Literature DB >> 1938575

Integration of multimodality imaging data for radiotherapy treatment planning.

M L Kessler1, S Pitluck, P Petti, J R Castro.   

Abstract

This paper describes computational techniques to permit the quantitative integration of magnetic resonance (MR), positron emission tomography (PET), and x-ray computed tomography (CT) imaging data sets. These methods are used to incorporate unique diagnostic information provided by PET and MR imaging into CT-based treatment planning for radiotherapy of intracranial tumors and vascular malformations. Integration of information from the different imaging modalities is treated as a two-step process. The first step is to determine the set of geometric parameters relating the coordinates of two imaging data sets. No universal method for determining these parameters is appropriate because of the diversity of contemporary imaging methods and data formats. Most situations can be handled by one of the four different techniques described. These four methods make use of specific geometric objects contained in the two data sets to determine the parameters. These objects are: (a) anatomical and/or fiducial points, (b) attached line markers, (c) anatomical surfaces, and (d) outlines of anatomical structures. The second step involves using the derived transformation to transfer outlines of treatment volumes and/or anatomical structures drawn on the images of one imaging study to the images of another study, usually the treatment planning CT. Solid modelling and image processing techniques have been adapted and developed further to accomplish this task. Clinical examples and phantom studies are presented which verify the different aspects of these techniques and demonstrate the accuracy with which they can be applied. Clinical use of these techniques for treatment planning has resulted in improvements in localization of treatment volumes and critical structures in the brain. These improvements have allowed greater sparing of normal tissues and more precise delivery of energy to the desired irradiation volume. It is believed that these improvements will have a positive impact on the outcome of radiation therapy.

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Mesh:

Year:  1991        PMID: 1938575     DOI: 10.1016/0360-3016(91)90345-5

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


  15 in total

1.  Technical note: deformable image registration on partially matched images for radiotherapy applications.

Authors:  Deshan Yang; S Murty Goddu; Wei Lu; Olga L Pechenaya; Yu Wu; Joseph O Deasy; Issam El Naqa; Daniel A Low
Journal:  Med Phys       Date:  2010-01       Impact factor: 4.071

Review 2.  The use of medical images in planning and delivery of radiation therapy.

Authors:  I J Kalet; M M Austin-Seymour
Journal:  J Am Med Inform Assoc       Date:  1997 Sep-Oct       Impact factor: 4.497

Review 3.  Treatment planning with heavy ions.

Authors:  P Chauvel
Journal:  Radiat Environ Biophys       Date:  1995-03       Impact factor: 1.925

4.  CT- and MRI-based gross target volume comparison in vestibular schwannomas.

Authors:  Bhudevi Soubhagya N Kulkarni; Harjot Bajwa; Mukka Chandrashekhar; Sunil Dutt Sharma; Rohith Singareddy; Dileep Gudipudi; Shabbir Ahmad; Alok Kumar; N V N Madusudan Sresty; Alluri Krishnam Raju
Journal:  Rep Pract Oncol Radiother       Date:  2017-04-22

5.  PET/MRI of inflammation in myocardial infarction.

Authors:  Won Woo Lee; Brett Marinelli; Anja M van der Laan; Brena F Sena; Rostic Gorbatov; Florian Leuschner; Partha Dutta; Yoshiko Iwamoto; Takuya Ueno; Mark P V Begieneman; Hans W M Niessen; Jan J Piek; Claudio Vinegoni; Mikael J Pittet; Filip K Swirski; Ahmed Tawakol; Marcelo Di Carli; Ralph Weissleder; Matthias Nahrendorf
Journal:  J Am Coll Cardiol       Date:  2012-01-10       Impact factor: 24.094

6.  A fast inverse consistent deformable image registration method based on symmetric optical flow computation.

Authors:  Deshan Yang; Hua Li; Daniel A Low; Joseph O Deasy; Issam El Naqa
Journal:  Phys Med Biol       Date:  2008-10-14       Impact factor: 3.609

Review 7.  Results of heavy ion radiotherapy.

Authors:  J R Castro
Journal:  Radiat Environ Biophys       Date:  1995-03       Impact factor: 1.925

8.  CT-3D rotational angiography automatic registration: a sensitivity analysis.

Authors:  J Stancanello; C Cavedon; P Francescon; P Cerveri; G Ferrigno; F Causin; F Colombo
Journal:  Med Biol Eng Comput       Date:  2005-09       Impact factor: 3.079

9.  Intensity modulated radiotherapy: advantages, limitations and future developments.

Authors:  Ky Cheung
Journal:  Biomed Imaging Interv J       Date:  2006-01-01

10.  The use of PET/CT in radiotherapy planning: contribution of deformable registration.

Authors:  Ela Delikgoz Soykut; Esat Mahmut Ozsahin; Yildiz Yukselen Guney; Suheyla Aytac Arslan; Ozlem Derinalp Or; Muzaffer Bedri Altundag; Gamze Ugurluer; Pelagia G Tsoutsou
Journal:  Front Oncol       Date:  2013-04-12       Impact factor: 6.244

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