Konstantinos P. Chatzipapas

Background Targeted radionuclide therapy (TRT) has emerged as a unique and effective treatment modality for cancer. Monte Carlo simulations have greatly advanced investigations into radiation-caused DNA damage, including the complexity of this damage. Purpose This study aimed to evaluate DNA damage induced by high-linear energy transfer therapeutic radionuclides used in TRT, specifically Ac-225, Lu-177, and Pb-212, using Geant4-DNA Monte Carlo simulations. Methods The Geant4-DNA toolkit, incorporating the molecularDNA example, was employed to simulate radiation interactions within a human fibroblast cell model featuring a fractal chromatin fiber geometry within an ellipsoidal nucleus. Three source geometries (membrane, cytoplasm, nucleus) were modeled to assess the impact of radionuclide localization. Key metrics, including absorbed dose, double-strand break (DSB) yield, single-strand break/DSB ratio, and DSB/Gbp/decay, were calculated for Ac-225 (alpha emitter), Lu-177 (beta emitter), and Pb-212 (mixed alpha/beta emitter). Simulations accounted for physical, physicochemical, and chemical stages, with validation against published data for Lu-177 and Ac-225. Results Alpha emitter Ac-225 exhibited the highest DSB/Gbp/decay (1.646 in nucleus geometry) and absorbed dose (0.256 Gy/decay), followed by Pb-212 (0.455 DSB/Gbp/decay, 0.0684 Gy/decay), and Lu-177 (0.0058 DSB/Gbp/decay, 0.0007 Gy/decay). DSB yields increased with proximity to the nucleus, with Ac-225 showing up to 284 times greater DSB/Gbp/decay than Lu-177. Validation showed < 10% divergence from reference studies. Conclusions Geant4-DNA simulations highlight the superior radiobiological effectiveness of alpha emitters, particularly Ac-225, for inducing DNA damage and emphasize the importance of source localization. These findings enhance our understanding of TRT’s radiobiological effects and can be used to support development of refined therapeutic strategies.

Background This study aimed to develop a novel human cell geometry for the Geant4-DNA simulation toolkit that explicitly incorporates all 23 chromosome pairs of the human cell. This approach contrasts with the existing, default human cell, geometrical model, which utilizes a continuous Hilbert curve. Methods A Python-based tool named “complexDNA” was developed to facilitate the design of both simple and complex DNA geometries. This tool was employed to construct a human cell geometry with individual pairs of chromosomes. Subsequently, the performance of this chromosomal model was compared to the standard human cell model provided in the “molecularDNA” Geant4-DNA example. Results Simulations using the new chromosomal model revealed minimal discrepancies in DNA damage yield and fragment size distribution compared to the default human cell model. Notably, the chromosomal model demonstrated significant computational efficiency, requiring approximately three times less simulation time to achieve equivalent results. Conclusions This work highlights the importance of incorporating chromosomal structure into human cell models for radiation biology research. The “complexDNA” tool offers a valuable resource for creating intricate DNA structures for future studies. Further refinements, such as implementing smaller voxels for euchromatin regions, are proposed to enhance the model’s accuracy.

The evolution of 3D printing has ushered in accessibility and cost-effectiveness, spanning various industries including biomedical engineering, education, and microfluidics. In biomedical engineering, it encompasses bioprinting tissues, producing prosthetics, porous metal orthopedic implants, and facilitating educational models. Hybrid Additive Manufacturing approaches and, more specifically, the integration of Fused Deposition Modeling (FDM) with bio-inkjet printing offers the advantages of improved accuracy, structural support, and controlled geometry, yet challenges persist in cell survival, interaction, and nutrient delivery within printed structures. The goal of this study was to develop and present a low-cost way to produce physical phantoms of human organs that could be used for research and training, bridging the gap between the use of highly detailed computational phantoms and real-life clinical applications. To this purpose, this study utilized anonymized clinical Computed Tomography (CT) data to create a liver physical model using the Creality Ender-3 printer. Polylactic Acid (PLA), Polyvinyl Alcohol (PVA), and light-bodied silicone (Polysiloxane) materials were employed for printing the liver including its veins and arteries. In brief, PLA was used to create a mold of a liver to be filled with biocompatible light-bodied silicone. Molds of the veins and arteries were printed using PVA and then inserted in the liver model to create empty channel. In addition, the PVA was then washed out by the final product using warm water. Despite minor imperfections due to the printer’s limitations, the final product imitates the computational model accurately enough. Precision adjustments in the design phase compensated for this variation. The proposed novel low-cost 3D printing methodology successfully produced an anatomically accurate liver physical model, presenting promising applications in medical education, research, and surgical planning. Notably, its implications extend to medical training, personalized medicine, and organ transplantation. The technology’s potential includes injection training for medical professionals, personalized anthropomorphic phantoms for radiation therapy, and the future prospect of creating functional living organs for organ transplantation, albeit requiring significant interdisciplinary collaboration and financial investment. This technique, while showcasing immense potential in biomedical applications, requires further advancements and interdisciplinary cooperation for its optimal utilization in revolutionizing medical science and benefiting patient healthcare.

Abstract Purpose The scientific community shows great interest in the study of DNA damage induction, DNA damage repair, and the biological effects on cells and cellular systems after exposure to ionizing radiation. Several in silico methods have been proposed so far to study these mechanisms using Monte Carlo simulations. This study outlines a Geant4-DNA example application, named “molecularDNA”, publicly released in the 11.1 version of Geant4 (December 2022). Methods It was developed for novice Geant4 users and requires only a basic understanding of scripting languages to get started. The example includes two different DNA-scale geometries of biological targets, namely “cylinders” and “human cell”. This public version is based on a previous prototype and includes new features, such as: the adoption of a new approach for the modeling of the chemical stage, the use of the standard DNA damage format to describe radiation-induced DNA damage, and upgraded computational tools to estimate DNA damage response. Results Simulation data in terms of single-strand break and double-strand break yields were produced using each of the available geometries. The results were compared with the literature, to validate the example, producing less than 5% difference in all cases. Conclusion: “molecularDNA” is a prototype tool that can be applied in a wide variety of radiobiology studies, providing the scientific community with an open-access base for DNA damage quantification calculations. New DNA and cell geometries for the “molecularDNA” example will be included in future versions of Geant4-DNA.