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Smith K, Ulin K, Knopp M, Kry S, Xiao Y, Rosen M, Michalski J, Iandoli M, Laurie F, Quigley J, Reifler H, Santiago J, Briggs K, Kirby S, Schmitter K, Prior F, Saltz J, Sharma A, Bishop-Jodoin M, Moni J, Cicchetti MG, FitzGerald TJ. Quality improvements in radiation oncology clinical trials. Front Oncol 2023; 13:1015596. [PMID: 36776318 PMCID: PMC9911211 DOI: 10.3389/fonc.2023.1015596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 01/06/2023] [Indexed: 01/27/2023] Open
Abstract
Clinical trials have become the primary mechanism to validate process improvements in oncology clinical practice. Over the past two decades there have been considerable process improvements in the practice of radiation oncology within the structure of a modern department using advanced technology for patient care. Treatment planning is accomplished with volume definition including fusion of multiple series of diagnostic images into volumetric planning studies to optimize the definition of tumor and define the relationship of tumor to normal tissue. Daily treatment is validated by multiple tools of image guidance. Computer planning has been optimized and supported by the increasing use of artificial intelligence in treatment planning. Informatics technology has improved, and departments have become geographically transparent integrated through informatics bridges creating an economy of scale for the planning and execution of advanced technology radiation therapy. This serves to provide consistency in department habits and improve quality of patient care. Improvements in normal tissue sparing have further improved tolerance of treatment and allowed radiation oncologists to increase both daily and total dose to target. Radiation oncologists need to define a priori dose volume constraints to normal tissue as well as define how image guidance will be applied to each radiation treatment. These process improvements have enhanced the utility of radiation therapy in patient care and have made radiation therapy an attractive option for care in multiple primary disease settings. In this chapter we review how these changes have been applied to clinical practice and incorporated into clinical trials. We will discuss how the changes in clinical practice have improved the quality of clinical trials in radiation therapy. We will also identify what gaps remain and need to be addressed to offer further improvements in radiation oncology clinical trials and patient care.
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Affiliation(s)
- Koren Smith
- Imaging and Radiation Oncology Core-Rhode Island, Department of Radiation Oncology, UMass Chan Medical School, Lincoln, RI, United States
| | - Kenneth Ulin
- Imaging and Radiation Oncology Core-Rhode Island, Department of Radiation Oncology, UMass Chan Medical School, Lincoln, RI, United States
| | - Michael Knopp
- Imaging and Radiation Oncology Core-Ohio, Department of Radiology, The Ohio State University, Columbus, OH, United States
| | - Stephan Kry
- Imaging and Radiation Oncology Core-Houston, Division of Radiation Oncology, University of Texas, MD Anderson, Houston, TX, United States
| | - Ying Xiao
- Imaging and Radiation Oncology Core Philadelphia, Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA, United States
| | - Mark Rosen
- Imaging and Radiation Oncology Core Philadelphia, Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Jeff Michalski
- Department of Radiation Oncology, Washington University, St Louis, MO, United States
| | - Matthew Iandoli
- Imaging and Radiation Oncology Core-Rhode Island, Department of Radiation Oncology, UMass Chan Medical School, Lincoln, RI, United States
| | - Fran Laurie
- Imaging and Radiation Oncology Core-Rhode Island, Department of Radiation Oncology, UMass Chan Medical School, Lincoln, RI, United States
| | - Jean Quigley
- Imaging and Radiation Oncology Core-Rhode Island, Department of Radiation Oncology, UMass Chan Medical School, Lincoln, RI, United States
| | - Heather Reifler
- Imaging and Radiation Oncology Core-Rhode Island, Department of Radiation Oncology, UMass Chan Medical School, Lincoln, RI, United States
| | - Juan Santiago
- Imaging and Radiation Oncology Core-Rhode Island, Department of Radiation Oncology, UMass Chan Medical School, Lincoln, RI, United States
| | - Kathleen Briggs
- Imaging and Radiation Oncology Core-Rhode Island, Department of Radiation Oncology, UMass Chan Medical School, Lincoln, RI, United States
| | - Shawn Kirby
- Imaging and Radiation Oncology Core-Rhode Island, Department of Radiation Oncology, UMass Chan Medical School, Lincoln, RI, United States
| | - Kate Schmitter
- Imaging and Radiation Oncology Core-Rhode Island, Department of Radiation Oncology, UMass Chan Medical School, Lincoln, RI, United States
| | - Fred Prior
- Department of Biomedical Informatics, University of Arkansas, Little Rock, AR, United States
| | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, United States
| | - Ashish Sharma
- Department of Biomedical Informatics, Emory University, Atlanta, GA, United States
| | - Maryann Bishop-Jodoin
- Imaging and Radiation Oncology Core-Rhode Island, Department of Radiation Oncology, UMass Chan Medical School, Lincoln, RI, United States
| | - Janaki Moni
- Imaging and Radiation Oncology Core-Rhode Island, Department of Radiation Oncology, UMass Chan Medical School, Lincoln, RI, United States
| | - M. Giulia Cicchetti
- Imaging and Radiation Oncology Core-Rhode Island, Department of Radiation Oncology, UMass Chan Medical School, Lincoln, RI, United States
| | - Thomas J. FitzGerald
- Imaging and Radiation Oncology Core-Rhode Island, Department of Radiation Oncology, UMass Chan Medical School, Lincoln, RI, United States
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