Respiration-correlated CT Research Articles

4DCT is long overdue for improvement.

4DCT is long overdue for improvement.

Cardiac motion and its dosimetric impact during radioablation for refractory ventricular tachycardia.

Cardiac radioablation (CR) is a noninvasive treatment option for patients with refractory ventricular tachycardia (VT) during which high doses of radiation, typically 25Gy, are delivered to myocardial scar. In this study, we investigate motion from cardiac cycle and evaluate the dosimetric impact in a cohort of patients treated with CR. This retrospective study included eight patients treated at our institution who had respiratory-correlated and ECG-gated 4DCT scans acquired within 2 weeks of CR. Deformable image registration was applied between maximum systole (SYS) and diastole (DIAS) CTs to assess cardiac motion. The average respiratory-correlated CT (AVGresp ) was deformably registered to the average cardiac (AVGcardiac ), SYS, and DIAS CTs, and contours were propagated using the deformation vector fields (DVFs). Finally, the original treatment plan was recalculated on the deformed AVGresp CT for dosimetric assessment. Motion magnitudes were measured as the mean (SD) value over the DVFs within each structure. Displacement during the cardiac cycle for all chambers was 1.4 (0.9) mm medially/laterally (ML), 1.6 (1.0) mm anteriorly/posteriorly (AP), and 3.0 (2.8) mm superiorly/inferiorly (SI). Displacement for the 12 distinct clinical target volumes (CTVs) was 1.7 (1.5) mm ML, 2.4 (1.1) mm AP, and 2.1 (1.5) SI. Displacements between the AVGresp and AVGcardiac scans were 4.2 (2.0) mm SI and 5.8 (1.4) mm total. Dose recalculations showed that cardiac motion may impact dosimetry, with dose to 95% of the CTV dropping from 27.0 (1.3) Gy on the AVGresp to 20.5 (7.1) Gy as estimated on the AVGcardiac . Cardiac CTV motion in this patient cohort is on average below 3mm, location-dependent, and when not accounted for in treatment planning may impact target coverage. Further study is needed to assess the impact of cardiac motion on clinical outcomes.

Automated clinical target volume delineation using deep 3D neural networks in radiation therapy of Non-small Cell Lung Cancer

Background and purposeClinical targeted volume (CTV) delineation accounting for the patient-specific microscopic tumor spread can be a difficult step in defining the treatment volume. We developed an intelligent and automated CTV delineation system for locally advanced non-small cell lung carcinoma (NSCLC) to cover the microscopic tumor spread while avoiding organs-at-risk (OAR).Materials and methodsA 3D UNet with a customized loss function was used, which takes both the patients’ respiration-correlated (“4D”) CT scan and the physician contoured internal gross target volume (iGTV) as inputs, and outputs the CTV delineation. Among the 84 identified patients, 60 were randomly selected to train the network, and the remaining as testing. The model performance was evaluated and compared with cropped expansions using the shape similarities to the physicians’ contours (the ground-truth) and the avoidance of critical OARs.ResultsOn the testing datasets, all model-predicted CTV contours followed closely to the ground truth, and were acceptable by physicians. The average dice score was 0.86. Our model-generated contours demonstrated better agreement with the ground-truth than the cropped 5 mm/8 mm expansion method (median of median surface distance of 1.0 mm vs 1.9 mm/2.0 mm), with a small overlap volume with OARs (0.4 cm3 for the esophagus and 1.2 cm3 for the heart).ConclusionsThe CTVs generated by our CTV delineation system agree with the physician's contours. This approach demonstrates the capability of intelligent volumetric expansions with the potential to be used in clinical practice.

Cardiac stereotactic body radiation therapy for refractory ventricular tachycardia: Impact of cardiac and respiratory movement on the target volume definition

Cardiac stereotactic body radiation therapy (SBRT) appears to be effective for patients with refractory ventricular tachycardia (VT) by delivering a single ablative radiation dose of 25 Gy to the arrhythmogenic region. Definition of treatment volume is a critical step, integrating combination of cardiac and respiratory motion. The main objective of this study was to evaluate the impact of cardiac and respiratory motion on the definition of target volume. The study presents the targeting data from the first patient enrolled in our institution for SBRT. Treatment planning was performed using different imaging modalities: a respiration-correlated 4D CT, a cardiac-correlated 4D CT, a MRI scan and electrophysiological data from prior catheter ablation. A registration was performed between the different imaging modalities. Respiratory and cardiac motions were quantified in left–right (LR), anteroposterior (AP) and supero-inferior (SI) directions for the target (calcifications) and for the defibrillation lead. The treatment area was delineated using diastolic and systolic cardiac phases of the cardiac-correlated 4D CT, to optimally define a treatment zone accounting for target's displacements related to cardiac motions. Target motions amplitude induced by heartbeats were close to those induced by respiration. Respiratory motions of the target were not correlated to that of defibrillation lead (see Table 1 ). The target volume was 15.9 cm 3 and 17.7 cm 3 for the diastolic and systolic phases, respectively, and 20.7 cm 3 when joined together. These differences emphasise the target deformation, and the need of 4D cardiac imaging data for SBRT. We showed that optimal definition of the target volume in SBRT requires respiratory and cardiac correlated images. The use of defibrillation lead as a surrogate might result in target localisation inaccuracies, which need to be taken into account in the final planning target volume.

Design and validation of a MV/kV imaging-based markerless tracking system for assessing real-time lung tumor motion.

Localizing lung tumors during treatment delivery is critical for managing respiratory motion, ensuring tumor coverage, and reducing toxicities. The purpose of this project is to develop a real-time system that performs markerless tracking of lung tumors using simultaneously acquired MV and kV images during radiotherapy of lung cancer with volumetric modulated arc therapy. Continuous MV/kV images were simultaneously acquired during dose delivery. In the subsequent analysis, a gantry angle-specific region of interest was defined according to the treatment aperture. After removing imaging artifacts, processed MV/kV images were directly registered to the corresponding daily setup cone-beam CT (CBCT) projections that served as reference images. The registration objective function consisted of a sum of normalized cross-correlation, weighted by the contrast-to-noise ratio of each MV and kV image. The calculated 3D shifts of the tumor were corrected by the displacements between the CBCT projections and the planning respiratory correlated CT (RCCT) to generate motion traces referred to a specific respiratory phase. The accuracy of the algorithm was evaluated on both anthropomorphic phantom and patient studies. The phantom consisted of localizing a 3D printed tumor, embedded in a thorax phantom, in an arc delivery. In an IRB-approved study, data were obtained from VMAT treatments of two lung cancer patients with three electromagnetic (Calypso) beacon transponders implanted in airways near the lung tumor. In the phantom study, the root mean square error (RMSE) between the registered and actual (programmed couch movement) target position was 1.2mm measured by the MV/kV imaging system, which was smaller compared to the MV or kV alone, of 4.1 and 1.3mm, respectively. In the patient study, the mean and standard deviation discrepancy between electromagnetic-based tumor position and the MV/KV-markerless approach was -0.2±0.6mm, 0.2±1.0mm, and -1.2±1.5mm along the superior-inferior, anterior-posterior, and left-right directions, respectively; resulting in a 3D displacement discrepancy of 2.0±1.1mm. Poor contrast around the tumor was the main contribution to registration uncertainties. The combined MV/kV imaging system can provide real-time 3D localization of lung tumor, with comparable accuracy to the electromagnetic-based system when features of tumors are detectable. Careful design of a registration algorithm and a VMAT plan that maximizes the tumor visibility are key elements for a successful MV/KV localization strategy.

Evaluation of respiratory motion-corrected cone-beam CT at end expiration in abdominal radiotherapy sites: a prospective study

Background: Cone beam computed tomography (CBCT) for radiotherapy image guidance suffers from respiratory motion artifacts. This limits soft tissue visualization and localization accuracy, particularly in abdominal sites. We report on a prospective study of respiratory motion-corrected (RMC)-CBCT to evaluate its efficacy in localizing abdominal organs and improving soft tissue visibility at end expiration.Material and methods: In an IRB approved study, 11 patients with gastroesophageal junction (GEJ) cancer and five with pancreatic cancer underwent a respiration-correlated CT (4DCT), a respiration-gated CBCT (G-CBCT) near end expiration and a one-minute free-breathing CBCT scan on a single treatment day. Respiration was recorded with an external monitor. An RMC-CBCT and an uncorrected CBCT (NC-CBCT) were computed from the free-breathing scan, based on a respiratory model of deformations derived from the 4DCT. Localization discrepancy was computed as the 3D displacement of the GEJ region (GEJ patients), or gross tumor volume (GTV) and kidneys (pancreas patients) in the NC-CBCT and RMC-CBCT relative to their positions in the G-CBCT. Similarity of soft-tissue features was measured using a normalized cross correlation (NCC) function.Results: Localization discrepancy from the end-expiration G-CBCT was reduced for RMC-CBCT compared to NC-CBCT in eight of eleven GEJ cases (mean ± standard deviation, respectively, 0.21 ± 0.11 and 0.43 ± 0.28 cm), in all five pancreatic GTVs (0.26 ± 0.21 and 0.42 ± 0.29 cm) and all ten kidneys (0.19 ± 0.13 and 0.51 ± 0.25 cm). Soft-tissue feature similarity around GEJ was higher with RMC-CBCT in nine of eleven cases (NCC =0.48 ± 0.20 and 0.43 ± 0.21), and eight of ten kidneys (0.44 ± 0.16 and 0.40 ± 0.17).Conclusions: In a prospective study of motion-corrected CBCT in GEJ and pancreas, RMC-CBCT yielded improved organ visibility and localization accuracy for gated treatment at end expiration in the majority of cases.

Particle therapy of moving targets-the strategies for tumour motion monitoring and moving targets irradiation.

Particle therapy of moving targets is still a great challenge. The motion of organs situated in the thorax and abdomen strongly affects the precision of proton and carbon ion radiotherapy. The motion is responsible for not only the dislocation of the tumour but also the alterations in the internal density along the beam path, which influence the range of particle beams. Furthermore, in case of pencil beam scanning, there is an interference between the target movement and dynamic beam delivery. This review presents the strategies for tumour motion monitoring and moving target irradiation in the context of hadron therapy. Methods enabling the direct determination of tumour position (fluoroscopic imaging of implanted radio-opaque fiducial markers, electromagnetic detection of inserted transponders and ultrasonic tumour localization systems) are presented. Attention is also drawn to the techniques which use external surrogate motion for an indirect estimation of target displacement during irradiation. The role of respiratory-correlated CT [four-dimensional CT (4DCT)] in the determination of motion pattern prior to the particle treatment is also considered. An essential part of the article is the review of the main approaches to moving target irradiation in hadron therapy: gating, rescanning (repainting), gated rescanning and tumour tracking. The advantages, drawbacks and development trends of these methods are discussed. The new accelerators, called "cyclinacs", are presented, because their application to particle therapy will allow making a breakthrough in the 4D spot scanning treatment of moving organs.

Impact of respiratory-correlated CT sorting algorithms on the choice of margin definition for free-breathing lung radiotherapy treatments

Background and purposeTo investigate the impact of Toshiba phase- and amplitude-sorting algorithms on the margin strategies for free-breathing lung radiotherapy treatments in the presence of breathing variations. Material and methods4D CT of a sphere inside a dynamic thorax phantom was acquired. The 4D CT was reconstructed according to the phase- and amplitude-sorting algorithms. The phantom was moved by reproducing amplitude, frequency, and a mix of amplitude and frequency variations. Artefact analysis was performed for Mid-Ventilation and ITV-based strategies on the images reconstructed by phase- and amplitude-sorting algorithms. The target volume deviation was assessed by comparing the target volume acquired during irregular motion to the volume acquired during regular motion. ResultsThe amplitude-sorting algorithm shows reduced artefacts for only amplitude variations while the phase-sorting algorithm for only frequency variations. For amplitude and frequency variations, both algorithms perform similarly. Most of the artefacts are blurring and incomplete structures. We found larger artefacts and volume differences for the Mid-Ventilation with respect to the ITV strategy, resulting in a higher relative difference of the surface distortion value which ranges between maximum 14.6% and minimum 4.1%. ConclusionsThe amplitude- is superior to the phase-sorting algorithm in the reduction of motion artefacts for amplitude variations while phase-sorting for frequency variations. A proper choice of 4D CT sorting algorithm is important in order to reduce motion artefacts, especially if Mid-Ventilation strategy is used.

Helical 4D CT pitch management for the Brilliance CT Big Bore in clinical practice.

In external beam radiotherapy treatment planning for patients with thoracic malignancies, respiratory‐correlated CT (4D CT) is used to obtain high quality studies in the presence of respiratory motion. When helical 4D CT scans are acquired with a Brilliance CT Big Bore, the pitch must meet two conditions. It must be low enough to avoid motion artifacts, and high enough to cover the entire scan length within 120 s to prevent overheating of the X‐ray tube. We developed a nomogram that can be used to obtain a suitable pitch satisfying both requirements. We also assessed the effects on the image quality of a pitch that exceeds the maximum pitch, and of a field of view (FOV) reduction. It was shown that, for AV G and MIP reconstructions, the manufacturer's maximum pitch equation yields an underestimation due to its FOV term.PACS number: 87.57.Q‐, 87.57.cp

Estimation of lung motion fields in 4D CT data by variational non-linear intensity-based registration: A comparison and evaluation study

Accurate and robust estimation of motion fields in respiration-correlated CT (4D CT) images, usually performed by non-linear registration of the temporal CT frames, is a precondition for the analysis of patient-specific breathing dynamics and subsequent image-supported diagnostics and treatment planning.In this work, we present a comprehensive comparison and evaluation study of non-linear registration variants applied to the task of lung motion estimation in thoracic 4D CT data. In contrast to existing multi-institutional comparison studies (e.g. MIDRAS and EMPIRE10), we focus on the specific but common class of variational intensity-based non-parametric registration and analyze the impact of the different main building blocks of the underlying optimization problem: the distance measure to be minimized, the regularization approach and the transformation space considered during optimization. In total, 90 different combinations of building block instances are compared.Evaluated on proprietary and publicly accessible 4D CT images, landmark-based registration errors (TRE) between 1.14 and 1.20 mm for the most accurate registration variants demonstrate competitive performance of the applied general registration framework compared to other state-of-the-art approaches for lung CT registration. Although some specific trends can be observed, effects of interchanging individual instances of the building blocks on the TRE are in general rather small (no single outstanding registration variant existing); the same level of accuracy is, however, associated with significantly different degrees of motion field smoothness and computational demands. Consequently, the building block combination of choice will depend on application-specific requirements on motion field characteristics.

SU-E-J-226: Propagation of Pancreas Target Contours On Respiratory Correlated CT Images Using Deformable Image Registration

Purpose: Respiratory Correlated CT (RCCT) scans to assess intra-fraction motion among pancreatic cancer patients undergoing radiotherapy allow for dose sparing of normal tissues, in particular for the duodenum. Contour propagation of the gross tumor volume (GTV) from one reference respiratory phase to 9 other phases is time consuming. Deformable image registration (DIR) has been successfully used for high contrast disease sites but lower contrast for pancreatic tumors may compromise accuracy. This study evaluates the accuracy of Fast Free Form (FFF) registration-based contour propagation of the GTV on RCCT scans of pancreas cancer patients. Methods: Twenty-four pancreatic cancer patients were retrospectively studied; 20 had tumors in the pancreatic head/neck, 4 in the body/tail. Patients were simulated with RCCT and images were sorted into 10 respiratory phases. A radiation oncologist manually delineated the GTV for 5 phases (0%, 30%, 50%, 70% and 90%). The FFF algorithm was used to map deformations between the EE (50%) phase and each of the other 4 phases. The resultant deformation fields served to propagate GTV contours from EE to the other phases. The Dice Similarity Coefficient (DSC), which measures agreement between the DIR-propagated and manually-delineated GTVs, was used to quantitatively examine DIR accuracy. Results: Average DSCmore » over all scans and patients is 0.82 and standard deviation is 0.09 (DSC range 0.97–0.57). For GTV volumes above and below the median volume of 20.2 cc, a Wilcoxon rank-sum test shows significantly different DSC (p=0.0000002). For the GTVs above the median volume, average +/− SD is 0.85 +/− 0.07; and for the GTVs below, the average +/− SD is 0.75 +/−0.08. Conclusion: For pancreatic tumors, the FFF DIR algorithm accurately propagated the GTV between the images in different phases of RCCT, with improved performance for larger tumors.« less

Evaluation of Respiratory Motion-Corrected Cone Beam CT in Abdominal Sites: A Prospective Study

Evaluation of Respiratory Motion-Corrected Cone Beam CT in Abdominal Sites: A Prospective Study

TU‐G‐141‐02: Evaluation of Respiration Motion‐Corrected Cone‐Beam CT: Prospective Study in Lung

Purpose: Respiratory motion adversely affects the ability of cone‐beam computerized tomography (CBCT) to guide radiation treatment, due to blurring and streaking artifacts. In a prospective patient study, we evaluate respiratory motion‐corrected (RMC) CBCT efficacy in reducing motion artifacts and improving localization accuracy and whether a correction model derived from a respiration‐correlated CT (RCCT) at simulation is still valid at treatment. Methods: In an IRB‐approved study, lung cancer patients receive an RCCT at simulation, and on one treatment day receive an RCCT, respiratory‐gated CBCT, and a one‐minute CBCT. A respiration monitor of abdominal displacement is used during all imaging. One‐minute CBCT projections are sorted into 10 bins based on abdominal displacement and reconstructed. Each binned CBCT is deformed to the end expiration state using a model derived from RCCT and added to produce an RMC‐CBCT. Comparison is made between uncorrected CBCT (NoCorr), RMC(sim) CBCT using simulation RCCT, and RMC(tx) CBCT using treatment RCCT. The gated CBCT, gated at end expiration, serves as the criterion standard for comparison. Each CBCT is registered twice to the gated CBCT, first to align to spine, second to tumor in lung. Localization accuracy is defined as the difference between tumor and spine registration. Agreement in tumor shape with the gated CBCT is evaluated by calculating normalized cross‐correlation (NCC) of pixel intensities within the local tumor region. Results: NCC from RMC(tx) is higher in 12/13 cases compared to NoCorr, and in 7/13 compared to RMC(sim). Tumor position in RMC(tx) is in closer agreement with gated CBCT than for NoCorr in 11/13 cases. Tumor position between RMC(tx) and RMC(sim) agrees within 2mm in all cases. Conclusion: This correction method reduces motion artifacts and improves localization accuracy in nearly all cases. Motion correction based on the simulation day RCCT or on the treatment day RCCT yields similar results. NIH/NCI award R01 CA126993 and research grant from Varian.

MO‐F‐WAB‐02: Constancy of Time Lag Relationship Between External and Internal Signal in Abdominal Tumor Sites

Purpose: To investigate constancy, within a treatment session, of the time lag relationship between implanted markers in abdominal tumors and an external motion surrogate. Methods: Six gastroesophageal junction and three pancreatic cancer patients (IRB‐approved protocol) received a respiration‐correlated CT (RCCT), and two cone‐beam CTs (CBCT), one before and one after the treatment. Time between initial and final scan varied from about 1 to 3 h. Each patient had at least one implanted fiducial marker near the tumor. In all scans, abdominal displacement (Varian RPM) was recorded as the external motion signal. In‐house software tracked fiducials, representing internal signal, in CBCT projection images and amplitude‐sorted RCCT. For each set of projection images, time lag between internal and external signals was found by maximizing the correlation coefficient in each breathing cycle and averaging over all cycles. For the RCCT, these quantities were calculated for the 1 –2 cycles during which the fiducial was imaged. Results: Mean ± standard deviation in time lag, over all scans and patients, was 0.10 ± 0.07 s (range 0.01 – 0.36 s). External signal lagged the internal in 20/27 scans. Change in time lag between pre‐and post‐RT CBCT was 0.06 ± 0.07s (range 0.01 – 0.22 s), corresponding to 3.1 ± 3.7% (range 0.6 – 10.8%) of the gate width (range 1.6 – 3.1 s). Including the RCCT scan, change in time lag increased to 6.5 ± 5.4% (range 0.2 – 16.1%) of the gate width, and in three patients, change in time lag exceeded 10% of the gate width. Conclusion: Time lag between internal and external signal is small compared to the treatment gate width in all patients. Change in time lag within a treatment session, inferred from pre to post‐RT measurements is also small, suggesting that a single measurement at the session start is adequate.NIH/NCI award R01 CA126993 and a research grant from Varian.

Toward correcting drift in target position during radiotherapy via computer‐controlled couch adjustments on a programmable Linac

Real-time tracking of respiratory target motion during radiation therapy is technically challenging, owing to rapid and possibly irregular breathing variations. The authors report on a method to predict and correct respiration-averaged drift in target position by means of couch adjustments on an accelerator equipped with such capability. Dose delivery is broken up into a sequence of 10 s field segments, each followed by a couch adjustment based on analysis of breathing motion from an external monitor as a surrogate of internal target motion. Signal averaging over three respiratory cycles yields a baseline representing target drift. A Kalman filter predicts the baseline position 5 s in advance, for determination of the couch correction. The method's feasibility is tested with a motion phantom programmed according to previously recorded patient signals. Computed couch corrections are preprogrammed into a research mode of an accelerator capable of computer-controlled couch translations synchronized with the motion phantom. The method's performance is evaluated with five cases recorded during hypofractionated treatment and five from respiration-correlated CT simulation, using a root-mean-squared deviation (RMSD) of the baseline from the treatment planned position. RMSD is reduced in all 10 cases, from a mean of 4.9 mm (range 2.7-9.4 mm) before correction to 1.7 mm (range 0.7-2.3 mm) after correction. Treatment time is increased ∼5% relative to that for no corrections. This work illustrates the potential for reduction in baseline respiratory drift with periodic adjustments in couch position during treatment. Future treatment machine capabilities will enable the use of "on-the-fly" couch adjustments during treatment.

Investigation of gated cone‐beam CT to reduce respiratory motion blurring

Methods of reducing respiratory motion blurring in cone-beam CT (CBCT) have been limited to lung where soft tissue contrast is large. Respiration-correlated cone-beam CT uses slow continuous gantry rotation but image quality is limited by uneven projection spacing. This study investigates the efficacy of a novel gated CBCT technique. In gated CBCT, the linac is programmed such that gantry rotation and kV image acquisition occur within a gate around end expiration and are triggered by an external respiratory monitor. Standard CBCT and gated CBCT scans are performed in 22 patients (11 thoracic, 11 abdominal) and a respiration-correlated CT (RCCT) scan, acquired on a standard CT scanner, from the same day serves as a criterion standard. Image quality is compared by calculating contrast-to-noise ratios (CNR) for tumors in lung, gastroesophageal junction (GEJ) tissue, and pancreas tissue, relative to surrounding background tissue. Congruence between the object in the CBCT images and that in the RCCT is measured by calculating the optimized normalized cross-correlation (NCC) following CBCT-to-RCCT rigid registrations. Gated CBCT results in reduced motion artifacts relative to standard CBCT, with better visualization of tumors in lung, and of abdominal organs including GEJ, pancreas, and organs at risk. CNR of lung tumors is larger in gated CBCT in 6 of 11 cases relative to standard CBCT. A paired two-tailed t-test of lung patient mean CNR shows no statistical significance (p = 0.133). In 4 of 5 cases where CNR is not increased, lung tumor motion observed in RCCT is small (range 1.3-5.2 mm). CNR is increased and becomes statistically significant for 6 out of 7 lung patients with > 5 mm tumor motion (p = 0.044). CNR is larger in gated CBCT in 5 of 7 GEJ cases and 3 of 4 pancreas cases (p = 0.082 and 0.192). Gated CBCT yields improvement with lower NCC relative to standard CBCT in 10 of 11, 7 of 7, and 3 of 4 patients for lung, GEJ, and pancreas images, respectively (p = 0.0014, 0.0030, 0.165). Gated CBCT reduces image blurring caused by respiratory motion. The gated gantry rotation yields uniformly and closely spaced projections resulting in improved reconstructed image quality. The technique is shown to be applicable to abdominal sites, where image contrast of soft tissues is low.

A study of respiration‐correlated cone‐beam CT scans to correct target positioning errors in radiotherapy of thoracic cancer

There is increasingly widespread usage of cone-beam CT (CBCT) for guiding radiation treatment in advanced-stage lung tumors, but difficulties associated with daily CBCT in conventionally fractionated treatments include imaging dose to the patient, increased workload and longer treatment times. Respiration-correlated cone-beam CT (RC-CBCT) can improve localization accuracy in mobile lung tumors, but further increases the time and workload for conventionally fractionated treatments. This study investigates whether RC-CBCT-guided correction of systematic tumor deviations in standard fractionated lung tumor radiation treatments is more effective than 2D image-based correction of skeletal deviations alone. A second study goal compares respiration-correlated vs respiration-averaged images for determining tumor deviations. Eleven stage II-IV nonsmall cell lung cancer patients are enrolled in an IRB-approved prospective off-line protocol using RC-CBCT guidance to correct for systematic errors in GTV position. Patients receive a respiration-correlated planning CT (RCCT) at simulation, daily kilovoltage RC-CBCT scans during the first week of treatment and weekly scans thereafter. Four types of correction methods are compared: (1) systematic error in gross tumor volume (GTV) position, (2) systematic error in skeletal anatomy, (3) daily skeletal corrections, and (4) weekly skeletal corrections. The comparison is in terms of weighted average of the residual GTV deviations measured from the RC-CBCT scans and representing the estimated residual deviation over the treatment course. In the second study goal, GTV deviations computed from matching RCCT and RC-CBCT are compared to deviations computed from matching respiration-averaged images consisting of a CBCT reconstructed using all projections and an average-intensity-projection CT computed from the RCCT. Of the eleven patients in the GTV-based systematic correction protocol, two required no correction, seven required a single correction, one required two corrections, and one required three corrections. Mean residual GTV deviation (3D distance) following GTV-based systematic correction (mean ± 1 standard deviation 4.8 ± 1.5 mm) is significantly lower than for systematic skeletal-based (6.5 ± 2.9 mm, p = 0.015), and weekly skeletal-based correction (7.2 ± 3.0 mm, p = 0.001), but is not significantly lower than daily skeletal-based correction (5.4 ± 2.6 mm, p = 0.34). In two cases, first-day CBCT images reveal tumor changes-one showing tumor growth, the other showing large tumor displacement-that are not readily observed in radiographs. Differences in computed GTV deviations between respiration-correlated and respiration-averaged images are 0.2 ± 1.8 mm in the superior-inferior direction and are of similar magnitude in the other directions. An off-line protocol to correct GTV-based systematic error in locally advanced lung tumor cases can be effective at reducing tumor deviations, although the findings need confirmation with larger patient statistics. In some cases, a single cone-beam CT can be useful for assessing tumor changes early in treatment, if more than a few days elapse between simulation and the start of treatment. Tumor deviations measured with respiration-averaged CT and CBCT images are consistent with those measured with respiration-correlated images; the respiration-averaged method is more easily implemented in the clinic.

TU-C-213CD-08: Investigation of Gated Cone-Beam CT to Reduce Respiratory Motion Blurring in Images of Thorax and Abdomen

Purpose: Methods of reducing respiratory motion blurring in cone-beam CT (CBCT) have been limited to lung where soft tissue contrast is large. Respiration-correlated cone-beam CT (RC-CBCT) uses slow continuous gantry rotation but image quality is limited by uneven projection spacing. This study investigates efficacy of a novel gated CBCT technique. Methods: In gated CBCT, the linac (Varian TrueBeam) is programmed such that gantry rotation and kV image acquisition occur within a gate around end expiration (EE) and are triggered by an external respiratory monitor. Standard CBCT and gated CBCT scans are performed in 14 patients (8 thoracic, 6 abdominal) and a respiration correlated CT (RCCT) scan from the same day serves as ground truth. Image quality is compared by calculating contrast-to-noise ratios (CNR) for tumors in lung, gastro-esophageal junction (GEJ) tissue, and liver tissue, relative to surrounding background tissue. Results: Gated CBCT results in reduced motion artifacts relative to standard CBCT, with better visualization of tumors in lung, and of abdominal organs including GEJ, stomach, liver, kidney, and spleen. CNR of lung tumors is larger in gated CBCT in 5 of 8 cases relative to standard CBCT with mean increase 8.8% (range −8.6%–+30.1%). In cases where CNR is not increased, lung tumor motion observed in RCCT is small (range 3.2–5.3 mm). For GEJ images, CNR is larger in gated CBCT in all 3 cases (mean increase 45%, range 24.7%–64.4%). For liver images, CNR is larger in gated CBCT in all 4 cases (mean increase of 73.8%, range 5.4%–119.9%). Conclusions: Gated CBCT reduces image blurring caused by respiratory motion. The gated gantry rotation yields uniformly and closely spaced projections resulting in improved reconstructed image quality. The technique is shown to be applicable to abdominal sites, where image contrast of soft tissues is low. NIH/NCI award R01 CA126993, research grant from Varian Medical Systems

SU-E-J-119: Comparative Evaluation of Respiratory Motion-Corrected Cone-Beam CT Images Derived from Treatment-Day Vs. Simulation-Day Respiration-Correlated CT Scans.

Respiration-induced motion artifacts in cone-beam CT (CBCT) can be corrected using a model of patient motion obtained from respiration-correlated CT (RCCT). This approach assumes that respiration-induced organ deformations at simulation, when RCCT scans are normally acquired, are still valid at treatment. The purpose of this study is to compare lung tumor image quality in motion-corrected CBCT images derived from treatment-day RCCT(tx) to simulation-day RCCT(sim) patient images. In an IRB-approved study, lung cancer patients receive an RCCT at simulation, and an RCCT, gated CBCT and 1-minute CBCT at one treatment session. CBCT projections from the 1-minute scan are sorted according to breathing amplitude from an external monitor and reconstructed and warped to obtain a motion-corrected MC-CBCT at end expiration. Motion correction uses a model adapted from either RCCT(tx) or RCCT(sim), thus obtaining MC-CBCT(tx) and MC-CBCT(sim) images respectively. A gated CBCT, in which gantry rotation and projection acquisition occur within a gate at end expiration, serves as ground truth for comparison. Quality of MC-CBCT images is evaluated from tumor-to-background contrast ratio (TBCR) values measured by delineating the tumor and annular volume around it on the gated CBCT then transferring the contours and aligning them to each MC-CBCT. TBCR is found tobe lower in MC-CBCT(sim) images, relative to MC-CBCT(tx), in four out of five patients with mean 21% reduction in a range 9-39%. In the remaining case, where there was no change in TBCR, tumor motion observed in the RCCT was small (2mm). Tumor motion extent relative to diaphragm is observed to change between RCCT(tx) and RCCT(sim) scans. Preliminary results indicate that deformation patterns in lung do change between simulation and treatment. Such variations may reduce the validity of using simulation data for motion-corrected CBCT at treatment. The findings require confirmation with larger numbers of patients. NIH/NCI award R01 CA126993, research grant from Varian Medical Systems.

Reduction of irregular breathing artifacts in respiration‐correlated CT images using a respiratory motion model

Respiration-correlated CT (RCCT) images produced with commonly used phase-based sorting of CT slices often exhibit discontinuity artifacts between CT slices, caused by cycle-to-cycle amplitude variations in respiration. Sorting based on the displacement of the respiratory signal yields slices at more consistent respiratory motion states and hence reduces artifacts, but missing image data (gaps) may occur. The authors report on the application of a respiratory motion model to produce an RCCT image set with reduced artifacts and without missing data. Input data consist of CT slices from a cine CT scan acquired while recording respiration by monitoring abdominal displacement. The model-based generation of RCCT images consists of four processing steps: (1) displacement-based sorting of CT slices to form volume images at 10 motion states over the cycle; (2) selection of a reference image without gaps and deformable registration between the reference image and each of the remaining images; (3) generation of the motion model by applying a principal component analysis to establish a relationship between displacement field and respiration signal at each motion state; (4) application of the motion model to deform the reference image into images at the 9 other motion states. Deformable image registration uses a modified fast free-form algorithm that excludes zero-intensity voxels, caused by missing data, from the image similarity term in the minimization function. In each iteration of the minimization, the displacement field in the gap regions is linearly interpolated from nearest neighbor nonzero intensity slices. Evaluation of the model-based RCCT examines three types of image sets: cine scans of a physical phantom programmed to move according to a patient respiratory signal, NURBS-based cardiac torso (NCAT) software phantom, and patient thoracic scans. Comparison in physical motion phantom shows that object distortion caused by variable motion amplitude in phase-based sorting is visibly reduced with model-based RCCT. Comparison of model-based RCCT to original NCAT images as ground truth shows best agreement at motion states whose displacement-sorted images have no missing slices, with mean and maximum discrepancies in lung of 1 and 3 mm, respectively. Larger discrepancies correlate with motion states having a larger number of missing slices in the displacement-sorted images. Artifacts in patient images at different motion states are also reduced. Comparison with displacement-sorted patient images as a ground truth shows that the model-based images closely reproduce the ground truth geometry at different motion states. Results in phantom and patient images indicate that the proposed method can produce RCCT image sets with reduced artifacts relative to phase-sorted images, without the gaps inherent in displacement-sorted images. The method requires a reference image at one motion state that has no missing data. Highly irregular breathing patterns can affect the method's performance, by introducing artifacts in the reference image (although reduced relative to phase-sorted images), or in decreased accuracy in the image prediction of motion states containing large regions of missing data.