Dataset Information

The Effects of Breathing Motion on DCE-MRI Images: Phantom Studies Simulating Respiratory Motion to Compare CAIPIRINHA-VIBE, Radial-VIBE, and Conventional VIBE.

ABSTRACT:

Objective

To compare the breathing effects on dynamic contrast-enhanced (DCE)-MRI between controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA)-volumetric interpolated breath-hold examination (VIBE), radial VIBE with k-space-weighted image contrast view-sharing (radial-VIBE), and conventional VIBE (c-VIBE) sequences using a dedicated phantom experiment.

Materials and methods

We developed a moving platform to simulate breathing motion. We conducted dynamic scanning on a 3T machine (MAGNETOM Skyra, Siemens Healthcare) using CAIPIRINHA-VIBE, radial-VIBE, and c-VIBE for six minutes per sequence. We acquired MRI images of the phantom in both static and moving modes, and we also obtained motion-corrected images for the motion mode. We compared the signal stability and signal-to-noise ratio (SNR) of each sequence according to motion state and used the coefficients of variation (CoV) to determine the degree of signal stability.

Results

With motion, CAIPIRINHA-VIBE showed the best image quality, and the motion correction aligned the images very well. The CoV (%) of CAIPIRINHA-VIBE in the moving mode (18.65) decreased significantly after the motion correction (2.56) (p < 0.001). In contrast, c-VIBE showed severe breathing motion artifacts that did not improve after motion correction. For radial-VIBE, the position of the phantom in the images did not change during motion, but streak artifacts significantly degraded image quality, also after motion correction. In addition, SNR increased in both CAIPIRINHA-VIBE (from 3.37 to 9.41, p < 0.001) and radial-VIBE (from 4.3 to 4.96, p < 0.001) after motion correction.

Conclusion

CAIPIRINHA-VIBE performed best for free-breathing DCE-MRI after motion correction, with excellent image quality.

SUBMITTER: Lee CK

PROVIDER: S-EPMC5313517 | biostudies-literature | 2017 Mar-Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The Effects of Breathing Motion on DCE-MRI Images: Phantom Studies Simulating Respiratory Motion to Compare CAIPIRINHA-VIBE, Radial-VIBE, and Conventional VIBE.

Lee Chang Kyung CK Seo Nieun N Kim Bohyun B Huh Jimi J Kim Jeong Kon JK Lee Seung Soo SS Kim In Seong IS Nickel Dominik D Kim Kyung Won KW

Korean journal of radiology 20170207 2

<h4>Objective</h4>To compare the breathing effects on dynamic contrast-enhanced (DCE)-MRI between controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA)-volumetric interpolated breath-hold examination (VIBE), radial VIBE with k-space-weighted image contrast view-sharing (radial-VIBE), and conventional VIBE (c-VIBE) sequences using a dedicated phantom experiment.<h4>Materials and methods</h4>We developed a moving platform to simulate breathing motion. We conducted dyn ...[more]

PMID: 28246509

Similar Datasets

Project description:PURPOSE:The aim of this study was to develop a portable perfusion phantom and validate its utility in quantitative dynamic contrast-enhanced magnetic resonance imaging of the abdomen. METHODS:A portable perfusion phantom yielding a reproducible contrast enhancement curve (CEC) was developed. A phantom package including perfusion and static phantoms were imaged simultaneously with each of three healthy human volunteers in two different 3T MR scanners. Look-up tables correlating reference (known) contrast concentrations with measured ones were created using either the static or perfusion phantom. Contrast maps of image slices showing four organs (liver, spleen, pancreas, and paravertebral muscle) were generated before and after data correction using the look-up tables. The contrast concentrations at 4.5 min after dosing in each of the four organs were averaged for each volunteer. The mean contrast concentrations (4 organs × 3 volunteers = 12) were compared for the two scanners, and the intra-class correlation coefficient (ICC) was calculated. Also, the ICC of the mean Ktrans values between the two scanners was calculated before and after data correction. RESULTS:The repeatability coefficient of CECs of perfusion phantom was higher than 0.997 in all measurements. The ICC of the tissue contrast concentrations between the two scanners was 0.693 before correction, but increased to 0.974 after correction using the look-up tables (LUTs) of perfusion phantom. However, the ICC was not increased after correction using static phantom (ICC: 0.617). Similarly, the ICC of the Ktrans values was 0.899 before correction, but increased to 0.996 after correction using perfusion phantom LUTs. The ICC of the Ktrans values, however, was not increased when static phantom LUTs were used (ICC: 0.866). CONCLUSIONS:The perfusion phantom reduced variability in quantitating contrast concentration and Ktrans values of human abdominal tissues across different MR units, but static phantom did not. The perfusion phantom has the potential to facilitate multi-institutional clinical trials employing quantitative DCE-MRI to evaluate various abdominal malignancies.

Project description:Respiration-correlated CT (RCCT) images produced with commonly used phase-based sorting of CT slices often exhibit discontinuity artifacts between CT slices, caused by cycle-to-cycle amplitude variations in respiration. Sorting based on the displacement of the respiratory signal yields slices at more consistent respiratory motion states and hence reduces artifacts, but missing image data (gaps) may occur. The authors report on the application of a respiratory motion model to produce an RCCT image set with reduced artifacts and without missing data.Input data consist of CT slices from a cine CT scan acquired while recording respiration by monitoring abdominal displacement. The model-based generation of RCCT images consists of four processing steps: (1) displacement-based sorting of CT slices to form volume images at 10 motion states over the cycle; (2) selection of a reference image without gaps and deformable registration between the reference image and each of the remaining images; (3) generation of the motion model by applying a principal component analysis to establish a relationship between displacement field and respiration signal at each motion state; (4) application of the motion model to deform the reference image into images at the 9 other motion states. Deformable image registration uses a modified fast free-form algorithm that excludes zero-intensity voxels, caused by missing data, from the image similarity term in the minimization function. In each iteration of the minimization, the displacement field in the gap regions is linearly interpolated from nearest neighbor nonzero intensity slices. Evaluation of the model-based RCCT examines three types of image sets: cine scans of a physical phantom programmed to move according to a patient respiratory signal, NURBS-based cardiac torso (NCAT) software phantom, and patient thoracic scans.Comparison in physical motion phantom shows that object distortion caused by variable motion amplitude in phase-based sorting is visibly reduced with model-based RCCT. Comparison of model-based RCCT to original NCAT images as ground truth shows best agreement at motion states whose displacement-sorted images have no missing slices, with mean and maximum discrepancies in lung of 1 and 3 mm, respectively. Larger discrepancies correlate with motion states having a larger number of missing slices in the displacement-sorted images. Artifacts in patient images at different motion states are also reduced. Comparison with displacement-sorted patient images as a ground truth shows that the model-based images closely reproduce the ground truth geometry at different motion states.Results in phantom and patient images indicate that the proposed method can produce RCCT image sets with reduced artifacts relative to phase-sorted images, without the gaps inherent in displacement-sorted images. The method requires a reference image at one motion state that has no missing data. Highly irregular breathing patterns can affect the method's performance, by introducing artifacts in the reference image (although reduced relative to phase-sorted images), or in decreased accuracy in the image prediction of motion states containing large regions of missing data.

Project description:Most clinically deployed strategies for respiratory motion management in lung radiotherapy (e.g., gating and tracking) use external markers that serve as surrogates for tumor motion. However, typical lung phantoms used to validate these strategies are based on a rigid exterior and a rigid or a deformable-interior. Such designs do not adequately represent respiration because the thoracic anatomy deforms internally as well as externally. In order to create a closer approximation of respiratory motion, the authors describe the construction and experimental testing of an externally as well as internally deformable, programmable lung phantom.The outer shell of a commercially available lung phantom (RS-1500, RSD, Inc.) was used. The shell consists of a chest cavity with a flexible anterior surface, and embedded vertebrae, rib-cage and sternum. A custom-made insert was designed using a piece of natural latex foam block. A motion platform was programmed with sinusoidal and ten patient-recorded lung tumor trajectories. The platform was used to drive a rigid foam "diaphragm" that compressed/decompressed the phantom interior. Experimental characterization comprised of determining the reproducibility and the external-internal correlation of external and internal marker trajectories extracted from kV x-ray fluoroscopy. Experiments were conducted to illustrate three example applications of the phantom-(i) validating the geometric accuracy of the VisionRT surface photogrammetry system; (ii) validating an image registration tool, NiftyReg; and (iii) quantifying the geometric error due to irregular motion in four-dimensional computed tomography (4DCT).The phantom correctly reproduced sinusoidal and patient-derived motion, as well as realistic respiratory motion-related effects such as hysteresis. The reproducibility of marker trajectories over multiple runs for sinusoidal as well as patient traces, as characterized by fluoroscopy, was within 0.25 mm RMS error. The motion trajectories of internal and external radio-opaque markers as measured by fluoroscopy were found to be highly correlated (R > 0.95). Using the phantom, it was demonstrated that the motion trajectories of regions-of-interest on the surface as measured by VisionRT are highly consistent with corresponding fluoroscopically acquired surface marker trajectories, with RMS errors within 0.26 mm. Furthermore, it was shown that the trajectories of external and internal marker trajectories derived from NiftyReg deformation vector fields were within 1 mm root mean square errors comparing to trajectories obtained by segmenting markers from individual fluoro frames. Finally, it was shown that while 4DCT can be used to localize internal markers for sinusoidal motion with reasonable accuracy, the localization error increases significantly (by a factor of ? 2) in the presence of cycle-to-cycle variations that are observed in patient-derived respiratory motion.The authors have developed a realistic externally and internally deformable, programmable lung phantom that will serve as a valuable tool for clinical and investigational motion management studies in thoracic and abdominal radiation therapies.

Project description:The aims of this study were to observe the pattern of transient motion after gadoxetic acid administration including incidence, onset, and duration, and to evaluate the clinical feasibility of free-breathing gadoxetic acid-enhanced liver magnetic resonance imaging using golden-angle radial sparse parallel (GRASP) imaging with respiratory gating.In this institutional review board-approved prospective study, 59 patients who provided informed consents were analyzed. Free-breathing dynamic T1-weighted images (T1WIs) were obtained using GRASP at 3 T after a standard dose of gadoxetic acid (0.025 mmol/kg) administration at a rate of 1 mL/s, and development of transient motion was monitored, which is defined as a distinctive respiratory frequency alteration of the self-gating MR signals. Early arterial, late arterial, and portal venous phases retrospectively reconstructed with and without respiratory gating and with different temporal resolutions (nongated 13.3-second, gated 13.3-second, gated 6-second T1WI) were evaluated for image quality and motion artifacts. Diagnostic performance in detecting focal liver lesions was compared among the 3 data sets.Transient motion (mean duration, 21.5 ± 13.0 seconds) was observed in 40.0% (23/59) of patients, 73.9% (17/23) of which developed within 15 seconds after gadoxetic acid administration. On late arterial phase, motion artifacts were significantly reduced on gated 13.3-second and 6-second T1WI (3.64 ± 0.34, 3.61 ± 0.36, respectively), compared with nongated 13.3-second T1WI (3.12 ± 0.51, P < 0.0001). Overall, image quality was the highest on gated 13.3-second T1WI (3.76 ± 0.39) followed by gated 6-second and nongated 13.3-second T1WI (3.39 ± 0.55, 2.57 ± 0.57, P < 0.0001). Only gated 6-second T1WI showed significantly higher detection performance than nongated 13.3-second T1WI (figure of merit, 0.69 [0.63-0.76]) vs 0.60 [0.56-0.65], P = 0.004).Transient motion developed in 40% (23/59) of patients shortly after gadoxetic acid administration, and gated free-breathing T1WI using GRASP was able to consistently provide acceptable arterial phase imaging in patients who exhibited transient motion.

Project description:Purpose:Prostate motion during radiation therapy (ie, intrafraction motion) can cause unwanted loss of radiation dose to the prostate and increased dose to the surrounding organs at risk. A compact but general statistical description of this motion could be useful for simulation of radiation therapy delivery or margin calculations. We investigated whether prostate motion could be modeled with a random walk model. Methods and materials:Prostate motion recorded during 548 radiation therapy fractions in 17 patients was analyzed and used for input in a random walk prostate motion model. The recorded motion was categorized on the basis of whether any transient excursions (ie, rapid prostate motion in the anterior and superior direction followed by a return) occurred in the trace and transient motion. This was separately modeled as a large step in the anterior/superior direction followed by a returning large step. Random walk simulations were conducted with and without added artificial transient motion using either motion data from all observed traces or only traces without transient excursions as model input, respectively. Results:A general estimate of motion was derived with reasonable agreement between simulated and observed traces, especially during the first 5 minutes of the excursion-free simulations. Simulated and observed diffusion coefficients agreed within 0.03, 0.2 and 0.3 mm2/min in the left/right, superior/inferior, and anterior/posterior directions, respectively. A rapid increase in variance at the start of observed traces was difficult to reproduce and seemed to represent the patient's need to adjust before treatment. This could be estimated somewhat using artificial transient motion. Conclusions:Random walk modeling is feasible and recreated the characteristics of the observed prostate motion. Introducing artificial transient motion did not improve the overall agreement, although the first 30 seconds of the traces were better reproduced. The model provides a simple estimate of prostate motion during delivery of radiation therapy.

Dataset Information

The Effects of Breathing Motion on DCE-MRI Images: Phantom Studies Simulating Respiratory Motion to Compare CAIPIRINHA-VIBE, Radial-VIBE, and Conventional VIBE.

Objective

Materials and methods

Results

Conclusion

Publications

The Effects of Breathing Motion on DCE-MRI Images: Phantom Studies Simulating Respiratory Motion to Compare CAIPIRINHA-VIBE, Radial-VIBE, and Conventional VIBE.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets