Cancer clinics currently use high-dose stereotactic body radiation therapy as a curative treatment for several kinds of cancers. However, the contribution of vascular endothelial cells to tumor response to radiation remains controversial. Using dual-recombinase technology, we generated primary sarcomas in mice with targeted genetic mutations specifically in tumor cells or endothelial cells. We selectively mutated the proapoptotic gene Bax or the DNA damage–response gene Atm to genetically manipulate the radiosensitivity of endothelial cells in primary soft tissue sarcomas. Bax deletion from endothelial cells did not affect radiation-induced cell death in tumor endothelial cells or sarcoma response to radiation therapy. Although Atm deletion increased endothelial cell death after radiation therapy, deletion of Atm from endothelial cells failed to enhance sarcoma eradication. In contrast, deletion of Atm from tumor cells increased sarcoma eradication by radiation therapy. These results demonstrate that tumor cells, rather than endothelial cells, are critical targets that regulate sarcoma eradication by radiation therapy. Treatment with BEZ235, a small-molecule protein kinase inhibitor, radiosensitized primary sarcomas more than hearts. These results suggest that inhibiting ATM kinase during radiation therapy is a viable strategy for radiosensitization of some tumors.

This work provides a large cohort of highly detailed pediatric phantoms with 4D capabilities of varying age, height, and body mass. The population of phantoms will provide a vital tool with which to optimize 3D and 4D pediatric imaging devices and techniques in terms of image quality and radiation-absorbed dose.

Purpose:The authors previously developed an adult population of 4D extended cardiac-torso (XCAT) phantoms for multimodality imaging research. In this work, the authors develop a reference set of 4D pediatric XCAT phantoms consisting of male and female anatomies at ages of newborn, 1, 5, 10, and 15 years. These models will serve as the foundation from which the authors will create a vast population of pediatric phantoms for optimizing pediatric CT imaging protocols. Methods: Each phantom was based on a unique set of CT data from a normal patient obtained from the Duke University database. The datasets were selected to best match the reference values for height and weight for the different ages and genders according to ICRP Publication 89. The major organs and structures were segmented from the CT data and used to create an initial pediatric model defined using nonuniform rational B-spline surfaces. The CT data covered the entire torso and part of the head. To complete the body, the authors manually added on the top of the head and the arms and legs using scaled versions of the XCAT adult models or additional models created from cadaver data. A multichannel large deformation diffeomorphic metric mapping algorithm was then used to calculate the transform from a template XCAT phantom (male or female 50th percentile adult) to the target pediatric model. The transform was applied to the template XCAT to fill in any unsegmented structures within the target phantom and to implement the 4D cardiac and respiratory models in the new anatomy. The masses of the organs in each phantom were matched to the reference values given in ICRP Publication 89. The new reference models were checked for anatomical accuracy via visual inspection. Results: The authors created a set of ten pediatric reference phantoms that have the same level of detail and functionality as the original XCAT phantom adults. Each consists of thousands of anatomical structures and includes parameterized models for the cardiac and respiratory motions. Based on patient data, the phantoms capture the anatomic variations of childhood, such as the development of bone in the skull, pelvis, and long bones, and the growth of the vertebrae and organs. The phantoms can be combined with existing simulation packages to generate realistic pediatric imaging data from different modalities. Conclusions: The development of patient-derived pediatric computational phantoms is useful in providing variable anatomies for simulation. Future work will expand this ten-phantom base to a host of pediatric phantoms representative of the public at large. This can provide a means to evaluate and improve pediatric imaging devices and to optimize CT protocols in terms of image quality and radiation dose.