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Evaluation of AI Detection of Lung Nodules in Routine Chest CTs Compared to Lung Cancer Screening CTs  

February 18, 2026
2 min

ECR 2026: Poster Presentation 

Edgar Wakelin, Jeroen Mollink, Marios Koulakis, Maurits Engbersen, Bryan Haslam  

Abstract 

Purpose 

Despite lung cancer being a leading cause of mortality in Europe, eligibility requirements for screening are complex and region specific, limiting adoption rates. Artificial intelligence (AI) that identifies lung nodules in routine CT scans could help detect lung nodules that would otherwise be missed, but it is unclear if the same AI can be used for both screening and routine CTs given the different patient populations scanned. Here we characterize the performance of an AI algorithm to detect lung nodules within routine chest CT scans and compare to screening low dose CT (LDCT).  

Methods and Materials 

A total of 310 CT scans (143 LDCT (73 with nodules, 70 without) and 167 routine (92 with nodules, 75 without)) were included. Five thoracic radiologists segmented all nodules measuring 4–30mm, with majority voting (≥3/5 rads) used to define the ground-truth. AI performance was evaluated using: FROC analysis, reporting the average sensitivity across false-positive rates (from 0.125 to 8.0 false positives per scan (FPPS)); nodule sensitivity; and FPPS at the selected operating point.  

Results 

Across the 310 CT scans, 330 nodules were identified. The median nodule diameter was 6.0±4.71mm. All scans were successfully processed by the AI and produced similar detection performance between algorithms (FROC sensitivity: LDCTs: 0.732(95%CI:0.672-0.795), routine: 0.791(95%CI: 0.743-0.837)). At the device operating point the nodule sensitivity was also similar  (routine: 0.811(95%CI:0.754-0.867), LDCT: 0.793(95%CI:0.713-0.866)) and the FPPS was similar (routine: 0.894(95%CI:0.700-1.114), LDCTs: 1.013(95%CI:0.703-1.388)).  

Conclusion 

The AI model successfully identified lung nodules within routine chest CT scans with high sensitivity and low FPPS showing similar performance to screening LDCT exams. This performance highlights the potential for using the same AI to support early lung cancer detection for both screening LDCT and routine CT scans. 

Disclaimers: 

Disclaimers: Chest Suite comprises multiple applications including Veye Lung Nodules, Veye Reporting, DeepHealth Lung AI, DeepHealth Viewer and HealthCCSng. Veye Lung Nodules and Veye Reporting are manufactured by Aidence B.V. and distributed by DeepHealth, Inc. Neither Veye Lung Nodules nor Veye Reporting are FDA cleared for distribution in the US. DeepHealth Lung AI is FDA 510(k) pending. DeepHealth Viewer is manufactured by eRAD, Inc. and distributed by DeepHealth, Inc. in the US. HealthCCSng is manufactured by Nanox AI, Ltd. and distributed by DeepHealth, Inc. DeepHealth Lung AI is 510(k) pending. Any claims made about Chest Suite may reference claims associated with its individual components. Not all products and functionalities are commercially available in all countries

Any claims made about Chest Suite may reference claims associated with its individual components. 

Not all products and functionalities are commercially available in all countries. For clearance and commercial availability in your geography of functionalities listed and compatibility with other systems, please contact your account manager. 

Disclaimers: DeepHealth Prostate is manufactured as Quantib Prostate by Quantib BV for DeepHealth Inc., DeepHealth Lung is manufactured as Veye Lung Nodules by Aidence BV for DeepHealth Inc., DeepHeath Lung Tracker is manufactured as Veye Clinic by Aidence BV for DeepHealth Inc. and DeepHealth Brain is manufactured as Quantib ND by Quantib BV for DeepHealth Inc. Not all products and functionalities are commercially available in all countries. For clearance and commercial availability in your geography of functionalities listed and compatibility with other systems, please contact us