Treatment plan verification: A review on the comparison of dose distributions

Regression fitting megavoltage depth dose curves to determine material relative electron density in radiotherapy

The relative electron density (RED) parameter is ubiquitous throughout radiotherapy for clinical dosimetry and treatment planning purposes as it provides a more accurate description of the relevant radiological properties over mass density alone. RED is in practice determined indirectly from calibrated CT Hounsfield Units (HU). While CT images provide useful 3D information, the spectral differences between CT and clinical LINAC beams may impact the validity of the CT-ED calibration, especially in the context of novel tissue-mimicking materials where deviations from biologically typical atomic number to atomic weight ratios 〈Z/A〉 occur and/or high-Z materials are present. A theoretical basis for determining material properties directly in a clinical beam spectrum via an electron-density equivalent pathlength (eEPL) method has been previously established. An experimental implementation of this approach is introduced whereby material-specific measured percentage depth dose curves (PDDs) are regressed to a PDD measured in a reference material (water), providing an inference of 〈Z/A〉, which when combined with the physical density provides a determination of RED. This method is validated over a range of tissue-mimicking materials and compared against the standard CT output, as well as compositional information obtained from the manufacturer's specifications. The measured PDD regression method shows consistent results against both manufacturer-provided and CT-derived values between 0.9 and 1.15 RED. Outside of this soft-tissue range a trend was observed whereby the 〈Z/A〉 determined becomes unrealistic indicating the method is no longer reporting RED alone and the assumptions around the eEPL model are constrained. Within the soft-tissue RED range of validity, the regression method provides a practical and robust characterisation for unknown materials in the clinical setting and may be used to improve on the CT derived RED where high Z material components are suspected.

Isodose surface differences: A novel tool for the comparison of dose distributions

BACKGROUND

Comparing dose distributions is a routine task in radiotherapy, mainly in patient-specific quality assurance (PSQA). Currently, the evaluation of the dose distributions is being performed mainly with statistical methods, which could underestimate the clinical importance of the spotted differences, as per the literature.

PURPOSE

This paper aims to provide proof-of-concept for a novel dose distribution comparison method based on the difference of the isodose surfaces. The new method connects acceptance tolerance to QA limitations (equipment capabilities) and integrates a clinical approach into the analysis procedure.

METHODS

The distance of dose points from the isocenter can be used as a function to define the shape of an isodose surface expressed as a histogram. Isodose surface differences (ISD) are defined as the normalized differences of reference and evaluated surface histograms plotted against their corresponding isodose. Acceptance tolerances originate from actual QA tolerances and are presented clinically intuitively. The ISD method was compared to the gamma index using intentionally erroneous VMAT and IMRT plans.

RESULTS

Results revealed that the ISD method is sensitive to all errors induced in the plans. Discrepancies are presented per isodose, enabling the evaluation of the plan in two regions representing PTV and Normal Tissue. ISD manages to flag errors that would remain undetected under the gamma analysis.

CONCLUSION

The ISD method is a meaningful, QA-related, registration-free, and clinically oriented technique of dose distribution evaluation. This method can be used either as a standalone or an auxiliary tool to the well-established evaluation procedures, overcoming significant limitations reported in the literature.

Preliminary study on dosimetry characteristics of a novel cylindrical dose verification system

OBJECTIVE

To develop a novel ionization chamber array dosimetry system, study its dosimetry characteristics, and perform preliminary tests for plan dose verification.

METHODS

The dosimetry characteristics of this new array were tested, including short-term and long-term reproducibility, dose linearity, dose rate dependence, field size dependence, and angular dependence. The open field and MLC field plans were designed for dose testing. Randomly select 30 patient treatment plans (10 intensity-modulated radiation therapy [IMRT] plans and 20 volumetric modulated arc therapy [VMAT] plans) that have undergone dose verification using Portal Dosimetry to perform verification measurement and evaluate dose verification test results.

RESULTS

The dosimetry characteristics of the arrays all performed well. The gamma passing rates (3%/2 mm) were more than 96% for the combined open field and MLC field plans. The average gamma pass rates were (99.54 ± 0.58)% and (96.70 ± 3.41)% for the 10 IMRT plans and (99.32 ± 0.89)% and (94.91 ± 6.01)% for the 20 VMAT plans at the 3%/2 mm and 2%/2 mm criteria, respectively, which is similar to the Portal Dosimetry's measurement results.

CONCLUSIONS

This novel ionization chamber array demonstrates good dosimetry characteristics and is suitable for clinical IMRT and VMAT plan verifications.

The geometric and dosimetric accuracy of kilovoltage cone beam computed tomography images for adaptive treatment: a systematic review

Objectives

To provide an overview and meta-analysis of different techniques adopted to accomplish kVCBCT for dose calculation and automated segmentation.

Methods

A systematic review and meta-analysis were performed on eligible studies demonstrating kVCBCT-based dose calculation and automated contouring of different tumor features. Meta-analysis of the performance was accomplished on the reported γ analysis and dice similarity coefficient (DSC) score of both collected results as three subgroups (head and neck, chest, and abdomen).

Results

After the literature scrutinization (n = 1008), 52 papers were recognized for the systematic review. Nine studies of dosimtric studies and eleven studies of geometric analysis were suitable for inclusion in meta-analysis. Using kVCBCT for treatment replanning depends on a method used. Deformable Image Registration (DIR) methods yielded small dosimetric error (≤2%), γ pass rate (≥90%) and DSC (≥0.8). Hounsfield Unit (HU) override and calibration curve-based methods also achieved satisfactory yielded small dosimetric error (≤2%) and γ pass rate ((≥90%), but they are prone to error due to their sensitivity to a vendor-specific variation in kVCBCT image quality.

Conclusions

Large cohorts of patients ought to be undertaken to validate methods achieving low levels of dosimetric and geometric errors. Quality guidelines should be established when reporting on kVCBCT, which include agreed metrics for reporting on the quality of corrected kVCBCT and defines protocols of new site-specific standardized imaging used when obtaining kVCBCT images for adaptive radiotherapy.

Advances in knowledge

This review gives useful knowledge about methods making kVCBCT feasible for kVCBCT-based adaptive radiotherapy, simplifying patient pathway and reducing concomitant imaging dose to the patient.

Absorbed dose calculation for a realistic CT-derived mouse phantom irradiated with a standard Cs-137 cell irradiator using a Monte Carlo method

Computed tomography (CT) derived Monte Carlo (MC) phantoms allow dose determination within small animal models that is not feasible with in-vivo dosimetry. The aim of this study was to develop a CT-derived MC phantom generated from a mouse with a xenograft tumour that could then be used to calculate both the dose heterogeneity in the tumour volume and out of field scattered dose for pre-clinical small animal irradiation experiments. A BEAMnrc Monte-Carlo model has been built of our irradiation system that comprises a lead collimator with a 1 cm diameter aperture fitted to a Cs-137 gamma irradiator. The MC model of the irradiation system was validated by comparing the calculated dose results with dosimetric film measurement in a polymethyl methacrylate (PMMA) phantom using a 1D gamma-index analysis. Dose distributions in the MC mouse phantom were calculated and visualized on the CT-image data. Dose volume histograms (DVHs) were generated for the tumour and organs at risk (OARs). The effect of the xenographic tumour volume on the scattered out of field dose was also investigated. The defined gamma index analysis criteria were met, indicating that our MC simulation is a valid model for MC mouse phantom dose calculations. MC dose calculations showed a maximum out of field dose to the mouse of 7% of Dmax. Absorbed dose to the tumour varies in the range 60%-100% of Dmax. DVH analysis demonstrated that tumour received an inhomogeneous dose of 12 Gy-20 Gy (for 20 Gy prescribed dose) while out of field doses to all OARs were minimized (1.29 Gy-1.38 Gy). Variation of the xenographic tumour volume exhibited no significant effect on the out of field scattered dose to OARs. The CT derived MC mouse model presented here is a useful tool for tumour dose verifications as well as investigating the doses to normal tissue (in out of field) for preclinical radiobiological research.

Evaluation of Dose Calculation Based on Cone-Beam CT Using Different Measuring Correction Methods for Head and Neck Cancer Patients

Purpose: To investigate and compare 2 cone-beam computed tomography (CBCT) correction methods for CBCT-based dose calculation. Materials and Methods: Routine CBCT image sets of 12 head and neck cancer patients who received volumetric modulated arc therapy (VMAT) treatment were retrospectively analyzed. The CBCT images obtained using an on-board imager (OBI) at the first treatment fraction were firstly deformable registered and padded with the kVCT images to provide enough anatomical information about the tissues for dose calculation. Then, 2 CBCT correction methods were developed and applied to correct CBCT Hounsfield unit (HU) values. One method (HD method) is based on protocol-specific CBCT HU to physical density (HD) curve, and the other method (HM method) is based on histogram matching (HM) of HU value. The corrected CBCT images (CBCT_HD and CBCT_HM for HD and HM methods) were imported into the original planning system for dose calculation based on the HD curve of kVCT (the planning CT). The dose computation result was analyzed and discussed to compare these 2 CBCT-correction methods. Results: Dosimetric parameters, such as the D_mean, D_max and D_5% of the target volume in CBCT plan doses, were higher than those in the kVCT plan doses; however, the deviations were less than 2%. The D_2%, in parallel organs such as the parotid glands, the deviations from the CBCT_HM plan dose were less than those of the CBCT_HD plan dose. The differences were statistically significant (P < .05). Meanwhile, the V₃₀ value based on the HM method was better than that based on the HD method in the oral cavity region (P = .016). In addition, we also compared the γ passing rates of kVCT plan doses with the 2 CBCT plan doses, and negligible differences were found. Conclusion: The HM method was more suitable for head and neck cancer patients than the HD one. Furthermore, with the CBCT_HM-based method, the dose calculation result better matches the kVCT-based dose calculation.

Implementation of TG-218 for patient specific QA Tolerance and Action Limits determination: Gamma passing rates evaluation using 3DVH software

PURPOSE

To determine the tolerance (TL) and action limits (AL) of gamma passing rates (%GP) for Volumetric-Modulated Arc Therapy (VMAT) patient-specific quality assurance (PSQA), according to the AAPM TG-218 recommendations, and to evaluate comparatively the clinical relevance of 2D%GP and 3D%GP.

MATERIALS AND METHODS

PSQA was performed for 100 head and neck (H&N) and 73 prostate cancer VMAT treatment plans. Measurements were acquired using a cylindrical water equivalent phantom, hollow in the center, allowing measurements with homogeneous or heterogeneous inserts. LINAC delivered dose distributions were compared to the ones calculated from the treatment planning system (TPS) through gamma index. TL and AL were determined through the computation of 2D%GP, using the recommended acceptance criteria. Dose-volume histograms (DVH) were reconstructed from the measurements using a commercially available software, to detect the dosimetric differences (%DE) between the compared dose distributions. Utilizing the estimated dose on the patient anatomy, structure specific %GP (3D%GP) were calculated. The 3D%GP were compared to the 2D%GP ones, based on their correlation with the %DE. Each metric's sensitivity was determined through receiver operator characteristic (ROC) analysis.

RESULTS

TL and AL were in concordance with the universal ones, regarding the prostate cancer cases, but were lower for the H&N cases. Evaluation of %DE did not deem the plans unacceptable. The 2D%GP and the 3D%GP did not differ significantly regarding their correlation with %DE. For prostate plans, %GP sensitivity was higher than for H&N cases.

CONCLUSIONS

Determination of institutional specific TL and AL allow the monitoring of the PSQA procedure, yet for plans close to the limits clinically relevant metrics should be used before they are deemed unacceptable, for the process to be of higher sensitivity and efficiency. This article is protected by copyright. All rights reserved.

Comparative performance analysis of 2D and 3D gamma metrics for patient specific QA in VMAT using Octavius 4D with 2D-Array 1500

INTRODUCTION

Gamma pass percentage (GPP) is the predominant metric used for Patient Specific Quality Assurance (PSQA) in radiation therapy. The dimensionality of the measurement geometry in PSQA has evolved from 2D planar to 3D planar, and presently to state-of-the-art 3D volumetric geometry. We aim to critically examine the performance of the three-dimensional gammas vis-à-vis the older gamma metrics of lower dimensionality to determine their mutual fungibility in PSQA, using clinically approved Volumetric Arc Therapy (VMAT) plans.

METHODS AND MATERIALS

Gamma pass percentages derived from PSQA for VMAT plans using Octavius 4D phantom with 2D-Array 1500 and its proprietary software were recorded. 2D planar, 3D planar, and 3D volumetric gamma pass percentages were retrospectively extracted for multiple treatment plans at three sites, using three acceptance limits, and for two modes of normalization. The differences in mean pass percentages, and the pairwise correlation between geometries were calculated within limits of statistical significance.

RESULTS

A significant increase in mean pass rates was observed from 2D planar to 3D planar geometries. The difference was less pronounced from 3D planar to 3D volumetric. 2D planar v/s 3D planar showed a significant degree of correlation among themselves, which was not seen against most of the 3D volumetric pass rates.

CONCLUSION

The mean gamma pass rates show conclusive evidence of the benefits of shifting from 2D planar to higher dimensions measurement geometries, but the benefits of using 3D volumetric compared to 3D planar is not always unequivocal. The correlations show mixed results regarding the interdependence of pass percentages at different geometries.

Assessment of the Sun Nuclear ArcCHECK to detect errors in 6MV FFF VMAT delivery of brain SABR using ROC analysis

Institutions use a range of different detector systems for patient-specific quality assurance (QA) measurements conducted to assure that the dose delivered by a patient's radiotherapy treatment plan matches the calculated dose distribution. However, the ability of different detectors to detect errors from different sources is often unreported. This study contains a systematic evaluation of Sun Nuclear's ArcCHECK in terms of the detectability of potential machine-related treatment errors. The five investigated sources of error were multileaf collimator (MLC) leaf positions, gantry angle, collimator angle, jaw positions, and dose output. The study encompassed the clinical treatment plans of 29 brain cancer patients who received stereotactic ablative radiotherapy (SABR). Six error magnitudes were investigated per source of error. In addition, the Eclipse AAA beam model dosimetric leaf gap (DLG) parameter was varied with four error magnitudes. Error detectability was determined based on the area under the receiver operating characteristic (ROC) curve (AUC). Detectability of DLG errors was good or excellent (AUC >0.8) at an error magnitude of at least ±0.4 mm, while MLC leaf position and gantry angle errors reached good or excellent detectability at error magnitudes of at least 1.0 mm and 0.6°, respectively. Ideal thresholds, that is, gamma passing rates, to maximize sensitivity and specificity ranged from 79.1% to 98.7%. The detectability of collimator angle, jaw position, and dose output errors was poor for all investigated error magnitudes, with an AUC between 0.5 and 0.6. The ArcCHECK device's ability to detect errors from treatment machine-related sources was evaluated, and ideal gamma passing rate thresholds were determined for each source of error. The ArcCHECK was able to detect errors in DLG value, MLC leaf positions, and gantry angle. The ArcCHECK was unable to detect the studied errors in collimator angle, jaw positions, and dose output.

Patient-specific IMRT QA verification using machine learning and gamma radiomics

Gamma function is the standard methodology for comparing dose distributions. It is calculated in dedicated software, and its results verification is not performed. Thus we developed an automatic tool for patient-specific QA results verification through high accuracy machine learning (ML) models based on the radiomics characteristics extraction from gamma images. We used 158 patient-specific QA tests and extracted 105 radiomics features from each gamma image. Three random forest models were developed (ML I, ML II, and ML III). ML I and ML II verified the gamma image approval using criteria of 2%/2mm/15% threshold and 3%/3mm/15% threshold, respectively. ML III verified if the gamma analyzes software recommended protocol was followed to detect if the TPS grid modification step was done. The models were based on the most important features selected using the mean decreased impurity, and their performances were evaluated. ML I included 25 features. Its accuracy was 0.85 using the test set and 0.84 using dataset B. ML II included 10 features, and its accuracy with the test set was 0.98; the same value was achieved using the never seen data (dataset B). The First-order 10th percentile feature was identified as a feature strongly related to the approved classification. ML III selected 23 features with an accuracy of 0.99 for test set and 0.98 for dataset B. An automatic workflow example for gamma analyses QA results verification could be proposed combining the models to detect grid inconsistencies on software evaluation, followed by the test approval classification.