Radiography and radiotherapy of the simulated human tissue environment with high-energy protons: A theoretical study

Stopping power, range, and time of proton in water, lung, bladder, and intestinal human tissues are calculated using density functional theory and Beth’s relativistic equation in range of proton energy (0.01–1,000 MeV). The experimental data extracted from SRIM-2013 program were used to proton to the same human tissues applied in the MATLAB-2021 program, and the mean ionization potential of water and the studied tissues is calculated using Gaussian 09W program. A good agreement has been found between our calculations for stopping power, range, and time of protons in the studied human body tissues and SRIM-2013 program calculations.

In this research, the stopping power and range of protons in biological human soft and hard tissues (blood, brain, skeleton-cortical bone, and skin) of both child and adult are calculated at the energies ranging from 1MeV to 350 MeV. The data is collected from ICRU Report 46 and calculated the stopping power employing the Bethe formula. Moreover, the simple integration (continuous slowing down approximation) method is employed for calculating protons range at the target. Then, the stopping power and range of protons value in human tissues have been compared with the program called SRIM. Moreover, the results of the stopping power vs energy and the range vs energy have been presented graphically. Proper agreement is found between the gained and the SRIM results and varies almost linearly with energy up to 250 MeV.

Energy deposition evaluation of monoenergetic proton beam along the depth in water phantom is an important technique in treatment planning to estimate the dose delivered to the tumor. Out of many, Monte Carlo is the most accurate technique being used to study the transport of nuclear radiation. In this paper, energy deposition in water due to high energy (E=175 MeV) protons has been carried out using the general purpose nuclear radiation transport computer code MCNPX. Furthermore, evaluation of stopping powers of protons in water has been performed by analytical methodology. A comparison of values of stopping powers based on MCNPX and analytical methodology has been presented. The work also includes verification of Bragg curve for therapeutic protons based on the Monte Carlo technique. Secondary neutrons, generated due to proton interactions with the medium, have been tracked and their contribution to the dose deposition, beyond the range of protons, has been considered. Energy bin concept has been used in computing the stopping power of protons to minimize the error. In addition, a comparison of the residual energy of protons as a function of depth with the analytical results found in the literature shows a good agreement except for some deviation near the range of protons.

Effect of scattering angle on energy loss radiography imaging for various proton energies relevant in proton therapy: A simulation study

In this work, the mass stopping power and range of protons in biological human body tissues (ovary, lung and breast) were calculated at the energy ranging from 0.04 MeV to 200 MeV using the MATLAB Program. The data relating to the densities, average atomic number to mass number and excitation energy for the present tissues were collected from ICRU Report 46. The mass stopping power was calculated by the Bethe formula. Moreover, the simple integration (continuous slowing down approximation) method was employed for calculating protons range at the tissues. The results of the mass stopping power versus energy and the range versus energy were presented graphically and the empirical formulae for calculating the mass stopping power and the ranges were obtained. The present results for mass stopping powers and ranges were compared with the results obtained by others. Good agreements were found between them, especially at the energy ranging from 3 to 200 MeV.

In this work, the electronic mass stopping power and the range of protons in some biological human body parts (Water, Muscle, Skeletal and Bone, Cortical) were calculated in the energy range of protons 0.04 to 200 MeV using the theory of Bethe-Bloch formula as giving in the references. All these calculations were done using Matlab program. The data related to the densities, average atomic number to mass number and excitation energies for the present tissues and substances were collected from ICRU Report 44 (1989). The present results for electronic mass stopping powers and ranges were compared with the data of PSTAR and good agreements were found between them, especially at energies between 1 - 200 MeV for stopping power and 4 - 200 MeV for the range. Also in this study, several important quantities in the field of radiation, such as thickness, linear energy transfer (LET), absorbed dose, equivalent dose, and effective dose of the protons in the given biological human body parts were calculated at protons energy 0.04 - 200 MeV.

Novel imaging modalities can improve the estimation of patient elemental compositions for particle treatment planning. The mean excitation energy (I-value) is a main contributor to the proton range uncertainty. To minimize their impact on beam range errors and quantify their uncertainties, the currently used I-values proposed in 1982 are revisited. The study aims at proposing a new set of optimized elemental I-values for use with the Bragg additivity rule (BAR) and establishing uncertainties on the optimized I-values and the BAR.We optimize elemental I-values for the use in compounds based on measured material I-values. We gain a new set of elemental I-values and corresponding uncertainties, based on the experimental uncertainties and our uncertainty model. We evaluate uncertainties on I-values and relative stopping powers (RSP) of 70 human tissues, taking into account statistical correlations between tissues and water. The effect of new I-values on proton beam ranges is quantified using Monte Carlo simulations.Our elemental I-values describe measured material I-values with higher accuracy than ICRU-recommended I-values (RMSE: 6.17% (ICRU), 5.19% (this work)). Our uncertainty model estimates an uncertainty component from the BAR to 4.42%. Using our elemental I-values, we calculate the I-value of water as 78.73 ± 2.89 eV, being consistent with ICRU 90 (78 ± 2 eV). We observe uncertainties on tissue I-values between 1.82-3.38 eV, and RSP uncertainties between 0.002%–0.44%. With transport simulations of a proton beam in human tissues, we observe range uncertainties between 0.31% and 0.47%, as compared to current estimates of 1.5%.We propose a set of elemental I-values well suited for human tissues in combination with the BAR. Our model establishes uncertainties on elemental I-values and the BAR, enabling to quantify uncertainties on tissue I-values, RSP as well as particle range. This work is particularly relevant for Monte Carlo simulations where the interaction probabilities are reconstructed from elemental compositions.

Proton therapy has become an established form of cancer treatment, but dose calculations and treatment planning are routinely performed based on X-ray computed tomography (XRCT), which requires a conversion to proton stopping power. A more appropriate method to directly measure stopping power and dose is proton computed tomography (pCT), where high-energy protons are measured after traversing completely through the patient. Proton radiographs and pCT have historically been limited by blurring due to multiple scattering. However, proton-by- proton track reconstruction techniques, measuring entry positions and exit positions and energies of each scanning proton, promise to greatly improve the spatial resolution of proton radiographs. We use simplified physical models of proton transport (including Bethe-Bloch energy loss, energy straggling, and multiple Coulomb scattering) in the 0-300 MeV energy range of interest to analytically quantify the tradeoffs and scaling between dose, spatial resolution, density resolution, and scanning voxel size. Monte Carlo results and comparisons to this scaling are generated with a small fast Monte Carlo code specifically written for proton transport and pCT (pint).

Many different approaches exist to calculate stopping power and range of protons and heavy charged particles. These methods may be broadly categorized as physically complete theories (widely applicable and complex) or semi-empirical approaches (narrowly applicable and simple). However, little attention has been paid in the literature to approaches that are both widely applicable and simple. We developed simple analytical models of stopping power and range for ions of hydrogen, carbon, iron, and uranium that spanned intervals of ion energy from 351 keV u−1 to 450 MeV u−1 or wider. The analytical models typically reproduced the best-available evaluated stopping powers within 1% and ranges within 0.1 mm. The computational speed of the analytical stopping power model was 28% faster than a full-theoretical approach. The calculation of range using the analytic range model was 945 times faster than a widely-used numerical integration technique. The results of this study revealed that the new, simple analytical models are accurate, fast, and broadly applicable. The new models require just 6 parameters to calculate stopping power and range for a given ion and absorber. The proposed model may be useful as an alternative to traditional approaches, especially in applications that demand fast computation speed, small memory footprint, and simplicity.

Introduction: Proton therapy delivers radiation to tumor tissue in a much more confined way than conventional photon therapy thus allowing the radiation oncologist to use a greater dose while still minimizing side. Materials and Methods: protons release most of their energy within the tumor region. As a result, the treating physician can potentially give an even greater dose to the tumor while minimizing unwanted side effects. This is especially important when treating children, because protons help reduce radiation to growing and developing tissues. In this work by Bethe formula using quantum mechanics we determine stooping power, mass stopping power and range of proton in substances of human body and compared our obtained results with available experimental data. Results: We calculated mean excitation energies, I using the quantum mechanical approach in muscle, bone, water, tissue. Our obtained results show that this parameter will change from 19 to 1000 eV. After that by Bethe formula using quantum mechanics with determining stooping power, mass stopping power and range of proton in ovary, breast, eye lens, lung, adipose, brain blood, bone, muscle and water we find that both of stopping and mass stopping power at first increases with enhancement of proton energy then decreases while, range of protons increases with increasing of proton energy. Conclusion: In this research, by Bethe formula using quantum mechanics the numerical values of stopping, mass stopping power and proton range in substances of human body are determined accurately and these obtained results help more accurately treat cancer patients using proton therapy.

Exploring the Potential of Breast Microbiota as Biomarker for Breast Cancer and Therapeutic Response

The role of proton therapy in radiation therapy is currently expanding. In the U.S., there are at present 11 clinical proton treatment facilities, with 10 centers operating proton gantries and 6 additional facilities under construction. One of the main challenges in proton therapy is the uncertainty in predicting proton range. Range uncertainties in proton therapy are related to ambiguity in converting x‐ray CT attenuation data to proton relative stopping power and are further compounded by organ deformation and internal motion as well as increasing relative biological effectiveness in the distal part of proton beams. Closely related to this issue is the continued development of image guidance technology in the treatment room that ideally will provide feedback for in‐room treatment plan modifications (adaptive proton therapy). Proton therapy treatment planning applies quite substantial range uncertainty margins, negating, in part, some of the advantages of the finite range. The problem of range uncertainty in proton therapy has been addressed in many ways, the ultimate goal being to reduce this uncertainty to ∼1 mm. Approaches to address this problem include Monte Carlo simulations to study the effects of different sources on proton range uncertainty, studies showing the amount of range uncertainties in patients, robust planning techniques, and various technological and calibration methods that attempt to improve the accuracy of relative proton stopping power and to detect and minimize range errors at the time of treatment, e.g., dual energy CT scanners, proton CT and radiography, prompt gamma registration and monitoring of proton radiation therapy with PET imaging. This symposium will present a broad overview of the current status of modern computational and imaging approaches to addressing the range‐uncertainty problem of proton beams in radiation therapy.Learning Objectives:1. Understand the prevailing range uncertainties in proton therapy and how they can affect clinical practice.2. Learn how the magnitude of range uncertainties has been studied with Monte Carlo simulations and in patients.3. Get an overview of new technologies addressing the range uncertainty problem in proton therapy.4. Learn about principles of proton computed tomography and radiography and how these techniques may be used for better range definition and pre‐treatment quality assurance.5. Learn about the use of prompt gamma emission for proton therapy range verification.6. Learn about the different implementations and initial clinical experience of PET verification of treatment delivery in proton and ion therapy.

Simple SummaryHuman breast tissue extracellular matrix (ECM) is a microenvironment essential for the survival and biological activities of mammary epithelial cells. The ECM structural features of human breast tissues remain poorly defined. In this study, we identified the structural and mechanical properties of human normal breast and invasive ductal carcinoma tissue ECM using histological methods and atomic force microscopy. Additionally, a protein hydrogel was generated using human breast tissue ECM and defined for its microstructural features using immunofluorescence imaging and machine learning. Furthermore, we examined the three-dimensional growth of normal mammary epithelial cells or breast cancer cells cultured on the ECM protein hydrogel, where the cells exhibited biological phenotypes like those seen in native breast tissues. Our data provide novel insights into cancer cell biology, tissue microenvironment mimicry and engineering, and native tissue ECM-based biomedical and pharmaceutical applications.Tissue extracellular matrix (ECM) is a structurally and compositionally unique microenvironment within which native cells can perform their natural biological activities. Cells grown on artificial substrata differ biologically and phenotypically from those grown within their native tissue microenvironment. Studies examining human tissue ECM structures and the biology of human tissue cells in their corresponding tissue ECM are lacking. Such investigations will improve our understanding about human pathophysiological conditions for better clinical care. We report here human normal breast tissue and invasive ductal carcinoma tissue ECM structural features. For the first time, a hydrogel was successfully fabricated using whole protein extracts of human normal breast ECM. Using immunofluorescence staining of type I collagen (Col I) and machine learning of its fibrous patterns in the polymerized human breast ECM hydrogel, we have defined the microstructural characteristics of the hydrogel and compared the microstructures with those of other native ECM hydrogels. Importantly, the ECM hydrogel supported 3D growth and cell-ECM interaction of both normal and cancerous mammary epithelial cells. This work represents further advancement toward full reconstitution of the human breast tissue microenvironment, an accomplishment that will accelerate the use of human pathophysiological tissue-derived matrices for individualized biomedical research and therapeutic development.

Laser-accelerated proton beam for fast ignition considering formation factor of a cloud and penetrability in P11B reaction

Determination of WER and WET equivalence estimators for proton beams in the therapeutic energy range using MCNP6.1 and TOPAS codes