Online from: 1995
Subject Area: Mechanical & Materials Engineering
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|Title:||Geometrical modeling of H&N cancer tumor|
|Author(s):||Ali K. Kamrani, (Design and Free Form Fabrication Laboratory, University of Houston, Houston, Texas, USA King Saud University, Riyadh, Saudi Arabia), Maryam Azimi, (Design and Free Form Fabrication Laboratory, Industrial Engineering Department, University of Houston, Houston, Texas, USA)|
|Citation:||Ali K. Kamrani, Maryam Azimi, (2011) "Geometrical modeling of H&N cancer tumor", Rapid Prototyping Journal, Vol. 17 Iss: 1, pp.55 - 63|
|Keywords:||Cancer, Head (anatomy), Image scanners, Modelling, Neck (anatomy), Radiotherapy|
|Article type:||Research paper|
|DOI:||10.1108/13552541111098635 (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
Purpose – Most of the current radiation treatment planning systems use pre-treatment computed tomography (CT) images to detect the tumor location and then plan the radiation therapy to be delivered during the treatment period. It is assumed that the tumor geometry will not change throughout the treatment course; however, tumor geometry is shown to be changing over time. The purpose of this paper is to present results of an ongoing research in 3-D modeling and reconstruction of head and neck cancer tumors. The results from this phase of the project will be used in developing a prediction model for tumor deformation during radiation treatment of cancer patients.
Design/methodology/approach – By using CT scan data in the 3-D ASCII format, the tumor's progressive geometric changes during the treatment period are quantified. After constructing slice contours, both triangular and rectangular patch approaches are applied to map and analyze the tumor surface and volume. The changes in tumor location are calculated based on a reference feature on the top of the spine canal. MATLAB routines are developed to perform the required calculations. A set of prototype mockups of different stages are used for the purpose of validation and verification of the proposed methodology.
Findings – The proposed method is applied to calculate volume, surface, and displacement of the tumor, using patients’ data obtained from the University of Texas-MD Anderson Cancer Center. The results are consistent with the actual data.
Originality/value – The proposed methodology increases the accuracy of treatment planning by predicting the changes in tumor geometry. The literature survey reveals that no work has been devoted to mathematically model the geometrical changes that a tumor might go through after each radiation.
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