Motion vector field phase-to-amplitude resampling for 4D motion-compensated cone-beam CT

Until today, several software-based approaches to increase the temporal resolution in cardiac computed tomography by estimating motion vector fields (MVFs) have been developed. Thereunder, the majority are motion compensation algorithms, which estimate the MVFs employing a three-dimensional registration routine working on reconstructions of multiple cardiac phases.^{2, 6, 7, 12}We present an algorithm that requires nothing more than the data needed for a short scan reconstruction for motion estimation and motion-compensated reconstruction, which both are based on the reconstruction of volumes from a limited angular range.^{2, 3, 7, 8} Those partial angle reconstructions are centered at different time points during the short scan and have a temporal resolution of about 10ms each. The MVFs are estimated by a constrained cost function optimization routine employing a motion artifact measuring cost function. During optimization, the MVFs are applied directly by warping the partial angle reconstructions, and the motion compensation is established by simply adding the shifted images. In order to enforce smooth vector fields and keep the number of parameters low, the motion is modeled by a low degree polynomial. Furthermore, to find a good estimation of the MVFs even in phases with rapid cardiac motion, the constrained optimization is re-initialized multiple times. The algorithm is validated with the help of a simulation study and applied to patient data, where motion- compensated reconstructions are performed in various cardiac phases. We show that the image quality can be improved, also in more rapid cardiac phases due to re-initialization of the optimization routine.

Purpose: Compare the localization accuracy of 3D cone beam computed tomography (CBCT) and 4D CBCT for a dynamic respiratory phantom, considering cases with and without respiratory variations between planning and treatment. Methods and Materials: A respiratory phantom was imaged using 3D CBCT and 4D CBCT. Measurements of the amplitude of motion in 3D CBCT and 4D CBCT and size of the sphere at its exhale position in 4D CBCT were acquired. The phantom was then misaligned by known distances relative to a reference position. 3D CBCT and 4D CBCT were used to re-align the phantom by comparing localization images to reference images. Because the ideal 4D CBCT registration approach was to be determined, multiple localization-reference pairs of images were examined. Comparison was performed for multiple respiratory waveforms at two amplitudes as well as for waveforms where amplitudes were increased or decreased by 30%, simulating changes in respiratory behavior between simulation and localization. Error of localization trials was defined as the difference between the recommended table shifts and the known displacement. Results: Measurements of the respiratory amplitude were underestimated for all cases. Measurement of the sphere diameter exhibited < 2 mm error. Localization errors were less than 2.6 mm for all cases. When the motion amplitude was the same during localization as planning, automatic registration of the exhale frame from the 4D CBCT to the reference exhale frame had the smallest error in localization of 0.54 ± 0.03 mm. However, automatic registration of the 4D CBCT AIP to the reference AIP had the smallest errors when the motion amplitude changed between planning and localization, 1.59 ± 0.12 mm for the +30% amplitude change and 0.69 ± 0.02 mm for the -30% amplitude change. Conclusion: Because lung tumor motion amplitude throughout treatment may vary between planning and treatment, the use of 4D CBCT AIP registered to reference AIP was recommended for localization. 4D CBCT provided additional benefits compared to 3D CBCT of substantial reduction in target blurring and verification of respiratory motion characteristics prior to treatment.

Respiratory motion is a long-standing challenge for lung stereotactic body radiotherapy (SBRT), particularly for centrally located lung tumors where increased toxicity demands more precise motion management during treatment. Current two-dimensional imaging approaches are insufficient for 3D tumor deformable motion tracking. In this study, we developed and evaluated a Surface-derived Three-dimensional (3D) AI-driven Real-time (STAR) imaging system by transforming a surface imaging system into a 3D real-time imaging solution. STAR integrated two key components: (1) prior-model-free spatiotemporal implicit neural representation (PMF-STINR): a machine-learning sub-system for pretreatment dynamic cone-beam CT (CBCT) reconstruction and motion modeling; and (2) surface-to-deformation network (Surf2DefNet): a deep-learning model that correlates intra-treatment body surface images with internal 3D anatomy and motion fields, trained based on the dynamic CBCT and motion model output of PMF-STINR. Specifically, PMF-STINR reconstructs a reference CBCT and solves an eigenvector-based motion model from a pretreatment CBCT, while Surf2DefNet predicts the motion eigen-vector weightings from surface images, enabling it to infer real-time CBCTs and motion vector fields (MVFs) using intra-treatment surface maps acquired later. We evaluated STAR imaging using both a digital extended cardiac torso (XCAT) phantom with regular and irregular motion patterns and ten patient datasets. The relative error (RE), center-of-mass error (COME), 95th percentile Hausdorff distance (HD95), Dice coefficients (DICE), and Pearson correlation coefficient (PCC) metrics between STAR images and the 'GT' were evaluated. For the XCAT phantom and the ten patients, the mean COME values are within 1 mm for all but one patient (1.3 mm). The RE values were consistently low, and the DICE and PCC values exceeded 0.89 in all cases. The HD95 are all within 2 mm except for one patient (2. 78 mm). These results demonstrate that the STAR imaging system can achieve accurate spatiotemporal reconstructions from surface images, providing CBCTs and MVFs for intra-treatment real-time image-guidance, and has the potential to improve safety and efficacy of SBRT for lung cancer.

Background: Several factors must be considered when selecting the appropriate field of view (FOV) and voxel size for good image quality on Cone Beam Computed-Tomography (CBCT). The purpose of this study is to determine the factors that must be considered in selecting the appropriate FOV and voxel size to achieve good image quality according to the purpose of the examination. Method: Articles in Q1 and Q2 journals published within the period from January 2016 to September 2021 were searched from Scopus and PubMed online using the keywords field of view/FOV in CBCT, voxel size in CBCT, and FOV and voxel size in CBCT. On the basis of the article selection criteria, 13 journals were included in the study. Also included in the study were several types of three-dimensional (3D) CBCT machines: Planmeca ProMax® 3D ProFaceTM, i-Cat Cone Beam 3D, Picasso Trio CBCT: Carestream unit® CS 9300 CBCT, and Accuitomo F17D 3D CBCT. Result: It is generally recommended that a 0.2 mm voxel size be used to detect periodontal disease, secondary caries, fractures, external resorption, and endodontic complications. Meanwhile, for root fractures with an intracanal metallic post and an anatomic isthmus in the root canal, a 0.1 mm voxel size is recommended to be used, and for evaluating the implant, 0.3 mm and 0.4 mm voxel sizes are recommended. Conclusion: It was found in the review that most of the selected studies recommended using the smallest FOV available in the CBCT unit to detect pathological conditions and important anatomical structures.

Purpose: Complex, involuntary, non-periodic, deformable motion presents a confounding factor to cone-beam CT (CBCT) image quality due to long (>10 s) scan times. We report and demonstrate an image-based deformable motion compensation method for CBCT, including phantom, cadaver, and animal studies as precursors to clinical studies. Methods: The method corrects deformable motion in CBCT scan data by solving for a motion vector field (MVF) that optimizes a sharpness criterion in the 3D image (viz., gradient entropy). MVFs are estimated by interpolating M locally rigid motion trajectories across N temporal nodes and are incorporated in a modified 3D filtered backprojection approach. The method was evaluated in a cervical spine phantom under flexion, and a cadaver undergoing variable magnitude of complex motion while imaged on a mobile C-arm (Cios Spin 3D, Siemens Healthineers, Forchheim, Germany). Further assessment was performed on a preclinical animal study using a clinical fixed-room C-arm (Artis Zee, Siemens Healthineers, Forchheim, Germany). Results: In phantom studies, the algorithm resolved visibility of cervical vertebrae under situations of strong flexion, reducing the root-mean-square error by 60% when compared to a motion-free reference. Reduced motion artifacts (blurring, streaks, and loss of soft-tissue edges) were evident in abdominal CBCT of a cadaver imaged during small, medium, and large motion-induced deformation. The animal study demonstrated reduction of streaks from complex motion of bowel gas during the scan. Conclusion: Overall, the studies demonstrate the robustness of the algorithm to a broad range of motion amplitudes, frequencies, data sources (i.e., mobile or fixed-room C-arms) and other confounding factors in real (not simulated) experimental data (e.g., truncation and scatter). These preclinical studies successfully demonstrate reduction of motion artifacts in CBCT and support translation of the method to clinical studies in interventional body radiology.

In this paper, we propose a deep neural network (DNN)-based volumetric image reconstruction framework, enabling an end-to-end volume inference from a 2D X-ray image. The proposed framework is built upon the vector quantised-variational autoencoders of the 2D X-ray images and the 3D cone-beam CT (CBCT) images. We present a bi-directional cross-modal transition module between the discrete latent variables of the 2D and 3D images. In the X-ray-to-CBCT pass, the transition module takes the feature maps of the X-ray images as an input and outputs the discrete volumetric embedding, which is combined with the codebook in the embedding space for the reconstruction of CBCT images. On the other hand, the CBCT-to-X-ray pass realizes the DNN-based volume rendering. Given real clinically-obtained X-ray images without paired volumetric images, we devise an unsupervised learning scheme to optimize the discrete embedding transition module. Our approach utilizes the quantised latent representation and the cross-modality transition module to infer volumetric images. The proposed method has been applied to the lateral X-ray-based CBCT image reconstruction in clinical orthodontics, achieving performance improvements over compared methods.

On-board cone-beam computed tomography (CBCT) has recently become available to provide volumetric information of a patient in the treatment position, and holds promises for improved target localization and irradiation dose verification. The design of currently available on-board CBCT, however, is far from optimal. Its quality is adversely influenced by many factors, such as scatter, beam hardening, and intra-scanning organ motion. In this work we quantitatively study the influence of organ motion on CBCT imaging and investigate a strategy to acquire high quality phase-resolved [four-dimensional (4D)] CBCT images based on phase binning of the CBCT projection data. An efficient and robust method for binning CBCT data according to the patient's respiratory phase derived in the projection space was developed. The phase-binned projections were reconstructed using the conventional Feldkamp algorithm to yield 4D CBCT images. Both phantom and patient studies were carried out to validate the technique and to optimize the 4D CBCT data acquisition protocol. Several factors that are important to the clinical implementation of the technique, such as the image quality, scanning time, number of projections, and radiation dose, were analyzed for various scanning schemes. The general references drawn from this study are: (i) reliable phase binning of CBCT projections is accomplishable with the aid of external or internal marker and simple analysis of its trace in the projection space, and (ii) artifact-free 4D CBCT images can be obtained without increasing the patient radiation dose as compared to the current 3D CBCT scan.

To evaluate whether intra-procedural cone-beam computed tomography (CBCT) performed during modified balloon-occluded retrograde transvenous obliteration (mBRTO) can accurately determine technical success of complete variceal obliteration. From June 2012 to December 2014, 15 patients who received CBCT during mBRTO for treatment of portal hypertensive gastric variceal bleeding were retrospectively evaluated. Three-dimensional (3D) CBCT images were performed and evaluated prior to the end of the procedure, and these were further analyzed and compared to the pre-procedure contrast-enhanced computed tomography to determine the technical success of mBRTO including: Complete occlusion/obliteration of: (1) gastrorenal shunt (GRS); (2) gastric varices; and (3) afferent feeding veins. Post-mBRTO contrast-enhanced CT was used to confirm the accuracy and diagnostic value of CBCT within 2-3 d. Intra-procedural 3D-CBCT images were 100% accurate in determining the technical success of mBRTO in all 15 cases. CBCT demonstrated complete occlusion/obliteration of GRS, gastric varices, collaterals and afferent feeding veins during mBRTO, which was confirmed with post-mBRTO CT. Two patients showed incomplete obliteration of gastric varices and feeding veins on CBCT, which therefore required additional gelfoam injections to complete the procedure. No patient required additional procedures or other interventions during their follow-up period (684 ± 279 d). CBCT during mBRTO appears to accurately and immediately determine the technical success of mBRTO. This may improve the technical and clinical success/outcome of mBRTO and reduce additional procedure time in the future.

Objective: This study aimed to investigate the prevalence of pre-eruptive intracoronal resorption (PIR) using cone beam computed tomography (CBCT) and panoramic radiography and to compare the findings of these imaging techniques.Methods: This retrospective study consisted of 733 patients who had at least one unerupted tooth and had undergoneimaging with both three-dimensional (3D) CBCT and two-dimensional (2D) panoramic radiography. In all the images, the number of teeth with intracoronal resorption, affected tooth type and number, and size and location of the PIR defects were recorded. The McNemar test was used to compare the prevalence of PIR in the CBCT and panoramic images.Results: Fewer PIR defects were detected in the panoramic images (3.1% of the patients) than in the CBCT images (9.5% of the patients) (p< .001). According to the CBCT images, the distribution of PIR defects was as follows: third molars (59.5%), canine teeth (11.4%), second molars and premolars (7.6% for both), supernumerary teeth (5.1%), second molars (3.8%), central incisors (2.5%), and first premolar and primary second molar teeth (1.5% for both). According to the scoring classification system for PIR defects, PIR 1 defects were the most common (65.8%), followed by PIR 3 (24.1%) and PIR 2 (10.1%). Of these defects, 69.6% were located in the central aspect of the crown. Ectopically positioned teeth showing intracoronal resorption accounted for 51.9% of the cases of PIR.Conclusions: CBCT detected more cases of PIR than panoramic radiography. The mandibular third permanent molar was the most commonly affected tooth.

On-Board Patient Positioning for Head-and-Neck IMRT: Comparing Digital Tomosynthesis to Kilovoltage Radiography and Cone-Beam Computed Tomography

BackgroundThis is a prospective study to evaluate the dosimetric benefits of treatment plan adaptation for patients who had undergone repeat computed tomography (ReCT)and re-planning due to treatment-induced anatomical changes during radiotherapy.Materials and MethodsThis study involved five head and neck cancer patients who had their treatment plan modified, based on weekly thrice imaging protocol. Impact of mid-course imaging was assessed in patients using ReCT and cone beam computed tomography (CBCT)-based dose verification. Patients were imaged, apart from their initial CT, during the course of their radiation therapy with a ReCT and on board imager CBCT (Varian Medical Systems Inc., Palo Alto, CA, USA). Each CBCT/CT series was rigidly registered to the initial CT in the treatment planning system Eclipse (Varian Medical Systems Inc.) using bony landmarks. The structures were copied to the current CBCT/CT series and, where needed, manually edited slicewise. The dose distribution from the treatment plan was viewed as of the current anatomy by applying the treatment plan the CBCT/CT series, and studying the corresponding dose–volume histograms for organs at risk doses.ResultsThe reduction of parotid volumes due to weight loss was observed in all patients, which means an increase in predicted mean doses of parotid when initial CT plan was re-calculated on ReCT and CBCT (Table 1). This explains the necessity of adaptive planning. The predicted mean dose of parotid glands was increased and constraints to spinal cord and skin were exceeded, so re-planning was performed.ConclusionsThe CBCT is a useful tool to view anatomic changes in patients and get an estimate of their impact on dose distribution. Re-planning based on imaging in head and neck patients during the course of radiotherapy is mandatory to reduce side effects.

IntroductionDuring neurosurgical image-guided procedures, a head clamp, with attached titanium pins, is used to immobilize the head. Titanium is chosen for several reasons including cost effectiveness, biocompatibility and fracture resistance....

Purpose: To evaluate the dosimetric improvement of IMRT treatment plans generated with patient-specific margins compared to uniform margins for prostate cancer patients. Methods and Materials: For 13 prostate cancer patients who underwent IMRT treatment, daily cone-beam computed tomography (CBCT) scans were acquired during the first week, followed by weekly scans (total of 85 scans) for the remainder of the treatment. Both prostate and seminal vesicles were retrospectively segmented on all CBCTs. The patient-specific planning target volume (PTVPS) was defined based on a composite volume of both prostate and seminal vesicles from the first four daily CBCTs and the planning CT. A 3-mm margin was added around the composite volume to obtain PTVPS. As a comparison, we also generated a PTV in the planning CT with a uniform margin (PTVUni) of 10-mm in all directions, except 5-mm posteriorly, around the prostate and seminal vesicles. An IMRT plan for each PTV was generated for each patient. Evaluation plans based on each of weekly CBCT were generated to gauge the DVHs resulting from these IMRT plans to the patient volumes segmented on weekly CBCTs. Results: Evaluation plans generated with PTVPS in place of PTVUni resulted in average improvements of 1.4% and 2.8% for V95 of prostate and seminal vesicles, respectively, and average reduction of 7.0% and 4.7% for V50 of bladder and rectum, respectively. Out of 85 weekly CBCT evaluation plans for each PTV, 7.1% of cases showed improvement for V95 of prostate with PTVUni, 40.0% for V95 of seminal vesicles, 28.2% for V50 of bladder and 29.4% for V50 of rectum. Conclusions: Patient-specific margins, designed using multiple scans, appear to provide little dosimetric benefit with respect to target coverage over a standard uniform margin formulation; sparing critical structures is improved to a greater degree. “Partially supported by Varian Medical Systems”.

This paper presents a three-dimensional method to reconstruct moving objects from cone-beam X-ray projections using an iterative reconstruction algorithm and a given motion vector field. For the image representation, adapted blobs are used, which can be implemented efficiently as basis functions. Iterative reconstruction requires the calculation of line integrals (forward projections) through the image volume, which are compared with the actual measurements to update the image volume. In the existence of a divergent motion vector field, a change in the volumes of the blobs has to be taken into account in the forward and backprojections. An efficient method to calculate the line integral through the adapted blobs is proposed. It solves the problem, how to compensate for the divergence in the motion vector field on a grid of basis functions. The method is evaluated on two phantoms, which are subject to three different known motions. Moreover, a motion-compensated filtered back-projection reconstruction method is used, and the reconstructed images are compared. Using the correct motion vector field with the iterative motion-compensated reconstruction, sharp images are obtained, with a quality that is significantly better than gated reconstructions.

BackgroundThe aim of this study was to evaluate the validity and the inter- and intra-examiner reliability of panoramic-radiograph-driven findings of different maxillary sinus anatomic variations and pathologies, which had initially been prediagnosed by cone beam computed tomography (CBCT).MethodsAfter pairs of two-dimensional (2D) panoramic and three-dimensional (3D) CBCT images of patients having received treatment at the outpatient department had been screened, the predefinition of 54 selected maxillary sinus conditions was initially performed on CBCT images by two blinded consultants individually using a questionnaire that defined ten different clinically relevant findings. Using the identic questionnaire, these consultants performed the evaluation of the panoramic radiographs at a later time point. The results were analyzed for inter-imaging differences in the evaluation of the maxillary sinus between 2D and 3D imaging methods. Additionally, two resident groups (first year and last year of training) performed two diagnostic runs of the panoramic radiographs and results were analyzed for inter- and intra-observer reliability.ResultsThere is a moderate risk for false diagnosis of findings of the maxillary sinus if only panoramic radiography is used. Based on the ten predefined conditions, solely maxillary bone cysts penetrating into the sinus were frequently detected differently comparing 2D to 3D diagnostics. Additionally, on panoramic radiographs, the inter-observer comparison demonstrated that basal septa were significantly often rated differently and the intra-observer comparison showed a significant lack in reliability in detecting maxillary bone cysts penetrating into the sinus.ConclusionsPanoramic radiography provides the most information on the maxillary sinus, and it may be an adequate imaging method. However, particular findings of the maxillary sinus in panoramic imaging may be based on a rather examiner-dependent assessment. Therefore, a persistent and precise evaluation of specific conditions of the maxillary sinus may only be possible using CBCT because it provides additional information compared to panoramic radiography. This might be relevant for consecutive surgical procedures; consequently, we recommend CBCT if a precise preoperative evaluation is mandatory. However, higher radiation dose and costs of 3D imaging need to be considered.