Segmentation of positron emission tomography images: some recommendations for target delineation in radiation oncology.

Positron emission tomography can be used in radiation oncology for the delineation of target volumes in the treatment planning stage. Numerous publications deal with this topic and the scientific community has investigated many methodologies, ranging from simple uptake thresholding to very elaborate probabilistic models. Nevertheless, no consensus seems to emerge. This paper reviews delineation techniques that are popular in the literature. Special attention is paid to threshold-based techniques and the caveats of this methodology are pointed out by formal analysis. Next, a simple model of positron emission tomography is suggested in order to shed some light on the difficulties of target delineation and how they might be eventually overcome. Validation aspects are considered as well. Finally, a few recommendations are gathered in the conclusion.

[1]  A. Alavi,et al.  PET and PET/CT: A Clinical Guide , 2010, Journal of Nuclear Medicine.

[2]  Liesbeth Boersma,et al.  Feasibility of pathology-correlated lung imaging for accurate target definition of lung tumors. , 2007, International journal of radiation oncology, biology, physics.

[3]  Daoqiang Zhang,et al.  Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation , 2007, Pattern Recognit..

[4]  D J Hawkes,et al.  Validation and clinical application of computer-combined computed tomography and positron emission tomography with 2-[18F]fluoro-2-deoxy-D-glucose head and neck images. , 1996, American journal of surgery.

[5]  D. Visvikis,et al.  Incorporation of wavelet-based denoising in iterative deconvolution for partial volume correction in whole-body PET imaging , 2009, European Journal of Nuclear Medicine and Molecular Imaging.

[6]  C. Ling,et al.  Effect of respiratory gating on quantifying PET images of lung cancer. , 2002, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[7]  Sasa Mutic,et al.  Concurrent multimodality image segmentation by active contours for radiotherapy treatment planning. , 2007, Medical physics.

[8]  Anne Bol,et al.  Tri-dimensional automatic segmentation of PET volumes based on measured source-to-background ratios: influence of reconstruction algorithms. , 2003, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[9]  A. Riegel,et al.  Variability of gross tumor volume delineation in head-and-neck cancer using CT and PET/CT fusion. , 2005, International journal of radiation oncology, biology, physics.

[10]  Mithat Gönen,et al.  Evaluation of Different Methods of 18F-FDG-PET Target Volume Delineation in the Radiotherapy of Head and Neck Cancer , 2008, American journal of clinical oncology.

[11]  Philippe Lambin,et al.  Tumor delineation based on time-activity curve differences assessed with dynamic fluorodeoxyglucose positron emission tomography-computed tomography in rectal cancer patients. , 2009, International journal of radiation oncology, biology, physics.

[12]  Andrew J Reader,et al.  The promise of new PET image reconstruction. , 2008, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

[13]  Don Robinson,et al.  Comparison of three image segmentation techniques for target volume delineation in positron emission tomography , 2007, Journal of applied clinical medical physics.

[14]  Agnese Cecconi,et al.  Combined 18F-FDG-PET/CT imaging in radiotherapy target delineation for head-and-neck cancer. , 2009, International journal of radiation oncology, biology, physics.

[15]  Tomio Inoue,et al.  Use of PET and PET/CT for radiation therapy planning: IAEA expert report 2006-2007. , 2009, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[16]  T. Brewin,et al.  Radiotherapy and oncology. , 1983, British medical journal.

[17]  Habib Zaidi,et al.  18F-fluorocholine PET-guided target volume delineation techniques for partial prostate re-irradiation in local recurrent prostate cancer. , 2009, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[18]  Maurizio Conti,et al.  First experimental results of time-of-flight reconstruction on an LSO PET scanner , 2007, Physics in medicine and biology.

[19]  L. R. Dice.  Measures of the Amount of Ecologic Association Between Species , 1945 .

[20]  Randall K Ten Haken,et al.  Using fluorodeoxyglucose positron emission tomography to assess tumor volume during radiotherapy for non-small-cell lung cancer and its potential impact on adaptive dose escalation and normal tissue sparing. , 2009, International journal of radiation oncology, biology, physics.

[21]  S. Nehmeh,et al.  An iterative technique to segment PET lesions using a Monte Carlo based mathematical model. , 2009, Medical physics.

[22]  Edgar Arce Santana,et al.  Hidden Markov Measure Field Models for Image Segmentation , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  P Vera,et al.  Development of a generic thresholding algorithm for the delineation of 18FDG-PET-positive tissue: application to the comparison of three thresholding models , 2009, Physics in medicine and biology.

[24]  Xavier Geets,et al.  Adaptive biological image-guided IMRT with anatomic and functional imaging in pharyngo-laryngeal tumors: impact on target volume delineation and dose distribution using helical tomotherapy. , 2007, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[25]  Nico Karssemeijer,et al.  A novel iterative method for lesion delineation and volumetric quantification with FDG PET , 2007, Nuclear medicine communications.

[26]  Simon Stute,et al.  LuCaS: Efficient Monte Carlo simulations of highly realistic PET tumor images , 2008, 2008 IEEE Nuclear Science Symposium Conference Record.

[27]  Anne Bol,et al.  A gradient-based method for segmenting FDG-PET images: methodology and validation , 2007, European Journal of Nuclear Medicine and Molecular Imaging.

[28]  David Schuster,et al.  Comparison of CT- and FDG-PET-defined gross tumor volume in intensity-modulated radiotherapy for head-and-neck cancer. , 2005, International journal of radiation oncology, biology, physics.

[29]  Frederik Maes,et al.  Biological image-guided radiotherapy in rectal cancer: challenges and pitfalls. , 2009, International journal of radiation oncology, biology, physics.

[30]  G Loi,et al.  Threshold segmentation for PET target volume delineation in radiation treatment planning: the role of target-to-background ratio and target size. , 2008, Medical physics.

[31]  C. Rübe,et al.  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. , 2005, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[32]  Ellen Yorke,et al.  18F-FDG PET/CT for Image-Guided and Intensity-Modulated Radiotherapy* , 2009, Journal of Nuclear Medicine.

[33]  Vladimir Y. Panin,et al.  Fully 3-D PET reconstruction with system matrix derived from point source measurements , 2006, IEEE Transactions on Medical Imaging.

[34]  J. Thie.  Understanding the standardized uptake value, its methods, and implications for usage. , 2004, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[35]  Jerry L Prince,et al.  Current methods in medical image segmentation. , 2000, Annual review of biomedical engineering.

[36]  Karin Haustermans,et al.  PET-based treatment planning in radiotherapy: a new standard? , 2007, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[37]  Steve R. Gunn,et al.  Markov Random Field Models for Segmentation of PET Images , 2001, IPMI.

[38]  Richard L. Wahl,et al.  Principles and Practice of Positron Emission Tomography , 2002 .

[39]  F Hofheinz,et al.  Effects of cold sphere walls in PET phantom measurements on the volume reproducing threshold , 2010, Physics in medicine and biology.

[40]  David W. Townsend,et al.  Positon emission tomography: basic science and clinical practice , 2008 .

[41]  Cyrill Burger,et al.  Automated functional image-guided radiation treatment planning for rectal cancer. , 2005, International journal of radiation oncology, biology, physics.

[42]  M. Bandstra,et al.  Measurements of Fukushima fallout by the Berkeley Radiological Air and Water Monitoring project , 2011, 2011 IEEE Nuclear Science Symposium Conference Record.

[43]  H. Zaidi,et al.  Assessment of various strategies for 18F-FET PET-guided delineation of target volumes in high-grade glioma patients , 2009, European Journal of Nuclear Medicine and Molecular Imaging.

[44]  Wilson Roa,et al.  A local contrast based approach to threshold segmentation for PET target volume delineation. , 2006, Medical physics.

[45]  Johan Vansteenkiste,et al.  The role of PET scan in diagnosis, staging, and management of non-small cell lung cancer. , 2004, The oncologist.

[46]  Aswin L Hoffmann,et al.  Comparison of five segmentation tools for 18F-fluoro-deoxy-glucose-positron emission tomography-based target volume definition in head and neck cancer. , 2007, International journal of radiation oncology, biology, physics.

[47]  Cyrill Burger,et al.  Radiation treatment planning with an integrated positron emission and computer tomography (PET/CT): a feasibility study. , 2003, International journal of radiation oncology, biology, physics.

[48]  Dale L. Bailey,et al.  Data Acquisition and Performance Characterization in PET , 2005 .

[49]  Ron Kohavi,et al.  A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.

[50]  Marco Brambilla,et al.  FDG-PET/CT imaging for staging and target volume delineation in preoperative conformal radiotherapy of rectal cancer. , 2008, International journal of radiation oncology, biology, physics.

[51]  Wilson Roa,et al.  Threshold modification for tumour imaging in non-small-cell lung cancer using positron emission tomography , 2005, Nuclear medicine communications.

[52]  A. Kirov,et al.  Partial volume effect correction in PET using regularized iterative deconvolution with variance control based on local topology , 2008, Physics in medicine and biology.

[53]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[54]  Heinrich R Schelbert,et al.  Improvements in cancer staging with PET/CT: literature-based evidence as of September 2006. , 2007, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[55]  Jos B. T. M. Roerdink,et al.  The Watershed Transform: Definitions, Algorithms and Parallelization Strategies , 2000, Fundam. Informaticae.

[56]  Sasa Mutic,et al.  18F-FDG PET definition of gross tumor volume for radiotherapy of non-small cell lung cancer: is a single standardized uptake value threshold approach appropriate? , 2006, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[57]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[58]  B. Murray,et al.  Thresholding in PET images of static and moving targets , 2005, Physics in medicine and biology.

[59]  Daniel A Low,et al.  A novel PET tumor delineation method based on adaptive region-growing and dual-front active contours. , 2008, Medical physics.

[60]  R. Kessler,et al.  Analysis of emission tomographic scan data: limitations imposed by resolution and background. , 1984, Journal of computer assisted tomography.

[61]  J. C. Noordam,et al.  Multivariate image segmentation based on geometrically guided fuzzy C‐means clustering , 2002 .

[62]  Di Yan,et al.  Defining a radiotherapy target with positron emission tomography. , 2002, International journal of radiation oncology, biology, physics.

[63]  Thomas K. Lewellen,et al.  Modeling and incorporation of system response functions in 3-D whole body PET , 2006, IEEE Transactions on Medical Imaging.

[64]  X Allen Li,et al.  Initial experience of FDG-PET/CT guided IMRT of head-and-neck carcinoma. , 2006, International journal of radiation oncology, biology, physics.

[65]  W. Oyen,et al.  Efficacy of fluorine-18-deoxyglucose positron emission tomography in detecting tumor recurrence after local ablative therapy for liver metastases: a prospective study. , 2002, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[66]  Paul Kinahan,et al.  Tumor delineation using PET in head and neck cancers: threshold contouring and lesion volumes. , 2006, Medical physics.

[67]  Anil K. Jain,et al.  Data clustering: a review , 1999, CSUR.

[68]  I. Buvat,et al.  Partial-Volume Effect in PET Tumor Imaging* , 2007, Journal of Nuclear Medicine.

[69]  Anne Bol,et al.  The limitation of PET imaging for biological adaptive-IMRT assessed in animal models. , 2009, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[70]  Jean-François Daisne,et al.  Tumor volume in pharyngolaryngeal squamous cell carcinoma: comparison at CT, MR imaging, and FDG PET and validation with surgical specimen. , 2004, Radiology.

[71]  S M Larson,et al.  Segmentation of lung lesion volume by adaptive positron emission tomography image thresholding , 1997, Cancer.

[72]  Gábor Székely,et al.  Assessment of 18F PET signals for automatic target volume definition in radiotherapy treatment planning. , 2006, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[73]  Aswin L Hoffmann,et al.  Can FDG-PET assist in radiotherapy target volume definition of metastatic lymph nodes in head-and-neck cancer? , 2009, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[74]  Michel Defrise,et al.  Image Reconstruction Algorithms in PET , 2005 .

[75]  Geoffrey J. McLachlan,et al.  Finite Mixture Models , 2019, Annual Review of Statistics and Its Application.

[76]  James A. Scott,et al.  Positron Emission Tomography: Basic Science and Clinical Practice , 2004 .

[77]  Ron Kikinis,et al.  Statistical validation of image segmentation quality based on a spatial overlap index. , 2004, Academic radiology.

[78]  Joe Y. Chang,et al.  GTV spatial conformity between different delineation methods by 18FDG PET/CT and pathology in esophageal cancer. , 2009, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[79]  Matt A. King,et al.  SPECT volume quantitation: influence of spatial resolution, source size and shape, and voxel size. , 1991, Medical physics.

[80]  Andre Dekker,et al.  The integration of PET-CT scans from different hospitals into radiotherapy treatment planning. , 2008, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[81]  P.E. Kinahan,et al.  Modeling and incorporation of system response functions in 3D whole body PET , 2004, IEEE Symposium Conference Record Nuclear Science 2004..