Literature DB >> 17398018

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.

Angela van Baardwijk1, Geert Bosmans, Liesbeth Boersma, Jeroen Buijsen, Stofferinus Wanders, Monique Hochstenbag, Robert-Jan van Suylen, André Dekker, Cary Dehing-Oberije, Ruud Houben, Søren M Bentzen, Marinus van Kroonenburgh, Philippe Lambin, Dirk De Ruysscher.   

Abstract

PURPOSE: To compare source-to-background ratio (SBR)-based PET-CT auto-delineation with pathology in non-small-cell lung cancer (NSCLC) and to investigate whether auto-delineation reduces the interobserver variability compared with manual PET-CT-based gross tumor volume (GTV) delineation. METHODS AND MATERIALS: Source-to-background ratio-based auto-delineation was compared with macroscopic tumor dimensions to assess its validity in 23 tumors. Thereafter, GTVs were delineated manually on 33 PET-CT scans by five observers for the primary tumor (GTV-1) and the involved lymph nodes (GTV-2). The delineation was repeated after 6 months with the auto-contour provided. This contour was edited by the observers. For comparison, the concordance index (CI) was calculated, defined as the ratio of intersection and the union of two volumes (A intersection B)/(A union or logical sum B).
RESULTS: The maximal tumor diameter of the SBR-based auto-contour correlated strongly with the macroscopic diameter of primary tumors (correlation coefficient = 0.90) and was shown to be accurate for involved lymph nodes (sensitivity 67%, specificity 95%). The median auto-contour-based target volumes were smaller than those defined by manual delineation for GTV-1 (31.8 and 34.6 cm(3), respectively; p = 0.001) and GTV-2 (16.3 and 21.8 cm(3), respectively; p = 0.02). The auto-contour-based method showed higher CIs than the manual method for GTV-1 (0.74 and 0.70 cm(3), respectively; p < 0.001) and GTV-2 (0.60 and 0.51 cm(3), respectively; p = 0.11).
CONCLUSION: Source-to-background ratio-based auto-delineation showed a good correlation with pathology, decreased the delineated volumes of the GTVs, and reduced the interobserver variability. Auto-contouring may further improve the quality of target delineation in NSCLC patients.

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Year:  2007        PMID: 17398018     DOI: 10.1016/j.ijrobp.2006.12.067

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  90 in total

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2.  Recommendations for the use of PET and PET-CT for radiotherapy planning in research projects.

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Review 4.  Imaging techniques for tumour delineation and heterogeneity quantification of lung cancer: overview of current possibilities.

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5.  Comparative methods for PET image segmentation in pharyngolaryngeal squamous cell carcinoma.

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6.  Should patient setup in lung cancer be based on the primary tumor? An analysis of tumor coverage and normal tissue dose using repeated positron emission tomography/computed tomography imaging.

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7.  Stability of FDG-PET Radiomics features: an integrated analysis of test-retest and inter-observer variability.

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Review 8.  PET in the management of locally advanced and metastatic NSCLC.

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9.  Automated Delineation of Lung Tumors from CT Images Using a Single Click Ensemble Segmentation Approach.

Authors:  Yuhua Gu; Virendra Kumar; Lawrence O Hall; Dmitry B Goldgof; Ching-Yen Li; René Korn; Claus Bendtsen; Emmanuel Rios Velazquez; Andre Dekker; Hugo Aerts; Philippe Lambin; Xiuli Li; Jie Tian; Robert A Gatenby; Robert J Gillies
Journal:  Pattern Recognit       Date:  2013-03-01       Impact factor: 7.740

10.  Evaluation of the Metabolic Response to Cyclopamine Therapy in Pancreatic Cancer Xenografts Using a Clinical PET-CT System.

Authors:  Hany Kayed; Patrick Meyer; Yong He; Bettina Kraenzlin; Christian Fink; Norbert Gretz; Stefan O Schoenberg; Maliha Sadick
Journal:  Transl Oncol       Date:  2012-10-01       Impact factor: 4.243

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