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This variation was considered to represent intratumoral heterogeneity. These findings cannot be obtained from commonly-used geometric factor, i. , tumor volume or maximum diameter measured on CT images. 40 Applied Biological Engineering – Principles and Practice Fig. 9. Changes in 3D tumor geometries represented in surface geometry maps. 6 (mm) Fig. 10. Comparison of tumor geometries calculated in this method with actual tumor geometries using 2D surface geometry map (case A). 2 Fig. 11. Comparison of tumor geometries calculated in this method with actual tumor geometries using 2D surface geometry map (case B).
It was revealed that tumors shrunk uniformly keeping their initial morphological features during radiotherapy. This finding cannot be obtained from traditional evaluation by measuring diameters of the tumors on CT images. This study also proposed a novel simulation method to predict changes in 3D tumor geometries during radiotherapy considering intratumoral heterogeneity of radiosensitivity. The simulation results were found to conform to actual changes in tumor geometry. Although some difficulties still remain to be solved, tumor geometries could be predicted using our approach.
Changes in tumor volume and surface area are shown in Fig. 5 and 6. 7% of its initial volume in case A, 15% in Computer Simulation and Analysis of Three-Dimensional Tumor Geometry in Radiotherapy 37 case B, and 23% in case C. Changes in tumor surface area showed similar tendency with changes in tumor volume. Tumor surface areas at the end of the treatment were 20%, 28%, and 37% for case A, B, and C, respectively. Changes in SSF are shown in Fig. 7. 8 through the treatment duration and did not vary widely in all three cases.