Volumetric visualization of head and neck CT data for treatment planning.

PURPOSE To demonstrate the utility of volume rendering, an alternative visualization technique to surface rendering, in the practice of CT based radiotherapy planning for the head and neck. METHODS AND MATERIALS Rendo-avs, a volume visualization tool developed at the University of Chicago, was used to volume render head and neck CT scans from two cases. Rendo-avs is a volume rendering tool operating within the graphical user interface environment of AVS (Application Visualization System). Users adjust the opacity of various tissues by defining the opacity transfer function (OTF), a function which preclassifies voxels by opacity prior to rendering. By defining the opacity map (OTF), the user selectively enhances and suppresses structures of various intensity. Additional graphics tools are available within the AVS network, allowing for the manipulation of perspective, field of view, data orientation. Users may draw directly on volume rendered images, create a partial surface, and thereby correlate objects in the 3D scene to points on original axial slices. Information in volume rendered images is mapped into the original CT slices via a Z buffer, which contains the depth information (Z coordinate) for each pixel in the rendered view. Locally developed software was used to project conventionally designed GTV contours onto volume rendered images. RESULTS The lymph nodes, salivary glands, vessels, and airway are visualized in detail without prior manual segmentation. Volume rendering can be used to explore the finer anatomic structures that appear on consecutive axial slices as "points." Rendo-avs allowed for acceptable interactivity, with a processing time of approximately 5 seconds per 256 x 256 pixel output image. CONCLUSIONS Volume rendering is a useful alternative to surface rendering, offering high-quality visualization, 3D anatomic delineation, and time savings to the user, due to the elimination of manual segmentation as a preprocessing step. Volume rendered images can be merged with conventional treatment planning images to add anatomic information to the treatment planning process.

[1]  M Schwaiger,et al.  The value of F-18-fluorodeoxyglucose PET for the 3-D radiation treatment planning of malignant gliomas. , 1998, International journal of radiation oncology, biology, physics.

[2]  R. A. Drebin,et al.  Fidelity of Three‐dimensional CT Imaging for Detecting Fracture Gaps , 1989, Journal of computer assisted tomography.

[3]  Ross T. Whitaker,et al.  Direct visualization of volume data , 1992, IEEE Computer Graphics and Applications.

[4]  C. Pelizzari,et al.  Accurate Three‐Dimensional Registration of CT, PET, and/or MR Images of the Brain , 1989, Journal of computer assisted tomography.

[5]  B S Kuszyk,et al.  The current state of the art in three dimensional oncologic imaging: an overview. , 1995, International journal of radiation oncology, biology, physics.

[6]  K R Hoffmann,et al.  Small simulated polyps in pig colon: sensitivity of CT virtual colography. , 1997, Radiology.

[7]  K. K. Tan,et al.  Surface of the brain: three-dimensional MR images created with volume rendering. , 1989, Radiology.

[8]  Marc Levoy,et al.  Display of surfaces from volume data , 1988, IEEE Computer Graphics and Applications.

[9]  G. Tracton,et al.  Image registration: an essential part of radiation therapy treatment planning. , 1998, International journal of radiation oncology, biology, physics.

[10]  A. Luessenhop,et al.  Cerebral arteriovenous malformations. Indications for and results of surgery, and the role of intravascular techniques. , 1984, Journal of neurosurgery.

[11]  M W Vannier,et al.  Craniosynostosis: diagnostic value of three-dimensional CT reconstruction. , 1989, Radiology.

[12]  Marc Levoy,et al.  Interactive visualization of 3D medical data , 1989, Computer.

[13]  G T Chen,et al.  Volumetric visualization of anatomy for treatment planning. , 1996, International journal of radiation oncology, biology, physics.

[14]  I. Kalet,et al.  Three dimensional planning target volumes: a model and a software tool. , 1995, International Journal of Radiation Oncology, Biology, Physics.

[15]  T. Todd Elvins,et al.  A survey of algorithms for volume visualization , 1992, COMG.

[16]  M Goitein,et al.  Multi-dimensional treatment planning: I. Delineation of anatomy. , 1983, International journal of radiation oncology, biology, physics.

[17]  K R Hoffmann,et al.  CT colonography with three-dimensional problem solving for detection of colonic polyps. , 1998, AJR. American journal of roentgenology.

[18]  G T Chen,et al.  Tumor and target delineation: current research and future challenges. , 1995, International journal of radiation oncology, biology, physics.

[19]  Marc Levoy,et al.  Three‐dimensional high‐resolution volume rendering (HRVR) of computed tomography data: Applications to otolaryngology—head and neck surgery , 1991, The Laryngoscope.

[20]  M Goitein,et al.  Computed tomography in planning radiation therapy. , 1979, International journal of radiation oncology, biology, physics.

[21]  Karl Heinz Höhne,et al.  A volume-based anatomical atlas , 1992, IEEE Computer Graphics and Applications.

[22]  Pat Hanrahan,et al.  Volume rendering , 1998 .

[23]  Charles A. Pelizzari,et al.  Real-Time Merging of Visible Surfaces for Display and Segmentation , 1996, VBC.

[24]  H. Hricak,et al.  Prostate volumes defined by magnetic resonance imaging and computerized tomographic scans for three-dimensional conformal radiotherapy. , 1996, International journal of radiation oncology, biology, physics.

[25]  M Goitein,et al.  The utility of computed tomography in radiation therapy: an estimate of outcome. , 1979, International journal of radiation oncology, biology, physics.

[26]  V Argiro,et al.  Perspective volume rendering of CT and MR images: applications for endoscopic imaging. , 1996, Radiology.

[27]  R. Lindberg Distribution of cervical lymph node metastases from squamous cell carcinoma of the upper respiratory and digestive tracts , 1972, Cancer.

[28]  Pat Hanrahan,et al.  Volume Rendering , 2020, Definitions.

[29]  M. Bomans,et al.  Volume Visualization in Magnetic Resonance Angiography , 1992 .

[30]  C. Pelizzari,et al.  Functional imaging in treatment planning of brain lesions. , 1997, International journal of radiation oncology, biology, physics.

[31]  Richard A. Robb,et al.  Visualization in biomedical computing , 1999, Parallel Comput..

[32]  G. Herman,et al.  3D Imaging In Medicine , 1991 .

[33]  C H Ketting,et al.  Consistency of three-dimensional planning target volumes across physicians and institutions. , 1997, International journal of radiation oncology, biology, physics.

[34]  B R Paliwal,et al.  A three-dimensional volume visualization package applied to stereotactic radiosurgery treatment planning. , 1991, International journal of radiation oncology, biology, physics.

[35]  Richard A. Robb,et al.  A Software System for Interactive and Quantitative Analysis of Biomedical Images , 1990 .