DMLC IMRT delivery to targets moving in 2D in Beam's eye view

The goal of this article is to present the algorithm for DMLC leaf control capable of delivering IMRT to tumors that experience motion in two dimensions in the beams eye view (BEV) plane. The generic, two-dimensional (2D) motion of the projection of the rigid target on BEV plane can be divided into two components. The first component describes the motion of the projection of the target along the x axis (parallel to the MLC leaf motions) and the other describes the motion of the target projection on the y axis (perpendicular to the leaf motion direction). First, time optimal leaf trajectories are calculated independently for each leaf pair of the MLC assembly to compensate the x-axis component of the 2D motion of the target on the BEV. These leaf trajectories are then synchronized following the mid time (MT) synchronization procedure. To compensate for the y-axis component of the motion of the target projection on the BEV plane, the procedure of "switching" leaf pair trajectories in the upward (or downward) direction is executed when the target's BEV projection moves upward (or downward) from its equilibrium position along the y axis. When the intensity function is a 2D histogram, the error between the intended and delivered intensity in 2D DMLC IMRT delivery will depend on the shape of the intensity map and on the MLC physical constraint (leaf width and maximum admissible leaf speed). The MT synchronization of leaf trajectories decreases the impact of above constraints on the error in 2D DMLC IMRT intensity map delivery. The proof is provided, that if hardware constraints in the 2D DMLC IMRT delivery strategy are removed, the errors between planned and delivered 2D intensity maps are entirely eliminated. Examples of 2D DMLC IMRT delivery to rigid targets moving along elliptical orbits on BEV planes are calculated and analyzed for 20 clinical fluence maps. The comparisons between the intensity delivered without motion correction, with motion correction along x axis only, and with motion correction for full 2D motion of the target are calculated and quantitatively evaluated. The fluence maps were normalized to 100 MU and the rms difference between the desired and delivered fluence was 12 MU for no motion compensation, 11.18 MU for 1D compensation, and 4.73 MU for 2D motion compensations. The advantage of correcting for full 2D motion of target projected on the BEV plane is demonstrated.     

IMRT delivery to a moving target by dynamic MLC tracking: delivery for targets moving in two dimensions in the beam's eye view

A new modification of the dynamic multileaf collimator (dMLC) delivery technique for intensity-modulated therapy (IMRT) is outlined. This technique enables the tracking of a target moving through rigid-body translations in a 2D trajectory in the beam's eye view. The accuracy of the delivery versus that of deliveries with no tracking and of 1D tracking techniques is quantified with clinically derived intensity-modulated beams (IMBs). Leaf trajectories calculated in the target-reference frame were iteratively synchronized assuming regular target motion. This allowed the leaves defined in the lab-reference frame to simultaneously follow the target motion and to deliver the required IMB without violation of the leaf maximum-velocity constraint. The leaves are synchronized until the gradient of the leaf position at every instant is less than a calculated maximum. The delivered fluence in the target-reference frame was calculated with a simple primary-fluence model. The new 2D tracking technique was compared with the delivered fluence produced by no-tracking deliveries and by 1D tracking deliveries for 33 clinical IMBs. For the clinical IMBs normalized to a maximum fluence of 200 MUs, the rms difference between the desired and the delivered IMB was 15.6 +/- 3.3 MU for the case of a no-tracking delivery, 7.9 +/- 1.6 MU for the case where only the primary component of motion was corrected and 5.1 +/- 1.1 MU for the 2D tracking delivery. The residual error is due to interpolation and sampling effects. The 2D tracking delivery technique requires an increase in the delivery time evaluated as between 0 and 50% of the unsynchronized delivery time for each beam with a mean increase of 13% for the IMBs tested. The 2D tracking dMLC delivery technique allows an optimized IMB to be delivered to moving targets with increased accuracy and with acceptable increases in delivery time. When combined with real-time knowledge of the target motion at delivery time, this technique facilitates improved target conformality relative to no-tracking deliveries and allows PTV margin reduction.     

Dynamic-MLC leaf control utilizing on-flight intensity calculations: a robust method for real-time IMRT delivery over moving rigid targets

An algorithm is presented that allows for the control of multileaf collimation (MLC) leaves based entirely on real-time calculations of the intensity delivered over the target. The algorithm is capable of efficiently correcting generalized delivery errors without requiring the interruption of delivery (self-correcting trajectories), where a generalized delivery error represents anything that causes a discrepancy between the delivered and intended intensity profiles. The intensity actually delivered over the target is continually compared to its intended value. For each pair of leaves, these comparisons are used to guide the control of the following leaf and keep this discrepancy below a user-specified value. To demonstrate the basic principles of the algorithm, results of corrected delivery are shown for a leading leaf positional error during dynamic-MLC (DMLC) IMRT delivery over a rigid moving target. It is then shown that, with slight modifications, the algorithm can be used to track moving targets in real time. The primary results of this article indicate that the algorithm is capable of accurately delivering DMLC IMRT over a rigid moving target whose motion is (1) completely unknown prior to delivery and (2) not faster than the maximum MLC leaf velocity over extended periods of time. These capabilities are demonstrated for clinically derived intensity profiles and actual tumor motion data, including situations when the target moves in some instances faster than the maximum admissible MLC leaf velocity. The results show that using the algorithm while calculating the delivered intensity every 50 ms will provide a good level of accuracy when delivering IMRT over a rigid moving target translating along the direction of MLC leaf travel. When the maximum velocities of the MLC leaves and target were 4 and 4.2 cm/s, respectively, the resulting error in the two intensity profiles used was 0.1 +/- 3.1% and -0.5 +/- 2.8% relative to the maximum of the intensity profiles. For the same target motion, the error was shown to increase rapidly as (1) the maximum MLC leaf velocity was reduced below 75% of the maximum target velocity and (2) the system response time was increased.     

A parallelizable real-time motion tracking algorithm with applications to ultrasonic strain imaging

Ultrasound-based mechanical strain imaging systems utilize signals from conventional diagnostic ultrasound systems to image tissue elasticity contrast that provides new diagnostically valuable information. Previous works (Hall et al 2003 Ultrasound Med. Biol. 29 427, Zhu and Hall 2002 Ultrason. Imaging 24 161) demonstrated that uniaxial deformation with minimal elevation motion is preferred for breast strain imaging and real-time strain image feedback to operators is important to accomplish this goal. The work reported here enhances the real-time speckle tracking algorithm with two significant modifications. One fundamental change is that the proposed algorithm is a column-based algorithm (a column is defined by a line of data parallel to the ultrasound beam direction, i.e. an A-line), as opposed to a row-based algorithm (a row is defined by a line of data perpendicular to the ultrasound beam direction). Then, displacement estimates from its adjacent columns provide good guidance for motion tracking in a significantly reduced search region to reduce computational cost. Consequently, the process of displacement estimation can be naturally split into at least two separated tasks, computed in parallel, propagating outward from the center of the region of interest (ROI). The proposed algorithm has been implemented and optimized in a Windows system as a stand-alone ANSI C++ program. Results of preliminary tests, using numerical and tissue-mimicking phantoms, and in vivo tissue data, suggest that high contrast strain images can be consistently obtained with frame rates (10 frames s(-1)) that exceed our previous methods.     

A fiducial detection algorithm for real-time image guided IMRT based on simultaneous MV and kV imaging

The advantage of highly conformal dose techniques such as 3DCRT and IMRT is limited by intrafraction organ motion. A new approach to gain near real-time 3D positions of internally implanted fiducial markers is to analyze simultaneous onboard kV beam and treatment MV beam images (from fluoroscopic or electronic portal image devices). Before we can use this real-time image guidance for clinical 3DCRT and IMRT treatments, four outstanding issues need to be addressed. (1) How will fiducial motion blur the image and hinder tracking fiducials? kV and MV images are acquired while the tumor is moving at various speeds. We find that a fiducial can be successfully detected at a maximum linear speed of 1.6 cm/s. (2) How does MV beam scattering affect kV imaging? We investigate this by varying MV field size and kV source to imager distance, and find that common treatment MV beams do not hinder fiducial detection in simultaneous kV images. (3) How can one detect fiducials on images from 3DCRT and IMRT treatment beams when the MV fields are modified by a multileaf collimator (MLC)? The presented analysis is capable of segmenting a MV field from the blocking MLC and detecting visible fiducials. This enables the calculation of nearly real-time 3D positions of markers during a real treatment. (4) Is the analysis fast enough to track fiducials in nearly real time? Multiple methods are adopted to predict marker positions and reduce search regions. The average detection time per frame for three markers in a 1024 x 768 image was reduced to 0.1 s or less. Solving these four issues paves the way to tracking moving fiducial markers throughout a 3DCRT or IMRT treatment. Altogether, these four studies demonstrate that our algorithm can track fiducials in real time, on degraded kV images (MV scatter), in rapidly moving tumors (fiducial blurring), and even provide useful information in the case when some fiducials are blocked from view by the MLC. This technique can provide a gating signal or be used for intra-fractional tumor tracking on a Linac equipped with a kV imaging system. Any motion exceeding a preset threshold can warn the therapist to suspend a treatment session and reposition the patient.     

A leaf sequencing algorithm to enlarge treatment field length in IMRT

With MLC-based IMRT, the maximum usable field size is often smaller than the maximum field size for conventional treatments. This is due to the constraints of the overtravel distances of MLC leaves and/or jaws. Using a new leaf sequencing algorithm, the usable IMRT field length (perpendicular to the MLC motion) can be mostly made equal to the full length of the MLC field without violating the upper jaw overtravel limit. For any given intensity pattern, a criterion was proposed to assess whether an intensity pattern can be delivered without violation of the jaw position constraints. If the criterion is met, the new algorithm will consider the jaw position constraints during the segmentation for the step and shoot delivery method. The strategy employed by the algorithm is to connect the intensity elements outside the jaw overtravel limits with those inside the jaw overtravel limits. Several methods were used to establish these connections during segmentation by modifying a previously published algorithm (areal algorithm), including changing the intensity level, alternating the leaf-sequencing direction, or limiting the segment field size. The algorithm was tested with 1000 random intensity patterns with dimensions of 21 x 27 cm2, 800 intensity patterns with higher intensity outside the jaw overtravel limit, and three different types of clinical treatment plans that were undeliverable using a segmentation method from a commercial treatment planning system. The new algorithm achieved a success rate of 100% with these test patterns. For the 1,000 random patterns, the new algorithm yields a similar average number of segments of 36.9 +/- 2.9 in comparison to 36.6 +/- 1.3 when using the areal algorithm. For the 800 patterns with higher intensities outside the jaw overtravel limits, the new algorithm results in an increase of 25% in the average number of segments compared to the areal algorithm. However, the areal algorithm fails to create deliverable segments for 90% of these patterns. Using a single isocenter, the new algorithm provides a solution to extend the usable IMRT field length from 21 to 27 cm for IMRT on a commercial linear accelerator using the step and shoot delivery method.     

A new way of adapting IMRT delivery fraction-by-fraction to cater for variable intrafraction motion

In this paper a technique is presented for adaptive therapy to compensate for variable intrafraction tissue motion. So long as the motion can be measured or deduced for each fraction the technique modifies the fluence profile for the subsequent fractions in a repeatable cyclic way. The fluence modification is based on projecting the dose discrepancies between the cumulative delivered dose after each fraction and the expected planned dose at the same stage. It was shown that, in general, it is best to adapt the fluence profile to moving leaves that also have been modified to 'breathe' according to some regular default motion. However, it is important to point out that, if this regular default motion were to differ too much from the variable motion at each fraction, then the result can be worse than adapting to non-breathing leaves in a dynamic MLC technique. Furthermore, in general it should always be possible to improve results by starting the adaptation process with a constrained deconvolution of the regular default motion.     

A multiple model approach to respiratory motion prediction for real-time IGRT

Respiration induces significant movement of tumours in the vicinity of thoracic and abdominal structures. Real-time image-guided radiotherapy (IGRT) aims to adapt radiation delivery to tumour motion during irradiation. One of the main problems for achieving this objective is the presence of time lag between the acquisition of tumour position and the radiation delivery. Such time lag causes significant beam positioning errors and affects the dose coverage. A method to solve this problem is to employ an algorithm that is able to predict future tumour positions from available tumour position measurements. This paper presents a multiple model approach to respiratory-induced tumour motion prediction using the interacting multiple model (IMM) filter. A combination of two models, constant velocity (CV) and constant acceleration (CA), is used to capture respiratory-induced tumour motion. A Kalman filter is designed for each of the local models and the IMM filter is applied to combine the predictions of these Kalman filters for obtaining the predicted tumour position. The IMM filter, likewise the Kalman filter, is a recursive algorithm that is suitable for real-time applications. In addition, this paper proposes a confidence interval (CI) criterion to evaluate the performance of tumour motion prediction algorithms for IGRT. The proposed CI criterion provides a relevant measure for the prediction performance in terms of clinical applications and can be used to specify the margin to accommodate prediction errors. The prediction performance of the IMM filter has been evaluated using 110 traces of 4-minute free-breathing motion collected from 24 lung-cancer patients. The simulation study was carried out for prediction time 0.1-0.6 s with sampling rates 3, 5 and 10 Hz. It was found that the prediction of the IMM filter was consistently better than the prediction of the Kalman filter with the CV or CA model. There was no significant difference of prediction errors for the sampling rates 5 and 10 Hz. For these sampling rates, the errors of the IMM filter for 0.4 s prediction time were less than 2.1 mm in terms of the 95% CI criterion or 1.1 mm in terms of the standard deviation (SD) or root mean squared errors (RMSE) criterion. For the prediction time of 0.6 s the errors were less than 3.6 mm in terms of the 95% CI criterion or 1.8 mm in terms of the SD/RMSE criterion. The prediction error analysis showed that the average percentage of the target lies outside the 95% CI margin was 5.2% and outside the SD/RMSE margin was 24.3%. This indicates the effectiveness of the 95% CI criterion as a margining strategy to accommodate prediction errors.     

A simple method to control aspects of fluence modulation in IMRT planning

Many inverse-planning algorithms and commercial systems generate intensity-modulated beam profiles that have considerable structure. This is the desirable outcome of the quest for high dose-space conformality. However, when these profiles are realized experimentally using the dynamic multileaf collimator (DMLC) method of delivery the monitor-unit efficiency can be quite small, with unwanted consequences. Also the interpretation of these fields leads to the generation of small field segments, again with undesirable consequences. In this note it is shown that the features of beam-space can be user-controlled to minimize these problems. There is a tradeoff between obtaining desirable features in beam-space and high conformality in dose-space.     

A robotic approach to 4D real-time tumor tracking for radiotherapy

Respiratory and cardiac motions induce displacement and deformation of the tumor volumes in various internal organs. To accommodate this undesired movement and other errors, physicians incorporate a large margin around the tumor to delineate the planning target volume, so that the clinical target volume receives the prescribed radiation dose under any scenario. Consequently, a large volume of healthy tissue is irradiated and sometimes it is difficult to spare critical organs adjacent to the tumor. In this study we have proposed a novel approach to the 4D active tracking and dynamic delivery incorporating the tumor motion prediction technique. This method has been applied to the two commercially available robotic treatment couches. The proposed algorithm can predict the tumor position and the robotic systems are able to continuously track the tumor during radiation dose delivery. Therefore a precise dose is given to a moving target while the dose to the nearby critical organs is reduced to improve the patient treatment outcome. The efficacy of the proposed method has been investigated by extensive computer simulation. The tumor tracking method is simulated for two couches: HexaPOD robotic couch and ELEKTA Precise Table. The comparison results have been presented in this paper. In order to assess the clinical significance, dosimetric effects of the proposed method have been analyzed.     

A bird's eye view on the role of dendritic cells in SARS-CoV-2 infection: Perspectives for immune-based vaccines

Coronavirus disease-19 (COVID-19) is a complex disorder caused by the pandemic diffusion of a novel coronavirus named SARS-CoV-2. Clinical manifestations vary from silent infection to severe pneumonia, disseminated thrombosis, multi-organ failure, and death. COVID-19 pathogenesis is still not fully elucidated, while increasing evidence suggests that disease phenotypes are strongly related to the virus-induced immune system's dysregulation. Indeed, when the virus-host cross talk is out of control, the occurrence of an aberrant systemic inflammatory reaction, named “cytokine storm,” leads to a detrimental impairment of the adaptive immune response. Dendritic cells (DCs) are the most potent antigen-presenting cells able to support innate immune and promote adaptive responses. Besides, DCs play a key role in the anti-viral defense. The aim of this review is to focus on DC involvement in SARS-CoV-2 infection to better understand pathogenesis and clinical behavior of COVID-19 and explore potential implications for immune-based therapy strategies.     

A 2D driven 3D vessel segmentation algorithm for 3D digital subtraction angiography data

Cerebrovascular disease is among the leading causes of death in western industrial nations. 3D rotational angiography delivers indispensable information on vessel morphology and pathology. Physicians make use of this to analyze vessel geometry in detail, i.e. vessel diameters, location and size of aneurysms, to come up with a clinical decision. 3D segmentation is a crucial step in this pipeline. Although a lot of different methods are available nowadays, all of them lack a method to validate the results for the individual patient. Therefore, we propose a novel 2D digital subtraction angiography (DSA)-driven 3D vessel segmentation and validation framework. 2D DSA projections are clinically considered as gold standard when it comes to measurements of vessel diameter or the neck size of aneurysms. An ellipsoid vessel model is applied to deliver the initial 3D segmentation. To assess the accuracy of the 3D vessel segmentation, its forward projections are iteratively overlaid with the corresponding 2D DSA projections. Local vessel discrepancies are modeled by a global 2D/3D optimization function to adjust the 3D vessel segmentation toward the 2D vessel contours. Our framework has been evaluated on phantom data as well as on ten patient datasets. Three 2D DSA projections from varying viewing angles have been used for each dataset. The novel 2D driven 3D vessel segmentation approach shows superior results against state-of-the-art segmentations like region growing, i.e. an improvement of 7.2% points in precision and 5.8% points for the Dice coefficient. This method opens up future clinical applications requiring the greatest vessel accuracy, e.g. computational fluid dynamic modeling.     

Extraction of visual motion information for the control of eye and head movement during head-free pursuit

We investigated how effectively briefly presented visual motion could be assimilated and used to track future target motion with head and eyes during target disappearance. Without vision, continuation of eye and head movement is controlled by internal (extra-retinal) mechanisms, but head movement stimulates compensatory vestibulo-ocular reflex (VOR) responses that must be countermanded for gaze to remain in the direction of target motion. We used target exposures of 50-200 ms at the start of randomised step-ramp stimuli, followed by > 400 ms of target disappearance, to investigate the ability to sample target velocity and subsequently generate internally controlled responses. Subjects could appropriately grade gaze velocity to different target velocities without visual feedback, but responses were fully developed only when exposure was > 100 ms. Gaze velocities were sustained or even increased during target disappearance, especially when there was expectation of target reappearance, but they were always less than for controls, where the target was continuously visible. Gaze velocity remained in the direction of target motion throughout target extinction, implying that compensatory (VOR) responses were suppressed by internal drive mechanisms. Regression analysis revealed that the underlying compensatory response remained active, but with gain slightly less than unity (0.85), resulting in head-free gaze responses that were very similar to, but slightly greater than, head-fixed. The sampled velocity information was also used to grade head velocity, but in contrast to gaze, head velocity was similar whether the target was briefly or continuously presented, suggesting that head motion was controlled by internal mechanisms alone, without direct influence of visual feedback.     

A new algorithm for determining collimator angles that favor efficiency in MLC based IMRT delivery

A new algorithm to determine collimator angles that favor delivery efficiency of intensity modulated radiotherapy plans was developed. It was found that the number of segments and monitor units (MUs) were largely reduced with the set of collimator angles determined with the new algorithm without compromising plan quality. The improvement of delivery efficiency using the new algorithm depends on the size and shape of the target(s), the number of modulation levels, and the type of leaf-sequencing algorithm. In a typical prostate case, when a sweeping leaf-sequencer is used for Varian 120 leaf (0.5 x 0.5 cm2 beamlet), 80 leaf (1 x 1 cm2 beamlet) and Elekta 40 leaf (1 x 1 cm2 beamlet), the number of segments was reduced by 42%, 29%, and 5%, respectively. The number of MUs was reduced by 41%, 35%, and 10%. For the Siemens MLC (IMFAST leaf sequencer, 1 x 1 cm2 beamlet) the segment reduction was 32% and the MU reduction was 14%. Comparison of the plans using the new and Brahme algorithms, in terms of target conformity index and dose volume histogram of the organs at risk, showed that the quality of the plans using the new algorithm was uncompromised. Similar results were obtained for a set of head and neck treatment plans.     

Quantification of the fluence error in the motion-compensated dynamic MLC (DMLC) technique for delivering intensity-modulated radiotherapy (IMRT)

When a correction for intrafraction organ motion is to be attempted using the dynamic multileaf collimator (DMLC) 'breathing leaves' technique for intensity-modulated radiotherapy (IMRT), there is a finite response time between the measurement of organ motion and the feeding of a corresponding corrective motion to the leaves. Whilst small this is non-zero. This letter presents a computational strategy to assess the error introduced to the delivered fluence by this system latency. The error depends on the functional form of the intended fluence modulation, the variability of the breathing motion and the magnitude of the system latency.     

A device to control the mass concentration of protein-containing aerosoles in real-time mode

The article is dedicated to the device to measure the mass concentration of protein-containing aerosols, which is now being developed at State Scientific and Research Institute of Biological Instrument Making. The operation of the device is based on the registration of spectral-luminescent and dispersing properties of individual particles of biological nature. Experiments carried out on aerosol static-dynamic stand have demonstrated that the device measures the mass concentration of protein-vitamin concentrate aerosol in real-time mode with 50% accuracy.     

Inferential modeling and predictive feedback control in real-time motion compensation using the treatment couch during radiotherapy

Tumor motion induced by respiration presents a challenge to the reliable delivery of conformal radiation treatments. Real-time motion compensation represents the technologically most challenging clinical solution but has the potential to overcome the limitations of existing methods. The performance of a real-time couch-based motion compensation system is mainly dependent on two aspects: the ability to infer the internal anatomical position and the performance of the feedback control system. In this paper, we propose two novel methods for the two aspects respectively, and then combine the proposed methods into one system. To accurately estimate the internal tumor position, we present partial-least squares (PLS) regression to predict the position of the diaphragm using skin-based motion surrogates. Four radio-opaque markers were placed on the abdomen of patients who underwent fluoroscopic imaging of the diaphragm. The coordinates of the markers served as input variables and the position of the diaphragm served as the output variable. PLS resulted in lower prediction errors compared with standard multiple linear regression (MLR). The performance of the feedback control system depends on the system dynamics and dead time (delay between the initiation and execution of the control action). While the dynamics of the system can be inverted in a feedback control system, the dead time cannot be inverted. To overcome the dead time of the system, we propose a predictive feedback control system by incorporating forward prediction using least-mean-square (LMS) and recursive least square (RLS) filtering into the couch-based control system. Motion data were obtained using a skin-based marker. The proposed predictive feedback control system was benchmarked against pure feedback control (no forward prediction) and resulted in a significant performance gain. Finally, we combined the PLS inference model and the predictive feedback control to evaluate the overall performance of the feedback control system. Our results show that, with the tumor motion unknown but inferred by skin-based markers through the PLS model, the predictive feedback control system was able to effectively compensate intra-fraction motion.