Search NASA⌕ Search

Engineering topics

Benedict, S.

Publications and source records attributed to Benedict, S..

MO-E-BRB-01: Panel Member

In this interactive session, lung SBRT patient cases will be presented to highlight real-world considerations for ensuring safe and accurate treatment delivery. An expert panel of speakers will discuss challenges specific to lung SBRT including patient selection, patient immobilization techniques, 4D CT simulation and respiratory motion management, target delineation for treatment planning, online treatment alignment, and established prescription regimens and OAR dose limits. Practical examples of cases, including the patient flow thought the clinical process are presented and audience participation will be encouraged. This panel session is designed to provide case demonstration and review for lung SBRT in terms of (1) clinical appropriateness in patient selection, (2) strategies for simulation, including 4D and respiratory motion management, and (3) applying multi imaging modality (4D CT imaging, MRI, PET) for tumor volume delineation and motion extent, and (4) image guidance in treatment delivery. Learning Objectives: Understand the established requirements for patient selection in lung SBRT Become familiar with the various immobilization strategies for lung SBRT, including technology for respiratory motion management Understand the benefits and pitfalls of applying multi imaging modality (4D CT imaging, MRI, PET) for tumor volume delineation and motion extent determination for lung SBRT Understand established prescription regimes and OAR dose limits.

60 APPLIED LIFE SCIENCES↗

WE-H-BRB-01: Overview of the ASTRO-NIH-AAPM 2015 Workshop On Exploring Opportunities for Radiation Oncology in the Era of Big Data

Big Data in Radiation Oncology: (1) Overview of the NIH 2015 Big Data Workshop, (2) Where do we stand in the applications of big data in radiation oncology?, and (3) Learning Health Systems for Radiation Oncology: Needs and Challenges for Future Success The overriding goal of this trio panel of presentations is to improve awareness of the wide ranging opportunities for big data impact on patient quality care and enhancing potential for research and collaboration opportunities with NIH and a host of new big data initiatives. This presentation will also summarize the Big Data workshop that was held at the NIH Campus on August 13–14, 2015 and sponsored by AAPM, ASTRO, and NIH. The workshop included discussion of current Big Data cancer registry initiatives, safety and incident reporting systems, and other strategies that will have the greatest impact on radiation oncology research, quality assurance, safety, and outcomes analysis. Learning Objectives: To discuss current and future sources of big data for use in radiation oncology research To optimize our current data collection by adopting new strategies from outside radiation oncology To determine what new knowledge big data can provide for clinical decision support for personalized medicine L. Xing, NIH/NCI Google Inc.

60 APPLIED LIFE SCIENCES↗