Quantitative investigation of dose accumulation errors from intra-fraction motion in MRgRT for prostate cancer.

Accurate spatial dose delivery in radiotherapy is frequently complicated due to changes in the patient's internal anatomy during and in-between therapy segments. The recent introduction of hybrid MRI radiotherapy systems allows unequaled soft-tissue visualization during radiation delivery and can be used for dose reconstruction to quantify the impact of motion. To this end, knowledge of anatomical deformations obtained from continuous monitoring during treatment has to be combined with information on the spatio-temporal dose delivery to perform motion-compensated dose accumulation (MCDA). Here, the influence of the choice of deformable image registration algorithm, dose warping strategy, and magnetic resonance image resolution and signal-to-noise-ratio on the resulting MCDA is investigated. For a quantitative investigation, four 4D MRI-datasets representing typical patient observed motion patterns are generated using finite element modeling and serve as a gold standard. Energy delivery is simulated intra-fractionally in the deformed image space and, subsequently, MCDA-processed. Finally, the results are substantiated by comparing MCDA strategies on clinically acquired patient data. It is shown that MCDA is needed for correct quantitative dose reconstruction. For prostate treatments, using the energy per mass transfer dose warping strategy has the largest influence on decreasing dose estimation errors.

Anatomically-adaptive multi-modal image registration for image-guided external-beam radiotherapy.

Image-guided radiotherapy (IGRT) allows observation of the location and shape of the tumor and organs-at-risk (OAR) over the course of a radiation cancer treatment. Such information may in turn be used for reducing geometric uncertainties during therapeutic planning, dose delivery and response assessment. However, given the multiple imaging modalities and/or contrasts potentially included within the imaging protocol over the course of the treatment, the current manual approach to determining tissue displacement may become time-consuming and error prone. In this context, variational multi-modal deformable image registration (DIR) algorithms allow automatic estimation of tumor and OAR deformations across the acquired images. In addition, they require short computational times and a low number of input parameters, which is particularly beneficial for online adaptive applications, which require on-the-fly adaptions with the patient on the treatment table. However, the majority of such DIR algorithms assume that all structures across the entire field-of-view (FOV) undergo a similar deformation pattern. Given that various anatomical structures may behave considerably different, this may lead to the estimation of anatomically implausible deformations at some locations, thus limiting their validity. Therefore, in this paper we propose an anatomically-adaptive variational multi-modal DIR algorithm, which employs a regionalized registration model in accordance with the local underlying anatomy. The algorithm was compared against two existing methods which employ global assumptions on the estimated deformations patterns. Compared to the existing approaches, the proposed method has demonstrated an improved anatomical plausibility of the estimated deformations over the entire FOV as well as displaying overall higher accuracy. Moreover, despite the more complex registration model, the proposed approach is very fast and thus suitable for online scenarios. Therefore, future adaptive IGRT workflows may benefit from an anatomically-adaptive registration model for precise contour propagation and dose accumulation, in areas showcasing considerable variations in anatomical properties.

Accelerating multi-modal image registration using a supervoxel-based variational framework.

For the successful completion of medical interventional procedures, several concepts, such as daily positioning compensation, dose accumulation or delineation propagation, rely on establishing a spatial coherence between planning images and images acquired at different time instants over the course of the therapy. To meet this need, image-based motion estimation and compensation relies on fast, automatic, accurate and precise registration algorithms. However, image registration quickly becomes a challenging and computationally intensive task, especially when multiple imaging modalities are involved. In the current study, a novel framework is introduced to reduce the computational overhead of variational registration methods. The proposed framework selects representative voxels of the registration process, based on a supervoxel algorithm. Costly calculations are hereby restrained to a subset of voxels, leading to a less expensive spatial regularized interpolation process. The novel framework is tested in conjunction with the recently proposed EVolution multi-modal registration method. This results in an algorithm requiring a low number of input parameters, is easily parallelizable and provides an elastic voxel-wise deformation with a subvoxel accuracy. The performance of the proposed accelerated registration method is evaluated on cross-contrast abdominal T1/T2 MR-scans undergoing a known deformation and annotated CT-images of the lung. We also analyze the ability of the method to capture slow physiological drifts during MR-guided high intensity focused ultrasound therapies and to perform multi-modal CT/MR registration in the abdomen. Results have shown that computation time can be reduced by 75% on the same hardware with no negative impact on the accuracy.

Respiratory motion model based on the noise covariance matrix of a receive array.

PURPOSE: Tracking of the internal anatomy by means of a motion model that uses the MR-derived motion fields and noise covariance matrix (NCM) dynamic as a surrogate signal. METHODS: A 2D respiratory motion model was developed based on the MR-derived motion fields and the NCM of a receive array used in MRI. Temporal dynamics of the NCM were used as a motion surrogate for a linear correspondence motion model. The model performance was tested on five healthy volunteers with a liver as the target. The motion fields were calculated from the cineMR frames with an optical flow registration tool. RESULTS: The model estimated the liver motion with an average residual error of 2.3 mm (13% of the motion amplitude). The model formation takes 3 min and the model latency was 0.5 s in the current implementation. The limiting factor for the latency is the current update time of the NCM (0.48 s), which in principle can be reduced to 0.004 s with an alternative way to determine the NCM. CONCLUSIONS: The 2D respiratory motion of the liver can be effectively estimated with the linear motion model that uses the temporal behavior of the NCM as motion surrogate. Magn Reson Med 79:1730-1735, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

A novel adaptive needle insertion sequencing for robotic, single needle MR-guided high-dose-rate prostate brachytherapy.

MR-guided high-dose-rate (HDR) brachytherapy has gained increasing interest as a treatment for patients with localized prostate cancer because of the superior value of MRI for tumor and surrounding tissues localization. To enable needle insertion into the prostate with the patient in the MR bore, a single needle MR-compatible robotic system involving needle-by-needle dose delivery has been developed at our institution. Throughout the intervention, dose delivery may be impaired by: (1) sub-optimal needle positioning caused by e.g. needle bending, (2) intra-operative internal organ motion such as prostate rotations or swelling, or intra-procedural rectum or bladder filling. This may result in failure to reach clinical constraints. To assess the first aforementioned challenge, a recent study from our research group demonstrated that the deposited dose may be greatly improved by real-time adaptive planning with feedback on the actual needle positioning. However, the needle insertion sequence is left to the doctor and therefore, this may result in sub-optimal dose delivery. In this manuscript, a new method is proposed to determine and update automatically the needle insertion sequence. This strategy is based on the determination of the most sensitive needle track. The sensitivity of a needle track is defined as its impact on the dose distribution in case of sub-optimal positioning. A stochastic criterion is thus presented to determine each needle track sensitivity based on needle insertion simulations. To assess the proposed sequencing strategy, HDR prostate brachytherapy was simulated on 11 patients with varying number of needle insertions. Sub-optimal needle positioning was simulated at each insertion (modeled by typical random angulation errors). In 91% of the scenarios, the dose distribution improved when the needle was inserted into the most compared to the least sensitive needle track. The computation time for sequencing was less than 6 s per needle track. The proposed needle insertion sequencing can therefore assist in delivering an optimal dose in HDR prostate brachytherapy.

EVolution: an edge-based variational method for non-rigid multi-modal image registration.

Image registration is part of a large variety of medical applications including diagnosis, monitoring disease progression and/or treatment effectiveness and, more recently, therapy guidance. Such applications usually involve several imaging modalities such as ultrasound, computed tomography, positron emission tomography, x-ray or magnetic resonance imaging, either separately or combined. In the current work, we propose a non-rigid multi-modal registration method (namely EVolution: an edge-based variational method for non-rigid multi-modal image registration) that aims at maximizing edge alignment between the images being registered. The proposed algorithm requires only contrasts between physiological tissues, preferably present in both image modalities, and assumes deformable/elastic tissues. Given both is shown to be well suitable for non-rigid co-registration across different image types/contrasts (T1/T2) as well as different modalities (CT/MRI). This is achieved using a variational scheme that provides a fast algorithm with a low number of control parameters. Results obtained on an annotated CT data set were comparable to the ones provided by state-of-the-art multi-modal image registration algorithms, for all tested experimental conditions (image pre-filtering, image intensity variation, noise perturbation). Moreover, we demonstrate that, compared to existing approaches, our method possesses increased robustness to transient structures (i.e. that are only present in some of the images).

Adaptive planning strategy for high dose rate prostate brachytherapy­a simulation study on needle positioning errors.

The development of magnetic resonance (MR) guided high dose rate (HDR) brachytherapy for prostate cancer has gained increasing interest for delivering a high tumor dose safely in a single fraction. To support needle placement in the limited workspace inside the closed-bore MRI, a single-needle MR-compatible robot is currently under development at the University Medical Center Utrecht (UMCU). This robotic device taps the needle in a divergent way from a single rotation point into the prostate. With this setup, it is warranted to deliver the irradiation dose by successive insertions of the needle. Although robot-assisted needle placement is expected to be more accurate than manual template-guided insertion, needle positioning errors may occur and are likely to modify the pre-planned dose distribution.In this paper, we propose a dose plan adaptation strategy for HDR prostate brachytherapy with feedback on the needle position: a dose plan is made at the beginning of the interventional procedure and updated after each needle insertion in order to compensate for possible needle positioning errors. The introduced procedure can be used with the single needle MR-compatible robot developed at the UMCU. The proposed feedback strategy was tested by simulating complete HDR procedures with and without feedback on eight patients with different numbers of needle insertions (varying from 4 to 12). In of the cases tested, the number of clinically acceptable plans obtained at the end of the procedure was larger with feedback compared to the situation without feedback. Furthermore, the computation time of the feedback between each insertion was below 100 s which makes it eligible for intra-operative use.

An improved optical flow tracking technique for real-time MR-guided beam therapies in moving organs.

Magnetic resonance (MR) guided high intensity focused ultrasound and external beam radiotherapy interventions, which we shall refer to as beam therapies/interventions, are promising techniques for the non-invasive ablation of tumours in abdominal organs. However, therapeutic energy delivery in these areas becomes challenging due to the continuous displacement of the organs with respiration. Previous studies have addressed this problem by coupling high-framerate MR-imaging with a tracking technique based on the algorithm proposed by Horn and Schunck (H and S), which was chosen due to its fast convergence rate and highly parallelisable numerical scheme. Such characteristics were shown to be indispensable for the real-time guidance of beam therapies. In its original form, however, the algorithm is sensitive to local grey-level intensity variations not attributed to motion such as those that occur, for example, in the proximity of pulsating arteries.In this study, an improved motion estimation strategy which reduces the impact of such effects is proposed. Displacements are estimated through the minimisation of a variation of the H and S functional for which the quadratic data fidelity term was replaced with a term based on the linear L(1)norm, resulting in what we have called an L(2)-L(1) functional.The proposed method was tested in the livers and kidneys of two healthy volunteers under free-breathing conditions, on a data set comprising 3000 images equally divided between the volunteers. The results show that, compared to the existing approaches, our method demonstrates a greater robustness to local grey-level intensity variations introduced by arterial pulsations. Additionally, the computational time required by our implementation make it compatible with the work-flow of real-time MR-guided beam interventions.To the best of our knowledge this study was the first to analyse the behaviour of an L(1)-based optical flow functional in an applicative context: real-time MR-guidance of beam therapies in moving organs.

An automated optimization tool for high-dose-rate (HDR) prostate brachytherapy with divergent needle pattern.

Focal high-dose-rate (HDR) for prostate cancer has gained increasing interest as an alternative to whole gland therapy as it may contribute to the reduction of treatment related toxicity. For focal treatment, optimal needle guidance and placement is warranted. This can be achieved under MR guidance. However, MR-guided needle placement is currently not possible due to space restrictions in the closed MR bore. To overcome this problem, a MR-compatible, single-divergent needle-implant robotic device is under development at the University Medical Centre, Utrecht: placed between the legs of the patient inside the MR bore, this robot will tap the needle in a divergent pattern from a single rotation point into the tissue. This rotation point is just beneath the perineal skin to have access to the focal prostate tumor lesion. Currently, there is no treatment planning system commercially available which allows optimization of the dose distribution with such needle arrangement. The aim of this work is to develop an automatic inverse dose planning optimization tool for focal HDR prostate brachytherapy with needle insertions in a divergent configuration. A complete optimizer workflow is proposed which includes the determination of (1) the position of the center of rotation, (2) the needle angulations and (3) the dwell times. Unlike most currently used optimizers, no prior selection or adjustment of input parameters such as minimum or maximum dose or weight coefficients for treatment region and organs at risk is required. To test this optimizer, a planning study was performed on ten patients (treatment volumes ranged from 8.5 cm(3)to 23.3 cm(3)) by using 2-14 needle insertions. The total computation time of the optimizer workflow was below 20 min and a clinically acceptable plan was reached on average using only four needle insertions.

Performance analysis of a dedicated breast MR-HIFU system for tumor ablation in breast cancer patients.

MR-guided HIFU ablation is a promising technique for the non-invasive treatment of breast cancer. A phase I study was performed to assess the safety and treatment accuracy and precision of MR-HIFU ablation in breast cancer patients (n=10) using a newly developed MR-HIFU platform dedicated to applications in the breast. In this paper a technical analysis of the performance of the dedicated breast MR-HIFU system during breast tumors ablation is described. The main points of investigation were the spatial targeting accuracy and precision of the system and the performance of real-time respiration-corrected MR thermometry.The mean targeting accuracy was in the range of 2.4-2.6 mm, whereas the mean targeting precision was in the range of 1.5-1.8 mm. To correct for respiration-induced magnetic field fluctuations during MR temperature mapping a look-up-table (LUT)-based correction method was used. An optimized procedural sedation protocol in combination with the LUT-based correction method allowed for precise MR thermometry during the ablation procedure (temperature standard deviation <3 °C). No unwanted heating in the near field (i.e. skin) nor in the far field (pectoral muscle) was detected.The newly developed dedicated breast MR-HIFU system allows for safe, accurate and precise ablation of breast tumors.

[Therapies by focused ultrasound]. / Thérapies par ultrasons focalisés.

Many techniques of thermotherapy have emerged over the last several years in the field of oncology using different types of physical agents, including ultrasound. Only ultrasound can target deep seated lesions non-invasively without need for percutaneous probe insertion. Depending on their utilization, it is possible to select either thermal effects, in a continuous mode, at low temperature (allowing thermo-induced biological effects) or at high temperature (allowing thermoablation), or mechanical effects, in a pulsed mode, at low energy level (allowing biological effects) or at high energy levels (histotripsy). Thermoablation by focused ultrasound is now developing fast for applications in many organs. It gained a well defined role for the treatment of prostatic cancer and uterine leiomyoma but needs to be better evaluated in other organs such as the breast. Treatment of abdominal tumors must still be considered as experimental as long as problems related to acoustic interfaces (produced by ribs and gas) and movement correction are not resolved. Biological applications of focused ultrasound are currently being explored and have a great long term potential.

PCA-based magnetic field modeling: application for on-line MR temperature monitoring.

Magnetic Resonance (MR) temperature mapping can be used to monitor temperature changes during minimally invasive thermal therapies. However, MR-thermometry contains artefacts caused by phase errors induced by organ motion in inhomogeneous magnetic fields. This paper proposes a novel correction strategy based on a Principal Component Analysis (PCA) to estimate magnetic field perturbation assuming a linear magnetic field variation with organ displacement. The correction method described in this paper consists of two steps: a magnetic field perturbation model is computed in a learning step; subsequently, during the intervention, this model is used to reconstruct the magnetic field perturbation corresponding to the actual organ position which in turns allow computation of motion corrected thermal maps.

Magnetic resonance temperature imaging.

Continuous, real-time, 3D temperature mapping during a hyperthermic procedure may provide (i) enhanced safety by visualizing temperature maps in and around the treated region, (ii) improved efficiency by adapting local energy deposition with feedback coupling algorithms and (iii) therapy end-points based on the accumulated thermal dose. Non-invasive mapping of temperature changes can be achieved with MRI and may be based on temperature dependent MRI parameters. The excellent linearity of the temperature dependency of the proton resonance frequency (PRF) and its near-independence with respect to tissue type make the PRF-based methods the preferred choice for many applications, in particular at mid- to-high field strength (> or =0.5 T). The PRF methods employ RF-spoiled gradient echo imaging methods and incorporate fat suppression techniques for most organs. A standard deviation of less than 1 degrees C, for a temporal resolution below 1 s and a spatial resolution of approximately 2 mm is feasible for immobile tissues. Special attention is paid to methods for reducing artifacts in MR temperature mapping caused by intra-scan and inter-scan motion and motion and temperature-induced susceptibility effects in mobile tissues. Real-time image processing and visualization techniques, together with accelerated MRI acquisition techniques, are described because of their potential for therapy guidance.