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Dosimetric evaluation of VMAT treatment plans for patients with stage IIB or III non-small cell lung carcinomas

Published online by Cambridge University Press:  31 May 2023

Amani Shaaer
Affiliation:
Department of Medical Physics, Grand River Regional Cancer Centre, Kitchener, ON, Canada Department of Biomedical Physics, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
Ernest Osei*
Affiliation:
Department of Medical Physics, Grand River Regional Cancer Centre, Kitchener, ON, Canada Department of Physics and Astronomy, University of Waterloo, Waterloo, ON, Canada Department of Clinical Studies, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada
Johnson Darko
Affiliation:
Department of Medical Physics, Grand River Regional Cancer Centre, Kitchener, ON, Canada Department of Physics and Astronomy, University of Waterloo, Waterloo, ON, Canada Department of Clinical Studies, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
Darin Gopaul
Affiliation:
Department of Radiation Oncology, Grand River Regional Cancer Centre, Kitchener, ON, Canada
*
Corresponding author: Ernest Osei; Email: Ernest.osei@grhosp.on.ca
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Abstract

Introduction:

Volumetric-modulated arc therapy (VMAT) has emerged as a promising radiation treatment technique. One of the challenges in VMAT planning for lung carcinoma is the lack of consistency among different institutions with respect to what is considered an acceptable treatment plan in terms of target coverage and doses to the organs at risk (OAR). Additionally, the accuracy of dose calculations in the presence of heterogeneous medium (i.e. air) is another challenge in lung VMAT planning. Our objective is to develop an institutional criteria for non-stereotactic body radiotherapy (non-SBRT) lung treatment plans by evaluating the dosimetric impact of plan normalisation and dose calculation algorithms, including the Anisotropic Analytical Algorithm (AAA), AcurosXB (AXB) and Monte Carlo (MC) simulation, on VMAT plans for non-small cell lung cancer (NSCLC).

Methods:

The CT dataset of 20 patients with NSCLC was randomly selected to ensure a spectrum of target sizes and locations. All treatment planning was accomplished with 2–3 VMAT arcs and a prescription of 60 Gy in 30 fractions. Two plan normalisation methods were employed: (i) planning target volume (PTV) V100% = 95% and (ii) PTV V95% = 95%.

Results:

All three dose calculation algorithms revealed heterogeneous and conformal plans irrespective of plan normalisations. The PTV and OARs dose–volume constraints were met using both normalisation methods. However, we observed that AAA overestimated the minimum PTV doses by 2–5% regardless of plan normalisation. The mean PTV-V100% was lower for AAA in comparison with AXB and MC algorithms.

Conclusions:

VMAT is an effective radiotherapy technique for achieving greater target dose conformity, heterogeneity and dose fall-off from the PTV for the treatment of NSCLC. The results of this study can provide the basis for the development of local plan acceptability criteria for NSCLC VMAT plans, and the clinical implementation can be achieved with minimal or no imposition on resources and time constraints. Occasionally, plan normalisation of PTV-V95% = 95% may be required to ensure that the OAR dose tolerances are not exceeded.

Information

Type
Original Article
Copyright
© The Author(s), 2023. Published by Cambridge University Press
Figure 0

Table 1. Summary of patients’ characteristics

Figure 1

Table 2. Planning target volume (PTV) and organ at risks (OARs) dose constraints based on PTV V100% = 95% and PTV V95% = 95% plan normalisations criteria

Figure 2

Table 3. A summary of the statistical analysis of the target dose for plans normalised to PTV V100% = 95%

Figure 3

Table 4. A summary of the statistical analysis of the target dose for plans normalised to PTV V95% = 95%

Figure 4

Table 5. A summary of statistical analysis of OARs for plans normalised to PTV V100% = 95%

Figure 5

Table 6. A summary of statistical analysis of OARs for plans normalised to PTV V95% = 95%

Figure 6

Figure 1. Scatter plot showing the correlation between PTV and GTV equivalent sphere diameters (cm). Abbreviations: GTV, gross target volume; PTV, planning target volume.

Figure 7

Figure 2. Dose volume histogram (DVH) of PTV, bilateral lung and spinal canal for the 20 patients for PTV V100% = 95% normalisation and for the three different dose calculation algorithms: AAA, AXB and MC. The mean DVHs are also shown (red lines). Abbreviations: PTV, planning target volume; AAA, Anisotropic Analytic Algorithm; AXB, AcurosXB; MC, Monte Carlo.

Figure 8

Figure 3. Dose volume histogram (DVH) of PTV, bilateral lung and spinal canal for the 20 patients for PTV V95% = 95% normalisation criteria and for the three different dose calculation algorithms: AcurosXB, AAA and Monte Carlo (MC) simulation, respectively. The mean DVHs are also shown (red lines). Abbreviations: PTV, planning target volume; AAA, Anisotropic Analytic Algorithm; AXB, AcurosXB; MC, Monte Carlo.

Figure 9

Figure 4. Dose volume histogram (DVH) of PTV, bilateral lung, spinal canal, oesophagus and heart averaged over 20 patients. Results are shown for both normalisation methods and the three different dose calculation algorithms: AAA, AXB and MC. Abbreviations: PTV, Planning Target Volume; AAA, Anisotropic Analytic Algorithm; AXB, AcurosXB; MC, Monte Carlo.