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Comprehensive nodal breast VMAT: solving the low-dose wash dilemma using an iterative knowledge-based radiotherapy
Cameron Stanton1, Linda J Bell1, Andrew Le1
1Radiation Oncology Department, Northern Sydney Cancer Centre, Royal North Shore Hospital, St Leonards, New South Wales, Australia.
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 < 0.05) compared to h-VMAT with minor reduction in breast coverage. CI was enhanced for a small reduction in breast HI with improved dose sparing to ipsilateral-lung and humeral head (P < 0.05) at immaterial expense to spinal cord. Significantly, low-dose wash to OARs and RVR were comparable between all plan types demonstrating a simple VMAT class solution robust to patient-specific anatomic variation can be applied to CLN breast without need for complex beam modification (hybrid plans, avoidance sectors or other). This result was supported by blinded RO review.
Conclusions:
A simple and robust ipsilateral VMAT class solution for CLN breast generated using iterative KBP modelling can achieve clinically acceptable target coverage and OAR sparing without unwanted increase in low-dose wash associated with increased second malignancy risk.
