@article {51, title = {A semiautomatic CT-based ensemble segmentation of lung tumors: comparison with oncologists{\textquoteright} delineations and with the surgical specimen.}, journal = {Radiother Oncol}, volume = {105}, year = {2012}, month = {2012 Nov}, pages = {167-73}, abstract = {

PURPOSE: To assess the clinical relevance of a semiautomatic CT-based ensemble segmentation method, by comparing it to pathology and to CT/PET manual delineations by five independent radiation oncologists in non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS: For 20 NSCLC patients (stages Ib-IIIb) the primary tumor was delineated manually on CT/PET scans by five independent radiation oncologists and segmented using a CT based semi-automatic tool. Tumor volume and overlap fractions between manual and semiautomatic-segmented volumes were compared. All measurements were correlated with the maximal diameter on macroscopic examination of the surgical specimen. Imaging data are available on www.cancerdata.org.

RESULTS: High overlap fractions were observed between the semi-automatically segmented volumes and the intersection (92.5{\textpm}9.0, mean{\textpm}SD) and union (94.2{\textpm}6.8) of the manual delineations. No statistically significant differences in tumor volume were observed between the semiautomatic segmentation (71.4{\textpm}83.2 cm(3), mean{\textpm}SD) and manual delineations (81.9{\textpm}94.1 cm(3); p=0.57). The maximal tumor diameter of the semiautomatic-segmented tumor correlated strongly with the macroscopic diameter of the primary tumor (r=0.96).

CONCLUSIONS: Semiautomatic segmentation of the primary tumor on CT demonstrated high agreement with CT/PET manual delineations and strongly correlated with the macroscopic diameter considered as the "gold standard". This method may be used routinely in clinical practice and could be employed as a starting point for treatment planning, target definition in multi-center clinical trials or for high throughput data mining research. This method is particularly suitable for peripherally located tumors.

}, keywords = {Algorithms, Humans, Lung Neoplasms, Multimodal Imaging, Positron-Emission Tomography, Tomography, X-Ray Computed}, issn = {1879-0887}, doi = {10.1016/j.radonc.2012.09.023}, author = {Rios Velazquez, Emmanuel and Aerts, Hugo J W L and Gu, Yuhua and Goldgof, Dmitry B and De Ruysscher, Dirk and Dekker, Andre and Korn, Ren{\'e} and Gillies, Robert J and Lambin, Philippe} }