Four-dimensional CT Images Research Articles

Spatiotemporal correlation enhanced real-time 4D-CBCT imaging using convolutional LSTM networks.

To enhance the accuracy of real-time four-dimensional cone beam CT (4D-CBCT) imaging by incorporating spatiotemporal correlation from the sequential projection image into the single projection-based 4D-CBCT estimation process. We first derived 4D deformation vector fields (DVFs) from patient 4D-CT. Principal component analysis (PCA) was then employed to extract distinctive feature labels for each DVF, focusing on the first three PCA coefficients. To simulate a wide range of respiratory motion, we expanded the motion amplitude and used random sampling to generate approximately 900 sets of PCA labels. These labels were used to produce 900 simulated 4D-DVFs, which in turn deformed the 0% phase 4D-CT to obtain 900 CBCT volumes with continuous motion amplitudes. Following this, the forward projection was performed at one angle to get all of the digital reconstructed radiographs (DRRs). These DRRs and the PCA labels were used as the training data set. To capture the spatiotemporal correlation in the projections, we propose to use the convolutional LSTM (ConvLSTM) network for PCA coefficient estimation. For network testing, when several online CBCT projections (with different motion amplitudes that cover the full respiration range) are acquired and sent into the network, the corresponding 4D-PCA coefficients will be obtained and finally lead to a full online 4D-CBCT prediction. A phantom experiment is first performed with the XCAT phantom; then, a pilot clinical evaluation is further conducted. Results on the XCAT phantom and the patient data show that the proposed approach outperformed other networks in terms of visual inspection and quantitative metrics. For the XCAT phantom experiment, ConvLSTM achieves the highest quantification accuracy with MAPE(Mean Absolute Percentage Error), PSNR (Peak Signal-to-Noise Ratio), and RMSE(Root Mean Squared Error) of 0.0459, 64.6742, and 0.0011, respectively. For the patient pilot clinical experiment, ConvLSTM also achieves the best quantification accuracy with that of 0.0934, 63.7294, and 0.0019, respectively. The quantification evaluation labels that we used are 1) the Mean Absolute Error (MAE), 2) the Normalized Cross Correlation (NCC), 3)the Structural Similarity Index Measurement(SSIM), 4)the Peak Signal-to-Noise Ratio (PSNR), 5)the Root Mean Squared Error(RMSE), and 6) the Absolute Percentage Error (MAPE). The spatiotemporal correlation-based respiration motion modeling supplied a potential solution for accurate real-time 4D-CBCT reconstruction.

Optimization of mesh generation for geometric accuracy, robustness, and efficiency of biomechanical-model-based deformable image registration.

Successful generation of biomechanical-model-based deformable image registration (BM-DIR) relies on user-defined parameters that dictate surface mesh quality. The trial-and-error process to determine the optimal parameters can be labor-intensive and hinder DIR efficiency and clinical workflow. To identify optimal parameters in surface mesh generation as boundary conditions for a BM-DIR in longitudinal liver and lung CT images to facilitate streamlined image registration processes. Contrast-enhanced CT images of 29 colorectal liver cancer patients and end-exhale four-dimensional CT images of 26 locally advanced non-small cell lung cancer patients were collected. Different combinations of parameters that determine the triangle mesh quality (voxel side length and triangle edge length) were investigated. The quality of DIRs generated using these parameters was evaluated with metrics for geometric accuracy, robustness, and efficiency. Metrics for geometric accuracy included target registration error (TRE) of internal vessel bifurcations, dice similar coefficient (DSC), mean distance to agreement (MDA), Hausdorff distance (HD) for organ contours, and number of vertices in the triangle mesh. American Association of Physicists in Medicine Task Group 132 was used to ensure parameters met TRE, DSC, MDA recommendations before the comparison among the parameters. Robustness was evaluated as the success rate of DIR generation, and efficiency was evaluated as the total time to generate boundary conditions and compute finite element analysis. Voxel side length of 0.2cm and triangle edge length of 3 were found to be the optimal parameters for both liver and lung, with success rate of 1.00 and 0.98 and average DIR computation time of 100 and 143s, respectively. For this combination, the average TRE, DSC, MDA, and HD were 0.38-0.40, 0.96-0.97, 0.09-0.12, and 0.87-1.17mm, respectively. The optimal parameters were found for the analyzed patients. The decision-making process described in this study serves as a recommendation for BM-DIR algorithms to be used for liver and lung. These parameters can facilitate consistence in the evaluation of published studies and more widespread utilization of BM-DIR in clinical practice.

Fluoroscopic 3D Image Generation from Patient-Specific PCA Motion Models Derived from 4D-CBCT Patient Datasets: A Feasibility Study.

A method for generating fluoroscopic (time-varying) volumetric images using patient-specific motion models derived from four-dimensional cone-beam CT (4D-CBCT) images was developed. 4D-CBCT images acquired immediately prior to treatment have the potential to accurately represent patient anatomy and respiration during treatment. Fluoroscopic 3D image estimation is performed in two steps: (1) deriving motion models and (2) optimization. To derive motion models, every phase in a 4D-CBCT set is registered to a reference phase chosen from the same set using deformable image registration (DIR). Principal components analysis (PCA) is used to reduce the dimensionality of the displacement vector fields (DVFs) resulting from DIR into a few vectors representing organ motion found in the DVFs. The PCA motion models are optimized iteratively by comparing a cone-beam CT (CBCT) projection to a simulated projection computed from both the motion model and a reference 4D-CBCT phase, resulting in a sequence of fluoroscopic 3D images. Patient datasets were used to evaluate the method by estimating the tumor location in the generated images compared to manually defined ground truth positions. Experimental results showed that the average tumor mean absolute error (MAE) along the superior–inferior (SI) direction and the 95th percentile in two patient datasets were 2.29 and 5.79 mm for patient 1, and 1.89 and 4.82 mm for patient 2. This study demonstrated the feasibility of deriving 4D-CBCT-based PCA motion models that have the potential to account for the 3D non-rigid patient motion and localize tumors and other patient anatomical structures on the day of treatment.

Prediction and Analysis of Respiratory Circulation System in Radiotherapy Patients by Four-Dimensional Computed Tomography Image Technology

Usually, radiotherapy not only acts on the parts that need to be treated, but also radiates on the normal parts of the human body, resulting in damage to the normal parts. Recently, some scholars have used the fourdimensional CT image technology to monitor and adjust the radiotherapy process in real time, which can reduce the damage to the normal parts. Therefore, it is a very meaningful subject to apply the real-time monitoring technology to the radiotherapy process of the respiratory circulation system. In order to reduce the damage of related organs in the respiratory circulation system during radiotherapy, this paper optimizes the particle swarm optimization (PSO) algorithm and combines it with artificial neural network (ANN) technology to predict and analyze the respiratory circulation system of human body. The results show that in the analysis of CT image results, there is no significant difference in respiratory flow velocity between the left lung and the right lung from three-dimensional point of view (P > 0.05). Different algorithms are used to analyze the respiratory circulation system, and it is found that the model constructed in this paper can effectively reduce the probability of BP-NN (Back Propagation-Neural Network) falling into the local optimum, and the error is reduced by 25%, while the effect of the original PSO algorithm is inferior to that of the model constructed. Therefore, through this study, it is found that the PSO algorithm can be used in real-time monitoring of the radiotherapy process, and its prediction accuracy has been significantly improved, which achieves the expected effect, and provides experimental basis for the later clinical radiotherapy of respiratory circulation system.

Implementación y validación de un protocolo de IGRT basado en imagen de kV de fluoroscopia y CBCT para el tratamiento de SBRT pulmonar

The aim of this work is to describe our Image-Guided Radiation Therapy (IGRT) protocol for lung Stereotactic Body Radiation Therapy (SBRT) together with the evaluation of the results from applying this protocol over a sample of 47 patients analyzed retrospectively. Simulation time-resolved four-dimensional CT (4DCT) images are acquired taking into account the respiratory cycle of the patient. During the treatment, using VMAT technique, pre- and post- treatment Cone Beam Computer Tomography (CBCT), as well as intrafraction fluoroscopy whenever possible due to lesion position visualization, are performed to verify tumor amplitude motion and position. Fluoroscopy image was acquired in 72% of patients analyzed, from which 71% verified the right position against 29% who needed to be reposition by using intrafraction CBCT at least in one fraction. Post-treatment CBCT systematic and random errors are below 1 mm, thereby protocol validation is accepted. Fluoroscopy manages to verify tumor position accuracy depending on high contrast visualization. However, in comparison to intrafraction CBCT, it involves reducing treatment duration and minimizing dose to patient. Fluoroscopy, in conjunction with CBCT, allows monitoring motion during the treatment.

Carpal kinematic changes after scaphoid nonunion: an in vivo study with four-dimensional CT imaging

The aim was to evaluate if motion between the scaphoid bone fragments is related to the position of the fracture line and if a scaphoid nonunion results in the uncoupling of the proximal and distal carpal row during wrist motion. The influence of dorsal intercalated segment instability on interfragmentary motion was also analysed. In this study, 12 patients were included with unilateral scaphoid nonunion. Four-dimensional computerized tomography was used to analyse flexion–extension and radioulnar deviation motion of both wrists. We found that an increased instability of the scaphoid fragments is associated with the presence of dorsal intercalated segment instability and is not dependent on the position of the fracture line relative to the scaphoid apex. Additionally, a scaphoid nonunion results in an uncoupling of the carpal rows.

Tumour volume comparison between 16-row multi-detector computed tomography and 320-row area-detector computed tomography in patients with small lung tumours treated with stereotactic body radiotherapy: Effect of respiratory motion

PurposeWe compared image quality and volume of a moving simulated tumour and of lung tumours in patients who were treated with stereotactic body radiotherapy (SBRT) in a 16-row multi-detector CT (MDCT) versus a 320-row area-detector CT (ADCT). Tumour volumes in each respiratory phase were also evaluated. Materials and MethodsWe acquired static and four-dimensional CT (4DCT) images of a moving phantom with 10- and 30-mm amplitudes with three periods of patterns (2, 4, and 6 s). Breath-hold and 4DCT images were acquired for 12 lung tumour patients who underwent SBRT. Image data were acquired via MDCT and ADCT. The tumours were delineated in each respiratory phase and their volumes in end-expiratory/end-inspiratory phase and mid-respiratory phase were compared. ResultsIn the phantom study, tumour volumes were smaller and closer to the static image when evaluated by ADCT than by MDCT. In the clinical study, average tumour volumes ± standard deviations were 9.58 ± 1.07 cm3 with MDCT (2.5-mm slice), and 7.12 ± 0.23 cm3 with ADCT (p < 0.01). Tumour volumes were closer to that of the breath hold CT in all patients evaluated by ADCT than by MDCT. Unlike MDCT, tumour volumes acquired by ADCT were smaller in end-expiratory or end-inspiratory phase than in the mid-respiratory phase. ConclusionsTumour volumes in each of the respiratory phases in ADCT were significantly smaller and closer to the static image than the corresponding volumes in MDCT. This suggests that treated volume can be reduced if ADCT is used in treatment planning.

CT-based ventilation imaging in radiation oncology.

A form of lung function imaging is emerging that uses phase-resolved four-dimensional CT (4DCT or breath-hold CT) images along with image processing techniques to generate lung function maps that provide a surrogate of lung ventilation. CT-based ventilation (referred to as CT-ventilation) research has gained momentum in Radiation Oncology because many lung cancer patients undergo four-dimensional CT simulation as part of the standard treatment planning process. Therefore, generating CT-ventilation images provides functional information without burdening the patient with an extra imaging procedure.CT-ventilation has progressed from an image processing calculation methodology, to validation efforts, to retrospective demonstration of clinical utility in Radiation Oncology. In particular, CT-ventilation has been proposed for two main clinical applications: functional avoidance radiation therapy and thoracic dose–response assessment. The idea of functional avoidance radiation therapy is to preferentially spare functional portions of the lung (as measured by CT-ventilation) during radiation therapy with the hypothesis that reducing dose to functional portions of the lung will lead to reduced rates of radiation-related thoracic toxicity. The idea of imaging-based dose–response assessment is to evaluate pre- to post-treatment CT-ventilation-based imaging changes. The hypothesis is that early, imaging-change-based response can be an early predictor of subsequent thoracic toxicity. Based on the retrospective evidence, the clinical applications of CT-ventilation have progressed from the retrospective setting to on-going prospective clinical trials. This review will cover basic CT-ventilation calculation methodologies, validation efforts, presentation of clinical applications, summarize on-going clinical trials, review potential uncertainties and shortcomings of CT-ventilation, and discuss future directions of CT-ventilation research.

High-quality reconstruction of four-dimensional cone beam CT from motion registration prior image

Four-dimensional cone beam CT (4D-CBCT) imaging can provide accurate location information of real-time breathing for imaging-guided radiotherapy. How to improve the accuracy of 4D-CBCT reconstruction image is a hot topic in current studies. PICCS algorithm performs remarkably in all 4D-CBCT reconstruction algorithms based on CS theory. The improved PICCS algorithm proposed in this paper improves the prior image on the basis of the traditional PICCS algorithm. According to the location information of each phase, the corresponding prior image is constructed, which completely eliminates the motion blur of the reconstructed image caused by the mismatch of the projection data. Meanwhile, the data fidelity model of the proposed method is consistent with the traditional PICCS algorithm. The experimental results showed that the reconstructed image using the proposed method had a clearer organization boundary compared with that of images reconstructed using the traditional PICCS algorithm. This proposed method significantly reduced the motion artifact and improved the image resolution.

Comparison of internal target volumes defined on 3-dimensional, 4-dimensonal, and cone-beam CT images of non-small-cell lung cancer.

PurposeThe purpose of this study was to compare the positional and volumetric differences of internal target volumes defined on three-dimensional computed tomography (3DCT), four-dimensional CT (4DCT), and cone-beam CT (CBCT) images of non-small-cell lung cancer (NSCLC).Materials and methodsThirty-one patients with NSCLC sequentially underwent 3DCT and 4DCT simulation scans of the thorax during free breathing. The first CBCT was performed and registered to the planning CT using the bony anatomy registration during radiotherapy. The gross tumor volumes were contoured on the basis of 3DCT, maximum intensity projection (MIP) of 4DCT, and CBCT. CTV3D (clinical target volume), internal target volumes, ITVMIP and ITVCBCT, were defined with a 7 mm margin accounting for microscopic disease. ITV10 mm and ITV5 mm were defined on the basis of CTV3D: ITV10 mm with a 5 mm margin in left–right (LR), anterior–posterior (AP) directions and 10 mm in cranial–caudal (CC) direction; ITV5 mm with an isotropic internal margin (IM) of 5 mm. The differences in the position, size, Dice’s similarity coefficient (DSC) and inclusion relation of different volumes were evaluated.ResultsThe median size ratios of ITV10 mm, ITV5 mm, and ITVMIP to ITVCBCT were 2.33, 1.88, and 1.03, respectively, for tumors in the upper lobe and 2.13, 1.76, and 1.1, respectively, for tumors in the middle-lower lobe. The median DSCs of ITV10 mm, ITV5 mm, ITVMIP, and ITVCBCT were 0.6, 0.66, and 0.83 for all patients. The median percentages of ITVCBCT not included in ITV10 mm, ITV5 mm, and ITVMIP were 0.1%, 1.63%, and 15.21%, respectively, while the median percentages of ITV10 mm, ITV5 mm, and ITVMIP not included in ITVCBCT were 57.08%, 48.89%, and 20.04%, respectively.ConclusionThe use of the individual ITV derived from 4DCT merely based on bony registration in radiotherapy may result in a target miss. The ITVs derived from 3DCT with isotropic margins have a good coverage of the ITV from CBCT, but the use of those would result in a high proportion of normal tissue being irradiated unnecessarily.

Comparison of planning target volumes based on three-dimensional and four-dimensional CT imaging of thoracic esophageal cancer.

Background and purposeTo investigate the definition of planning target volumes (PTVs) based on four-dimensional computed tomography (4DCT) compared with conventional PTV definition and PTV definition using asymmetrical margins for thoracic primary esophageal cancer.Materials and methodsForty-three patients with esophageal cancer underwent 3DCT and 4DCT simulation scans during free breathing. The motions of primary tumors located in the proximal (group A), middle (group B), and distal (group C) thoracic esophagus were obtained from the 4DCT scans. PTV3D was defined on 3DCT using the tumor motion measured based on 4DCT, PTV conventional (PTVconv) was defined on 3DCT by adding a 1.0 cm margin to the clinical target volume, and PTV4D was defined as the union of the target volumes contoured on the ten phases of the 4DCT images. The centroid positions, volumetric differences, and dice similarity coefficients were evaluated for all PTVs.ResultsThe median centroid shifts between PTV3D and PTV4D and between PTVconv and PTV4D in all three dimensions were <0.3 cm for the three groups. The median size ratios of PTV4D to PTV3D were 0.80, 0.88, and 0.71, and PTV4D to PTVconv were 0.67, 0.73, and 0.76 (χ2=−3.18, −2.98, and −3.06; P=0.001, 0.003, and 0.002) for groups A, B, and C, respectively. The dice similarity coefficients were 0.87, 0.90, and 0.81 between PTV4D and PTV3D and 0.80, 0.84, and 0.83 between PTV4D and PTVconv (χ2 =−3.18, −2.98, and −3.06; P=0.001, 0.003, and 0.002) for groups A, B, and C, respectively. The difference between the degree of inclusion of PTV4D in PTV3D and that of PTV4D in PTVconv was <2% for all groups. Compared with PTVconv, the amount of irradiated normal tissue for PTV3D was decreased by 11.81% and 11.86% in groups A and B, respectively, but was increased by 2.93% in group C.ConclusionFor proximal and middle esophageal cancer, 3DCT-based PTV using asymmetrical margins provides good coverage of PTV4D; however, for distal esophageal cancer, 3DCT-based PTV using conventional margins provides ideal conformity with PTV4D.

Comparison of the Planning Target Volume Based on Three-Dimensional CT and Four-Dimensional CT Images of Thoracic Esophageal Cancer

Comparison of the Planning Target Volume Based on Three-Dimensional CT and Four-Dimensional CT Images of Thoracic Esophageal Cancer

Detection of the correlations in target volumes for primary tumor of non­small cell lung cancer based on FDG PET/CT and the end­expiration phase of 4D­CT

Objective To investigate the correlations in target volumes based on positron emission tomography CT (PET/CT) and the end-expiration phase of four-dimensional CT (4D-CT) images for non-small cell lung cancer (NSCLC). Methods Seventeen patients with NSCLC sequentially underwent three-dimensional CT (3DCT), 4D-CT and 18F-FDG PET/CT thoracic simulation scans. The gross target volume (GTV) was contoured on the end-expiration phase (50%) of 4D-CT and defined as GTV50%. The internal gross target volumes (IGTV) based on PET/CT images (IGTVPET) were determined by the standardized uptake value (SUV) 2.0 (IGTVPET2.0) and 20% percentage of the maximal standardized uptake value (SUVmax) (IGTVPET20%). The following parameters were calculated to analyze the correlation between IGTVPET and GTV50% in volume ratio (VR) and conformity index (CI): maximum transverse diameter of GTV50%, volume of GTV50%, the displacement of GTV in the cranial-caudal direction and 3D Vector calculated from 4D-CT dataset as well as the SUVmax. Results There was no significant correlation between the VR of IGTVPET2.0 to GTV50% and the maximum transverse diameter of GTV50%, volume of GTV50%, the displacement of GTV in the cranial-caudal direction, 3D Vector and the SUVmax (P>0.05). The VR between IGTVPET20% and GTV50% inversely related to maximum transverse diameter of GTV50%, volume of GTV50% and SUVmax (r=-0.663, -0.669, -0.752, P<0.05). The CI between IGTVPET2.0 and GTV50% positively related to volume of GTV50% and maximum transverse diameter of GTV50% (r=0.613, 0.483, P<0.05). Conclusions 3D PET images provide a time-averaged image of the tumor during the numerous breathing cycle. They fail to include the full information of moving tumor. The target volumes based on 3D PET might not reflect the real IGTV of NSCLC. Key words: Non-small cell lung cancer; Fluorodeoxyglucose positron emission tomography; Four-dimensional computed tomography; Standardized uptake value; Internal gross target volume

Dynamic Four-dimensional Computed Tomography (4D CT) Imaging for Re-entry Risk Assessment in Re-do Sternotomy - First experience

Repeat cardiac surgeries are well known to have higher rates of complications, one of the important reasons being injuries associated with re-do sternotomy. Routine imaging with CT can help to minimise this risk by pre-operatively assessing the anatomical relation between the sternum and the underlying cardiovascular structures, but is limited by its inability to determine the presence and severity of functional tethering and adhesions between these structures. However, with the evolution of wide area detector MD CT scanners, it is possible to assess the presence of tethering using the dynamic four-dimensional CT (4D CT) imaging technique. Nineteen patients undergoing re-do cardiac surgery were pre-operatively imaged using dynamic 4D CT during regulated respiration. The datasets were assessed in cine mode for presence of differential motion between sternum and underlying cardiovascular structures which indicates lack of significant tethering. Overall, there was excellent correlation between preoperative imaging and intraoperative findings. The technique enabled our surgeons to meticulously plan the procedures and to avoid re-entry related injuries. Our initial experience shows that dynamic 4D CT is useful in risk stratification prior to re-do sternotomy by determining the presence or absence of tethering between sternum and underlying structures based on assessment of differential motion. Furthermore we determined the technique to be superior to non-dynamic assessment of retrocardiac tethering.

Generation of fluoroscopic 3D images with a respiratory motion model based on an external surrogate signal

Respiratory motion during radiotherapy can cause uncertainties in definition of the target volume and in estimation of the dose delivered to the target and healthy tissue. In this paper, we generate volumetric images of the internal patient anatomy during treatment using only the motion of a surrogate signal. Pre-treatment four-dimensional CT imaging is used to create a patient-specific model correlating internal respiratory motion with the trajectory of an external surrogate placed on the chest. The performance of this model is assessed with digital and physical phantoms reproducing measured irregular patient breathing patterns. Ten patient breathing patterns are incorporated in a digital phantom. For each patient breathing pattern, the model is used to generate images over the course of thirty seconds. The tumor position predicted by the model is compared to ground truth information from the digital phantom. Over the ten patient breathing patterns, the average absolute error in the tumor centroid position predicted by the motion model is 1.4 mm. The corresponding error for one patient breathing pattern implemented in an anthropomorphic physical phantom was 0.6 mm. The global voxel intensity error was used to compare the full image to the ground truth and demonstrates good agreement between predicted and true images. The model also generates accurate predictions for breathing patterns with irregular phases or amplitudes.

Simulation of spatiotemporal CT data sets using a 4D MRI-based lung motion model

Four-dimensional CT imaging is widely used to account for motion-related effects during radiotherapy planning of lung cancer patients. However, 4D CT often contains motion artifacts, cannot be used to measure motion variability, and leads to higher dose exposure. In this article, we propose using 4D MRI to acquire motion information for the radiotherapy planning process. From the 4D MRI images, we derive a time-continuous model of the average patient-specific respiratory motion, which is then applied to simulate 4D CT data based on a static 3D CT. The idea of the motion model is to represent the average lung motion over a respiratory cycle by cyclic B-spline curves. The model generation consists of motion field estimation in the 4D MRI data by nonlinear registration, assigning respiratory phases to the motion fields, and applying a B-spline approximation on a voxel-by-voxel basis to describe the average voxel motion over a breathing cycle. To simulate a patient-specific 4D CT based on a static CT of the patient, a multi-modal registration strategy is introduced to transfer the motion model from MRI to the static CT coordinates. Differences between model-based estimated and measured motion vectors are on average 1.39mm for amplitude-based binning of the 4D MRI data of three patients. In addition, the MRI-to-CT registration strategy is shown to be suitable for the model transformation. The application of our 4D MRI-based motion model for simulating 4D CT images provides advantages over standard 4D CT (less motion artifacts, radiation-free). This makes it interesting for radiotherapy planning.

Comparison of Gross Target Volumes Based on 3-Dimensional CT, 4-Dimensional CT, and Cone Beam CT Images of Non-Small Cell Lung Cancer

To compare positional and volumetric differences of gross target volumes (GTVs) delineated based on three-dimensional CT (3DCT), four-dimensional CT (4DCT) and cone-beam CT (CBCT) images of non-small-cell lung cancer.

The effect of irregular breathing patterns on internal target volumes in four-dimensional CT and cone-beam CT images in the context of stereotactic lung radiotherapy

Stereotactic lung radiotherapy is complicated by tumor motion from patient respiration. Four-dimensional CT (4DCT) imaging is a motion compensation method used in treatment planning to generate a maximum intensity projection (MIP) internal target volume (ITV). Image guided radiotherapy during treatment may involve acquiring a volumetric cone-beam CT (CBCT) image and visually aligning the tumor to the planning 4DCT MIP ITV contour. Moving targets imaged with CBCT can appear blurred and currently there are no studies reporting on the effect that irregular breathing patterns have on CBCT volumes and their alignment to 4DCT MIP ITV contours. The objective of this work was therefore to image a phantom moving with irregular breathing patterns to determine whether any configurations resulted in errors in volume contouring or alignment. A Perspex thorax phantom was used to simulate a patient. Three wooden "lung" inserts with embedded Perspex "lesions" were moved up to 4 cm with computer-generated motion patterns, and up to 1 cm with patient-specific breathing patterns. The phantom was imaged on 4DCT and CBCT with the same acquisition settings used for stereotactic lung patients in the clinic and the volumes on all phantom images were contoured. This project assessed the volumes for qualitative and quantitative changes including volume, length of the volume, and errors in alignment between CBCT volumes and 4DCT MIP ITV contours. When motion was introduced 4DCT and CBCT volumes were reduced by up to 20% and 30% and shortened by up to 7 and 11 mm, respectively, indicating that volume was being under-represented at the extremes of motion. Banding artifacts were present in 4DCT MIP images, while CBCT volumes were largely reduced in contrast. When variable amplitudes from patient traces were used and CBCT ITVs were compared to 4DCT MIP ITVs there was a distinct trend in reduced ITV with increasing amplitude that was not seen when compared to true ITVs. Breathing patterns with a rest period following expiration resulted in well-defined superior edges and were better aligned using an edge-to-edge alignment technique. In most cases, sinusoidal motion patterns resulted in the closest agreements to true values and the smallest misalignments. Strategies are needed to compensate for volume losses at the extremes of motion for both 4DCT MIP and CBCT images for larger and varied amplitudes, and for patterns with rest periods following expiration. Lesions moving greater than 2 cm would warrant larger treatment margins added to the 4DCT MIP ITV to account for the volume being under-represented at the extremes of motion. Lesions moving with a rest period following expiration would be better aligned using an edge-to-edge alignment technique. Sinusoidal patterns represented the ideal clinical scenario, reinforcing the importance of investigating clinically relevant motions and their effects on 4DCT MIP and CBCT volumes. Since most patients do not breathe sinusoidally this may lead to misinterpretation of previous studies using only sinusoidal motion.

Analysis of Acquisition Parameters That Caused Artifacts in Four-dimensional (4D) CT Images of Targets Undergoing Regular Motion

Analysis of Acquisition Parameters That Caused Artifacts in Four-dimensional (4D) CT Images of Targets Undergoing Regular Motion

The use of respiratory‐correlated four‐dimensional CT where kidney motion has the potential to impact upon the radiotherapy planning process

Four-dimensional CT (4D-CT) image data can be sorted into bins of each 10% of the respiratory cycle. From these data, an averaged scan (AS) and a maximum intensity projection (MIP) are derived. While sorting based on the respiratory cycle applies to lung tumours, the use of 4D-CT for the kidney has not been analysed. Both kidneys from five patients were contoured from every phase of the 4D-CT, MIP and AS (in total 116 kidneys were contoured). For each patient, the kidney volumes on the AS and calculated mathematical average (CMA) from individual phases were compared. The kidney volumes on the MIP and Boolean expansion of all phases were compared. The maximum excursions of the superior and inferior poles of the kidneys were measured in the craniocaudal and anterior-posterior (AP) directions. Mid-kidney excursion was measured in the AP and medial-lateral directions. Mean difference between CMA and AS was -0.91 cm(3) (range -8.04 to 5.07 cm(3) ). Mean difference between Boolean and MIP was 18.92 cm(3) (range -2.24 to 44.34 cm(3) ). Mean maximum displacement of mid-kidney was 0.28 cm anteriorly (range 0 to 1.0 cm), 0.22 cm posteriorly (range 0.1 to 0.4 cm), 0.28 cm medially (range 0.1 to 0.5 cm) and 0.27 cm laterally (range 0.1 to 0.5 cm). Mean maximum excursion of superior pole was 0.31 cm anteriorly (range 0.2 to 0.5 cm), 0.29 cm posteriorly (range 0.2 to 0.5 cm) and 1.23 cm craniocaudally (range of 0.6 to 2.7 cm). Mean maximum excursion of inferior pole was 0.52 cm anteriorly (range 0.2 to 0.9 cm), 0.23 cm posteriorly (range 0.1 to 0.4 cm) and 0.67 cm craniocaudally (range of 0.3 to 1.8 cm). The current study using 4D-CT has shown that the derived MIP is a good surrogate for the evaluation of three-dimensional kidney displacement, and that the volume of the AS is not largely different from the average volume for individual phases. The 4D-CT is useful for the creation of individual patient internal target volume or planning organ at risk volume when kidney motion impacts on radiotherapy planning.