Radiation Oncology: Future Vision for Quality Assurance and Data Management in Clinical Trials and Translational Science
Ding, Linda ; Bradford, Carla ; Kuo, I-Lin ; Fan, Yankhua ; Ulin, Kenneth ; Khalifeh, Abdulnasser ; Yu, Suhong ; Liu, Fenghong ; Saleeby, Jonathan ; Bushe, Harry ... show 10 more
Citations
Authors
Bradford, Carla
Kuo, I-Lin
Fan, Yankhua
Ulin, Kenneth
Khalifeh, Abdulnasser
Yu, Suhong
Liu, Fenghong
Saleeby, Jonathan
Bushe, Harry
Smith, Koren
Bianciu, Camelia
LaRosa, Salvatore
Prior, Fred
Saltz, Joel
Sharma, Ashish
Smyczynski, Mark S.
Bishop-Jodoin, Maryann
Laurie, Fran
Iandoli, Matthew
Moni, Janaki
Cicchetti, M Giulia
FitzGerald, Thomas J
Student Authors
Faculty Advisor
Academic Program
UMass Chan Affiliations
Document Type
Publication Date
Subject Area
Collections
Embargo Expiration Date
Link to Full Text
Abstract
The future of radiation oncology is exceptionally strong as we are increasingly involved in nearly all oncology disease sites due to extraordinary advances in radiation oncology treatment management platforms and improvements in treatment execution. Due to our technology and consistent accuracy, compressed radiation oncology treatment strategies are becoming more commonplace secondary to our ability to successfully treat tumor targets with increased normal tissue avoidance. In many disease sites including the central nervous system, pulmonary parenchyma, liver, and other areas, our service is redefining the standards of care. Targeting of disease has improved due to advances in tumor imaging and application of integrated imaging datasets into sophisticated planning systems which can optimize volume driven plans created by talented personnel. Treatment times have significantly decreased due to volume driven arc therapy and positioning is secured by real time imaging and optical tracking. Normal tissue exclusion has permitted compressed treatment schedules making treatment more convenient for the patient. These changes require additional study to further optimize care. Because data exchange worldwide have evolved through digital platforms and prisms, images and radiation datasets worldwide can be shared/reviewed on a same day basis using established de-identification and anonymization methods. Data storage post-trial completion can co-exist with digital pathomic and radiomic information in a single database coupled with patient specific outcome information and serve to move our translational science forward with nimble query elements and artificial intelligence to ask better questions of the data we collect and collate. This will be important moving forward to validate our process improvements at an enterprise level and support our science. We have to be thorough and complete in our data acquisition processes, however if we remain disciplined in our data management plan, our field can grow further and become more successful generating new standards of care from validated datasets.
Source
Ding L, Bradford C, Kuo IL, Fan Y, Ulin K, Khalifeh A, Yu S, Liu F, Saleeby J, Bushe H, Smith K, Bianciu C, LaRosa S, Prior F, Saltz J, Sharma A, Smyczynski M, Bishop-Jodoin M, Laurie F, Iandoli M, Moni J, Cicchetti MG, FitzGerald TJ. Radiation Oncology: Future Vision for Quality Assurance and Data Management in Clinical Trials and Translational Science. Front Oncol. 2022 Aug 10;12:931294. doi: 10.3389/fonc.2022.931294. PMID: 36033446; PMCID: PMC9399423.