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Updated: Apr 16, 2026
Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
Published on: May 19, 2023
Computer-aided detection of artificial pulmonary nodules using an ex vivo lung phantom: influence of exposure
Mark O Wielpütz1, Jacek Wroblewski1, Mathieu Lederlin2
1Department of Diagnostic and Interventional Radiology, University Hospital of Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany; Translational Lung Research Center (TLRC) Heidelberg, Member of the German Center for Lung Research (DZL), Im Neuenheimer Feld 350, 69120 Heidelberg, Germany; Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Amalienstr. 5, 69126 Heidelberg, Germany; Department of Radiology, German Cancer Research Center (dkfz), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
Objectives:
To evaluate the influence of exposure parameters and raw-data based iterative reconstruction (IR) on the performance of computer-aided detection (CAD) of pulmonary nodules on chest multidetector computed tomography (MDCT).
Material And Methods:
Seven porcine lung explants were inflated in a dedicated ex vivo phantom shell and prepared with n=162 artificial nodules of a clinically relevant volume and maximum diameter (46-1063 μl, and 6.2-21.5 mm). n=118 nodules were solid and n=44 part-solid. MDCT was performed with different combinations of 120 and 80 kV with 120, 60, 30 and 12 mA*s, and reconstructed with both filtered back projection (FBP) and IR. Subsequently, 16 datasets per lung were subjected to dedicated CAD software. The rate of true positive, false negative and false positive CAD marks was measured for each reconstruction.
Results:
The rate of true positive findings ranged between 88.9-91.4% for FBP and 88.3-90.1% for IR (n.s.) with most exposure settings, but was significantly lower with the combination of 80 kV and 12 mA*s (80.9% and 81.5%, respectively, p<0.05). False positive findings ranged between 2.3-8.1 annotations per lung. For nodule volumes <200 μl the rate of true positives was significantly lower than for >300 μl (p<0.05). Similarly, it was significantly lower for diameters <12 mm compared to ≥12 mm (p<0.05). The rate of true positives for solid and part-solid nodules was similar.
Conclusions:
Nodule CAD on chest MDCT is robust over a wide range of exposure settings. Noise reduction by IR is not detrimental for CAD, and may be used to improve image quality in the setting of low-dose MDCT for lung cancer screening.
