Dataset Information

Patient specific prospective respiratory motion correction for efficient, free-breathing cardiovascular MRI.

ABSTRACT: PURPOSE:To develop a patient-specific respiratory motion correction technique with true 100% acquisition efficiency. METHODS:A short training scan consisting of a series of single heartbeat images, each acquired with a preceding diaphragmatic navigator, was performed to fit a model relating the patient-specific 3D respiratory motion of the heart-to-diaphragm position. The resulting motion model was then used to update the imaging plane in real-time to correct for translational motion based on respiratory position provided by the navigator. The method was tested in a group of 11 volunteers with 5 separate free-breathing acquisitions: FB, no motion correction; FB-TF, free breathing with a linear tracking factor; Nav Gate, navigator gating; Nav Gate-TF, navigator gating with a tracking factor; and PROCO, prospective motion correction (proposed). Each acquisition lasted for 50 accepted heartbeats, where non-gated scans had a 100% acceptance rate, and gated scans accepted data only within a ±4 mm navigator window. Retrospective image registration was used to measure residual motion and determine the effectiveness of each method. RESULTS:PROCO reduced the range/RMSE of residual motion to 4.08 ± 1.4/0.90 ± 0.3 mm, compared to 10.78 ± 6.9/2.97 ± 2.2 mm for FB, 5.32 ± 2.92/1.24 ± 0.8 mm for FB-TF, 4.08 ± 1.6/0.93 ± 0.4 mm for Nav Gate, and 2.90 ± 1.0/0.63 ± 0.2 mm for Nav Gate-TF. Nav Gate and Nav Gate-TF reduced scan efficiency to 48.84 ± 9.31% and 54.54 ± 10.12%, respectively. CONCLUSION:PROCO successfully limited the residual motion in single-shot imaging to the level of traditional navigator gating while maintaining 100% acquisition efficiency.

SUBMITTER: Bush MA

PROVIDER: S-EPMC6814292 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Patient specific prospective respiratory motion correction for efficient, free-breathing cardiovascular MRI.

Bush Michael A MA Ahmad Rizwan R Jin Ning N Liu Yingmin Y Simonetti Orlando P OP

Magnetic resonance in medicine 20190214 6

<h4>Purpose</h4>To develop a patient-specific respiratory motion correction technique with true 100% acquisition efficiency.<h4>Methods</h4>A short training scan consisting of a series of single heartbeat images, each acquired with a preceding diaphragmatic navigator, was performed to fit a model relating the patient-specific 3D respiratory motion of the heart-to-diaphragm position. The resulting motion model was then used to update the imaging plane in real-time to correct for translational mot ...[more]

PMID: 30761599

Similar Datasets

Project description:PurposeGastrointestinal motion patterns such as peristalsis and segmental contractions can alter the shape and position of the stomach and intestines with respect to other irradiated organs during radiation therapy. Unfortunately, these deformations are concealed by conventional four-dimensional (4D)-MRI techniques, which were developed to visualize respiratory motion by binning acquired data into respiratory motion states without considering the phases of GI motion. We present a method to reconstruct breathing-compensated images showing the phases of periodic gastric motion and study the effect of this motion on regional anatomical structures.MethodsSixty-seven DCE-MRI examinations were performed on patients undergoing MRI simulation for hepatocellular carcinoma using a golden-angle stack-of-stars sequence that collected 2000 radial spokes over 5 min. The collected data were reconstructed using a method with integrated respiratory motion correction into a time series of 3D image volumes without visible breathing motion. From this series, a gastric motion signal was extracted by temporal filtering of time-intensity curves in the stomach. Using this motion signal, breathing-corrected back-projection images were sorted according to the gastric phase and reconstructed into 21 gastric motion state images showing the phases of gastric motion.ResultsReconstructed image volumes showed gastric motion states clearly with no visible breathing motion or related artifacts. The mean frequency of the gastric motion signal was 3 cycles/min with a standard deviation of 0.27 cycles/min.ConclusionsPeriodic gastrointestinal motion can be visualized without confounding respiratory motion using the presented GI 4D MRI technique. GI 4D MRIs may help define internal target volumes for treatment planning, aid in planning organ at risk volume definition, or support motion model development for gastrointestinal motion tracking algorithms for real-time MR-guided radiation therapy.

Project description:PurposeTo develop a physical, adaptive motion perturbation model to predict tumor motion using feedback from dynamic measurement of breathing conditions to compensate for breathing irregularities.Methods and materialsA novel respiratory motion perturbation (RMP) model was developed to predict tumor motion variations caused by breathing irregularities. This model contained 2 terms: the initial tumor motion trajectory, measured from 4-dimensional computed tomography (4DCT) images, and motion perturbation, calculated from breathing variations in tidal volume (TV) and breathing pattern (BP). The motion perturbation was derived from the patient-specific anatomy, tumor-specific location, and time-dependent breathing variations. Ten patients were studied, and 2 amplitude-binned 4DCT images for each patient were acquired within 2 weeks. The motion trajectories of 40 corresponding bifurcation points in both 4DCT images of each patient were obtained using deformable image registration. An in-house 4D data processing toolbox was developed to calculate the TV and BP as functions of the breathing phase. The motion was predicted from the simulation 4DCT scan to the treatment 4DCT scan, and vice versa, resulting in 800 predictions. For comparison, noncorrected motion differences and the predictions from a published 5-dimensional model were used.ResultsThe average motion range in the superoinferior direction was 9.4 ± 4.4 mm, the average ΔTV ranged from 10 to 248 mm3 (-26% to 61%), and the ΔBP ranged from 0 to 0.2 (-71% to 333%) between the 2 4DCT scans. The mean noncorrected motion difference was 2.0 ± 2.8 mm between 2 4DCT motion trajectories. After applying the RMP model, the mean motion difference was reduced significantly to 1.2 ± 1.8 mm (P=.0018), a 40% improvement, similar to the 1.2 ± 1.8 mm (P=.72) predicted with the 5-dimensional model.ConclusionsA novel physical RMP model was developed with an average accuracy of 1.2 ± 1.8 mm for interfraction motion prediction, similar to that of a published lung motion model. This physical RMP was analytically derived and is able to adapt to breathing irregularities. Further improvement of this RMP model is under investigation.

Dataset Information

Patient specific prospective respiratory motion correction for efficient, free-breathing cardiovascular MRI.

Publications

Patient specific prospective respiratory motion correction for efficient, free-breathing cardiovascular MRI.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets