Dataset Information

An MRI framework for respiratory motion modelling validation.

ABSTRACT:

Introduction

Respiratory motion models establish a correspondence between respiratory-correlated (RC) 4-dimensional (4D) imaging and respiratory surrogates, to estimate time-resolved (TR) 3D breathing motion. To evaluate the performance of motion models on real patient data, a validation framework based on magnetic resonance imaging (MRI) is proposed, entailing the use of RC 4DMRI to build the model, and on both (i) TR 2D cine-MRI and (ii) additional 4DMRI data for testing intra-/inter-fraction breathing motion variability.

Methods

Repeated MRI data were acquired in 7 patients with abdominal lesions. The considered model relied on deformable image registration (DIR) for building the model and compensating for inter-fraction baseline variations. Both 2D and 3D validation were performed, by comparing model estimations with the ground truth 2D cine-MRI and 4DMRI respiratory phases, respectively.

Results

The median DIR error was comparable to the voxel size (1.33 × 1.33 × 5 mm³ ), with higher values in the presence of large inter-fraction motion (median value: 2.97 mm). In the 2D validation, the median estimation error on anatomical landmarks' position resulted below 4 mm in every scenario, whereas in the 3D validation it was 1.33 mm and 4.21 mm when testing intra- and inter-fraction motion, respectively. The range of motion described in the cine-MRI was comparable to the motion of the building 4DMRI, being always above the estimation error. Overall, the model performance was dependent on DIR error, presenting reduced accuracy when inter-fraction baseline variations occurred.

Conclusions

Results suggest the potential of the proposed framework in evaluating global motion models for organ motion management in MRI-guided radiotherapy.

SUBMITTER: Meschini G

PROVIDER: S-EPMC8251859 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

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 implement, validate, and apply a self-gated free-running whole-heart five-dimensional (5D) flow MRI framework to evaluate respiration-driven effects on three-dimensional (3D) hemodynamics in a clinical setting.Materials and methodsIn this prospective study, a free-running five-dimensional (5D) flow sequence was implemented with 3D radial sampling, self-gating, and a compressed-sensing reconstruction. The 5D flow was evaluated in a pulsatile phantom and adult participants with aortic and/or valvular disease who were enrolled between May and August 2019. Conventional twofold-accelerated four-dimensional (4D) flow of the thoracic aorta with navigator gating was performed as a reference comparison. Continuous parameters were evaluated for parameter normality and were compared between conventional 4D flow and 5D flow using a signed-rank or two-tailed paired t test. Differences between respiratory states were evaluated using a repeated-measure analysis of variance or a nonparametric Friedman test.ResultsA total of 20 adult participants (mean age, 49 years ± 17 [standard deviation]; 18 men and two women) were included. In vitro 5D flow results showed excellent agreement with conventional 4D flow-derived values (peak and net flow, <7% difference over all quantified planes). Whole-heart 5D flow data were collected in all participants in 7.65 minutes ± 0.35 (acceleration rate = 36.0-76.9) versus 9.88 minutes ± 3.17 for conventional aortic 4D flow. In vivo, 5D flow demonstrated moderate agreement with conventional 4D flow but demonstrated overestimation in net flow and peak velocity (up to 26% and 12%, respectively) in the ascending aorta and underestimation (<12%) in the arch and descending aorta. Respiratory-resolved analyses of caval veins showed significantly increased net and peak flow in the inferior vena cava in end inspiration compared with end expiration, and the opposite trend was shown in the superior vena cava.ConclusionA free-running 5D flow MRI framework consistently captured cardiac and respiratory motion-resolved 3D hemodynamics in less than 8 minutes. Supplemental material is available for this article. © RSNA, 2020.

Project description:Magnetic resonance imaging (MRI) can potentially be used for non-invasive screening of patients with stable angina pectoris to identify probable obstructive coronary artery disease. MRI-based coronary blood flow quantification has to date only been performed in a 2D fashion, limiting its clinical applicability. In this study, we propose a framework for coronary blood flow quantification using accelerated 4D flow MRI with respiratory motion correction and compressed sensing image reconstruction. We investigate its feasibility and repeatability in healthy subjects at rest. Fourteen healthy subjects received 8 times-accelerated 4D flow MRI covering the left coronary artery (LCA) with an isotropic spatial resolution of 1.0 mm3. Respiratory motion correction was performed based on 1) lung-liver navigator signal, 2) real-time monitoring of foot-head motion of the liver and LCA by a separate acquisition, and 3) rigid image registration to correct for anterior-posterior motion. Time-averaged diastolic LCA flow was determined, as well as time-averaged diastolic maximal velocity (VMAX) and diastolic peak velocity (VPEAK). 2D flow MRI scans of the LCA were acquired for reference. Scan-rescan repeatability and agreement between 4D flow MRI and 2D flow MRI were assessed in terms of concordance correlation coefficient (CCC) and coefficient of variation (CV). The protocol resulted in good visibility of the LCA in 11 out of 14 subjects (six female, five male, aged 28 ± 4 years). The other 3 subjects were excluded from analysis. Time-averaged diastolic LCA flow measured by 4D flow MRI was 1.30 ± 0.39 ml/s and demonstrated good scan-rescan repeatability (CCC/CV = 0.79/20.4%). Time-averaged diastolic VMAX (17.2 ± 3.0 cm/s) and diastolic VPEAK (24.4 ± 6.5 cm/s) demonstrated moderate repeatability (CCC/CV = 0.52/19.0% and 0.68/23.0%, respectively). 4D flow- and 2D flow-based diastolic LCA flow agreed well (CCC/CV = 0.75/20.1%). Agreement between 4D flow MRI and 2D flow MRI was moderate for both diastolic VMAX and VPEAK (CCC/CV = 0.68/20.3% and 0.53/27.0%, respectively). In conclusion, the proposed framework of accelerated 4D flow MRI equipped with respiratory motion correction and compressed sensing image reconstruction enables repeatable diastolic LCA flow quantification that agrees well with 2D flow MRI.

Project description:PurposeTo validate a respiratory motion correction method called focused navigation (fNAV) for free-running radial whole-heart 4D flow MRI.MethodsUsing fNAV, respiratory signals derived from radial readouts are converted into three orthogonal displacements, which are then used to correct respiratory motion in 4D flow datasets. Hundred 4D flow acquisitions were simulated with non-rigid respiratory motion and used for validation. The difference between generated and fNAV displacement coefficients was calculated. Vessel area and flow measurements from 4D flow reconstructions with (fNAV) and without (uncorrected) motion correction were compared to the motion-free ground-truth. In 25 patients, the same measurements were compared between fNAV 4D flow, 2D flow, navigator-gated Cartesian 4D flow, and uncorrected 4D flow datasets.ResultsFor simulated data, the average difference between generated and fNAV displacement coefficients was 0.04 ±$$ \pm $$ 0.32 mm and 0.31 ±$$ \pm $$ 0.35 mm in the x and y directions, respectively. In the z direction, this difference was region-dependent (0.02 ±$$ \pm $$ 0.51 mm up to 5.85 ±$$ \pm $$ 3.41 mm). For all measurements (vessel area, net volume, and peak flow), the average difference from ground truth was higher for uncorrected 4D flow datasets (0.32 ±$$ \pm $$ 0.11 cm2 , 11.1 ±$$ \pm $$ 3.5 mL, and 22.3 ±$$ \pm $$ 6.0 mL/s) than for fNAV 4D flow datasets (0.10 ±$$ \pm $$ 0.03 cm2 , 2.6 ±$$ \pm $$ 0.7 mL, and 5.1 ±0$$ \pm 0 $$ .9 mL/s, p < 0.05). In vivo, average vessel area measurements were 4.92 ±$$ \pm $$ 2.95 cm2 , 5.06 ±$$ \pm $$ 2.64 cm2 , 4.87 ±$$ \pm $$ 2.57 cm2 , 4.87 ±$$ \pm $$ 2.69 cm2 , for 2D flow and fNAV, navigator-gated and uncorrected 4D flow datasets, respectively. In the ascending aorta, all 4D flow datasets except for the fNAV reconstruction had significantly different vessel area measurements from 2D flow. Overall, 2D flow datasets demonstrated the strongest correlation to fNAV 4D flow for both net volume (r2 = 0.92) and peak flow (r2 = 0.94), followed by navigator-gated 4D flow (r2 = 0.83 and r2 = 0.86, respectively), and uncorrected 4D flow (r2 = 0.69 and r2 = 0.86, respectively).ConclusionfNAV corrected respiratory motion in vitro and in vivo, resulting in fNAV 4D flow measurements that are comparable to those derived from 2D flow and navigator-gated Cartesian 4D flow datasets, with improvements over those from uncorrected 4D flow.

Project description:PurposeMulti-slice scanning in the abdomen and thorax of small animals is compromised by the effects of respiration unless imaging and respiration are synchronised. To avoid the signal modulations that result from respiration motion and a variable TR, blocks of fully relaxed slices are typically acquired during inter-breath periods, at the cost of scan efficiency. This paper reports a conceptually simple yet effective prospective gating acquisition mode for multi-slice scanning in free breathing small animals at any fixed TR of choice with reduced sensitivity to respiratory motion.MethodsMulti-slice scan modes have been implemented in which each slice has its own specific projection or phase encode loop index counter. When a breath is registered RF pulses continue to be applied but data are not acquired, and the corresponding counters remain fixed so that the data are acquired one TR later, providing it coincides with an inter-breath period. The approach is refined to reacquire the slice data that are acquired immediately before each breath is detected. Only the data with reduced motion artefact are used in image reconstruction. The efficacy of the method is demonstrated in the RARE scan mode which is well known to be particularly useful for tumour visualization.ResultsValidation in mice with RARE demonstrates improved stability with respect to ungated scanning where signal averaging is often used to reduce artefacts. SNR enhancement maps demonstrate the improved efficiency of the proposed method that is equivalent to at least a 2.5 fold reduction in scan time with respect to ungated signal averaging. A steady-state magnetisation transfer contrast prepared gradient echo implementation is observed to highlight tumour structure. Supplementary simulations demonstrate that only small variations in respiration rate are required to enable efficient sampling with the proposed method.ConclusionsThe proposed prospective gating acquisition scheme enables efficient multi-slice scanning in small animals at the optimum TR with reduced sensitivity to respiratory motion. The method is compatible with a wide range of complementary methods including non-Cartesian scan modes, partially parallel imaging, and compressed sensing. In particular, the proposed scheme reduces the need for continual close monitoring to effect operator intervention in response to respiratory rate changes, which is both difficult to maintain and precludes high throughput.