ELPHA: Dynamically deformable liver phantom for real-time motion-adaptive radiotherapy treatments.

In stereotactic body radiation therapy (SBRT) of prostatic cancer, a high dose per fraction is applied to the target with steep dose gradients. Intrafractional prostate motion can occur unpredictably during the treatment and lead to target miss. This work investigated the dosimetric benefit of motion compensation with dynamic treatment-couch tracking for prostate SBRT treatments in the presence of prostatic motion. Ten SBRT treatment plans for prostate cancer patients with integrated boosts to their index lesion were prepared. The treatment plans were applied with a TrueBeam linear accelerator to a phantom in (a) static reference position, (b) moved with five prostate motion trajectories without any motion compensation, and (c) with real-time compensation using transponder-guided couch tracking. The geometrical position of the electromagnetic transponder was evaluated in the tracked and untracked situation. The dosimetric performance of couch tracking was evaluated, using Gamma agreement indices (GAI) and other dose parameters. These were evaluated within the phantoms biplanar diode array, as well as target- and organ-specific. The root-mean-square error of the motion traces (range: 0.8-4.4 mm) was drastically reduced with couch tracking (0.2-0.4 mm). Residual motion was mainly observed at abrupt direction changes with steep motion gradients. The phantom measurements showed significantly better GAI1%/1mm with tracked (range: 83.4%-100.0%) than with untracked motion (28.9%-99.7%). Also GAI2%/2mm was significantly superior for the tracked (98.4%-100.0%) than the untracked motion (52.3%-100.0%). The organ-specific evaluation showed significantly better target coverage with tracking. The dose to the rectum and bladder showed a dependency on the anterior-posterior motion direction. Couch tracking clearly improved the dosimetric accuracy of prostate SBRT treatments. The treatment couch was able to compensate the prostatic motion with only some minor residual motion. Therefore, couch tracking combined with electromagnetic position monitoring for prostate SBRT is feasible and improves the accuracy in treatment delivery when prostate motion is present.

Purpose: The era of real-time adaptive radiotherapy is here: patients are being treated by CyberKnife (since 2004), Vero (2011) and MLC tracking (2013) technology, with couch tracking planned to be clinical in 2015. We have developed a common set of tools for benchmarking real-time adaptive radiotherapy systems and to test the hypothesis that, across delivery systems and institutions, real-time adaptive radiotherapy improves the dosimetric accuracy over non-adaptive radiotherapy in the presence of realistic tumor motion. Methods: Ten institutions with CyberKnife, Vero, MLC or couch tracking technology were involved in the study. Common materials were anonymized lung and prostate CT and structure sets, patient-measured motion traces (four lung, four prostate) and SBRT planning protocols (lung: RTOG1021, prostate: RTOG0938). The institutions delivered lung and prostate plans to a moving dosimeter programmed with tumor motion. For each trace the plan was delivered twice; with and without motion adaptation, each measurement was compared to the static dosimeter dose and the percentage of failed points for γ-tests recorded. Results: Eleven measurement sets were obtained for this study; two CyberKnife, two Vero, five MLC and two couch tracking sets. For all lung traces all sets show improved dose accuracy from a mean 2%/2mm γ-failrate of 1.6% with adaptation and 14.7% with no motion correction(p<0.001). For all prostate traces the mean 2%/2mm γ-failrate was 1.6% with adaptation and 17.4% with no motion correction (p<0.001). The difference between the four adaptive systems was small with an average 2%/2mm γ-failrate of <3% for all systems with adaptation for lung and prostate. Conclusion: A common set of tools has been developed for benchmarking real-time adaptive radiotherapy systems and a multi-platform multi-institutional study performed. The results show the systems all account for realistic tumor motion accurately and performed to a similar high standard, with real-time adaptation significantly outperforming non-adaptive methods.

Purpose: 4D dose calculations have been developed that explicitly incorporate patient motion and deformation in the calculation of dose. Before these calculations can be used in the clinic it is necessary to evaluate and verify their accuracy. The purpose of this study was to develop a deformable lung phantom for verification of 4D dose calculations. Method and Materials: The Radiological Physics Center (RPC) had previously developed an anthropomorphic thoracic phantom with inhomogeneities and an imageable target. An insert was built for the lung cavity of this phantom to incorporate motion and deformation. The insert was composed of disks of sponges of different compressabilities and a computer controlled motor‐driven piston to compress the sponges. The control system is capable of reproducing measured respiratory motion traces as well as simple sinusoidal motions. A tissue‐equivalent target was placed in one of the sponge disks and planes of films were distributed throughout the target and between sponge disks. Results: The choice of sponge compressibility, thickness, and order has allowed us to shape the lung motion to mimic clinically observed deformations. In addition the design of the deformable phantom offers flexibility of target position and motion, film placement and diaphragm motion pattern. Conclusion: The deformable lung insert for the RPC phantom provides an anthropomorphic phantom that can be used to verify the accuracy of 4D dose calculations. Conflict of Interest: This work is partially supported through a Sponsored Research Agreement with Philips Healthcare.

This paper presents a visual-servoing method for compensating motion of soft tissue structures using 4D ultra-sound. The motion of soft tissue structures caused by physiological and external motion makes it difficult to investigate them for diagnostic and therapeutic purposes. The main goal is to track non-rigidly moving soft tissue structures and compensate the motion in order to keep a lesion on its target position during a treatment. We define a 3D non-rigid motion model by extending the Thin-Plate Spline (TPS) algorithm. The motion parameters are estimated with intensity-value changes of a points set in a tracking soft tissue structure. Finally, the global rigid motion is compensated with a 6-DOF robot according to the motion parameters of the tracking structure. Simulation experiments are performed with recorded 3D US images of in-vivo soft tissue structures and validate the effectiveness of the non-rigid motion tracking method. Robotic experiments demonstrated the success of our method with a deformable phantom.

BackgroundFetal cardiovascular MRI complements ultrasound to assess fetal cardiovascular pathophysiology.PurposeTo develop a free‐breathing method for retrospective fetal cine MRI using Doppler ultrasound (DUS) cardiac gating and tiny golden angle radial sampling (tyGRASP) for accelerated acquisition capable of detecting fetal movements for motion compensation.Study TypeFeasibility study.SubjectsNine volunteers (gestational week 34–40). Short‐axis and four‐chamber views were acquired during maternal free‐breathing and breath‐hold.Field Strength/Sequence1.5T cine balanced steady‐state free precession.AssessmentA self‐gated reconstruction method was improved for clinical application by using 1) retrospective DUS gating, and 2) motion detection and rejection/correction algorithms for compensating for fetal motion. The free‐breathing reconstructions were qualitatively and quantitatively assessed, and DUS‐gating was compared with self‐gating in breath‐hold reconstructions. A scoring of 1–4 for overall image quality, cardiac, and extracardiac diagnostic quality was used.Statistical TestsFriedman's test was used to assess differences in qualitative scoring between observers. A Wilcoxon matched‐pairs signed rank test was used to assess differences between breath‐hold and free‐breathing acquisitions and between observers' quantitative measurements.ResultsIn all cases, 111 free‐breathing and 145 breath‐hold acquisitions, the automatically calculated DUS‐based cardiac gating signal provided reconstructions of diagnostic quality (median score 4, range 1–4). Free‐breathing did not affect the DUS‐based cardiac gated retrospective radial reconstruction with respect to image or diagnostic quality (all P > 0.06). Motion detection with rejection/correction in k‐space produced high‐quality free‐breathing DUS‐based reconstructions [median 3, range (2–4)], whereas free‐breathing self‐gated methods failed in 80 out of 88 cases to produce a stable gating signal.Data ConclusionFree‐breathing fetal cine cardiac MRI based on DUS gating and tyGRASP with motion compensation yields diagnostic images. This simplifies acquisition for the pregnant woman and thus could help increase fetal cardiac MRI acceptance in the clinic.Level of Evidence: 2Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:260–272.

We present a video object extraction algorithm combining image partition with motion detection. It consists of three stages: spatial image partition (SIP), temporal motion detection (TMD) and spatiotemporal projection (STP). Firstly, we partition the current video frame into a series of image regions by a modified watershed transform with double open-closing reconstruction and non-linear pixel classification, and the corresponding region boundaries are achieved. In the next stage, global motion estimation and compensation (GME & GMC) are performed, then motion detection based on Gaussianity test is applied to pixels on region boundaries, not to all pixels belonging to regions. In final stage, motion mask is projected to the current frame to segmenting video objects. Preliminary simulation results demonstrate the performance of the proposed algorithm.

IMRT delivery follows a planned leaf sequence, which is optimized before treatment delivery. However, it is hard to model real-time variations, such as respiration, in the planning procedure. In this paper, we propose a negative feedback system of IMRT delivery that incorporates real-time optimization to account for intra-fraction motion. Specifically, we developed a feasible workflow of real-time motion-adaptive-optimization (MAO) for TomoTherapy delivery. TomoTherapy delivery is characterized by thousands of projections with a fast projection rate and ultra-fast binary leaf motion. The technique of MAO-guided delivery calculates (i) the motion-encoded dose that has been delivered up to any given projection during the delivery and (ii) the future dose that will be delivered based on the estimated motion probability and future fluence map. These two pieces of information are then used to optimize the leaf open time of the upcoming projection right before its delivery. It consists of several real-time procedures, including ‘motion detection and prediction’, ‘delivered dose accumulation’, ‘future dose estimation’ and ‘projection optimization’. Real-time MAO requires that all procedures are executed in time less than the duration of a projection. We implemented and tested this technique using a TomoTherapy® research system. The MAO calculation took about 100 ms per projection. We calculated and compared MAO-guided delivery with two other types of delivery, motion-without-compensation delivery (MD) and static delivery (SD), using simulated 1D cases, real TomoTherapy plans and the motion traces from clinical lung and prostate patients. The results showed that the proposed technique effectively compensated for motion errors of all test cases. Dose distributions and DVHs of MAO-guided delivery approached those of SD, for regular and irregular respiration with a peak-to-peak amplitude of 3 cm, and for medium and large prostate motions. The results conceptually proved that the proposed method is applicable for real-time motion compensation in TomoTherapy delivery. Extension of the method to real-time adaptive radiation therapy (ART) that compensates for all kinds of delivery errors was proposed. Further validation and clinical implementation is underway.For more information on this article see medicalphysicsweb.org

Aiming at the higher bit-rate occupation of motion vector encoding and more time load of full-searching strategies, a multi-resolution motion estimation and compensation algorithm based on adjacent prediction of frame difference was proposed. Differential motion detection was employed to image sequences and proper threshold was adopted to identify the connected region. Then the motion region was extracted to carry out motion estimation and motion compensation on it. The experiment results show that the encoding efficiency of motion vector is promoted, the complexity of motion estimation is reduced and the quality of the reconstruction image at the same bit-rate as Multi-Resolution Motion Estimation (MRME) is improved.

Purpose: A critical component of real-time MLC tracking is to incorporate motion prediction in order to account for system latency, the time between the occurrence of motion and MLC leaf repositioning, so as to avoid geometric and dosimetric errors. In this work, we address a major limitation of current motion prediction algorithms – estimating the inherent error in prediction in real-time. We propose using an ensemble of real-time predictors to reduce overall prediction error, and provide a quantitative metric to trigger beam holds based on a user-defined error threshold. Methods: An ensemble of eighteen kernel density estimation (KDE)-based estimators was implemented in parallel and deployed on motion traces recorded from ten lung cancer patients. For each trace, the ensemble generated a sequence of predictions for a look-ahead time of 250ms, typical for many real-time systems. Each predictor, and the ensemble as a whole, was evaluated based on their root-mean-square error (RMSE) with respect to the original data, and assigned a beam hold score between 0 (perfect) and 1 to quantify the number of false beam holds and false beam releases. Results: The average execution time of the KDE-ensemble was 16ms, well below the 250ms look-ahead. For all traces, the ensemble produced a lower RMSE and hold score than any of the individual constituent predictors. For the worst-case motion trace, the minimum RMSE(hold score) for individual predictors was 0.912cm(0.340) compared to 0.854cm(0.305) for the KDE-ensemble predictor. The hold score for individual estimators was ∼0.6 when error estimates were not used to assert beam holds. Conclusion: The KDE-ensemble approach results in improved motion prediction. More importantly, it also provides real-time estimations of prediction error, thus addressing a major gap in current motion prediction algorithms. Such error prediction can be utilized to assert beam-holds during MLC tracking, preventing serious geometric and dosimetric errors. Funding for this work was provided by Elekta Limited.

In this paper, to detect the moving objects between frames in compressed video and to obtain the best compression video and the noiseless video. We describe a video in which frames by classifying macroblocks (MB), and describe motion estimation (ME), motion vector field (MV) and motion compensation (MC). we propose to classify Macroblocks of each video frame into different classes and use this class information to describe the frame content based on the motion vector. MB class information video applications such as shot change detection, motion discontinuity detection, Outlier rejection for global motion estimation. To reduce the noise and to improve the clarity of the compressed video by using contrast limited adaptive histogram equalization (CLAHE) Algorithm.

While head motion is considered a significant problem in magnetic resonance imaging (MRI), there is no data to quantify its extent, severity, or effect on image quality. PROPELLER (Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction) MRI offers a novel means of quantifying and compensating for head motion. We performed axial T2-weighted PROPELLER (motion corrected: P-CR; uncorrected: P-UNCR) and conventional MRI (CONV), with equal scan times, in five normal volunteers and 35 clinical subjects. Volunteers were examined lying still and performing two separate head movements (shake "no" and nod "yes") to assess detection and compensation of in-plane motion by PROPELLER MRI. Images were examined by three radiologists for motion artifact and for overall image quality. Head rotation and translation was detected in all subjects during each slice acquisition, with expected changes occurring with volunteer head motion. Motion artifact was less commonly seen on PROPELLER than CONV MR (chi(2) test P < 0.001). PROPELLER was preferred over CONV in all subjects (P < 0.05) and P-CR was judged superior to P-UNCR (P = 0.02). Intracranial pathology was equally or better demonstrated with PROPELLER. PROPELLER MRI offers a means of quantifying head motion, reducing motion artifact, and improving image quality.

The occurrence of physiological artifacts generated by eye movements in electrical brain activity (electroencephalography, EEG) is a well-known problem in clinical practice. In order to increase the accuracy of the detection of eye movements during EEG examination, additional electrooculogram channels (electrooculography, EOG) with a standard PC keyboard are used. The EOG technique is not always comfortable for patients. Another issue is that the use of EOG channels in the EEG examination leads to the prolongation of time required for patient preparation. To solve these problems, we developed a new peripheral device suitable for the indication of common ocular artifacts in EEG. The obtained differences between the recommended methods (i.e., EOG, PC keyboard) and our new device have been presented using RMSE (root mean square error). The presented equipment can be used either during EEG examination or after registration of EEG signals in order to indicate the ocular artifacts. Furthermore, this device is compatible with the EEG software used in clinical practice.

Plant foliage is known to respond rapidly to environmental stressors by adjusting leaf orientation at different timescales. One of the most fascinating mechanisms is paraheliotropism, also known as light avoidance through leaf movement. The leaf orientation (zenith and azimuth angles) is a parameter often overlooked in the plant and remote sensing community due to its challenging measurement procedures under field conditions. In this study, we investigate the synergistic potential of uncrewed aerial vehicle (UAV)-based mutlispectral imaging, terrestrial laser scanning (TLS) and radiative transfer model (RTM) inversion to identify the paraheliotropic response of two distinct soybean varieties: Minngold, a chlorophyll-deficient mutant, and Eiko, a wild variety. We examined their responses to drought stress during the boreal summer drought in 2022 in western Germany by measuring average leaf inclination angle (ALIA) and canopy reflectance. Measurements were taken in the morning and at midday to track leaf movement. Our observations show significant differences between the paraheliotropic response of both varieties. Eiko’s terminal and lateral leaves became vertically erect in the midday (54→61∘), while Minngold’s ALIA remained largely unchanged (52→57∘). Apart from the vertical leaf movement, we also observed leaf inversion (exposing the abaxial side of the leaf) in Eiko under extreme water scarcity. The red edge band at 740 nm showed the strongest correlation with ALIA (r2=0.52−0.76) The ratio of the far red edge to near infrared (RE740/NIR842) vegetation index compensated for varying light levels during morning and afternoon measurements, exhibiting strong correlations with ALIA when considering only sun-lit leaf spectra (r2=0.72). The retrieval of ALIA with PROSAIL varied based on ALIA constraints and the spectra used for retrieval (full spectrum or the combination of bands 742 and 842), resulting in a root mean square error (RMSE) of 7.7-12.9°. PROSAIL faced challenges in simulating the spectra of plots with very low LAI due to the soil background. This study made the first attempt to observe different paraheliotropic responses of two soybean varieties with UAV-based multispectral imaging. Proximal sensing opens up the possibilities to observe early stress indicators such as paraheliotropism, at much higher spatial and temporal resolution than ever before.

Introduction: In radiotherapy, tumors may move due to the patient’s respiration, which decreases treatment accuracy. Some motion mitigation methods require measuring the tumor position during treatment. Current available sensors often suffer from time delays, which degrade the motion mitigation performance. However, the tumor motion is often periodic and continuous, which allows predicting the motion ahead. Method and Materials: A couch tracking system was simulated in MATLAB and five prediction filters selected from literature were implemented and tested on 51 respiration signals (median length: 103 s). The five filters were the linear filter (LF), the local regression (LOESS), the neural network (NN), the support vector regression (SVR), and the wavelet least mean squares (wLMS). The time delay to compensate was 320 ms. The normalized root mean square error (nRMSE) was calculated for all prediction filters and respiration signals. The correlation coefficients between the nRMSE of the prediction filters were computed. Results: The prediction filters were grouped into a low and a high nRMSE group. The low nRMSE group consisted of the LF, the NN, and the wLMS with a median nRMSE of 0.14, 0.15, and 0.14, respectively. The high nRMSE group consisted of the LOESS and the SVR with both a median nRMSE of 0.34. The correlations between the low nRMSE filters were above 0.87 and between the high nRMSE filters it was 0.64. Conclusion: The low nRMSE prediction filters not only have similar median nRMSEs but also similar nRMSEs for the same respiration signals as the high correlation shows. Therefore, good prediction filters perform similarly for identical respiration patterns, which might indicate a minimally achievable nRMSE for a given respiration pattern.

Rainfall induced landslides have been the No.1 geohazards in Hong Kong (HK). In coastal subtropical monsoon regions, air temperature and humidity vary substantially and frequently. Tropospheric delays (TDs) limit the accurate detection of slow slope motion (which is the common case in HK) using interferometric synthetic aperture radar (InSAR). &amp;#160;In this presentation, we introduce a new TD correction method for InSAR line-of-sight (LOS) measurements at individual slope scale. The TD signal was estimated from LOS time series through a blind source separation (i.e., independent component analysis). The stratified TD was isolated according to a spatially elevation-linked and temporally periodic independent-component (IC), which was determined via a correlation test and power spectrum analysis. Therefore, the TD correction was not relying on any external weather products/meteorological data and had unprecedented spatiotemporal details equivalent to the SAR images.A case study in Tai O, HK was conducted to verify the proposed method using 63 descending CosmoSkyMed (CSK) and 143 ascending Sentinel-1 (SNT-1) images. We used meteorological data of air temperature, humidity and weather products of ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-5 and GACOS (Generic Atmospheric Correction Online Service) to validate the estimated TD. We estimated up to 3-4 cm spatiotemporally relative TD in the LOS directions of CSK and SNT-1, corresponding to a slope elevation change of ~ 400 m. The estimated TD was largely affected by specific air conditions (e.g., temperature and humidity) on the SAR image-acquisition days. In addition, we found the relative TD exhibited a slower increment rate than that of the slope elevation, suggesting the TD was not linearly related to the elevation. Ground deformation measurements from prisms and records of rainfall and tide were used to validate and interpret the InSAR deformation time series. It is interesting to find different hydrological forcings regulate the seasonal deformations in the slope (~ 10mm) and the reclamation (~ 15mm) in Tai O. Downslope movement (due to increase in pore-water pressure) occurred when rainfall accumulated from a dry season to a wet season, whereas upslope rebound (due to soil shrinkage) occurred when rainfall decreased from a wet season to a dry season. However, the periodic deformation of the reclamation substrate seemed to be more related to the sea level, instead of rainfall. The TD correction has reduced the root-mean-square error (RMSE) by 42.3%, such that InSAR LOS time series with millimeter-level accuracy (potentially 1-3 mm) were obtained in the Tai O case.