|
1
|
Ma M, Kidd E, Fahimian BP, Han B, Niedermayr TR, Hristov D, Xing L, Yang Y. Dose Prediction for Cervical Cancer Brachytherapy Using 3-D Deep Convolutional Neural Network. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2022. [DOI: 10.1109/trpms.2021.3098507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
|
|
2
|
Glide-Hurst CK, Lee P, Yock AD, Olsen JR, Cao M, Siddiqui F, Parker W, Doemer A, Rong Y, Kishan AU, Benedict SH, Li XA, Erickson BA, Sohn JW, Xiao Y, Wuthrick E. Adaptive Radiation Therapy (ART) Strategies and Technical Considerations: A State of the ART Review From NRG Oncology. Int J Radiat Oncol Biol Phys 2020; 109:1054-1075. [PMID: 33470210 DOI: 10.1016/j.ijrobp.2020.10.021] [Citation(s) in RCA: 113] [Impact Index Per Article: 22.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 10/08/2020] [Accepted: 10/19/2020] [Indexed: 12/21/2022]
Abstract
The integration of adaptive radiation therapy (ART), or modifying the treatment plan during the treatment course, is becoming more widely available in clinical practice. ART offers strong potential for minimizing treatment-related toxicity while escalating or de-escalating target doses based on the dose to organs at risk. Yet, ART workflows add complexity into the radiation therapy planning and delivery process that may introduce additional uncertainties. This work sought to review presently available ART workflows and technological considerations such as image quality, deformable image registration, and dose accumulation. Quality assurance considerations for ART components and minimum recommendations are described. Personnel and workflow efficiency recommendations are provided, as is a summary of currently available clinical evidence supporting the implementation of ART. Finally, to guide future clinical trial protocols, an example ART physician directive and a physics template following standard NRG Oncology protocol is provided.
Collapse
Affiliation(s)
- Carri K Glide-Hurst
- Department of Human Oncology, University of Wisconsin-Madison, Madison, Wisconsin.
| | - Percy Lee
- Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Adam D Yock
- Department of Radiation Oncology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Jeffrey R Olsen
- Department of Radiation Oncology, University of Colorado- Denver, Denver, Colorado
| | - Minsong Cao
- Department of Radiation Oncology, University of California-Los Angeles, Los Angeles, California
| | - Farzan Siddiqui
- Department of Radiation Oncology, Henry Ford Cancer Institute, Detroit, Michigan
| | - William Parker
- Department of Radiation Oncology, McGill University, Montreal, Quebec, Canada
| | - Anthony Doemer
- Department of Radiation Oncology, Henry Ford Cancer Institute, Detroit, Michigan
| | - Yi Rong
- Department of Radiation Oncology, University of California-Davis, Sacramento, California
| | - Amar U Kishan
- Department of Radiation Oncology, University of California-Los Angeles, Los Angeles, California
| | - Stanley H Benedict
- Department of Radiation Oncology, University of California-Davis, Sacramento, California
| | - X Allen Li
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Beth A Erickson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Jason W Sohn
- Department of Radiation Oncology, Allegheny Health Network, Pittsburgh, Pennsylvania
| | - Ying Xiao
- Department of Radiation Oncology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Evan Wuthrick
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, Florida
| |
Collapse
|
|
3
|
Wang Y, Tu W, Tang Y, Zhang S. Prevention and treatment for radiation-induced skin injury during radiotherapy. RADIATION MEDICINE AND PROTECTION 2020. [DOI: 10.1016/j.radmp.2020.02.004] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
|
|
4
|
Ma M, K. Buyyounouski M, Vasudevan V, Xing L, Yang Y. Dose distribution prediction in isodose feature‐preserving voxelization domain using deep convolutional neural network. Med Phys 2019; 46:2978-2987. [DOI: 10.1002/mp.13618] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2019] [Revised: 05/01/2019] [Accepted: 05/02/2019] [Indexed: 01/30/2023] Open
Affiliation(s)
- Ming Ma
- Department of Radiation Oncology Stanford University 875 Blake Wilbur Drive Stanford CA 94305‐5847USA
| | - Mark K. Buyyounouski
- Department of Radiation Oncology Stanford University 875 Blake Wilbur Drive Stanford CA 94305‐5847USA
| | - Varun Vasudevan
- Department of Radiation Oncology Stanford University 875 Blake Wilbur Drive Stanford CA 94305‐5847USA
| | - Lei Xing
- Department of Radiation Oncology Stanford University 875 Blake Wilbur Drive Stanford CA 94305‐5847USA
| | - Yong Yang
- Department of Radiation Oncology Stanford University 875 Blake Wilbur Drive Stanford CA 94305‐5847USA
| |
Collapse
|