a 12% relative reduction in prediabetes prevalence (95% CI 1–21%), with stronger associations in non-diabetic participants [S14]. That is the case for treating muscle as a modifiable cardiometabolic organ rather than a geriatric endpoint: the gradient runs through the ordinary population, not just the visibly frail. The design limits are equally plain — cross-sectional, bioimpedance-derived muscle mass, and no demonstration that intervening on muscle mass alters diabetes incidence.

A hypothesis, stated as a hypothesis. If muscle is simultaneously the body’s largest glucose sink and its largest amino-acid reservoir, then a person carrying more of it has more metabolic buffer — somewhere to put a glucose load without sustained hyperglycaemia and compensatory hyperinsulinaemia, and a reserve to mobilise during infection, injury or catabolic illness, when amino acids are drawn on for immune function and acute-phase protein synthesis. It is biologically plausible that this buffer matters for inflammatory, infectious and neoplastic risk, and chronic hyperinsulinaemia with IGF-1 signalling is a coherent candidate pathway. But plausible is not proven. There is no direct human evidence that increasing muscle mass reduces cancer or infection incidence, and it should not be implied that there is. The hypothesis is here because it is the most interesting open question in the field — not because it is settled.
A second axial CT slice at L3 showing much more visceral fat and much less muscle
Compare with the scan at the top of this essay — here the dark visceral fat around the bowel is much greater and the muscle is noticeably thinner. This is the sarcopenic-obesity pattern, where a normal body weight can hide low muscle and high internal fat.

Click a labelled point on this scan too ↑

Tap a tissue on this scan

The same tissues as the first scan, but a very different balance — more fat stored inside the belly, and less muscle around the spine.

For cardiometabolic rehabilitation this reframes muscle from cosmetic to prognostic: it is the tissue rehabilitation is trying to build, the endocrine organ (via myokines) through which exercise exerts systemic effects, and a measurable marker of whether a programme is working. A rehab pathway that never quantifies muscle is flying without its most informative instrument — one that, on any patient who has had a CT, is already in the archive.

Where the prognostic signal is strongest — and what it does not prove

The most consistent muscle data in medicine comes from populations that are already unwell. In cancer, low skeletal muscle index predicts worse overall survival, worse recurrence-free survival and more postoperative complications with unusual consistency across tumour types: a meta-analysis of 26 studies in cholangiocarcinoma (4,398 patients) found sarcopenia associated with roughly a doubling of mortality hazard, with myosteatosis carrying an independent penalty [S15]. In breast cancer, pooled analysis found sarcopenic patients had a 68% higher mortality risk and more than double the rate of grade 3–5 chemotherapy toxicity [S16]. Toxicity is the mechanistically cleanest of these findings — cytotoxic dosing is calculated from body surface area, which knows nothing about how much lean tissue is available to distribute and metabolise the drug. The same review is a useful corrective in the other direction: low muscle density was not predictive of overall survival in that dataset. The quality signal is not uniformly strong everywhere the quantity signal is.

End-stage kidney disease shows the same pattern. A meta-analysis of 30 studies (6,162 dialysis patients) found sarcopenia in 28.5% and an associated mortality hazard of 1.82 (95% CI 1.38–2.39) [S17]. Dialysis also makes a second and more specifically radiological point: fluid shifts wreck the cheap tools. Bioimpedance and DXA both infer lean mass in ways that hydration status distorts — and hydration status is precisely what is unstable in this population. If body composition is to be measured in dialysis patients at all, it has to be measured by a method that counts tissue rather than infers it. That is an argument for cross-sectional imaging in exactly the group where the cheap alternatives fail, and it is an argument the imaging economics usually gets backwards.

The inference that does not follow. It is tempting to move from “patients with better body composition survive longer” to “optimising body composition is a preventive strategy”. That step is not yet earned. Almost all of this evidence is observational, and reverse causation is not a technicality here: occult malignancy, uraemia and chronic inflammation cause muscle loss, so wasting is partly a marker of the disease rather than an independent cause of dying from it. Exercise-oncology trials reliably improve strength, function and quality of life; they have not established a survival benefit. The defensible claim is that muscle is a powerful, cheap, already-acquired prognostic marker and a biologically plausible therapeutic target. The claim that building muscle prevents cancer death is a hypothesis under test, and should be described as one.

← Back to Part I    Continue to Part III — Act →

Part III · Act

Treatments & the evidence

The reassuring headline is that sarcopenia is modifiable, and the most effective interventions are not pharmaceutical. The uncomfortable one is that no drug is yet approved specifically to treat it, so any pharmacological claim must be framed carefully.

1 · Resistance exercise — the cornerstone

The single most consistently effective intervention across randomised trials and meta-analyses, improving muscle mass, strength and physical performance. Progressive resistance training is first-line, first-priority, and the benchmark every other treatment is measured against. Aerobic and combined training add cardiometabolic benefit, but resistance work drives the muscle adaptation.

2 · Protein and nutrition

Higher protein intake augments gains in lean mass and strength primarily when combined with resistance training; protein alone in healthy adults has modest effect [S9]. In sarcopenic older adults, whey-protein supplementation during resistance training improves muscle mass and strength versus training alone [S10]. Practical targets sit above the RDA — commonly ~1.0–1.2 g/kg/day, up to ~1.2–1.6 g/kg/day where intake and renal function allow — with attention to leucine and per-meal distribution. Vitamin D repletion is warranted where deficient, though it does not build muscle in replete individuals.

3 · Treat the metabolic driver

In type 2 diabetes and sarcopenic obesity, controlling glycaemia, inflammation and the underlying disease is part of muscle preservation, given the bidirectional loop [S8]. Weight loss must be quality weight loss — fat down, muscle protected.

4 · The GLP-1 caveat — the live debate

GLP-1 and dual GLP-1/GIP receptor agonists produce large weight loss, but a meaningful fraction is lean mass — reported from as little as ~15% up to 40–60% of total weight lost, with wide heterogeneity by drug, population and comorbidity [S11]. Two honest qualifications: some lean-mass loss is the expected physiological accompaniment of fat loss, and DXA “lean mass” is an imperfect stand-in for muscle function. The prudent position is to pair these agents with resistance exercise and adequate protein, and to be especially vigilant in older, frailer patients — precisely the population in which serial imaging-based body-composition tracking earns its keep.

5 · Emerging pharmacotherapy — promising surrogates, unproven function

The most watched agents target the activin/myostatin pathway. In the BELIEVE phase 2 trial (Nature Medicine, 2026; 507 adults, 72 weeks), bimagrumab — an anti-activin type II receptor antibody — plus semaglutide produced ~22% total weight loss of which ~92% was fat, while limiting lean-mass loss to ~2.9%, versus ~7.4% with semaglutide alone; bimagrumab alone actually increased lean mass (~2.5%) [S12].

Lead with the caveat: these are body-composition surrogate endpoints. There is not yet evidence that preserved lean mass translates into better strength, physical function, falls reduction or cardiovascular outcomes, and muscle spasms were a notable adverse effect in bimagrumab monotherapy arms. “Preserves muscle mass” is not the same claim as “keeps patients stronger and alive longer.”
Bottom line. Progressive resistance exercise plus adequate protein remains the evidence-based core, with vitamin D repletion where indicated and management of the underlying metabolic disease. Pharmacotherapy is advancing quickly on body-composition endpoints — the muscle-preserving-weight-loss story is real and commercially significant — but functional and hard-outcome evidence has not yet caught up, and the responsible position is to say so.

What a muscle-aware pathway would need

Measuring muscle is the easy part. A service that reports a skeletal muscle index without a route to act on it has added a number to a report and changed nothing. A defensible pathway needs at least four things: a local reference standard the metric is calibrated against, so the cut-point means something in this population rather than in a Canadian oncology cohort; a named clinician who receives the result and is resourced to act on it; a referral destination — exercise physiology, dietetics, endocrinology or renal medicine, depending on the driver; and a re-measurement interval, because a single value is a snapshot and the trajectory is the more useful signal. None of that is radiology’s job alone, which is precisely why it usually does not happen.

What this is worth — and what it costs

The opportunistic-imaging argument is close to unanswerable on cost: no additional scan, no additional dose, marginal cost approaching the compute to segment the slice — increasingly automated by AI. The honest counterweights are reimbursement (often no item number for a muscle metric), workflow integration, medico-legal handling of incidental findings, and false-positive risk from miscalibrated thresholds at scale. The opportunity is to be the credible party that measures muscle rigorously, reports it with humility, links it to a cardiometabolic action pathway, and does so within Australian accreditation and radiologist-governance standards. Measuring the organ we have spent a century looking straight through is one of the highest-yield, lowest-cost moves available in preventive imaging.

← Back to Part II

References

Literature identified via PubMed and web search, July 2026. DOIs and figures to be re-verified before publication.

Dr Lisa Sorger is a consultant radiologist, healthcare executive, medical administrator, company director and founder of myradiologist.ai. She writes on the economics and ethics of preventative imaging and diagnostic radiology.

Connect with me on LinkedIn · Instagram · drlisasorger.com · lisa@drlisasorger.com

All views expressed here are my own personal opinions and are not medical advice. General information only — not clinical or financial advice. myradiologist.ai · ABN 29 692 758 115 · ACN 692 758 115

From essay to practice. The measure-and-rebuild approach described here is now a clinical program — Onnafit, the muscle building & sarcopenia system at Ayana HealthSpan, Barker Road, Subiaco. Education only — assessment first, always.