#313 - What Happens When We Start Imaging Healthy People? | Dr. Daniel Durand & Mike Haney
LEVELS – A Whole New LevelShow Notes
Most medical imaging happens after a symptom, injury, or abnormal test gives a clinician a reason to look. But what changes if imaging becomes a more routine measurement, creating a record of the body before something goes wrong? In this episode of Next Level, Mike Haney talks with Dr. Daniel Durand, chief medical officer at Prenuvo, about whole-body MRI as a test case for a broader shift from episodic medicine toward longitudinal health data. Whole-body MRI is controversial, and Durand is clearly an advocate. The conversation takes the skepticism seriously, then asks a larger question: as measurement gets cheaper, more frequent, and increasingly visible to patients themselves, how should medicine decide what is worth knowing?
Free course: Improve your metabolic health Get our free email course on how glucose, nutrition, exercise, sleep, and measurement can help you build habits that support better energy and long-term health: https://levels.link/wnl
What We Cover: How X-rays, CT scans, ultrasound, and MRI differ, and why radiation matters when you start thinking about repeated imaging What whole-body MRI sees well, and where CT, colonoscopy, or blood-based approaches may still be better The concerns around incidental findings, overdiagnosis, anxiety, and unnecessary follow-up, and Durand’s response to them What the current cancer-detection evidence for whole-body MRI does, and does not, establish Why having prior scans could help distinguish a stable abnormality from something genuinely new How faster scans and AI interpretation could eventually connect imaging with genomic, proteomic, and other health data
🎙️ About the Guest: Dr. Daniel Durand is chief medical officer at Prenuvo and president of the Prenuvo Medical Group. He trained at Johns Hopkins, is board-certified in adult and pediatric radiology, and previously served as chief clinical officer and chief innovation officer at LifeBridge Health.
📍What Dr. Daniel Durand & Mike Haney discussed: 03:32 - Why imaging belongs in a series about continuous measurement 15:32 - Imaging 101: X-rays, CT, ultrasound, and MRI 28:57 - How AI is shortening MRI scan times 38:52 - Screening versus surveillance 40:26 - Which cancers whole-body MRI can miss 46:39 - The case against scanning healthy people 52:40 - What the cancer-detection data actually shows 54:39 - "We're all going to get a body scan" 1:03:31 - What would make routine imaging more useful? 1:11:49 - Building a baseline of the healthy body 1:17:43 - When AI can see more than a radiologist 1:21:28 - Is it better to know, even when you can't treat it?
🔗 Helpful Links: Dr. Daniel Durand, Prenuvo: Prenuvo medical leadership Meta-analysis behind the ~9,000 participants and ~1.6% detection figures. It notes limits, including incidental findings (European Radiology, 2026): PubMed Prenuvo-associated study of 1,011 people, 2.2% confirmed cancer detection (Cancer Research/AACR, 2025): AACR abstract Incidental findings in whole-body MRI and their psychosocial effects (European Journal of Radiology, 2021): PubMed Prenuvo's research overview, including Polaris data (company-reported): Prenuvo clinical research
Watch the conversation: https://youtu.be/rFZVbzUPSaA Find us on YouTube: https://youtube.com/levelshealth?sub_confirmation=1
📲 Connect: Connect with Dr. Daniel Durand at LinkedIn
👋 Who we are: Levels helps you understand your metabolic health with personalized data, expert guidance, and tools that connect your daily choices to measurable changes in your body. Our goal is to help you make better decisions about food, exercise, sleep, and long-term health.
Look for new shows every month on A Whole New Level, where we have in-depth conversations with thought leaders about metabolic health.
More from LEVELS – A Whole New Level
Heart disease is the leading cause of death, but it’s also one of the most preventable. Decades of research have established a strong causal role for LDL and other ApoB-containing particles in atherosclerosis, and we now have multiple proven ways to lower them. The harder question is how to turn that evidence into a decision for an individual person. Mike Haney talks with Johns Hopkins cardiologist Dr. Seth Martin, a co-author of the new 2026 dyslipidemia guidelines, about what the latest evidence says we should actually measure and act on. The throughline is pragmatic: lower exposure to atherogenic particles earlier and for longer, use additional tests when they can change a decision, and distinguish interesting new measurements from ones that have actually been shown to improve outcomes.
Most of NextLevel starts with a measurement problem: we can see more biology than ever, but we still have to figure out what to do with it. Bioelectronic medicine flips that sequence. We already know how to send electrical signals into the nervous system to change biology, including an FDA-approved vagus nerve treatment for rheumatoid arthritis, even though we still can’t map or read most of the individual nerve fibers carrying those signals.
Most health decisions happen before the science is settled. A study points one way, another points somewhere else, experts disagree about what matters, and even strong population-level evidence may not tell you what will happen to you.
Alcohol has spent the last 40 years bouncing between two health narratives: a little is good for your heart, or any amount is dangerous. The science doesn’t really support either slogan. Dr. Tim Naimi has spent decades studying the health effects of alcohol and, just as importantly, why the research is so difficult to interpret. His read of the evidence is less dramatic but more useful: there’s no good reason to start drinking for your health, very low intake may carry little measurable added risk, and risk rises as consumption does. Understanding why earlier studies made moderate drinking look protective helps explain a lot of the whiplashing headlines.
From a single blood sample, new proteomic tools can now measure thousands of proteins at once. Dr. Tony Wyss-Coray’s lab is using that flood of data, together with machine learning, to build a much higher-resolution picture of what’s happening throughout the body and where someone’s health may be headed.