OnCo
ideasIdea

Every routine CT scan checked by AI for early cancer signs, with a tracked follow-up pathway

Hundreds of millions of CT scans are done each year for other reasons. Software could check each one for early lung, kidney, liver and pancreas changes, but only if a follow-up system exists.

Opportunistic screening algorithms exist for lung nodules, renal masses, liver lesions, and body composition. Propose a module running on all adult CTs with structured incidental-finding output, an automated tracking system to ensure follow-up, and a registry recording downstream procedures and cancers found so harm can be measured.

Hypothesis
Opportunistic AI on routine CT detects one to two additional stage I-II cancers per 1,000 scans, with follow-up completion of at least 90% when tracking is automated, versus under 50% today for incidental findings.
Rationale
Incidental findings are already common but get lost in free-text reports; the failure is tracking, not detection.
What would test it
Prospective pilot in two hospital systems (100,000 scans), measuring incremental cancers, stage, procedures per cancer, and lost-to-follow-up rate.
Maturity
early clinical
Who has to act
engineering
Cost to try
Medium ($1M to $50M)
Years to first evidence
3
Bottlenecks it attacks
  • Most lethal cancers are found late · Screening exists for only a few cancers. Pancreatic, ovarian, liver, oesophageal and most lung cancers are found when cure is unlikely.
  • Overdiagnosis and false alarms · Finding more cancer is not the same as saving lives. Screening also finds cancers that would never have hurt anyone, and treats them.

Connected

11top

Pages like this

not linked directly; found by shared links