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Title: SU-F-J-81: Evaluation of Automated Deformable Registration Between Planning Computed Tomography (CT) and Daily Cone Beam CT Images Over the Course of Prostate Cancer Radiotherapy

Abstract

Purpose: To compute daily dose delivered during radiotherapy, deformable registration needs to be relatively fast, automated, and accurate. The aim of this study was to evaluate the performance of commercial deformable registration software for deforming between two modalities: planning computed tomography (pCT) images acquired for treatment planning and cone beam (CB) CT images acquired prior to each fraction of prostate cancer radiotherapy. Methods: A workflow was designed using MIM Software™ that aligned and deformed pCT into daily CBCT images in two steps: (1) rigid shifts applied after daily CBCT imaging to align patient anatomy to the pCT and (2) normalized intensity-based deformable registration to account for interfractional anatomical variations. The physician-approved CTV and organ and risk (OAR) contours were deformed from the pCT to daily CBCT over the course of treatment. The same structures were delineated on each daily CBCT by a radiation oncologist. Dice similarity coefficient (DSC) mean and standard deviations were calculated to quantify the deformable registration quality for prostate, bladder, rectum and femoral heads. Results: To date, contour comparisons have been analyzed for 31 daily fractions of 2 of 10 of the cohort. Interim analysis shows that right and left femoral head contours demonstrate the highest agreementmore » (DSC: 0.96±0.02) with physician contours. Additionally, deformed bladder (DSC: 0.81±0.09) and prostate (DSC: 0.80±0.07) have good agreement with physician-defined daily contours. Rectum contours have the highest variations (DSC: 0.66±0.10) between the deformed and physician-defined contours on daily CBCT imaging. Conclusion: For structures with relatively high contrast boundaries on CBCT, the MIM automated deformable registration provided accurate representations of the daily contours during treatment delivery. These findings will permit subsequent investigations to automate daily dose computation from CBCT. However, improved methods need to be investigated to improve deformable results for rectum contours.« less

Authors:
; ; ; ; ; ; ;  [1]
  1. University North Carolina, Chapel Hill, NC (United States)
Publication Date:
OSTI Identifier:
22632208
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; ANATOMY; BEAMS; BIOMEDICAL RADIOGRAPHY; BLADDER; CALCULATION METHODS; CALORIMETRY; COMPUTER CODES; COMPUTERIZED TOMOGRAPHY; HEAD; IMAGE PROCESSING; MEDICAL PERSONNEL; NEOPLASMS; PATIENTS; PERFORMANCE; PLANNING; PROSTATE; RADIATION DOSES; RADIOTHERAPY; RECTUM

Citation Formats

Matney, J, Hammers, J, Kaidar-Person, O, Wang, A, Chen, R, Das, S, Marks, L, and Mavroidis, P. SU-F-J-81: Evaluation of Automated Deformable Registration Between Planning Computed Tomography (CT) and Daily Cone Beam CT Images Over the Course of Prostate Cancer Radiotherapy. United States: N. p., 2016. Web. doi:10.1118/1.4955989.
Matney, J, Hammers, J, Kaidar-Person, O, Wang, A, Chen, R, Das, S, Marks, L, & Mavroidis, P. SU-F-J-81: Evaluation of Automated Deformable Registration Between Planning Computed Tomography (CT) and Daily Cone Beam CT Images Over the Course of Prostate Cancer Radiotherapy. United States. doi:10.1118/1.4955989.
Matney, J, Hammers, J, Kaidar-Person, O, Wang, A, Chen, R, Das, S, Marks, L, and Mavroidis, P. Wed . "SU-F-J-81: Evaluation of Automated Deformable Registration Between Planning Computed Tomography (CT) and Daily Cone Beam CT Images Over the Course of Prostate Cancer Radiotherapy". United States. doi:10.1118/1.4955989.
@article{osti_22632208,
title = {SU-F-J-81: Evaluation of Automated Deformable Registration Between Planning Computed Tomography (CT) and Daily Cone Beam CT Images Over the Course of Prostate Cancer Radiotherapy},
author = {Matney, J and Hammers, J and Kaidar-Person, O and Wang, A and Chen, R and Das, S and Marks, L and Mavroidis, P},
abstractNote = {Purpose: To compute daily dose delivered during radiotherapy, deformable registration needs to be relatively fast, automated, and accurate. The aim of this study was to evaluate the performance of commercial deformable registration software for deforming between two modalities: planning computed tomography (pCT) images acquired for treatment planning and cone beam (CB) CT images acquired prior to each fraction of prostate cancer radiotherapy. Methods: A workflow was designed using MIM Software™ that aligned and deformed pCT into daily CBCT images in two steps: (1) rigid shifts applied after daily CBCT imaging to align patient anatomy to the pCT and (2) normalized intensity-based deformable registration to account for interfractional anatomical variations. The physician-approved CTV and organ and risk (OAR) contours were deformed from the pCT to daily CBCT over the course of treatment. The same structures were delineated on each daily CBCT by a radiation oncologist. Dice similarity coefficient (DSC) mean and standard deviations were calculated to quantify the deformable registration quality for prostate, bladder, rectum and femoral heads. Results: To date, contour comparisons have been analyzed for 31 daily fractions of 2 of 10 of the cohort. Interim analysis shows that right and left femoral head contours demonstrate the highest agreement (DSC: 0.96±0.02) with physician contours. Additionally, deformed bladder (DSC: 0.81±0.09) and prostate (DSC: 0.80±0.07) have good agreement with physician-defined daily contours. Rectum contours have the highest variations (DSC: 0.66±0.10) between the deformed and physician-defined contours on daily CBCT imaging. Conclusion: For structures with relatively high contrast boundaries on CBCT, the MIM automated deformable registration provided accurate representations of the daily contours during treatment delivery. These findings will permit subsequent investigations to automate daily dose computation from CBCT. However, improved methods need to be investigated to improve deformable results for rectum contours.},
doi = {10.1118/1.4955989},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = {Wed Jun 15 00:00:00 EDT 2016},
month = {Wed Jun 15 00:00:00 EDT 2016}
}
  • Purpose: To investigate quantitatively the performance of different deformable-image-registration algorithms (DIR) with helical (HCT), axial (ACT) and cone-beam CT (CBCT) by evaluating the variations in the CT-numbers and lengths of targets moving with controlled motion-patterns. Methods: Four DIR-algorithms including demons, fast-demons, Horn-Schunk and Locas-Kanade from the DIRART-software are used to register CT-images of a mobile-phantom. A mobile-phantom is scanned with different imaging techniques that include helical, axial and cone-beam CT. The phantom includes three targets with different lengths that are made from water-equivalent material and inserted in low-density-foam which is moved with adjustable motion-amplitudes and frequencies. Results: Most of themore » DIR-algorithms are able to produce the lengths of the stationary-targets, however, they do not produce the CT-number values in CBCT. The image-artifacts induced by motion are more regular in CBCT imaging where the mobile-target elongation increases linearly with motion-amplitude. In ACT and HCT, the motion-artifacts are irregular where some mobile -targets are elongated or shrunk depending on the motion-phase during imaging. The DIR-algorithms are successful in deforming the images of the mobile-targets to the images of the stationary-targets producing the CT-number values and length of the target for motion-amplitudes < 20 mm. Similarly in ACT, all DIR-algorithms produced the actual CT-number and length of the stationary-targets for motion-amplitudes < 15 mm. As stronger motion-artifacts are induced in HCT and ACT, DIR-algorithms fail to produce CT-values and shape of the stationary-targets and fast-demons-algorithm has worst performance. Conclusion: Most of DIR-algorithms produce the CT-number values and lengths of the stationary-targets in HCT and ACT images that has motion-artifacts induced by small motion-amplitudes. As motion-amplitudes increase, the DIR-algorithms fail to deform mobile-target images to the stationary-images in HCT and ACT. In CBCT, DIR-algorithms are successful in producing length and shape of the stationary-targets, however, they fail to produce the accurate CT-number level.« less
  • Purpose: To estimate the dose distributions delivered to the patient in each treatment fraction using deformable image registration (DIR) and assess the radiobiological impact of the inter-fraction variations due to patient deformation and setup. Methods: The work is based on the cone beam CT (CBCT) images and treatment plans of two lung cancer patients. Both patients were treated with intensity modulated radiation therapy (IMRT) to 66Gy in 2Gy/fraction. The treatment plans were exported from the treatment planning system (TPS) to the Velocity AI where DIR was performed and the same deformation matrix was used for the deformation of the plannedmore » dose distribution and organ contours to each CBCT dataset. A radiobiological analysis was performed based on the radiobiological parameters of the involved organs at risk (OARs) and planning target volume (PTV). Using the complication free tumor control probability (P+) index, differences in P+ were observed between each CBCT as well as between CBCT and planning dose distributions. Results: The optimal CBCT P? values ranged from 91.6 % to 94.8 % for patient #1 and from 88.8 % to 90.6 % for patient #2. At the dose level of the clinical prescription, the CBCT P+ values ranged from 80.3% to 80.7% for patient #1 and from 80.7% to 81.0% for the patient #2. The planning CT P+ values were 81.0% and 80.7% for the two patients, respectively. These differences emphasize the significance of using the radiobiological analysis when assessing changes in the dose distribution due to the tumor motion and lung deformations. Conclusion: Daily setup variations yield to differences in the actual dose delivered versus the planned one. The observed differences were rather small when only looking at the dosimetric comparison of the dose distributions, however the radiobiology analysis was able to detect clinically relevant differences among the studied dose distributions.« less
  • Purpose: To investigate quantitatively the displacement-vector-fields (DVF) obtained from different deformable image registration algorithms (DIR) in helical (HCT), axial (ACT) and cone-beam CT (CBCT) to register CT images of a mobile phantom and its correlation with motion amplitudes and frequencies. Methods: HCT, ACT and CBCT are used to image a mobile phantom which includes three targets with different sizes that are manufactured from water-equivalent material and embedded in low density foam. The phantom is moved with controlled motion patterns where a range of motion amplitudes (0–40mm) and frequencies (0.125–0.5Hz) are used. The CT images obtained from scanning of the mobilemore » phantom are registered with the stationary CT-images using four deformable image registration algorithms including demons, fast-demons, Horn-Schunk and Locas-Kanade from DIRART software. Results: The DVF calculated by the different algorithms correlate well with the motion amplitudes that are applied on the mobile phantom where maximal DVF increase linearly with the motion amplitudes of the mobile phantom in CBCT. Similarly in HCT, DVF increase linearly with motion amplitude, however, its correlation is weaker than CBCT. In ACT, the DVF’s do not correlate well with the motion amplitudes where motion induces strong image artifacts and DIR algorithms are not able to deform the ACT image of the mobile targets to the stationary targets. Three DIR-algorithms produce comparable values and patterns of the DVF for certain CT imaging modality. However, DVF from fast-demons deviated strongly from other algorithms at large motion amplitudes. Conclusion: In CBCT and HCT, the DVF correlate well with the motion amplitude of the mobile phantom. However, in ACT, DVF do not correlate with motion amplitudes. Correlations of DVF with motion amplitude as in CBCT and HCT imaging techniques can provide information about unknown motion parameters of the mobile organs in real patients as demonstrated in this phantom visibility study.« less
  • Purpose: We introduce a new method combined with the deformable image registration (DIR) and regions-of-interest mapping (ROIM) technique to accurately calculate dose on daily CBCT for esophageal cancer. Methods: Patients suffered from esophageal cancer were enrolled in the study. Prescription was set to 66 Gy/30 F and 54 Gy/30 F to the primary tumor (PTV66) and subclinical disease (PTV54) . Planning CT (pCT) were segmented into 8 substructures in terms of their differences in physical density, such as gross target volume (GTV), venae cava superior (SVC), aorta, heart, spinal cord, lung, muscle and bones. The pCT and its substructures weremore » transferred to the MIM software to readout their mean HU values. Afterwards, a deformable planning CT to daily KV-CBCT image registration method was then utilized to acquire a new structure set on CBCT. The newly generated structures on CBCT were then transferred back to the treatment planning system (TPS) and its HU information were overridden manually with mean HU values obtained from pCT. Finally, the treatment plan was projected onto the CBCT images with the same beam arrangements and monitor units (MUs) to accomplish dose calculation. Planning target volume (PTV) and organs at risk (OARs) from both of the pCT and CBCT were compared to evaluate the dose calculation accuracy. Results: It was found that the dose distribution in the CBCT showed little differences compared to the pCT, regardless of whether PTV or OARs were concerned. Specifically, dose variation in GTV, PTV54, PTV66, SVC, lung and heart were within 0.1%. The maximum dose variation was presented in the spinal cord, which was up to 2.7% dose difference. Conclusion: The proposed method combined with DIR and ROIM technique to accurately calculate dose distribution on CBCT for esophageal cancer is feasible.« less
  • Purpose: We evaluated the performance of two commercially available and one open source B-Spline deformable image registration (DIR) algorithms between T2-weighted MRI and treatment planning CT using the DICE indices. Methods: CT simulation (CT-SIM) and MR simulation (MR-SIM) for four prostate cancer patients were conducted on the same day using the same setup and immobilization devices. CT images (120 kVp, 500 mAs, voxel size = 1.1x1.1x3.0 mm3) were acquired using an open-bore CT scanner. T2-weighted Turbo Spine Echo (T2W-TSE) images (TE/TR/α = 80/4560 ms/90°, voxel size = 0.7×0.7×2.5 mm3) were scanned on a 1.0T high field open MR-SIM. Prostates, seminalmore » vesicles, rectum and bladders were delineated on both T2W-TSE and CT images by the attending physician. T2W-TSE images were registered to CT images using three DIR algorithms, SmartAdapt (Varian), Velocity AI (Velocity) and Elastix (Klein et al 2010) and contours were propagated. DIR results were evaluated quantitatively or qualitatively by image comparison and calculating organ DICE indices. Results: Significant differences in the contours of prostate and seminal vesicles were observed between MR and CT. On average, volume changes of the propagated contours were 5%, 2%, 160% and 8% for the prostate, seminal vesicles, bladder and rectum respectively. Corresponding mean DICE indices were 0.7, 0.5, 0.8, and 0.7. The intraclass correlation coefficient (ICC) was 0.9 among three algorithms for the Dice indices. Conclusion: Three DIR algorithms for CT/MR registration yielded similar results for organ propagation. Due to the different soft tissue contrasts between MRI and CT, organ delineation of prostate and SVs varied significantly, thus efforts to develop other DIR evaluation metrics are warranted. Conflict of interest: Submitting institution has research agreements with Varian Medical System and Philips Healthcare.« less