17 March 2006 Comparative performance analysis for computer aided lung nodule detection and segmentation on ultra-low-dose vs. standard-dose CT
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Abstract
The performance of computer aided lung nodule detection (CAD) and computer aided nodule volumetry is compared between standard-dose (70-100 mAs) and ultra-low-dose CT images (5-10 mAs). A direct quantitative performance comparison was possible, since for each patient both an ultra-low-dose and a standard-dose CT scan were acquired within the same examination session. The data sets were recorded with a multi-slice CT scanner at the Charite university hospital Berlin with 1 mm slice thickness. Our computer aided nodule detection and segmentation algorithms were deployed on both ultra-low-dose and standard-dose CT data without any dose-specific fine-tuning or preprocessing. As a reference standard 292 nodules from 20 patients were visually identified, each nodule both in ultra-low-dose and standard-dose data sets. The CAD performance was analyzed by virtue of multiple FROC curves for different lower thresholds of the nodule diameter. For nodules with a volume-equivalent diameter equal or larger than 4 mm (149 nodules pairs), we observed a detection rate of 88% at a median false positive rate of 2 per patient in standard-dose images, and 86% detection rate in ultra-low-dose images, also at 2 FPs per patient. Including even smaller nodules equal or larger than 2 mm (272 nodules pairs), we observed a detection rate of 86% in standard-dose images, and 84% detection rate in ultra-low-dose images, both at a rate of 5 FPs per patient. Moreover, we observed a correlation of 94% between the volume-equivalent nodule diameter as automatically measured on ultra-low-dose versus on standard-dose images, indicating that ultra-low-dose CT is also feasible for growth-rate assessment in follow-up examinations. The comparable performance of lung nodule CAD in ultra-low-dose and standard-dose images is of particular interest with respect to lung cancer screening of asymptomatic patients.
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Rafael Wiemker, Rafael Wiemker, Patrik Rogalla, Patrik Rogalla, Roland Opfer, Roland Opfer, Ahmet Ekin, Ahmet Ekin, Valentina Romano, Valentina Romano, Thomas Bülow, Thomas Bülow, } "Comparative performance analysis for computer aided lung nodule detection and segmentation on ultra-low-dose vs. standard-dose CT", Proc. SPIE 6146, Medical Imaging 2006: Image Perception, Observer Performance, and Technology Assessment, 614605 (17 March 2006); doi: 10.1117/12.649790; https://doi.org/10.1117/12.649790
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