## 4 Discussion
Lower-energy X-rays (50-60 keV) are absorbed more by tissues, leading to higher energy deposition and greater biological risks, making careful dose management essential in medical applications. In contrast, higher-energy X-rays (>60 keV) pass through tissues more easily, reducing the risk of harm. This study's energy range of 50-100 keV highlights the varying safety concerns across different energy levels [11; 12; 13; 14]. Proper selection of energy levels is crucial for minimizing risks in imaging and radiotherapy. Simulation toolslike PHITS, SRIM, GEANT4, MCNPX, and FLUKA provide accurate predictions of X-ray interactions and are invaluable for improving safety and efficacy in medical applications, particularly when experimental studies are challenging or costly [19; 20; 21; 22]. The differences between real tissues and tissue-equivalent materials can reduce the reliability of simulations and affect the accuracy of dose calculations in clinical applications [34; 50; 51]. This study provides important findings by comparing the X-ray absorption behavior of mandibular tissues using both real tissues and tissue-equivalent materials. Tissue-equivalent materials, especially at low energy levels, tend to absorb fewer X-rays compared to real tissues. raising concerns about the accuracy of these materials [52; 53]. There is a need to develop more accurate and precise tissue-equivalent materials to ensure that simulations used for dose calculations in medical imaging and radiation therapy are reliable. The current tissue-equivalent materials, especially for soft and muscle tissues, are insufficient, and this represents an area of focus for future research [31; 52; 54]. Numerous studies in the literature have explored X-ray dose estimations using Monte Carlo simulations, including tools like PHITS, GEANT4, and MCNPX [55; 56; 57; 58]. These simulation systems are well-established in their ability to model complex particle interactions and are frequently used to estimate radiation absorption in biological tissues. For example, using GEANT4 to simulate X-ray interactions in soft tissues provides highly accurate predictions of the absorbed dose and emphasizes the importance of precise tissue modeling in radiation therapy [59]. Similarly, using MCNPX to study radiation dose distribution in bone tissues demonstrates the tool's capability to reflect real-world clinical settings through accurate simulation results [60]. These works underline the critical role Monte Carlo simulations play in radiation dosimetry, as they allow for highly detailed, three-dimensional modeling of tissue interactions with radiation, something that is often difficult to achieve through experimental means alone [55; 56; 57; 58; 59; 60]. The value of Monte Carlo-based studies lies in their ability to model various physical processes, such as photoelectric absorption, Compton scattering, and pair production, depending on the energy range of the X-rays [55; 56; 57; 58; 59]. For example, PHITS simulations closely matched experimental data when modeling the interaction of high-energy X-rays with different tissue types, providing insights into how dose distribution varies across different anatomical regions [61]. Furthermore, a comparative study between MCNPX and experimental results in dental tissues confirmed the reliability of the Monte Carlo methods in predicting X-ray absorption patterns and potential risks to sensitive areas such as the mandible [62].