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High School Student with a Traditionally Underrepresented Background

HS Poster

Poster 100 - Investigation of Hafnium-Based Nanoparticles for Optimal Radiosensitization using pyPENELOPE

Saturday, October 26, 2024
10:00 AM - 12:00 PM EST
Location: Exhibit Hall E, F & G

    Presenting Author(s)

  • RK

    Rohan Kakaria (he/him/his)

    Student Researcher
    Pennsylvania State University, Department of Materials Science and Engineering
    Mechanicsburg, Pennsylvania, United States

    • Co-Author(s)

  • DS

    David Skrodzki, n/a

    Graduate Student
    Pennsylvania State University
    State College, Pennsylvania, United States

  • Vikram Kakaria

    Undergraduate Student
    Princeton University
    Mechanicsburg, Pennsylvania, United States

    • Last Author(s)

  • DP

    Dipanjan Pan

    Chair Professor
    Penn State, United States


Introduction: Radiotherapy utilizes ionizing radiation to destroy tumor cells, making it a commonly used modality to treat malignancy or cancer. As opposed to chemotherapy, radiotherapy is more localized, precise, and allows for radiation to be delivered to deep tissue. However, it can harm surrounding healthy tissue. There has been emerging interest in the use of high-atomic number (Z) nanoparticles to deliver radiation therapy while preserving healthy surrounding tissue during cancer treatment. Specifically, hafnium-based nanoparticles have the potential to maximize apoptosis of cancer cells. Hafnium compounds, such as hafnium oxide, exhibit a high degree of chemical stability and therefore minimize damage in tumor-adjacent normal tissue. Currently, hafnium oxide is the only clinically studied high-Z radiosensitizing nanoparticle. Further research is ongoing for other hafnium-based compounds, such as hafnium sulfide. The goal of this study was to investigate which hafnium-based nanoparticles can be utilized with high absorption into target cells with the fewest adverse effects using a computational model.

Materials and

Methods: In this study, we used the software pyPENELOPE to simulate fractions of primary electrons that were backscattered and absorbed, secondary particle generation probabilities, and the average energy deposited within each body of the sample. For the purposes of this study, we tested hafnium oxide (HfO2), hafnium sulfide (HfS2), hafnium-doped magnetite (Hf0.6Fe2.4O4), hafnium chloride (HfCl4), and hafnium fluoride (HfF4). We conducted a literary search, and these were some of the most commonly found hafnium-based nanoparticles. After the simulations, we plotted and analyzed the fractions of primary electrons that were backscattered and absorbed for these compounds.

Results, Conclusions, and Discussions: By utilizing the software pyPENELOPE, we demonstrated that Hf0.6Fe2.4O4 was the most effective nanoparticle, as it absorbed the most electrons and had the least backscattering when compared to other nanoparticles, as shown in Figure 1. HfCl4 and HfF4 had similar values for electrons absorbed and backscattering, as did HfS2 and HfO2. This is consistent with the idea that elements in the same group have similar chemical properties. As can be seen from Figure 1, there appears to be an inverse relationship between electrons absorbed and backscattering. HfO2, despite being the only clinically studied high-Z radiosensitizing nanoparticle, absorbed the least amount of electrons and had the most backscattering. Thus far, studies have shown that hafnium-based nanoparticles are not physically or chemically reactive in biologic systems until radiation is administered, therefore making them ideal tools for cancer treatment. The data from our study shows that it is possible for other hafnium-based nanoparticles, specifically Hf0.6Fe2.4O4, to be very effective as potential radiosensitizers.

We have provided computational support regarding the use of several hafnium-based high-Z radiosensitizing nanoparticles which can be effectively utilized to optimize the delivery of radiotherapy to cancer cells. pyPenelope helped us compare properties of different hafnium-based nanoparticles, which may be most suitable for optimal radiosensitization. Although Hf0.6Fe2.4O4 may be the most promising compound for radiosensitization, further research is necessary to confirm these results experimentally.

Acknowledgements (Optional):

References (Optional): Welcome — pyPENELOPE. https://pypenelope.sourceforge.net/index.html (accessed 2024- 06-14).
Skrodzki, D.; Molinaro, M.; Brown, R.; Moitra, P.; Pan, D. Synthesis and Bioapplication of Emerging Nanomaterials of Hafnium. ACS Nano 2024. https://doi.org/10.1021/acsnano.3c08917.
Zhou W, Liu Z, Wang N, Chen X, Sun X, Cheng Y. Hafnium-Based Metal-Organic Framework Nanoparticles as a Radiosensitizer to Improve Radiotherapy Efficacy in Esophageal Cancer. ACS Omega. 2022 Mar 30;7(14):12021-12029. doi: 10.1021/acsomega.2c00223. PMID: 35449918; PMCID: PMC9016869.