Rectal deformation management with IGRT in prostate radiotherapy: Can it be managed with rigid alignment alone?

PURPOSE: It is challenging to achieve appropriate target coverage of the prostate with Image Guided Radiation Therapy (IGRT) while simultaneously constraining rectal doses within planned values when there is significant variability in rectal filling and shape. We investigated if rectum planning goals can be fulfilled using rigid CBCT-based on-board alignment to account for interfraction rectal deformations. METHODS: Delivered rectal doses corresponding to prostate alignment ("PR") and anterior rectum alignment ("AR") for 239 daily treatments from 13 patients are reported. Rectal doses were estimated by rigidly mapping the planned dose on the daily CT derived from the daily CBCT according to respective alignment shifts. Rectum V95% (rV95%) was used for analyses. RESULTS: Compared to "PR", "AR" alignment increased rV95% for an average of 34.4% across all patients. rV95% (cc) averaged over all fractions was significant from planning values for 10/13 patients for "PR" and for 9/13 for "AR". 3/13 patients had reproducible anatomy. Of patients with non-reproducible anatomy, three had dosimetrically more favorable, while seven had less favorable anatomies. Most shift differences (82.3%) between the "PR" and "AR" alignments larger than 2 mm resulted in rV95% changes larger than 2 cc. Most shift differences (82.2%) of 2 mm or less between the "PR" and "AR" alignments resulted in rV95% changes less than 2 cc. The average percentage of fractions among patients in which anterior or posterior shifts for "AR" and "PR" alignment was larger than the PTV margins was 9.1% (0.0%-37.5%) and 1.3% (0%-10%). CONCLUSION: Rectal deformation and subsequent inconsistent interfraction separation between prostate and rectal wall translate into anatomical changes that cannot always be mitigated with rigid alignment. If systematic differences exist due to a non-reproducible planning anatomy, attempts to restore the planned rectal doses through anterior rectum alignment produce rather small improvements and may result in unacceptable target underdosage.

Automated Lung Cancer Segmentation Using a PET and CT Dual-Modality Deep Learning Neural Network.

PURPOSE: To develop an automated lung tumor segmentation method for radiation therapy planning based on deep learning and dual-modality positron emission tomography (PET) and computed tomography (CT) images. METHODS AND MATERIALS: A 3-dimensional (3D) convolutional neural network using inputs from diagnostic PETs and simulation CTs was constructed with 2 parallel convolution paths for independent feature extraction at multiple resolution levels and a single deconvolution path. At each resolution level, the extracted features from the convolution arms were concatenated and fed through the skip connections into the deconvolution path that produced the tumor segmentation. Our network was trained/validated/tested by a 3:1:1 split on 290 pairs of PET and CT images from patients with lung cancer treated at our clinic, with manual physician contours as the ground truth. A stratified training strategy based on the magnitude of the gross tumor volume (GTV) was investigated to improve performance, especially for small tumors. Multiple radiation oncologists assessed the clinical acceptability of the network-produced segmentations. RESULTS: The mean Dice similarity coefficient, Hausdorff distance, and bidirectional local distance comparing manual versus automated contours were 0.79 ± 0.10, 5.8 ± 3.2 mm, and 2.8 ± 1.5 mm for the unstratified 3D dual-modality model. Stratification delivered the best results when the model for the large GTVs (>25 mL) was trained with all-size GTVs and the model for the small GTVs (<25 mL) was trained with small GTVs only. The best combined Dice similarity coefficient, Hausdorff distance, and bidirectional local distance from the 2 stratified models on their corresponding test data sets were 0.83 ± 0.07, 5.9 ± 2.5 mm, and 2.8 ± 1.4 mm, respectively. In the multiobserver review, 91.25% manual versus 88.75% automatic contours were accepted or accepted with modifications. CONCLUSIONS: By using an expansive clinical PET and CT image database and a dual-modality architecture, the proposed 3D network with a novel GTVbased stratification strategy generated clinically useful lung cancer contours that were highly acceptable on physician review.

Effects of the recurrence pattern on patient survival following SABR for stage I lung cancer.

Background: Information on the effect of the recurrence pattern on survival for stage I lung cancer following stereotactic ablative radiotherapy (SABR) is limited.Materials and Methods: The recurrence pattern was analyzed for 100 consecutive stage I non-small-cell lung cancer patients treated with SABR using predominantly 12 Gy × 4. Recurrences were classified as local, regional lymph nodes and distant. Distant recurrences included recurrences in the lung and outside the chest. Single lung recurrences were named solitary, if no other location was involved. Kaplan-Meier survival estimates were calculated for different locations of recurrence. Clinical and dosimetrical factors affecting survival were also analyzed.Results: Median follow-up was 32 months (3-123), median age 70 years (49-95). In total, 31 patients had recurrences after a median 21 months (4-60): 5 local; 10 regional; 8 distant outside the chest; 25 non-local lung recurrences, of which 15 were single - 10 of which solitary - and 10 multiple lung nodules. Patients with a solitary lung recurrence had longer survival compared to local or distant recurrences (p = .04 each), and compared to multiple lung nodules (p = .09). 3-year local recurrence-free survival was 92%, disease-free survival 69% and overall survival 59%. On multivariate analysis, disease-free survival was associated with statin use (p = .038) and tumor location (p = .035). Smoking history predicted overall survival (p < .0006).Conclusions: A total of 81% of recurrences involved the lungs. Patients with solitary lung recurrences/second primary lung cancers had the longest overall survival suggesting definitive treatment should be considered. The effects of statin use need to be explored further.

Evaluation of Image Registration Accuracy for Tumor and Organs at Risk in the Thorax for Compliance With TG 132 Recommendations.

PURPOSE: To evaluate accuracy for 2 deformable image registration methods (in-house B-spline and MIM freeform) using image pairs exhibiting changes in patient orientation and lung volume and to assess the appropriateness of registration accuracy tolerances proposed by the American Association of Physicists in Medicine Task Group 132 under such challenging conditions via assessment by expert observers. METHODS AND MATERIALS: Four-dimensional computed tomography scans for 12 patients with lung cancer were acquired with patients in prone and supine positions. Tumor and organs at risk were delineated by a physician on all data sets: supine inhale (SI), supine exhale, prone inhale, and prone exhale. The SI image was registered to the other images using both registration methods. All SI contours were propagated using the resulting transformations and compared with physician delineations using Dice similarity coefficient, mean distance to agreement, and Hausdorff distance. Additionally, propagated contours were anonymized along with ground-truth contours and rated for quality by physician-observers. RESULTS: Averaged across all patients, the accuracy metrics investigated remained within tolerances recommended by Task Group 132 (Dice similarity coefficient >0.8, mean distance to agreement <3 mm). MIM performed better with both complex (vertebrae) and low-contrast (esophagus) structures, whereas the in-house method performed better with lungs (whole and individual lobes). Accuracy metrics worsened but remained within tolerances when propagating from supine to prone; however, the Jacobian determinant contained regions with negative values, indicating localized nonphysiologic deformations. For MIM and in-house registrations, 50% and 43.8%, respectively, of propagated contours were rated acceptable as is and 8.2% and 11.0% as clinically unacceptable. CONCLUSIONS: The deformable image registration methods performed reliably and met recommended tolerances despite anatomically challenging cases exceeding typical interfraction variability. However, additional quality assurance measures are necessary for complex applications (eg, dose propagation). Human review rather than unsupervised implementation should always be part of the clinical registration workflow.

Technical Note: A method for quality assurance of landmark sets for use in evaluation of deformable image registration accuracy of lung parenchyma.

PURPOSE: To develop a quality control method to improve the accuracy of corresponding landmark sets used for deformable image registration (DIR) evaluation in the lung parenchyma. METHODS: An iterative workflow was developed as a method for quality assurance of landmark sets. Starting with the initial landmark set for a given image pair, a landmark-based deformation was applied to one of the images. A difference image and a color overlay were generated using the deformed image and the other image of the pair. Inspection of these generated images at locations of landmarks allowed for the identification of misplaced landmarks. The observer responsible for creating the initial landmark set was tasked with review and revision of points flagged by the quality assurance procedure. Using the updated landmark sets, the process was repeated until all points were acceptable to the reviewer. RESULTS: Eighteen landmark sets, containing a mean (SD) of 170 (31) landmarks, were created using CT images from non-small cell lung cancer patients exhibiting large geometric changes and atelectasis resolution, making landmark specification challenging. Following the quality assurance procedure, the final landmark sets contained a mean (SD) of 165 (25) landmarks, as points too difficult to match were removed and points were added to regions deficient in landmarks. For landmark sets in which changes were made, maximum and mean differences in landmark positions before and after quality assurance ranged between 8.7-81.5 mm and 0.3-9.6 mm, respectively. CONCLUSIONS: An effective method for improving the accuracy of landmark correspondence was presented. This quality assurance approach enables more accurate evaluation of DIR for lung parenchyma in clinical image pairs in the absence of a ground truth deformation and may be applicable to other feature-rich anatomical sites.

Interobserver reliability in describing radiographic lung changes after stereotactic body radiation therapy.

PURPOSE: Radiographic lung changes after stereotactic body radiation therapy (SBRT) vary widely between patients. Standardized descriptions of acute (≤6 months after treatment) and late (>6 months after treatment) benign lung changes have been proposed but the reliable application of these classification systems has not been demonstrated. Herein, we examine the interobserver reliability of classifying acute and late lung changes after SBRT. METHODS AND MATERIALS: A total of 280 follow-up computed tomography scans at 3, 6, and 12 months post-treatment were analyzed in 100 patients undergoing thoracic SBRT. Standardized descriptions of acute lung changes (3- and 6-month scans) include diffuse consolidation, patchy consolidation and ground glass opacity (GGO), diffuse GGO, patchy GGO, and no change. Late lung change classifications (12-month scans) include modified conventional pattern, mass-like pattern, scar-like pattern, and no change. Five physicians scored the images independently in a blinded fashion. Fleiss' kappa scores quantified the interobserver agreement. RESULTS: The Kappa scores were 0.30 at 3 months, 0.20 at 6 months, and 0.25 at 12 months. The proportion of patients in each category at 3 and 6 months was as follows: Diffuse consolidation 11% and 21%; patchy consolidation and GGO 15% and 28%; diffuse GGO 10% and 11%; patchy GGO 15% and 15%; and no change 49% and 25%, respectively. The percentage of patients in each category at 12 months was as follows: Modified conventional 46%; mass-like 16%; scar-like 26%; and no change 12%. Uniform scoring between the observers occurred in 26, 8, and 14 cases at 3, 6, and 12 months, respectively. CONCLUSIONS: Interobserver reliability scores indicate a fair agreement to classify radiographic lung changes after SBRT. Qualitative descriptions are insufficient to categorize these findings because most patient scans do not fit clearly into a single classification. Categorization at 6 months may be the most difficult because late and acute lung changes can arise at that time.

CALIPER: A deformable image registration algorithm for large geometric changes during radiotherapy for locally advanced non-small cell lung cancer.

PURPOSE: Locally advanced non-small cell lung cancer (NSCLC) patients may experience dramatic changes in anatomy during radiotherapy and could benefit from adaptive radiotherapy (ART). Deformable image registration (DIR) is necessary to accurately accumulate dose during plan adaptation, but current algorithms perform poorly in the presence of large geometric changes, namely atelectasis resolution. The goal of this work was to develop a DIR framework, named Consistent Anatomy in Lung Parametric imagE Registration (CALIPER), to handle large geometric changes in the thorax. METHODS: Registrations were performed on pairs of baseline and mid-treatment CT datasets of NSCLC patients presenting with atelectasis at the start of treatment. Pairs were classified based on atelectasis volume change as either full, partial, or no resolution. The evaluated registration algorithms consisted of several combinations of a hybrid intensity- and feature-based similarity cost function to investigate the ability to simultaneously match healthy lung parenchyma and adjacent atelectasis. These components of the cost function included a mass-preserving intensity cost in the lung parenchyma, use of filters to enhance vascular structures in the lung parenchyma, manually delineated lung lobes as labels, and several intensity cost functions to model atelectasis change. Registration error was quantified with landmark-based target registration error and post-registration alignment of atelectatic lobes. RESULTS: The registrations using both lobe labels and vasculature enhancement in addition to intensity of the CT images were found to have the highest accuracy. Of these registrations, the mean (SD) of mean landmark error across patients was 2.50 (1.16) mm, 2.80 (0.70) mm, and 2.04 (0.13) mm for no change, partial resolution, and full atelectasis resolution, respectively. The mean (SD) atelectatic lobe Dice similarity coefficient was 0.91 (0.08), 0.90 (0.08), and 0.89 (0.04), respectively, for the same groups. Registration accuracy was comparable to healthy lung registrations of current state-of-the-art algorithms reported in literature. CONCLUSIONS: The CALIPER algorithm developed in this work achieves accurate image registration for challenging cases involving large geometric and topological changes in NSCLC patients, a requirement for enabling ART in this patient group.

Variabilities of Magnetic Resonance Imaging-, Computed Tomography-, and Positron Emission Tomography-Computed Tomography-Based Tumor and Lymph Node Delineations for Lung Cancer Radiation Therapy Planning.

PURPOSE: To investigate interobserver delineation variability for gross tumor volumes of primary lung tumors and associated pathologic lymph nodes using magnetic resonance imaging (MRI), and to compare the results with computed tomography (CT) alone- and positron emission tomography (PET)-CT-based delineations. METHODS AND MATERIALS: Seven physicians delineated the tumor volumes of 10 patients for the following scenarios: (1) CT only, (2) PET-CT fusion images registered to CT ("clinical standard"), and (3) postcontrast T1-weighted MRI registered with diffusion-weighted MRI. To compute interobserver variability, the median surface was generated from all observers' contours and used as the reference surface. A physician labeled the interface types (tumor to lung, atelectasis (collapsed lung), hilum, mediastinum, or chest wall) on the median surface. Contoured volumes and bidirectional local distances between individual observers' contours and the reference contour were analyzed. RESULTS: Computed tomography- and MRI-based tumor volumes normalized relative to PET-CT-based volumes were 1.62 ± 0.76 (mean ± standard deviation) and 1.38 ± 0.44, respectively. Volume differences between the imaging modalities were not significant. Between observers, the mean normalized volumes per patient averaged over all patients varied significantly by a factor of 1.6 (MRI) and 2.0 (CT and PET-CT) (P=4.10 × 10-5 to 3.82 × 10-9). The tumor-atelectasis interface had a significantly higher variability than other interfaces for all modalities combined (P=.0006). The interfaces with the smallest uncertainties were tumor-lung (on CT) and tumor-mediastinum (on PET-CT and MRI). CONCLUSIONS: Although MRI-based contouring showed overall larger variability than PET-CT, contouring variability depended on the interface type and was not significantly different between modalities, despite the limited observer experience with MRI. Multimodality imaging and combining different imaging characteristics might be the best approach to define the tumor volume most accurately.

Effect of variations in atelectasis on tumor displacement during radiation therapy for locally advanced lung cancer.

PURPOSE: Atelectasis (AT), or collapsed lung, is frequently associated with central lung tumors. We investigated the variation of atelectasis volumes during radiation therapy and analyzed the effect of AT volume changes on the reproducibility of the primary tumor (PT) position. METHODS AND MATERIALS: Twelve patients with lung cancer who had AT and 10 patients without AT underwent repeated 4-dimensional fan beam computed tomography (CT) scans during radiation therapy per protocols that were approved by the institutional review board. Interfraction volume changes of AT and PT were correlated with PT displacements relative to bony anatomy using both a bounding box (BB) method and change in center of mass (COM). Linear regression modeling was used to determine whether PT and AT volume changes were independently associated with PT displacement. PT displacement was compared between patients with and without AT. RESULTS: The mean initial AT volume on the planning CT was 189 cm3 (37-513 cm3), and the mean PT volume was 93 cm3 (12-176 cm3). During radiation therapy, AT and PT volumes decreased on average 136.7 cm3 (20-369 cm3) for AT and 40 cm3 (-7 to 131 cm3) for PT. Eighty-three percent of patients with AT had at least one unidirectional PT shift that was greater than 0.5 cm outside of the initial BB during treatment. In patients with AT, the maximum PT COM shift was ≥0.5 cm in all patients and >1 cm in 58% of patients (0.5-2.4 cm). Changes in PT and AT volumes were independently associated with PT displacement (P < .01), and the correlation was smaller with COM (R2 = 0.58) compared with the BB method (R2 = 0.80). The median root mean squared PT displacement with the BB method was significantly less for patients without AT (0.45 cm) compared with those with AT (0.8cm, P = .002). CONCLUSIONS: Changes in AT and PT volumes during radiation treatment were significantly associated with PT displacements that often exceeded standard setup margins. Repeated 3-dimensional imaging is recommended in patients with AT to evaluate for PT displacements during treatment.

Lung and Heart Dose Variability During Radiation Therapy of Non-Small Cell Lung Cancer.

PURPOSE: To investigate the hypothesis that positional and anatomic variations during radiation therapy induce changes in lung and heart volumes and associated radiation doses. METHODS AND MATERIALS: In this longitudinal investigation, variations in lung and heart volumes and standard dose parameters of mean lung dose, lung V20Gy, mean heart dose, and heart V40Gy were analyzed on weekly 4-dimensional CT scans of 15 lung cancer patients during conventionally fractionated radiochemotherapy. Tumor, individual lung lobes, and heart were delineated on the mid-ventilation phase of weekly 4-dimensional CT scans. Lung lobes and heart were also contoured on individual breathing phases of pre-, mid-, and end-of-treatment scans. Planning dose was transferred to consecutive scans via rigid registration. Volume and dose variations were assessed relative to the initial planning scan. RESULTS: Interfraction lung volume variability relative to week 0 was twice as large as tidal volume variability (8.0% ± 5.3% vs 4.0% ± 3.3%, P=.003). Interfraction lung volume variation ranged between 0.8% and 17.1% for individual patient means. Lower lung lobes had larger volume variability compared with upper lobes (13.5% ± 8.1% vs 7.0% ± 5.0%, P<.00001). Average mean lung dose variation was 0.5 Gy (range, 0.2-1.0 Gy for individual patient means) and average lung V20Gy variation 0.9% (range, 0.2%-1.6%). Average heart volume variation was 7.2% (range, 3.4%-12.6%). Average mean heart dose variation was 1.2 Gy (range, 0.1-3.0 Gy) and average heart V40Gy variation 1.4% (range, 0%-4.2%). CONCLUSIONS: Anatomic and positional variations during radiation therapy induce changes in radiation doses to lung and heart. Repeated lung and heart dose assessment will provide a better estimate of the actual delivered dose and will improve prediction models for normal tissue toxicity, if assessed in larger cohorts.

Effect of atelectasis changes on tissue mass and dose during lung radiotherapy.

PURPOSE: To characterize mass and density changes of lung parenchyma in non-small cell lung cancer (NSCLC) patients following midtreatment resolution of atelectasis and to quantify the impact this large geometric change has on normal tissue dose. METHODS: Baseline and midtreatment CT images and contours were obtained for 18 NSCLC patients with atelectasis. Patients were classified based on atelectasis volume reduction between the two scans as having either full, partial, or no resolution. Relative mass and density changes from baseline to midtreatment were calculated based on voxel intensity and volume for each lung lobe. Patients also had clinical treatment plans available which were used to assess changes in normal tissue dose constraints from baseline to midtreatment. The midtreatment image was rigidly aligned with the baseline scan in two ways: (1) bony anatomy and (2) carina. Treatment parameters (beam apertures, weights, angles, monitor units, etc.) were transferred to each image. Then, dose was recalculated. Typical IMRT dose constraints were evaluated on all images, and the changes from baseline to each midtreatment image were investigated. RESULTS: Atelectatic lobes experienced mean (stdev) mass changes of -2.8% (36.6%), -24.4% (33.0%), and -9.2% (17.5%) and density changes of -66.0% (6.4%), -25.6% (13.6%), and -17.0% (21.1%) for full, partial, and no resolution, respectively. Means (stdev) of dose changes to spinal cord Dmax, esophagus Dmean, and lungs Dmean were 0.67 (2.99), 0.99 (2.69), and 0.50 Gy (2.05 Gy), respectively, for bone alignment and 0.14 (1.80), 0.77 (2.95), and 0.06 Gy (1.71 Gy) for carina alignment. Dose increases with bone alignment up to 10.93, 7.92, and 5.69 Gy were found for maximum spinal cord, mean esophagus, and mean lung doses, respectively, with carina alignment yielding similar values. 44% and 22% of patients had at least one metric change by at least 5 Gy (dose metrics) or 5% (volume metrics) for bone and carina alignments, respectively. Investigation of GTV coverage showed mean (stdev) changes in VRx, Dmax, and Dmin of -5.5% (13.5%), 2.5% (4.2%), and 0.8% (8.9%), respectively, for bone alignment with similar results for carina alignment. CONCLUSIONS: Resolution of atelectasis caused mass and density decreases, on average, and introduced substantial changes in normal tissue dose metrics in a subset of the patient cohort.

Respiratory motion variability of primary tumors and lymph nodes during radiotherapy of locally advanced non-small-cell lung cancers.

BACKGROUND AND PURPOSE: The need for target adjustment due to respiratory motion variation and the value of carina as a motion surrogate is evaluated for locally advanced non-small-cell lung cancer. MATERIAL AND METHODS: Using weekly 4D CTs (with audio-visual biofeedback) of 12 patients, respiratory motion variation of primary tumors (PT), lymph nodes (LN) and carina (C) were determined. RESULTS: Mean (SD) 3D respiratory motion ranges of PT, LN and C were 4 (3), 5 (3) and 5 (3) mm. PT and LN (p = 0.003), and LN and C motion range were correlated (p = 0.03). Only 20 %/5 % of all scans had variations >3 mm/5 mm. Large respiratory motion range on the initial scan was associated with larger during-treatment variations for PT (p = 0.03) and LN (p = 0.001). Mean (SD) 3D relative displacements of PT-C, LN-C and PT-LN were each 6 (2) mm. Variations of displacements >3 mm/5 mm were observed in 28 %/6 % of scans for PT-LN, 20 %/9 % for PT-C, and 20 %/8 % for LN-C. CONCLUSIONS: Motion reassessment is recommended in patients with large initial motion range. Relative motion-related displacements between PT and LN were larger than PT and LN motion alone. Both PT and C appear to be comparable surrogates for LN respiratory motion.

Interfraction displacement of primary tumor and involved lymph nodes relative to anatomic landmarks in image guided radiation therapy of locally advanced lung cancer.

PURPOSE: To analyze primary tumor (PT) and lymph node (LN) position changes relative to each other and relative to anatomic landmarks during conventionally fractionated radiation therapy for patients with locally advanced lung cancer. METHODS AND MATERIALS: In 12 patients with locally advanced non-small cell lung cancer PT, LN, carina, and 1 thoracic vertebra were manually contoured on weekly 4-dimensional fan-beam CT scans. Systematic and random interfraction displacements of all contoured structures were identified in the 3 cardinal directions, and resulting setup margins were calculated. Time trends and the effect of volume changes on displacements were analyzed. RESULTS: Three-dimensional displacement vectors and systematic/random interfraction displacements were smaller for carina than for vertebra both for PT and LN. For PT, mean (SD) 3-dimensional displacement vectors with carina-based alignment were 7 (4) mm versus 9 (5) mm with bony anatomy (P<.0001). For LN, smaller displacements were found with carina- (5 [3] mm, P<.0001) and vertebra-based (6 [3] mm, P=.002) alignment compared with using PT for setup (8 [5] mm). Primary tumor and LN displacements relative to bone and carina were independent (P>.05). Displacements between PT and bone (P=.04) and between PT and LN (P=.01) were significantly correlated with PT volume regression. Displacements between LN and carina were correlated with LN volume change (P=.03). CONCLUSIONS: Carina-based setup results in a more reproducible PT and LN alignment than bony anatomy setup. Considering the independence of PT and LN displacement and the impact of volume regression on displacements over time, repeated CT imaging even with PT-based alignment is recommended in locally advanced disease.

Evaluation of 4-dimensional computed tomography to 4-dimensional cone-beam computed tomography deformable image registration for lung cancer adaptive radiation therapy.

PURPOSE: To evaluate 2 deformable image registration (DIR) algorithms for the purpose of contour mapping to support image-guided adaptive radiation therapy with 4-dimensional cone-beam CT (4DCBCT). METHODS AND MATERIALS: One planning 4D fan-beam CT (4DFBCT) and 7 weekly 4DCBCT scans were acquired for 10 locally advanced non-small cell lung cancer patients. The gross tumor volume was delineated by a physician in all 4D images. End-of-inspiration phase planning 4DFBCT was registered to the corresponding phase in weekly 4DCBCT images for day-to-day registrations. For phase-to-phase registration, the end-of-inspiration phase from each 4D image was registered to the end-of-expiration phase. Two DIR algorithms-small deformation inverse consistent linear elastic (SICLE) and Insight Toolkit diffeomorphic demons (DEMONS)-were evaluated. Physician-delineated contours were compared with the warped contours by using the Dice similarity coefficient (DSC), average symmetric distance, and false-positive and false-negative indices. The DIR results are compared with rigid registration of tumor. RESULTS: For day-to-day registrations, the mean DSC was 0.75 ± 0.09 with SICLE, 0.70 ± 0.12 with DEMONS, 0.66 ± 0.12 with rigid-tumor registration, and 0.60 ± 0.14 with rigid-bone registration. Results were comparable to intraobserver variability calculated from phase-to-phase registrations as well as measured interobserver variation for 1 patient. SICLE and DEMONS, when compared with rigid-bone (4.1 mm) and rigid-tumor (3.6 mm) registration, respectively reduced the average symmetric distance to 2.6 and 3.3 mm. On average, SICLE and DEMONS increased the DSC to 0.80 and 0.79, respectively, compared with rigid-tumor (0.78) registrations for 4DCBCT phase-to-phase registrations. CONCLUSIONS: Deformable image registration achieved comparable accuracy to reported interobserver delineation variability and higher accuracy than rigid-tumor registration. Deformable image registration performance varied with the algorithm and the patient.