Volumetric CT-based segmentation of NSCLC using 3D-Slicer

• DOI: 10.1038/srep03529
• Publication Date: 2013-12-18T10:20:37Z
• Authors: Emmanuel Rios Vel...; Chintan Parmar; Mohammed Jermoumi; Raymond H. Mak; Angela van Baardwijk; Fiona M. Fennessy; John H. Lewis; Dirk De Ruysscher; Ron Kikinis; Philippe Lambin; Hugo J. W. L. Aerts
• Keywords: Lung Neoplasms; 610; Cone-Beam Computed Tomography; Article; Pattern Recognition, Automated; 3. Good health; 03 medical and health sciences; Imaging, Three-Dimensional; 0302 clinical medicine; Carcinoma, Non-Small-Cell Lung; Positron-Emission Tomography; 616; Biomarkers, Tumor; Humans; Diagnosis, Computer-Assisted; Lung; Algorithms; Software

Accurate volumetric assessment in non-small cell lung cancer (NSCLC) is critical for adequately informing treatments. In this study we assessed the clinical relevance of a semiautomatic computed tomography (CT)-based segmentation method using the competitive region-growing based algorithm, implemented in the free and public available 3D-Slicer software platform. We compared the 3D-Slicer segmented volumes by three independent observers, who segmented the primary tumour of 20 NSCLC patients twice, to manual slice-by-slice delineations of five physicians. Furthermore, we compared all tumour contours to the macroscopic diameter of the tumour in pathology, considered as the "gold standard". The 3D-Slicer segmented volumes demonstrated high agreement (overlap fractions > 0.90), lower volume variability (p = 0.0003) and smaller uncertainty areas (p = 0.0002), compared to manual slice-by-slice delineations. Furthermore, 3D-Slicer segmentations showed a strong correlation to pathology (r = 0.89, 95%CI, 0.81-0.94). Our results show that semiautomatic 3D-Slicer segmentations can be used for accurate contouring and are more stable than manual delineations. Therefore, 3D-Slicer can be employed as a starting point for treatment decisions or for high-throughput data mining research, such as Radiomics, where manual delineating often represent a time-consuming bottleneck.