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

Source: https://onco.cc/ideas/idea-prev-opportunistic-ct-ai-registry/  
OnCo record `idea-prev-opportunistic-ct-ai-registry` (Idea). Data CC BY-NC 4.0, attribute "Data from OnCo (onco.cc)"; commercial use needs a licence.

## TL;DR

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.

## Summary

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.

## Fields

- Kind: Idea
- Last checked: 2026-09-08
- 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.
- Proposed test: 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
- Actor: engineering

## Sources

- Bottleneck evidence (The hardest cancers are found late): Crosby et al., Early detection of cancer (Science 2022): https://doi.org/10.1126/science.aay9040

## Connected records

- cancers: [Hepatocellular carcinoma](https://onco.cc/cancers/hcc/), [Non-small-cell lung cancer](https://onco.cc/cancers/nsclc/), [Pancreatic ductal adenocarcinoma](https://onco.cc/cancers/pancreatic/), [Renal cell carcinoma](https://onco.cc/cancers/rcc/)
- fronts: [Early Detection & Screening](https://onco.cc/fronts/early-detection/), [Imaging](https://onco.cc/fronts/imaging/)
- technologies: [AI in radiology](https://onco.cc/technologies/radiology-ai-screening/), [CT (computed tomography)](https://onco.cc/technologies/ct/)
- companies: [Aidoc](https://onco.cc/companies/aidoc/)
- bottlenecks: [Overdiagnosis and false alarms](https://onco.cc/bottlenecks/b-overdiagnosis/), [The hardest cancers are found late](https://onco.cc/bottlenecks/b-early-detection/)
- key papers: [Early detection of cancer](https://onco.cc/key-papers/paper-crosby-science/)
- roadmaps: [AI in oncology roadmap: pattern readers → foundation models → agents in the workflow](https://onco.cc/roadmaps/ai-oncology-roadmap/)

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