Evaluation of a novel CBCT conversion method implemented in a treatment planning system

BACKGROUND

To evaluate a novel CBCT conversion algorithm for dose calculation implemented in a research version of a treatment planning system (TPS).

METHODS

The algorithm was implemented in a research version of RayStation (v. 11B-DTK, RaySearch, Stockholm, Sweden). CBCTs acquired for each ten head and neck (HN), gynecology (GYN) and lung cancer (LNG) patients were collected and converted using the new algorithm (CBCTc). A bulk density overriding technique implemented in the same version of the TPS was used for comparison (CBCTb). A deformed CT (dCT) was created by using deformable image registration of the planning CT (pCT) to the CBCT to reduce anatomical changes. All treatment plans were recalculated on the pCT, dCT, CBCTc and the CBCTb. The resulting dose distributions were analyzed using the MICE toolkit (NONPIMedical AB Sweden, Umeå) with local gamma analysis, with 1% dose difference and 1 mm distance to agreement criteria. A Wilcoxon paired rank sum test was applied to test the differences in gamma pass rates (GPRs). A p value smaller than 0.05 considered statistically significant.

RESULTS

The GPRs for the CBCTb method were systematically lower compared to the CBCTc method. Using the 10% dose threshold and the dCT as reference the median GPRs were for the CBCTc method were 100% and 99.8% for the HN and GYN cases, respectively. Compared to that the GPRs of the CBCTb method were lower with values of 99.8% and 98.0%, for the HN and GYN cases, respectively. The GPRs of the LNG cases were 99.9% and 97.5% for the CBCTc and CBCTb method, respectively. These differences were statistically significant. The main differences between the dose calculated on the CBCTs and the pCTs were found in regions near air/tissue interfaces, which are also subject to anatomical variations.

CONCLUSION

The dose distribution calculated using the new CBCTc method showed excellent agreement with the dose calculated using dCT and pCT and was superior to the CBCTb method. The main reasons for deviations of the calculated dose distribution were caused by anatomical variations between the pCT and the corrected CBCT.

Utilising pseudo-CT data for dose calculation and plan optimization in adaptive radiotherapy

To quantify the dose calculation error and resulting optimization uncertainty caused by performing inverse treatment planning on inaccurate electron density data (pseudo-CT) as needed for adaptive radiotherapy and Magnetic Resonance Imaging (MRI) based treatment planning. Planning Computer Tomography (CT) data from 10 cervix cancer patients was used to generate 4 pseudo-CT data sets. Each pseudo-CT was created based on an available method of assigning electron density to an anatomic image. An inversely modulated radiotherapy (IMRT) plan was developed on each planning CT. The dose calculation error caused by each pseudo-CT data set was quantified by comparing the dose calculated each pseudo-CT data set with that calculated on the original planning CT for the same IMRT plan. The optimization uncertainty introduced by the dose calculation error was quantified by re-optimizing the same optimization parameters on each pseudo-CT data set and comparing against the original planning CT. Dose differences were quantified by assessing the Equivalent Uniform Dose (EUD) for targets and relevant organs at risk. Across all pseudo-CT data sets and all organs, the absolute mean dose calculation error was 0.2 Gy, and was within 2 % of the prescription dose in 98.5 % of cases. Then absolute mean optimisation error was 0.3 Gy EUD, indicating that that inverse optimisation is impacted by the dose calculation error. However, the additional uncertainty introduced to plan optimisation is small compared the sources of variation which already exist. Use of inaccurate electron density data for inverse treatment planning results in a dose calculation error, which in turn introduces additional uncertainty into the plan optimization process. In this study, we showed that both of these effects are clinically acceptable for cervix cancer patients using four different pseudo-CT data sets. Dose calculation and inverse optimization on pseudo-CT is feasible for this patient cohort.

Investigation of the usability of conebeam CT data sets for dose calculation

BACKGROUND

To investigate the feasibility and accuracy of dose calculation in cone beam CT (CBCT) data sets.

METHODS

Kilovoltage CBCT images were acquired with the Elekta XVI system, CT studies generated with a conventional multi-slice CT scanner (Siemens Somatom Sensation Open) served as reference images. Material specific volumes of interest (VOI) were defined for commercial CT Phantoms (CATPhan and Gammex RMI) and CT values were evaluated in CT and CBCT images. For CBCT imaging, the influence of image acquisition parameters such as tube voltage, with or without filter (F1 or F0) and collimation on the CT values was investigated. CBCT images of 33 patients (pelvis n = 11, thorax n = 11, head n = 11) were compared with corresponding planning CT studies. Dose distributions for three different treatment plans were calculated in CT and CBCT images and differences were evaluated. Four different correction strategies to match CT values (HU) and density (D) in CBCT images were analysed: standard CT HU-D table without adjustment for CBCT; phantom based HU-D tables; patient group based HU-D tables (pelvis, thorax, head); and patient specific HU-D tables.

RESULTS

CT values in the CBCT images of the CATPhan were highly variable depending on the image acquisition parameters: a mean difference of 564 HU +/- 377 HU was calculated between CT values determined from the planning CT and CBCT images. Hence, two protocols were selected for CBCT imaging in the further part of the study and HU-D tables were always specific for these protocols (pelvis and thorax with M20F1 filter, 120 kV; head S10F0 no filter, 100 kV). For dose calculation in real patient CBCT images, the largest differences between CT and CBCT were observed for the standard CT HU-D table: differences were 8.0% +/- 5.7%, 10.9% +/- 6.8% and 14.5% +/- 10.4% respectively for pelvis, thorax and head patients using clinical treatment plans. The use of patient and group based HU-D tables resulted in small dose differences between planning CT and CBCT: 0.9% +/- 0.9%, 1.8% +/- 1.6%, 1.5% +/- 2.5% for pelvis, thorax and head patients, respectively. The application of the phantom based HU-D table was acceptable for the head patients but larger deviations were determined for the pelvis and thorax patient populations.

CONCLUSION

The generation of three HU-D tables specific for the anatomical regions pelvis, thorax and head and specific for the corresponding CBCT image acquisition parameters resulted in accurate dose calculation in CBCT images. Once these HU-D tables are created, direct dose calculation on CBCT datasets is possible without the need of a reference CT images for pixel value calibration.

Shading correction algorithm for improvement of cone-beam CT images in radiotherapy

Cone-beam CT (CBCT) images have recently become an established modality for treatment verification in radiotherapy. However, identification of soft-tissue structures and the calculation of dose distributions based on CBCT images is often obstructed by image artefacts and poor consistency of density calibration. A robust method for voxel-by-voxel enhancement of CBCT images using a priori knowledge from the planning CT scan has been developed and implemented. CBCT scans were enhanced using a low spatial frequency grey scale shading function generated with the aid of a planning CT scan from the same patient. This circumvents the need for exact correspondence between CBCT and CT and the process is robust to the appearance of unshared features such as gas pockets. Enhancement was validated using patient CBCT images. CT numbers in regions of fat and muscle tissue in the processed CBCT were both within 1% of the values in the planning CT, as opposed to 10-20% different for the original CBCT. Visual assessment of processed CBCT images showed improvement in soft-tissue visibility, although some cases of artefact introduction were observed.