The effect of respiratory motion variability and tumor size on the accuracy of average intensity projection from four-dimensional computed tomography: An investigation based on dynamic MRI

A Simulation Study of Tolerance of Breathing Amplitude Variations in Radiotherapy of Lung Cancer Using 4DCT and Time-Resolved 4DMRI

As patient breathing irregularities can introduce a large uncertainty in targeting the internal tumor volume (ITV) of lung cancer patients, and thereby affect treatment quality, this study evaluates dose tolerance of tumor motion amplitude variations in ITV-based volumetric modulated arc therapy (VMAT). A motion-incorporated planning technique was employed to simulate treatment delivery of 10 lung cancer patients' clinical VMAT plans using original and three scaling-up (by 0.5, 1.0, and 2.0 cm) motion waveforms from single-breath four-dimensional computed tomography (4DCT) and multi-breath time-resolved 4D magnetic resonance imaging (TR-4DMRI). The planning tumor volume (PTV = ITV + 5 mm margin) dose coverage (PTV D95%) was evaluated. The repeated waveforms were used to move the isocenter in sync with the clinical leaf motion and gantry rotation. The continuous VMAT arcs were broken down into many static beam fields at the control points (2°-interval) and the composite plan represented the motion-incorporated VMAT plan. Eight motion-incorporated plans per patient were simulated and the plan with the native 4DCT waveform was used as a control. The first (D95% ≤ 95%) and second (D95% ≤ 90%) plan breaching points due to motion amplitude increase were identified and analyzed. The PTV D95% in the motion-incorporated plans was 99.4 ± 1.0% using 4DCT, closely agreeing with the corresponding ITV-based VMAT plan (PTV D95% = 100%). Tumor motion irregularities were observed in TR-4DMRI and triggered D95% ≤ 95% in one case. For small tumors, 4 mm extra motion triggered D95% ≤ 95%, and 6-8 mm triggered D95% ≤ 90%. For large tumors, 14 mm and 21 mm extra motions triggered the first and second breaching points, respectively. This study has demonstrated that PTV D95% breaching points may occur for small tumors during treatment delivery. Clinically, it is important to monitor and avoid systematic motion increase, including baseline drift, and large random motion spikes through threshold-based beam gating.

Comparison of internal target volumes defined by three-dimensional, four-dimensional, and cone-beam computed tomography images of a motion phantom

Background

To explore the variations of the gross tumor volume (GTV) from different three-dimensional computed tomography (3DCT) scan modes and the consistency of internal target volume (ITV) between different 3DCT, cone-beam computed tomography (CBCT) and four-dimensional computed tomography (4DCT) scan, a study using a motion phantom simulating sinusoidal movement was conducted.

Methods

For three 3DCT scan modes: the GTV was contoured, and ITV_I was generated on the basis of GTV with a 10-mm margin while ITV_II and ITV_III with a 0-mm margin on the motion direction. ITV_CBCT and ITV_MIP were contoured on the images of CBCT and maximum-intensity projection (MIP) reconstructed 4DCT images. The centroid position shifts of ITVs were analyzed. The volume consistency between ITV_I, ITV_II, ITV_III and ITV_MIP were evaluated by calculating the Dice similarity coefficient (Dsc) and the value of Δ Volume (ΔV). Furthermore, the 3DCT and CBCT images from 12 NSCLC patients were retrospectively collected, then the Dsc and ΔV were calculated.

Results

The mean ± standard deviation of centroid position of ITV_I, ITV_II and ITV_III were 2.3±4.7, 2.6±4.0, and 1.0±1.4 mm, respectively. The mean ± standard deviation of Dsc between ITV_I, ITV_II, ITV_III and ITV_MIP were 0.78±0.77, 0.86±0.1, and 0.94±0.05, respectively. The ΔV of ITV_I, ITV_II, ITV_III were 29.67%, 17.22%, and 6.46%, respectively. The ITV from CBCT showed a deduction rate of 3.1-9.3% compared to 4DCT. For the patients, the mean Dsc andΔV between ITV_I and ITV_CBCT were 0.50 and 60.76%.

Conclusions

The GTV acquired from 3DCT scan mode I possessed great deviation of centroid position and target volume. ITV on the basis of this GTV was significantly larger than ITV_MIP. A good similarity was showed between ITV_III and ITV_MIP, 4DCT is still a golden standard for the ITV delineation, but in the absence of 4DCT, image from 3DCT scan mode III and KV-CBCT may be considered for ITV delineation with caution.

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.

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.

Development and prospective in-patient proof-of-concept validation of a surface photogrammetry + CT-based volumetric motion model for lung radiotherapy

PURPOSE

We develop and validate a motion model that uses real-time surface photogrammetry acquired concurrently with four-dimensional computed tomography (4DCT) to estimate respiration-induced changes within the entire irradiated volume, over arbitrarily many respiratory cycles.

METHODS

A research, couch-mounted, VisionRT (VRT) system was used to acquire optical surface data (15 Hz, ROI = 15 × 20 cm² ) from the thoraco-abdominal surface of a consented lung SBRT patient, concurrently with their standard-of-care 4DCT. The end-exhalation phase from the 4DCT was regarded as reference and for each remaining phase, deformation vector fields (DVFs) with respect to the reference phase were computed. To reduce dimensionality, the first two principal components (PCs) of the matrix of nine DVFs were calculated. In parallel, ten phase-averaged VRT surfaces were created. Surface DVFs and corresponding PCs were computed. A principal least squares regression was used to relate the PCs of surface DVF to those of volume DVFs, establishing a relationship between time-varying surface and the underlying time-varying volume. Proof-of-concept validation was performed during each treatment fraction by concurrently acquiring 30 s time series of real-time surface data and "ground truth" kV fluoroscopic data (FL). A ray-tracing algorithm was used to create a digitally reconstructed fluorograph (DRF), and motion trajectories of high-contrast, soft-tissue, anatomical features in the DRF were compared with those from kV FL.

RESULTS

For five of the six fluoroscopic acquisition sessions, the model out-performed 4DCT in predicting contour Dice coefficient with respect to fluoroscopy-derived contours. Similarly, the model exhibited a marked improvement over 4DCT for patch positions on the diaphragm. Model patch position errors varied from 5 to -15 mm while 4DCT errors ranged between 5 and -22.4 mm. For one fluoroscopic acquisition, a marked change in the a priori internal-external correlation resulted in model errors comparable to those of 4DCT.

CONCLUSIONS

We described the development and a proof-of-concept validation for a volumetric motion model that uses surface photogrammetry to correlate the time-varying thoraco-abdominal surface to the time-varying internal thoraco-abdominal volume. These early results indicate that the proposed approach can result in a marked improvement over 4DCT. While limited by the duration of the fluoroscopic acquisitions as well as the resolution of the acquired images, the DRF-based proof-of-concept technique developed here is model-agnostic, and therefore, has the potential to be used as an in-patient validation tool for other volumetric motion models.

Dosimetric comparison between three- and four-dimensional computerised tomography radiotherapy for breast cancer

At present, methods of radiotherapy simulation for breast cancer based on four-dimensional computerised tomography (4D-CT) or three-dimensional CT (3D-CT) simulation remain controversial. In the present study, 7 patients with residual breast tissue received whole breast radiotherapy based on 3D-CT and 4D-CT simulation. For the 4D-CT plan, four types of CT images were produced, including images of the end of inspiration and the end of expiration, and images acquired by the maximal intensity projection (MIP) and average intensity projection (AIP). In the 3D-CT plan, the clinical target volume (CTV) and plan target volume (PTV) were marginally higher compared with the 4D-CT plan. In addition, the minimum point dose of the target volume (D_min), the maximum point dose of the target volume (D_max) and the mean point dose of the target volume (D_mean) of the CTV and PTV in the MIP and AIP plans were marginally higher compared with the 3D-CT plan. For the contralateral breast (C-B), volumes of the 4D-CT plan were markedly lower compared with the 3D-CT plan. Furthermore, D_min, D_max and D_mean of the 3D-CT plan were higher compared with the AIP and MIP plans. For the ipsilateral lungs (I-L), volumes of the 3D-CT and AIP plans were higher compared with the MIP plan. Furthermore, when breast lesions were on the left side, for the heart, the volume receiving no less than 40% of the prescription dose (V₄₀) and the volume receiving no less than 30% of the prescription dose (V₃₀) of the MIP and AIP plans were slightly lower compared with those of the 3D plan. In conclusion, 4D-CT radiotherapy based on the MIP and AIP plans provides a slightly smaller radiation area and slightly higher radiotherapy dosage of the CTV and PTV compared with 3D-CT radiotherapy for breast radiotherapy. Therefore, the MIP and AIP plans prevent C-B radiation exposure and improve sparing of the heart and I-L.

Continuous generation of volumetric images during stereotactic body radiation therapy using periodic kV imaging and an external respiratory surrogate

We present a technique for continuous generation of volumetric images during SBRT using periodic kV imaging and an external respiratory surrogate signal to drive a patient-specific PCA motion model. Using the on-board imager, kV radiographs are acquired every 3 s and used to fit the parameters of a motion model so that it matches observed changes in internal patient anatomy. A multi-dimensional correlation model is established between the motion model parameters and the external surrogate position and velocity, enabling volumetric image reconstruction between kV imaging time points. Performance of the algorithm was evaluated using 10 realistic eXtended CArdiac-Torso (XCAT) digital phantoms including 3D anatomical respiratory deformation programmed with 3D tumor positions measured with orthogonal kV imaging of implanted fiducial gold markers. The clinically measured ground truth 3D tumor positions provided a dataset with realistic breathing irregularities, and the combination of periodic on-board kV imaging with recorded external respiratory surrogate signal was used for correlation modeling to account for any changes in internal-external correlation. The three-dimensional tumor positions are reconstructed with an average root mean square error (RMSE) of 1.47 mm, and an average 95th percentile 3D positional error of 2.80 mm compared with the clinically measured ground truth 3D tumor positions. This technique enables continuous 3D anatomical image generation based on periodic kV imaging of internal anatomy without the additional dose of continuous kV imaging. The 3D anatomical images produced using this method can be used for treatment verification and delivered dose computation in the presence of irregular respiratory motion.

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.

Moving targets in 4D-CTs versus MIP and AIP: comparison of patients data to phantom data

Purpose

Maximum (MIP) and average intensity projection (AIP) CTs allow rapid definition of internal target volumes in a 4D-CT. The purpose of this study was to assess the accuracy of these techniques in a large patient cohort in combination with simulations on a lung phantom.

Methods

4DCT data from a self-developed 3D lung phantom and from 50 patients with lung tumors were analyzed. ITVs were contoured in maximum (ITV_MIP) and average intensity projection (ITV_AIP) and subsequently compared to ITVs contoured in 10 phases of a 4D-CT (ITV₁₀). In the phantom study additionally a theoretical target volume was calculated for each motion and compared to the contoured volumes.

Results

ITV₁₀ overestimated the actual target volume by 9.5% whereas ITV_MIP and ITV_AIP lead to an underestimation of − 1.8% and − 11.4% in the phantom study. The ITV_MIP (ITV_AIP) was in average − 10.0% (− 18.7%) smaller compared to the ITV₁₀. In the patient CTs deviations between ITV₁₀ and MIP/AIP were significantly larger (MIP: – 20.2% AIP: -33.7%) compared to this. Tumors adjacent to the chestwall, the mediastinum or the diaphragm showed lower conformity between ITV₁₀ and ITV_MIP (ITV_AIP) compared to tumors solely surrounded by lung tissue. Large tumor diameters (> 3.5 cm) and large motion amplitudes (> 1 cm) were associated with lower conformity between intensity projection CTs and ITV₁₀₋.

Conclusion

The application of MIP and AIP in the clinical practice should not be a standard procedure for every patient, since relevant underestimation of tumor volumes may occur. This is especially true if the tumor borders the mediastinum, the chest wall or the diaphragm and if tumors show a large motion amplitude.

Initial clinical observations of intra- and interfractional motion variation in MR-guided lung SBRT

OBJECTIVE

To evaluate variations in intra- and interfractional tumour motion, and the effect on internal target volume (ITV) contour accuracy, using deformable image registration of real-time two-dimensional-sagittal cine-mode MRI acquired during lung stereotactic body radiation therapy (SBRT) treatments.

METHODS

Five lung tumour patients underwent free-breathing SBRT treatments on the ViewRay system, with dose prescribed to a planning target volume (defined as a 3-6 mm expansion of the 4DCT-ITV). Sagittal slice cine-MR images (3.5 × 3.5 mm² pixels) were acquired through the centre of the tumour at 4 frames per second throughout the treatments (3-4 fractions of 21-32 min). Tumour gross tumour volumes (GTVs) were contoured on the first frame of the MR cine and tracked for the first 20 min of each treatment using offline optical-flow based deformable registration implemented on a GPU cluster. A ground truth ITV (MR-ITV_20 min) was formed by taking the union of tracked GTV contours. Pseudo-ITVs were generated from unions of the GTV contours tracked over 10 s segments of image data (MR-ITV_10 s).

RESULTS

Differences were observed in the magnitude of median tumour displacement between days of treatments. MR-ITV_10 s areas were as small as 46% of the MR-ITV_20 min.

CONCLUSION

An ITV offers a "snapshot" of breathing motion for the brief period of time the tumour is imaged on a specific day. Real-time MRI over prolonged periods of time and over multiple treatment fractions shows that ITV size varies. Further work is required to investigate the dosimetric effect of these results. Advances in knowledge: Five lung tumour patients underwent free-breathing MRI-guided SBRT treatments, and their tumours tracked using deformable registration of cine-mode MRI. The results indicate that variability of both intra- and interfractional breathing amplitude should be taken into account during planning of lung radiotherapy.

A treatment planning comparison between modulated tri-cobalt-60 teletherapy and linear accelerator-based stereotactic body radiotherapy for central early-stage non-small cell lung cancer

We evaluated the feasibility of planning stereotactic body radiotherapy (SBRT) for large central early-stage non-small cell lung cancer with a tri-cobalt-60 (tri-(60)Co) system equipped with real-time magnetic resonance imaging (MRI) guidance, as compared to linear accelerator (LINAC)-based SBRT. In all, 20 patients with large central early-stage non-small cell lung cancer who were treated between 2010 and 2015 with LINAC-based SBRT were replanned using a tri-(60)Co system for a prescription dose of 50Gy in 4 fractions. Doses to organs at risk were evaluated based on established MD Anderson constraints for central lung SBRT. R100 values were calculated as the total tissue volume receiving 100% of the dose (V100) divided by the planning target volume and compared to assess dose conformity. Dosimetric comparisons between LINAC-based and tri-(60)Co SBRT plans were performed using Student׳s t-test and Wilcoxon Ranks test. Blinded reviews by radiation oncologists were performed to assess the suitability of both plans for clinical delivery. The mean planning target volume was 48.3cc (range: 12.1 to 139.4cc). Of the tri-(60)Co SBRT plans, a mean 97.4% of dosimetric parameters per patient met MD Anderson dose constraints, whereas a mean 98.8% of dosimetric parameters per patient were met with LINAC-based SBRT planning (p = 0.056). R100 values were similar between both plans (1.20 vs 1.21, p = 0.79). Upon blinded review by 4 radiation oncologists, an average of 90% of the tri-(60)Co SBRT plans were considered acceptable for clinical delivery compared with 100% of the corresponding LINAC-based SBRT plans (p = 0.17). SBRT planning using the tri-(60)Co system with built-in MRI is feasible and achieves clinically acceptable plans for most central lung patients, with similar target dose conformity and organ at risk dosimetry. The added benefit of real-time MRI-guided therapy may further optimize tumor targeting while improving normal tissue sparing, which warrants further investigation in a prospective feasibility clinical trial.

Common-mask guided image reconstruction (c-MGIR) for enhanced 4D cone-beam computed tomography

Compared to 3D cone beam computed tomography (3D CBCT), the image quality of commercially available four-dimensional (4D) CBCT is severely impaired due to the insufficient amount of projection data available for each phase. Since the traditional Feldkamp-Davis-Kress (FDK)-based algorithm is infeasible for reconstructing high quality 4D CBCT images with limited projections, investigators had developed several compress-sensing (CS) based algorithms to improve image quality. The aim of this study is to develop a novel algorithm which can provide better image quality than the FDK and other CS based algorithms with limited projections. We named this algorithm 'the common mask guided image reconstruction' (c-MGIR).In c-MGIR, the unknown CBCT volume is mathematically modeled as a combination of phase-specific motion vectors and phase-independent static vectors. The common-mask matrix, which is the key concept behind the c-MGIR algorithm, separates the common static part across all phase images from the possible moving part in each phase image. The moving part and the static part of the volumes were then alternatively updated by solving two sub-minimization problems iteratively. As the novel mathematical transformation allows the static volume and moving volumes to be updated (during each iteration) with global projections and 'well' solved static volume respectively, the algorithm was able to reduce the noise and under-sampling artifact (an issue faced by other algorithms) to the maximum extent. To evaluate the performance of our proposed c-MGIR, we utilized imaging data from both numerical phantoms and a lung cancer patient. The qualities of the images reconstructed with c-MGIR were compared with (1) standard FDK algorithm, (2) conventional total variation (CTV) based algorithm, (3) prior image constrained compressed sensing (PICCS) algorithm, and (4) motion-map constrained image reconstruction (MCIR) algorithm, respectively. To improve the efficiency of the algorithm, the code was implemented with a graphic processing unit for parallel processing purposes.Root mean square error (RMSE) between the ground truth and reconstructed volumes of the numerical phantom were in the descending order of FDK, CTV, PICCS, MCIR, and c-MGIR for all phases. Specifically, the means and the standard deviations of the RMSE of FDK, CTV, PICCS, MCIR and c-MGIR for all phases were 42.64  ±  6.5%, 3.63  ±  0.83%, 1.31%  ±  0.09%, 0.86%  ±  0.11% and 0.52 %  ±  0.02%, respectively. The image quality of the patient case also indicated the superiority of c-MGIR compared to other algorithms.The results indicated that clinically viable 4D CBCT images can be reconstructed while requiring no more projection data than a typical clinical 3D CBCT scan. This makes c-MGIR a potential online reconstruction algorithm for 4D CBCT, which can provide much better image quality than other available algorithms, while requiring less dose and potentially less scanning time.

Lung dynamic MRI deblurring using low-rank decomposition and dictionary learning

PURPOSE

Lung dynamic MRI (dMRI) has emerged to be an appealing tool to quantify lung motion for both planning and treatment guidance purposes. However, this modality can result in blurry images due to intrinsically low signal-to-noise ratio in the lung and spatial/temporal interpolation. The image blurring could adversely affect the image processing that depends on the availability of fine landmarks. The purpose of this study is to reduce dMRI blurring using image postprocessing.

METHODS

To enhance the image quality and exploit the spatiotemporal continuity of dMRI sequences, a low-rank decomposition and dictionary learning (LDDL) method was employed to deblur lung dMRI and enhance the conspicuity of lung blood vessels. Fifty frames of continuous 2D coronal dMRI frames using a steady state free precession sequence were obtained from five subjects including two healthy volunteer and three lung cancer patients. In LDDL, the lung dMRI was decomposed into sparse and low-rank components. Dictionary learning was employed to estimate the blurring kernel based on the whole image, low-rank or sparse component of the first image in the lung MRI sequence. Deblurring was performed on the whole image sequences using deconvolution based on the estimated blur kernel. The deblurring results were quantified using an automated blood vessel extraction method based on the classification of Hessian matrix filtered images. Accuracy of automated extraction was calculated using manual segmentation of the blood vessels as the ground truth.

RESULTS

In the pilot study, LDDL based on the blurring kernel estimated from the sparse component led to performance superior to the other ways of kernel estimation. LDDL consistently improved image contrast and fine feature conspicuity of the original MRI without introducing artifacts. The accuracy of automated blood vessel extraction was on average increased by 16% using manual segmentation as the ground truth.

CONCLUSIONS

Image blurring in dMRI images can be effectively reduced using a low-rank decomposition and dictionary learning method using kernels estimated by the sparse component.

Generation of fluoroscopic 3D images with a respiratory motion model based on an external surrogate signal

Respiratory motion during radiotherapy can cause uncertainties in definition of the target volume and in estimation of the dose delivered to the target and healthy tissue. In this paper, we generate volumetric images of the internal patient anatomy during treatment using only the motion of a surrogate signal. Pre-treatment four-dimensional CT imaging is used to create a patient-specific model correlating internal respiratory motion with the trajectory of an external surrogate placed on the chest. The performance of this model is assessed with digital and physical phantoms reproducing measured irregular patient breathing patterns. Ten patient breathing patterns are incorporated in a digital phantom. For each patient breathing pattern, the model is used to generate images over the course of thirty seconds. The tumor position predicted by the model is compared to ground truth information from the digital phantom. Over the ten patient breathing patterns, the average absolute error in the tumor centroid position predicted by the motion model is 1.4 mm. The corresponding error for one patient breathing pattern implemented in an anthropomorphic physical phantom was 0.6 mm. The global voxel intensity error was used to compare the full image to the ground truth and demonstrates good agreement between predicted and true images. The model also generates accurate predictions for breathing patterns with irregular phases or amplitudes.

Evaluation of template matching for tumor motion management with cine-MR images in lung cancer patients

PURPOSE

Accurate determination of tumor position is crucial for successful application of motion compensated radiotherapy in lung cancer patients. This study tested the performance of an automated template matching algorithm in tracking the tumor position on cine-MR images by examining the tracking error and further comparing the tracking error to the interoperator variability of three human reviewers.

METHODS

Cine-MR images of 12 lung cancer patients were analyzed. Tumor positions were determined both automatically with template matching and manually by a radiation oncologist and two additional reviewers trained by the radiation oncologist. Performance of the automated template matching was compared against the ground truth established by the radiation oncologist. Additionally, the tracking error of template matching, defined as the difference in the tumor positions determined with template matching and the ground truth, was investigated and compared to the interoperator variability for all patients in the anterior-posterior (AP) and superior-inferior (SI) directions, respectively.

RESULTS

The median tracking error for ten out of the 12 patients studied in both the AP and SI directions was less than 1 pixel (= 1.95 mm). Furthermore, the median tracking error for seven patients in the AP direction and nine patients in the SI direction was less than half a pixel (= 0.975 mm). The median tracking error was positively correlated with the tumor motion magnitude in both the AP (R = 0.55, p = 0.06) and SI (R = 0.67, p = 0.02) directions. Also, a strong correlation was observed between tracking error and interoperator variability (y = 0.26 + 1.25x, R = 0.84, p < 0.001) with the latter larger.

CONCLUSIONS

Results from this study indicate that the performance of template matching is comparable with or better than that of manual tumor localization. This study serves as preliminary investigations towards developing online motion tracking techniques for hybrid MRI-Linac systems. Accuracy of template matching makes it a suitable candidate to replace the labor intensive manual tumor localization for obtaining the ground truth when testing other motion management techniques.

Feasibility of automated pancreas segmentation based on dynamic MRI

OBJECTIVE

MRI-guided radiotherapy is particularly attractive for abdominal targets with low CT contrast. To fully utilize this modality for pancreas tracking, automated segmentation tools are needed. A hybrid gradient, region growth and shape constraint (hGReS) method to segment two-dimensional (2D) upper abdominal dynamic MRI (dMRI) is developed for this purpose.

METHODS

2D coronal dynamic MR images of two healthy volunteers were acquired with a frame rate of 5 frames per second. The regions of interest (ROIs) included the liver, pancreas and stomach. The first frame was used as the source where the centres of the ROIs were manually annotated. These centre locations were propagated to the next dMRI frame. Four-neighborhood region transfer growth was performed from these initial seeds before refinement using shape constraints. RESULTS from hGReS and two other automated segmentation methods using integrated edge detection and region growth (IER) and level set, respectively, were compared with manual contours using Dice's index (DI).

RESULTS

For the first patient, the hGReS resulted in the organ segmentation accuracy as a measure by the DI (0.77) for the pancreas, superior to the level set method (0.72) and IER (0.71). The hGReS was shown to be reproducible on the second subject, achieving a DI of 0.82, 0.92 and 0.93 for the pancreas, stomach and liver, respectively. Motion trajectories derived from the hGReS were highly correlated to respiratory motion.

CONCLUSION

We have shown the feasibility of automated segmentation of the pancreas anatomy on dMRI.

ADVANCES IN KNOWLEDGE

Using the hybrid method improves segmentation robustness of low-contrast images.

Investigating the feasibility of rapid MRI for image-guided motion management in lung cancer radiotherapy

Cycle-to-cycle variations in respiratory motion can cause significant geometric and dosimetric errors in the administration of lung cancer radiation therapy. A common limitation of the current strategies for motion management is that they assume a constant, reproducible respiratory cycle. In this work, we investigate the feasibility of using rapid MRI for providing long-term imaging of the thorax in order to better capture cycle-to-cycle variations. Two nonsmall-cell lung cancer patients were imaged (free-breathing, no extrinsic contrast, and 1.5 T scanner). A balanced steady-state-free-precession (b-SSFP) sequence was used to acquire cine-2D and cine-3D (4D) images. In the case of Patient 1 (right midlobe lesion, ~40 mm diameter), tumor motion was well correlated with diaphragmatic motion. In the case of Patient 2, (left upper-lobe lesion, ~60 mm diameter), tumor motion was poorly correlated with diaphragmatic motion. Furthermore, the motion of the tumor centroid was poorly correlated with the motion of individual points on the tumor boundary, indicating significant rotation and/or deformation. These studies indicate that image quality and acquisition speed of cine-2D MRI were adequate for motion monitoring. However, significant improvements are required to achieve comparable speeds for truly 4D MRI. Despite several challenges, rapid MRI offers a feasible and attractive tool for noninvasive, long-term motion monitoring.

Adequacy of inhale/exhale breathhold CT based ITV margins and image-guided registration for free-breathing pancreas and liver SBRT

Purpose

To evaluate use of breath-hold CTs and implanted fiducials for definition of the internal target volume (ITV) margin for upper abdominal stereotactic body radiation therapy (SBRT). To study the statistics of inter- and intra-fractional motion information.

Methods and materials

11 patients treated with SBRT for locally advanced pancreatic cancer (LAPC) or liver cancer were included in the study. Patients underwent fiducial implantation, free-breathing CT and breath-hold CTs at end inhalation/exhalation. All patients were planned and treated with SBRT using volumetric modulated arc therapy (VMAT). Two margin strategies were studied: Strategy I uses PTV = ITV + 3 mm; Strategy II uses PTV = GTV + 1.5 cm. Both CBCT and kV orthogonal images were taken and analyzed for setup before patient treatments. Tumor motion statistics based on skeletal registration and on fiducial registration were analyzed by fitting to Gaussian functions.

Results

All 11 patients met SBRT planning dose constraints using strategy I. Average ITV margins for the 11 patients were 2 mm RL, 6 mm AP, and 6 mm SI. Skeletal registration resulted in high probability (RL = 69%, AP = 4.6%, SI = 39%) that part of the tumor will be outside the ITV. With the 3 mm ITV expansion (Strategy 1), the probability reduced to RL 32%, AP 0.3%, SI 20% for skeletal registration; and RL 1.2%, AP 0%, SI 7% for fiducial registration. All 7 pancreatic patients and 2 liver patients failed to meet SBRT dose constraints using strategy II. The liver dose was increased by 36% for the other 2 liver patients that met the SBRT dose constraints with strategy II.

Conclusions

Image guidance matching to skeletal anatomy is inadequate for SBRT positioning in the upper abdomen and usage of fiducials is highly recommended. Even with fiducial implantation and definition of an ITV, a minimal 3 mm planning margin around the ITV is needed to accommodate intra-fractional uncertainties.

Accelerating dynamic magnetic resonance imaging (MRI) for lung tumor tracking based on low-rank decomposition in the spatial-temporal domain: a feasibility study based on simulation and preliminary prospective undersampled MRI

PURPOSE

To evaluate a low-rank decomposition method to reconstruct down-sampled k-space data for the purpose of tumor tracking.

METHODS AND MATERIALS

Seven retrospective lung cancer patients were included in the simulation study. The fully-sampled k-space data were first generated from existing 2-dimensional dynamic MR images and then down-sampled by 5 × -20 × before reconstruction using a Cartesian undersampling mask. Two methods, a low-rank decomposition method using combined dynamic MR images (k-t SLR based on sparsity and low-rank penalties) and a total variation (TV) method using individual dynamic MR frames, were used to reconstruct images. The tumor trajectories were derived on the basis of autosegmentation of the resultant images. To further test its feasibility, k-t SLR was used to reconstruct prospective data of a healthy subject. An undersampled balanced steady-state free precession sequence with the same undersampling mask was used to acquire the imaging data.

RESULTS

In the simulation study, higher imaging fidelity and low noise levels were achieved with the k-t SLR compared with TV. At 10 × undersampling, the k-t SLR method resulted in an average normalized mean square error <0.05, as opposed to 0.23 by using the TV reconstruction on individual frames. Less than 6% showed tracking errors >1 mm with 10 × down-sampling using k-t SLR, as opposed to 17% using TV. In the prospective study, k-t SLR substantially reduced reconstruction artifacts and retained anatomic details.

CONCLUSIONS

Magnetic resonance reconstruction using k-t SLR on highly undersampled dynamic MR imaging data results in high image quality useful for tumor tracking. The k-t SLR was superior to TV by better exploiting the intrinsic anatomic coherence of the same patient. The feasibility of k-t SLR was demonstrated by prospective imaging acquisition and reconstruction.

Respiration-based sorting of dynamic MRI to derive representative 4D-MRI for radiotherapy planning

PURPOSE

Current pretreatment, 4D imaging techniques are suboptimal in that they sample breathing motion over a very limited "snap-shot" in time. To potentially address this, the authors have developed a longer-duration MRI and postprocessing technique to derive the average or most-probable state of mobile anatomy and meanwhile capture and convey the observed motion variability.

METHODS

Sagittal and coronal multislice, 2D dynamic MRI was acquired in a sequential fashion over extended durations in two abdominal and four lung studies involving healthy volunteers. Two sequences, readily available on a commercial system, were employed. Respiratory interval-correlated, or 4D-MRI, volumes were retrospectively derived using a two-pass approach. In a first pass, a respiratory trace acquired simultaneous with imaging was processed and slice stacking was used to derive a set of MRI volumes, each representing an equal time or proportion of respiration. Herein, all raw 2D frames mapping to the given respiratory interval, per slice location, were averaged. In a second-pass, this prior reconstruction provided a set of template images and a similarity metric was employed to discern the subset of best-matching raw 2D frames for secondary averaging (per slice location and respiratory interval). Breathing variability (per respiratory interval and slice location) was depicted by computing both a maximum intensity projection as well as a pixelwise standard deviation image.

RESULTS

These methods were successfully demonstrated in both the lung and abdomen for both applicable sequences, performing reconstructions with ten respiratory intervals. The first-pass (average) resulted in motion-induced blurring, especially for irregular breathing. The authors have demonstrated qualitatively that the second-pass result can mitigate this blurring.

CONCLUSIONS

They have presented a novel methodology employing dMRI to derive representative 4D-MRI. This set of techniques are practical in that (1) they employ MRI sequences that are standard across commercial vendors; (2) the 2D imaging planes can be oriented onto an arbitrary axis (e.g., sagittal, coronal, axial[ellipsis (horizontal)]); (3) the image processing techniques are relatively simple. Systematically applying this and similar dMRI-based techniques in patients is a crucial next step to demonstrate efficacy beyond CT-only based practice.

Comparison of patient-specific internal gross tumor volume for radiation treatment of primary esophageal cancer based separately on three-dimensional and four-dimensional computed tomography images

To compare the target volume, position and matching index of the patient-specific internal gross tumor volume (IGTV) based on three-dimensional (3D) and four-dimensional (4D) computed tomography (CT) images for primary esophageal cancer. Twenty-nine patients with primary thoracic esophageal cancer underwent 3DCT and 4DCT scans during free breathing. IGTVs were constructed using three approaches: combining the gross target volumes from the 10 respiratory phases of the 4DCT dataset to produce IGTV10 ; IGTV2 was acquired by combining the two extreme phases; and IGTV3D was created from the 3DCT-based gross target volume by enlarging the 95th percentile of motion in each direction measured by the 4DCT. 0.16 cm lateral (LR), 0.14 cm anteroposterior (AP) and 0.29 cm superoinferior (SI) in the upper; 0.18 cm LR, 0.10 cm AP and 0.63 cm SI in the middle; and 0.40 cm LR, 0.58 cm AP and 0.82 cm in the lower thoracic esophagus could account for 95% of respiratory-induced tumor motion. The centroid position shift between IGTV10 and IGTV2 was all below 0.10 cm, and less than 0.20 cm between IGTV10 and IGTV3D . IGTV10 was bigger than IGTV2 ; the mean value of matching index for IGTV2 to IGTV10 was 0.87 ± 0.05, 0.85 ± 0.06 and 0.83 ± 0.05 for upper, middle and distal thoracic esophageal tumors, respectively, and just 0.57 ± 0.11, 0.56 ± 0.13 and 0.40 ± 0.03 between IGTV3D and IGTV10 . 4DCT-based IGTV10 is a reasonable patient-specific IGTV for primary thoracic esophageal cancer, and IGTV2 is considered as an acceptable alternative to IGTV10 . However, it seems unreasonable to use IGTV3D substitute IGTV10 .

Quantifying ITV instabilities arising from 4DCT: a simulation study using patient data

Treatment planning for patients undergoing radiation therapy is often performed based on four-dimensional computed tomography (4DCT) when respiratory motion is present, as in lung cancer patients. 4DCT is used to define the internal target volume (ITV) that, ideally, incorporates all potential locations of the tumour. In this work, we use the locations of gold fiducial markers implanted in lung tumours of eight patients to represent tumour motion. These fiducial locations are used in a simulation of a four-slice CT scanner to generate the ITV for 10, 20 and 30 mm diameter model tumours. To demonstrate instabilities in the ITV definition based on 4DCT, the ITV calculation was repeated for the same patients for consecutive scan start times, staggered by 1 s. The volumetric difference in the ITV and the per cent of time that the ITV contains in the tumour are both evaluated. The ITV from a single patient was found to vary by 46%-127% for a tumour diameter of 10 mm. The ITV did not cover the entirety of the tumour 11%-74% of the time for a 10 mm tumour diameter.

Magnetic resonance imaging and computed tomography of respiratory mechanics

Radiotherapy for organs with respiratory motion has motivated the development of dynamic volume lung imaging with computed tomography (4D-CT) or magnetic resonance imaging (4D-MRI). 4D-CT can be realized in helical (continuous couch translation during image acquisition) or cine mode (translation step-by-step), either acquired prospectively or reconstructed retrospectively with temporal resolutions of up to 250 msec. Long exposure times result in high radiation dose and restrict 4D-CT to specific indications (ie, radiotherapy planning). Dynamic MRI accelerated by parallel imaging and echo sharing reaches temporal resolutions of up to 10 images/sec (2D+t) or 1 volume/s (3D+t) that allow analyzing respiratory motion of the lung and its tumors. Near isotropic 4D-MRI can be used to assess tumor displacement, chest wall invasion, and segmental respiratory mechanics. Limited temporal resolution of dynamic volume acquisitions (in their current implementation) may lead to an overestimation of tumor size, as the mass is volume averaged into many voxels during motion. Nevertheless, 4D-MRI allows for repeated and prolonged measurements without radiation exposure and therefore appears to be appropriate for patient selection in motion-adapted radiotherapy as well as for a broad spectrum of scientific applications.

Variations in tumor size and position due to irregular breathing in 4D-CT: a simulation study

PURPOSE

To estimate the position and volume errors in 4D-CT caused by irregular breathing.

METHODS

A virtual 4D-CT scanner was designed to reproduce axial mode scans with retrospective resorting. This virtual scanner creates an artificial spherical tumor based on the specifications of the user, and recreates images that might be produced by a 4D-CT scanner using a patient breathing waveform. 155 respiratory waveforms of patients were used to test the variability of 4D-CT scans. Each breathing waveform was normalized and scaled to 1, 2, and 3 cm peak-to-peak motion, and artificial tumors with 2 and 4 cm radius were simulated for each scaled waveform. The center of mass and volume of resorted 4D-CT images were calculated and compared to the expected values of center of mass and volume for the artificial tumor. Intrasubject variability was investigated by running the virtual scanner over different subintervals of each patient's breathing waveform.

RESULTS

The average error in the center of mass location of an artificial tumor was less than 2 mm standard deviation for 2 cm motion. The corresponding average error in volume was less than 4%. In the worst-case scenarios, a center of mass error of 1.0 cm standard deviation and volume errors of 30%-60% at inhale were found. Systematic errors were observed in a subset of patients due to irregular breathing, and these errors were more pronounced when the tumor volume is smaller.

CONCLUSIONS

Irregular breathing during 4D-CT simulation causes systematic errors in volume and center of mass measurements. These errors are small but depend on the tumor size, motion amplitude, and degree of breathing irregularity.

On correlated sources of uncertainty in four dimensional computed tomography data sets

The purpose of this work is to estimate the degree of uncertainty inherent to a given four dimensional computed tomography (4D-CT) imaging modality and to test for interaction of the investigated factors (i.e., object displacement, velocity, and the period of motion) when determining the object motion coordinates, motion envelope, and the confomality in which it can be defined within a time based data series. A motion phantom consisting of four glass spheres imbedded in low density foam on a one dimensional moving platform was used to investigate the interaction of uncertainty factors in motion trajectory that could be used in comparison of trajectory definition, motion envelope definition and conformality in an optimal 4D-CT imaging environment. The motion platform allowed for a highly defined motion trajectory that could be as the ground truth in the comparison with observed motion in 4D-CT data sets. 4D-CT data sets were acquired for 9 different motion patterns. Multifactor analysis of variance (ANOVA) was performed where the factors considered were the phantom maximum velocity, object volume, and the image intensity used to delineate the high density objects. No statistical significance was found for three factor interaction for definition of the motion trajectory, motion envelope, or Dice Similarity Coefficient (DSC) conformality. Two factor interactions were found to be statistically significant for the DSC for the interactions of 1) object volume and the HU threshold used for delineation and 2) the object velocity and object volume. Moreover, a statistically significant single factor direct proportionality was observed between the maximum velocity and the mean tracking error. In this work multiple factors impacting on the uncertainty in 4D data sets have been considered and some statistically significant two-factor interactions have been identified. Therefore, the detailed evaluation of errors and uncertainties in 4D imaging modalities is recommended in order to assess the clinical implications of interaction among the various uncertainty factors.

4D-MRI analysis of lung tumor motion in patients with hemidiaphragmatic paralysis

PURPOSE

To investigate the complex breathing patterns in patients with hemidiaphragmatic paralysis due to malignant infiltration using four-dimensional magnetic resonance imaging (4D-MRI).

PATIENTS AND METHODS

Seven patients with bronchial carcinoma infiltrating the phrenic nerve were examined using 1.5 T MRI. The motion of the tumor and of both hemi-diaphragms were measured on dynamic 2D TrueFISP and 4D FLASH MRI sequences.

RESULTS

For each patient, 3-6 breathing cycles were recorded. The respiratory-induced mean cranio-caudal displacement of the tumor was 6.6 mm (+/-2.8 SD). The mean displacement anterior-posterior was 7.4 mm (+/-2.6), while right-left movement was about 7.4 mm (+/-4.5). The mediastinum moved sidewards during inspiration, realizing a "mediastinal shift". The paralyzed hemidiaphragm and the tumor showed a paradox motion during respiration in five patients. In two patients, the affected hemidiaphragm had a regular, however minimal and asynchronous motion during respiration. Respiratory variability of both tumor and diaphragm motions was about 20% although patients were instructed to breath normally. The findings showed significant differences compared to breathing patterns of patients without diaphragm dysfunction.

CONCLUSION

4D-MRI is a promising tool to analyze complex breathing patterns in patients with lung tumors. It should be considered for use in planning of radiotherapy to account for individual tumor motion.