Holding both sides of the ledger
A position paper on my work in preventative healthcare, and the standard I bring to it
I work at the point where three questions about preventative imaging collide: does it help the person, does it justify the cost, and who is accountable when a machine reads first. My career has run through the reading room, the executive suite and the boardroom, and the through-line has been the same discipline in each: count both sides of the ledger before you decide, and be willing to publish the strongest objection to your own position.
What I actually do
As a consultant radiologist I read the scans; as founder and managing director of myradiologist.ai I have built the operational and governance systems that let AI-enabled reading happen at scale without losing the accountability that makes it safe; and as a company director I sit on the side of the table that has to answer for the results. That combination is deliberate. It is easy to advocate for preventative imaging from the clinic and ignore the economics, and just as easy to critique it from the finance office and ignore what a confident diagnosis does for a patient. I try to hold both, because the decisions that matter in this field are made precisely where clinical judgement, health economics and corporate governance intersect, and very few people are standing in all three places at once.
My public work — the essays, the speaking, the Longevity Imaging Brief — is the argument made in the open. My commercial work is the argument put into practice, in a business that has to make the numbers add up while keeping a credentialled radiologist accountable for every read.
The thesis I keep returning to
Preventative imaging is neither a miracle nor a racket, and almost every public argument about it fails by choosing one of those caricatures. The honest position is that the ledger has two real columns, and both have to be counted.
On the strong side: opportunistic biomarkers extracted from scans a population is already having — coronary calcium, bone density, visceral and liver fat — are validated, near-zero marginal cost, and in combination rival the best clinical risk models we use [S1][S8][S10][S11][S12][S13]. Direct radiologist consultation measurably improves how patients understand and act on their results [S14][S15]. These are genuine goods, and I will make the case for them without apology.
On the cautionary side, held in the same hand: whole-body screening of well people is a low-prevalence, Bayesian problem rather than a harm. A meta-analysis of 9,024 asymptomatic people put the confirmed-cancer detection rate at just 1.57% (95% CI 1.22–2.03%)[S5], so the positive predictive value of a flagged finding is low and incidental or indeterminate findings are frequent, while long-term outcome and cost-effectiveness data are largely absent[S4]. The disciplined response is not to reject the modality but to govern it — structured reporting through ONCO-RADS, explicit guardrails for who is scanned, and the performance metrics and ROC curves we already hold breast screening to[S17]. An advocate who counts only the benefits and a critic who counts only the risks are making the same mistake from opposite ends. My work is to refuse both.
The standard I bring
Australia has already shown it can assess a preventative technology properly when it decides to. The Pharmaceutical Benefits Advisory Committee, in a 2011 decision, counted savings that landed in a different budget from the cost and insisted on a time horizon long enough for prevention to demonstrate its value [S19]; the Medical Services Advisory Committee has run bespoke Clinical Utility Card assessments for genetic tests since 2016 when the standard mould did not fit [S18]. The task in preventative imaging is not to invent a new economics. It is to be consistent with the rigorous one we already trust, and to insist that imaging be assessed by the same published standard the regulator applies elsewhere.
That is the standard I bring to a board, to a keynote, and to my own company: assess the technology on its own terms, count both columns of the ledger, name the counter-case out loud, and hold whoever reads first — human or machine — accountable for the result. It is not the most comfortable position to occupy, because it satisfies neither the pure advocate nor the pure sceptic. It is, I think, the only honest one.
References
- [S1] Gómez-Diaz D et al. Role of Coronary Artery Calcium Score CT in Risk Stratification of Asymptomatic Individuals. J Cardiovasc Dev Dis, 2025.
- [S4] Kwee RM et al. Whole-body MRI for preventive health screening: a systematic review. J Magn Reson Imaging, 2019 (12 studies, 5,373 asymptomatic subjects).
- [S5] Martins da Fonseca J et al. Whole-body MRI for opportunistic cancer detection in asymptomatic individuals: systematic review and meta-analysis. Eur Radiol, 2025 (10 studies, 9,024 participants).
- [S8] Aggarwal V et al. Opportunistic diagnosis of osteoporosis from routine CT scans. Ther Adv Musculoskelet Dis, 2021.
- [S10] Löffler M et al. Automatic opportunistic osteoporosis screening in routine CT versus DXA. Eur Radiol, 2021 (192 patients).
- [S11] Pickhardt PJ et al. Opportunistic Screening at Abdominal CT: Automated Body Composition Biomarkers for Added Cardiometabolic Value. RadioGraphics (RSNA), 2021.
- [S12] Modanwal G et al. Opportunistic hepatic steatosis assessment in low-dose CAC CT (LARI). eBioMedicine, 2025.
- [S13] Neeland IJ et al. Visceral and ectopic fat, atherosclerosis, and cardiometabolic disease: a position statement. Lancet Diabetes Endocrinol, 2019.
- [S14] Gutzeit A et al. Direct communication between radiologists and patients following imaging examinations. Eur Radiol, 2018 (202 patients).
- [S15] Mohan SK et al. Making Time for Patients: Positive Impact of Direct Patient Reporting. AJR, 2017 (27 patients).
- [S17] Hu et al. ONCO-RADS whole-body MRI cohort. Cancer Imaging, 2024 (2,064 participants). DOI 10.1186/s40644-024-00665-z.
- [S18] Norris S et al. Evaluating genetic and genomic tests for heritable conditions in Australia: lessons learnt from health technology assessments (MSAC Clinical Utility Card framework). J Community Genet, 2021. PMC9530105.
- [S19] Pharmaceutical Benefits Advisory Committee, 2011 decision (public record).
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