Clinical evaluation of soft tissue organ boundary visualization on cone-beam computed tomographic imaging.

PURPOSE Cone-beam computed tomographic images (CBCTs) are increasingly used for setup correction, soft tissue targeting, and image-guided adaptive radiotherapy. However, CBCT image quality is limited by low contrast and imaging artifacts. This analysis investigates the detectability of soft tissue boundaries in CBCT by performing a multiple-observer segmentation study. METHODS AND MATERIALS In four prostate cancer patients prostate, bladder and rectum were repeatedly delineated by five observers on CBCTs and fan-beam CTs (FBCTs). A volumetric analysis of contouring variations was performed by calculating coefficients of variation (COV: standard deviation/average volume). The topographical distribution of contouring variations was analyzed using an average surface mesh-based method. RESULTS Observer- and patient-averaged COVs for FBCT/CBCT were 0.09/0.19 for prostate, 0.05/0.08 for bladder, and 0.09/0.08 for rectum. Contouring variations on FBCT were significantly smaller than on CBCT for prostate (p < 0.03) and bladder (p < 0.04), but not for rectum (p < 0.37; intermodality differences). Intraobserver variations from repeated contouring of the same image set were not significant for either FBCT or CBCT (p < 0.05). Average standard deviations of individual observers' contour differences from average surface meshes on FBCT vs. CBCT were 1.5 vs. 2.1 mm for prostate, 0.7 vs. 1.4 mm for bladder, and 1.3 vs. 1.5 mm for rectum. The topographical distribution of contouring variations was similar for FBCT and CBCT. CONCLUSION Contouring variations were larger on CBCT than FBCT, except for rectum. Given the well-documented uncertainty in soft tissue contouring in the pelvis, improvement of CBCT image quality and establishment of well-defined soft tissue identification rules are desirable for image-guided radiotherapy.

[1]  M. Macpherson,et al.  Calcifications are potential surrogates for prostate localization in image-guided radiotherapy. , 2008, International journal of radiation oncology, biology, physics.

[2]  T. Rosewall,et al.  Comparison of localization performance with implanted fiducial markers and cone-beam computed tomography for on-line image-guided radiotherapy of the prostate. , 2007, International journal of radiation oncology, biology, physics.

[3]  P. Kunz,et al.  A qualitative and a quantitative analysis of an auto-segmentation module for prostate cancer. , 2009, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[4]  L. Xing,et al.  Feature-based rectal contour propagation from planning CT to cone beam CT. , 2008, Medical physics.

[5]  D A Jaffray,et al.  Inter-observer variability of prostate delineation on cone beam computerised tomography images. , 2009, Clinical oncology (Royal College of Radiologists (Great Britain)).

[6]  Jinkoo Kim,et al.  Examining margin reduction and its impact on dose distribution for prostate cancer patients undergoing daily cone-beam computed tomography. , 2008, International journal of radiation oncology, biology, physics.

[7]  M van Herk,et al.  Comparison of prostate cancer treatment in two institutions: a quality control study. , 1999, International journal of radiation oncology, biology, physics.

[8]  Jan-Jakob Sonke,et al.  Adaptive radiotherapy for prostate cancer using kilovoltage cone-beam computed tomography: first clinical results. , 2008, International journal of radiation oncology, biology, physics.

[9]  John Wong,et al.  Assessment of residual error for online cone-beam CT-guided treatment of prostate cancer patients. , 2004, International journal of radiation oncology, biology, physics.

[10]  M. Fuss,et al.  Volumetric image-guidance: Does routine usage prompt adaptive re-planning? An institutional review , 2008, Acta oncologica.

[11]  Jeffrey Williamson,et al.  How does CT image noise affect 3D deformable image registration for image-guided radiotherapy planning? , 2008, Medical physics.

[12]  J. Galvin,et al.  A cone beam CT-Based Study for Clinical Target Definition Using Pelvic Anatomy During Postprostatectomy Radiotherapy. , 2008, International journal of radiation oncology, biology, physics.

[13]  Radhe Mohan,et al.  A deformable image registration method to handle distended rectums in prostate cancer radiotherapy. , 2006, Medical physics.

[14]  Fang-Fang Yin,et al.  Dosimetric feasibility of cone-beam CT-based treatment planning compared to CT-based treatment planning. , 2006, International journal of radiation oncology, biology, physics.

[15]  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.

[16]  M van Herk,et al.  Definition of the prostate in CT and MRI: a multi-observer study. , 1999, International journal of radiation oncology, biology, physics.

[17]  David A Jaffray,et al.  Improving image-guided target localization through deformable registration , 2008, Acta oncologica.

[18]  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.

[19]  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.

[20]  Robert A. Hummel,et al.  Exploiting Triangulated Surface Extraction Using Tetrahedral Decomposition , 1995, IEEE Trans. Vis. Comput. Graph..

[21]  D. Hallahan,et al.  A study on adaptive IMRT treatment planning using kV cone-beam CT. , 2007, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[22]  T. Marchant,et al.  Shading correction algorithm for improvement of cone-beam CT images in radiotherapy , 2008, Physics in medicine and biology.