Prediction models as decision-support tools for virtual patient-specific quality assurance of helical tomotherapy plans.

ABSTRACT:

Background and purpose

Prediction models may be reliable decision-support tools to reduce the workload associated with the measurement-based patient-specific quality assurance (PSQA) of radiotherapy plans. This study compared the effectiveness of three different models based on delivery parameters, complexity metrics and sinogram radiomics features as tools for virtual-PSQA (vPSQA) of helical tomotherapy (HT) plans.

Materials and methods

A dataset including 881 RT plans created with two different treatment planning systems (TPSs) was collected. Sixty-five indicators including 12 delivery parameters (DP) and 53 complexity metrics (CM) were extracted using a dedicated software library. Additionally, 174 radiomics features (RF) were extracted from the plans' sinograms. Three gr

SUBMITTER: Cavinato S 

PROVIDER: S-EPMC10113896 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature