Two Dutch hospitals implement AI for lung nodule detection on chest X-rays
Catharina Ziekenhuis (Eindhoven) and UMC Utrecht are integrating Qure.ai's chest X-ray solution, qXR, into daily radiology workflows. The focus: earlier, more consistent detection of small lung nodules and clearer referral decisions. The programs will also support opportunistic screening-flagging nodules even when the X-ray was ordered for other reasons.
Why this matters for care teams
Lung cancer remains the leading cause of cancer deaths, and finding it earlier improves outcomes. Subtle nodules on chest X-rays are easy to miss, especially in busy settings or when interpreted by readers with different subspecialties or experience levels. AI can serve as a constant second reader to reduce variability and prompt timely follow-up.
What the AI actually does
Qure.ai's qXR scans chest X-rays and flags findings consistent with lung nodules, including small, subtle lesions. It integrates into existing radiology systems so notifications appear within the standard reading workflow. Radiologists remain in control-AI is there to highlight and prioritize, not replace clinical judgment.
Voices from the clinics
Dr. Firdaus Mohamed Hoesein, Thoracic Radiologist and AI expert at UMC Utrecht: "By integrating this AI program into our workflow, we can significantly enhance our ability to detect subtle lung nodules, which is paramount for the early diagnosis of lung cancer." He noted the initiative supports UMC Utrecht's mission to catch lung cancer earlier and improve outcomes.
Dr. Joost Nederend, Radiologist at Catharina Ziekenhuis: "There is growing evidence that AI can improve detection rates without compromising-and potentially even improving-the positive predictive value for referrals. It can also be valuable in supporting consistent decision-making, especially when chest X-rays are interpreted by radiologists from different subspecialties, those in the earlier stages of their careers, or residents in training."
Hospital context
UMC Utrecht is one of the Netherlands' largest academic centers with a strong track record in lung cancer imaging research and AI. As a teaching institution, it is also preparing clinicians to work with AI-enabled diagnostics in practice. Catharina Ziekenhuis is a tertiary care hospital that treats lung cancer; many of its X-rays come from GP referrals for symptoms like persistent cough.
Clinical and operational value at a glance
- Earlier flagging of small nodules that can be overlooked on routine X-rays.
- More consistent referral decisions across readers and experience levels.
- Support for residents and non-thoracic radiologists without slowing throughput.
- Opportunistic screening on existing imaging-no extra appointment required.
Implementation notes for healthcare teams
- Define referral pathways and thresholds for AI-flagged nodules (e.g., CT follow-up criteria).
- Embed QA: periodic audits comparing AI flags with final reports and downstream outcomes.
- Calibrate to local prevalence and workflows; validate performance on your population.
- Train readers and residents on interpretation and documentation of AI findings.
- Ensure data protection, access controls, and GDPR compliance across PACS/RIS.
Momentum in the Netherlands
Erasmus Medical Centre in Rotterdam recently expanded its work with Qure.ai by launching a chest X-ray AI study, and now Catharina Ziekenhuis and UMC Utrecht are deploying AI in routine care. Qure.ai's oncology lead, Bhargava Reddy, emphasized that earlier detection is essential and that specialist healthcare AI can act as a tireless second set of eyes to spot small nodules that might otherwise be missed.
Context: lung cancer burden
Lung cancer remains the top cause of cancer mortality worldwide, including in the Netherlands. For background data and incidence trends, see the International Agency for Research on Cancer's resources here.
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