Last year, we presented methodology to perform knowledge-based medical imaging informatics research on specific
clinical scenarios where brain tumor patients are treated with Proton Beam Therapy (PT). In this presentation, we
demonstrate the design and implementation of quantification and visualization tools to develop the knowledge base for
therapy treatment planning based on DICOM-RT-ION objects. Proton Beam Therapy (PT) is a particular treatment that
utilizes energized charged particles, protons, to deliver dose to the target region. Similar to traditional Radiation Therapy
(RT), complex clinical imaging and informatics data are generated during the treatment process that guide the planning
and the success of the treatment. Therefore, an Electronic Patient Record (ePR) System has been developed to
standardize and centralize clinical imaging and informatics data and properly distribute data throughout the treatment
duration. To further improve treatment planning process, we developed a set of decision support tools to improve the
QA process in treatment planning process. One such example is a tool to assist in the planning of stereotactic PT cases
where CT and MR images need to be analyzed simultaneously during treatment plan assessment. These tools are add-on
features for DICOM standard ePR system of brain cancer patients and improve the clinical efficiency of PT treatment
planning. Additional outcome data collected for PT cases are included in the overall DICOM-RT-ION database design
as knowledge to enhance outcomes analysis for future PT adopters.
In existing proton treatment centers, dose calculations are performed based on x-ray computerized tomography (CT). Alternatively, the therapeutic proton beam could be used to collect the data for treatment planning via proton CT (pCT). With the development of medical proton gantries, first at Loma Linda University Medical Center and now in several other proton treatment centers, it is of interest to continue the early pCT investigations of the 1970s and the early 1980s. From that time, the basic idea of the pCT method has advanced from average energy loss measurements to an individual proton tracking technique. This reduces the image degradation due to multiple Coulomb scattering. Thereby, the central pCT problem shifts to the fidelity of the physical information obtained about the scanned patient, which will be used for proton treatment planning. The accuracy of relative electron density distributions extracted from pCT images was investigated in this work using continuous slowing down approximation (CSDA) and water-equivalent-thickness (WET) concepts. Analytical results were checked against Monte Carlo simulations, which were obtained with SRIM2003 and GEANT4 Monte Carlo software packages. The range of applications and the sources of absolute errors are discussed.
Conformal proton radiation therapy requires accurate prediction of the Bragg peak position. This problem may be solved by using protons rather than conventional x-rays to determine the relative electron density distribution via proton computed tomography (proton CT). However, proton CT has its own limitations, which need to be carefully studied before this technique can be introduced into routine clinical practice. In this work, we have used analytical relationships as well as the Monte Carlo simulation tool GEANT4 to study the principal resolution limits of proton CT. The GEANT4 simulations were validated by comparing them to predictions of the Bethe Bloch theory and Tschalar's theory of energy loss straggling, and were found to be in good agreement. The relationship between phantom thickness, initial energy, and the relative electron density uncertainty was systematically investigated to estimate the number of protons and dose needed to obtain a given density resolution. The predictions of this study were verified by simulating the performance of a hypothetical proton CT scanner when imaging a cylindrical water phantom with embedded density inhomogeneities. We show that a reasonable density resolution can be achieved with a relatively small number of protons, thus providing a possible dose advantage over x-ray CT.