Respiration-induced Organ Motion Research Articles

Respiration-Induced Organ Motion Compensation: A Review.

Motion of organs in the abdominal and thoracic cavity caused by respiration is a major issue that affects a wide range of clinical diagnoses or treatment outcomes, including radiotherapy, high-intensity focused ultrasound ablation, and many generalized percutaneous needle interventions. These motions pose significant challenges in accurately reaching the target even for the experienced clinician. This review was conducted through comprehensive search on IEEE Explore, Google Scholar, and PubMed. Diverse methods have been proposed to compensate for this motion effect to enable effective surgical operations. This review paper aims to examine the current respiratory motion compensation techniques used across the clinical procedures of radiotherapy, high-intensity focused ultrasound, and percutaneous needle procedures. The complexity of respiratory-induced organ motion and diversity of areas for which compensation can be applied allows for a variety of methodsto be implemented. This review aims to serve as inspiration for the future development of new systems to achieve clinical relevance.

Feasibility assessment of inspiration breath-hold motion management for tumor tracking during cone-beam computed tomography for setup and radiotherapy in Veterinary Medicine: A pilot study.

Radiotherapy (RT) for lung or liver tumors can be challenging due to respiration-induced organ motion (RIOM). There are some methodological solutions to minimize RIOM. We explored a new approach to evaluate the feasibility and reproducibility of RIOM during RT with five total client-owned tumor-bearing animals using a remote-triggered breath-hold ventilator under general anesthesia during image acquisition and RT. There was one stereotactic body radiotherapy, one conventionally fractionated definitive intent, and three conventionally fractionated palliative intent RT cases. Based on repeated cone beam CT, there were no treatment table shifts required prior to initiating beam on. No clinically significant complications such as hypotension occurred during anesthesia. This technique appeared to be safe in this group of patients and was easily clinically implemented and highly reproducible. More complete follow-up data and larger studies are needed to evaluate clinical outcomes with this breath-hold ventilator technique in veterinary RT.

Correlation between respiratory-induced target motion and dosimetric variance on EBRT

During radiation therapy, it is crucial to realise adequate dose coverage of the target at depth. However, physicists must overcome many challenges before they can achieve better accuracy. Respiratory-induced organ motion (RIOM) remains a challenge that negatively contributes to external beam radiotherapy (EBRT) accuracy. Although the magnitude of respiratory motion amplitude is a major factor in maximising or minimising the dosimetric effect of respiratory motion, other factors may negatively or positively contribute to this effect. This study investigated the impact of respiratory motion and tumour parameters, amplitude, and volume, on gross tumour volume (GTV) coverage during EBRT. In addition, it analysed the impact of tumour volume on the dosimetric effect of RIOM. A GEANT4 code was used for simulating the in vivo interaction of matter with ionising radiation was used to provide a model of respiratory-induced organ motion and voxel-level dosimetry of a simulated target. Thirty different setups were simulated using the GEANT4 simulation toolkit. Each setup demonstrated how a specific combination of respiratory and tumour parameters, amplitude, and size impact GTV coverage. The results show that the dosimetric effect of respiratory motion depends more on respiratory parameters i.e. on the respiratory motion amplitude. The reduction in GTV coverage for a tumour of 5 mm diameter can vary from approximately 28%–67%. At a certain respiratory amplitude, the tumour size can strongly affect GTV coverage. This effect becomes more dominant when the respiratory amplitude exceeds the tumour diameter. This study shows that any approach to compensate for RIOM in EBRT should consider the role of tumour size.

Intrafraction Accuracy of Respiratory Gating Comparable to Deep Inspiration Breath Hold for Pancreatic Cancer Treatment

Deep inspiration breath hold (DIBH) and respiratory gating (RG) are two strategies widely used for reducing respiration-induced organ motion. We hypothesized that accuracy comparable to DIBH would be achieved with RG for pancreas treatment. Twelve consecutive patients with pancreas cancer treated with DIBH (eight) or RG (four) volumetric modulated arc therapy in 2017 and 2018 were included in this study, each with some radiopaque markers (fiducials or surgical clips) implanted near or inside the target. Nine patients were treated in 25 fractions, while the other two were treated in 20 and 15 fractions. Only the patients who could not tolerate DIBH were treated with RG. Both techniques relied on respiratory signals from external markers mounted on a plastic block on the patient’s abdomen. A 3-mm gating window was used for the DIBH treatment; and RG treatment was centered at end expiration with 40% duty cycle, corresponding to 2—3 mm window. During dose delivery, kV images were taken every 20˚ or 40˚ gantry rotation using the intrafraction motion review (IMR) application, resulting in over 7000 images for the cohort. The internal markers were manually identified in the IMR images. The displacement from their initial positions found in the setup images as well as the residual motion amplitudes of the markers were calculated. The displacements of the internal markers for each patient’s entire treatment course were analyzed to characterize the typical intrafraction accuracy of the two techniques. For all patients, the fiducial displacement relative to the initial position during setup was small. Within a single fraction, the average displacement varied from <1 mm to 5 mm for DIBH and 1—6 mm for RG. The magnitude of displacement averaged over the whole course for each patient ranged from <1 mm to 3 mm for both techniques. No significant difference in displacement was observed between the two techniques (p=0.4). The residual motion over the entire treatment course varied from 3 mm to 10 mm, in average 6 mm for DIBH and 8 mm for RG, the difference being statistically insignificant (p=0.1). The intrafraction accuracy of RG treatment was comparable to that of DIBH treatment for pancreas irradiation. RG serves as a viable backup strategy when DIBH could not tolerated.

Introduction of a pseudo demons force to enhance deformation range for robust reconstruction of super-resolution time-resolved 4DMRI.

The purpose of this study was to enhance the deformation range of demons-based deformable image registration (DIR) for large respiration-induced organ motion in the reconstruction of time-resolved four-dimensional magnetic resonance imaging (TR-4DMRI) for multi-breath motion simulation. A demons-based DIR algorithm was modified to enhance the deformation range for TR-4DMRI reconstruction using the super-resolution approach. A pseudo demons force was introduced to accelerate the coarse deformation in a multi-resolution (n=3) DIR approach. The intensity gradient of a voxel was applied to its neighboring (5×5×5) voxels with a weight of Gaussian probability profile (σ=1 voxel) to extend the demons force, especially on those voxels that have little intensity gradience but high-intensity difference. A digital 4DMRI phantom with 3-8cm diaphragmatic motions was used for DIR comparison. Six volunteers were scanned with two high-resolution (highR: 2×2×2mm3 ) breath-hold (BH) 3DMR images at full inhalation (BHI) and full exhalation (BHE) and low-resolution (lowR: 5×5×5mm3 ) free-breathing (FB) 3DMR cine images (2Hz) under an IRB-approved protocol. A cross-consistency check (CCC) (BHI→FB←BHE), with voxel intensity correlation (VIC) and inverse consistency error (ICE), was introduced for cross-verification of TR-4DMRI reconstruction. Using the digital phantom, the maximum deformable magnitude is doubled using the modified DIR from 3 to 6cm at the diaphragm. In six human subjects, the first 15-iteration DIR using the pseudo force deforms 200±150% more than the original force, and succeeds in all 12 cases, whereas the original demons-based DIR failed in 67% of tested cases. Using the pseudo force, high VIC (>0.9) and small ICE (1.6±0.6mm) values are observed for DIR of BHI&BHE, BHI→FB, and BHE→FB. The CCC identifies four questionable cases, in which two cases need further DIR refinement, without missing true negative. The introduction of a pseudo demons force enhances the largest deformation magnitude up to 6cm. The cross-consistency check ensures the quality of TR-4DMRI reconstruction. Further investigation is ongoing to fully characterize TR-4DMRI for potential multi-breathing-cycle radiotherapy simulation.

Novel 4D-MRI of tumor infiltrating vasculature: characterizing tumor and vessel volume motion for selective boost volume definition in pancreatic radiotherapy

BackgroundPancreatic ductal adenocarcinoma has dismal prognosis. Most patients receive radiation therapy (RT), which is complicated by respiration induced organ motion in upper abdomen. The purpose of this study is to report our early clinical experience in a novel self-gated k-space sorted four-dimensional magnetic resonance imaging (4D-MRI) with slab-selective (SS) excitation to highlight tumor infiltrating blood vessels for pancreatic RT.MethodsTen consecutive patients with borderline resectable or locally advanced pancreatic cancer were recruited to the study. Non-contrast 4D-MRI with and without slab-selective excitation and 4D-CT with delay contrast were performed on all patients. Vessel-tissue CNR were calculated for aorta and critical vessels (superior mesenteric artery or superior mesenteric vein) encompassed by tumor. Respiratory motion trajectories for tumor, as well as involved vessels were analyzed on SS-4D-MRI. Intra-class cross correlation (ICC) between tumor volume and involved vessels were calculated.ResultsAmong all 4D imaging modalities evaluated, SS-4D-MRI sampling trajectory results in images with highest vessel-tissue CNR comparing to non-slab-selective 4D-MRI and 4D-CT for all patients studied. Average (±standard deviation) CNR for involved vessels are 13.1 ± 8.4 and 3.2 ± 2.7 for SS-4D-MRI and 4D-CT, respectively. The ICC factors comparing tumor and involved vessels motion trajectories are 0.93 ± 0.10, 0.65 ± 0.31 and 0.77 ± 0.23 for superior-inferior, anterior-posterior and medial-lateral directions respectively.ConclusionsA novel 4D-MRI sequence based on 3D-radial sampling and slab-selective excitation has been assessed for pancreatic cancer patients. The non-contrast 4D-MRI images showed significantly better contrast to noise ratio for the vessels that limit tumor resectability compared to 4D-CT with delayed contrast. The sequence has great potential in accurately defining both the tumor and boost volume margins for pancreas RT with simultaneous integrated boost.

Motion compensation with skin contact control for high intensity focused ultrasound surgery in moving organs

High intensity focused ultrasound (HIFU) is an emerging therapeutic solution that enables non-invasive treatment of several pathologies, mainly in oncology. On the other hand, accurate targeting of moving abdominal organs (e.g. liver, kidney, pancreas) is still an open challenge. This paper proposes a novel method to compensate the physiological respiratory motion of organs during HIFU procedures, by exploiting a robotic platform for ultrasound-guided HIFU surgery provided with a therapeutic annular phased array transducer. The proposed method enables us to keep the same contact point between the transducer and the patient’s skin during the whole procedure, thus minimizing the modification of the acoustic window during the breathing phases. The motion of the target point is compensated through the rotation of the transducer around a virtual pivot point, while the focal depth is continuously adjusted thanks to the axial electronically steering capabilities of the HIFU transducer.The feasibility of the angular motion compensation strategy has been demonstrated in a simulated respiratory-induced organ motion environment. Based on the experimental results, the proposed method appears to be significantly accurate (i.e. the maximum compensation error is always under 1 mm), thus paving the way for the potential use of this technique for in vivo treatment of moving organs, and therefore enabling a wide use of HIFU in clinics.

Prediction of Lung Motion From Four-Dimensional Computer Tomography (4DCT) Images Using Bayesian Registration and Trajectory Modelling

Respiratory motion causes difficulty in locating tumours in the thorax and upper abdomen for image-guided radiotherapy. Precisely predicting the respiratory-induced organ motion is still a challenging problem at present. In this paper, to predict the motion of lungs in a respiratory cycle, we propose a novel method comprising Bayesian registration and trajectory modelling based on cine four-dimensional computer tomography (4DCT) images. Specifically, we take the CT image captured at the end-inhale phase as the source image and those captured at other phases as the moving images. We then align the source image to each moving-phase image to generate the displacement fields using the Bayesian registration method. The lung-motion trajectory is then modelled based on a continuous time-related displacement field by linking the displacement fields at discrete phases. The results indicate that any point in the lungs at any given time is accurately predicted using the proposed method, which provides an alternative method of estimating the lung and tumour motions for radiation therapy.

Experimental validation of a 4D dose calculation routine for pencil beam scanning proton therapy

Respiratory induced organ motion poses a major challenge for high-precision radiotherapy such as pencil beam scanning proton therapy (PBS). In order to employ PBS for target regions affected by respiratory motion, the implementation of dedicated motion mitigation techniques should be considered and residual uncertainties need to be assessed. For the latter purpose, a routine simulating the delivery of a scanned proton beam to a moving target was developed and implemented in the commercial treatment planning system RayStation. The time structure of the beam delivery was extracted from electronic irradiation protocols of the delivery system. Alternatively to electronic irradiation protocols, an empirical time model of the beam delivery was created to allow for prospective estimations of interplay effects between target motion and pencil beam scanning. The experimental validation of the routine was performed using a two-dimensional ionization chamber array and a dynamic phantom. A 4D CT data set, including 10 respiratory phases, provided the spatial temporal information about the phantom motion. The dosimetric comparison of the measured and the calculated dose distribution yielded gamma pass rates above 96% using a 3% dose difference and a 3mm distance to agreement criterion. Thus, a tool for the evaluation of interplay effects is available in a clinical software environment and patient-specific quality assurance can be extended to dynamic treatment scenarios.

Ultrasound image based visual servoing for moving target ablation by high intensity focused ultrasound.

BackgroundAlthough high intensity focused ultrasound (HIFU) is a promising technology for tumor treatment, a moving abdominal target is still a challenge in current HIFU systems. In particular, respiratory‐induced organ motion can reduce the treatment efficiency and negatively influence the treatment result. In this research, we present: (1) a methodology for integration of ultrasound (US) image based visual servoing in a HIFU system; and (2) the experimental results obtained using the developed system.Materials and methodsIn the visual servoing system, target motion is monitored by biplane US imaging and tracked in real time (40 Hz) by registration with a preoperative 3D model. The distance between the target and the current HIFU focal position is calculated in every US frame and a three‐axis robot physically compensates for differences. Because simultaneous HIFU irradiation disturbs US target imaging, a sophisticated interlacing strategy was constructed.ResultsIn the experiments, respiratory‐induced organ motion was simulated in a water tank with a linear actuator and kidney‐shaped phantom model. Motion compensation with HIFU irradiation was applied to the moving phantom model. Based on the experimental results, visual servoing exhibited a motion compensation accuracy of 1.7 mm (RMS) on average. Moreover, the integrated system could make a spherical HIFU‐ablated lesion in the desired position of the respiratory‐moving phantom model.ConclusionsWe have demonstrated the feasibility of our US image based visual servoing technique in a HIFU system for moving target treatment.

Method of evaluating respiratory induced organ motion by vector volume histogram

PurposePublished organ motion data have been collected from measurements of a limited number of points within the organ, the centroid, or the edge of the organ. These are derived from the spatial characteristics of respiratory induced motion; however, this approach does not consider non-rigid organ deformation. We propose a novel quantitative method for evaluating respiratory induced organ motion using Deformable Image Registration (DIR). MethodTwo phases from a 4-dimensional computed tomography (4D CT) dataset at maximum inspiration and expiration were each taken from five patients. The left and right lungs, esophagus, stomach, spinal cord, and liver were manually contoured in the end-expiration phase. The hybrid deformable registration algorithm of the RayStation treatment planning system (TPS) was used to deform the end-expiration phase to the end-inspiration phase. From this, the deformation vector field (DVF) was calculated. DVFs consist of DVFLR (left-right), DVFAP (anterior-posterior), and DVFSI (superior-inferior) as separate files. We calculated the vector volume histogram (VVH) and Lmax (maximum absolute vector of the organ) to evaluate every vector for each individual organ. We also measured respiratory organ motion from the position of the organ centroid in two phases. ResultsVVH enabled us to find the absolute distance and volume of the organ contributing to motion points on the curve. Organ motion using the centroid method was smaller than Lmax using VVH. Using the centroid method, it is difficult to evaluate the deformable organ motion. ConclusionVVH may be a useful technique in evaluating organ volumetric change during respiratory organ motion.

EP-1412: Respiration-induced organ motion in children during image-guided radiation therapy

EP-1412: Respiration-induced organ motion in children during image-guided radiation therapy

211 - 4D dose calculations: Tetrahedral meshes versus voxel-based structures

Purpose: The estimation of the distribution patterns of energy and dose in respiratory-induced organ motion represents a technical challenge for hadron therapy treatment planning, notably in the case of lung cancer in which many difficulties arose, like tissue densities variation and the tumor position shifting during breathing. This study focuses on the comparison between deformable tetrahedral meshes and voxel-based structures used as computational phantoms in four-dimensional dose calculations. The former use a continuous representation of tissue densities by respecting mass conservation principle, while the latter is a discrete grid of density values (CT-scan). Methods: The movement used to simulate breathing is generated with deformable image registration (DIR) of CT images (Castillo, 2010) (Klein, 2010) (Shamonin, 2013). Tissue tracking for tetrahedral model is implicitly performed by the fact that the meshes maintain their topology during deformations. The dose distribution is calculated using the time-dependent tetrahedral density map issued from 4D-CT scans (Petru Manescu, 2014). Unlike image-based methods, the deposited energy is accumulated inside each deforming tetrahedron of the meshes. An implementation of this dose computation method on a deformable anatomy in the case of a passive scattering beam line is demonstrated using the Geant4 code (Agostinelli, 2003). Besides, energy values in voxel-based structures are calculated for each time step and accumulated using the transformations provided by the registration. Then, values are accumulated back onto the reference image and divided by the mass to obtain the 4D dose map. Figure 1 illustrates the process used to accumulate dose in respiratory-induced simulations. Results: The tetrahedral mesh dose distribution was compared to the conventional voxel-based structure using a thoracic 4D-CT data of a patient case. Preliminary results show that dose distributions for both representations are in a good agreement (figure 2), and dose homogeneity is about the same (table1). However, motion-induced dose accumulations are more intuitive using a tetrahedral model since they do not introduce additional uncertainties with image resampling and interpolation methods, and also for the fact that they respect mass conservation principle. Conclusion: We have developed a 4D tetrahedral model for Monte Carlo dose calculations alongside its implementation on the Geant4 platform. Results of comparison with conventional methods based on voxels have shown that dose distributions are in good agreement. This novel structure can be of a great aid for treatment planning of moving targets. An experimental validation based on 4D anthropomorphic phantom (e.g. LuCa phantom developed in paul scherrer institute) (Neihart, 2013) would draw a clear conclusion regarding the performance of the presented method in comparison with the classical methods. Nevertheless, the main advantage of this method is that, coupled with a patient-specific biomechanical model, it could be used in the future to correct motion artefacts in treatment planning.

Motion compensation for PET image reconstruction using deformable tetrahedral meshes

Respiratory-induced organ motion is a technical challenge to PET imaging. This motion induces displacements and deformation of the organs tissues, which need to be taken into account when reconstructing the spatial radiation activity. Classical image-based methods that describe motion using deformable image registration (DIR) algorithms cannot fully take into account the non-reproducibility of the respiratory internal organ motion nor the tissue volume variations that occur during breathing. In order to overcome these limitations, various biomechanical models of the respiratory system have been developed in the past decade as an alternative to DIR approaches. In this paper, we describe a new method of correcting motion artefacts in PET image reconstruction adapted to motion estimation models such as those based on the finite element method. In contrast with the DIR-based approaches, the radiation activity was reconstructed on deforming tetrahedral meshes. For this, we have re-formulated the tomographic reconstruction problem by introducing a time-dependent system matrix based calculated using tetrahedral meshes instead of voxelized images. The MLEM algorithm was chosen as the reconstruction method. The simulations performed in this study show that the motion compensated reconstruction based on tetrahedral deformable meshes has the capability to correct motion artefacts. Results demonstrate that, in the case of complex deformations, when large volume variations occur, the developed tetrahedral based method is more appropriate than the classical DIR-based one. This method can be used, together with biomechanical models controlled by external surrogates, to correct motion artefacts in PET images and thus reducing the need for additional internal imaging during the acquisition.

128: 4D dose calculations and 4D PET image reconstruction using deformable tetrahedral models of moving organs

Purpose: Respiratory-induced organ motion is a technical challenge to nuclear imaging and to particle therapy dose calculations for lung cancer treatment in particular. Internal organ tissue displacements and deformations induced by breathing need to be taken into account when calculating Monte Carlo dose distributions or when performing tomographic reconstructions for PET imaging. Current techniques based on Deformable Image Registration (DIR) cannot fully take into account complex internal deformations of the lungs nor the fact that respiratory motion is not reproducible. This study proposes a method to calculate dose distribution and to reconstruct PET activities over adaptive tetrahedral meshes which deform with time. As an illustration, biomechanical modeling based on Finite Element Analysis (FEA) was used for motion field computation.

Computer assisted radiation Therapy

Hadron therapy is an advanced radiotherapy technique for cancer treatment. It offers a better irradiation ballistic than conventional techniques and requires an appropriate quality assurance procedures. Tumor motion during irradiation reduces target coverage and increases dose to healthy tissues. Unfortunately, the continuous organ density changes due to respiratory motion and affect the ranges of ions which can lead to unwanted dose distributions in the case of lung tumors. Accurate 4D dosimetry calculations are important for treatment planning verification and evaluation. They require temporal information about the tumor position, size and shape, as well as information regarding the tissue density variation along the beam path during treatment. For more precision, several studies have focused on the biomechanical models of the respiratory system based on finite element method. These approaches are based on continuum mechanics of materials properties, mesh organ geometry, as well as anatomical boundary conditions. However, so far, they do not take completely into account density variations needed for dose calculations. In this context, Velec et al. have developed a model that incorporates rigid body motion and deformation (RBD) in order to study the impact of respiratory-induced organ motion on dose calculation for liver tumors. They use linear interpolation to modulate the dose distribution previously calculated from exhale position to inhale position in each tetrahedral element for these intermediate breathing states.

Reducing Gated IMRT Delivery Times: Dual-gated Delivery Optimization and Implementation

Reducing Gated IMRT Delivery Times: Dual-gated Delivery Optimization and Implementation

Respiratory-Induced Organ Motion During Free-Breathing: A Source Of Errors During Radiosurgery For The Upper Urinary Tract

Respiratory-Induced Organ Motion During Free-Breathing: A Source Of Errors During Radiosurgery For The Upper Urinary Tract

Application of the Radiobiological P + Index as a Modality Discriminator for Mobile Tumor Radiotherapy: A Preliminary Study Involving 4DCT Volumes of 18 Lung Cancer Patients

Technological advancements provide sophisticated radiotherapy modalities that promise exquisite target conformality with sparing of surrounding healthy tissue. Of interest is the radiotherapy of mobile tumors where 4D target tracking radiotherapy (4DTRT) is being developed to manage respiratory-induced organ motion. The clinical implementation of 4DTRT can be very challenging compared to conventional radiotherapy using individualized motion margins (CONV). The need to justify the added technological effort for the clinical return is an important one facing the radiotherapy community.

On a PCA-based lung motion model

Respiration-induced organ motion is one of the major uncertainties in lung cancer radiotherapy and is crucial to be able to accurately model the lung motion. Most work so far has focused on the study of the motion of a single point (usually the tumor center of mass), and much less work has been done to model the motion of the entire lung. Inspired by the work of Zhang et al (2007 Med. Phys. 34 4772–81), we believe that the spatiotemporal relationship of the entire lung motion can be accurately modeled based on principle component analysis (PCA) and then a sparse subset of the entire lung, such as an implanted marker, can be used to drive the motion of the entire lung (including the tumor). The goal of this work is twofold. First, we aim to understand the underlying reason why PCA is effective for modeling lung motion and find the optimal number of PCA coefficients for accurate lung motion modeling. We attempt to address the above important problems both in a theoretical framework and in the context of real clinical data. Second, we propose a new method to derive the entire lung motion using a single internal marker based on the PCA model. The main results of this work are as follows. We derived an important property which reveals the implicit regularization imposed by the PCA model. We then studied the model using two mathematical respiratory phantoms and 11 clinical 4DCT scans for eight lung cancer patients. For the mathematical phantoms with cosine and an even power (2n) of cosine motion, we proved that 2 and 2n PCA coefficients and eigenvectors will completely represent the lung motion, respectively. Moreover, for the cosine phantom, we derived the equivalence conditions for the PCA motion model and the physiological 5D lung motion model (Low et al 2005 Int. J. Radiat. Oncol. Biol. Phys. 63 921–9). For the clinical 4DCT data, we demonstrated the modeling power and generalization performance of the PCA model. The average 3D modeling error using PCA was within 1 mm (0.7 ± 0.1 mm). When a single artificial internal marker was used to derive the lung motion, the average 3D error was found to be within 2 mm (1.8 ± 0.3 mm) through comprehensive statistical analysis. The optimal number of PCA coefficients needs to be determined on a patient-by-patient basis and two PCA coefficients seem to be sufficient for accurate modeling of the lung motion for most patients. In conclusion, we have presented thorough theoretical analysis and clinical validation of the PCA lung motion model. The feasibility of deriving the entire lung motion using a single marker has also been demonstrated on clinical data using a simulation approach.