Literature DB >> 20847172

Autocontouring and manual contouring: which is the better method for target delineation using 18F-FDG PET/CT in non-small cell lung cancer?

Kailiang Wu1, Yee C Ung, David Hwang, Ming S Tsao, Gail Darling, Donna E Maziak, Romeo Tirona, Kathy Mah, C Shun Wong.   

Abstract

UNLABELLED: Previously, we showed that a CT window and level setting of 1,600 and -300 Hounsfield units, respectively, and autocontouring using an (18)F-FDG PET 50% intensity level correlated best with pathologic results. The aim of this study was to compare this autocontouring with manual contouring, to determine which method is better.
METHODS: Seventeen patients with non-small cell lung cancer underwent (18)F-FDG PET/CT before surgery. The maximum diameter on pathologic examination was determined. Seven sets of gross tumor volumes (GTVs) were defined. The first set (GTV(CT)) was contoured manually using only CT information. The second set (GTV(Auto)) was autocontoured using a 50% intensity level for (18)F-FDG PET images. The third set (GTV(Manual)) was manually contoured using a visual method on PET images. The other 4 sets combined CT and (18)F-FDG PET images fused to one another to become composite volumes: GTV(CT+Auto), GTV(CT+Manual), GTV(CT-Auto), and GTV(CT-Manual). To quantitate the degree to which CT and (18)F-FDG PET defined the same region of interest, a matching index was calculated for each case. The maximum diameter of GTV was compared with the maximum diameter on pathologic examination.
RESULTS: The median GTV(CT), GTV(Auto), GTV(Manual), GTV(CT+Auto), GTV(CT+Manual), GTV(CT-Auto), and GTV(CT-Manual) were 6.96, 2.42, 4.37, 7.46, 10.17, 2.21, and 3.38 cm(3), respectively. The median matching indexes of GTV(CT) versus GTV(CT+Auto), GTV(Auto) versus GTV(CT+Auto), GTV(CT) versus GTV(CT+Manual), and GTV(Manual) versus GTV(CT+Manual) were 0.86, 0.65, 0.88, and 0.81, respectively. Compared with the maximum diameter on pathologic examination, the correlations of GTV(CT), GTV(Auto), GTV(Manual), GTV(CT+Auto), and GTV(CT+Manual) were 0.87, 0.83, 0.93, 0.86, and 0.94, respectively.
CONCLUSION: The matching index was higher for manual contouring than for autocontouring using a 50% intensity level on (18)F-FDG PET images. When using a 50% intensity level to contour the target of non-small cell lung cancer, one should also consider using manual contouring of (18)F-FDG PET to check for any missed disease.

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Year:  2010        PMID: 20847172     DOI: 10.2967/jnumed.110.077974

Source DB:  PubMed          Journal:  J Nucl Med        ISSN: 0161-5505            Impact factor:   10.057


  5 in total

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Authors:  Sue Chua; John Dickson; Ashley M Groves
Journal:  Eur J Nucl Med Mol Imaging       Date:  2011-09       Impact factor: 9.236

2.  Quantification of metabolic tumor activity and burden in patients with non-small-cell lung cancer: Is manual adjustment of semiautomatic gradient-based measurements necessary?

Authors:  Piotr Obara; Haiping Liu; Kristen Wroblewski; Chen-Peng Zhang; Peng Hou; Yulei Jiang; Ping Chen; Yonglin Pu
Journal:  Nucl Med Commun       Date:  2015-08       Impact factor: 1.690

3.  Impact of tumor size and tracer uptake heterogeneity in (18)F-FDG PET and CT non-small cell lung cancer tumor delineation.

Authors:  Mathieu Hatt; Catherine Cheze-le Rest; Angela van Baardwijk; Philippe Lambin; Olivier Pradier; Dimitris Visvikis
Journal:  J Nucl Med       Date:  2011-10-11       Impact factor: 10.057

4.  Potential advantages of FDG-PET radiomic feature map for target volume delineation in lung cancer radiotherapy.

Authors:  Zahra Falahatpour; Parham Geramifar; Seyed Rabie Mahdavi; Hamid Abdollahi; Yazdan Salimi; Alireza Nikoofar; Mohammad Reza Ay
Journal:  J Appl Clin Med Phys       Date:  2022-06-14       Impact factor: 2.243

5.  User Interaction in Semi-Automatic Segmentation of Organs at Risk: a Case Study in Radiotherapy.

Authors:  Anjana Ramkumar; Jose Dolz; Hortense A Kirisli; Sonja Adebahr; Tanja Schimek-Jasch; Ursula Nestle; Laurent Massoptier; Edit Varga; Pieter Jan Stappers; Wiro J Niessen; Yu Song
Journal:  J Digit Imaging       Date:  2016-04       Impact factor: 4.056

  5 in total

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