Assessment of daily dose accumulation for robustly optimized intensity modulated proton therapy treatment of prostate cancer

PURPOSE

To implement a daily CBCT based dose accumulation technique in order to assess ideal robust optimization (RO) parameters for IMPT treatment of prostate cancer.

METHODS

Ten prostate cancer patients previously treated with VMAT and having daily CBCT were included. First, RO-IMPT plans were created with ± 3 mm and ± 5 mm patient setup and ± 3% proton range uncertainties, respectively. Second, the planning CT (pCT) was deformably registered to the CBCT to create a synthetic CT (sCT). Both daily and weekly sampling strategies were employed to determine optimal dose accumulation frequency. Doses were recalculated on sCTs for both ± 3 mm/±3% and ± 5 mm/±3% uncertainties and were accumulated back to the pCT. Accumulated doses generated from ± 3 mm/±3% and ± 5 mm/±3% RO-IMPT plans were evaluated using the clinical dose volume constraints for CTV, bladder, and rectum.

RESULTS

Daily accumulated dose based on both ± 3mm/±3% and ±5 mm/±3% uncertainties for RO-IMPT plans resulted in satisfactory CTV coverage (RO-IMPT_3mm/3% CTV_V95 = 99.01 ± 0.87% vs. RO-IMPT_5mm/3% CTV_V95 = 99.81 ± 0.2%, P = 0.002). However, the accumulated dose based on ± 3 mm/3% RO-IMPT plans consistently provided greater OAR sparing than ±5 mm/±3% RO-IMPT plans (RO-IMPT_3mm/3% rectum_V65Gy = 2.93 ± 2.39% vs. RO-IMPT_5mm/3% rectum_V65Gy = 4.38 ± 3%, P < 0.01; RO-IMPT_3mm/3% bladder_V65Gy = 5.2 ± 7.12% vs. RO-IMPT_5mm/3% bladder_V65Gy = 7.12 ± 9.59%, P < 0.01). The gamma analysis showed high dosimetric agreement between weekly and daily accumulated dose distributions.

CONCLUSIONS

This study demonstrated that for RO-IMPT optimization, ±3mm/±3% uncertainty is sufficient to create plans that meet desired CTV coverage while achieving superior sparing to OARs when compared with ± 5 mm/±3% uncertainty. Furthermore, weekly dose accumulation can accurately estimate the overall dose delivered to prostate cancer patients.

Evaluation of deformable image registration accuracy for CT images of the thorax region

PURPOSE

Evaluate the performance of three commercial deformable image registration (DIR) solutions on computed tomography (CT) image-series of the thorax.

METHODS

DIRs were performed on CT image-series of a thorax phantom with tumor inserts and on six 4-dimensional patient CT image-series of the thorax. The center of mass shift (CMS), dice similarity coefficient (DSC) and dose-volume-histogram (DVH) parameters were used to evaluate the accuracy. Dose calculations on deformed patient images were compared to calculations on un-deformed images for the gross tumor volume (GTV) (D_mean, D_98%), lung (V_20Gy, V_12Gy), heart and spinal cord (D_2%).

RESULTS

Phantom structures with constant volume and shifts ≤30 mm were reproduced with visually acceptable accuracy (DSC ≥ 0.91, CMS ≤ 0.9 mm) for all software solutions. Deformations including volume changes were less accurate with 9/12 DIRs considered visually unacceptable. In patients, organs were reproduced with DSC ≥ 0.83. GTV shifts ≤1.6 cm were reproduced with visually acceptable accuracy by all software while larger shifts resulted in failures for at least one of the software. In total, the best software succeeded in 18/25 DIRs while the worst succeeded in 12/25 DIRs. Visually acceptable DIRs resulted in deviations ≤3.0% of the prescribed dose and ≤3.6% of the total structure volume in the evaluated DVH-parameters.

CONCLUSIONS

The take home message from the results of this study is the importance to have a visually acceptable registration. DSC and CMS are not predictive of the associated dose deviation. Visually acceptable DIRs implied dose deviations ≤3.0%.

Accuracy of deformable image registration on magnetic resonance images in digital and physical phantoms

PURPOSE

Accurate deformable image registration is necessary for longitudinal studies. The error associated with commercial systems has been evaluated using computed tomography (CT). Several in-house algorithms have been evaluated for use with magnetic resonance imaging (MRI), but there is still relatively little information about MRI deformable image registration. This work presents an evaluation of two deformable image registration systems, one commercial (Velocity) and one in-house (demons-based algorithm), with MRI using two different metrics to quantify the registration error.

METHODS

The registration error was analyzed with synthetic MR images. These images were generated from interpatient and intrapatient variation models trained on 28 patients. Four synthetic post-treatment images were generated for each of four synthetic pretreatment images, resulting in 16 image registrations for both the T1- and T2-weighted images. The synthetic post-treatment images were registered to their corresponding synthetic pretreatment image. The registration error was calculated between the known deformation vector field and the generated deformation vector field from the image registration system. The registration error was also analyzed using a porcine phantom with ten implanted 0.35-mm diameter gold markers. The markers were visible on CT but not MRI. CT, T1-weighted MR, and T2-weighted MR images were taken in four different positions. The markers were contoured on the CT images and rigidly registered to their corresponding MR images. The MR images were deformably registered and the distance between the projected marker location and true marker location was measured as the registration error.

RESULTS

The synthetic images were evaluated only on Velocity. Root mean square errors (RMSEs) of 0.76 mm in the left-right (LR) direction, 0.76 mm in the anteroposterior (AP) direction, and 0.69 mm in the superior-inferior (SI) direction were observed for the T1-weighted MR images. RMSEs of 1.1 mm in the LR direction, 0.75 mm in the AP direction, and 0.81 mm in the SI direction were observed for the T2-weighted MR images. The porcine phantom MR images, when evaluated with Velocity, had RMSEs of 1.8, 1.5, and 2.7 mm in the LR, AP, and SI directions for the T1-weighted images and 1.3, 1.2, and 1.6 mm in the LR, AP, and SI directions for the T2-weighted images. When the porcine phantom images were evaluated with the in-house demons-based algorithm, RMSEs were 1.2, 1.5, and 2.1 mm in the LR, AP, and SI directions for the T1-weighted images and 0.81, 1.1, and 1.1 mm in the LR, AP, and SI directions for the T2-weighted images.

CONCLUSIONS

The MRI registration error was low for both Velocity and the in-house demons-based algorithm according to both image evaluation methods, with all RMSEs below 3 mm. This implies that both image registration systems can be used for longitudinal studies using MRI.