AI-based chest X-ray prioritization in the lung cancer diagnostic pathway: the LungIMPACT randomized controlled trial
Summary
Prioritizing artificial intelligence (AI)-detected imaging findings may reduce the time to diagnosis of lung cancer. This prospective, multicentre, randomized controlled trial tested whether immediate AI prioritization of primary care-requested chest X-rays (CXR) influenced time to computed tomography (CT) and lung cancer diagnosis, the primary outcomes. Secondary outcomes included the number of urgent suspected lung cancer referrals, incidence and stage of lung cancer, times to urgent ref
Content
# AI-based chest X-ray prioritization in the lung cancer diagnostic pathway: the LungIMPACT randomized controlled trial
*Published: 2026 May*
Prioritizing artificial intelligence (AI)-detected imaging findings may reduce
the time to diagnosis of lung cancer. This prospective, multicentre, randomized
controlled trial tested whether immediate AI prioritization of primary
care-requested chest X-rays (CXR) influenced time to computed tomography (CT)
and lung cancer diagnosis, the primary outcomes. Secondary outcomes included the
number of urgent suspected lung cancer referrals, incidence and stage of lung
cancer, times to urgent referral and treatment, concordance between AI and
radiology reports, and algorithm accuracy. AI was available in both study arms,
with AI prioritization randomized by day. Of 97,731 participant CXRs, 4,405 were
excluded due to data compliance issues or failure of randomization, resulting in
93,326 CXRs analyzed (45,987 and 47,339 in the prioritization 'on' or 'off'
arms, respectively). A total of 13,347 CTs were identified, with 2,766 performed
within 14 days of CXR. Median (interquartile range) times to CT were 53 days
(17-145) and 53 days (19-141), with and without AI prioritization, corresponding
to a ratio of geometric means of 0.97 (95% confidence interval (CI) = 0.93-1.02;
P = 0.31). When restricted to CTs performed within 14 days of CXR, the median
time to CT was 8 days (5-11) in both groups. Lung cancer was diagnosed in 558
people (0.6% of CXRs). Median times to diagnosis were 44 days (26-90) and 46
days (24-105) respectively, with a ratio of geometric means of 0.98 (95%
CI = 0.83-1.16; P = 0.84). No significant differences were observed in time to
lung cancer referral (14 versus 15 days; P = 0.13), time to treatment (76 versus
72.5 days; P = 0.99) or stage at diagnosis (P = 0.34). Discordance between AI
and radiology reports occurred in 28,261 CXRs (30.3%) and expert radiology
review identified actionable findings in 6,750 cases (23.9%). AI prioritization
of CXR requested by UK primary care has no significant impact on the lung cancer
pathway. Therefore, CXR AI deployments should not include worklist
prioritization in this context. Future research should differentiate between
primary pathway changes and the direct impact of AI. ISRCTN registration:
78987039 .
DOI: 10.1038/s41591-026-04253-5