Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Velazquez ER

PROVIDER: S-EPMC3866632 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature

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Publications

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

Velazquez Emmanuel Rios ER Parmar Chintan C Jermoumi Mohammed M Mak Raymond H RH van Baardwijk Angela A Fennessy Fiona M FM Lewis John H JH De Ruysscher Dirk D Kikinis Ron R Lambin Philippe P Aerts Hugo J W L HJ

Scientific reports 20131218

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 ...[more]

PMID: 24346241

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Dataset Information

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

Publications

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

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