Literature DB >> 15930608

A feasibility study to investigate the use of thin-plate splines to account for prostate deformation.

Niranjan Venugopal1, Boyd McCurdy, Alex Hnatov, Arbind Dubey.   

Abstract

Image registration is an important step in the radiotherapy treatment planning process. It provides a method of fusing different types of diagnostic imaging information. One such application is to combine magnetic resonance spectroscopic images (MRSI) of the prostate with anatomical MRI and/or computed tomography images that are routinely used in the radiation treatment planning of prostate cancer. MRSI provides in vivo information related to the underlying metabolic activity of tissues, and can be related to the presence of cancer. However, the inflated endorectal coil required during MRS imaging poses a potential problem by deforming the prostate when it is filled with approximately 100 cm3 of air during image acquisition. This pushes the prostate superiorly/anteriorly, deforming the prostate and consequently the spectroscopic imaging data in a nonlinear manner. In this application, the coil-deformed MRS images are warped back to a non-deformed state, using a single data set. A nonlinear warping algorithm is presented to achieve this. Results indicate that the algorithm attains an accuracy of 97% (4 cm3 difference) when reproducing the total prostate volume compared to a Radiation Oncologist defined prostate volume. This difference is slightly smaller than the measured intra-operator variance of +/-1.5 cm3 (deflated coil) and the measured algorithm variance of +/-1.0 cm3. Additionally, intraprostatic nodules were used to assess the accuracy of the warping algorithm in regions inside the prostate. While choosing anatomical tie points along the external prostate surface, analysis of the nodules revealed the algorithm accuracy reduced to 63-93%.

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Year:  2005        PMID: 15930608     DOI: 10.1088/0031-9155/50/12/010

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  11 in total

1.  PROBABILISTIC NON-RIGID REGISTRATION OF PROSTATE IMAGES: MODELING AND QUANTIFYING UNCERTAINTY.

Authors:  Petter Risholm; Andriy Fedorov; Jennifer Pursley; Kemal Tuncali; Robert Cormack; William M Wells
Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2011-06-09

Review 2.  MR-guided prostate interventions.

Authors:  Clare Tempany; Sarah Straus; Nobuhiko Hata; Steven Haker
Journal:  J Magn Reson Imaging       Date:  2008-02       Impact factor: 4.813

3.  Multimodal image registration for the identification of dominant intraprostatic lesion in high-precision radiotherapy treatments.

Authors:  Delia Ciardo; Barbara Alicja Jereczek-Fossa; Giuseppe Petralia; Giorgia Timon; Dario Zerini; Raffaella Cambria; Elena Rondi; Federica Cattani; Alessia Bazani; Rosalinda Ricotti; Maria Garioni; Davide Maestri; Giulia Marvaso; Paola Romanelli; Marco Riboldi; Guido Baroni; Roberto Orecchia
Journal:  Br J Radiol       Date:  2017-08-22       Impact factor: 3.039

4.  Learning statistical correlation for fast prostate registration in image-guided radiotherapy.

Authors:  Yonghong Shi; Shu Liao; Dinggang Shen
Journal:  Med Phys       Date:  2011-11       Impact factor: 4.071

5.  Three-dimensional elastic image registration based on strain energy minimization: application to prostate magnetic resonance imaging.

Authors:  Bao Zhang; Dwayne D Arola; Steve Roys; Rao P Gullapalli
Journal:  J Digit Imaging       Date:  2011-08       Impact factor: 4.056

6.  A Bayesian nonrigid registration method to enhance intraoperative target definition in image-guided prostate procedures through uncertainty characterization.

Authors:  Jennifer Pursley; Petter Risholm; Andriy Fedorov; Kemal Tuncali; Fiona M Fennessy; William M Wells; Clare M Tempany; Robert A Cormack
Journal:  Med Phys       Date:  2012-11       Impact factor: 4.071

Review 7.  Current role and future perspectives of magnetic resonance spectroscopy in radiation oncology for prostate cancer.

Authors:  Aleksandra Zapotoczna; Giuseppe Sasso; John Simpson; Mack Roach
Journal:  Neoplasia       Date:  2007-06       Impact factor: 5.715

8.  Assessment of a commercially available automatic deformable registration system.

Authors:  B Gino Fallone; D Ryan C Rivest; Terence A Riauka; Albert D Murtha
Journal:  J Appl Clin Med Phys       Date:  2010-06-09       Impact factor: 2.102

9.  Interactive, multi-modality image registrations for combined MRI/MRSI-planned HDR prostate brachytherapy.

Authors:  Galen Reed; J Adam Cunha; Susan Noworolski; John Kurhanewicz; Daniel Vigneron; I-Chow Hsu; Jean Pouliot
Journal:  J Contemp Brachytherapy       Date:  2011-03-31

10.  A framework for deformable image registration validation in radiotherapy clinical applications.

Authors:  Raj Varadhan; Grigorios Karangelis; Karthik Krishnan; Susanta Hui
Journal:  J Appl Clin Med Phys       Date:  2013-01-02       Impact factor: 2.102

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