Purpose: Four-dimensional computed tomography (4D-CT) has been widely used in radiation therapy to assess patient-specific breathing motion for determining individual safety margins. However, it has two major drawbacks: low soft-tissue contrast and an excessive imaging dose to the patient. This research aimed to develop a clinically feasible four-dimensional magnetic resonance imaging (4D-MRI) technique to overcome these limitations. Methods: The proposed 4D-MRI technique was achieved by continuously acquiring axial images throughout the breathing cycle using fast 2D cine-MR imaging, and then retrospectively sorting the images by respiratory phase. The key component of the technique was the use of body area (BA) of the axial MR images as an internal respiratory surrogate to extract the breathing signal. The validation of the BA surrogate was performed using 4D-CT images of 12 cancer patients by comparing the respiratory phases determined using the BA method to those determined clinically using the Real-time position management (RPM) system. The feasibility of the 4D-MRI technique was tested on a dynamic motion phantom, the 4D extended Cardiac Torso (XCAT) digital phantom, and two healthy human subjects. Results: Respiratory phases determined from the BA matched closely to those determined from the RPM: mean (6SD) difference in phase: À3.9% (66.4%); mean (6SD) absolute difference in phase: 10.40% (63.3%); mean (6SD) correlation coefficient: 0.93 (60.04). In the motion phantom study, 4D-MRI clearly showed the sinusoidal motion of the phantom; image artifacts observed were minimal to none. Motion trajectories measured from 4D-MRI and 2D cine-MRI (used as a reference) matched excellently: the mean (6SD) absolute difference in motion amplitude: À0.3 (60.5) mm. In the 4D-XCAT phantom study, the simulated "4D-MRI" images showed good consistency with the original 4D-XCAT phantom images. The motion trajectory of the hypothesized "tumor" matched excellently between the two, with a mean (6SD) absolute difference in motion amplitude of 0.5 (60.4) mm. 4D-MRI was able to reveal the respiratory motion of internal organs in both human subjects; superior-inferior (SI) maximum motion of the left kidney of Subject #1 and the diaphragm of Subject #2 measured from 4D-MRI was 0.88 and 1.32 cm, respectively. Conclusions: Preliminary results of our study demonstrated the feasibility of a novel retrospective 4D-MRI technique that uses body area as a respiratory surrogate.

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Purpose: T2-weighted MRI provides excellent tumor-to-tissue contrast for target volume delineation in radiation therapy treatment planning. This study aims at developing a novel T2-weighted retrospective four dimensional magnetic resonance imaging (4D-MRI) phase sorting technique for imaging organ/tumor respiratory motion. Methods: A 2D fast T2-weighted half-Fourier acquisition single-shot turbo spin-echo MR sequence was used for image acquisition of 4D-MRI, with a frame rate of 2-3 frames/s. Respiratory motion was measured using an external breathing monitoring device. A phase sorting method was developed to sort the images by their corresponding respiratory phases. Besides, a result-driven strategy was applied to effectively utilize redundant images in the case when multiple images were allocated to a bin. This strategy, selecting the image with minimal amplitude error, will generate the most representative 4D-MRI. Since we are using a different image acquisition mode for 4D imaging (the sequential image acquisition scheme) with the conventionally used cine or helical image acquisition scheme, the 4D dataset sufficient condition was not obviously and directly predictable. An important challenge of the proposed technique was to determine the number of repeated scans (N R ) required to obtain sufficient phase information at each slice position. To tackle this challenge, the authors first conducted computer simulations using real-time position management respiratory signals of the 29 cancer patients under an IRB-approved retrospective study to derive the relationships between N R and the following factors: number of slices (N S ), number of 4D-MRI respiratory bins (N B ), and starting phase at image acquisition (P 0 ). To validate the authors' technique, 4D-MRI acquisition and reconstruction were simulated on a 4D digital extended cardiac-torso (XCAT) human phantom using simulation derived parameters. Twelve healthy volunteers were involved in an IRB-approved study to investigate the feasibility of this technique. Results: 4D data acquisition completeness (C p ) increases as NR increases in an inverse-exponential fashion (C p = 100 − 99 × exp(−0.18 × N R ), when N B = 6, fitted using 29 patients' data). The N R required for 4D-MRI reconstruction (defined as achieving 95% completeness, C p = 95%, N R = N R,95 ) is proportional to N B (N R,95 ∼ 2.86 × N B , r = 1.0), but independent of N S and P 0 . Simulated XCAT 4D-MRI showed a clear pattern of respiratory motion. Tumor motion trajectories measured on 4D-MRI were comparable to the average input signal, with a mean relative amplitude error of 2.7% ± 2.9%. Reconstructed 4D-MRI for healthy volunteers illustrated clear respiratory motion on three orthogonal planes, with minimal image artifacts. The artifacts were presumably caused by breathing irregularity and incompleteness of data acquisition (95% acquired only). The mean relative amplitude error between critical structure trajectory and average breathing curve for 12 healthy volunteers is 2.5 ± 0.3 mm in superior-...

Purpose To evaluate the relationship between liver tumor motion and diaphragm motion. Methods and Materials Fourteen patients with hepatocellular carcinoma (10 of 14) or liver metastases (4 of 14) undergoing radiation therapy were included in this study. All patients underwent single-slice cine–magnetic resonance imaging simulations across the center of the tumor in 3 orthogonal planes. Tumor and diaphragm motion trajectories in the superior–inferior (SI), anterior–posterior (AP), and medial–lateral (ML) directions were obtained using an in-house-developed normalized cross-correlation–based tracking technique. Agreement between the tumor and diaphragm motion was assessed by calculating phase difference percentage, intraclass correlation coefficient, and Bland-Altman analysis (Diff). The distance between the tumor and tracked diaphragm area was analyzed to understand its impact on the correlation between the 2 motions. Results Of all patients, the mean (±standard deviation) phase difference percentage values were 7.1% ± 1.1%, 4.5% ± 0.5%, and 17.5% ± 4.5% in the SI, AP, and ML directions, respectively. The mean intraclass correlation coefficient values were 0.98 ± 0.02, 0.97 ± 0.02, and 0.08 ± 0.06 in the SI, AP, and ML directions, respectively. The mean Diff values were 2.8 ± 1.4 mm, 2.4 ± 1.1 mm, and 2.2 ± 0.5 mm in the SI, AP, and ML directions, respectively. Tumor and diaphragm motions had high concordance when the distance between the tumor and tracked diaphragm area was small. Conclusions This study showed that liver tumor motion had good correlation with diaphragm motion in the SI and AP directions, indicating diaphragm motion in the SI and AP directions could potentially be used as a reliable surrogate for liver tumor motion.