Literature DB >> 15465216

Automated model-based organ delineation for radiotherapy planning in prostatic region.

Vladimir Pekar1, Todd R McNutt, Michael R Kaus.   

Abstract

PURPOSE: Organ delineation is one of the most tedious and time-consuming parts of radiotherapy planning. It is usually performed by manual contouring in two-dimensional slices using simple drawing tools, and it may take several hours to delineate all structures of interest in a three-dimensional (3D) data set used for planning. In this paper, a 3D model-based approach to automated organ delineation is introduced that allows for a significant reduction of the time required for contouring. METHODS AND MATERIALS: The presented method is based on an adaptation of 3D deformable surface models to the boundaries of the anatomic structures of interest. The adaptation is based on a tradeoff between deformations of the model induced by its attraction to certain image features and the shape integrity of the model. To make the concept clinically feasible, interactive tools are introduced that allow quick correction in problematic areas in which the automated model adaptation may fail. A feasibility study with 40 clinical data sets was done for the male pelvic area, in which the risk organs (bladder, rectum, and femoral heads) were segmented by automatically adapting the corresponding organ models.
RESULTS: In several cases of the validation study, minor user interaction was required. Nevertheless, a statistically significant reduction in the time required compared with manual organ contouring was achieved. The results of the validation study showed that the presented model-based approach is accurate (1.0-1.7 mm mean error) for the tested anatomic structures.
CONCLUSION: A framework for organ delineation in radiotherapy planning is presented, including automated 3D model-based segmentation, as well as tools for interactive corrections. We demonstrated that the proposed approach is significantly more efficient than manual contouring in two-dimensional slices.

Mesh:

Year:  2004        PMID: 15465216     DOI: 10.1016/j.ijrobp.2004.06.004

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


  28 in total

1.  Assessment of accuracy and efficiency of atlas-based autosegmentation for prostate radiotherapy in a variety of clinical conditions.

Authors:  I Simmat; P Georg; D Georg; W Birkfellner; G Goldner; M Stock
Journal:  Strahlenther Onkol       Date:  2012-06-07       Impact factor: 3.621

Review 2.  Accurate accumulation of dose for improved understanding of radiation effects in normal tissue.

Authors:  David A Jaffray; Patricia E Lindsay; Kristy K Brock; Joseph O Deasy; W A Tomé
Journal:  Int J Radiat Oncol Biol Phys       Date:  2010-03-01       Impact factor: 7.038

3.  Deformable registration of abdominal kilovoltage treatment planning CT and tomotherapy daily megavoltage CT for treatment adaptation.

Authors:  Deshan Yang; Summer R Chaudhari; S Murty Goddu; David Pratt; Divya Khullar; Joseph O Deasy; Issam El Naqa
Journal:  Med Phys       Date:  2009-02       Impact factor: 4.071

4.  Combining a deformable model and a probabilistic framework for an automatic 3D segmentation of prostate on MRI.

Authors:  Nasr Makni; P Puech; R Lopes; A S Dewalle; O Colot; N Betrouni
Journal:  Int J Comput Assist Radiol Surg       Date:  2008-12-03       Impact factor: 2.924

5.  Bridging the text-image gap: a decision support tool for real-time PACS browsing.

Authors:  Merlijn Sevenster; Rob van Ommering; Yuechen Qian
Journal:  J Digit Imaging       Date:  2012-04       Impact factor: 4.056

Review 6.  Automated delineation of radiotherapy volumes: are we going in the right direction?

Authors:  G A Whitfield; P Price; G J Price; C J Moore
Journal:  Br J Radiol       Date:  2013-01       Impact factor: 3.039

7.  Iterative-cuts: longitudinal and scale-invariant segmentation via user-defined templates for rectosigmoid colon in gynecological brachytherapy.

Authors:  Tobias Lüddemann; Jan Egger
Journal:  J Med Imaging (Bellingham)       Date:  2016-06-20

8.  Segmentation of pelvic structures for planning CT using a geometrical shape model tuned by a multi-scale edge detector.

Authors:  Fabio Martínez; Eduardo Romero; Gaël Dréan; Antoine Simon; Pascal Haigron; Renaud de Crevoisier; Oscar Acosta
Journal:  Phys Med Biol       Date:  2014-03-05       Impact factor: 3.609

Review 9.  Vision 20/20: perspectives on automated image segmentation for radiotherapy.

Authors:  Gregory Sharp; Karl D Fritscher; Vladimir Pekar; Marta Peroni; Nadya Shusharina; Harini Veeraraghavan; Jinzhong Yang
Journal:  Med Phys       Date:  2014-05       Impact factor: 4.071

10.  Evolution of surface-based deformable image registration for adaptive radiotherapy of non-small cell lung cancer (NSCLC).

Authors:  Matthias Guckenberger; Kurt Baier; Anne Richter; Juergen Wilbert; Michael Flentje
Journal:  Radiat Oncol       Date:  2009-12-21       Impact factor: 3.481

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