Project description:Purposes/objectivesHistorically, 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 materialsThis 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.Results303,123 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).ConclusionDiaphragmatic 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.

Project description:Defining myocardial contours is often the most time-consuming portion of dynamic cardiac MRI image analysis. Displacement encoding with stimulated echoes (DENSE) is a quantitative MRI technique that encodes tissue displacement into the phase of the complex MRI images. Cine DENSE provides a time series of these images, thus facilitating the non-invasive study of myocardial kinematics. Epicardial and endocardial contours need to be defined at each frame on cine DENSE images for the quantification of regional displacement and strain as a function of time. This work presents a reliable and effective two-dimensional semi-automated segmentation technique that uses the encoded motion to project a manually-defined region of interest through time. Contours can then easily be extracted for each cardiac phase. This method boasts several advantages, including, (1) parameters are based on practical physiological limits, (2) contours are calculated for the first few cardiac phases, where it is difficult to visually distinguish blood from myocardium, and (3) the method is independent of the shape of the tissue delineated and can be applied to short- or long-axis views, and on arbitrary regions of interest. Motion-guided contours were compared to manual contours for six conventional and six slice-followed mid-ventricular short-axis cine DENSE datasets. Using an area measure of segmentation error, the accuracy of the segmentation algorithm was shown to be similar to inter-observer variability. In addition, a radial segmentation error metric was introduced for short-axis data. The average radial epicardial segmentation error was 0.36+/-0.08 and 0.40+/-0.10 pixels for slice-followed and conventional cine DENSE, respectively, and the average radial endocardial segmentation error was 0.46+/-0.12 and 0.46+/-0.16 pixels for slice following and conventional cine DENSE, respectively. Motion-guided segmentation employs the displacement-encoded phase shifts intrinsic to DENSE MRI to accurately propagate a single set of pre-defined contours throughout the remaining cardiac phases.

Project description:We have previously developed a retrospective 4D-MRI technique using body area as the respiratory surrogate, but generally, the reconstructed 4D MR images suffer from severe or mild artifacts mainly caused by irregular motion during image acquisition. Those image artifacts may potentially affect the accuracy of tumor target delineation or the shape representation of surrounding nontarget tissues and organs. So the purpose of this study is to propose an approach employing principal component analysis (PCA), combined with a linear polynomial fitting model, to remodel the displacement vector fields (DVFs) obtained from deformable image registration (DIR), with the main goal of reducing the motion artifacts in 4D MR images. Seven patients with hepatocellular carcinoma (2/7) or liver metastases (5/7) in the liver, as well as a patient with non-small cell lung cancer (NSCLC), were enrolled in an IRB-approved prospective study. Both CT and MR simulations were performed for each patient for treatment planning. Multiple-slice, multiple-phase, cine-MRI images were acquired in the axial plane for 4D-MRI reconstruction. Single-slice 2D cine-MR images were acquired across the center of the tumor in axial, coronal, and sagittal planes. For a 4D MR image dataset, the DVFs in three orthogonal direction (inferior–superior (SI), anterior–posterior (AP), and medial–lateral (ML)) relative to a specific reference phase were calculated using an in-house DIR algorithm. The DVFs were preprocessed in three temporal and spatial dimensions using a polynomial fitting model, with the goal of correcting the potential registration errors introduced by three-dimensional DIR. Then PCA was used to decompose each fitted DVF into a linear combination of three principal motion bases whose spanned subspaces combined with their projections had been validated to be sufficient to represent the regular respiratory motion. By wrapping the reference MR image using the remodeled DVFs, 'synthetic' MR images with reduced motion artifacts were generated at selected phase. Tumor motion trajectories derived from cine-MRI, 4D CT, original 4D MRI, and 'synthetic' 4D MRI were analyzed in the SI, AP, and ML directions, respectively. Their correlation coefficient (CC) and difference (D) in motion amplitude were calculated for comparison. Of all the patients, the means and standard deviations (SDs) of CC comparing 'synthetic' 4D MRI and cine-MRI were 0.98 ± 0.01, 0.98 ± 0.01, and 0.99 ± 0.01 in SI, AP, and ML directions, respectively. The mean ± SD Ds were 0.59 ± 0.09 mm, 0.29± 0.10 mm, and 0.15 ± 0.05 mm in SI, AP and ML directions, respectively. The means and SDs of CC comparing 'synthetic' 4D MRI and 4D CT were 0.96 ± 0.01, 0.95± 0.01, and 0.95 ± 0.01 in SI, AP, and ML directions, respectively. The mean ± SD Ds were 0.76 ± 0.20 mm, 0.33 ± 0.14 mm, and 0.19± 0.07 mm in SI, AP, and ML directions, respectively. The means and SDs of CC comparing 'synthetic' 4D MRI and original 4D MRI were 0.98 ± 0.01, 0.98± 0.01, and 0.97± 0.01 in SI, AP, and ML directions, respectively. The mean ± SD Ds were 0.58 ± 0.10 mm, 0.30 ± 0.09mm, and 0.17 ± 0.04 mm in SI, AP, and ML directions, respectively. In this study we have proposed an approach employing PCA combined with a linear polynomial fitting model to capture the regular respiratory motion from a 4D MR image dataset. And its potential usefulness in reducing motion artifacts and improving image quality has been demonstrated by the preliminary results in oncological patients.

Project description:PurposeTo describe and report longitudinal quality assurance (QA) measurements for the mechanical and dosimetric performance of an Elekta Unity MR-linac during the first year of clinical use in our institution.Materials and methodsThe mechanical and dosimetric performance of the MR-linac was evaluated with daily, weekly, monthly, and annual QA testing. The measurements monitor the size of the radiation isocenter, the MR-to-MV isocenter concordance, MLC and jaw position, the accuracy and reproducibility of step-and-shoot delivery, radiation output and beam profile constancy, and patient-specific QA for the first 50 treatments in our institution. Results from end-to-end QA using anthropomorphic phantoms are also included as a reference for baseline comparisons. Measurements were performed in water or water-equivalent plastic using ion chambers of various sizes, an ion chamber array, MR-compatible 2D/3D diode array, portal imager, MRI, and radiochromic film.ResultsThe diameter of the radiation isocenter and the distance between the MR/MV isocenters was (μ ± σ) 0.39 ± 0.01 mm and 0.89 ± 0.05 mm, respectively. Trend analysis shows both measurements to be well within the tolerance of 1.0 mm. MLC and jaw positional accuracy was within 1.0 mm while the dosimetric performance of step-and-shoot delivery was within 2.0%, irrespective of gantry angle. Radiation output and beam profile constancy were within 2.0% and 1.0%, respectively. End-to-end testing performed with ion-chamber and radiochromic film showed excellent agreement with treatment plan. Patient-specific QA using a 3D diode array identified gantry angles with low-pass rates allowing for improvements in plan quality after necessary adjustments.ConclusionThe MR-linac operates within the guidelines of current recommendations for linear accelerator performance, stability, and safety. The analysis of the data supports the recently published guidance in establishing clinically acceptable tolerance levels for relative and absolute measurements.

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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

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