In silico investigation of factors affecting the MV imaging performance of a novel water-equivalent EPID

Comparison of two different EPID-based solutions performing pretreatment quality assurance: 2D portal dosimetry versus 3D forward projection method

PURPOSE

The aim of this paper is to characterize two different EPID-based solutions for pre-treatment VMAT quality assurance, the 2D portal dosimetry and the 3D projection technique. Their ability to catch the main critical delivery errors was studied.

METHODS

Measurements were performed with a linac accelerator equipped with EPID aSi1000, Portal Dose Image Prediction (PDIP), and PerFRACTION softwares. Their performances were studied simulating perturbations of a reference plan through systematic variations in dose values and micromultileaf collimator position. The performance of PDIP, based on 2D forward method, was evaluated calculating gamma passing rate (%GP) between no-error and error-simulated measurements. The impact of errors with PerFRACTION, based on 3D projection technique, was analyzed by calculating the difference between reference and perturbed DVH (%ΔD). Subsequently pre-treatment verification with PerFRACTION was done for 27 patients of different pathologies.

RESULTS

The sensitivity of PerFRACTION was slightly higher than sensitivity of PDIP, reaching a maximum of 0.9. Specificity was 1 for PerFRACTION and 0.6 for PDIP. The analysis of patients' DVHs indicated that the mean %ΔD was (1.2 ± 1.9)% for D2%, (0.6 ± 1.7)% for D95% and (-0.0 ± 1.2)% for Dmean of PTV. Regarding OARs, we observed important discrepancies on DVH but that the higher dose variations were in low dose area (<10 Gy).

CONCLUSIONS

This study supports the introduction of the new 3D forward projection method for pretreatment QA raising the claim that the visualization of the delivered dose distribution on patient anatomy has major advantages over traditional portal dosimetry QA systems.

Exploration of temporal stability and prognostic power of radiomic features based on electronic portal imaging device images

PURPOSE

We aimed to explore the temporal stability of radiomic features in the presence of tumor motion and the prognostic powers of temporally stable features.

METHODS

We selected single fraction dynamic electronic portal imaging device (EPID) (n = 275 frames) and static digitally reconstructed radiographs (DRRs) of 11 lung cancer patients, who received stereotactic body radiation therapy (SBRT) under free breathing. Forty-seven statistical radiomic features, which consisted of 14 histogram-based features and 33 texture features derived from the graylevel co-occurrence and graylevel run-length matrices, were computed. The temporal stability was assessed by using a multiplication of the intra-class correlation coefficients (ICCs) between features derived from the EPID and DRR images at three quantization levels. The prognostic powers of the features were investigated using a different database of lung cancer patients (n = 221) based on a Kaplan-Meier survival analysis.

RESULTS

Fifteen radiomic features were found to be temporally stable for various quantization levels. Among these features, seven features have shown potentials for prognostic prediction in lung cancer patients.

CONCLUSIONS

This study suggests a novel approach to select temporally stable radiomic features, which could hold prognostic powers in lung cancer patients.