RESUMEN
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.
Asunto(s)
Tomografía Computarizada de Haz Cónico/métodos , Neoplasias Pancreáticas/radioterapia , Radioterapia Guiada por Imagen/métodos , Neoplasias Gástricas/radioterapia , Adulto , Anciano , Neoplasias Esofágicas/diagnóstico por imagen , Neoplasias Esofágicas/radioterapia , Unión Esofagogástrica/diagnóstico por imagen , Femenino , Humanos , Masculino , Persona de Mediana Edad , Movimiento (Física) , Neoplasias Pancreáticas/diagnóstico por imagen , Estudios Prospectivos , Planificación de la Radioterapia Asistida por Computador , Respiración , Neoplasias Gástricas/diagnóstico por imagenRESUMEN
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).
Asunto(s)
Tomografía Computarizada de Haz Cónico/métodos , Neoplasias Pulmonares/diagnóstico por imagen , Pulmón/diagnóstico por imagen , Movimiento (Física) , Respiración , Abdomen/fisiopatología , Artefactos , Simulación por Computador , Diafragma/diagnóstico por imagen , Diafragma/fisiopatología , Humanos , Pulmón/fisiopatología , Neoplasias Pulmonares/fisiopatología , Neoplasias Pulmonares/radioterapia , Modelos Biológicos , Reconocimiento de Normas Patrones Automatizadas/métodos , Estudios Prospectivos , Columna Vertebral/diagnóstico por imagenRESUMEN
PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
Asunto(s)
Artefactos , Procesamiento de Imagen Asistido por Computador/métodos , Modelos Biológicos , Movimiento , Respiración , Tomografía Computarizada por Rayos X/métodos , HumanosRESUMEN
PURPOSE: To evaluate the use of megavoltage cone-beam computed tomography (MV CBCT) to measure interfractional variation in lung tumor position. METHODS AND MATERIALS: Eight non-small-cell lung cancer patients participated in the study, 4 with respiratory gating and 4 without. All patients underwent MV CBCT scanning at weekly intervals. Contoured planning CT and MV CBCT images were spatially registered based on vertebral anatomy, and displacements of the tumor centroid determined. Setup error was assessed by comparing weekly portal orthogonal radiographs with digitally reconstructed radiographs generated from planning CT images. Hypothesis testing was performed to test the statistical significance of the volume difference, centroid displacement, and setup uncertainty. RESULTS: The vertebral bodies and soft tissue portions of tumor within lung were visible on the MV CBCT scans. Statistically significant systematic volume decrease over the course of treatment was observed for 1 patient. The average centroid displacement between simulation CT and MV CBCT scans were 2.5 mm, -2.0 mm, and -1.5 mm with standard deviations of 2.7 mm, 2.7 mm, and 2.6 mm in the right-left, anterior-posterior and superior-inferior directions. The mean setup errors were smaller than the centroid shifts, while the standard deviations were comparable. In most cases, the gross tumor volume (GTV) defined on the MV CBCT was located on average at least 5 mm inside a 10 mm expansion of the GTV defined on the planning CT scan. CONCLUSIONS: The MV CBCT technique can be used to image lung tumors and may prove valuable for image-guided radiotherapy. Our conclusions must be verified in view of the small patient number.
Asunto(s)
Carcinoma de Pulmón de Células no Pequeñas/diagnóstico por imagen , Carcinoma de Pulmón de Células no Pequeñas/radioterapia , Neoplasias Pulmonares/diagnóstico por imagen , Neoplasias Pulmonares/radioterapia , Movimiento , Tomografía Computarizada por Rayos X/métodos , Algoritmos , Estudios de Factibilidad , Humanos , Variaciones Dependientes del Observador , Aceleradores de Partículas , Planificación de la Radioterapia Asistida por Computador/métodosRESUMEN
The modeling of respiratory motion is important for a more accurate understanding and accounting of its effect on dose to cancers in the thorax and abdomen by radiotherapy. We have developed a model of respiration-induced organ motion in the thorax without the commonly adopted assumption of repeatable breath cycles. The model describes the motion of a volume of interest within the patient based on a reference three-dimensional (3D) image (at end expiration) and the diaphragm positions at different time points. The input data are respiration-correlated CT (RCCT) images of patients treated for non-small- cell lung cancer, consisting of 3D images, including the diaphragm positions, at ten phases of the respiratory cycle. A deformable image registration algorithm calculates the deformation field that maps each 3D image to the reference 3D image. A principal component analysis is performed to parameterize the 3D deformation field in terms of the diaphragm motion. We show that the first two principal components are adequate to accurately and completely describe the organ motion in the data of four patients. Artifacts in the RCCT images that commonly occur at the mid-respiration states are reduced in the model-generated images. Further validation of the model is demonstrated in the successful application of the parameterized 3D deformation field to RCCT data of the same patient but acquired several days later. We have developed a method for predicting respiration-induced organ motion in patients that has potential for improving the accuracy of dose calculation in radiotherapy. Possible limitations of the model are cases where the correlation between lung tumor and diaphragm position is less reliable such as superiorly situated tumors and interfraction changes in tumor-diaphragm correlation. The limited number of clinical cases examined suggests, but does not confirm, the model's applicability to a wide range of patients.
Asunto(s)
Modelos Biológicos , Movimiento , Pacientes , Planificación de la Radioterapia Asistida por Computador/métodos , Respiración , Neoplasias Abdominales/diagnóstico por imagen , Neoplasias Abdominales/fisiopatología , Neoplasias Abdominales/radioterapia , Espiración , Humanos , Imagenología Tridimensional , Inhalación , Neoplasias Pulmonares/diagnóstico por imagen , Neoplasias Pulmonares/fisiopatología , Neoplasias Pulmonares/radioterapia , Neoplasias Torácicas/diagnóstico por imagen , Neoplasias Torácicas/fisiopatología , Neoplasias Torácicas/radioterapia , Tomografía Computarizada por Rayos XRESUMEN
PURPOSE: We investigate the characteristics of lung tumor motion measured with respiration-correlated computed tomography (RCCT) and examine the method's applicability to radiotherapy planning and treatment. METHODS AND MATERIALS: Six patients treated for non-small-cell lung carcinoma received a helical single-slice computed tomography (CT) scan with a slow couch movement (1 mm/s), while simultaneously respiration is recorded with an external position-sensitive monitor. Another 6 patients receive a 4-slice CT scan in a cine mode, in which sequential images are acquired for a complete respiratory cycle at each couch position while respiration is recorded. The images are retrospectively resorted into different respiration phases as measured with the external monitor (4-slice data) or patient surface displacement observed in the images (single-slice data). The gross tumor volume (GTV) in lung is delineated at one phase and serves as a visual guide for delineation at other phases. Interfractional GTV variation is estimated by scaling diaphragm position variations measured in gated radiographs at treatment with the ratio of GTV:diaphragm displacement observed in the RCCT data. RESULTS: Seven out of 12 patients show GTV displacement with respiration of more than 1 cm, primarily in the superior-inferior (SI) direction; 2 patients show anterior-posterior displacement of more than 1 cm. In all cases, extremes in GTV position in the SI direction are consistent with externally measured extremes in respiration. Three patients show evidence of hysteresis in GTV motion, in which the tumor trajectory is displaced 0.2 to 0.5 cm anteriorly during expiration relative to inspiration. Significant (>1 cm) expansion of the GTV in the SI direction with respiration is observed in 1 patient. Estimated intrafractional GTV motion for gated treatment at end expiration is 0.6 cm or less in all cases; however; interfraction variation estimates (systematic plus random) are more than 1 cm in 3/9 patients. CONCLUSION: Respiration-correlated CT can be performed with currently available CT equipment and acquisition settings. RCCT provides not only three-dimensional information on intrafractional tumor motion and deformation, but also allows estimates of interfractional tumor variation when combined with radiographic measurements of diaphragm position variation during treatment.
Asunto(s)
Carcinoma de Pulmón de Células no Pequeñas/diagnóstico por imagen , Neoplasias Pulmonares/diagnóstico por imagen , Movimiento , Respiración , Tomografía Computarizada por Rayos X/métodos , Humanos , Planificación de la Radioterapia Asistida por ComputadorRESUMEN
BACKGROUND AND PURPOSE: To study the effect of breathing motion on gross tumor volume (GTV) coverage for lung tumors using dose-volume histograms and relevant dosimetric indices. PATIENTS AND METHODS: Treatment plans were chosen for 12 patients treated at our institution for lung carcinoma. GTV volumes of these patients ranged from 1.2 to 97.3 cm(3). A margin of 1-2 cm was used to generate the planning target volume (PTV). Additional margins of 0.6-1.0 cm were added to the PTV when designing treatment portals. For the purposes of TCP calculation, the prescription dose was assumed to be 70 Gy to remove the effects of prescription differences. Setup error was incorporated into the evaluation of treatment plans with a systematic component of sigma(RL) = 0.2 cm, sigma(AP) = 0.2 cm, and sigma(SI) = 0.3 cm and a random component of sigma(RL) = 0.3 cm, sigma(AP) = 0.3 cm, and sigma(SI) = 0.3 cm. Breathing motion was incorporated into these plans based on an independent analysis of fluoroscopic movies of the diaphragm for 7 patients. The systematic component of breathing motion (sigma(RL) = 0.3 cm, sigma(AP) = 0.2 cm, and sigma(SI) = 0.6 cm) was incorporated into the treatment plans on a slice by slice basis. The intrafractional component of breathing motion (sigma(RL) = 0.3 cm, sigma(AP) = 0.2 cm, and sigma(SI) = 0.6 cm) was incorporated by averaging the dose calculation over all displacements of the breathing cycle. Each patient was simulated 500 times to discern the range of possible outcomes. The simulations were repeated for a worst case scenario which used only breathing data with a large diaphragmatic excursion, both with and without intrafractional breathing motion. RESULTS: Dose to 95% of the GTV (D95), volume of the GTV receiving 95% of the prescription dose (V95) and TCP changed an average of -1.4+/-4.2, -1.0+/-3.3, and -1.4+/-3.8%, respectively, with the incorporation of normal breathing effects. In the worst case scenario (heavy breathers), D95 and V95 changed an average of -9.8+/-10.1 and -8.3+/-11.3%, respectively, and TCP changed by -8.1+/-9.1%. GTVs with volumes greater than 60 cm(3) showed stronger sensitivity to breathing especially if the shape was non-ellipsoidal. In the normal breathing case, the probability of a decrease in D95, V95, or TCP of a magnitude greater than 10% is less than 4%, and in the worse case scenario this probability is approximately 30-40% with intrafractional breathing motion included, and less than 10% with intrafractional breathing motion not included. CONCLUSIONS: With the PTV margins routinely used at our center, the effects of normal breathing on coverage are small on the average, with a less than 4% chance of a 10% or greater decrease in D95, V95, or TCP. However, in patients with large respiration-induced motion, the effect can be significant and efforts to identify such patients are important.