Evaluation of a new secondary dose calculation software for Gamma Knife radiosurgery

Sensitivity and specificity of secondary dose calculation for head and neck treatment plans

PURPOSE

Secondary dose calculation (SDC) with an independent algorithm is one option to perform plan-specific quality assurance (QA). While measurement-based QA can potentially detect errors in plan delivery, the dose values are typically only compared to calculations on homogeneous phantom geometries instead of patient CT data. We analyzed the sensitivity and specificity of an SDC software by purposely introducing different errors and determined thresholds for optimal decisions.

METHODS

Thirty head and neck VMAT plans and 30 modifications of those plans, including errors related to density and beam modelling, were recalculated using RadCalc with a Monte Carlo algorithm. Decision thresholds were obtained by receiver operating characteristics (ROC) analysis. For comparison, measurement-based QA using the ArcCHECK phantom was carried out and evaluated in the same way.

RESULTS

Despite optimized decision thresholds, none of the systems was able to reliably detect all errors. ArcCHECK analysis using a 2%/2 mm criterion with a threshold of 91.1% had an area under the curve (AUC) of 0.80. Evaluating differences in recalculated and planned DVH parameter of the target structures in RadCalc with a 2% threshold an AUC of 0.86 was achieved. Out-of-field deviations could be attributed to weaknesses in the beam model.

CONCLUSIONS

Secondary dose calculation with RadCalc is an alternative to established measurement-based phantom QA. Different tools catch different errors; therefore, a combination of approaches should be preferred.

In silico trial of simulation-free hippocampal-avoidance whole brain adaptive radiotherapy

Background and Purpose

Hippocampal-avoidance whole brain radiotherapy (HA-WBRT) can be a time-consuming process compared to conventional whole brain techniques, thus potentially limiting widespread utilization. Therefore, we evaluated the in silico clinical feasibility, via dose-volume metrics and timing, by leveraging a computed tomography (CT)-based commercial adaptive radiotherapy (ART) platform and workflow in order to create and deliver patient-specific, simulation-free HA-WBRT.

Materials and methods

Ten patients previously treated for central nervous system cancers with cone-beam computed tomography (CBCT) imaging were included in this study. The CBCT was the adaptive image-of-the-day to simulate first fraction on-board imaging. Initial contours defined on the MRI were rigidly matched to the CBCT. Online ART was used to create treatment plans at first fraction. Dose-volume metrics of these simulation-free plans were compared to standard-workflow HA-WBRT plans on each patient CT simulation dataset. Timing data for the adaptive planning sessions were recorded.

Results

For all ten patients, simulation-free HA-WBRT plans were successfully created utilizing the online ART workflow and met all constraints. The median hippocampi D100% was 7.8 Gy (6.6-8.8 Gy) in the adaptive plan vs 8.1 Gy (7.7-8.4 Gy) in the standard workflow plan. All plans required adaptation at first fraction due to both a failing hippocampal constraint (6/10 adaptive fractions) and sub-optimal target coverage (6/10 adaptive fractions). Median time for the adaptive session was 45.2 min (34.0-53.8 min).

Conclusions

Simulation-free HA-WBRT, with commercially available systems, was clinically feasible via plan-quality metrics and timing, in silico.

Dosimetric Validation of a GAN-Based Pseudo-CT Generation for MRI-Only Stereotactic Brain Radiotherapy

PURPOSE

Stereotactic radiotherapy (SRT) has become widely accepted as a treatment of choice for patients with a small number of brain metastases that are of an acceptable size, allowing for better target dose conformity, resulting in high local control rates and better sparing of organs at risk. An MRI-only workflow could reduce the risk of misalignment between magnetic resonance imaging (MRI) brain studies and computed tomography (CT) scanning for SRT planning, while shortening delays in planning. Given the absence of a calibrated electronic density in MRI, we aimed to assess the equivalence of synthetic CTs generated by a generative adversarial network (GAN) for planning in the brain SRT setting.

METHODS

All patients with available MRIs and treated with intra-cranial SRT for brain metastases from 2014 to 2018 in our institution were included. After co-registration between the diagnostic MRI and the planning CT, a synthetic CT was generated using a 2D-GAN (2D U-Net). Using the initial treatment plan (Pinnacle v9.10, Philips Healthcare), dosimetric comparison was performed using main dose-volume histogram (DVH) endpoints in respect to ICRU 91 guidelines (Dmax, Dmean, D2%, D50%, D98%) as well as local and global gamma analysis with 1%/1 mm, 2%/1 mm and 2%/2 mm criteria and a 10% threshold to the maximum dose. t-test analysis was used for comparison between the two cohorts (initial and synthetic dose maps).

RESULTS

184 patients were included, with 290 treated brain metastases. The mean number of treated lesions per patient was 1 (range 1-6) and the median planning target volume (PTV) was 6.44 cc (range 0.12-45.41). Local and global gamma passing rates (2%/2 mm) were 99.1 CI95% (98.1-99.4) and 99.7 CI95% (99.6-99.7) respectively (CI: confidence interval). DVHs were comparable, with no significant statistical differences regarding ICRU 91's endpoints.

CONCLUSIONS

Our study is the first to compare GAN-generated CT scans from diagnostic brain MRIs with initial CT scans for the planning of brain stereotactic radiotherapy. We found high similarity between the planning CT and the synthetic CT for both the organs at risk and the target volumes. Prospective validation is under investigation at our institution.