Department of Physics

The Winston-Lutz has been the standard test for isocenter convergence, however, any adjustments needed – in case the test fails – are time consuming since the source of error is not readily available from the results. Isopoint by the Aktina Medical company has been developed to address this problem via decoupling the mechanical from the radiation isocenter and providing the user with information that was inaccessible before. The focus of this research is to perform optimization of the isocenter by using the Isopoint and to confirm the validity of its results, as well as to find how much time is saved via this new technology. The data for this project was collected on a 2012 Elekta Synergy, a Varian 21ix, and a 2021 Elekta Versa through partnership with GenesisCare. Our findings indicate that the Isopoint will allow for more accurate and speedy adjustments of the LINAC (Linear Accelerator) and will be integral in the future of this
field.

The study of the electrical properties of red blood cells (RBCs) plays a crucial role in advancing our understanding of human health. As RBCs age, they undergo changes that affect hemorheology and blood microcirculation, which have far-reaching implications for disease research. Furthermore, the shortage of RBC storage units can be a major issue for patients, underscoring the importance of characterizing RBC aging with respect to cell densities. In individuals with abnormal hemoglobin disease, alterations in hemoglobin and its functionality can modify the volume and density of RBCs, making their study even more crucial. To this end, our aim is to investigate the impedance alterations of RBCs after distributing them into different layers based on their densities. We have developed a novel method for non-invasive, rapid, and real-time single-cell analysis of RBCs. Our approach involves the use of electrical impedance spectroscopy (EIS) to study the cells after performing cell fractionation. Our studies indicate an increasing trend for RBC resistance and a decreasing trend for the cell membrane as the density of the layer increases. Additionally, we have developed a method for extracting hemoglobin with high purity from fresh samples of RBCs. By passing lysed RBCs through ultrafiltration devices and removing debris and membranes, we were able to isolate hemoglobin. Using the EIS technique, we studied the alterations of impedance over a frequency range, obtaining valuable insight into the electrical properties of hemoglobin.

Core-Collapse Supernovae (CCSNe) are some of the most powerful events in the universe liberating an astonishing 3×1053 ergs of the gravitational binding energy released by the collapse of the stellar core to a nascent neutron star (PNS) that is formed in these events. The visible display is capable of outshining the entire galaxy where it inhabits. Most of this energy, ~ 99%, is carried away by neutrinos of all flavors, however.
According to the favored theory of CCSNe, the production and transport of neutrinos from the dense core through the less dense mantle is believed to deposit energy in the mantle and thereby initiate the supernova explosion. Numerically modeling these events realistically to validate the model therefore requires an accurate neutrino transport algorithm coupled to sophisticated neutrino microphysics to compute the emission, transport, and energy deposition of neutrinos.
The CHIMERA code is a radiation-hydrodynamics code that has been developed to numerically model CCSNe in multiple spatial dimensions. The neutrino transport algorithm currently incorporated in CHIMERA is based upon the Multigroup Flux-Limited Diffusion (MGFLD) method. This current method basically uses only the zeroth angular moment of the Boltzmann equation and closes the system with terms dropped from the first angular moment to produce a diffusion-like equation. A flux-limiter is added to interpolate between the diffusive and free-streaming regimes, and to prevent the algorithm from computing acausal, i.e., faster than light transport, in regions where the neutrino mean free paths are large.

We examine how best to associate quantum states of a single particle to modes of a narrowly collimated beam of classical radiation modeled in the paraxial approximation, both for scalar particles and for photons. Our analysis stresses the importance of the relationship between the inner product used to define orthogonal modes of the paraxial beam, on the one hand, and the inner product underlying the statistical interpretation of the quantum theory, on the other. While several candidates for such an association have been proposed in the literature, we argue that one of them is uniquely well suited to the task. Specifically, the mapping from beam modes to ”henochromatic” fields on spacetime is unique within a large class of similar mappings in that it is unitary in a mathematically precise sense. We also show that the single-particle quantum states associated to the orthogonal modes of a classical beam in the henochromatic approach are not only orthogonal, but also complete in the quantum Hilbert space.

Proton Therapy, an effective cancer treatment, poses unintended consequences for patients and personnel due to secondary neutron production. This study investigates neutron attenuation in shielding materials like concrete using Monte Carlo (MC) simulations to optimize shielding requirements. Experimental limitations, such as detector sensitivity, energy range response, and spatial resolution, lead to inaccurate evaluations. MC simulations address that by modeling radiation transport and neutron interactions with shielding materials.
The TOPAS-MC code simulated secondary neutrons generated by a 226.5 MeV energy proton beam on a 30 cm diameter tissue-equivalent target. The target was placed in a 200 cm spherical concrete shell with a 100 cm inner radius and 2.3 g/cm3 density. Energy deposition and particle fluence were scored in 20 radial points across 18 angular positions, and the mean value per particle was estimated. Neutron fluence to ambient dose equivalent conversion coefficients from ICRU Report No. 95 were used to calculate the total dose equivalent values, which were scaled based on distance and concrete shield thickness.

With the advent of newly and more reliably designed targeted therapy methods in the past several years, targeted radionuclide therapy has attracted more attentions around the world as a more reliable treatment modality in combination with other well established traditional cancer treatments i.e., external beam radiotherapy and chemotherapy. Alpha particles have a high relative biological effectiveness (RBE) due to their high linear energy transfer (LET). However, to utilize them for therapeutic purposes, precise human body dosimetry calculation is required. The measurement of their uptake and biodistribution can be quite challenging. Also, due to the complex biology of different types of cells, their shapes and functions, there is not a simple and clear understanding of the mechanism of action that fits all. This study aims to estimate and compare the human organ dosimetry of the alpha emitter, 212Pb, from animal data assuming that it is conjugated with three different types of commonly used targeting nanoparticles. For this purpose, the pre-published animal data of three different radionuclide labeled peptide, antibody, and small molecule carriers were selected and converted to human data. Then a compartmental model was designed for each of them to fit the model to the human data with 212Pb, half-life of 10.64 hours. Once each model reached the desired fit, the area under the curves were extracted then the estimated human organ dosimetry calculations took place via the MIRD scheme. The organ dosimetry results for 212Pb + three different carriers are presented in Tables 14, 17, and 20.

Hepatocellular carcinoma is currently one of the most fatal cancers in the world. The routine treatment for this type of cancer consists of surgery, chemotherapy, and finally radiation therapy. Recent advancements in technology have enabled us to deliver highly conformed dose to planning target volume. Two of these methods are Intensity modulated Radiation Therapy (IMRT) and Stereotactic Body Radiation Therapy (SBRT). The difference between these two methods is that in the SBRT high radiation dose per fraction is delivered, but smaller number of fractions which renders better tumor control probability. However, better tumor control comes at the price of complications and radiation induced liver damage.
In this work, we compare the outcome of radiation with regards to the probability of radiation damage to the liver after IMRT and SBRT. For this purpose, we analyzed 10 anonymized patients’ data with liver cancer, and we made two similar treatment plans for them. The difference in two plans is dose per fraction and total dose. After optimizing the treatments and calculating the dose volume histogram, we found the effective volume of the liver being irradiated. Finally, this effective volume and the corresponding dose were used to show that SBRT has the advantage of better tumor control probability at the cost of higher probability of complications.

In radiotherapy, radiobiological indices tumor control probability (TCP), normal tissue complication probability (NTCP), and equivalent uniform dose (EUD) are computed by analytical models. These models are rarely employed to rank and optimize treatment plans even though radiobiological indices weights more compared to dosimetric indices to reflect treatment goal. The objective of this study is to predict TCP, NTCP and EUDs for lung cancer radiotherapy treatment plans using an artificial neural network (ANN). A total of 100 lung cancer patients’ treatment plans were selected for this study. Normal tissue complication probability (NTCP) of organs at risk (OARs) i.e., esophagus, spinal cord, heart and contralateral lung and tumor control probability (TCP) of treatment target volume (i.e., tumor) were calculated by the equivalent uniform dose (EUD) model. TCP/NTCP pairing with corresponding EUD are used individually as outputs for the neural network. The inputs for ANN are planning target volume (PTV), treatment modality, tumor location, prescribed dose, number of fractions, mean dose to PTV, gender, age, and mean doses to the OARs. The ANN is based on Levenberg-Marquardt algorithm with one hidden layer having 13 inputs and 2 outputs. 70% of the data was used for training, 15% for validation and 15% for testing the ANN. Our ANN model predicted TCP and EUD with correlation coefficient of 0.99 for training, 0.96 for validation, and 0.94 for testing. In NTCP and EUD prediction, averages of correlation coefficients are 0.94 for training, 0.89 for validation and 0.84 for testing. The maximum mean squared error (MSE) for the ANN is 0.025 in predicting the NTCP and EUD of heart. Our results show that an ANN model can be used with high discriminatory power to predict the radiobiological indices for lung cancer treatment plans.

In this effort, we present progress toward demonstrating a Decoy-State Quantum Key Distribution (QKD) source based on a polarization-modulator and a wavelength-stable attenuated pulsed laser. A three-state QKD protocol is achieved by preparing particular quantum polarization states. The polarization-modulator-based QKD source improves security by removing several sources of side-channel attacks that exist when multiple sources are used to generate different QKD states. Here we present a QKD source design and an evaluation of critical subsystems characterized by the Quantum Bit Error Rate, Quantum State tomography, and achievable Key Rates. The QKD source is intended to operate within compact Size, Weight, and Power constraints. The Polarization-Modulator QKD source has applications in future mobile quantum networks such as Unmanned-Aerial Vehicles (UAV) and autonomous vehicles, as well as fixed fiber-based quantum networks.
Quantum mechanics can produce correlations that are stronger than classically allowed. This stronger-than-the-classical correlation is the “fuel” for quantum computing. In 1991 Schumacher forwarded a beautiful geometric approach, analogous to the well-known result of Bell, to capture the non-classicality of this correlation for a singlet state. He used well-established information distance defined on an ensemble of identically–prepared states. He calculated that for certain detector settings used to measure the entangled state, the resulting geometry violated a triangle inequality —a violation that is not possible classically. This provided novel information–based on geometric Bell inequality in terms of a “covariance distance.” Here we experimentally reproduce his construction and demonstrate a definitive violation for a Bell state of two photons based on the usual spontaneous parametric down-conversion in a paired BBO crystal. The state we produced had visibility of Vad = 0.970}0.012. We discuss generalizations to higher dimensional multipartite quantum states.

The ultimate challenge for assisted reproductive technologies (ARTs) is to select the most competent sperm population from a semen sample in an efficient way. In this thesis, we report on an effective sperm sorting microfluidic device that exploits the rheotaxis of sperm and investigates the sperm quality sorted under various flow conditions. Rheotaxis is the ability of a sperm cell to orient itself in the direction of the flow and swim against it. We developed a novel passively driven pumping system that provides a steady flow rate while it requires no external power source. We have also developed another rheotaxis-based microfluidic device that washes out the raw semen sample from any dead or less motile sperm. The device consists of a collection and waste chamber. To evaluate the effect of the shape and height of the collection chamber, we measured the sperm motility and velocity parameters after sorting using varying the shape and height of the collection chamber. We demonstrated that sperm selected with all devices have higher motility, normal morphology, and a fewer degree of DNA fragmentation compared to a control group.