Three-dimensional liver motion tracking using real-time two-dimensional MRI

Dynamic T 2 * relaxometry of hyperpolarized [1-13 C]pyruvate MRI in the human brain and kidneys

PURPOSE

This study aimed to quantifyT 2 * $$ {T}_2^{\ast } $$ for hyperpolarized [1-13 C]pyruvate and metabolites in the healthy human brain and renal cell carcinoma (RCC) patients at 3 T.

METHODS

DynamicT 2 * $$ {T}_2^{\ast } $$ values were measured with a metabolite-specific multi-echo spiral sequence. The dynamicT 2 * $$ {T}_2^{\ast } $$ of [1-13 C]pyruvate, [1-13 C]lactate, and 13 C-bicarbonate was estimated in regions of interest in the whole brain, sinus vein, gray matter, and white matter in healthy volunteers, as well as in kidney tumors and the contralateral healthy kidneys in a separate group of RCC patients.T 2 * $$ {T}_2^{\ast } $$ was fit using a mono-exponential function; and metabolism was quantified using pyruvate-to-lactate conversion rate maps and lactate-to-pyruvate ratio maps, which were compared with and without an estimatedT 2 * $$ {T}_2^{\ast } $$ correction.

RESULTS

TheT 2 * $$ {T}_2^{\ast } $$ of pyruvate was shown to vary during the acquisition, whereas theT 2 * $$ {T}_2^{\ast } $$ of lactate and bicarbonate were relatively constant through time and across the organs studied. TheT 2 * $$ {T}_2^{\ast } $$ of lactate was similar in gray matter (29.75 ± 1.04 ms), white matter (32.89 ± 0.9 ms), healthy kidney (34.61 ± 4.07 ms), and kidney tumor (33.01 ± 2.31 ms); and theT 2 * $$ {T}_2^{\ast } $$ of bicarbonate was different between whole-brain (108.17 ± 14.05 ms) and healthy kidney (58.45 ± 6.63 ms). TheT 2 * $$ {T}_2^{\ast } $$ of pyruvate had similar trends in both brain and RCC studies, reducing from 75.56 ± 2.23 ms to 22.24 ± 1.24 ms in the brain and reducing from 122.72 ± 9.86 ms to 57.38 ± 7.65 ms in the kidneys.

CONCLUSION

Multi-echo dynamic imaging can quantifyT 2 * $$ {T}_2^{\ast } $$ and metabolism in a single integrated acquisition. Clear differences were observed in theT 2 * $$ {T}_2^{\ast } $$ of metabolites and in their behavior throughout the timecourse.

Intraoperative liver deformation and organ motion caused by ventilation, laparotomy, and pneumoperitoneum in a porcine model for image-guided liver surgery

BACKGROUND

Image-guidance promises to make complex situations in liver interventions safer. Clinical success is limited by intraoperative organ motion due to ventilation and surgical manipulation. The aim was to assess influence of different ventilatory and operative states on liver motion in an experimental model.

METHODS

Liver motion due to ventilation (expiration, middle, and full inspiration) and operative state (native, laparotomy, and pneumoperitoneum) was assessed in a live porcine model (n = 10). Computed tomography (CT)-scans were taken for each pig for each possible combination of factors. Liver motion was measured by the vectors between predefined landmarks along the hepatic vein tree between CT scans after image segmentation.

RESULTS

Liver position changed significantly with ventilation. Peripheral regions of the liver showed significantly higher motion (maximal Euclidean motion 17.9 ± 2.7 mm) than central regions (maximal Euclidean motion 12.6 ± 2.1 mm, p < 0.001) across all operative states. The total average motion measured 11.6 ± 0.7 mm (p < 0.001). Between the operative states, the position of the liver changed the most from native state to pneumoperitoneum (14.6 ± 0.9 mm, p < 0.001). From native state to laparotomy comparatively, the displacement averaged 9.8 ± 1.2 mm (p < 0.001). With pneumoperitoneum, the breath-dependent liver motion was significantly reduced when compared to other modalities. Liver motion due to ventilation was 7.7 ± 0.6 mm during pneumoperitoneum, 13.9 ± 1.1 mm with laparotomy, and 13.5 ± 1.4 mm in the native state (p < 0.001 in all cases).

CONCLUSIONS

Ventilation and application of pneumoperitoneum caused significant changes in liver position. Liver motion was reduced but clearly measurable during pneumoperitoneum. Intraoperative guidance/navigation systems should therefore account for ventilation and intraoperative changes of liver position and peripheral deformation.

Online prediction for respiratory movement compensation: a patient-specific gating control for MRI-guided radiotherapy

BACKGROUND

This study aims to validate the effectiveness of linear regression for motion prediction of internal organs or tumors on 2D cine-MR and to present an online gating signal prediction scheme that can improve the accuracy of MR-guided radiotherapy for liver and lung cancer.

MATERIALS AND METHODS

We collected 2D cine-MR sequences of 21 liver cancer patients and 10 lung cancer patients to develop a binary gating signal prediction algorithm that forecasts the crossing-time of tumor motion traces relative to the target threshold. Both 0.4 s and 0.6 s prediction windows were tested using three linear predictors and three recurrent neural networks (RNNs), given the system delay of 0.5 s. Furthermore, an adaptive linear regression model was evaluated using only the first 30 s as the burn-in period, during which the model parameters were adapted during the online prediction process. The accuracy of the predicted traces was measured using amplitude metrics (MAE, RMSE, and R2), and in addition, we proposed three temporal metrics, namely crossing error, gating error, and gating accuracy, which are more relevant to the nature of the gating signals.

RESULTS

In both 0.6 s and 0.4 s prediction cases, linear regression outperformed other methods, demonstrating significantly smaller amplitude errors compared to the RNNs (P < 0.05). The proposed algorithm with adaptive linear regression had the best performance with an average gating accuracy of 98.3% and 98.0%, a gating error of 44 ms and 45 ms, for liver cancer and lung cancer patients, respectively.

CONCLUSION

A functional online gating control scheme was developed with an adaptive linear regression that is both more cost-efficient and accurate than sophisticated RNN based methods in all studied metrics.

Design of a Patient-Specific Respiratory-Motion-Simulating Platform for In Vitro 4D Flow MRI

Four-dimensional (4D) flow magnetic resonance imaging (MRI) is a leading-edge imaging technique and has numerous medicinal applications. In vitro 4D flow MRI can offer some advantages over in vivo ones, especially in accurately controlling flow rate (gold standard), removing patient and user-specific variations, and minimizing animal testing. Here, a complete testing method and a respiratory-motion-simulating platform are proposed for in vitro validation of 4D flow MRI. A silicon phantom based on the hepatic arteries of a living pig is made. Under the free-breathing, a human volunteer's liver motion (inferior-superior direction) is tracked using a pencil-beam MRI navigator and is extracted and converted into velocity-distance pairs to program the respiratory-motion-simulating platform. With the magnitude displacement of about 1.3 cm, the difference between the motions obtained from the volunteer and our platform is ≤ 1 mm which is within the positioning error of the MRI navigator. The influence of the platform on the MRI signal-to-noise ratio can be eliminated even if the actuator is placed in the MRI room. The 4D flow measurement errors are respectively 0.4% (stationary phantom), 9.4% (gating window = 3 mm), 27.3% (gating window = 4 mm) and 33.1% (gating window = 7 mm). The vessel resolutions decreased with the increase of the gating window. The low-cost simulation system, assembled from commercially available components, is easy to be duplicated.

Atrial fibrillation cardiac radioablation target visibility on magnetic resonance imaging

Magnetic resonance imaging (MRI) guided cardiac radioablation (CR) for atrial fibrillation (AF) is a promising treatment concept. However, the visibility of AF CR targets on MRI acquisitions requires further exploration and MRI sequence and parameter optimization has not yet been performed for this application. This pilot study explores the feasibility of MRI-guided tracking of AF CR targets by evaluating AF CR target visualization on human participants using a selection of 3D and 2D MRI sequences.MRI datasets were acquired in healthy and AF participants using a range of MRI sequences and parameters. MRI acquisition categories included 3D free-breathing acquisitions (3D_acq), 2D breath-hold ECG-gated acquisitions (2D_ECG-gated), stacks of 2D breath-hold ECG-gated acquisitions which were retrospectively interpolated to 3D datasets (3D_interp), and 2D breath-hold ungated acquisitions (2D_real-time). The ease of target delineation and the presence of artifacts were qualitatively analyzed. Image quality was quantitatively analyzed using signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and non-uniformity. Confident 3D target delineation was achievable on all 3D_interp datasets but was not possible on any of the 3D_acq datasets. Fewer artifacts and significantly better SNR, CNR and non-uniformity metrics were observed with 3D_interp compared to 3D_acq. 2D_real-time datasets had slightly lower SNR and CNR than 2D_ECG-gated and 3D_{interp n} datasets. AF CR target visualization on MRI was qualitatively and quantitatively evaluated. The study findings indicate that AF CR target visualization is achievable despite the imaging challenges associated with these targets, warranting further investigation into MRI-guided AF CR treatments.

Real-Time Non-Rigid 3D Respiratory Motion Estimation for MR-Guided Radiotherapy Using MR-MOTUS

The MR-Linac is a combination of an MR-scanner and radiotherapy linear accelerator (Linac) which holds the promise to increase the precision of radiotherapy treatments with MR-guided radiotherapy by monitoring motion during radiotherapy with MRI, and adjusting the radiotherapy plan accordingly. Optimal MR-guidance for respiratory motion during radiotherapy requires MR-based 3D motion estimation with a latency of 200-500 ms. Currently this is still challenging since typical methods rely on MR-images, and are therefore limited by the 3D MR-imaging latency. In this work, we present a method to perform non-rigid 3D respiratory motion estimation with 170 ms latency, including both acquisition and reconstruction. The proposed method called real-time low-rank MR-MOTUS reconstructs motion-fields directly from k -space data, and leverages an explicit low-rank decomposition of motion-fields to split the large scale 3D+t motion-field reconstruction problem posed in our previous work into two parts: (I) a medium-scale offline preparation phase and (II) a small-scale online inference phase which exploits the results of the offline phase for real-time computations. The method was validated on free-breathing data of five volunteers, acquired with a 1.5T Elekta Unity MR-Linac. Results show that the reconstructed 3D motion-field are anatomically plausible, highly correlated with a self-navigation motion surrogate ( R=0.975 ±0.0110 ), and can be reconstructed with a total latency of 170 ms that is sufficient for real-time MR-guided abdominal radiotherapy.

MRI-guided cardiac-induced target motion tracking for atrial fibrillation cardiac radioablation

BACKGROUND AND PURPOSE

Atrial fibrillation (AF) cardiac radioablation (CR) challenges radiotherapy tracking: multiple small targets close to organs-at-risk undergo rapid differential cardiac contraction and respiratory motion. MR-guidance offers a real-time target tracking solution. This work develops and investigates MRI-guided tracking of AF CR targets with cardiac-induced motion.

MATERIALS AND METHODS

A direct tracking method (Tracking_direct) and two indirect tracking methods leveraging population-based surrogacy relationships with the left atria (Tracking_{indirect_LA}) or other target (Tracking_{indirect_target}) were developed. Tracking performance was evaluated using transverse ECG-gated breathhold MRI images from 15 healthy and 10 AF participants. Geometric and volumetric tracking errors were calculated, defined as the difference between the ground-truth and tracked target centroids and volumes respectively. Transverse, breath-hold, noncardiac-gated cine images were acquired at 4 Hz in 5 healthy and 5 AF participants to qualitatively characterize tracking performance on images more comparable to MRILinac acquisitions.

RESULTS

The average 3D geometric tracking errors for Tracking_direct, Tracking_{indirect_LA} and Tracking_{indirect_target} respectively were 1.7 ± 1.2 mm, 1.6 ± 1.1 mm and 1.9 ± 1.3 mm in healthy participants and 1.7 ± 1.3 mm, 1.5 ± 1.0 mm and 1.7 ± 1.2 mm in AF participants. For Tracking_direct, 88% of analyzed images had 3D geometric tracking errors <3 mm and the average volume tracking error was 1.7 ± 1.3 cc. For Tracking_direct on non-cardiac-gated cine images, tracked targets overlapped organsat-risk or completely missed the target area on 2.2% and 0.08% of the images respectively.

CONCLUSION

The feasibility of non-invasive MRI-guided tracking of cardiac-induced AF CR target motion was demonstrated for the first time, showing potential for improving AF CR treatment efficacy.

Time domain principal component analysis for rapid, real-time 2D MRI reconstruction from undersampled data

PURPOSE

A rapid real-time 2D accelerated method was developed for magnetic resonance imaging (MRI) using principal component analysis (PCA) in the temporal domain. This method employs a moving window of previous dynamic frames to reconstruct the current, real-time frame within this window. This technique could be particularly useful in real-time tracking applications such as in MR-guided radiotherapy, where low latency real-time reconstructions are essential.

METHODS

The method was tested retrospectively on 15 fully-sampled data sets of lung patient data acquired on a 3T Philips Achieva system. High frequency data are incoherently undersampled, while the central low-frequency data are always acquired to characterize the temporal fluctuations through PCA. The undersampling pattern is derived in such a way that all of k-space is acquired within a pre-determined number of frames. The missing data in the current frame are then filled in by fitting the temporal characterizations to the acquired undersampled data, using a pre-determined number of PCs. A subset of six patients was used to test the contour ability of the images. Various accelerations between 3x and 8x were tested along with the optimal number of PCs for fitting. A comparison was also performed with previous work from our group proposed by Dietz et al. as well as with a standard low resolution acquisition. In order to determine how the method would perform at lower signal to noise ratio (SNR), noise levels of 2×, 4×, and 6× were added to the 3T data. Metrics such as normalised mean square error and Dice coefficient were used to measure the reconstruction image quality and contour ability.

RESULTS

The proposed method demonstrated good temporal robustness as consistent metrics were detected for the duration of the imaging session. It was found that the optimal number of PCs for temporal fitting was dependent on the acceleration rate. For the data tested, five PCs were found to be optimal at the acceleration rates of 3× and 4×. This number decreases to three at accelerations of 5× and 6× and further decreases to two at an acceleration rate of 8×, likely due to greater instability with fewer acquired data points. The use of too many PCs for fitting increased the chances of noisy reconstruction which affected contourability.

CONCLUSIONS

The proposed 2D real-time MR acceleration method demonstrated greater robustness in the metrics over time when compared with previous real-time PCA methods using metrics such as normalised mean squared error, peak SNR and structural similarity up to an acceleration of 8x. Improved temporal robustness of image structure contourability and accurate definition was also demonstrated using several metrics including the Dice coefficient. Reconstruction of raw acquired data can be performed at approximately 50 ms per frame using an Intel core i5 CPU. The method has the advantage of being very flexible in terms of hardware requirements as it can operate successfully on a single coil channel and does not require specialized computing power to implement in real-time.

Stability of conventional and machine learning-based tumor auto-segmentation techniques using undersampled dynamic radial bSSFP acquisitions on a 0.35 T hybrid MR-linac system

PURPOSE

Hybrid MRI-linear accelerator systems (MR-linacs) allow for the incorporation of MR images with high soft-tissue contrast into the radiation therapy procedure prior to, during, or post irradiation. This allows not only for the optimization of the treatment planning, but also for real-time monitoring of the tumor position using cine MRI, from which intrafractional motion can be compensated. Fast imaging and accurate tumor tracking are crucial for effective compensation. This study investigates the application of cine MRI with a radial acquisition scheme on a low-field MR-linac to accelerate the acquisition rate and evaluates the effect on tracking accuracy.

METHODS

An MR sequence using tiny golden-angle radial k-space sampling was developed and applied to cine imaging on patients with liver tumors on a 0.35 T MR-linac. Tumor tracking was assessed for accuracy and stability from the cine images with increasing k-space undersampling factors. Tracking was achieved using two different auto-segmentation algorithms: a deformable image registration B-spline similar to that implemented on the MR-linac and a convolutional neural network approach known as U-Net.

RESULTS

Radial imaging allows for increased temporal resolution with reliable tumor tracking, although tracking robustness decreases as temporal resolution increases. Additional acquisition-based artifacts can be avoided by reducing the angle increment using tiny golden-angles. The U-net algorithm was found to have superior auto-segmentation metrics compared to B-spline. U-net was able to track two well-defined tumors, imaged with just 30 spokes per image (10.6 frames per second), with an average Dice coefficient ≥ 83%, Hausdorff distance ≤ 1.4 pixel, and mean contour distance ≤ 0.5 pixel.

CONCLUSIONS

Radial acquisitions are commonplace in dynamic imaging; however, in MR-guided radiotherapy, robust tumor tracking is also required. This study demonstrates the in vivo feasibility of tumor tracking from radially acquired images on a low-field MR-linac. Radial imaging allows for decreased image acquisition times while maintaining robust tracking. The U-net algorithm can track a tumor with higher accuracy in images with undersampling artifacts than a conventional deformable B-spline algorithm and is a promising tool for tracking in MR-guided radiation therapy.

Effects of Gadolinium MRI Contrast Agents on DNA Damage and Cell Survival when Used in Combination with Radiation

Gadolinium is a commonly used contrast agent for magnetic resonance imaging (MRI). The goal of this work was to determine how MRI contrast agents affect radiosensitivity for tumour cells. Using a 225kVp X-ray cabinet source, immunofluorescence and clonogenic assays were performed on six cancer cell lines: lung (H460), pancreas (MiaPaCa2), prostate (DU145), breast (MCF7), brain (U87) and liver (HEPG2). Dotarem® contrast agent, at concentrations of 0.2, 2 and 20 mM, was used to determine its effect on DNA damage and cell survival. Measurements were performed using inductively coupled plasma mass spectrometry (ICP-MS) to determine the amount of gadolinium taken up by each cell line for each concentration. A statistically significant increase in DNA damage was seen for all cell lines at a dose of 1 Gy for concentrations of 2 and 20 mM, at 1 h postirradiation. At 24 h postirradiation, most of the DNA damage had been repaired, with approximately 90% repair for almost all doses of radiation and concentrations of Dotarem. Clonogenic results showed no statistically significant decrease in cell survival for any cell line or concentration. Uptake measurements showed cell line-specific variations in uptake, with MCF7 and HEPG2 cells having a high percentage uptake compared to other cell lines, with 151.4 ± 0.3 × 10-15 g and 194.8 ± 0.4 × 10-15 g per cell, respectively, at 2 mM Dotarem concentration. In this work, a variability in gadolinium uptake was observed between cell lines. A significant increase was seen in initial levels of DNA damage after 1 Gy irradiation for all six cancer cell lines; however, no significant decrease in cell survival was seen with the clonogenic assay. The observation of high levels of repair suggest that while initial levels of DNA damage are increased, this damage is almost entirely repaired within 24 h, and does not affect the ability of cells to survive and produce colonies.

Nonrigid 3D motion estimation at high temporal resolution from prospectively undersampled k-space data using low-rank MR-MOTUS

Purpose

With the recent introduction of the MR‐LINAC, an MR‐scanner combined with a radiotherapy LINAC, MR‐based motion estimation has become of increasing interest to (retrospectively) characterize tumor and organs‐at‐risk motion during radiotherapy. To this extent, we introduce low‐rank MR‐MOTUS, a framework to retrospectively reconstruct time‐resolved nonrigid 3D+t motion fields from a single low‐resolution reference image and prospectively undersampled k‐space data acquired during motion.

Theory

Low‐rank MR‐MOTUS exploits spatiotemporal correlations in internal body motion with a low‐rank motion model, and inverts a signal model that relates motion fields directly to a reference image and k‐space data. The low‐rank model reduces the degrees‐of‐freedom, memory consumption, and reconstruction times by assuming a factorization of space‐time motion fields in spatial and temporal components.

Methods

Low‐rank MR‐MOTUS was employed to estimate motion in 2D/3D abdominothoracic scans and 3D head scans. Data were acquired using golden‐ratio radial readouts. Reconstructed 2D and 3D respiratory motion fields were, respectively, validated against time‐resolved and respiratory‐resolved image reconstructions, and the head motion against static image reconstructions from fully sampled data acquired right before and right after the motion.

Results

Results show that 2D+t respiratory motion can be estimated retrospectively at 40.8 motion fields per second, 3D+t respiratory motion at 7.6 motion fields per second and 3D+t head‐neck motion at 9.3 motion fields per second. The validations show good consistency with image reconstructions.

Conclusions

The proposed framework can estimate time‐resolved nonrigid 3D motion fields, which allows to characterize drifts and intra and inter‐cycle patterns in breathing motion during radiotherapy, and could form the basis for real‐time MR‐guided radiotherapy.

Continuous real time 3D motion reproduction using dynamic MRI and precomputed 4DCT deformation fields

Radiotherapy of mobile tumors requires specific imaging tools and models to reduce the impact of motion on the treatment. Online continuous nonionizing imaging has become possible with the recent development of magnetic resonance imaging devices combined with linear accelerators. This opens the way to new guided treatment methods based on the real-time tracking of anatomical motion. In such devices, 2D fast MR-images are well-suited to capture and predict the real-time motion of the tumor. To be used effectively in an adaptive radiotherapy, these MR images have to be combined with X-ray images such as CT, which are necessary to compute the irradiation dose deposition. We therefore developed a method combining both image modalities to track the motion on MR images and reproduce the tracked motion on a sequence of 3DCT images in real-time. It uses manually placed navigators to track organ interfaces in the image, making it possible to select anatomical object borders that are visible on both MRI and CT modalities and giving the operator precise control of the motion tracking quality. Precomputed deformation fields extracted from the 4DCT acquired in the planning phase are then used to deform existing 3DCT images to match the tracked object position, creating a new set of 3DCT images encompassing irregularities in the breathing pattern for the complete duration of the MRI acquisition. The final continuous reconstructed 4DCT image sequence reproduces the motion captured by the MRI sequence with high precision (difference below 2 mm).

Organ motion quantification and margins evaluation in carbon ion therapy of abdominal lesions

PURPOSE

In image-guided particle radiotherapy of abdominal lesions, respiratory motion hinders treatment accuracy. In this study, 2D cineMRI data were used to quantify the tumor (GTV) motion and to evaluate the clinical approach based on deriving an internal target volume (ITV) from a planning 4DCT for gating treatments.

METHODS

Seven patients with abdominal lesions were treated with carbon-ion therapy at the National Centre of Oncological Hadron-therapy (Italy). The MR scan was performed on the same day of the 4DCT acquisition. For four patients, an additional MR was acquired approximately after 1 week. The cineMRI combined with deformable image registration algorithm was used to quantify tumor motion. Afterwards, two ITVs were defined considering (1) all phases (ITVFB) and (2) only phases within the gating window (ITVG), and then compared with the clinical (4DCT-derived) ITVs (ITVCG and ITVCFB).

RESULTS

Tumor residual motion estimated by cineMRI data in the two MRI sessions resulted not significantly different from 4DCT, although cineMRI accounted for cycle-to-cycle variations. The ITV normalized for the GTV median values were higher for ITVFB with respect to ITVG, ITVCFB and ITVCG. The Hausdorff distances with respect to the GTV were up to 10.55 mm, 3.13 mm, 5.56 mm and 2.51 mm, for ITVFB, ITVG, ITVCFB and ITVCG, respectively. According to both metrics, ITVCG and ITVG were not found significantly different.

CONCLUSIONS

CineMRI acquisitions allowed to quantify organ motion without delivering additional dose to the patient and to verify treatment margins in gated carbon-ion therapy of abdominal lesions.

Magnetic resonance-guided radiation therapy: A review

Magnetic resonance-guided radiation therapy (MRgRT) is a promising approach to improving clinical outcomes for patients treated with radiation therapy. The roles of image guidance, adaptive planning and magnetic resonance imaging in radiation therapy have been increasing over the last two decades. Technical advances have led to the feasible combination of magnetic resonance imaging and radiation therapy technologies, leading to improved soft-tissue visualisation, assessment of inter- and intrafraction motion, motion management, online adaptive radiation therapy and the incorporation of functional information into treatment. MRgRT can potentially transform radiation oncology by improving tumour control and quality of life after radiation therapy and increasing convenience of treatment by shortening treatment courses for patients. Multiple groups have developed clinical implementations of MRgRT predominantly in the abdomen and pelvis, with patients having been treated since 2014. While studies of MRgRT have primarily been dosimetric so far, an increasing number of trials are underway examining the potential clinical benefits of MRgRT, with coordinated efforts to rigorously evaluate the benefits of the promising technology. This review discusses the current implementations, studies, potential benefits and challenges of MRgRT.

MR-MOTUS: model-based non-rigid motion estimation for MR-guided radiotherapy using a reference image and minimal k-space data

Time-resolved motion estimation from MRI data has received an increasing amount of interest due to the advent of the MR-Linac. The combination of an MRI scanner and a linear accelerator enables radiation plan adaptation based on internal organ motion estimated from MRI data. However, time-resolved estimation of this motion from MRI data still remains a challenge. In light of this application, we propose MR-MOTUS, a framework to estimate non-rigid 3D motion from minimal k-space data. MR-MOTUS consists of two main components: (1) a signal model that explicitly relates the k-space signal of a deforming object to non-rigid motion-fields and a reference image, and (2) model-based reconstructions of the non-rigid motion-fields directly from k-space data. Using an a priori available reference image and the fact that internal body motion exhibits a high level of spatial correlation, we represent the motion-fields in a low-dimensional space and reconstruct them from minimal k-space data that can be acquired very rapidly. The signal model is validated through numerical experiments with a digital 3D phantom and motion-fields are reconstructed from retrospectively undersampled in vivo head and abdomen data using various undersampling strategies. A comparison is made with state-of-the-art image registration performed on images reconstructed from the same undersampled data. Results show that MR-MOTUS reconstructs in vivo 3D rigid head motion from 474-fold retrospectively downsampled k-space data, and in vivo non-rigid 3D respiratory motion from 63-fold retrospectively undersampled k-space data. Preliminary results on prospectively undersampled data acquired with a 2D golden angle acquisition during free-breathing demonstrate the practical feasibility of the method.

An image regression motion prediction technique for MRI-guided radiotherapy evaluated in single-plane cine imaging

PURPOSE

To develop and evaluate a novel motion prediction method for magnetic resonance image (MRI)-guided radiotherapy applications. This method, which we deem "image regression," predicts future tissue motion based on a weighted combination of previously observed motion states. Motion predictions are derived from a sliding window of recent motion states which are defined by a temporal sequence of images. A key advantage of this method compared to other motion prediction methods is that its computational complexity scales weekly with the number of spatial points predicted. Applications of gating latency reduction and improvement in deformable registration-based target tracking are demonstrated.

METHODS

The image regression (IR) motion prediction method was developed and evaluated using 26.9 h of real-time imaging acquired from eight healthy volunteers and 13 patients using a 0.35 T MRI-guided radiotherapy system. Motion predictions were performed 0.25-0.33 s into the future using a weighted sum of previously observed motion states with image similarity-derived weights. The set of previously observed motion states were continuously updated to incorporate the changes in breathing patterns. The accuracy of the predicted radiotherapy gating decision, beam-on positive predictive value (PPV), and predicted vs ground-truth target centroid position errors are reported. The IR technique was compared against no prediction, linear extrapolation, and an established autoregressive linear prediction algorithm. The usage of IR to initialize the deformable registration and enhance the target tracking was demonstrated in the healthy volunteer studies. Deformable registration with IR initialization was compared to the initialization performed by current clinical software: no initialization, previous image registration initialization and linear motion extrapolation initialization.

RESULTS

The average IR-predicted radiation beam gating decision accuracy was 95.8%, with a PPV of 95.7%, and median and 95th percentile centroid position errors of 0.63 and 2.08 mm, respectively. Compared to the autoregressive linear prediction method, gating accuracy was 1.15% greater, PPV was 1.61% greater, and median and 95th percentile centroid distances were 0.21 and 0.23 mm smaller. The IR-initialized registration on average converged within 0.50 mm of the ground-truth position in fewer than 10 iterations whereas the next best initialization method required more than 25 iterations.

CONCLUSIONS

Image regression motion prediction has the potential to reduce the gating latencies and improve the speed and accuracy of deformable registration-based target tracking in MRI-guided radiotherapy.

Time-resolved volumetric MRI in MRI-guided radiotherapy: an in silico comparative analysis

MRI-treatment units enable 2D cine-MRI centred in the tumour for motion detection in radiotherapy, but they lack 3D information due to spatio-temporal limits. To derive time-resolved 3D information, different approaches have been proposed in the literature, but a rigorous comparison among these strategies has not yet been performed. The goal of this study is to quantitatively investigate five published strategies that derive time-resolved volumetric MRI in MRI-guided radiotherapy: Propagation, out-of-plane motion compensation, Fayad model, ROI-based model and Stemkens model. Comparisons were performed using an MRI digital phantom generated with six different patient-derived motion signals and tumour-shapes. An average 4D cycle was generated as well as 2D cine-MRI data with corresponding 3D in-room ground truth. Quantitative analysis was performed by comparing the estimated 3D volume to the ground truth available for each 2D cine-MRI sample. A grouped patient statistical analysis was performed to evaluate the performance of the selected methods, in case of tumour tracking or motion estimation of the whole anatomy. Analyses were also performed based on patient characteristics. Quantitative ranking of the investigated methods highlighted that Propagation and ROI-based model strategies achieved an overall median tumour centre of mass 3D distance from the ground truth of 1.1 mm and 1.3 mm, respectively, and a diaphragm distance below 1.6 mm. Higher errors and variabilities were instead obtained for other methods, which lack the ability to compensate for in-room variations and to account for regional changes. These results were especially evident when further analysing patient characteristics, where errors above 2 mm/5 mm in tumour/diaphragm were found for more irregular breathing patterns in case of out-of-plane motion compensation, Fayad and Stemkens models. These findings suggest the potential of the proposed in silico framework to develop and compare strategies to estimate time-resolved 3DMRI in MRI-guided radiotherapy.

2D ultrasound imaging based intra-fraction respiratory motion tracking for abdominal radiation therapy using machine learning

We have previously developed a robotic ultrasound imaging system for motion monitoring in abdominal radiation therapy. Owing to the slow speed of ultrasound image processing, our previous system could only track abdominal motions under breath-hold. To overcome this limitation, a novel 2D-based image processing method for tracking intra-fraction respiratory motion is proposed. Fifty-seven different anatomical features acquired from 27 sets of 2D ultrasound sequences were used in this study. Three 2D ultrasound sequences were acquired with the robotic ultrasound system from three healthy volunteers. The remaining datasets were provided by the 2015 MICCAI Challenge on Liver Ultrasound Tracking. All datasets were preprocessed to extract the feature point, and a patient-specific motion pattern was extracted by principal component analysis and slow feature analysis (SFA). The tracking finds the most similar frame (or indexed frame) by a k-dimensional-tree-based nearest neighbor search for estimating the tracked object location. A template image was updated dynamically through the indexed frame to perform a fast template matching (TM) within a learned smaller search region on the incoming frame. The mean tracking error between manually annotated landmarks and the location extracted from the indexed training frame is 1.80  ±  1.42 mm. Adding a fast TM procedure within a small search region reduces the mean tracking error to 1.14  ±  1.16 mm. The tracking time per frame is 15 ms, which is well below the frame acquisition time. Furthermore, the anatomical reproducibility was measured by analyzing the location's anatomical landmark relative to the probe; the position-controlled probe has better reproducibility and yields a smaller mean error across all three volunteer cases, compared to the force-controlled probe (2.69 versus 11.20 mm in the superior-inferior direction and 1.19 versus 8.21 mm in the anterior-posterior direction). Our method reduces the processing time for tracking respiratory motion significantly, which can reduce the delivery uncertainty.

Beyond T2 and 3T: New MRI techniques for clinicians

Technological advances in Magnetic Resonance Imaging (MRI) in terms of field strength and hybrid MR systems have led to improvements in tumor imaging in terms of anatomy and functionality. This review paper discusses the applications of such advances in the field of radiation oncology with regards to treatment planning, therapy guidance and monitoring tumor response and predicting outcome.

Real-time intrafraction motion monitoring in external beam radiotherapy

Radiotherapy (RT) aims to deliver a spatially conformal dose of radiation to tumours while maximizing the dose sparing to healthy tissues. However, the internal patient anatomy is constantly moving due to respiratory, cardiac, gastrointestinal and urinary activity. The long term goal of the RT community to 'see what we treat, as we treat' and to act on this information instantaneously has resulted in rapid technological innovation. Specialized treatment machines, such as robotic or gimbal-steered linear accelerators (linac) with in-room imaging suites, have been developed specifically for real-time treatment adaptation. Additional equipment, such as stereoscopic kilovoltage (kV) imaging, ultrasound transducers and electromagnetic transponders, has been developed for intrafraction motion monitoring on conventional linacs. Magnetic resonance imaging (MRI) has been integrated with cobalt treatment units and more recently with linacs. In addition to hardware innovation, software development has played a substantial role in the development of motion monitoring methods based on respiratory motion surrogates and planar kV or Megavoltage (MV) imaging that is available on standard equipped linacs. In this paper, we review and compare the different intrafraction motion monitoring methods proposed in the literature and demonstrated in real-time on clinical data as well as their possible future developments. We then discuss general considerations on validation and quality assurance for clinical implementation. Besides photon RT, particle therapy is increasingly used to treat moving targets. However, transferring motion monitoring technologies from linacs to particle beam lines presents substantial challenges. Lessons learned from the implementation of real-time intrafraction monitoring for photon RT will be used as a basis to discuss the implementation of these methods for particle RT.

A planning strategy for combined motion-assisted/gated MR guided focused ultrasound treatment of the pancreas

Objective: To develop and evaluate a combined motion-assisted/gated MRHIFU heating strategy designed to accelerate the treatment procedure by reducing the required number of sonications to ablate a target volume in the pancreas. Methods: A planning method for combined motion-assisted/gated MRHIFU using 4D-MRI and motion characterization is introduced. Six healthy volunteers underwent 4D-MRI for target motion characterization on a 3.0-T clinical scanner. Using displacement patterns, simulations were performed for all volunteers for three sonication approaches: gated, combined motion-assisted/gated, and static. The number of sonications needed to ablate the pancreas head was compared. The influence of displacement amplitude and target volume size was investigated. Spherical target volumes (8, 15, 20 and 34 mL) and displacement amplitudes ranging from 5 to 25 mm were evaluated. For this case, the number of sonications required to ablate the whole target was determined. Results: The number of required sonications was lowest for a static target, 62 on average (range 49-78). The gated approach required most sonications, 126 (range 97-159). The combined approach was almost as efficient as the hypothetical static case, with an average of 78 (range 53-123). Simulations showed that with a 5-mm displacement amplitude, the target could be treated by making use of motion-assisted MRHIFU sonications only. In that case, this approach allowed the lowest number of sonication, while for 10 mm and above, the number of required sonications increased. Conclusion: The use of a combined motion-assisted/gated MRHIFU strategy may accelerate tumor ablation in the pancreas when respiratory-induced displacement amplitudes are between 5 and 10 mm.

A fast volumetric 4D-MRI with sub-second frame rate for abdominal motion monitoring and characterization in MRI-guided radiotherapy

Background

To propose a fast volumetric 4D-MRI based on 3D pulse sequence acquisition for abdominal motion monitoring and characterization in MRI-guided radiotherapy (MRgRT).

Methods

A 3D spoiled gradient echo sequence volumetric interpolated breath-hold examination (VIBE) [repetition time/echo time (TR/TE) =0.53/1.57 ms, flip-angle =5°, receiver bandwidth (RBW) =1,400 Hz/voxel] based 4D-MRI acquisition, accelerated by 4-fold controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA), named CAIPIRINHA-VIBE 4D-MRI, was implemented on a 1.5T MRI simulator (MR-sim) and applied for abdominal imaging of nine healthy volunteers under free breathing. One hundred and forty-four dynamics of the entire abdomen volume (56 slices), in total 8,064 (144×56) images with a voxel size of 2.7×2.7×4.0 mm³, were acquired in 89 s for 4D-MRI. This CAIPIRINHA-VIBE 4D-MRI was qualitatively compared with a 2D half-Fourier acquisition single-shot turbo spin-echo (2D-HASTE) based 4D-MRI. The motions of liver dome, kidney and spleen were analyzed using the CAIPIRINHA-VIBE 4D-MRI data. The kidney motion was quantitatively characterized in terms of motion range and the correlations between left and right kidneys.

Results

CAIPIRINHA-VIBE 4D-MRI was successfully conducted in all subjects. CAIPIRINHA-VIBE 4D-MRI exhibited much higher effective volumetric temporal resolution (0.615 vs. ~5 s/volume) and better reconstructed volume consistency than 2D-HASTE 4D-MRI. CAIPIRINHA-VIBE 4D-MRI was able to characterize the respiratory motion of abdominal organs simultaneously in three orthogonal directions, and could potentially be used for whole abdomen deformable motion tracking. Renal motion range was most pronounced in superior-inferior (SI) direction (L: 10.03±2.65 mm; R: 10.38±2.80 mm), significantly larger (P<0.001) than that in anterior-posterior (AP) and the least in left-right (LR) directions. Right kidney had significantly larger mobility (4.18±2.19 vs. 2.32±1.34 mm, P=0.045) than left kidney in AP, but not in LR and SI directions. The Pearson correlation coefficients r between left and right kidney motion were 0.5063 (P=0.164), 0.6624 (P=0.052) and 0.5752 (P=0.105) in LR, AP and SI correspondingly. The correlation of renal motion in SI and AP was found significant in right kidney (r=0.843, P=0.004) but not in left kidney (r=0.467, P=0.205).

Conclusions

A fast volumetric 4D-MRI was implemented for abdominal motion monitoring in MRgRT. A sub-second volumetric temporal resolution of 0.615 s, covering the entire abdomen, was demonstrated for respiratory motion monitoring and characterization. This technique holds potentials for MRgRT applications.

3D nonrigid motion correction for quantitative assessment of hepatic lesions in DCE-MRI

Purpose

To provide nonrigid respiratory motion‐corrected DCE‐MRI images with isotropic resolution of 1.5 mm, full coverage of abdomen, and covering the entire uptake curve with a temporal resolution of 6 seconds, for the quantitative assessment of hepatic lesions.

Methods

3D DCE‐MRI data were acquired at 3 T during free breathing for 5 minutes using a 3D T₁‐weighted golden‐angle radial phase‐encoding sequence. Nonrigid respiratory motion information was extracted and used in motion‐corrected image reconstruction to obtain high‐quality DCE‐MRI images with temporal resolution of 6 seconds and isotropic resolution of 1.5 mm. An extended Tofts model was fitted to the dynamic data sets, yielding quantitative parametric maps of endothelial permeability using the hepatic artery as input function. The proposed approach was evaluated in 11 patients (52 ± 17 years, 5 men) with and without known hepatic lesions, undergoing DCE‐MRI.

Results

Respiratory motion produced artifacts and misalignment between dynamic volumes (lesion average motion amplitude of 3.82 ± 1.11 mm). Motion correction minimized artifacts and improved average contrast‐to‐noise ratio of hepatic lesions in late phase by 47% (p < .01). Quantitative endothelial permeability maps of motion‐corrected data demonstrated enhanced visibility of different pathologies (e.g., metastases, hemangiomas, cysts, necrotic tumor substructure) and showed improved contrast‐to‐noise ratio by 62% (p < .01) compared with uncorrected data.

Conclusion

3D nonrigid motion correction in DCE‐MRI improves both visual and quantitative assessment of hepatic lesions by ensuring accurate alignment between 3D DCE images and reducing motion blurring. This approach does not require breath‐holds and minimizes scan planning by using a large FOV with isotropic resolution.

Pancreas deformation in the presence of tumors using feature tracking from free-breathing XD-GRASP MRI

BACKGROUND

Quantifying the biomechanical properties of pancreatic tumors could potentially help with assessment of tumor aggressiveness, prognosis, and prediction of therapy response.

PURPOSE

To quantify respiratory-induced deformation in the pancreas and pancreatic lesions using XD-GRASP (eXtra-Dimensional Golden-angle RAdial Sparse Parallel), MRI.

STUDY TYPE

Retrospective study where patients undergoing clinically indicated abdominal MRI which included free-breathing radial T₁ -weighted (T₁ W) imaging were studied.

SUBJECTS

Thirty-two patients (12 male and 20 female) including nine with pancreatic lesions constituted our study cohort.

FIELD STRENGTH/SEQUENCE

3.0 T with T₁ WI contrast-enhanced gradient echo radial free-breathing acquisition.

ASSESSMENT

Using the XD-GRASP imaging technique, the acquired free-breathing radial data were sorted and binned into 10 consecutive respiratory motion states that were jointly reconstructed. 3D deformation fields along the respiratory dimension were computed using an optical flow method and were analyzed in the pancreas.

STATISTICAL TESTS

The Wilcoxon signed-rank test was used to assess the difference in average displacement across pancreatic regions, while the Wilcoxon rank-sum test was used for displacement differences between patients with and without tumors. The interclass correlation coefficient (ICC) was computed to assess consistency between observers for each image quality measure.

RESULTS

There was a significantly larger displacement in the pancreatic tail compared with the head (8.2 ± 3.7 mm > 5.8 ± 2.4 mm; P < 0.001) and body regions (8.2 ± 3.7 mm > 6.6 ± 2.9 mm; P < 0.001). Furthermore, there was reduced normalized average displacement in patients with pancreatic lesions compared with subjects without lesions (0.33 ± 0.1 < 0.69 ± 0.26, P < 0.001 for the head; 0.30 ± 0.1 < 0.84 ± 0.31, P < 0.001 for the body; and 0.44 ± 0.31 < 1.08 ± 0.53, P < 0.001 for the tail, respectively).

DATA CONCLUSION

Free-breathing respiratory motion-sorted XD-GRASP MRI has the potential to noninvasively characterize the biomechanical properties of the pancreas by quantifying breathing-induced mechanical displacement.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1633-1640.

A clustering approach to 4D MRI retrospective sorting for the investigation of different surrogates

PURPOSE

In retrospective 4-Dimensional Magnetic Resonance Imaging (4D MRI) sorting, respiratory surrogate selection affects the image quality of reconstructed volumes. We propose a method for retrospective 4D MRI sorting based on clustering, which allowed us to compare the performance of single or multiple internal surrogates vs. a conventional external signal.

METHODS

A k-medoids clustering algorithm was exploited for sorting 2D MRI into 4D MRI, relying on (A) multiple or (B) single automatically tracked internal landmarks or (C) respiratory belt signal. 4D MRI reconstructions for seven liver cancer patients were compared to those of the state-of-the-art mutual information (MI) approach. Sorting artifacts were measured by the root mean square error (RMSE) between the diaphragm profile and a fitted second order curve. Diaphragm and tumor motions were evaluated.

RESULTS

The median RMSEs ranged 0.97-1.66 mm, 1.24-1.89 mm, 1.43-2.27 mm, 1.74-3.72 mm for the MI, (A), (B) and (C) methods, respectively. Significant differences (Friedman, α = 5%) were found between (C) and all other methods, and between (B) and MI approaches. The discrepancies between (A) and MI approaches ranged 1.1-6.2 mm and 0.7-5.3 mm respectively in diaphragm and tumor motions. Methods (A) and (B) showed similar ranges of motion.

CONCLUSION

With multiple internal points, our method yielded the description of a higher range of motion and similar image quality with respect to the MI approach. The single point method led to more artifacts, suggesting the superior suitability of multiple internal surrogates for retrospective 4D MRI sorting. Considering internal rather than external information favored superior performance.

The impact of 2D cine MR imaging parameters on automated tumor and organ localization for MR-guided real-time adaptive radiotherapy

2D cine MR imaging may be utilized to monitor rapidly moving tumors and organs-at-risk for real-time adaptive radiotherapy. This study systematically investigates the impact of geometric imaging parameters on the ability of 2D cine MR imaging to guide template-matching-driven autocontouring of lung tumors and abdominal organs. Abdominal 4D MR images were acquired of six healthy volunteers and thoracic 4D MR images were obtained of eight lung cancer patients. At each breathing phase of the images, the left kidney and gallbladder or lung tumor, respectively, were outlined as volumes of interest. These images and contours were used to create artificial 2D cine MR images, while simultaneously serving as 3D ground truth. We explored the impact of five different imaging parameters (pixel size, slice thickness, imaging plane orientation, number and relative alignment of images as well as strategies to create training images). For each possible combination of imaging parameters, we generated artificial 2D cine MR images as training and test images. A template-matching algorithm used the training images to determine the tumor or organ position in the test images. Subsequently, a 3D base contour was shifted to the determined position and compared to the ground truth via centroid distance and Dice similarity coefficient. The median centroid distance between adapted and ground truth contours was 1.56 mm for the kidney, 3.81 mm for the gallbladder and 1.03 mm for the lung tumor (median Dice similarity coefficient: 0.95, 0.72 and 0.93). We observed that a decrease in image resolution led to a modest decrease in localization accuracy, especially for the small gallbladder. However, for all volumes of interest localization accuracy varied substantially more between subjects than due to the different imaging parameters. Automated tumor and organ localization using 2D cine MR imaging and template-matching-based autocontouring is robust against variation of geometric imaging parameters. Future work and optimization efforts of 2D cine MR imaging for real-time adaptive radiotherapy is needed to characterize the influence of sequence- and anatomical site-specific imaging contrast.

MRI-guidance for motion management in external beam radiotherapy: current status and future challenges

High precision conformal radiotherapy requires sophisticated imaging techniques to aid in target localisation for planning and treatment, particularly when organ motion due to respiration is involved. X-ray based imaging is a well-established standard for radiotherapy treatments. Over the last few years, the ability of magnetic resonance imaging (MRI) to provide radiation-free images with high-resolution and superb soft tissue contrast has highlighted the potential of this imaging modality for radiotherapy treatment planning and motion management. In addition, these advantageous properties motivated several recent developments towards combined MRI radiation therapy treatment units, enabling in-room MRI-guidance and treatment adaptation. The aim of this review is to provide an overview of the state-of-the-art in MRI-based image guidance for organ motion management in external beam radiotherapy. Methodological aspects of MRI for organ motion management are reviewed and their application in treatment planning, in-room guidance and adaptive radiotherapy described. Finally, a roadmap for an optimal use of MRI-guidance is highlighted and future challenges are discussed.

Evaluation of 2D and 3D ultrasound tracking algorithms and impact on ultrasound-guided liver radiotherapy margins

PURPOSE

Compensation for respiratory motion is important during abdominal cancer treatments. In this work we report the results of the 2015 MICCAI Challenge on Liver Ultrasound Tracking and extend the 2D results to relate them to clinical relevance in form of reducing treatment margins and hence sparing healthy tissues, while maintaining full duty cycle.

METHODS

We describe methodologies for estimating and temporally predicting respiratory liver motion from continuous ultrasound imaging, used during ultrasound-guided radiation therapy. Furthermore, we investigated the trade-off between tracking accuracy and runtime in combination with temporal prediction strategies and their impact on treatment margins.

RESULTS

Based on 2D ultrasound sequences from 39 volunteers, a mean tracking accuracy of 0.9 mm was achieved when combining the results from the 4 challenge submissions (1.2 to 3.3 mm). The two submissions for the 3D sequences from 14 volunteers provided mean accuracies of 1.7 and 1.8 mm. In combination with temporal prediction, using the faster (41 vs 228 ms) but less accurate (1.4 vs 0.9 mm) tracking method resulted in substantially reduced treatment margins (70% vs 39%) in contrast to mid-ventilation margins, as it avoided non-linear temporal prediction by keeping the treatment system latency low (150 vs 400 ms). Acceleration of the best tracking method would improve the margin reduction to 75%.

CONCLUSIONS

Liver motion estimation and prediction during free-breathing from 2D ultrasound images can substantially reduce the in-plane motion uncertainty and hence treatment margins. Employing an accurate tracking method while avoiding non-linear temporal prediction would be favorable. This approach has the potential to shorten treatment time compared to breath-hold and gated approaches, and increase treatment efficiency and safety.

On the direct acquisition of beam's-eye-view images in MRI for integration with external beam radiotherapy

The recent interest in the integration of external beam radiotherapy with a magnetic resonance (MR) imaging unit offers the potential for real-time adaptive tumour tracking during radiation treatment. The tracking of large tumours which follow a rapid trajectory may best be served by the generation of a projection image from the perspective of the beam source, or 'beam's eye view' (BEV). This type of image projection represents the path of the radiation beam, thus enabling rapid compensations for target translations, rotations and deformations, as well time-dependent critical structure avoidance. MR units have been traditionally incapable of this type of imaging except through lengthy 3D acquisitions and ray tracing procedures. This work investigates some changes to the traditional MR scanner architecture that would permit the direct acquisition of a BEV image suitable for integration with external beam radiotherapy. Based on the theory presented in this work, a phantom was imaged with nonlinear encoding-gradient field patterns to demonstrate the technique. The phantom was constructed with agarose gel tubes spaced two cm apart at their base and oriented to converge towards an imaginary beam source 100 cm away. A corresponding virtual phantom was also created and subjected to the same encoding technique as in the physical demonstration, allowing the method to be tested without hardware limitations. The experimentally acquired and simulated images indicate the feasibility of the technique, showing a substantial amount of blur reduction in a diverging phantom compared to the conventional imaging geometry, particularly with the nonlinear gradients ideally implemented. The theory is developed to demonstrate that the method can be adapted in a number of different configurations to accommodate all proposed integration schemes for MR units and radiotherapy sources. Depending on the configuration, the implementation of this technique will require between two and four additional nonlinear encoding coils.

Observation of different tumor motion magnitude within liver and estimate of internal motion margins in postoperative patients with hepatocellular carcinoma

Aims

To assess motion magnitude in different parts of the liver through surgical clips in postoperative patients with hepatocellular carcinoma and to examine the correlation between the clip and diaphragm motion.

Methods

Four-dimensional computed tomography images from 30 liver cancer patients under thermoplastic mask immobilization were selected for this study. Three to seven surgical clips were placed in the resection cavity of each patient. The liver volume on computed tomography image was divided into the right upper (RU), right middle (RM), right lower (RL), hilar, and left lobes. Agreement between the clip and diaphragm motion was assessed by calculating intraclass correlation coefficient, and Bland–Altman analysis (Diff). Furthermore, population-based and patient-specific margins for internal motion were evaluated.

Results

The clips located in the RU lobe showed the largest motion, (7.5±1.6) mm, which was significantly more than in the RM lobe (5.7±2.8 mm, p=0.019), RL lobe (4.8±3.3 mm, p=0.017), and hilar lobe (4.7±2.7 mm, p<0.001) in the cranial–caudal direction. The mean intraclass correlation coefficient values between the clip and diaphragm motion were 0.915, 0.735, 0.678, 0.670, and the mean Diff values between them were 0.1±0.8 mm, 2.3±1.4 mm, 3.1±2.0 mm, 2.4±1.5 mm, when clips were located in the RU lobe, RM lobe, RL lobe, and hilar lobe, respectively. The clip and diaphragm motions had high concordance when clips were located in the RU lobe. Internal margin can be reduced from 5 mm in the cranial–caudal direction based on patient population average and to 3 mm based on patient-specific margins.

Conclusions

The motion magnitude of clips varied significantly depending on their location within the liver. The diaphragm was a more appropriate surrogate for tumor located in the RU lobe than for other lobes.

MRI-guided lung SBRT: Present and future developments

Stereotactic body radiotherapy (SBRT) is rapidly becoming an alternative to surgery for the treatment of early-stage non-small cell lung cancer patients. Lung SBRT is administered in a hypo-fractionated, conformal manner, delivering high doses to the target. To avoid normal-tissue toxicity, it is crucial to limit the exposure of nearby healthy organs-at-risk (OAR). Current image-guided radiotherapy strategies for lung SBRT are mostly based on X-ray imaging modalities. Although still in its infancy, magnetic resonance imaging (MRI) guidance for lung SBRT is not exposure-limited and MRI promises to improve crucial soft-tissue contrast. Looking beyond anatomical imaging, functional MRI is expected to inform treatment decisions and adaptations in the future. This review summarises and discusses how MRI could be advantageous to the different links of the radiotherapy treatment chain for lung SBRT: diagnosis and staging, tumour and OAR delineation, treatment planning, and inter- or intrafractional motion management. Special emphasis is placed on a new generation of hybrid MRI treatment devices and their potential for real-time adaptive radiotherapy.

Tumour auto-contouring on 2d cine MRI for locally advanced lung cancer: A comparative study

BACKGROUND AND PURPOSE

Radiotherapy guidance based on magnetic resonance imaging (MRI) is currently becoming a clinical reality. Fast 2d cine MRI sequences are expected to increase the precision of radiation delivery by facilitating tumour delineation during treatment. This study compares four auto-contouring algorithms for the task of delineating the primary tumour in six locally advanced (LA) lung cancer patients.

MATERIAL AND METHODS

Twenty-two cine MRI sequences were acquired using either a balanced steady-state free precession or a spoiled gradient echo imaging technique. Contours derived by the auto-contouring algorithms were compared against manual reference contours. A selection of eight image data sets was also used to assess the inter-observer delineation uncertainty.

RESULTS

Algorithmically derived contours agreed well with the manual reference contours (median Dice similarity index: ⩾0.91). Multi-template matching and deformable image registration performed significantly better than feature-driven registration and the pulse-coupled neural network (PCNN). Neither MRI sequence nor image orientation was a conclusive predictor for algorithmic performance. Motion significantly degraded the performance of the PCNN. The inter-observer variability was of the same order of magnitude as the algorithmic performance.

CONCLUSION

Auto-contouring of tumours on cine MRI is feasible in LA lung cancer patients. Despite large variations in implementation complexity, the different algorithms all have relatively similar performance.

Spatiotemporal fractionation schemes for liver stereotactic body radiotherapy

BACKGROUND AND PURPOSE

Dose prescription in stereotactic body radiotherapy (SBRT) for liver tumors is often limited by the mean liver dose. We explore the concept of spatiotemporal fractionation as an approach to facilitate further dose escalation in liver SBRT.

MATERIALS AND METHODS

Spatiotemporal fractionation schemes aim at partial hypofractionation in the tumor along with near-uniform fractionation in normal tissues. This is achieved by delivering distinct dose distributions in different fractions, which are designed such that each fraction delivers a high single fraction dose to complementary parts of the tumor while creating a similar dose bath in the surrounding noninvolved liver. Thereby, higher biologically effective doses (BED) can be delivered to the tumor without increasing the mean BED in the liver. Planning of such treatments is performed by simultaneously optimizing multiple dose distributions based on their cumulative BED. We study this concept for five liver cancer patients with different tumor geometries.

RESULTS

Spatiotemporal fractionation presents a method of increasing the ratio of prescribed tumor BED to mean BED in the noninvolved liver by approximately 10-20%, compared to conventional SBRT using identical fractions.

CONCLUSIONS

Spatiotemporal fractionation may reduce the risk of liver toxicity or facilitate dose escalation in liver SBRT in circumstances where the mean dose to the non-involved liver is the prescription-limiting factor.

Magnitude, Impact, and Management of Respiration-induced Target Motion in Radiotherapy Treatment: A Comprehensive Review

Tumors in thoracic and upper abdomen regions such as lungs, liver, pancreas, esophagus, and breast move due to respiration. Respiration-induced motion introduces uncertainties in radiotherapy treatments of these sites and is regarded as a significant bottleneck in achieving highly conformal dose distributions. Recent developments in radiation therapy have resulted in (i) motion-encompassing, (ii) respiratory gating, and (iii) tracking methods for adapting the radiation beam aperture to account for the respiration-induced target motion. The purpose of this review is to discuss the magnitude, impact, and management of respiration-induced tumor motion.

Servoing Performance Enhancement via a Respiratory Organ Motion Prediction Model for a Non-Invasive Ultrasound Theragnostic System

[abstFig src='/00290002/15.jpg' width='300' text='Proposed method for tracking and following respiratory organ motion' ] High intensity focused ultrasound (HIFU) is potentially useful for treating stones and/or tumors. With respect to HIFU therapy, it is difficult to focus HIFU on the focal lesion due to respiratory organ motion, and this increases the risk of damaging the surrounding healthy tissues around the target focal lesion. Thus, this study proposes a method to cope with the fore-mentioned problem involving tracking and following the respiratory organ motion via a visual feedback and a prediction model for respiratory organ motion to realize highly accurate servoing performance for focal lesions. The prediction model is continuously updated based on the latest organ motion data. The results indicate that respiratory kidney motion of two healthy subjects is successfully tracked and followed with an accuracy of 0.88 mm by the proposed method and the constructed system.

The future of image-guided radiotherapy will be MR guided

Advances in image-guided radiotherapy (RT) have allowed for dose escalation and more precise radiation treatment delivery. Each decade brings new imaging technologies to help improve RT patient setup. Currently, the most frequently used method of three-dimensional pre-treatment image verification is performed with cone beam CT. However, more recent developments have provided RT with the ability to have on-board MRI coupled to the teleradiotherapy unit. This latest tool for treating cancer is known as MR-guided RT. Several varieties of these units have been designed and installed in centres across the globe. Their prevalence, history, advantages and disadvantages are discussed in this review article. In preparation for the next generation of image-guided RT, this review also covers where MR-guided RT might be heading in the near future.

Investigation of the 4D composite MR image distortion field associated with tumor motion for MR-guided radiotherapy

PURPOSE

Magnetic resonance (MR) images are affected by geometric distortions due to the specifics of the MR scanner and patient anatomy. Quantifying the distortions associated with mobile tumors is particularly challenging due to real anatomical changes in the tumor's volume, shape, and relative location within the MR imaging volume. In this study, the authors investigate the 4D composite distortion field, which combines the effects of the susceptibility-induced and system-related distortion fields, experienced by mobile lung tumors.

METHODS

The susceptibility (χ) effects were numerically simulated for two specific scenarios: (a) a full motion cycle of a lung tumor due to breathing as depicted on ten phases of a 4D CBCT data set and (b) varying the tumor size and location in lung tissue via a synthetically generated sphere with variable diameter (4-80 mm). The χ simulation procedure relied on the segmentation and generation of 3D susceptibility (χ) masks and computation of the magnetic field by means of finite difference methods. A system-related distortion field, determined with a phantom and image processing algorithm, was used as a reference. The 4D composite distortion field was generated as the vector summation of the χ-induced and system-related fields. The analysis was performed for two orientations of the main magnetic field (B0), which correspond to several MRIgRT system configurations. Specifically, B0 was set along the z-axis as in the case of a cylindrical-bore scanner and in the (x,y)-plane as for a biplanar MR. Computations were also performed for a full revolution at 15° increments in the case of a rotating biplanar magnet. Histograms and metrics such as maximum, mean, and range were used to evaluate the characteristics of the 4D distortion field.

RESULTS

The χ-induced field depends on the change in volume and shape of the moving tumor as well as the local surrounding anatomy. In the case of system-related distortions, the tumor experiences increased field perturbations as it moves further away from the MR isocenter. For a mobile lung tumor, the 4D composite field, corresponding to a 1.5 T field and a readout gradient of 5 mT/m, amounts to 3.0 and 2.8 mm for the MRIgRT system designs featuring B0 oriented along the z-axis (cylindrical-bore scanner) and in the (x,y)-plane (biplanar scanner), respectively. For a rotating biplanar scanner, the composite distortion field varied nonlinearly with the rotation angle. Overall, the dominant contribution to the composite field was from the system-related distortion field. The tumor centroid experienced a systematic shift of 2 mm and showed a negligible perturbation for different B0 values. The dependency on the tumor size was also investigated, namely the max values varied from 1.2 to 2.5 mm for spherical volumes with a diameter between 4 and 80 mm.

CONCLUSIONS

The composite distortion field requires adequate quantification for lung radiation therapy applications such as treatment planning, pretreatment patient setup verification, and real-time treatment delivery guidance. For certain scenarios such as small tumor volumes, the spatial distortions may be corrected by applying systematic shifts derived from a single tumor motion phase. In the case of high readout gradients common to fast imaging applications, the χ distortions were found to be less than 1 mm irrespective of scanner configuration.

Investigation of dosimetric variations of liver radiotherapy using deformable registration of planning CT and cone-beam CT

Many patients with technically unresectable or medically inoperable hepatocellular carcinoma (HCC) had hepatic anatomy variations as a result of interfraction deformation during fractionated radiotherapy. We conducted this retrospective study to investigate interfractional normal liver dosimetric consequences via reconstructing weekly dose in HCC patients. Twenty‐three patients with HCC received conventional fractionated three‐dimensional conformal radiation therapy (3DCRT) were enrolled in this retrospective investigation. Among them, seven patients had been diagnosed of radiation‐induced liver disease (RILD) and the other 16 patients had good prognosis after treatment course. The cone‐beam CT (CBCT) scans were acquired once weekly for each patient throughout the treatment, deformable image registration (DIR) of planning CT (pCT) and CBCT was performed to acquire modified CBCT (mCBCT), and the structural contours were propagated by the DIR. The same plan was applied to mCBCT to perform dose calculation. Weekly dose distribution was displayed on the pCT dose space and compared using dose difference, target coverage, and dose volume histograms. Statistical analysis was performed to identify the significant dosimetric variations. Among the 23 patients, the three weekly normal liver D₅₀ increased by 0.2 Gy, 4.2 Gy, and 4.7 Gy, respectively, for patients with RILD, and 1.0 Gy, 2.7 Gy, and 3.1 Gy, respectively, for patients without RILD. Mean dose to the normal liver (D_mean) increased by 0.5 Gy, 2.6 Gy, and 4.0 Gy, respectively, for patients with RILD, and 0.4 Gy, 3.1 Gy, and 3.4 Gy, respectively, for patients without RILD. Regarding patients with RILD, the average values of the third weekly D₅₀ and D_mean were both over hepatic radiation tolerance, while the values of patients without RILD were below. The dosimetric consequence showed that the liver dose between patients with and without RILD were different relative to the planned dose, and the RILD patients suffered from liver dose over hepatic radiation tolerance. Evaluation of routinely acquired CBCT images during radiation therapy provides biological information on the organs at risk, and dose estimation based on mCBCT could potentially form the basis for personalized response adaptive therapy.

Design and evaluation of an MRI-compatible linear motion stage

PURPOSE

To develop and evaluate a tool for accurate, reproducible, and programmable motion control of imaging phantoms for use in motion sensitive magnetic resonance imaging (MRI) appli cations.

METHODS

In this paper, the authors introduce a compact linear motion stage that is made of nonmagnetic material and is actuated with an ultrasonic motor. The stage can be positioned at arbitrary positions and orientations inside the scanner bore to move, push, or pull arbitrary phantoms. Using optical trackers, measuring microscopes, and navigators, the accuracy of the stage in motion control was evaluated. Also, the effect of the stage on image signal-to-noise ratio (SNR), artifacts, and B0 field homogeneity was evaluated.

RESULTS

The error of the stage in reaching fixed positions was 0.025 ± 0.021 mm. In execution of dynamic motion profiles, the worst-case normalized root mean squared error was below 7% (for frequencies below 0.33 Hz). Experiments demonstrated that the stage did not introduce artifacts nor did it degrade the image SNR. The effect of the stage on the B0 field was less than 2 ppm.

CONCLUSIONS

The results of the experiments indicate that the proposed system is MRI-compatible and can create reliable and reproducible motion that may be used for validation and assessment of motion related MRI applications.