Advanced automated treatment planning for total body irradiation: Implementation and effects on standardization.
Phys Med
; 112: 102623, 2023 Aug.
Article
em En
| MEDLINE
| ID: mdl-37356420
ABSTRACT
PURPOSE:
This work describes the automation of our volumetric modulated arc therapy (VMAT) total body irradiation (TBI) treatment planning. It also aims to determine if plan standardization is impacted by automation.METHODS:
We introduced automated beam placement for TBI in March 2021. For manual beam placement pre-2021, Python-modified DICOM files were imported to pre-set cumulative meterset weights, with other parameters selected by dosimetrists. Our automated planning script automates these processes and sets gantry stop angles and isocentre placement. To determine the impact of automation on plan standardization, we performed a retrospective review of a matched cohort of 168 patients. Plan parameters were compared with an external standard, and passing rates compared between patient cohorts. The dosimetric impact was investigated by comparing a Body-5 mm homogeneity index (HI = D2%/D98%) and mean lung dose (MLD) between cohorts.RESULTS:
Results are listed for manual and automated groups respectively. Median (range) passing rates were 97.7% (96.1-100) and 99.2% (98.3-100). Automated plans had a significantly higher passing rate (p ⪠0.05) and smaller variance (p = 0.001). Most failures were attributed to human error. Automated plans also had more consistent parameter identifiers. After considering dimensional outliers, median (range) Body-5 mm HI were 1.18 (1.14-1.23) and 1.18 (1.15-1.26), and mean ± standard deviation MLD were 103.8 ± 1.3% and 104.1 ± 0.9%. Variances were not significantly different between Body-5 mm HI (p = 0.092) but were for MLD (p = 0.013).CONCLUSIONS:
Implementation of automated planning in TBI resulted in significantly improved plan standardization. The decrease in variance of the MLD for the automated planning group points towards a potential dosimetric benefit of automation.
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MEDLINE
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En
Ano de publicação:
2023
Tipo de documento:
Article