Literature DB >> 15191296

Phantom validation of coregistration of PET and CT for image-guided radiotherapy.

William C Lavely1, Christopher Scarfone, Hakan Cevikalp, Rui Li, Daniel W Byrne, Anthony J Cmelak, Benoit Dawant, Ronald R Price, Dennis E Hallahan, J Michael Fitzpatrick.   

Abstract

Radiotherapy treatment planning integrating positron emission tomography (PET) and computerized tomography (CT) is rapidly gaining acceptance in the clinical setting. Although hybrid systems are available, often the planning CT is acquired on a dedicated system separate from the PET scanner. A limiting factor to using PET data becomes the accuracy of the CT/PET registration. In this work, we use phantom and patient validation to demonstrate a general method for assessing the accuracy of CT/PET image registration and apply it to two multi-modality image registration programs. An IAEA (International Atomic Energy Association) brain phantom and an anthropomorphic head phantom were used. Internal volumes and externally mounted fiducial markers were filled with CT contrast and 18F-fluorodeoxyglucose (FDG). CT, PET emission, and PET transmission images were acquired and registered using two different image registration algorithms. CT/PET Fusion (GE Medical Systems, Milwaukee, WI) is commercially available and uses a semi-automated initial step followed by manual adjustment. Automatic Mutual Information-based Registration (AMIR), developed at our institution, is fully automated and exhibits no variation between repeated registrations. Registration was performed using distinct phantom structures; assessment of accuracy was determined from registration of the calculated centroids of a set of fiducial markers. By comparing structure-based registration with fiducial-based registration, target registration error (TRE) was computed at each point in a three-dimensional (3D) grid that spans the image volume. Identical methods were also applied to patient data to assess CT/PET registration accuracy. Accuracy was calculated as the mean with standard deviation of the TRE for every point in the 3D grid. Overall TRE values for the IAEA brain phantom are: CT/PET Fusion = 1.71 +/- 0.62 mm, AMIR = 1.13 +/- 0.53 mm; overall TRE values for the anthropomorphic head phantom are: CT/PET Fusion = 1.66 +/- 0.53 mm, AMIR = 1.15 +/- 0.48 mm. Precision (repeatability by a single user) measured for CT/PET Fusion: IAEA phantom = 1.59 +/- 0.67 mm and anthropomorphic head phantom = 1.63 +/- 0.52 mm. (AMIR has exact precision and so no measurements are necessary.) One sample patient demonstrated the following accuracy results: CT/PET Fusion = 3.89 +/- 1.61 mm, AMIR = 2.86 +/- 0.60 mm. Semi-automatic and automatic image registration methods may be used to facilitate incorporation of PET data into radiotherapy treatment planning in relatively rigid anatomic sites, such as head and neck. The overall accuracies in phantom and patient images are < 2 mm and < 4 mm, respectively, using either registration algorithm. Registration accuracy may decrease, however, as distance from the initial registration points (CT/PET fusion) or center of the image (AMIR) increases. Additional information provided by PET may improve dose coverage to active tumor subregions and hence tumor control. This study shows that the accuracy obtained by image registration with these two methods is well suited for image-guided radiotherapy.

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Year:  2004        PMID: 15191296     DOI: 10.1118/1.1688041

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  14 in total

1.  A method of image registration for small animal, multi-modality imaging.

Authors:  Patrick L Chow; David B Stout; Evangelia Komisopoulou; Arion F Chatziioannou
Journal:  Phys Med Biol       Date:  2006-01-04       Impact factor: 3.609

2.  Fused radioimmunoscintigraphy for treatment planning.

Authors:  Rodney J Ellis; Deborah A Kaminsky
Journal:  Rev Urol       Date:  2006

3.  Validation of the CT-MRI image registration with a dedicated phantom.

Authors:  Sofia Spampinato; Anna Maria Gueli; Luigi Raffaele; Concetta Stancampiano; Giovanni Carlo Ettorre
Journal:  Radiol Med       Date:  2014-07-15       Impact factor: 3.469

4.  Partial volume correction strategies for quantitative FDG PET in oncology.

Authors:  Nikie J Hoetjes; Floris H P van Velden; Otto S Hoekstra; Corneline J Hoekstra; Nanda C Krak; Adriaan A Lammertsma; Ronald Boellaard
Journal:  Eur J Nucl Med Mol Imaging       Date:  2010-04-27       Impact factor: 9.236

5.  Acceptance test of a commercially available software for automatic image registration of computed tomography (CT), magnetic resonance imaging (MRI) and 99mTc-methoxyisobutylisonitrile (MIBI) single-photon emission computed tomography (SPECT) brain images.

Authors:  Gianfranco Loi; Marco Dominietto; Irene Manfredda; Eleonora Mones; Alessandro Carriero; Eugenio Inglese; Marco Krengli; Marco Brambilla
Journal:  J Digit Imaging       Date:  2008-09       Impact factor: 4.056

6.  Improving Accuracy for Image Fusion in Abdominal Ultrasonography.

Authors:  Caroline Ewertsen; Kristoffer L Hansen; Birthe M Henriksen; Michael B Nielsen
Journal:  Diagnostics (Basel)       Date:  2012-08-27

Review 7.  Image fusion techniques in permanent seed implantation.

Authors:  Alfredo Polo
Journal:  J Contemp Brachytherapy       Date:  2010-10-13

8.  Nonrigid image registration for head and neck cancer radiotherapy treatment planning with PET/CT.

Authors:  Rob H Ireland; Karen E Dyker; David C Barber; Steven M Wood; Michael B Hanney; Wendy B Tindale; Neil Woodhouse; Nigel Hoggard; John Conway; Martin H Robinson
Journal:  Int J Radiat Oncol Biol Phys       Date:  2007-04-18       Impact factor: 7.038

9.  A non-rigid registration method for the analysis of local deformations in the wood cell wall.

Authors:  Alessandra Patera; Stephan Carl; Marco Stampanoni; Dominique Derome; Jan Carmeliet
Journal:  Adv Struct Chem Imaging       Date:  2018-01-22

10.  Evaluation of GMI and PMI diffeomorphic-based demons algorithms for aligning PET and CT Images.

Authors:  Juan Yang; Hongjun Wang; You Zhang; Yong Yin
Journal:  J Appl Clin Med Phys       Date:  2015-07-08       Impact factor: 2.102

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