A semiautomatic CT-based ensemble segmentation of lung tumors: Comparison with oncologists’ delineations and with the surgical specimen

Jemal, 2010, Cancer statistics, CA Cancer J Clin, 60, 277, 10.3322/caac.20073 Auperin, 2010, Meta-analysis of concomitant versus sequential radiochemotherapy in locally advanced non-small-cell lung cancer, J Clin Oncol, 28, 2181, 10.1200/JCO.2009.26.2543 Jett, 2007, Treatment of non-small cell lung cancer, stage IIIB: ACCP evidence-based clinical practice guidelines (2nd edition), Chest, 132, 266S, 10.1378/chest.07-1380 Bradley, 2012, A phase II comparative study of gross tumor volume definition with or without PET/CT fusion in dosimetric planning for non-small-cell lung cancer (NSCLC): primary analysis of Radiation Therapy Oncology Group (RTOG) 0515, Int J Radiat Oncol Biol Phys, 82, e431, 10.1016/j.ijrobp.2010.09.033 Giraud, 2002, Conformal radiotherapy for lung cancer: different delineation of the gross tumor volume (GTV) by radiologists and radiation oncologists, Radiother Oncol, 62, 27, 10.1016/S0167-8140(01)00444-3 Grabarz, 2011, Quantifying interobserver variation in target definition in palliative radiotherapy, Int J Radiat Oncol Biol Phys, 80, 1498, 10.1016/j.ijrobp.2010.04.014 Greco, 2007, Current status of PET/CT for tumour volume definition in radiotherapy treatment planning for non-small cell lung cancer (NSCLC), Lung Cancer, 57, 125, 10.1016/j.lungcan.2007.03.020 Steenbakkers, 2005, Observer variation in target volume delineation of lung cancer related to radiation oncologist-computer interaction: a ‘Big Brother’ evaluation, Radiother Oncol, 77, 182, 10.1016/j.radonc.2005.09.017 Van de Steene, 2002, Definition of gross tumor volume in lung cancer: inter-observer variability, Radiother Oncol, 62, 37, 10.1016/S0167-8140(01)00453-4 Vorwerk, 2009, The delineation of target volumes for radiotherapy of lung cancer patients, Radiother Oncol, 91, 455, 10.1016/j.radonc.2009.03.014 Senan, 1999, Evaluation of a target contouring protocol for 3D conformal radiotherapy in non-small cell lung cancer, Radiother Oncol, 53, 247, 10.1016/S0167-8140(99)00143-7 Bowden, 2002, Measurement of lung tumor volumes using three-dimensional computer planning software, Int J Radiat Oncol Biol Phys, 53, 566, 10.1016/S0360-3016(02)02783-9 Caldwell, 2001, Observer variation in contouring gross tumor volume in patients with poorly defined non-small-cell lung tumors on CT: the impact of 18FDG-hybrid PET fusion, Int J Radiat Oncol Biol Phys, 51, 923, 10.1016/S0360-3016(01)01722-9 Buijsen, 2012, FDG-PET-CT reduces the interobserver variability in rectal tumor delineation, Radiother Oncol, 102, 371, 10.1016/j.radonc.2011.12.016 Steenbakkers, 2006, Reduction of observer variation using matched CT-PET for lung cancer delineation: a three-dimensional analysis, Int J Radiat Oncol Biol Phys, 64, 435, 10.1016/j.ijrobp.2005.06.034 van Baardwijk, 2007, PET-CT-based auto-contouring in non-small-cell lung cancer correlates with pathology and reduces interobserver variability in the delineation of the primary tumor and involved nodal volumes, Int J Radiat Oncol Biol Phys, 68, 771, 10.1016/j.ijrobp.2006.12.067 Lee, 2010, Segmentation of positron emission tomography images: some recommendations for target delineation in radiation oncology, Radiother Oncol, 96, 302, 10.1016/j.radonc.2010.07.003 Nestle, 2005, Comparison of different methods for delineation of 18F-FDG PET-positive tissue for target volume definition in radiotherapy of patients with non-Small cell lung cancer, J Nucl Med, 46, 1342 Wu, 2009, PET CT thresholds for radiotherapy target definition in non-small-cell lung cancer: how close are we to the pathologic findings?, Int J Radiat Oncol Biol Phys, 77, 699, 10.1016/j.ijrobp.2009.05.028 Wanet, 2010, Gradient-based delineation of the primary GTV on FDG-PET in non-small cell lung cancer: a comparison with threshold-based approaches, CT and surgical specimens, Radiother Oncol, 98, 117, 10.1016/j.radonc.2010.10.006 van Loon, 2011, Therapeutic implications of molecular imaging with PET in the combined modality treatment of lung cancer, Cancer Treat Rev, 37, 331, 10.1016/j.ctrv.2011.01.005 Sonke, 2010, Adaptive radiotherapy for lung cancer, Semin Radiat Oncol, 20, 94, 10.1016/j.semradonc.2009.11.003 Bendtsen, 2011, X-ray computed tomography: semiautomated volumetric analysis of late-stage lung tumors as a basis for response assessments, Int J Biomed Imaging, 2011, 11, 10.1155/2011/361589 Athelogou, 2007, Definiens cognition network technology – a novel multimodal image analysis technique for automatic identification and quantification of biological image contents Gu, Y, Kumar, V, Hall, LO, et al. Automated delineation of lung tumors from CT images using a single click ensemble segmentation approach. Pattern Recognition 2012;In press. van Baardwijk, 2008, Individualized radical radiotherapy of non-small-cell lung cancer based on normal tissue dose constraints: a feasibility study, Int J Radiat Oncol Biol Phys, 71, 1394, 10.1016/j.ijrobp.2007.11.070 van Baardwijk, 2010, Mature results of an individualized radiation dose prescription study based on normal tissue constraints in stages I to III non-small-cell lung cancer, J Clin Oncol, 28, 1380, 10.1200/JCO.2009.24.7221 Richtlijn Niet-kleincellig longcarcinoom: stadiering en behandeling. Vereniging van Integrale Kankercentra 2004. Available from: http://www.cbo.nl/thema/Richtlijnen/Overzicht-richtlijnen/Oncologie/. Aerts, 2009, Identification of residual metabolic-active areas within individual NSCLC tumours using a pre-radiotherapy (18)fluorodeoxyglucose-PET-CT scan, Radiother Oncol, 91, 386, 10.1016/j.radonc.2009.03.006 Hanna, 2010, Geometrical analysis of radiotherapy target volume delineation: a systematic review of reported comparison methods, Clin Oncol (R Coll Radiol), 22, 515, 10.1016/j.clon.2010.05.006 Nestle, 2006, Practical integration of [18F]-FDG-PET and PET-CT in the planning of radiotherapy for non-small cell lung cancer (NSCLC): the technical basis, ICRU-target volumes, problems, perspectives, Radiother Oncol, 81, 209, 10.1016/j.radonc.2006.09.011 Daisne, 2003, Tri-dimensional automatic segmentation of PET volumes based on measured source-to-background ratios: influence of reconstruction algorithms, Radiother Oncol, 69, 247, 10.1016/S0167-8140(03)00270-6 Hatt, 2010, Accurate automatic delineation of heterogeneous functional volumes in positron emission tomography for oncology applications, Int J Radiat Oncol Biol Phys, 77, 301, 10.1016/j.ijrobp.2009.08.018 Dehmeshki, 2008, Segmentation of pulmonary nodules in thoracic CT scans: a region growing approach, IEEE Trans Med Imaging, 27, 467, 10.1109/TMI.2007.907555 Armato, 2001, Automated detection of lung nodules in CT scans: preliminary results, Med Phys, 28, 1552, 10.1118/1.1387272 McNitt-Gray, 1999, A pattern classification approach to characterizing solitary pulmonary nodules imaged on high resolution CT: preliminary results, Med Phys, 26, 880, 10.1118/1.598603 Nishino, 2011, CT tumor volume measurement in advanced non-small-cell lung cancer: performance characteristics of an emerging clinical tool, Acad Radiol, 18, 54, 10.1016/j.acra.2010.08.021 Yankelevitz, 2000, Small pulmonary nodules: volumetrically determined growth rates based on CT evaluation, Radiology, 217, 251, 10.1148/radiology.217.1.r00oc33251 Uchiyama, 2003, Quantitative computerized analysis of diffuse lung disease in high-resolution computed tomography, Med Phys, 30, 2440, 10.1118/1.1597431 Ye, 2010, Automatic graph cut segmentation of lesions in CT using mean shift superpixels, Int J Biomed Imaging, 983963 Kakar, 2009, Automatic segmentation and recognition of lungs and lesion from CT scans of thorax, Comput Med Imaging Graph, 33, 72, 10.1016/j.compmedimag.2008.10.009 Stroom, 2007, Feasibility of pathology-correlated lung imaging for accurate target definition of lung tumors, Int J Radiat Oncol Biol Phys, 69, 267, 10.1016/j.ijrobp.2007.04.065 Daisne, 2004, Tumor volume in pharyngolaryngeal squamous cell carcinoma: comparison at CT, MR imaging, and FDG PET and validation with surgical specimen, Radiology, 233, 93, 10.1148/radiol.2331030660 Strassmann, 2010, Atlas-based semiautomatic target volume definition (CTV) for head-and-neck tumors, Int J Radiat Oncol Biol Phys, 78, 1270, 10.1016/j.ijrobp.2010.01.029 Anders, 2012, Performance of an atlas-based autosegmentation software for delineation of target volumes for radiotherapy of breast and anorectal cancer, Radiother Oncol, 102, 68, 10.1016/j.radonc.2011.08.043 Isambert, 2008, Evaluation of an atlas-based automatic segmentation software for the delineation of brain organs at risk in a radiation therapy clinical context, Radiother Oncol, 87, 93, 10.1016/j.radonc.2007.11.030