Date(s) - 06/11/2015
12:00 pm - 2:00 pm
Chair: Wesley Bolch
Major: Biomedical Engineering
Current radiation treatment modalities, including external beam therapy and beta-emitting radioimmunotherapies, have been successfully treating many forms of cancer. In cases where the cancer has metastasized to regions beyond its origin, these treatments are seldom effective. Alpha particle radioimmunotherapy is a promising modality for metastasized cancers (and other cancers requiring targeted therapy) given their high linear energy transfer (LET) and ability to provide potent, localized energy deposition due to their short, densely ionizing tracks.
Radiation dosimetry is an essential aspect of radiation therapies, allowing the effectiveness of treatments to be compared. Furthermore, accurate dosimetry calculations can be used to determine the potential threshold doses and increased risk associated with deterministic and stochastic effects, respectively, that may occur as a result of radiation exposures. Due to the short range of alpha particles typically used in radioimmunotherapy (on the order of 50-80 μm), dosimetry must be assessed at the sub-organ, microscopic level. As the case with all radioimmunotherapy, bone marrow is often the dose-limiting organ due to its inherent heightened radiosensitivity. In addition to the risk of marrow toxicity, kidney toxicity is of particular concern in radioimmunotherapy due to the physiology of the kidneys, acting as the major filtration and excretory organ in the body. To assess absorbed doses to these organs of interest, realistic computational microscopic and macroscopic models of organ geometries can be coupled with Monte Carlo methods to perform radiation transport for radionuclides of interest in alpha-particle radioimmunotherapy. The present study has made significant advances through the successful development of depth-dependent models of the spongiosa region as well as detailed, image-based models of both the macro- and microscopic renal anatomy from human cadaver specimens. These models were then used to generate a comprehensive library of S values for commonly used radionuclides in radioimmunotherapy.