Assessing the shift of radiobiological metrics in lung radiotherapy plans using 2D gamma index

Gamma Index Analysis as a Patient-Specific Quality Assurance Tool for High-Precision Radiotherapy: A Clinical Perspective of Single Institute Experience

Purpose

Patient-specific quality assurance (QA) by gamma (γ) analysis is an important component of high-precision radiotherapy. It is important to standardize institute-specific protocol. In this study, we describe our institutional experience of patient-specific QA for high-precision radiotherapy from a clinical perspective.

Methods

The planning data of 56 patients treated with intensity-modulated radiotherapy (IMRT)/volumetric modulated arc therapy (VMAT) were included. γ index analysis was done using Octavius 4D IMRT QA phantom (PTW, Freiburg, Germany) using 3 mm/3% criteria. Local, global, and volumetric gammas were calculated and compared. The relationship of γ index in the transverse, coronal, and sagittal direction and anatomical region of treatment was explored.

Results

Global three-dimensional (3D) γ indices in the coronal, sagittal, and transverse axes were 96.73 ± 2.35, 95.66 ± 3.01, and 93.36 ± 4.87 (p < 0.05). The average local two-dimensional (2D) γ index was 78.23 ± 5.44 and the global γ index was 92.41 ± 2.41 (p < 0.005). The average local 3D γ index was 84.99 ± 4.24 and the global 3D γ index was 95.25 ± 1.72 (p < 0.005, paired t-test). The average local volumetric γ index was 84.29 ± 4.73 and the global volumetric γ index was 95.96 ± 2.08 (p < 0.005). 3D global gamma index was significantly different in different anatomical regions (p < 0.05).

Conclusion

Our study shows that γ index analysis is a useful parameter for routine clinical IMRT QA. The choice of type of γ index depends on the context of use and degree of stringency in measurement. Average 2D and 3D global γ were different in anatomical regions. The average 3D γ index was significantly different in axes. No difference was observed with techniques of IMRT/VMAT. Localization of failed points in CT anatomy can be advantageous for clinical decision-making.

Agreement between gamma passing rates using computed tomography in radiotherapy and secondary cancer risk prediction from more advanced dose calculated models

BACKGROUND

During the past decades, in radiotherapy, the dose distributions were calculated using density correction methods with pencil beam as type 'a' algorithm. The objectives of this study are to assess and evaluate the impact of dose distribution shift on the predicted secondary cancer risk (SCR), using modern advanced dose calculation algorithms, point kernel, as type 'b', which consider change in lateral electrons transport.

METHODS

Clinical examples of pediatric cranio-spinal irradiation patients were evaluated. For each case, two radiotherapy treatment plans with were generated using the same prescribed dose to the target resulting in different number of monitor units (MUs) per field. The dose distributions were calculated, respectively, using both algorithms types. A gamma index (γ) analysis was used to compare dose distribution in the lung. The organ equivalent dose (OED) has been calculated with three different models, the linear, the linear-exponential and the plateau dose response curves. The excess absolute risk ratio (EAR) was also evaluated as (EAR = OED _{type 'b'} / OED _{type 'a'}).

RESULTS

The γ analysis results indicated an acceptable dose distribution agreement of 95% with 3%/3 mm. Although, the γ-maps displayed dose displacement >1 mm around the healthy lungs. Compared to type 'a', the OED values from type 'b' dose distributions' were about 8% to 16% higher, leading to an EAR ratio >1, ranged from 1.08 to 1.13 depending on SCR models.

CONCLUSIONS

The shift of dose calculation in radiotherapy, according to the algorithm, can significantly influence the SCR prediction and the plan optimization, since OEDs are calculated from DVH for a specific treatment. The agreement between dose distribution and SCR prediction depends on dose response models and epidemiological data. In addition, the γ passing rates of 3%/3 mm does not translate the difference, up to 15%, in the predictions of SCR resulting from alternative algorithms. Considering that modern algorithms are more accurate, showing more precisely the dose distributions, but that the prediction of absolute SCR is still very imprecise, only the EAR ratio could be used to rank radiotherapy plans.

Statistic and dosimetric criteria to assess the shift of the prescribed dose for lung radiotherapy plans when integrating point kernel models in medical physics: are we ready?

BACKGROUND

To apply the statistical bootstrap analysis and dosimetric criteria's to assess the change of prescribed dose (PD) for lung cancer to maintain the same clinical results when using new generations of dose calculation algorithms.

METHODS

Nine lung cancer cases were studied. For each patient, three treatment plans were generated using exactly the same beams arrangements. In plan 1, the dose was calculated using pencil beam convolution (PBC) algorithm turning on heterogeneity correction with modified batho (PBC-MB). In plan 2, the dose was calculated using anisotropic analytical algorithm (AAA) and the same PD, as plan 1. In plan 3, the dose was calculated using AAA with monitor units (MUs) obtained from PBC-MB, as input. The dosimetric criteria's include MUs, delivered dose at isocentre (Diso) and calculated dose to 95% of the target volume (D95). The bootstrap method was used to assess the significance of the dose differences and to accurately estimate the 95% confidence interval (95% CI). Wilcoxon and Spearman's rank tests were used to calculate P values and the correlation coefficient (ρ).

RESULTS

Statistically significant for dose difference was found using point kernel model. A good correlation was observed between both algorithms types, with ρ>0.9. Using AAA instead of PBC-MB, an adjustment of the PD in the isocentre is suggested.

CONCLUSIONS

For a given set of patients, we assessed the need to readjust the PD for lung cancer using dosimetric indices and bootstrap statistical method. Thus, if the goal is to keep on with the same clinical results, the PD for lung tumors has to be adjusted with AAA. According to our simulation we suggest to readjust the PD by 5% and an optimization for beam arrangements to better protect the organs at risks (OARs).

Evaluation and Performance of ArcCheck and Film using Gamma Criteria in Pre-treatment Quality Assurance of Stereotactic Ablative Radiotherapy

Aim:

The aim of this study is to assess the use of ArcCHECK (AC) as an alternative method to replace film dosimetry for pre-treatment quality assurance (QA) of three-dimensional conformal radiation therapy, intensity-modulated radiation therapy (IMRT), and volumetric-modulated arc therapy (VMAT) stereotactic ablative radiotherapy (SABR) treatment plans.

Materials and Methods:

Twenty-five patients with a varied diagnosis of lung, spine, sacrum, sternum, ribs, scapula, and femur undergoing SABR were selected for this study. Pre-treatment QA was performed for all the patients using ionization chamber and film dosimetry. Measurements were also carried out on an AC phantom. The planned and measured doses from the AC device and EBT3 films were compared using four different gamma criteria: 2%/2 mm, 3%/2 mm, 3%/1 mm, and 3%/3 mm.

Results:

The mean gamma passing rates at 3%/3 mm for all non-spine SABR cases were 98.79 ± 0.96 and 99.27 ± 1.03 with AC and films, respectively. The mean passing rates at 3%/2 mm for AC and films were 98.76 ± 0.42 and 99.43 ± 0.27 respectively for spine VMAT SABR, and 87.15 ± 2.45 and 99.79 ± 0.14 respectively for spine IMRT SABR. In the case of spine tumors, the gamma criterion was tightened due to the proximity of spinal cord to the planning target volume. Our results show that AC provides good results for all VMAT SABR plans.

Conclusion:

The AC results at 3%/3 mm were in good agreement with film dosimetry for most cases. We observed a significant reduction in QA time on using AC for SABR QA. This study showed that AC results are comparable to film dosimetry for all studied sites except for spine IMRT SABR.

Impact of dose calculation models on radiotherapy outcomes and quality adjusted life years for lung cancer treatment: do we need to measure radiotherapy outcomes to tune the radiobiological parameters of a normal tissue complication probability model?

BACKGROUND

The equivalent uniform dose (EUD) radiobiological model can be applied for lung cancer treatment plans to estimate the tumor control probability (TCP) and the normal tissue complication probability (NTCP) using different dose calculation models. Then, based on the different calculated doses, the quality adjusted life years (QALY) score can be assessed versus the uncomplicated tumor control probability (UTCP) concept in order to predict the overall outcome of the different treatment plans.

METHODS

Nine lung cancer cases were included in this study. For the each patient, two treatments plans were generated. The doses were calculated respectively from pencil beam model, as pencil beam convolution (PBC) turning on 1D density correction with Modified Batho's (MB) method, and point kernel model as anisotropic analytical algorithm (AAA) using exactly the same prescribed dose, normalized to 100% at isocentre point inside the target and beam arrangements. The radiotherapy outcomes and QALY were compared. The bootstrap method was used to improve the 95% confidence intervals (95% CI) estimation. Wilcoxon paired test was used to calculate P value.

RESULTS

Compared to AAA considered as more realistic, the PBC_MB overestimated the TCP while underestimating NTCP, P<0.05. Thus the UTCP and the QALY score were also overestimated.

CONCLUSIONS

To correlate measured QALY's obtained from the follow-up of the patients with calculated QALY from DVH metrics, the more accurate dose calculation models should be first integrated in clinical use. Second, clinically measured outcomes are necessary to tune the parameters of the NTCP model used to link the treatment outcome with the QALY. Only after these two steps, the comparison and the ranking of different radiotherapy plans would be possible, avoiding over/under estimation of QALY and any other clinic-biological estimates.