Comprehensive nodal breast VMAT: solving the low‐dose wash dilemma using an iterative knowledge‐based radiotherapy planning solution
| Autor: | Thomas Eade, Cameron Stanton, Susan Carroll, Leigh Ambrose, Andrew Le, Linda J. Bell, Jeremy T. Booth, Marita Morgia, Brooke Griffiths, Regina Bromley, Gillian Lamoury, Kenny Wu, Denise Andree-Evarts, Kirsten van Gysen, Brian Porter, Jessica Adams |
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| Rok vydání: | 2021 |
| Předmět: |
Organs at Risk
Radiological and Ultrasound Technology business.industry Knowledge Bases Radiotherapy Planning Computer-Assisted medicine.medical_treatment Low dose Planning target volume Radiotherapy Dosage Patient data medicine.disease Radiation therapy Breast cancer Radiation Oncology medicine Second Malignancy Humans Radiology Nuclear Medicine and imaging Radiotherapy Intensity-Modulated Nuclear medicine business Radiation oncologist Homogeneity index |
| Zdroj: | Journal of Medical Radiation Sciences. 69:85-97 |
| ISSN: | 2051-3909 2051-3895 |
| DOI: | 10.1002/jmrs.534 |
| Popis: | INTRODUCTION Aimed to develop a simple and robust volumetric modulated arc radiotherapy (VMAT) solution for comprehensive lymph node (CLN) breast cancer without increase in low-dose wash. METHODS Forty CLN-breast patient data sets were utilised to develop a knowledge-based planning (KBP) VMAT model, which limits low-dose wash using iterative learning and base-tangential methods as benchmark. Another twenty data sets were employed to validate the model comparing KBP-generated ipsilateral VMAT (ipsi-VMAT) plans against the benchmarked hybrid (h)-VMAT (departmental standard) and bowtie-VMAT (published best practice) methods. Planning target volume (PTV), conformity/homogeneity index (CI/HI), organ-at-risk (OAR), remaining-volume-at-risk (RVR) and blinded radiation oncologist (RO) plan preference were evaluated. RESULTS Ipsi- and bowtie-VMAT plans were dosimetrically equivalent, achieving greater nodal target coverage (P |
| Databáze: | OpenAIRE |
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