Development of advanced geometric models and acceleration techniques for Monte Carlo simulation in Medical Physics

Els programes de simulació Monte Carlo de caràcter general s'utilitzen actualment en una gran varietat d'aplicacions.Tot i això, els models geomètrics implementats en la majoria de programes imposen certes limitacions a la forma dels objectes que es poden definir. Aquests models no són adequats per descriure les superfícies arbitràries que es troben en estructures anatòmiques o en certs aparells mèdics i, conseqüentment, algunes aplicacions que requereixen l'ús de models geomètrics molt detallats no poden ser acuradament estudiades amb aquests programes.L'objectiu d'aquesta tesi doctoral és el desenvolupament de models geomètrics i computacionals que facilitin la descripció dels objectes complexes que es troben en aplicacions de física mèdica. Concretament, dos nous programes de simulació Monte Carlo basats en PENELOPE han sigut desenvolupats. El primer programa, penEasy, utilitza un algoritme de caràcter general estructurat i inclou diversos models de fonts de radiació i detectors que permeten simular fàcilment un gran nombre d'aplicacions. Les noves rutines geomètriques utilitzades per aquest programa, penVox, extenen el model geomètric estàndard de PENELOPE, basat en superfícices quàdriques, per permetre la utilització d'objectes voxelitzats. Aquests objectes poden ser creats utilitzant la informació anatòmica obtinguda amb una tomografia computeritzada i, per tant, aquest model geomètric és útil per simular aplicacions que requereixen l'ús de l'anatomia de pacients reals (per exemple, la planificació radioterapèutica). El segon programa, penMesh, utilitza malles de triangles per definir la forma dels objectes simulats. Aquesta tècnica, que s'utilitza freqüentment en el camp del disseny per ordinador, permet representar superfícies arbitràries i és útil per simulacions que requereixen un gran detall en la descripció de la geometria, com per exemple l'obtenció d'imatges de raig x del cos humà.Per reduir els inconvenients causats pels llargs temps d'execució, els algoritmes implementats en els nous programes s'han accelerat utilitzant tècniques sofisticades, com per exemple una estructura octree. També s'ha desenvolupat un paquet de programari per a la paral·lelització de simulacions Monte Carlo, anomentat clonEasy, que redueix el temps real de càlcul de forma proporcional al nombre de processadors que s'utilitzen.Els programes de simulació que es presenten en aquesta tesi són gratuïts i de codi lliures. Aquests programes s'han provat en aplicacions realistes de física mèdica i s'han comparat amb altres programes i amb mesures experimentals.Per tant, actualment ja estan llestos per la seva distribució pública i per la seva aplicació a problemes reals.Monte Carlo simulation of radiation transport is currently applied in a large variety of areas. However, the geometric models implemented in most general-purpose codes impose limitations on the shape of the objects that can be defined. These models are not well suited to represent the free-form (i.e., arbitrary) shapes found in anatomic structures or complex medical devices. As a result, some clinical applications that require the use of highly detailed phantoms can not be properly addressed.This thesis is devoted to the development of advanced geometric models and accelration techniques that facilitate the use of state-of-the-art Monte Carlo simulation in medical physics applications involving detailed anatomical phantoms. To this end, two new codes, based on the PENELOPE package, have been developed. The first code, penEasy, implements a modular, general-purpose main program and provides various source models and tallies that can be readily used to simulate a wide spectrum of problems. Its associated geometry routines, penVox, extend the standard PENELOPE geometry, based on quadric surfaces, to allow the definition of voxelised phantoms. This kind of phantoms can be generated using the information provided by a computed tomography and, therefore, penVox is convenient for simulating problems that require the use of the anatomy of real patients (e.g., radiotherapy treatment planning). The second code, penMesh, utilises closed triangle meshes to define the boundary of each simulated object. This approach, which is frequently used in computer graphics and computer-aided design, makes it possible to represent arbitrary surfaces and it is suitable for simulations requiring a high anatomical detail (e.g., medical imaging).A set of software tools for the parallelisation of Monte Carlo simulations, clonEasy, has also been developed. These tools can reduce the simulation time by a factor that is roughly proportional to the number of processors available and, therefore, facilitate the study of complex settings that may require unaffordable execution times in a sequential simulation.The computer codes presented in this thesis have been tested in realistic medical physics applications and compared with other Monte Carlo codes and experimental data. Therefore, these codes are ready to be publicly distributed as free and open software and applied to real-life problems.Postprint (published version

Energy Deposition in the Breast During CT Scanning: Quantification and Implications for Dose Reduction

Studies suggest that dose to the breast leads to a higher lifetime attributable cancer incidence risk from a chest CT scan for women compared to men. Numerous methods have been proposed for reducing dose to the breast during CT scanning, including bismuth shielding, tube current modulation, partial-angular scanning, and reduced kVp. These methods differ in how they alter the spectrum and fluence across projection angle. This study used Monte Carlo CT simulations of a voxelized female phantom to investigate the energy (dose) deposition in the breast as a function of both photon energy and projection angle. The resulting dose deposition matrix was then used to investigate several questions regarding dose reduction to the breast: (1) Which photon energies deposit the most dose in the breast, (2) How does increased filtration compare to tube current reduction in reducing breast dose, and (3) Do reduced kVp scans reduce dose to breast, and if so, by what mechanism? The results demonstrate that while high-energy photons deposit more dose per emitted photon, the low-energy photons deposit more dose to the breast for a 120 kVp acquisition. The results also demonstrate that decreasing the tube current for the AP views to match the fluence exiting a shield deposits nearly the same dose to the breast as when using a shield (within ~1%). Finally, results suggest that the dose reduction observed during lower kVp scans is caused by reduced photon fluence rather than the elimination of high-energy photons from the beam. Overall, understanding the mechanisms of dose deposition in the breast as a function of photon energy and projection angle enables comparisons of dose reduction methods and facilitates further development of optimized dose reduction schemes

A Database for Estimating Organ Dose for Chest and Head CT Scans for Arbitrary Spectra and Angular Tube Current Modulation

Purpose: The purpose of this study was to develop a database for estimating organ dose in a voxelized patient model for coronary angiography and brain perfusion CT acquisitions with any spectra and angular tube current modulation setting. The database enables organ dose estimation for existing and novel acquisition techniques without requiring Monte Carlo simulations. Methods: The study simulated transport of monoenergetic photons between 5 and 150 keV for 1000 projections over 360◦ through anthropomorphic voxelized female chest and head (0◦ and 30◦ tilt) phantoms and standard head and body CTDI dosimetry cylinders. The simulations resulted in tables of normalized dose deposition for several radiosensitive organs quantifying the organ dose per emitted photon for each incident photon energy and projection angle for coronary angiography and brain perfusion acquisitions. The values in a table can be multiplied by an incident spectrum and number of photons at each projection angle and then summed across all energies and angles to estimate total organ dose. Scanner-specific organ dose may be approximated by normalizing the database-estimated organ dose by the database-estimated CTDIvol and multiplying by a physical CTDIvol measurement. Two examples are provided demonstrating how to use the tables to estimate relative organ dose. In the first, the change in breast and lung dose during coronary angiography CT scans is calculated for reduced kVp, angular tube current modulation, and partial angle scanning protocols relative to a reference protocol. In the second example, the change in dose to the eye lens is calculated for a brain perfusion CT acquisition in which the gantry is tilted 30◦ relative to a nontilted scan. Results: Our database provides tables of normalized dose deposition for several radiosensitive organs irradiated during coronary angiography and brain perfusion CT scans. Validation results indicate total organ doses calculated using our database are within 1% of those calculated using Monte Carlo simulations with the same geometry and scan parameters for all organs except red bone marrow (within 6%), and within 23% of published estimates for different voxelized phantoms. Results from the example of using the database to estimate organ dose for coronary angiography CT acquisitions show 2.1%, 1.1%, and −32% change in breast dose and 2.1%, −0.74%, and 4.7% change in lung dose for reduced kVp, tube current modulated, and partial angle protocols, respectively, relative to the reference protocol. Results show −19.2% difference in dose to eye lens for a tilted scan relative to a nontilted scan. The reported relative changes in organ doses are presented without quantification of image quality and are for the sole purpose of demonstrating the use of the proposed database. Conclusions: The proposed database and calculation method enable the estimation of organ dose for coronary angiography and brain perfusion CT scans utilizing any spectral shape and angular tube current modulation scheme by taking advantage of the precalculated Monte Carlo simulation results. The database can be used in conjunction with image quality studies to develop optimized acquisition techniques and may be particularly beneficial for optimizing dual kVp acquisitions for which numerous kV, mA, and filtration combinations may be investigated. © 2012 American Association of Physicists in Medicine

Reducing Radiation Dose to the Female Breast during CT Coronary Angiography: A Simulation Study Comparing Breast Shielding, Angular Tube Current Modulation, Reduced kV, and Partial Angle Protocols Using an Unknown-location Signal-detectability Metric

Purpose: The authors compared the performance of five protocols intended to reduce dose to the breast during computed tomography (CT) coronary angiography scans using a model observer unknown-location signal-detectability metric. Methods: The authors simulated CT images of an anthropomorphic female thorax phantom for a 120 kV reference protocol and five “dose reduction” protocols intended to reduce dose to the breast: 120 kV partial angle (posteriorly centered), 120 kV tube-current modulated (TCM), 120 kV with shielded breasts, 80 kV, and 80 kV partial angle (posteriorly centered). Two image quality tasks were investigated: the detection and localization of 4-mm, 3.25 mg/ml and 1-mm, 6.0 mg/ml iodine contrast signals randomly located in the heart region. For each protocol, the authors plotted the signal detectability, as quantified by the area under the exponentially transformed free response characteristic curve estimator (AˆFE), as well as noise and contrast-to-noise ratio (CNR) versus breast and lung dose. In addition, the authors quantified each protocol\u27s dose performance as the percent difference in dose relative to the reference protocol achieved while maintaining equivalentAˆFE. Results: For the 4-mm signal-size task, the 80 kV full scan and 80 kV partial angle protocols decreased dose to the breast (80.5% and 85.3%, respectively) and lung (80.5% and 76.7%, respectively) withAˆFE= 0.96, but also resulted in an approximate three-fold increase in image noise. The 120 kV partial protocol reduced dose to the breast (17.6%) at the expense of increased lung dose (25.3%). The TCM algorithm decreased dose to the breast (6.0%) and lung (10.4%). Breast shielding increased breast dose (67.8%) and lung dose (103.4%). The 80 kV and 80 kV partial protocols demonstrated greater dose reductions for the 4-mm task than for the 1-mm task, and the shielded protocol showed a larger increase in dose for the 4-mm task than for the 1-mm task. In general, the CNR curves indicate a similar relative ranking of protocol performance as the correspondingAˆFEcurves, however, the CNR metric overestimated the performance of the shielded protocol for both tasks, leading to corresponding underestimates in the relative dose increases compared to those obtained when using theAˆFEmetric. Conclusions: The 80 kV and 80 kV partial angle protocols demonstrated the greatest reduction to breast and lung dose, however, the subsequent increase in image noise may be deemed clinically unacceptable. Tube output for these protocols can be adjusted to achieve a more desirable noise level with lesser breast dose savings. Breast shielding increased breast and lung dose when maintaining equivalentAˆFE. The results demonstrated that comparisons of dose performance depend on both the image quality metric and the specific task, and that CNR may not be a reliable metric of signal detectability

Using convolutional neural networks to discriminate between cysts and masses in Monte Carlo-simulated dual-energy mammography

Purpose: A substantial percentage of recalls (up to 20%) in screening mammography is attributed to extended round lesions. Benign fluid-filled breast cysts often appear similar to solid tumors in conventional mammograms. Spectral imaging (dual-energy or photon-counting mammography) has been shown to discriminate between cysts and solid masses with clinically acceptable accuracy. This work explores the feasibility of using convolutional neural networks (CNNs) for this task. Methods: A series of Monte Carlo experiments was conducted with digital breast phantoms and embedded synthetic lesions to produce realistic dual-energy images of both lesion types. We considered such factors as nonuniform anthropomorphic background, size of the mass, breast compression thickness, and variability in lesion x-ray attenuation. These data then were used to train a deep neural network (ResNet-18) to learn the differences in x-ray attenuation of cysts and masses. Results: Our simulation results showed that the CNN-based classifier could reliably discriminate between cystic and solid mass round lesions in dual-energy images with an area under the receiver operating characteristic curve (ROC AUC) of 0.98 or greater. Conclusions: The proposed approach showed promising performance and ease of implementation, and could be applied to novel photon-counting detector-based spectral mammography systems. © 2021 American Association of Physicists in Medicine. This article has been contributed to by US Government employees and their work is in the public domain in the USA.Public domain articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

PenMesh-Monte Carlo radiation transport simulation in a triangle mesh geometry

We have developed a general-purpose Monte Carlo simulation code, called penMesh, that combines the accuracy of the radiation transport physics subroutines from PENELOPE and the flexibility of a geometry based on triangle meshes. While the geometric models implemented in most general-purpose codes-such as PENELOPE's quadric geometry-impose some limitations in the shape of the objects that can be simulated, triangle meshes can be used to describe any free-form (arbitrary) object. Triangle meshes are extensively used in computer-aided design and computer graphics. We took advantage of the sophisticated tools already developed in these fields, such as an octree structure and an efficient ray-triangle intersection algorithm, to significantly accelerate the triangle mesh ray-tracing. A detailed description of the new simulation code and its ray-tracing algorithm is provided in this paper. Furthermore, we show how it can be readily used in medical imaging applications thanks to the detailed anatomical phantoms already available. In particular, we present a whole body radiography simulation using a triangulated version of the anthropomorphic NCAT phantom. An example simulation of scatter fraction measurements using a standardized abdomen and lumbar spine phantom, and a benchmark of the triangle mesh and quadric geometries in the ray-tracing of a mathematical breast model, are also presented to show some of the capabilities of penMesh

PenMesh-Monte Carlo radiation transport simulation in a triangle mesh geometry

We have developed a general-purpose Monte Carlo simulation code, called penMesh, that combines the accuracy of the radiation transport physics subroutines from PENELOPE and the flexibility of a geometry based on triangle meshes. While the geometric models implemented in most general-purpose codes-such as PENELOPE's quadric geometry-impose some limitations in the shape of the objects that can be simulated, triangle meshes can be used to describe any free-form (arbitrary) object. Triangle meshes are extensively used in computer-aided design and computer graphics. We took advantage of the sophisticated tools already developed in these fields, such as an octree structure and an efficient ray-triangle intersection algorithm, to significantly accelerate the triangle mesh ray-tracing. A detailed description of the new simulation code and its ray-tracing algorithm is provided in this paper. Furthermore, we show how it can be readily used in medical imaging applications thanks to the detailed anatomical phantoms already available. In particular, we present a whole body radiography simulation using a triangulated version of the anthropomorphic NCAT phantom. An example simulation of scatter fraction measurements using a standardized abdomen and lumbar spine phantom, and a benchmark of the triangle mesh and quadric geometries in the ray-tracing of a mathematical breast model, are also presented to show some of the capabilities of penMesh

Fast Monte Carlo codes for occupational dosimetry in interventional radiology

Interventional radiology techniques cause radiation exposure both to patient and personnel. The radiation dose to the operator is usually measured with dosimeters located at specific points above or below the lead aprons. The aim of this study is to develop and validate two fast Monte Carlo (MC) codes for radiation transport in order to improve the assessment of individual doses in interventional radiology. The proposed methodology reduces the number of required dosemeters and provides immediate dose results.Peer ReviewedObjectius de Desenvolupament Sostenible::3 - Salut i BenestarPostprint (published version