Medical physics

This study presents two significant investigations in the field of proton therapy, leveraging advanced Monte Carlo simulations to improve our understanding and modeling of proton beam characteristics and secondary particle dynamics. The first investigation centers on the development and validation of a Monte Carlo model tailored for the single-room Varian ProBeam pencil beam scanning system. The study begins with an in-depth simulation analysis to justify the selection of the "g4h-phy_QGSP_FTFP_BERT" physics list configuration for our TOPASSFPTI model, developed using the TOPAS 3.9 tool with a Geant4 base, version 10.07.p03. Comprehensive verification against clinical measurements in a water phantom demonstrated the accuracy of the model. A comparative analysis between the TOPASSFPTI model and a previously published TOPAS model for the Varian ProBeam system at Emory Proton Therapy Center (TOPASEmory) revealed distinct differences in the beam characteristics. Notably, the TOPASSFPTI model exhibited a closer alignment with the specific beam characterization at SFPTI, showing a strong consistency in beam energy spread (σE) and integrated depth dose distributions (IDDs), with a 98-100% agreement under 2%/2 mm γ-index criteria. Differences in lateral spot sizes were observed, with the TOPASSFPTI model showing slightly larger spot sizes compared to TOPASEmory, which aligns more closely with SFPTI’s clinical setup. Additionally, the calibration of absolute dose values indicated significant differences in the number of protons per monitor unit (MU) between the TOPASSFPTI and the clinical treatment planning system (TPS) data, with the TOPASSFPTI model consistently showing higher values.

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.

An algorithm to determine IMRT optimization parameters within the Elekta Monaco® treatment planning system that increases dose homogeneity and dose conformity in the planning target volume was developed. This algorithm determines IMRT optimization parameters by calculating the difference between two pairs of dose points along the target volume’s dose volume histogram: Dmax – Dmin, and D2 – D98. The algorithm was tested on the Elekta Monaco® Treatment Planning System at GenesisCare of Coconut Creek, Florida using CT data from 10 anonymized patients with non-small cell lung cancer of various tumor sizes and locations. Nine iterations of parameters were tested on each patient. Once the ideal parameters were found, the results were evaluated using the ICRU report 83 homogeneity index as well as the Paddick conformity index. As an outcome of this research, it is recommended that at least three iterations of IMRT optimization parameters should be calculated to find the ideal parameters.

The design and construction of a tri-cable, planar robotic device for use in neurophysical rehabilitation is presented. The criteria for this system are based primarily on marketability factors, rather than ideal models or mathematical outcomes. The device is designed to be low cost and sufficiently safe for a somewhat disabled individual to use unsupervised at home, as well as in a therapist's office. The key features are the use of a barrier that inhibits the user from coming into contact with the cables as well as a "break-away" joystick that the user utilizes to perform the rehabilitation tasks. In addition, this device is portable, aesthetically acceptable and easy to operate. Other uses of this system include sports therapy, virtual reality and teleoperation of remote devices.

The design and construction of a tri-cable, planar robotic device for use in neurophysical rehabilitation is presented. The criteria for this system are based primarily on marketability factors, rather than ideal models or mathematical outcomes. The device is designed to be low cost and sufficiently safe for a somewhat disabled individual to use unsupervised at home, as well as in a therapist's office. The key features are the use of a barrier that inhibits the user from coming into contact with the cables as well as a "break-away" joystick that the user utilizes to perform the rehabilitation tasks. In addition, this device is portable, aesthetically acceptable and easy to operate. Other uses of this system include sports therapy, virtual reality and teleoperation of remote devices.

Every scheduled treatment at a radiation therapy clinic involves a series of safety
protocol to ensure the utmost patient care. Despite safety protocol, on a rare occasion
an entirely preventable medical event, an accident, may occur. Delivering a treatment
plan to the wrong patient is preventable, yet still is a clinically documented error.
This research describes a computational method to identify patients with a novel
machine learning technique to combat misadministration.The patient identification
program stores face and fingerprint data for each patient. New, unlabeled data from
those patients are categorized according to the library. The categorization of data by
this face-fingerprint detector is accomplished with new machine learning algorithms
based on Sparse Modeling that have already begun transforming the foundation of
Computer Vision. Previous patient recognition software required special subroutines
for faces and di↵erent tailored subroutines for fingerprints. In this research, the same
exact model is used for both fingerprints and faces, without any additional subroutines
and even without adjusting the two hyperparameters. Sparse modeling is a powerful tool, already shown utility in the areas of super-resolution, denoising, inpainting,
demosaicing, and sub-nyquist sampling, i.e. compressed sensing. Sparse Modeling
is possible because natural images are inherrently sparse in some bases, due to their
inherrant structure. This research chooses datasets of face and fingerprint images to
test the patient identification model. The model stores the images of each dataset as
a basis (library). One image at a time is removed from the library, and is classified by
a sparse code in terms of the remaining library. The Locally Competetive Algorithm,
a truly neural inspired Artificial Neural Network, solves the computationally difficult
task of finding the sparse code for the test image. The components of the sparse
representation vector are summed by `1 pooling, and correct patient identification is
consistently achieved 100% over 1000 trials, when either the face data or fingerprint
data are implemented as a classification basis. The algorithm gets 100% classification
when faces and fingerprints are concatenated into multimodal datasets. This suggests
that 100% patient identification will be achievable in the clinal setting.

Patients receiving Intensity Modulated Radiation Therapy (IMRT) for late stage head and neck (HN) cancer often experience anatomical changes due to weight loss, tumor regression, and positional changes of normal anatomy (1). As a result, the actual dose delivered may vary from the original treatment plan. The purpose of this study was (a) to evaluate the dosimetric consequences of the parotid glands during the course of treatment, and (b) to determine if there would be an optimal timeframe for replanning. Nineteen locally advanced HN cancer patients underwent definitive IMRT. Each patient received an initial computerized tomography simulation (CT-SIM) scan and weekly cone beam computerized tomography (CBCT) scans. A Deformable Image Registration (DIR) was performed between the CT-SIM and CBCT of the parotid glands and Planning Target Volumes (PTVs) using the Eclipse treatment planning system (TPS) and the Velocity deformation software. A recalculation of the dose was performed on the weekly CBCTs using the original monitor units. The parameters for evaluation of our method were: the changes in volume of the PTVs and parotid glands, the dose coverage of the PTVs, the lateral displacement in the Center of Mass (COM), the mean dose, and Normal Tissue Complication Probability (NTCP) of the parotid glands. The studies showed a reduction of the volume in the PTVs and parotids, a medial displacement in COM, and alterations of the mean dose to the parotid glands as compared to the initial plans. Differences were observed for the dose volume coverage of the PTVs and NTCP of the parotid gland values between the initial plan and our proposed method utilizing deformable registration-based dose calculations.

Intracavitary high dose rate (HDR) brachytherapy is a form of radiation therapy generally in which a post-surgical tissue margin is treated. The dose gradient of HDR brachytherapy is very steep, and thus small displacements of the applicator, even as small as 1 mm, could potentially cause significant variations of dose which could result in undesired side effects such as overdose of a critical organ. In this retrospective dosimetric study, the variation of dose due to various small range motions of gynecological applicators is investigated. The results show that the implementation of additional immobilization and localization devices along with other safety measures needs to be further investigated.

Monte Carlo (MC) and Pencil Beam (PB) calculations are compared to their measured planar dose distributions using a 2-D diode array for lung Stereotactic Body Radiation Therapy (SBRT). The planar dose distributions were studied for two different phantom types: an in-house heterogeneous phantom and a homogeneous phantom. The motivation is to mimic the human anatomy during a lung SBRT treatment and incorporate heterogeneities into the pre-treatment Quality Assurance process, where measured and calculated planar dose distributions are compared before the radiation treatment. Individual and combined field dosimetry has been performed for both fixed gantry angle (anterior to posterior) and planned gantry angle delivery. A gamma analysis has been performed for all beam arrangements. The measurements were obtained using the 2-D diode array MapCHECK 2™.

Empirical methods of beam angle optimization (BAO) are tested against the BAO
that is currently employed in Eclipse treatment planning software. Creating an improved
BAO can decrease the amount of time a dosimetrist spends on making a treatment plan,
improve the treatment quality and enhance the tools an inexperienced dosimetrist can use
to develop planning techniques. Using empirical data created by experienced dosimetrists
from 69 patients treated for lung cancer, the most frequently used gantry angles were
applied to four different regions in each lung to gather an optimal set of fields that could
be used to treat future lung cancer patients. This method, given the moniker FAU BAO,
is compared in 7 plans created with the Eclipse BAO choosing 5 fields and 9 fields. The
results show that the conformality index improved by 30% or 3% when using the 5 and 9
fields. The conformation number was better by 12% from the 5 fields and 9% from the 9
fields. The organs at risk (OAR) were overall more protected to produce fewer
nonstochastic effects from the radiation treatment with the FAU BAO.