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Comment by jmhmd | Hacker News Reader

That's generally exactly what we do, which if we need to follow 2x or 10x incidental lesions in the population, leads to cost and availability problems. A lymphoma patient in remission needs follow up scans too, and I don't want them to have to wait 3 months because thousands of people are now following up their benign adrenal adenomas.

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If you could dramatically reduce cost and improve availability, would this still be a problem?

What's the limiting factor that prevents medical imaging from getting cheaper and more available?

Excluding the cost of X-ray/CT/MRI machines, operating them, getting people to them and through them, sometimes injecting contrast, and sometimes dealing with side effects of said contrast, radiologists, I think. You can scale all of the above except interpretation. AI is the natural next thought for how to scale that part, but it's been thought that this would happen any moment for over a decade.

The machines are expensive (millions range per MRI scanner), staffing the machines nearly around the clock with highly educated technologists, repair/maintenance of expensive specialized machinery, radiologists to read each scan (esp with a current shortage), means it’s very expensive to set up and run an imaging center. Opening and owning an imaging center used to be seen as fairly lucrative. and many radiology private practices did just that, however, the economics have changed over the years with dropping reimbursements, staffing shortages, etc and now often these imaging centers are seen as a liability rather than an asset.

I feel like the first part of this explanation reminds me of stories about mainframe computers in the 1950-70s - highly expensive special gear that needs special operators. Is there something about the physics of the process standing in the way?

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