Optimizing Treatment Planning: Enhancing Precision in Radiotherapy Treatment through the Estimation of Hounsfield Unit Values from CT-Scan Data Calculation

Abstract

This study aims to increase precision in radiotherapy treatment planning by optimizing the estimated Hounsfield Unit (HU) value through calculating CT-scan data as a template. Radiotherapy is a therapy commonly used in the health sector to treat abnormal and uncontrolled growth of organism cells, such as lung cancer, brain tumors, leukemia and bone tumors. Radiotherapy utilizes gamma rays to eliminate abnormal cells through copying, taking into account appropriate radiation dose limits to minimize damage to normal tissue during the copying process. The level of absorption or radiodensity of a network can be expressed in Hounsfield Unit (HU) values. This simulation application design is supported by computer equipment with Intel i3 2 GHz processor specifications supported by 2 GB RAM (Random Access Memory), VGA (Video Graphics Adapter) 1 GB and 160GB hard disk. The device is used to determine the attenuation value (radiation absorption coefficient for each tissue) using the air attenuation value as a reference. The data processing method uses Green Foot software based on the multiplatform Java programming language. The program input is a CT-scan image with Grayscale analysis, and the output is Hounsfield values. The results of this study show that the use of CT-scan data and Hounsfield Unit (HU) calculations can increase the accuracy of radiotherapy planning. Using this technology, the radiation dose can be adjusted more effectively to the targeted area, while still minimizing the impact on surrounding healthy tissue. The integration of CT-scan and HU calculation in this study provides a strong basis for further development, with a focus on improving the precision and efficiency of radiotherapy.