| Content Provider | Springer Nature : BioMed Central |
|---|---|
| Author | Liu, Hefei Schaal, David Curry, Heather Clark, Ryan Magliari, Anthony Kupelian, Patrick Khuntia, Deepak Beriwal, Sushil |
| Abstract | Adaptive radiotherapy (ART) was introduced in the late 1990s to improve the accuracy and efficiency of therapy and minimize radiation-induced toxicities. ART combines multiple tools for imaging, assessing the need for adaptation, treatment planning, quality assurance, and has been utilized to monitor inter- or intra-fraction anatomical variations of the target and organs-at-risk (OARs). Ethos™ (Varian Medical Systems, Palo Alto, CA), a cone beam computed tomography (CBCT) based radiotherapy treatment system that uses artificial intelligence (AI) and machine learning to perform ART, was introduced in 2020. Since then, numerous studies have been done to examine the potential benefits of Ethos™ CBCT-guided ART compared to non-adaptive radiotherapy. This review will explore the current trends of Ethos™, including improved CBCT image quality, a feasible clinical workflow, daily automated contouring and treatment planning, and motion management. Nevertheless, evidence of clinical improvements with the use of Ethos™ are limited and is currently under investigation via clinical trials. |
| Related Links | https://ro-journal.biomedcentral.com/counter/pdf/10.1186/s13014-023-02340-2.pdf |
| Ending Page | 12 |
| Page Count | 12 |
| Starting Page | 1 |
| File Format | HTM / HTML |
| DOI | 10.1186/s13014-023-02340-2 |
| Journal | Radiation Oncology |
| Issue Number | 1 |
| Volume Number | 18 |
| Language | English |
| Publisher | BioMed Central |
| Publisher Date | 2023-09-02 |
| Access Restriction | Open |
| Subject Keyword | Cancer Research Oncology Radiotherapy Imaging Radiology Cone-beam computed tomography (CBCT) Adaptive radiotherapy (ART) Ethos™ |
| Content Type | Text |
| Resource Type | Review |
| Subject | Radiology, Nuclear Medicine and Imaging Oncology |
| Journal Impact Factor | 3.3/2023 |
| 5-Year Journal Impact Factor | 3.6/2023 |
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