Direct Comparison of Respiration-Correlated Four-Dimensional Magnetic Resonance Imaging Reconstructed Using Concurrent Internal Navigator and External Bellows

Sorting lung tumor volumes from 4D-MRI data using an automatic tumor-based signal reduces stitching artifacts

PURPOSE

To investigate whether a novel signal derived from tumor motion allows more precise sorting of 4D-magnetic resonance (4D-MR) image data than do signals based on normal anatomy, reducing levels of stitching artifacts within sorted lung tumor volumes.

METHODS

(4D-MRI) scans were collected for 10 lung cancer patients using a 2D T2-weighted single-shot turbo spin echo sequence, obtaining 25 repeat frames per image slice. For each slice, a tumor-motion signal was generated using the first principal component of movement in the tumor neighborhood (TumorPC1). Signals were also generated from displacements of the diaphragm (DIA) and upper and lower chest wall (UCW/LCW) and from slice body area changes (BA). Pearson r coefficients of correlations between observed tumor movement and respiratory signals were determined. TumorPC1, DIA, and UCW signals were used to compile image stacks showing each patient's tumor volume in a respiratory phase. Unsorted image stacks were also built for comparison. For each image stack, the presence of stitching artifacts was assessed by measuring the roughness of the compiled tumor surface according to a roughness metric (Rg). Statistical differences in weighted means of Rg between any two signals were determined using an exact permutation test.

RESULTS

The TumorPC1 signal was most strongly correlated with superior-inferior tumor motion, and had significantly higher Pearson r values (median 0.86) than those determined for correlations of UCW, LCW, and BA with superior-inferior tumor motion (p < 0.05). Weighted means of ratios of Rg values in TumorPC1 image stacks to those in unsorted, UCW, and DIA stacks were 0.67, 0.69, and 0.71, all significantly favoring TumorPC1 (p = 0.02-0.05). For other pairs of signals, weighted mean ratios did not differ significantly from one.

CONCLUSION

Tumor volumes were smoother in 3D image stacks compiled using the first principal component of tumor motion than in stacks compiled with signals based on normal anatomy.

Motion Artifact Reduction Using U-Net Model with Three-Dimensional Simulation-Based Datasets for Brain Magnetic Resonance Images

This study aimed to remove motion artifacts from brain magnetic resonance (MR) images using a U-Net model. In addition, a simulation method was proposed to increase the size of the dataset required to train the U-Net model while avoiding the overfitting problem. The volume data were rotated and translated with random intensity and frequency, in three dimensions, and were iterated as the number of slices in the volume data. Then, for every slice, a portion of the motion-free k-space data was replaced with motion k-space data, respectively. In addition, based on the transposed k-space data, we acquired MR images with motion artifacts and residual maps and constructed datasets. For a quantitative evaluation, the root mean square error (RMSE), peak signal-to-noise ratio (PSNR), coefficient of correlation (CC), and universal image quality index (UQI) were measured. The U-Net models for motion artifact reduction with the residual map-based dataset showed the best performance across all evaluation factors. In particular, the RMSE, PSNR, CC, and UQI improved by approximately 5.35×, 1.51×, 1.12×, and 1.01×, respectively, and the U-Net model with the residual map-based dataset was compared with the direct images. In conclusion, our simulation-based dataset demonstrates that U-Net models can be effectively trained for motion artifact reduction.

Association of Internal and External Motion Based on Cine MR Images Acquired During Real-Time Treatment on MRI-Guided Linear Accelerator for Patients With Lung Cancer

Purpose

With the recent clinical implementation of magnetic resonance imaging (MRI)-guided linear accelerators, a large number of real-time planar MR images has been acquired during lung cancer treatment as a standard of care. In this study, associations among lung tumor, diaphragm, and external skin movement were studied based on MR cine imaging during the entire duration of each treatment fraction.

Methods and Materials

This retrospective study used 181,798 planar MRI frames acquired over 55 treatment/imaging sessions of 13 patients with lung cancer treated on 2 MRI-guided linear accelerators. From each planar MR image frame, in-house software automatically extracted 9 features: the superior-interior (SI) and posterior-anterior (PA) positions of a lung tumor; the area of the lung (Lung_Area); the posterior (Dia_Post), dome/apex (Dia_Dome), and anterior (Dia_Ant) points of a diaphragmatic curve; the diaphragm curve point (Dia_Max); and the chest (Chest) and belly (Belly) skin points experienced the maximum range of motions. Correlation analyses were performed among the 9 features for every session. Lung tumor motion range and standard deviations were calculated based on positions obtained in cine images and compared with motion ranges obtained from 4-dimensional computed tomography images.

Results

In the study, 177,009 frames of images were successfully analyzed. For all patients, correlation coefficients were as follows: 0.91 ± 0.10 between any 2 features among Lung_Area, Dia_Post, Dia_Dome, and Dia_Max; 0.82 ± 0.21 between SI and any feature among Lung_Area, Dia_Post, Dia_Dome, and Dia_Max; 0.75 ± 0.24 between SI and Belly. Six of 13 patients were considered large amplitude motion (patients with lung tumor SI motion standard deviation >5 mm). Furthermore, 92,956 frames of images were analyzed for the 6 large-amplitude motion patients. For this set, correlation coefficients were 0.93 ± 0.07 between any 2 features among Lung_Area, Dia_Post, Dia_Dome, and Dia_Max; 0.94 ± 0.06 between SI and any feature among Lung_Area, Dia_Post, Dia_Dome, and Dia_Max; and 0.90 ± 0.09 between SI and Belly.

Conclusions

Both belly and diaphragmatic motions as assessed by cine MRI are highly correlated with large amplitude lung tumor motion in the longitudinal axis.

Effectiveness of visual biofeedback-guided respiratory-correlated 4D-MRI for radiotherapy guidance on the MR-linac

PURPOSE

Respiratory-correlated 4D-MRI may provide motion characteristics for radiotherapy but is susceptible to irregular breathing. This study investigated the effectiveness of visual biofeedback (VBF) guidance for breathing regularization during 4D-MRI acquisitions on an MR-linac.

METHODS

A simultaneous multislice-accelerated 4D-MRI sequence was interleaved with a one-dimensional respiratory navigator (1D-RNAV) in 10 healthy volunteers on a 1.5T Unity MR-linac (Elekta AB, Stockholm, Sweden). Volunteer-specific breathing amplitudes and periods were derived from the 1D-RNAV signal obtained during unguided 4D-MRI acquisitions. These were used for the guidance waveform, while the 1D-RNAV positions were overlayed as VBF. VBF effectiveness was quantified by calculating the change in coefficient of variation (CV diff $$ {\mathrm{CV}}^{\mathrm{diff}} $$ ) for the breathing amplitude and period, the position SD of end-exhale, end-inhale and midposition locations, and the agreement between the 1D-RNAV signals and guidance waveforms. The 4D-MRI quality was assessed by quantifying amounts of missing data.

RESULTS

VBF had an average latency of 520 ± 2 ms. VBF reduced median breathing variations by 18% to 35% (amplitude) and 29% to 57% (period). Median position SD reductions ranged from -3% to 35% (end-exhale), 29% to 38% (end-inhale), and 25% to 37% (midposition). Average differences between guidance waveforms and 1D-RNAV signals were 0.0 s (period) and +1.7 mm (amplitude). VBF also decreased the median amount of missing data by 11% and 29%.

CONCLUSION

A VBF system was successfully implemented, and all volunteers were able to adapt to the guidance waveform. VBF during 4D-MRI acquisitions drastically reduced breathing variability but had limited effect on missing data in respiratory-correlated 4D-MRI.

Comparative study of sub-second temporal resolution 4D-MRI and 4D-CT for target motion assessment in a phantom model

To develop and investigate the feasibility of sub-second temporal resolution volumetric T1-weighted four-dimensional (4D-) MRI in comparison with 4D-CT for respiratory-correlated motion assessment using an MRI/CT-compatible phantom. Sub-second high temporal resolution (0.5 s) gradient-echo T1-weighted 4D-MRI was developed using a volumetric acquisition scheme with compressed sensing. An MRI/CT-compatible motion phantom (simulated liver tumor) with three sinusoidal movements of amplitudes and two respiratory patterns was introduced and imaged with 4D-MRI and 4D-CT to investigate the geometric accuracy of the target movement. The geometric accuracy, including centroid position, volume, similarity index of dice similarity coefficient (DSC), and Hausdorff distance (HD), was systematically evaluated. Proposed 4D-MRI achieved a similar geometric accuracy compared with 4D-CT regarding the centroid position, volume, and similarity index. The observed position differences of the absolute average centroid were within 0.08 cm in 4D-MRI and 0.03 cm in 4D-CT, less than the 1-pixel resolution for each modality. The observed volume difference in 4D-MRI/4D-CT was within 0.73 cm3 (4.5%)/0.29 cm3 (2.1%) for a large target and 0.06 cm3 (11.3%)/0.04 cm3 (11.6%) for a small target. The observed DSC values for 4D-MRI/4D-CT were at least 0.93/0.95 for the large target and 0.83/0.84 for the small target. The maximum HD values were 0.25 cm/0.31 cm for the large target and 0.21 cm/0.15 cm for the small target. Although 4D-CT potentially exhibit superior numerical accuracy in phantom studies, the proposed high temporal resolution 4D-MRI demonstrates sub-millimetre geometric accuracy comparable to that of 4D-CT. These findings suggest that the 4D-MRI technique is a viable option for characterizing motion and generating phase-dependent internal target volumes within the realm of radiotherapy.

Multi-parametric MRI for radiotherapy simulation

Magnetic resonance imaging (MRI) has become an important imaging modality in the field of radiotherapy (RT) in the past decade, especially with the development of various novel MRI and image-guidance techniques. In this review article, we will describe recent developments and discuss the applications of multi-parametric MRI (mpMRI) in RT simulation. In this review, mpMRI refers to a general and loose definition which includes various multi-contrast MRI techniques. Specifically, we will focus on the implementation, challenges, and future directions of mpMRI techniques for RT simulation.

Association Between Internal Organ/Liver Tumor and External Surface Motion From Cine MR Images on an MRI-Linac

Purposes/Objectives

Historically, motion correlation between internal tumor and external surrogates have been based on limited sets of X-ray or magnetic resonance (MR) images. With the recent clinical implementation of MR-guided linear accelerators, a vast quantity of continuous planar real-time MR imaging data is acquired. In this study, information was extracted from MR cine imaging during liver cancer treatments to establish associations between internal tumor/diaphragm and external surface/skin movement.

Methods and Materials

This retrospective study used 305,644 MR image frames acquired over 118 treatment/imaging sessions of the first 23 liver cancer patients treated on an MRI-linac. 9 features were automatically determined on each MR image frame: Lung_Area, the posterior (Dia_Post), dome (Dia_Dome), and anterior (Dia_Ant) points of a diaphragmatic curve and the diaphragm curve point (Dia_Max), the chest (Chest) and the belly (Belly) skin points experiencing the maximum motion ranges; the superior-interior (SI) and posterior-anterior (PA) positions of a target. For every session, correlation analyses were performed twice among the 9 features: 1) over a breath-hold (BH) set and 2) on a pseudo free-breathing (PFB) generated by removing breath-holding frames.

Results

303,123 frames of images were successfully analyzed. For BH set analysis, correlation coefficients were as follows: 0.94 ± 0.07 between any two features among Dia_Post, Dia_Dome, Dia_Max, and Lung_Area; 0.95 ± 0.06 between SI and any feature among Dia_Post, Dia_Dome, Dia_Max, or Lung_Area; 0.76 ± 0.29 between SI and Belly (with 50% of correlations ≥ 0.87). The PFB set had 142,862 frames of images. For this set, correlation coefficients were 0.96 ± 0.06 between any two features among Dia_Post, Dia_Dome, Dia_Max, and Lung_Area; 0.95 ± 0.06 between SI and any feature among Dia_Post, Dia_Dome, Dia_Max, or Lung_Area; 0.80 ± 0.26 between SI and Belly (with 50% of correlations ≥ 0.91).

Conclusion

Diaphragmatic motion as assessed by cine MR imaging is highly correlated with liver tumor motion. Belly vertical motion is highly correlated with liver tumor longitudinal motion in approximately half of the cases. More detailed analyses of those cases displaying weak correlations are in progress.

A Dual-supervised Deformation Estimation Model (DDEM) for constructing ultra-quality 4D-MRI based on a commercial low-quality 4D-MRI for liver cancer radiation therapy

BACKGROUND

Most available 4D-MRI techniques are limited by insufficient image quality and long acquisition times or require specially designed sequences or hardware that are not available in the clinic. These limitations have greatly hindered the clinical implementation of 4D-MRI.

PURPOSE

This study aims to develop a fast ultra-quality (UQ) 4D-MRI reconstruction method using a commercially available 4D-MRI sequence and dual-supervised deformation estimation model (DDEM).

METHODS

Thirty-nine patients receiving radiotherapy for liver tumors were included. Each patient was scanned using a TWIST-VIBE MRI sequence to acquire 4D-MR images. They also received 3D T1-/T2-weighted MRI scans as prior images and UQ 4D-MRI at any instant was considered a deformation of them. A DDEM was developed to obtain a 4D deformable vector field (DVF) from 4D-MRI data, and the prior images were deformed using this 4D-DVF to generate UQ 4D-MR images. The registration accuracies of the DDEM, VoxelMorph (normalized cross-correlation (NCC) supervised), VoxelMorph (end-to-end point error (EPE) supervised), and the parametric total variation (pTV) algorithm were compared. Tumor motion on UQ 4D-MRI was evaluated quantitatively using region-of-interest (ROI) tracking errors, while image quality was evaluated using the contrast-to-noise ratio (CNR), lung-liver edge sharpness, and perceptual blur metric (PBM).

RESULTS

The registration accuracy of the DDEM was significantly better than those of VoxelMorph (NCC supervised), VoxelMorph (EPE supervised) and the pTV algorithm (all, p < 0.001), with an inference time of 69.3 ± 5.9 ms. UQ 4D-MRI yielded ROI tracking errors of 0.79 ± 0.65, 0.50 ± 0.55, and 0.51 ± 0.58 mm in the superior-inferior, anterior-posterior, and mid-lateral directions, respectively. From the original 4D-MRI to UQ 4D-MRI, the CNR increased from 7.25 ± 4.89 to 18.86 ± 15.81; the lung-liver edge full-width-at-half-maximum decreased from 8.22 ± 3.17 to 3.65 ± 1.66 mm in the in-plane direction and from 8.79 ± 2.78 to 5.04 ± 1.67 mm in the cross-plane direction, and the PBM decreased from 0.68 ± 0.07 to 0.38 ± 0.01.

CONCLUSION

This novel DDEM method successfully generated UQ 4D-MR images based on a commercial 4D-MRI sequence. It shows great promise for improving liver tumor motion management during radiation therapy. This article is protected by copyright. All rights reserved.

Stability and Reliability of Enhanced External-Internal Motion Correlation via Dynamic Phase-Shift Corrections Over 30-min Timeframe for Respiratory-Gated Radiotherapy

To assess the stability of patient-specific phase shifts between external- and internal-respiratory motion waveforms, the reliability of enhanced external–internal correlation with phase-shift correction, and the feasibility of guiding respiratory-gated radiotherapy (RGRT) over 30 min. In this clinical feasibility investigation, external bellows and internal-navigator waveforms were simultaneously and prospectively acquired along with two four-dimensional magnetic resonance imaging (4DMRI) scans (6–15 m each) with 15–20 m intervals in 10 volunteers. A bellows was placed 5 cm inferior to the xiphoid to monitor abdominal motion, and an MR navigator was used to track the diaphragmatic motion. The mean phase-domain (MPD) method was applied, which combines three individual phase-calculating methods: phase-space oval fitting, principal component analysis, and analytic signal analysis, weighted by the reciprocal of their residual errors (RE) excluding outliers (RE >2σ). The time-domain cross-correlation (TCC) analysis was applied for comparison. Dynamic phase-shift correction was performed based on the phase shift detected on the fly within two 10 s moving datasets. Simulating bellows-triggered gating, the median and 95% confidence interval for the navigator's position at beam-on/beam-off and %harm (percentage of beam-on time outside the safety margin) were calculated. Averaged across all subjects, the mean phase shifts are found indistinguishable (p > .05) between scan 1 (55˚ ± 9˚) and scan 2 (59˚ ± 11˚). Using the MPD method the averaged correlation increases from 0.56 ± 0.22 to 0.85 ± 0.11 for scan 1 and from 0.47 ± 0.30 to 0.84 ± 0.08 for scan 2. The TCC correction results in similar results. After phase-shift correction, the number of cases that were suitable for amplitude gating (with <10%harm) increased from 2 to 17 out of 20 cases. A patient-specific, stable phase-shift between the external and internal motions was observed and corrected using the MPD and TCC methods, producing long-lasting enhanced motion correlation over 30m. Phase-shift correction offers a feasible strategy for improving the accuracy of tumor-motion prediction during RGRT.

Multi-contrast four-dimensional magnetic resonance imaging (MC-4D-MRI): Development and initial evaluation in liver tumor patients

PURPOSE

To develop a novel multi-contrast four-dimensional magnetic resonance imaging (MC-4D-MRI) technique that expands single image contrast 4D-MRI to a spectrum of native and synthetic image contrasts and to evaluate its feasibility in liver tumor patients.

METHODS AND MATERIALS

The MC-4D-MRI technique integrates multi-parametric MRI fusion, 4D-MRI, and deformable image registration (DIR) techniques. The fusion technique consists of native MRI as input, image pre-processing, fusion algorithm, adaptation, and fused multi-contrast MRI as output. Four-dimensional deformation vector fields (4D-DVF) were generated from an original T2/T1-w 4D-MRI by deforming end-of-inhalation (EOI) to nine other phase volumes via DIR. The 4D-DVF were applied to multi-contrast MRI to generate a spectrum of 4D-MRI in different image contrasts. The MC-4D-MRI technique was evaluated in five liver tumor patients on tumor contrast-to-noise ratio (CNR), internal target volume (ITV) contouring consistency, diaphragm motion range, and tumor motion trajectory; and in digital anthropomorphic phantoms on 4D-DIR introduced errors in tumor motion range, centroid location, extent, and volume.

RESULTS

MC-4D-MRI consisting of 4D-MRIs in native image contrasts (T1-w, T2-w, and T2/T1-w) and synthetic image contrasts, such as tumor-enhanced contrast (TEC) were generated in five liver tumor patients. Patient tumor CNR increased from 2.6 ± 1.8 in the T2/T1-w MRI, to -4.4 ± 2.4, 6.6 ± 3.0, and 9.6 ± 3.9 in the T1-w, T2-w, and TEC MRI, respectively. Patient ITV inter-observer mean Dice similarity coefficient (mDSC) increased from 0.65 ± 0.10 in the original T2/T1-w 4D-MRI, to 0.76 ± 0.14, 0.77 ± 0.12, and 0.86 ± 0.05 in the T1-w, T2-w, and TEC 4D-MRI, respectively. Patient diaphragm motion range absolute differences between the three new 4D-MRIs and original T2/T1-w 4D-MRI were 1.2 ± 1.3, 0.3 ± 0.7, and 0.5 ± 0.5 mm, respectively. Patient tumor displacement phase-averaged absolute differences between the three 4D-MRIs and the original 4D-MRI were 0.72 ± 0.33, 0.62 ± 0.54, and 0.74 ± 0.43 mm in the superior-inferior (SI) direction, and 0.59 ± 0.36, 0.51 ± 0.30, and 0.50 ± 0.24 mm in the anterior-posterior (AP) direction, respectively. In the digital phantoms, phase-averaged absolute tumor centroid shift caused by the 4D-DIR were at or below 0.5 mm in SI, AP, and left-right (LR) directions.

CONCLUSION

We developed an MC-4D-MRI technique capable of expanding single image contrast 4D-MRI along a new dimension of image contrast. Initial evaluations in liver tumor patients showed enhancements in image contrast variety, tumor contrast, and ITV contouring consistencies using MC-4D-MRI. The technique might offer new perspectives on the image contrast of MRI and 4D-MRI in MR-guided radiotherapy.

Comparative Evaluation of 4-Dimensional Computed Tomography and 4-Dimensional Magnetic Resonance Imaging to Delineate the Target of Primary Liver Cancer

Purpose: To evaluate the feasibility of 4-dimensional magnetic resonance imaging (4DMRI) in establishing the target of primary liver cancer in comparison with 4-dimensional computed tomography (4DCT). Methods and Materials: A total of 23 patients with primary liver cancer who received radiotherapy were selected, and 4DCT and T2w-4DMRI simulations were conducted to obtain 4DCT and T2w-4DMRI simulation images. The 4DCT and T2w-4DMRI data were sorted into 10 and 8 respiratory phase bins, respectively. The liver and gross tumor volumes (GTVs) were delineated in all images using programmed clinical workflows under tumor delineation guidelines. The internal organs at risk volumes (IRVs) and internal target volumes (ITVs) were the unions of all the phase livers and GTVs, respectively. Then, the artifacts, liver volume, GTV, and motion range in 4DCT and T2w-4DMRI were compared. Results: The mean GTV volume based on 4DMRI was 136.42 ± 231.27 cm³, which was 25.04 cm³ (15.5%) less than that of 4DCT (161.46 ± 280.29 cm³). The average volume of ITV determined by 4DMRI was 166.12 ± 270.43 cm³, which was 22.44 cm³ (11.9%) less than that determined by 4DCT (188.56 ± 307.57 cm³). Liver volume and IRV in 4DMRI increased by 4.0% and 6.6%, respectively, compared with 4DCT. The difference in tumor motion by T2w-4DMRI based on the centroid was greater than that of 4DCT in the L/R, A/P, and S/I directions, and the average displacement differences were 2.6, 2.8, and 6.9 mm, respectively. The severe artifacts in 4DCT were 47.8% (11/23) greater than in 4DMRI 17.4% (4/23). Conclusions: Compared with 4DCT, T2-weighted and navigator-triggered 4DMRI produces fewer artifacts and larger motion differences in hepatic intrafraction tumors, which is a feasible technique for primary liver cancer treatment planning.

Technical Note: Investigating internal-external motion correlation using fast helical CT

PURPOSE

To quantify the use of anterior torso skin surface position measurement as a breathing surrogate.

METHODS

Fourteen patients were scanned 25 times in alternating directions using a free-breathing low-mA fast helical CT protocol. Simultaneously, an abdominal pneumatic bellows was used as a real-time breathing surrogate. The imaged diaphragm dome position was used as a gold standard surrogate, characterized by localizing the most superior points of the diaphragm dome in each lung. These positions were correlated against the bellows signal acquired at the corresponding scan times. The bellows system has been shown to have a slow linear drift, and the bellows-to-CT synchronization process had a small uncertainty, so the drift and time offset were determined by maximizing the correlation coefficient between the craniocaudal diaphragm position and the drift-corrected bellows signal. The corresponding fit was used to model the real-time diaphragm position. To estimate the effectiveness of skin surface positions as surrogates, the anterior torso surface position was measured from the CT scans and correlated against the diaphragm position model. The residual error was defined as the root-mean-square correlation residual with the breathing amplitude normalized to the 5^th to 95^th breathing amplitude percentiles. The fit residual errors were analyzed over the surface for the fourteen studied patients and reported as percentages of the 5^th to 95^th percentile ranges.

RESULTS

A strong correlation was measured between the diaphragm motion and the abdominal bellows signal with an average residual error of 9.21% and standard deviation of 3.77%. In contrast, the correlations between the diaphragm position model and patient surface positions varied throughout the torso and from patient to patient. However, a consistently high correlation was found near the abdomen for each patient, and the average minimum residual error relating the skin surface to the diaphragm was 11.8% with a standard deviation of 4.61%.

CONCLUSIONS

The thoracic patient surface was found to be an accurate surrogate, but the accuracy varied across the surface sufficiently that care would need to be taken to use the surface as an accurate and reliable surrogate. Future studies will use surface imaging to determine surface patch algorithms that utilize the entire chest as well as thoracic and abdominal breathing relationships.

Feasibility of MR-guided radiotherapy using beam-eye-view 2D-cine with tumor-volume projection

PURPOSE

Current magnetic resonance imaging (MRI) guided radiotherapy (MRgRT) applies sagittal/coronal 2D-cine to monitor major tumor motions, however, the beam eye's view (BEV) with volumetric tumor projection would be the best measure for radiation beam conformality, independent of tumor through-plane motion. The goal is to assess the feasibility, accuracy, and performance of the BEV approach.

METHODS

Beam-specific BEV 2D-cine with volume-projected tumor contours were simulated to establish a 2D/3D tumor match against a tumor-motion library based on multi-breath time-resolved (TR) 4DMRI images. Two BEV-library-matching methods were developed: (1) fast screening with tumor center-of-mass (∆COM), in-plane area ratio, and DICE similarity, and finalizing with the highest DICE score and (2) DICE screening for top-3 candidates and finalizing with rigid registration. A 4D-XCAT digital phantom and 8 lung-cancer patients were used for assessment. For each patient, 3 sets of 40 s TR-4DMRI were acquired at 2 Hz and 6 representative BEV were created with the isocenter set at tumor COM in mid-respiration. One TR-4DMRI set (40 × 2 = 80-images) was used to simulate BEV 2D-cine and the other two (160-images) were used to create a library. The matching result was validated against the ground truth within the test set. Using a leave-one-out strategy, the success rate, accuracy, and speed of tumor matching were assessed for volume-projected tumors over 11520 time-points (=8patients•3sets•80images•6BEVs).

RESULTS

Volume-projected tumor contour area on the 6 BEVs varies by 60% ± 8% and [Formula: see text] (in-plane/volume-projected) varies by 82% ± 9%. The [Formula: see text] changes with tumor shape, orientation, and through-plane motion. Method-1 produces 96% matching success (ΔCOM = 0.7 ± 0.2 mm, [Formula: see text]=1.01 ± 0.02, Dice=0.92 ± 0.02) with the computational time of 15 ± 1 ms/match, while method-2 produces 94% ± 1% success (ΔCOM = 0.2 ± 0.1 mm, [Formula: see text]=1.00 ± 0.01, Dice = 0.94 ± 0.02) with 223 ± 13 ms/match.

CONCLUSION

This study has demonstrated the feasibility, accuracy, and benefits of BEV 2D-cine imaging with tumor-volume projection, allowing real-time tumor motion monitoring and beam conformality checking. Further clinical evaluation is necessary before MRgRT applications.

Enhanced super-resolution reconstruction of T1w time-resolved 4DMRI in low-contrast tissue using 2-step hybrid deformable image registration

Purpose

Deformable image registration (DIR) in low‐contrast tissues is often suboptimal because of low visibility of landmarks, low driving‐force to deform, and low penalty for misalignment. We aim to overcome the shortcomings for improved reconstruction of time‐resolved four‐dimensional magnetic resonance imaging (TR‐4DMRI).

Methods and Materials

Super‐resolution TR‐4DMRI reconstruction utilizes DIR to combine high‐resolution (highR:2x2x2mm³) breath‐hold (BH) and low‐resolution (lowR:5x5x5mm³) free‐breathing (FB) 3D cine (2Hz) images to achieve clinically acceptable spatiotemporal resolution. A 2‐step hybrid DIR approach was developed to segment low‐dynamic‐range (LDR) regions: low‐intensity lungs and high‐intensity “bodyshell” (=body‐lungs) for DIR refinement after conventional DIR. The intensity in LDR regions was renormalized to the full dynamic range (FDR) to enhance local tissue contrast. A T1‐mapped 4D XCAT digital phantom was created, and seven volunteers and five lung cancer patients were scanned with two BH and one 3D cine series per subject to compare the 1‐step conventional and 2‐step hybrid DIR using: (a) the ground truth in the phantom, (b) highR‐BH references, which were used to simulate 3D cine images by down‐sampling and Rayleigh‐noise‐adding, and (c) cross‐verification between two TR‐4DMRI images reconstructed from two BHs. To assess DIR improvement, 8‐17 blood vessel bifurcations were used in volunteers, and lung tumor position, size, and shape were used in phantom and patients, together with the voxel intensity correlation (VIC), structural similarity (SSIM), and cross‐consistency check (CCC).

Results

The 2‐step hybrid DIR improves contrast and DIR accuracy. In volunteers, it improves low‐contrast alignment from 6.5 ± 1.8 mm to 3.3 ± 1.0 mm. In phantom, it improves tumor center of mass alignment (COM = 1.3 ± 0.2 mm) and minimizes DIR directional difference. In patients, it produces almost‐identical tumor COM, size, and shape (dice> 0.85) as the reference. The VIC and SSIM are significantly increased and the number of CCC outliers are reduced by half.

Conclusion

The 2‐step hybrid DIR improves low‐contrast‐tissue alignment and increases lung tumor fidelity. It is recommended to adopt the 2‐step hybrid DIR for TR‐4DMRI reconstruction.

A modern review of the uncertainties in volumetric imaging of respiratory-induced target motion in lung radiotherapy

Radiotherapy has become a critical component for the treatment of all stages and types of lung cancer, often times being the primary gateway to a cure. However, given that radiation can cause harmful side effects depending on how much surrounding healthy tissue is exposed, treatment of the lung can be particularly challenging due to the presence of moving targets. Careful implementation of every step in the radiotherapy process is absolutely integral for attaining optimal clinical outcomes. With the advent and now widespread use of stereotactic body radiation therapy (SBRT), where extremely large doses are delivered, accurate, and precise dose targeting is especially vital to achieve an optimal risk to benefit ratio. This has largely become possible due to the rapid development of image-guided technology. Although imaging is critical to the success of radiotherapy, it can often be plagued with uncertainties due to respiratory-induced target motion. There has and continues to be an immense research effort aimed at acknowledging and addressing these uncertainties to further our abilities to more precisely target radiation treatment. Thus, the goal of this article is to provide a detailed review of the prevailing uncertainties that remain to be investigated across the different imaging modalities, as well as to highlight the more modern solutions to imaging motion and their role in addressing the current challenges.

Artificial intelligence in radiotherapy: a technological review

Radiation therapy (RT) is widely used to treat cancer. Technological advances in RT have occurred in the past 30 years. These advances, such as three-dimensional image guidance, intensity modulation, and robotics, created challenges and opportunities for the next breakthrough, in which artificial intelligence (AI) will possibly play important roles. AI will replace certain repetitive and labor-intensive tasks and improve the accuracy and consistency of others, particularly those with increased complexity because of technological advances. The improvement in efficiency and consistency is important to manage the increasing cancer patient burden to the society. Furthermore, AI may provide new functionalities that facilitate satisfactory RT. The functionalities include superior images for real-time intervention and adaptive and personalized RT. AI may effectively synthesize and analyze big data for such purposes. This review describes the RT workflow and identifies areas, including imaging, treatment planning, quality assurance, and outcome prediction, that benefit from AI. This review primarily focuses on deep-learning techniques, although conventional machine-learning techniques are also mentioned.

Evaluation of MRI-derived surrogate signals to model respiratory motion

An MR-Linac can provide motion information of tumour and organs-at-risk before, during, and after beam delivery. However, MR imaging cannot provide real-time high-quality volumetric images which capture breath-to-breath variability of respiratory motion. Surrogate-driven motion models relate the motion of the internal anatomy to surrogate signals, thus can estimate the 3D internal motion from these signals. Internal surrogate signals based on patient anatomy can be extracted from 2D cine-MR images, which can be acquired on an MR-Linac during treatment, to build and drive motion models. In this paper we investigate different MRI-derived surrogate signals, including signals generated by applying principal component analysis to the image intensities, or control point displacements derived from deformable registration of the 2D cine-MR images. We assessed the suitability of the signals to build models that can estimate the motion of the internal anatomy, including sliding motion and breath-to-breath variability. We quantitatively evaluated the models by estimating the 2D motion in sagittal and coronal slices of 8 lung cancer patients, and comparing them to motion measurements obtained from image registration. For sagittal slices, using the first and second principal components on the control point displacements as surrogate signals resulted in the highest model accuracy, with a mean error over patients around 0.80 mm which was lower than the in-plane resolution. For coronal slices, all investigated signals except the skin signal produced mean errors over patients around 1 mm. These results demonstrate that surrogate signals derived from 2D cine-MR images, including those generated by applying principal component analysis to the image intensities or control point displacements, can accurately model the motion of the internal anatomy within a single sagittal or coronal slice. This implies the signals should also be suitable for modelling the 3D respiratory motion of the internal anatomy.

A super-resolution framework for the reconstruction of T2-weighted (T2w) time-resolved (TR) 4DMRI using T1w TR-4DMRI as the guidance

PURPOSE

The purpose of this study was to develop T2-weighted (T2w) time-resolved (TR) four-dimensional magnetic resonance imaging (4DMRI) reconstruction technique with higher soft-tissue contrast for multiple breathing cycle motion assessment by building a super-resolution (SR) framework using the T1w TR-4DMRI reconstruction as guidance.

METHODS

The multi-breath T1w TR-4DMRI was reconstructed by deforming a high-resolution (HR: 2 × 2 × 2 mm³ ) volumetric breath-hold (BH, 20s) three-dimensional magnetic resonance imaging (3DMRI) image to a series of low-resolution (LR: 5 × 5 × 5 mm³ ) 3D cine images at a 2Hz frame rate in free-breathing (FB, 40 s) using an enhanced Demons algorithm, namely [T1^BH →FB] reconstruction. Within the same imaging session, respiratory-correlated (RC) T2w 4DMRI (2 × 2 × 2 mm³ ) was acquired based on an internal navigator to gain HR T2w (T2^HR ) in three states (full exhalation and mid and full inhalation) in ~5 min. Minor binning artifacts in the RC-4DMRI were automatically identified based on voxel intensity correlation (VIC) between consecutive slices as outliers (VIC < VIC^mean -σ) and corrected by deforming the artifact slices to interpolated slices from the adjacent slices iteratively until no outliers were identified. A T2^HR image with minimal deformation (<1 cm at the diaphragm) from the T1^BH image was selected for multi-modal B-Spline deformable image registration (DIR) to establish the T2^HR -T1^BH voxel correspondence. Two approaches to reconstruct T2w TR-4DMRI were investigated: (A) T2^HR →[T1^BH →FB]: to deform T2w HR to T1w BH only as T1w TR-4DMRI was reconstructed, and combine the two displacement vector fields (DVFs) to reconstruct T2w TR-4DMRI, and (B) [T2^HR ←T1^BH ]→FB: to deform T1w BH to T2w HR first and apply the deformed T1w BH to reconstruct T2w TR-4DMRI. The reconstruction times were similar, 8-12 min per volume. To validate the two methods, T2w- and T1w-mapped 4D XCAT digital phantoms were utilized with three synthetic spherical tumors (ϕ = 2.0, 3.0, and 4.0 cm) in the lower or mid lobes as the ground truth to evaluate the tumor location (the center of mass, COM), size (volume ratio, %V), and shape (Dice index). Six lung cancer patients were scanned under an IRB-approved protocol and the T2w TR-4DMRI images reconstructed from the two methods were compared based on the preservation of the three tumor characteristics. The local tumor-contained image quality was also characterized using the VIC and structure similarity (SSIM) indexes.

RESULTS

In the 4D digital phantom, excellent tumor alignment after T2^HR -T1^HR DIR is achieved: ∆COM = 0.8 ± 0.5 mm, %V = 1.06 ± 0.02, and Dice = 0.91 ± 0.03, in both deformation directions using the DIR-target image as the reference. In patients, binning artifacts are corrected with improved image quality: average VIC increases from 0.92 ± 0.03 to 0.95 ± 0.01. Both T2w TR-4DMRI reconstruction methods produce similar tumor alignment errors ∆COM = 2.9 ± 0.6 mm. However, method B ([T2^HR ←T1^BH ]→FB) produces superior results in preserving more T2w tumor features with a higher %V = 0.99 ± 0.03, Dice = 0.81 ± 0.06, VIC = 0.85 ± 0.06, and SSIM = 0.65 ± 0.10 in the T2w TR-4DMRI images.

CONCLUSIONS

This study has demonstrated the feasibility of T2w TR-4DMRI reconstruction with high soft-tissue contrast and adequately-preserved tumor position, size, and shape in multiple breathing cycles. The T2w-centric DIR (method B) produces a superior solution for the SR-based framework of T2w TR-4DMRI reconstruction with highly preserved tumor characteristics and local image features, which are useful for tumor delineation and motion management in radiation therapy.

Clinical evaluation of 4D MRI in the delineation of gross and internal tumor volumes in comparison with 4DCT

Purpose

To evaluate clinical utility of respiratory‐correlated (RC) four‐dimensional magnetic resonance imaging (4DMRI) for lung tumor delineation and motion assessment, in comparison with the current clinical standard of 4D computed tomography (4DCT).

Methods and Materials

A prospective T2‐weighted (T2w) RC‐4DMRI technique was applied to acquire coronal 4DMRI images for 14 lung cancer patients (16 lesions) during free breathing (FB) under an IRB‐approved protocol, together with a breath‐hold (BH) T1w 3DMRI and axial 4DMRI. Clinical simulation CT and 4DCT were acquired within 2 h. An internal navigator was applied to trigger amplitude‐binned 4DMRI acquisition whereas a bellows or real‐time position management (RPM) was used in the 4DCT reconstruction. Six radiation oncologists manually delineated the gross and internal tumor volumes (GTV and ITV) in 399 3D images using programmed clinical workflows under a tumor delineation guideline. The ITV was the union of GTVs within the breathing cycle without margin. Average GTV and motion range were assessed and ITV variation between 4DMRI and 4DCT was evaluated using the Dice similarity index, mean distance agreement (MDA), and volume difference.

Results

The mean tumor volume is similar between 4DCT (GTV^4DCT = 1.0, as the reference) and T2w‐4DMRI (GTV^T2wMR = 0.97), but smaller in T1w MRI (GTV^T1wMR = 0.76), suggesting possible peripheral edema around the tumor. Average GTV variation within the breathing cycle (22%) in 4DMRI is slightly greater than 4DCT (17%). GTV motion variation (−4 to 12 mm) and ITV variation (∆V^ITV=−25 to 95%) between 4DCT and 4DMRI are large, confirmed by relatively low ITV similarity (Dice = 0.72 ± 0.11) and large MDA = 2.9 ± 1.5 mm.

Conclusion

Average GTVs are similar between T2w‐4DMRI and 4DCT, but smaller by 25% in T1w BH MRI. Physician training and breathing coaching may be necessary to reduce ITV variability between 4DMRI and 4DCT. Four‐dimensional magnetic resonance imaging is a promising and viable technique for clinical lung tumor delineation and motion assessment.

Respiratory-Correlated (RC) vs. Time-Resolved (TR) Four-Dimensional Magnetic Resonance Imaging (4DMRI) for Radiotherapy of Thoracic and Abdominal Cancer

Recent technological and clinical advancements of both respiratory-correlated (RC) and time-resolved (TR) four-dimensional magnetic resonance imaging (4DMRI) techniques are reviewed in light of tumor/organ motion simulation, monitoring, and assessment in radiotherapy. For radiotherapy of thoracic and abdominal cancer, respiratory-induced tumor motion, and motion variation due to breathing irregularities are the major uncertainties in treatment. RC-4DMRI is developed to assess tumor motion for treatment planning, whereas TR-4DMRI is developed to assess both motion and motion variation for treatment planning, delivery and assessment. RC-4DMRI is reconstructed to provide one-breathing-cycle motion, similar to 4D computed tomography (4DCT), the current clinical standard, but with higher soft-tissue contrast, no ionizing radiation, and less binning artifacts due to the use of an internal respiratory surrogate. Recent studies have shown that its spatial resolution has reached or exceeded that of 4DCT and scanning time becomes clinically acceptable. TR-4DMRI is recently developed with an adequate spatiotemporal resolution to assess tumor motion and motion variations for treatment simulation, delivery and assessment. The super-resolution approach is most promising since it can image any organ/body motion, whereas RC-4D MRI are limited to resolve only respiration-induced motion and some TR-4DMRI approaches may more or less depend on RC-4DMRI. TR-4DMRI provides multi-breath motion data that are useful not only in MR-guided radiotherapy but also for building a patient-specific motion model to guide radiotherapy treatment using an non-MR-equipped linear accelerator. Based on 4DMRI motion data, motion-corrected dynamic contrast imaging and diffusion-weighted imaging have also been reported, aiming to facilitate tumor delineation for more accurate radiotherapy targeting. Both RC- and TR-4DMRI have been evaluated for potential clinical applications, such as delineation of tumor volumes, where sufficiently high spatial resolution and large field-of-view are required. The 4DMRI techniques are promising to play a role in motion assessment in radiotherapy treatment planning, delivery, assessment, and adaptation.

Effects of age-related breathing characteristics on the performance of four-dimensional magnetic resonance imaging reconstructed by prospective gating for radiation therapy planning

Background and purpose

Four-dimensional magnetic resonance imaging (4D MRI) has advanced recently by incorporating prospective gating, but its performance on pediatric populations has not been investigated. This study aimed to determine the age-related performance of prospective gating, as compared with retrospective sorting.

Materials and methods

Prospectively gated 4D MRI scans were acquired on a motion phantom driven by real respiratory waveforms obtained from 23 pediatric and young adult patients (aged 5–24 years). The correlations between patient-specific breathing characteristics and the performance of 4D MRI were comparatively evaluated against retrospective sorting for the same scan time. For six patients who underwent both 4D MRI and 4D CT, the internal target volumes (ITVs) determined by the two modalities were compared.

Results

Longer scan time and greater sorting error were most highly correlated (P < 0.001) with breathing irregularity and extent of diaphragm motion, but age was not a strong covariate because of interindividual variation. Prospective gating was more accurate than retrospective sorting except for those patients with severe breathing irregularity (peak-to-peak coefficient of variation >30%). The ITVs of 4D MRI and 4D CT were comparable (Dice similarity: >90%) unless the breathing characteristics changed between the two imaging sessions.

Conclusions

For most patients analyzed in this study, prospective gating provided more accurate 4D MRI (95th percentile of deviation: <1.5 mm) than did retrospective sorting within a clinically feasible scan time (median: 5.9 min). The 4D MRI tended to take longer and to give larger sorting errors with deeper and irregular breathers.

A novel amplitude binning strategy to handle irregular breathing during 4DMRI acquisition: improved imaging for radiotherapy purposes

Background

For radiotherapy of abdominal cancer, four-dimensional magnetic resonance imaging (4DMRI) is desirable for tumor definition and the assessment of tumor and organ motion. However, irregular breathing gives rise to image artifacts. We developed a outlier rejection strategy resulting in a 4DMRI with reduced image artifacts in the presence of irregular breathing.

Methods

We obtained 2D T2-weighted single-shot turbo spin echo images, with an interleaved 1D navigator acquisition to obtain the respiratory signal during free breathing imaging in 2 patients and 12 healthy volunteers. Prior to binning, upper and lower inclusion thresholds were chosen such that 95% of the acquired images were included, while minimizing the distance between the thresholds (inclusion range (IR)). We compared our strategy (Min95) with three commonly applied strategies: phase binning with all images included (Phase), amplitude binning with all images included (MaxIE), and amplitude binning with the thresholds set as the mean end-inhale and mean end-exhale diaphragm positions (MeanIE). We compared 4DMRI quality based on:

Data included (DI); percentage of images remaining after outlier rejection.

Reconstruction completeness (RC); percentage of bin-slice combinations containing at least one image after binning.

Intra-bin variation (IBV); interquartile range of the diaphragm position within the bin-slice combination, averaged over three central slices and ten respiratory bins.

IR.

Image smoothness (S); quantified by fitting a parabola to the diaphragm profile in a sagittal plane of the reconstructed 4DMRI.

A two-sided Wilcoxon’s signed-rank test was used to test for significance in differences between the Min95 strategy and the Phase, MaxIE, and MeanIE strategies.

Results

Based on the fourteen subjects, the Min95 binning strategy outperformed the other strategies with a mean RC of 95.5%, mean IBV of 1.6 mm, mean IR of 15.1 mm and a mean S of 0.90. The Phase strategy showed a poor mean IBV of 6.2 mm and the MaxIE strategy showed a poor mean RC of 85.6%, resulting in image artifacts (mean S of 0.76). The MeanIE strategy demonstrated a mean DI of 85.6%.

Conclusions

Our Min95 reconstruction strategy resulted in a 4DMRI with less artifacts and more precise diaphragm position reconstruction compared to the other strategies.

Trial registration

Volunteers: protocol W15_373#16.007; patients: protocol NL47713.018.14

Electronic supplementary material

The online version of this article (10.1186/s13014-019-1279-z) contains supplementary material, which is available to authorized users.

Enhancement of Long-Term External-Internal Correlation by Phase-Shift Detection and Correction Based on Concurrent External Bellows and Internal Navigator Signals

Purpose

The purpose of this study was to enhance the correlation between external and internal respiratory motions by dynamically determining and correcting the patient-specific phase shift between external and internal respiratory waveforms acquired concurrently during respiratory-correlated 4-dimensional magnetic resonance imaging scans.

Methods and Materials

Internal-navigator and external-bellows waveforms were acquired simultaneously during 6- to 15-minute respiratory-correlated 4-dimensional magnetic resonance imaging scans in 10 healthy participants under an institutional review board–approved protocol. The navigator was placed at the right lung–diaphragm interface, and the bellows were placed ∼5 cm inferior to the sternum. Three segments of each respiratory waveform, at the beginning, middle, and end of a scan, were analyzed. Three phase-domain methods were employed to estimate the phase shift, including analytical signal analysis, phase-space oval fitting, and principal component analysis. A robust strategy for estimating the phase shift was realized by combining these methods in a weighted average and by eliminating outliers (>2 σ) caused by breathing irregularities. Whether phase-shift correction affects the external-internal correlation was evaluated. The cross-correlation between the 2 waveforms in the time domain provided an independent check of the correlation enhancement.

Results

Phase-shift correction significantly enhanced the external-internal correlation in all participants across the entire 6- to 15-minute scans. On average, the correlation increased from 0.45 ± 0.28 to 0.85 ± 0.15 for the combined method. The combined method exhibited a 99.5% success rate and revealed that the phase of the external waveform leads that of the internal waveform in all 10 participants by 57 ^o ± 17^o (1.6 ± 0.5 bins) on average. Seven participants exhibited highly reproducible phase shifts over time, evidenced by standard deviations (σ) < 4^o, whereas 8^o < σ < 12^o in the remaining 3 participants. Regardless, phase-shift correction significantly improved the correlation in all participants.

Conclusions

Correcting the phase shift estimated by the phase-domain methods provides a new approach for enhancing the correlation between external and internal respiratory motions. This strategy holds promise for improving the accuracy of respiratory-gated radiation therapy.

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.

Super-resolution T2-weighted 4D MRI for image guided radiotherapy

BACKGROUND AND PURPOSE

The superior soft-tissue contrast of 4D-T2w MRI motivates its use for delineation in radiotherapy treatment planning. We address current limitations of slice-selective implementations, including thick slices and artefacts originating from data incompleteness and variable breathing.

MATERIALS AND METHODS

A method was developed to calculate midposition and 4D-T2w images of the whole thorax from continuously acquired axial and sagittal 2D-T2w MRI (1.5 × 1.5 × 5.0 mm3). The method employed image-derived respiratory surrogates, deformable image registration and super-resolution reconstruction. Volunteer imaging and a respiratory motion phantom were used for validation. The minimum number of dynamic acquisitions needed to calculate a representative midposition image was investigated by retrospectively subsampling the data (10-30 dynamic acquisitions).

RESULTS

Super-resolution 4D-T2w MRI (1.0 × 1.0 × 1.0 mm3, 8 respiratory phases) did not suffer from data incompleteness and exhibited reduced stitching artefacts compared to sorted multi-slice MRI. Experiments using a respiratory motion phantom and colour-intensity projection images demonstrated a minor underestimation of the motion range. Midposition diaphragm differences in retrospectively subsampled acquisitions were <1.1 mm compared to the full dataset. 10 dynamic acquisitions were found sufficient to generate midposition MRI.

CONCLUSIONS

A motion-modelling and super-resolution method was developed to calculate high quality 4D/midposition T2w MRI from orthogonal 2D-T2w MRI.

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.

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

PURPOSE

The purpose of this study was to enhance the deformation range of demons-based deformable image registration (DIR) for large respiration-induced organ motion in the reconstruction of time-resolved four-dimensional magnetic resonance imaging (TR-4DMRI) for multi-breath motion simulation.

METHODS

A demons-based DIR algorithm was modified to enhance the deformation range for TR-4DMRI reconstruction using the super-resolution approach. A pseudo demons force was introduced to accelerate the coarse deformation in a multi-resolution (n = 3) DIR approach. The intensity gradient of a voxel was applied to its neighboring (5 × 5 × 5) voxels with a weight of Gaussian probability profile (σ = 1 voxel) to extend the demons force, especially on those voxels that have little intensity gradience but high-intensity difference. A digital 4DMRI phantom with 3-8 cm diaphragmatic motions was used for DIR comparison. Six volunteers were scanned with two high-resolution (highR: 2 × 2 × 2 mm³ ) breath-hold (BH) 3DMR images at full inhalation (BHI) and full exhalation (BHE) and low-resolution (lowR: 5 × 5 × 5 mm³ ) free-breathing (FB) 3DMR cine images (2 Hz) under an IRB-approved protocol. A cross-consistency check (CCC) (BHI→FB←BHE), with voxel intensity correlation (VIC) and inverse consistency error (ICE), was introduced for cross-verification of TR-4DMRI reconstruction.

RESULTS

Using the digital phantom, the maximum deformable magnitude is doubled using the modified DIR from 3 to 6 cm at the diaphragm. In six human subjects, the first 15-iteration DIR using the pseudo force deforms 200 ± 150% more than the original force, and succeeds in all 12 cases, whereas the original demons-based DIR failed in 67% of tested cases. Using the pseudo force, high VIC (>0.9) and small ICE (1.6 ± 0.6 mm) values are observed for DIR of BHI&BHE, BHI→FB, and BHE→FB. The CCC identifies four questionable cases, in which two cases need further DIR refinement, without missing true negative.

CONCLUSIONS

The introduction of a pseudo demons force enhances the largest deformation magnitude up to 6 cm. The cross-consistency check ensures the quality of TR-4DMRI reconstruction. Further investigation is ongoing to fully characterize TR-4DMRI for potential multi-breathing-cycle radiotherapy simulation.

Comparison of four dimensional computed tomography and magnetic resonance imaging in abdominal radiotherapy planning

Background and Purpose

Four-dimensional (4D) computed tomography (CT) is widely used in radiotherapy (RT) planning and remains the current standard for motion evaluation. We assess a 4D magnetic resonance imaging (MRI) sequence in terms of motion and image quality in a phantom, healthy volunteers and patients undergoing RT.

Materials and Methods

The 4D-MRI sequence is a prototype T1-weighted 3D gradient echo with radial acquisition with self-gating. The accuracy of the 4D-MRI respiratory sorting based method was assessed using a MRI-CT compatible respiratory simulation phantom. In volunteers, abdominal viscera were evaluated for artefact, noise, structure delineation and overall image quality using a previously published four-point scoring system. In patients undergoing abdominal RT, the tumour (or a surrogate) was utilized to assess the range of motion on both 4D-CT and 4D-MRI. Furthermore, imaging quality was evaluated for both 4D-CT and 4D-MRI.

Results

In phantom studies 4D-MRI demonstrated amplitude of motion error of less than 0.2 mm for five, seven and ten bins. 4D-MRI provided excellent image quality for liver, kidney and pancreas. In patients, the median amplitude of motion seen on 4D-CT and 4D-MRI was 11.2 mm (range 2.8–20.3 mm) and 10.1 mm (range 0.7–20.7 mm) respectively. The median difference in amplitude between 4D-CT and 4D-MRI was −0.6 mm (range −3.4–5.2 mm). 4D-MRI demonstrated superior edge detection (median score 3 versus 1) and overall image quality (median score 2 versus 1) compared to 4D-CT.

Conclusions

The prototype 4D-MRI sequence demonstrated promising results and may be used in abdominal targeting, motion gating, and towards implementing MRI-based adaptive RT.

Evaluation of automatic contour propagation in T2-weighted 4DMRI for normal-tissue motion assessment using internal organ-at-risk volume (IRV)

Purpose

The purpose of this study was to evaluate the quality of automatically propagated contours of organs at risk (OARs) based on respiratory‐correlated navigator‐triggered four‐dimensional magnetic resonance imaging (RC‐4DMRI) for calculation of internal organ‐at‐risk volume (IRV) to account for intra‐fractional OAR motion.

Methods and Materials

T2‐weighted RC‐4DMRI images were of 10 volunteers acquired and reconstructed using an internal navigator‐echo surrogate and concurrent external bellows under an IRB‐approved protocol. Four major OARs (lungs, heart, liver, and stomach) were delineated in the 10‐phase 4DMRI. Two manual‐contour sets were delineated by two clinical personnel and two automatic‐contour sets were propagated using free‐form deformable image registration. The OAR volume variation within the 10‐phase cycle was assessed and the IRV was calculated as the union of all OAR contours. The OAR contour similarity between the navigator‐triggered and bellows‐rebinned 4DMRI was compared. A total of 2400 contours were compared to the most probable ground truth with a 95% confidence level (S95) in similarity, sensitivity, and specificity using the simultaneous truth and performance level estimation (STAPLE) algorithm.

Results

Visual inspection of automatically propagated contours finds that approximately 5–10% require manual correction. The similarity, sensitivity, and specificity between manual and automatic contours are indistinguishable (P > 0.05). The Jaccard similarity indexes are 0.92 ± 0.02 (lungs), 0.89 ± 0.03 (heart), 0.92 ± 0.02 (liver), and 0.83 ± 0.04 (stomach). Volume variations within the breathing cycle are small for the heart (2.6 ± 1.5%), liver (1.2 ± 0.6%), and stomach (2.6 ± 0.8%), whereas the IRV is much larger than the OAR volume by: 20.3 ± 8.6% (heart), 24.0 ± 8.6% (liver), and 47.6 ± 20.2% (stomach). The Jaccard index is higher in navigator‐triggered than bellows‐rebinned 4DMRI by 4% (P < 0.05), due to the higher image quality of navigator‐based 4DMRI.

Conclusion

Automatic and manual OAR contours from Navigator‐triggered 4DMRI are not statistically distinguishable. The navigator‐triggered 4DMRI image provides higher contour quality than bellows‐rebinned 4DMRI. The IRVs are 20–50% larger than OAR volumes and should be considered in dose estimation.

A Self-Sorting Coronal 4D-MRI Method for Daily Image Guidance of Liver Lesions on an MR-LINAC

PURPOSE

Novel hybrid MR-LINAC devices provide MRI's superior soft-tissue contrast in the treatment room and thus have the potential to increase accuracy of liver stereotactic body radiation therapy (SBRT). Requirements for daily position verification using 4-dimensional MRI include tumor visibility and short acquisition-reconstruction time (preferably <5 min). The proposed method provides fast acquisition-reconstruction time and the flexibility to vary T1- and T2-weighting, using standard imaging sequences for straightforward implementation on an MR-LINAC.

METHODS AND MATERIALS

Images were acquired using a coronal 2-dimensional, multislice, single-shot turbo spin-echo (TSE) and turbo field-echo (TFE) sequence, which were repeated 30 times. An image-based self-sorting signal (ImS) was extracted from the data, and rigid registration of the diaphragm per slice position was performed and corrected for amplitude variation in the anteroposterior direction. Data were sorted into 10 bins according to amplitude and phase. ImS was validated in 4 healthy volunteers against a navigator signal. Positional variations within bins, missing data, and smoothness of the liver dome were compared between amplitude and phase binning in 10 volunteers. Tumor contrast and registration were investigated in 3 patients.

RESULTS

Each ImS was found to be in excellent agreement with the navigator signal with a correlation coefficient of >0.95 and binning differences of <1 bin. Better liver dome smoothness per bin in case of amplitude binning compared with that in phase binning (2.0-2.6 mm vs 2.4-3.7 mm, respectively) is a tradeoff for more missing data (3.5%-17.5% vs 3.5%-4.7%, respectively). Liver lesions were visible in almost all coronal TSE and TFE images, but the lesion boundary was better defined in the TSE images. Rigid registrations could be performed on the tumor area.

CONCLUSIONS

An efficient self-sorted 4-dimensional MRI method was developed and validated using standard sequences and fast reconstruction on a LINAC-integrated MRI scanner providing good tumor visibility for daily image-guided liver stereotactic body radiation therapy.

T2-Weighted 4D Magnetic Resonance Imaging for Application in Magnetic Resonance-Guided Radiotherapy Treatment Planning

OBJECTIVES

The aim of this study was to develop and verify a method to obtain good temporal resolution T2-weighted 4-dimensional (4D-T2w) magnetic resonance imaging (MRI) by using motion information from T1-weighted 4D (4D-T1w) MRI, to support treatment planning in MR-guided radiotherapy.

MATERIALS AND METHODS

Ten patients with primary non-small cell lung cancer were scanned at 1.5 T axially with a volumetric T2-weighted turbo spin echo sequence gated to exhalation and a volumetric T1-weighted stack-of-stars spoiled gradient echo sequence with golden angle spacing acquired in free breathing. From the latter, 20 respiratory phases were reconstructed using the recently developed 4D joint MoCo-HDTV algorithm based on the self-gating signal obtained from the k-space center. Motion vector fields describing the respiratory cycle were obtained by deformable image registration between the respiratory phases and projected onto the T2-weighted image volume. The resulting 4D-T2w volumes were verified against the 4D-T1w volumes: an edge-detection method was used to measure the diaphragm positions; the locations of anatomical landmarks delineated by a radiation oncologist were compared and normalized mutual information was calculated to evaluate volumetric image similarity.

RESULTS

High-resolution 4D-T2w MRI was obtained. Respiratory motion was preserved on calculated 4D-T2w MRI, with median diaphragm positions being consistent with less than 6.6 mm (2 voxels) for all patients and less than 3.3 mm (1 voxel) for 9 of 10 patients. Geometrical positions were coherent between 4D-T1w and 4D-T2w MRI as Euclidean distances between all corresponding anatomical landmarks agreed to within 7.6 mm (Euclidean distance of 2 voxels) and were below 3.8 mm (Euclidean distance of 1 voxel) for 355 of 470 pairs of anatomical landmarks. Volumetric image similarity was commensurate between 4D-T1w and 4D-T2w MRI, as mean percentage differences in normalized mutual information (calculated over all respiratory phases and patients), between corresponding respiratory phases of 4D-T1w and 4D-T2w MRI and the tie-phase of 4D-T1w and 3-dimensional T2w MRI, were consistent to 0.41% ± 0.37%. Four-dimensional T2w MRI displayed tumor extent, structure, and position more clearly than corresponding 4D-T1w MRI, especially when mobile tumor sites were adjacent to organs at risk.

CONCLUSIONS

A methodology to obtain 4D-T2w MRI that retrospectively applies the motion information from 4D-T1w MRI to 3-dimensional T2w MRI was developed and verified. Four-dimensional T2w MRI can assist clinicians in delineating mobile lesions that are difficult to define on 4D-T1w MRI, because of poor tumor-tissue contrast.

Novel Super-Resolution Approach to Time-Resolved Volumetric 4-Dimensional Magnetic Resonance Imaging With High Spatiotemporal Resolution for Multi-Breathing Cycle Motion Assessment

PURPOSE

To develop and evaluate a super-resolution approach to reconstruct time-resolved 4-dimensional magnetic resonance imaging (TR-4DMRI) with a high spatiotemporal resolution for multi-breathing cycle motion assessment.

METHODS AND MATERIALS

A super-resolution approach was developed to combine fast 3-dimensional (3D) cine MRI with low resolution during free breathing (FB) and high-resolution 3D static MRI during breath hold (BH) using deformable image registration. A T1-weighted, turbo field echo sequence, coronal 3D cine acquisition, partial Fourier approximation, and SENSitivity Encoding parallel acceleration were used. The same MRI pulse sequence, field of view, and acceleration techniques were applied in both FB and BH acquisitions; the intensity-based Demons deformable image registration method was used. Under an institutional review board-approved protocol, 7 volunteers were studied with 3D cine FB scan (voxel size: 5 × 5 × 5 mm³) at 2 Hz for 40 seconds and a 3D static BH scan (2 × 2 × 2 mm³). To examine the image fidelity of 3D cine and super-resolution TR-4DMRI, a mobile gel phantom with multi-internal targets was scanned at 3 speeds and compared with the 3D static image. Image similarity among 3D cine, 4DMRI, and 3D static was evaluated visually using difference image and quantitatively using voxel intensity correlation and Dice index (phantom only). Multi-breathing-cycle waveforms were extracted and compared in both phantom and volunteer images using the 3D cine as the references.

RESULTS

Mild imaging artifacts were found in the 3D cine and TR-4DMRI of the mobile gel phantom with a Dice index of >0.95. Among 7 volunteers, the super-resolution TR-4DMRI yielded high voxel-intensity correlation (0.92 ± 0.05) and low voxel-intensity difference (<0.05). The detected motion differences between TR-4DMRI and 3D cine were -0.2 ± 0.5 mm (phantom) and -0.2 ± 1.9 mm (diaphragms).

CONCLUSION

Super-resolution TR-4DMRI has been reconstructed with adequate temporal (2 Hz) and spatial (2 × 2 × 2 mm³) resolutions. Further TR-4DMRI characterization and improvement are necessary before clinical applications. Multi-breathing cycles can be examined, providing patient-specific breathing irregularities and motion statistics for future 4D radiation therapy.