Correlation between the γ passing rates of IMRT plans and the volumes of air cavities and bony structures in head and neck cancer

The impact of plan complexity on calculation and measurement-based pre-treatment verifications for sliding-window intensity-modulated radiotherapy

Background and purpose

In sliding-window intensity-modulated radiotherapy, increased plan modulation often leads to increased plan complexities and dose uncertainties. Dose calculation and/or measurement checks are usually adopted for pre-treatment verification. This study aims to evaluate the relationship among plan complexities, calculated doses and measured doses.

Materials and methods

A total of 53 plan complexity metrics (PCMs) were selected, emphasizing small field characteristics and leaf speed/acceleration. Doses were retrieved from two beam-matched treatment devices. The intended dose was computed employing the Anisotropic Analytical Algorithm and validated through Monte Carlo (MC) and Collapsed Cone Convolution (CCC) algorithms. To measure the delivered dose, 3D diode arrays of various geometries, encompassing helical, cross, and oblique cross shapes, were utilized. Their interrelation was assessed via Spearman correlation analysis and principal component linear regression (PCR).

Results

The correlation coefficients between calculation-based (CQA) and measurement-based verification quality assurance (MQA) were below 0.53. Most PCMs showed higher correlation rpcm-QA with CQA (max: 0.84) than MQA (max: 0.65). The proportion of rpcm-QA  ≥ 0.5 was the largest in the pelvis compared to head-and-neck and chest-and-abdomen, and the highest rpcm-QA occurred at 1 %/1mm. Some modulation indices for the MLC speed and acceleration were significantly correlated with CQA and MQA. PCR's determination coefficients (R2 ) indicated PCMs had higher accuracy in predicting CQA (max: 0.75) than MQA (max: 0.42).

Conclusions

CQA and MQA demonstrated a weak correlation. Compared to MQA, CQA exhibited a stronger correlation with PCMs. Certain PCMs related to MLC movement effectively indicated variations in both quality assurances.

Dosimetric performance evaluation of the Halcyon treatment platform for stereotactic radiotherapy: A pooled study

With the advancement of radiotherapy equipment, stereotactic radiotherapy (SRT) has been increasingly used. Among the many radiotherapy devices, Halcyon shows promising applications. This article reviews the dosimetric performance such as plan quality, plan complexity, and gamma passing rates of SRT plans with Halcyon to determine the effectiveness and safety of Halcyon SRT plans. This article retrieved the last 5 years of PubMed studies on the effectiveness and safety of the Halcyon SRT plans. Two authors independently reviewed the titles and abstracts to decide whether to include the studies. A search was conducted to identify publications relevant to evaluating the dosimetric performance of SRT plans on Halcyon using the key strings Halcyon, stereotactic radiosurgery, SRT, stereotactic body radiotherapy, and stereotactic ablative radiotherapy. A total of 18 eligible publications were retrieved. Compared to SRT plans on the TrueBeam, the Halcyon has advantages in terms of plan quality, plan complexity, and gamma passing rates. The high treatment speed of SRT plans on the Halcyon is impressive, while the results of its plan evaluation are also encouraging. As a result, Halcyon offers a new option for busy radiotherapy units while significantly improving patient comfort in treatment. For more accurate results, additional relevant publications will need to be followed up in subsequent studies.

Dose difference between anisotropic analytical algorithm (AAA) and Acuros XB (AXB) caused by target's air content for volumetric modulated arc therapy of head and neck cancer

Background

We clarified the dose difference between the anisotropic analytical algorithm (AAA) and Acuros XB (AXB) with increasing target's air content using a virtual phantom and clinical cases.

Materials and methods

Whole neck volumetric modulated arc therapy (VMAT) plan was transferred into a virtual phantom with a cylindrical air structure at the center. The diameter of the air structure was changed from 0 to 6 cm, and the target's air content defined as the air/planning target volume (PTV) in percent (air/PTV) was varied. VMAT plans were recalculated by AAA and AXB with the same monitor unit (MU) and multi-leaf collimator (MLC) motions. The dose at each air/PTV (5%-30%) was compared between each algorithm with D98%, D95%, D50% and D2% for the PTV. In addition, MUs were also compared with the same MLC motions between the D95% prescription with AAA (AAA_D95%), AXB_D95%, and the prescription to 100% minus air/PTV (AXB_D100%-air/PTV) in clinical cases of head and neck (HNC).

Results

When air/PTV increased (5-30%), the dose differences between AAA and AXB for D98%, D95%, D50% and D2% were 3.08-15.72%, 2.35-13.92%, 0.63-4.59%, and 0.14-6.44%, respectively. At clinical cases with air/PTV of 5.61% and 28.19%, compared to AAA_D95%, the MUs differences were, respectively, 2.03% and 6.74% for AXB_D95% and 1.80% and 0.50% for AXB_D100%-air/PTV.

Conclusion

The dose difference between AAA and AXB increased as the target's air content increased, and AXB_D95% resulted in a dose escalation over AAA_D95% when the target's air content was ≥ 5%. The D100%-air/PTV of PTV using AXB was comparable to the D95% of PTV using AAA.

Using machine learning to predict gamma passing rate in volumetric-modulated arc therapy treatment plans

PURPOSE

This study aims to develop an algorithm to predict gamma passing rate (GPR) in the volumetric-modulated arc therapy (VMAT) technique.

MATERIALS AND METHODS

A total of 118 clinical VMAT plans, including 28 mediastina, 25 head and neck, 40 brains intensity-modulated radiosurgery, and 25 prostate cases, were created in RayStation treatment planning system for Edge and TrueBeam linacs. In-house scripts were developed to compute Modulation indices such as plan-averaged beam area (PA), plan-averaged beam irregularity (PI), total monitor unit (MU), leaf travel/arc length, mean dose rate variation, and mean gantry speed variation. Pretreatment verifications were performed on ArcCHECK phantom with SNC software. GPR was calculated with 3%/2 mm and 10% threshold. The dataset was randomly split into a training (70%) and a test (30%) dataset. A random forest regression (RFR) model and support vector regression (SVR) with linear kernel were trained to predict GPR using the complexity metrics as input. The prediction performance was evaluated by calculating the mean absolute error (MAE), R² , and root mean square error (RMSE).

RESULTS

RMSEs at γ 3%/2 mm for RFR and SVR were 1.407 ± 0.103 and 1.447 ± 0.121, respectively. MAE was 1.14 ± 0.084 for RFR and 1.101 ± 0.09 for SVR. R² was equal to 0.703 ± 0.027 and 0.689 ± 0.053 for RFR and SVR, respectively. GPR of 3%/2 mm with a 10% threshold can be predicted with an error smaller than 3% for 94% of plans using RFR and SVR models. The most important metrics that had the greatest impact on how accurately GPR can be predicted were determined to be the PA, PI, and total MU.

CONCLUSION

In terms of its prediction values and errors, SVR (linear) appeared to be comparable with RFR for this dataset. Based on our results, the PA, PI, and total MU calculations may be useful in guiding VMAT plan evaluation and ultimately reducing uncertainties in planning and radiation delivery.

Radiobiological Comparison of Acuros External Beam and Anisotropic Analytical Algorithm on Esophageal Carcinoma Radiotherapy Treatment Plans

Objective

The present study aimed to investigate the dose differences and radiobiological assessment between Anisotropic Analytical Algorithm (AAA) and Acuros External Beam (AXB) with its 2 calculation models, namely, dose-to-water (AXB-Dw) and dose-to-medium (AXB-Dm), on esophageal carcinoma radiotherapy treatment plans.

Materials and methods

The AXB-Dw and AXB-Dm plans were generated by recalculating the initial 66 AAA plans using the AXB algorithm with the same monitor units and beam parameters as those in the original plan. The dosimetric and radiobiological assessment parameters were calculated for the planning target volume (PTV) and organs at risk (OARs). The gamma agreement for the PTV and the correlation between it and the volume of the air cavity and bone among the different algorithms were compared simultaneously. The dose discrepancy between the theoretical calculation and treatment planning system (TPS) when switching from AXB-Dm to AXB-Dw was analyzed according to the composition of the structures.

Results

The PTV dose of AXB-Dm plans was significantly smaller than that of the AAA and AXB-Dw plans (P < .05), except for D₂. The difference values for AAA vs AXB-Dm (∆D_{x,(AAA-AXB,Dm)}) and AXB-Dw vs AXB-Dm (∆D_{x,(AXB,Dw-AXB,Dm)}) were 1.94% [1.27%, 2.64%] and 1.95% [1.56%, 2.27%], respectively. For the spinal cord and heart, there were obvious differences between the AAA vs AXB-Dm (spinal cord: 1.15%, heart: 2.89%) and AXB-Dw vs AXB-Dm (spinal cord: 1.88%, heart: 3.25%) plans. For the lung, the differences between AAA vs AXB-Dm and AAA vs AXB-Dw were significantly larger than those of AXB-Dm vs AXB-Dw. Compared to the case of AAA and AXB-Dw, the decrease in biologically effective dose (BED¹⁰, αβ=10 ) of AXB-Dm due to dose non-uniformity exceeded 6.5%, even for a small σ. The average values of equivalent uniform dose in the AAA, AXB-Dw, and AXB-Dm plans were 52.03±.39 Gy, 52.24 ± .81 Gy, and 51.13 ± .47 Gy, respectively. The tumor control probability (TCP) results for PTV in the AAA, AXB-Dw, and AXB-Dm plans were 62.29 ± 1.57%, 62.82 ± 1.69%, and 58.68±1.88%, respectively. With the 2%/2 mm and 3%/3 mm acceptance criteria, the mean values of  ΔγAAAAXB−Dw, ΔγAAAAXB−Dm, and  ΔγAXB−DmAXB−Dw were 87.24, 63.3, and 64.81% vs 97.86, 91.77, and 89.25%, respectively. The dose discrepancy between the theoretical calculation and TPS when switching from AXB-Dm to AXB-Dw was approximately 1.63%.

Conclusions

The AAA and AXB-Dw algorithms overestimated the radiobiological parameters when the tumor particularly consisted of nonuniform tissues. A relatively small dose difference could cause a significant reduction in the corresponding TCP. Dose distribution algorithms should be carefully chosen by physicists and oncologists to improve tumor control, as well as to optimize OARs protection.