Automated and Clinically Optimal Treatment Planning for Cancer Radiotherapy.

Each year, approximately 18 million new cancer cases are diagnosed worldwide, and about half must be treated with radiotherapy. A successful treatment requires treatment planning with the customization of penetrating radiation beams to sterilize cancerous cells without harming nearby normal organs and tissues. This process currently involves extensive manual tuning of parameters by an expert planner, making it a time-consuming and labor-intensive process, with quality and immediacy of critical care dependent on the planner's expertise. To improve the speed, quality, and availability of this highly specialized care, Memorial Sloan Kettering Cancer Center developed and applied advanced optimization tools to this problem (e.g., using hierarchical constrained optimization, convex approximations, and Lagrangian methods). This resulted in both a greatly improved radiotherapy treatment planning process and the generation of reliable and consistent high-quality plans that reflect clinical priorities. These improved techniques have been the foundation of high-quality treatments and have positively impacted over 4,000 patients to date, including numerous patients in severe pain and in urgent need of treatment who might have otherwise required longer hospital stays or undergone unnecessary surgery to control the progression of their disease. We expect that the wide distribution of the system we developed will ultimately impact patient care more broadly, including in resource-constrained countries.

Clinical Experience of Automated SBRT Paraspinal and Other Metastatic Tumor Planning With Constrained Hierarchical Optimization.

PURPOSE: We report on the clinical performance of a fully automated approach to treatment planning based on a Pareto optimal, constrained hierarchical optimization algorithm, named Expedited Constrained Hierarchical Optimization (ECHO). METHODS AND MATERIALS: From April 2017 to October 2018, ECHO produced 640 treated plans for 523 patients who underwent stereotactic body radiation therapy (RT) for paraspinal and other metastatic tumors. A total of 182 plans were for 24 Gy in a single fraction, 387 plans were for 27 Gy in 3 fractions, and the remainder were for other prescriptions or fractionations. Of the plans, 84.5% were for paraspinal tumors, with 69, 302, and 170 in the cervical, thoracic, and lumbosacral spine, respectively. For each case, after contouring, a template plan using 9 intensity modulated RT fields based on disease site and tumor location was sent to ECHO through an application program interface plug-in from the treatment planning system. ECHO returned a plan that satisfied all critical structure hard constraints with optimal target volume coverage and the lowest achievable normal tissue doses. Upon ECHO completion, the planner received an e-mail indicating the plan was ready for review. The plan was accepted if all clinical criteria were met. Otherwise, a limited number of parameters could be adjusted for another ECHO run. RESULTS: The median planning target volume size was 84.3 cm3 (range, 6.9-633.2). The median time to produce 1 ECHO plan was 63.5 minutes (range, 11-340 minutes) and was largely dependent on the field sizes. Of the cases, 79.7% required 1 run to produce a clinically accepted plan, 13.3% required 1 additional run with minimal parameter adjustments, and 7.0% required ≥2 additional runs with significant parameter modifications. All plans met or bettered the institutional clinical criteria. CONCLUSIONS: We successfully implemented automated stereotactic body RT paraspinal and other metastatic tumors planning. ECHO produced high-quality plans, improved planning efficiency and robustness, and enabled expedited treatment planning at our clinic.

Automated intensity modulated treatment planning: The expedited constrained hierarchical optimization (ECHO) system.

PURPOSE: To develop and implement a fully automated approach to intensity modulated radiation therapy (IMRT) treatment planning. METHOD: The optimization algorithm is developed based on a hierarchical constrained optimization technique and is referred internally at our institution as expedited constrained hierarchical optimization (ECHO). Beamlet contributions to regions-of-interest are precomputed and captured in the influence matrix. Planning goals are of two classes: hard constraints that are strictly enforced from the first step (e.g., maximum dose to spinal cord), and desirable goals that are sequentially introduced in three constrained optimization problems (better planning target volume (PTV) coverage, lower organ at risk (OAR) doses, and smoother fluence map). After solving the optimization problems using external commercial optimization engines, the optimal fluence map is imported into an FDA-approved treatment planning system (TPS) for leaf sequencing and accurate full dose calculation. The dose-discrepancy between the optimization and TPS dose calculation is then calculated and incorporated into optimization by a novel dose correction loop technique using Lagrange multipliers. The correction loop incorporates the leaf sequencing and scattering effects into optimization to improve the plan quality and reduce the calculation time. The resultant optimal fluence map is again imported into TPS for leaf sequencing and final dose calculation for plan evaluation and delivery. The workflow is automated using application program interface (API) scripting, requiring user interaction solely to prepare the contours and beam arrangement prior to launching the ECHO plug-in from the TPS. For each site, parameters and objective functions are chosen to represent clinical priorities. The first site chosen for clinical implementation was metastatic paraspinal lesions treated with stereotactic body radiotherapy (SBRT). As a first step, 75 ECHO paraspinal plans were generated retrospectively and compared with clinically treated plans generated by planners using VMAT (volumetric modulated arc therapy) with 4 to 6 partial arcs. Subsequently, clinical deployment began in April, 2017. RESULTS: In retrospective study, ECHO plans were found to be dosimetrically superior with respect to tumor coverage, plan conformity, and OAR sparing. For example, the average PTV D95%, cord and esophagus max doses, and Paddick Conformity Index were improved, respectively, by 1%, 6%, 14%, and 15%, at a negligible 3% cost of the average skin D10cc dose. CONCLUSION: Hierarchical constrained optimization is a powerful and flexible tool for automated IMRT treatment planning. The dosimetric correction step accurately accounts for detailed dosimetric multileaf collimator and scattering effects. The system produces high-quality, Pareto optimal plans and avoids the time-consuming trial-and-error planning process.

Tumor-aware, Adversarial Domain Adaptation from CT to MRI for Lung Cancer Segmentation.

We present an adversarial domain adaptation based deep learning approach for automatic tumor segmentation from T2-weighted MRI. Our approach is composed of two steps: (i) a tumor-aware unsupervised cross-domain adaptation (CT to MRI), followed by (ii) semi-supervised tumor segmentation using Unet trained with synthesized and limited number of original MRIs. We introduced a novel target specific loss, called tumor-aware loss, for unsupervised cross-domain adaptation that helps to preserve tumors on synthesized MRIs produced from CT images. In comparison, state-of-the art adversarial networks trained without our tumor-aware loss produced MRIs with ill-preserved or missing tumors. All networks were trained using labeled CT images from 377 patients with non-small cell lung cancer obtained from the Cancer Imaging Archive and unlabeled T2w MRIs from a completely unrelated cohort of 6 patients with pre-treatment and 36 on-treatment scans. Next, we combined 6 labeled pre-treatment MRI scans with the synthesized MRIs to boost tumor segmentation accuracy through semi-supervised learning. Semi-supervised training of cycle-GAN produced a segmentation accuracy of 0.66 computed using Dice Score Coefficient (DSC). Our method trained with only synthesized MRIs produced an accuracy of 0.74 while the same method trained in semi-supervised setting produced the best accuracy of 0.80 on test. Our results show that tumor-aware adversarial domain adaptation helps to achieve reasonably accurate cancer segmentation from limited MRI data by leveraging large CT datasets.

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.

Simultaneous MV-kV imaging for intrafractional motion management during volumetric-modulated arc therapy delivery.

The purpose of this study was to evaluate the accuracy and clinical feasibility of a motion monitoring method employing simultaneously acquired MV and kV images during volumetric-modulated arc therapy (VMAT). Short-arc digital tomosynthesis (SA-DTS) is used to improve the quality of the MV images that are then combined with orthogonally acquired kV images to assess 3D motion. An anthropomorphic phantom with implanted gold seeds was used to assess accuracy of the method under static, typical prostatic, and respiratory motion scenarios. Automatic registra-tion of kV images and single MV frames or MV SA-DTS reconstructed with arc lengths from 2° to 7° with the appropriate reference fiducial template images was performed using special purpose-built software. Clinical feasibility was evaluated by retrospectively analyzing images acquired over four or five sessions for each of three patients undergoing hypofractionated prostate radiotherapy. The standard deviation of the registration error in phantom using MV SA-DTS was similar to single MV images for the static and prostate motion scenarios (σ = 0.25 mm). Under respiratory motion conditions, the standard deviation of the registration error increased to 0.7mm and 1.7 mm for single MV and MV SA-DTS, respectively. Registration failures were observed with the respiratory scenario only and were due to motion-induced fiducial blurring. For the three patients studied, the mean and standard deviation of the difference between automatic registration using 4° MV SA-DTS and manual registration using single MV images results was 0.07±0.52mm. The MV SA-DTS results in patients were, on average, superior to single-frame MV by nearly 1 mm - significantly more than what was observed in phantom. The best MV SA-DTS results were observed with arc lengths of 3° to 4°. Registration failures in patients using MV SA-DTS were primarily due to blockage of the gold seeds by the MLC. The failure rate varied from 2% to 16%. Combined MV SA-DTS and kV imaging is feasible for intratreatment motion monitoring during VMAT of anatomic sites where limited motion is expected, and improves registration accuracy compared to single MV/kV frames. To create a clinically robust technique, further improvements to ensure visualization of fiducials at the desired control points without degradation of the treatment plan are needed.

Adaptation, Commissioning, and Evaluation of a 3D Treatment Planning System for High-Resolution Small-Animal Irradiation.

Although spatially precise systems are now available for small-animal irradiations, there are currently limited software tools available for treatment planning for such irradiations. We report on the adaptation, commissioning, and evaluation of a 3-dimensional treatment planning system for use with a small-animal irradiation system. The 225-kV X-ray beam of the X-RAD 225Cx microirradiator (Precision X-Ray) was commissioned using both ion-chamber and radiochromic film for 10 different collimators ranging in field size from 1 mm in diameter to 40 × 40 mm(2) A clinical 3-dimensional treatment planning system (Metropolis) developed at our institution was adapted to small-animal irradiation by making it compatible with the dimensions of mice and rats, modeling the microirradiator beam orientations and collimators, and incorporating the measured beam data for dose calculation. Dose calculations in Metropolis were verified by comparison with measurements in phantoms. Treatment plans for irradiation of a tumor-bearing mouse were generated with both the Metropolis and the vendor-supplied software. The calculated beam-on times and the plan evaluation tools were compared. The dose rate at the central axis ranges from 74 to 365 cGy/min depending on the collimator size. Doses calculated with Metropolis agreed with phantom measurements within 3% for all collimators. The beam-on times calculated by Metropolis and the vendor-supplied software agreed within 1% at the isocenter. The modified 3-dimensional treatment planning system provides better visualization of the relationship between the X-ray beams and the small-animal anatomy as well as more complete dosimetric information on target tissues and organs at risk. It thereby enhances the potential of image-guided microirradiator systems for evaluation of dose-response relationships and for preclinical experimentation generally.

Technical Note: Intrafractional changes in time lag relationship between anterior-posterior external and superior-inferior internal motion signals 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 two cone-beam CTs (CBCT), one before and one after treatment. Time between scans was less than 30 min. 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. Purpose-built software tracked fiducials, representing internal signal, in CBCT projection images. Time lag between superior-inferior (SI) internal and anterior-posterior external signals was found by maximizing the correlation coefficient in each breathing cycle and averaging over all cycles. Time-lag-induced discrepancy between internal SI position and that predicted from the external signal (external prediction error) was also calculated. RESULTS: Mean ± standard deviation 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 17/18 scans. Change in time lag between pre- and post-treatment CBCT was 0.06 ± 0.07 s (range 0.01-0.22 s), corresponding to 3.1% ± 3.7% (range 0.6%-10.8%) of gate width (range 1.6-3.1 s). In only one patient, change in time lag exceeded 10% of the gate width. External prediction error over all scans of all patients varied from 0.1 ± 0.1 to 1.6 ± 0.4 mm. CONCLUSIONS: Time lag between internal motion along SI and external signals is small compared to the treatment gate width of abdominal patients examined in this study. Change in time lag within a treatment session, inferred from pre- to post-treatment measurements is also small, suggesting that a single measurement of time lag at the session start is adequate. These findings require confirmation in a larger number of patients.

Modeling pancreatic tumor motion using 4-dimensional computed tomography and surrogate markers.

PURPOSE: To assess intrafractional positional variations of pancreatic tumors using 4-dimensional computed tomography (4D-CT), their impact on gross tumor volume (GTV) coverage, the reliability of biliary stent, fiducial seeds, and the real-time position management (RPM) external marker as tumor surrogates for setup of respiratory gated treatment, and to build a correlative model of tumor motion. METHODS AND MATERIALS: We analyzed the respiration-correlated 4D-CT images acquired during simulation of 36 patients with either a biliary stent (n=16) or implanted fiducials (n=20) who were treated with RPM respiratory gated intensity modulated radiation therapy for locally advanced pancreatic cancer. Respiratory displacement relative to end-exhalation was measured for the GTV, the biliary stent, or fiducial seeds, and the RPM marker. The results were compared between the full respiratory cycle and the gating interval. Linear mixed model was used to assess the correlation of GTV motion with the potential surrogate markers. RESULTS: The average ± SD GTV excursions were 0.3 ± 0.2 cm in the left-right direction, 0.6 ± 0.3 cm in the anterior-posterior direction, and 1.3 ± 0.7 cm in the superior-inferior direction. Gating around end-exhalation reduced GTV motion by 46% to 60%. D95% was at least the prescribed 56 Gy in 76% of patients. GTV displacement was associated with the RPM marker, the biliary stent, and the fiducial seeds. The correlation was better with fiducial seeds and with biliary stent. CONCLUSIONS: Respiratory gating reduced the margin necessary for radiation therapy for pancreatic tumors. GTV motion was well correlated with biliary stent or fiducial seed displacements, validating their use as surrogates for daily assessment of GTV position during treatment. A patient-specific internal target volume based on 4D-CT is recommended both for gated and not-gated treatment; otherwise, our model can be used to predict the degree of GTV motion.

Evaluation of tumor localization in respiration motion-corrected cone-beam CT: prospective study in lung.

PURPOSE: Target localization accuracy of cone-beam CT (CBCT) images used in radiation treatment of respiratory disease sites is affected by motion artifacts (blurring and streaking). The authors have previously reported on a method of respiratory motion correction in thoracic CBCT at end expiration (EE). The previous retrospective study was limited to examination of reducing motion artifacts in a small number of patient cases. They report here on a prospective study in a larger group of lung cancer patients to evaluate respiratory motion-corrected (RMC)-CBCT ability to improve lung tumor localization accuracy and reduce motion artifacts in Linac-mounted CBCT images. A second study goal examines whether the motion correction derived from a respiration-correlated CT (RCCT) at simulation yields similar tumor localization accuracy at treatment. METHODS: In an IRB-approved study, 19 lung cancer patients (22 tumors) received a RCCT at simulation, and on one treatment day received a RCCT, a respiratory-gated CBCT at end expiration, and a 1-min CBCT. A respiration monitor of abdominal displacement was used during all scans. In addition to a CBCT reconstruction without motion correction, the motion correction method was applied to the same 1-min scan. Projection images were sorted into ten bins based on abdominal displacement, and each bin was reconstructed to produce ten intermediate CBCT images. Each intermediate CBCT was deformed to the end expiration state using a motion model derived from RCCT. The deformed intermediate CBCT images were then added to produce a final RMC-CBCT. In order to evaluate the second study goal, the CBCT was corrected in two ways, one using a model derived from the RCCT at simulation [RMC-CBCT(sim)], the other from the RCCT at treatment [RMC-CBCT(tx)]. Image evaluation compared uncorrected CBCT, RMC-CBCT(sim), and RMC-CBCT(tx). The gated CBCT at end expiration served as the criterion standard for comparison. Using automatic rigid image registration, each CBCT was registered twice to the gated CBCT, first aligned to spine, second to tumor in lung. Localization discrepancy was defined as the difference between tumor and spine registration. Agreement in tumor localization with the gated CBCT was further evaluated by calculating a normalized cross correlation (NCC) of pixel intensities within a volume-of-interest enclosing the tumor in lung. RESULTS: Tumor localization discrepancy was reduced with RMC-CBCT(tx) in 17 out of 22 cases relative to no correction. If one considers cases in which tumor motion is 5 mm or more in the RCCT, tumor localization discrepancy is reduced with RMC-CBCT(tx) in 14 out of 17 cases (p = 0.04), and with RMC-CBCT(sim) in 13 out of 17 cases (p = 0.05). Differences in localization discrepancy between correction models [RMC-CBCT(sim) vs RMC-CBCT(tx)] were less than 2 mm. In 21 out of 22 cases, improvement in NCC was higher with RMC-CBCT(tx) relative to no correction (p < 0.0001). Differences in NCC between RMC-CBCT(sim) and RMC-CBCT(tx) were small. CONCLUSIONS: Motion-corrected CBCT improves lung tumor localization accuracy and reduces motion artifacts in nearly all cases. Motion correction at end expiration using RCCT acquired at simulation yields similar results to that using a RCCT on the treatment day (2-3 weeks after simulation).

Automatic tracking of arbitrarily shaped implanted markers in kilovoltage projection images: a feasibility study.

PURPOSE: Certain types of commonly used fiducial markers take on irregular shapes upon implantation in soft tissue. This poses a challenge for methods that assume a predefined shape of markers when automatically tracking such markers in kilovoltage (kV) radiographs. The authors have developed a method of automatically tracking regularly and irregularly shaped markers using kV projection images and assessed its potential for detecting intrafractional target motion during rotational treatment. METHODS: Template-based matching used a normalized cross-correlation with simplex minimization. Templates were created from computed tomography (CT) images for phantom studies and from end-expiration breath-hold planning CT for patient studies. The kV images were processed using a Sobel filter to enhance marker visibility. To correct for changes in intermarker relative positions between simulation and treatment that can introduce errors in automatic matching, marker offsets in three dimensions were manually determined from an approximately orthogonal pair of kV images. Two studies in anthropomorphic phantom were carried out, one using a gold cylindrical marker representing regular shape, another using a Visicoil marker representing irregular shape. Automatic matching of templates to cone beam CT (CBCT) projection images was performed to known marker positions in phantom. In patient data, automatic matching was compared to manual matching as an approximate ground truth. Positional discrepancy between automatic and manual matching of less than 2 mm was assumed as the criterion for successful tracking. Tracking success rates were examined in kV projection images from 22 CBCT scans of four pancreas, six gastroesophageal junction, and one lung cancer patients. Each patient had at least one irregularly shaped radiopaque marker implanted in or near the tumor. In addition, automatic tracking was tested in intrafraction kV images of three lung cancer patients with irregularly shaped markers during 11 volumetric modulated arc treatments. Purpose-built software developed at our institution was used to create marker templates and track the markers embedded in kV images. RESULTS: Phantom studies showed mean ± standard deviation measurement uncertainty of automatic registration to be 0.14 ± 0.07 mm and 0.17 ± 0.08 mm for Visicoil and gold cylindrical markers, respectively. The mean success rate of automatic tracking with CBCT projections (11 frames per second, fps) of pancreas, gastroesophageal junction, and lung cancer patients was 100%, 99.1% (range 98%-100%), and 100%, respectively. With intrafraction images (approx. 0.2 fps) of lung cancer patients, the success rate was 98.2% (range 97%-100%), and 94.3% (range 93%-97%) using templates from 1.25 mm and 2.5 mm slice spacing CT scans, respectively. Correction of intermarker relative position was found to improve the success rate in two out of eight patients analyzed. CONCLUSIONS: The proposed method can track arbitrary marker shapes in kV images using templates generated from a breath-hold CT acquired at simulation. The studies indicate its feasibility for tracking tumor motion during rotational treatment. Investigation of the causes of misregistration suggests that its rate of incidence can be reduced with higher frequency of image acquisition, templates made from smaller CT slice spacing, and correction of changes in intermarker relative positions when they occur.

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

PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

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 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. METHODS: 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. 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, 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). 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.

Correction of motion artifacts in cone-beam CT using a patient-specific respiratory motion model.

PURPOSE: Respiratory motion adversely affects CBCT image quality and limits its localization accuracy for image-guided radiation treatment. Motion correction methods in CBCT have focused on the thorax because of its higher soft tissue contrast, whereas low-contrast tissue in abdomen remains a challenge. The authors report on a method to correct respiration-induced motion artifacts in 1 min CBCT scans that is applicable in both thorax and abdomen, using a motion model adapted to the patient from a respiration-correlated image set. METHODS: Model adaptation consists of nonrigid image registration that maps each image to a reference image in the respiration-correlated set, followed by a principal component analysis to reduce errors in the nonrigid registration. The model parametrizes the deformation field in terms of observed surrogate (diaphragm or implanted marker) position and motion (inhalation or exhalation) between the images. In the thorax, the model is obtained from the same CBCT images that are to be motion-corrected, whereas in the abdomen, the model uses respiration-correlated CT (RCCT) images acquired prior to the treatment session. The CBCT acquisition is a single 360 degrees rotation lasting 1 min, while simultaneously recording patient breathing. The approximately 600 projection images are sorted into six (in thorax) or ten (in abdomen) subsets and reconstructed to obtain a set of low-quality respiration-correlated RC-CBCT images. Application of the motion model deforms each of the RC-CBCT images to a chosen reference image in the set; combining all images yields a single high-quality CBCT image with reduced blurring and motion artifacts. Repeated application of the model with different reference images produces a series of motion-corrected CBCT images over the respiration cycle, for determining the motion extent of the tumor and nearby organs at risk. The authors also investigate a simpler correction method, which does not use PCA and correlates motion state with respiration phase, thus assuming repeatable breathing patterns. Comparison of contrast-to-noise ratios of pixel intensities within anatomical structures relative to surrounding background tissue provides a quantitative assessment of relative organ visibility. RESULTS: Evaluation in lung phantom, two patient cases in thorax and two in upper abdomen, shows that blurring and streaking artifacts are visibly reduced with motion correction. The boundaries of tumors in the thorax, liver, and kidneys are sharper and more discernible. Repeat application of the method in one thorax case, with reference images chosen at end expiration and end inspiration, indicates its feasibility for observing tumor motion extent. Phase-based motion correction without PCA reduces blurring less effectively; in addition, implanted markers appear broken up, indicating inconsistencies in the phase-based correction. In structures showing 1 cm or more motion excursion, PCA-based motion correction shows the highest contrast-to-noise ratios in the cases examined. CONCLUSIONS: Motion correction of CBCT is feasible and yields observable improvement in the thorax and abdomen. The PCA-based model is an important component: First, by reducing deformation errors caused by the nonrigid registration and second, by relating deformation to surrogate position rather than phase, thus accommodating breathing pattern changes between imaging sessions. The accuracy of the method requires confirmation in further patient studies.

Evaluation of respiration-correlated digital tomosynthesis in lung.

Digital tomosynthesis (DTS) with a linear accelerator-mounted imaging system provides a means of reconstructing tomographic images from radiographic projections over a limited gantry arc, thus requiring only a few seconds to acquire. Its application in the thorax, however, often results in blurred images from respiration-induced motion. This work evaluates the feasibility of respiration-correlated (RC) DTS for soft-tissue visualization and patient positioning. Image data acquired with a gantry-mounted kilovoltage imaging system while recording respiration were retrospectively analyzed from patients receiving radiotherapy for non-small-cell lung carcinoma. Projection images spanning an approximately 30 degrees gantry arc were sorted into four respiration phase bins prior to DTS reconstruction, which uses a backprojection, followed by a procedure to suppress structures above and below the reconstruction plane of interest. The DTS images were reconstructed in planes at different depths through the patient and normal to a user-selected angle close to the center of the arc. The localization accuracy of RC-DTS was assessed via a comparison with CBCT. Evaluation of RC-DTS in eight tumors shows visible reduction in image blur caused by the respiratory motion. It also allows the visualization of tumor motion extent. The best image quality is achieved at the end-exhalation phase of the respiratory motion. Comparison of RC-DTS with respiration-correlated cone-beam CT in determining tumor position, motion extent and displacement between treatment sessions shows agreement in most cases within 2-3 mm, comparable in magnitude to the intraobserver repeatability of the measurement. These results suggest the method's applicability for soft-tissue image guidance in lung, but must be confirmed with further studies in larger numbers of patients.

Shape-correlated Deformation Statistics for Respiratory Motion Prediction in 4D Lung.

4D image-guided radiation therapy (IGRT) for free-breathing lungs is challenging due to the complicated respiratory dynamics. Effective modeling of respiratory motion is crucial to account for the motion affects on the dose to tumors. We propose a shape-correlated statistical model on dense image deformations for patient-specic respiratory motion estimation in 4D lung IGRT. Using the shape deformations of the high-contrast lungs as the surrogate, the statistical model trained from the planning CTs can be used to predict the image deformation during delivery verication time, with the assumption that the respiratory motion at both times are similar for the same patient. Dense image deformation fields obtained by diffeomorphic image registrations characterize the respiratory motion within one breathing cycle. A point-based particle optimization algorithm is used to obtain the shape models of lungs with group-wise surface correspondences. Canonical correlation analysis (CCA) is adopted in training to maximize the linear correlation between the shape variations of the lungs and the corresponding dense image deformations. Both intra- and inter-session CT studies are carried out on a small group of lung cancer patients and evaluated in terms of the tumor location accuracies. The results suggest potential applications using the proposed method.

From phase-based to displacement-based gating: a software tool to facilitate respiration-gated radiation treatment.

The Varian Real-time Position Management (RPM) system allows respiratory gating based on either the phase or displacement (amplitude) of the breathing waveform. A problem in clinical application is that phase-based gating, required for respiration-correlated (4D-CT) simulation, is not robust to irregular breathing patterns during treatment, and a widely used system version (1.6) does not provide an easy means to change from a phase-based gate into an equivalent displacement-based one. We report on the development and evaluation of a robust method to convert phase-gate thresholds, set by the physician, into equivalent displacement-gate thresholds to facilitate its clinical application to treatment. The software tool analyzes the respiration trace recorded during the 4D-CT simulation, and determines a relationship between displacement and phase through a functional fit. The displacement gate thresholds are determined from an average of two values of this function, corresponding to the start and end thresholds of the original phase gate. The software tool was evaluated in two ways: first, whether in-gate residual target motion and predicted treatment beam duty cycle are equivalent between displacement gating and phase gating during 4D-CT simulation (using retrospective phase recalculation); second, whether residual motion is improved with displacement gating during treatment relative to phase gating (using real-time phase calculation). Residual target motion was inferred from the respiration traces and quantified in terms of mean and standard deviation in-gate displacement measured relative to the value at the start of the recorded trace. For retrospectively-calculated breathing traces compared with real-time calculated breathing traces, we evaluate the inaccuracies of real-time phase calculation by measuring the phase gate position in each trace as well as the mean in-gate displacement and standard deviation of the displacement. Retrospectively-calculated data from ten patients were analyzed. The patient averaged in-gate mean +/- standard deviation displacement (representing residual motion) was reduced from 0.16 +/- 0.14 cm for phase gating under simulation conditions to 0.12 +/- 0.08 cm for displacement gating. Evaluation of respiration traces under treatment conditions (real-time phase calculation) showed that the average displacement gate threshold results in a lower in-gate mean and residual motion (variance) for all patients studied. The patient-averaged in-gate mean +/- standard deviation displacement was reduced from 0.26 +/- 0.18 cm for phase gating (under treatment conditions) to 0.15 +/- 0.09 cm for displacement gating. Real-time phase gating sometimes leads to gating on incorrect portions of the breathing cycle when the breathing trace is irregular. Displacement gating is less prone to such errors, as evidenced by the lower in-gate residual motion in a large majority of cases.

A SHAPE-NAVIGATED IMAGE DEFORMATION MODEL FOR 4D LUNG RESPIRATORY MOTION ESTIMATION.

Intensity modulated radiation therapy (IMRT) for cancers in the lung remains challenging due to the complicated respiratory dynamics. We propose a shape-navigated dense image deformation model to estimate the patient-specific breathing motion using 4D respiratory correlated CT (RCCT) images. The idea is to use the shape change of the lungs, the major motion feature in the thorax image, as a surrogate to predict the corresponding dense image deformation from training.To build the statistical model, dense diffeomorphic deformations between images of all other time points to the image at end expiration are calculated, and the shapes of the lungs are automatically extracted. By correlating the shape variation with the temporally corresponding image deformation variation, a linear mapping function that maps a shape change to its corresponding image deformation is calculated from the training sample. Finally, given an extracted shape from the image at an arbitrary time point, its dense image deformation can be predicted from the pre-computed statistics.The method is carried out on two patients and evaluated in terms of the tumor and lung estimation accuracies. The result shows robustness of the model and suggests its potential for 4D lung radiation treatment planning.

Quality assurance challenges for motion-adaptive radiation therapy: gating, breath holding, and four-dimensional computed tomography.

Compared with conventional three-dimensional (3D) conformal radiation therapy and intensity-modulated radiation therapy treatments, quality assurance (QA) for motion-adaptive radiation therapy involves various challenges because of the added temporal dimension. Here we discuss those challenges for three specific techniques related to motion-adaptive therapy: namely respiratory gating, breath holding, and four-dimensional computed tomography. Similar to the introduction of any other new technologies in clinical practice, typical QA measures should be taken for these techniques also, including initial testing of equipment and clinical procedures, as well as frequent QA examinations during the early stage of implementation. Here, rather than covering every QA aspect in depth, we focus on some major QA challenges. The biggest QA challenge for gating and breath holding is how to ensure treatment accuracy when internal target position is predicted using external surrogates. Recommended QA measures for each component of treatment, including simulation, planning, patient positioning, and treatment delivery and verification, are discussed. For four-dimensional computed tomography, some major QA challenges have also been discussed.

Automated finite-element analysis for deformable registration of prostate images.

Two major factors preventing the routine clinical use of finite-element analysis for image registration are: 1) the substantial labor required to construct a finite-element model for an individual patient's anatomy and 2) the difficulty of determining an appropriate set of finite-element boundary conditions. This paper addresses these issues by presenting algorithms that automatically generate a high quality hexahedral finite-element mesh and automatically calculate boundary conditions for an imaged patient. Medial shape models called m-reps are used to facilitate these tasks and reduce the effort required to apply finite-element analysis to image registration. Encouraging results are presented for the registration of CT image pairs which exhibit deformation caused by pressure from an endorectal imaging probe and deformation due to swelling.