Automatic prostate segmentation in cone-beam computed tomography images using rigid registration

We propose to evaluate automatic three-dimensional gray-value rigid registration (RR) methods for prostate localization on cone-beam computed tomography (CBCT) scans. In total, 103 CBCT scans of 9 prostate patients have been analyzed. Each one was registered to the planning CT scan using different methods: (a) global RR, (b) pelvis bone structure RR, (c) bone RR refined by local soft-tissue RR using the CT clinical target volume (CTV) expanded with a 1, 3, 5, 8, 10, 12, 15 or 20-mm margin. To evaluate results, a radiation oncologist was asked to manually delineate the CTV on the CBCT scans. The Dice coefficients between each automatic CBCT segmentation - derived from the transformation of the manual CT segmentation - and the manual CBCT segmentation were calculated. Global or bone CT/CBCT RR has been shown to yield insufficient results in average. Local RR with an 8-mm margin around the CTV after bone RR was found to be the best candidate for systematically significantly improving prostate localization.

[1]  Daniel W. Miller,et al.  Comparison of conventional-dose vs high-dose conformal radiation therapy in clinically localized adenocarcinoma of the prostate: a randomized controlled trial. , 2005, JAMA.

[2]  Lei Dong,et al.  Automatic registration of the prostate for computed-tomography-guided radiotherapy. , 2003, Medical physics.

[3]  David Wilkins,et al.  A study of prostate delineation referenced against a gold standard created from the visible human data. , 2007, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[4]  Luis Ibáñez,et al.  The ITK Software Guide , 2005 .

[5]  M. V. van Herk,et al.  The influence of a dietary protocol on cone beam CT-guided radiotherapy for prostate cancer patients. , 2008, International journal of radiation oncology, biology, physics.

[6]  D. Wolfe,et al.  Nonparametric Statistical Methods. , 1974 .

[7]  L. R. Dice.  Measures of the Amount of Ecologic Association Between Species , 1945 .

[8]  Jeffrey Williamson,et al.  Clinical evaluation of soft tissue organ boundary visualization on cone-beam computed tomographic imaging. , 2010, International journal of radiation oncology, biology, physics.

[9]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[10]  Guido Gerig,et al.  User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability , 2006, NeuroImage.

[11]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[12]  Jan-Jakob Sonke,et al.  Automatic prostate localization on cone-beam CT scans for high precision image-guided radiotherapy. , 2005, International journal of radiation oncology, biology, physics.

[13]  Marcel van Herk,et al.  Quantification of shape variation of prostate and seminal vesicles during external beam radiotherapy. , 2005, International journal of radiation oncology, biology, physics.

[14]  J. Udupa,et al.  Shape-based interpolation of multidimensional objects. , 1990, IEEE transactions on medical imaging.

[15]  J. Wong,et al.  Flat-panel cone-beam computed tomography for image-guided radiation therapy. , 2002, International journal of radiation oncology, biology, physics.