Literature DB >> 15380600

Automatic localization of the prostate for on-line or off-line image-guided radiotherapy.

Monique H P Smitsmans1, Jochem W H Wolthaus, Xavier Artignan, Josien de Bois, David A Jaffray, Joos V Lebesque, Marcel van Herk.   

Abstract

PURPOSE: With higher radiation dose, higher cure rates have been reported in prostate cancer patients. The extra margin needed to account for prostate motion, however, limits the level of dose escalation, because of the presence of surrounding organs at risk. Knowledge of the precise position of the prostate would allow significant reduction of the treatment field. Better localization of the prostate at the time of treatment is therefore needed, e.g. using a cone-beam computed tomography (CT) system integrated with the linear accelerator. Localization of the prostate relies upon manual delineation of contours in successive axial CT slices or interactive alignment and is fairly time-consuming. A faster method is required for on-line or off-line image-guided radiotherapy, because of prostate motion, for patient throughput and efficiency. Therefore, we developed an automatic method to localize the prostate, based on 3D gray value registration. METHODS AND MATERIALS: A study was performed on conventional repeat CT scans of 19 prostate cancer patients to develop the methodology to localize the prostate. For each patient, 8-13 repeat CT scans were made during the course of treatment. First, the planning CT scan and the repeat CT scan were registered onto the rigid bony structures. Then, the delineated prostate in the planning CT scan was enlarged by an optimum margin of 5 mm to define a region of interest in the planning CT scan that contained enough gray value information for registration. Subsequently, this region was automatically registered to a repeat CT scan using 3D gray value registration to localize the prostate. The performance of automatic prostate localization was compared to prostate localization using contours. Therefore, a reference set was generated by registering the delineated contours of the prostates in all scans of all patients. Gray value registrations that showed large differences with respect to contour registrations were detected with a chi(2) analysis and were removed from the data set before further analysis.
RESULTS: Comparing gray value registration to contour registration, we found a success rate of 91%. The accuracy for rotations around the left-right, cranial-caudal, and anterior-posterior axis was 2.4 degrees, 1.6 degrees, and 1.3 degrees (1 SD), respectively, and for translations along these axes 0.7, 1.3, and 1.2 mm (1 SD), respectively. A large part of the error is attributed to uncertainty in the reference contour set. Automatic prostate localization takes about 45 seconds on a 1.7 GHz Pentium IV personal computer.
CONCLUSIONS: This newly developed method localizes the prostate quickly, accurately, and with a good success rate, although visual inspection is still needed to detect outliers. With this approach, it will be possible to correct on-line or off-line for prostate movement. Combined with the conformity of intensity-modulated dose distributions, this method might permit dose escalation beyond that of current conformal approaches, because margins can be safely reduced.

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Year:  2004        PMID: 15380600     DOI: 10.1016/j.ijrobp.2004.05.027

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


  14 in total

1.  A novel approach for establishing benchmark CBCT/CT deformable image registrations in prostate cancer radiotherapy.

Authors:  Jinkoo Kim; Sanath Kumar; Chang Liu; Hualiang Zhong; Deepak Pradhan; Mira Shah; Richard Cattaneo; Raphael Yechieli; Jared R Robbins; Mohamed A Elshaikh; Indrin J Chetty
Journal:  Phys Med Biol       Date:  2013-10-31       Impact factor: 3.609

2.  Prostate CT segmentation method based on nonrigid registration in ultrasound-guided CT-based HDR prostate brachytherapy.

Authors:  Xiaofeng Yang; Peter Rossi; Tomi Ogunleye; David M Marcus; Ashesh B Jani; Hui Mao; Walter J Curran; Tian Liu
Journal:  Med Phys       Date:  2014-11       Impact factor: 4.071

3.  Online updating of context-aware landmark detectors for prostate localization in daily treatment CT images.

Authors:  Xiubin Dai; Yaozong Gao; Dinggang Shen
Journal:  Med Phys       Date:  2015-05       Impact factor: 4.071

4.  Registration accuracy for MR images of the prostate using a subvolume based registration protocol.

Authors:  Joakim H Jonsson; Patrik Brynolfsson; Anders Garpebring; Mikael Karlsson; Karin Söderström; Tufve Nyholm
Journal:  Radiat Oncol       Date:  2011-06-16       Impact factor: 3.481

5.  Comparison of localization performance with implanted fiducial markers and cone-beam computed tomography for on-line image-guided radiotherapy of the prostate.

Authors:  Douglas J Moseley; Elizabeth A White; Kirsty L Wiltshire; Tara Rosewall; Michael B Sharpe; Jeffrey H Siewerdsen; Jean-Pierre Bissonnette; Mary Gospodarowicz; Padraig Warde; Charles N Catton; David A Jaffray
Journal:  Int J Radiat Oncol Biol Phys       Date:  2007-03-01       Impact factor: 7.038

6.  Sparse patch-based label propagation for accurate prostate localization in CT images.

Authors:  Shu Liao; Yaozong Gao; Jun Lian; Dinggang Shen
Journal:  IEEE Trans Med Imaging       Date:  2012-11-27       Impact factor: 10.048

7.  The role of seminal vesicle motion in target margin assessment for online image-guided radiotherapy for prostate cancer.

Authors:  Jian Liang; Qiuwen Wu; Di Yan
Journal:  Int J Radiat Oncol Biol Phys       Date:  2008-12-26       Impact factor: 7.038

8.  Evaluation of Image Enhancement Method on Target Registration Using Cone Beam CT in Radiation Therapy.

Authors:  Hui Yan; Ren Lei; Jackie Wu; Fu Di; Fang-Fang Yin
Journal:  Clin Med Oncol       Date:  2008-03-28

9.  Development of CBCT-based prostate setup correction strategies and impact of rectal distension.

Authors:  Christine Boydev; Abdelmalik Taleb-Ahmed; Foued Derraz; Laurent Peyrodie; Jean-Philippe Thiran; David Pasquier
Journal:  Radiat Oncol       Date:  2015-04-10       Impact factor: 3.481

10.  Comparison of User-Directed and Automatic Mapping of the Planned Isocenter to Treatment Space for Prostate IGRT.

Authors:  Zijie Xu; Ronald Chen; Andrew Wang; Andrea Kress; Mark Foskey; An Qin; Timothy Cullip; Gregg Tracton; Sha Chang; Joel Tepper; Di Yan; Edward Chaney
Journal:  Int J Biomed Imaging       Date:  2013-11-21
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