Repeatability of AI-quantified incidental findings on lung cancer screening CT scans in the NELSON trial - Scorecard - MDSpire

Repeatability of AI-quantified incidental findings on lung cancer screening CT scans in the NELSON trial

  • By

  • Stijn Bunk

  • Thijs Bruins Slot

  • Edwin Bennink

  • Grigory Sidorenkov

  • Nils van der Velden

  • Niels Schurink

  • Félix Lades

  • Markus Sebald

  • Marjolein A. Heuvelmans

  • Hester A. Gietema

  • Joachim G. Aerts

  • Geertruida H. de Bock

  • Cornelia Schaefer-Prokop

  • Pim A. de Jong

  • Rozemarijn Vliegenthart

  • Firdaus A. A. Mohamed Hoesein

  • June 17, 2026

  • 0 min

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Clinical Scorecard: Consistency of AI-Detected Incidental Findings in Lung Cancer Screening CT Scans from the NELSON Study

At a Glance

CategoryDetail
Condition
Key Mechanisms
Target PopulationIndividuals aged 50–75 years with significant smoking history
Care Setting

Key Highlights

  • Study focuses on repeatability and agreement of AI measurements.

Guideline-Based Recommendations

Diagnosis

    Management

      Monitoring & Follow-up

        Risks

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        Patient & Prescribing Data

        AI can enhance the identification and management of incidental findings, potentially improving patient outcomes.

        Clinical Best Practices

        • Ensure accurate segmentation of AI-generated measurements
        • Use standardized imaging protocols for consistency
        • Validate AI measurements against manual assessments
        • Continuously validate AI tools in clinical settings.

        Related Resources & Content

        Original Source(s)

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