Dataset Information

Accelerated Wideband Myocardial Perfusion Pulse Sequence with Compressed Sensing Reconstruction for Myocardial Blood Flow Quantification in Patients with a Cardiac Implantable Electronic Device.

ABSTRACT: Purpose:To develop an accelerated wideband cardiac perfusion pulse sequence and test whether it can produce diagnostically acceptable image quality and whether it can be used to reliably quantify myocardial blood flow (MBF) in patients with a cardiac implantable electronic device (CIED). Materials and Methods:A fivefold-accelerated wideband perfusion pulse sequence was developed using compressed sensing to sample one arterial input function plane and three myocardial perfusion (MP) planes per heartbeat in patients with a CIED with heart rates as high as 102 beats per minute. Resting perfusion scans were performed in 10 patients with a CIED and in 10 patients with no device as a control group. Two clinical readers compared the resulting images and retrospective images of the 10 patients with a CIED, which were obtained by using a previously described twofold-accelerated wideband perfusion pulse sequence with temporal generalized autocalibrating partially parallel acquisition. Summed visual score (SVS) was defined as the sum of conspicuity, artifact, and noise scores individually ranging from 1 (worst) to 5 (best). Resting MBF in the remote zones was quantified using Fermi deconvolution. Results:Median SVS was significantly different (P < .05) between the prospective and retrospective CIED groups (13 vs nine) and between the nondevice group and the retrospective CIED group (13.5 vs nine); all median SVSs were nine or greater (clinically acceptable cut point). The median resting MBF in remote zones was not significantly different (P = .27) between patients with a CIED (1.1 mL/min/g; median left ventricular ejection fraction [LVEF], 52.5%) and patients with no device (1.3 mL/min/g; median LVEF, 64.0%). Mean MBF values were consistent with those (mean resting MBF range, 1.0-1.2 mL/min/g) reported by two prior state-of-the-art cardiac perfusion MRI studies. Conclusion:The proposed scan yielded diagnostically acceptable image quality and enabled reliable quantification of MBF with three MP planes per heartbeat in patients with a CIED with heart rates as high as 102 beats per minute. Supplemental material is available for this article. © RSNA, 2020.

SUBMITTER: Hong K

PROVIDER: S-EPMC7207204 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Accelerated Wideband Myocardial Perfusion Pulse Sequence with Compressed Sensing Reconstruction for Myocardial Blood Flow Quantification in Patients with a Cardiac Implantable Electronic Device.

Hong KyungPyo K Collins Jeremy D JD Freed Benjamin H BH Fan Lexiaozi L Arai Andrew E AE Hsu Li-Yueh LY Lee Daniel C DC Kim Daniel D

Radiology. Cardiothoracic imaging 20200416 2

<h4>Purpose</h4>To develop an accelerated wideband cardiac perfusion pulse sequence and test whether it can produce diagnostically acceptable image quality and whether it can be used to reliably quantify myocardial blood flow (MBF) in patients with a cardiac implantable electronic device (CIED).<h4>Materials and methods</h4>A fivefold-accelerated wideband perfusion pulse sequence was developed using compressed sensing to sample one arterial input function plane and three myocardial perfusion (MP ...[more]

PMID: 32420548

Similar Datasets

Project description:Electron paramagnetic resonance (EPR) imaging has evolved as a promising tool to provide non-invasive assessment of tissue oxygenation levels. Due to the extremely short T2 relaxation time of electrons, single point imaging (SPI) is used in EPRI, limiting achievable spatial and temporal resolution. This presents a problem when attempting to measure changes in hypoxic state. In order to capture oxygen variation in hypoxic tissues and localize cycling hypoxia regions, an accelerated EPRI imaging method with minimal loss of information is needed.We present an image acceleration technique, partial Fourier compressed sensing (PFCS), that combines compressed sensing (CS) and partial Fourier reconstruction. PFCS augments the original CS equation using conjugate symmetry information for missing measurements. To further improve image quality in order to reconstruct low-resolution EPRI images, a projection onto convex sets (POCS)-based phase map and a spherical-sampling mask are used in the reconstruction process. The PFCS technique was used in phantoms and in vivo SCC7 tumor mice to evaluate image quality and accuracy in estimating O2 concentration.In both phantom and in vivo experiments, PFCS demonstrated the ability to reconstruct images more accurately with at least a 4-fold acceleration compared to traditional CS. Meanwhile, PFCS is able to better preserve the distinct spatial pattern in a phantom with a spatial resolution of 0.6mm. On phantoms containing Oxo63 solution with different oxygen concentrations, PFCS reconstructed linewidth maps that were discriminative of different O2 concentrations. Moreover, PFCS reconstruction of partially sampled data provided a better discrimination of hypoxic and oxygenated regions in a leg tumor compared to traditional CS reconstructed images.EPR images with an acceleration factor of four are feasible using PFCS with reasonable assessment of tissue oxygenation. The technique can greatly enhance EPR applications and improve our understanding cycling hypoxia. Moreover this technique can be easily extended to various MRI applications.

Project description:Recent advances in compressed sensing (CS) enable accurate CT image reconstruction from highly undersampled and noisy projection measurements, due to the sparsifiable feature of most CT images using total variation (TV). These novel reconstruction methods have demonstrated advantages in clinical applications where radiation dose reduction is critical, such as onboard cone-beam CT (CBCT) imaging in radiation therapy. The image reconstruction using CS is formulated as either a constrained problem to minimize the TV objective within a small and fixed data fidelity error, or an unconstrained problem to minimize the data fidelity error with TV regularization. However, the conventional solutions to the above two formulations are either computationally inefficient or involved with inconsistent regularization parameter tuning, which significantly limit the clinical use of CS-based iterative reconstruction. In this paper, we propose an optimization algorithm for CS reconstruction which overcomes the above two drawbacks.The data fidelity tolerance of CS reconstruction can be well estimated based on the measured data, as most of the projection errors are from Poisson noise after effective data correction for scatter and beam-hardening effects. We therefore adopt the TV optimization framework with a data fidelity constraint. To accelerate the convergence, we first convert such a constrained optimization using a logarithmic barrier method into a form similar to that of the conventional TV regularization based reconstruction but with an automatically adjusted penalty weight. The problem is then solved efficiently by gradient projection with an adaptive Barzilai-Borwein step-size selection scheme. The proposed algorithm is referred to as accelerated barrier optimization for CS (ABOCS), and evaluated using both digital and physical phantom studies.ABOCS directly estimates the data fidelity tolerance from the raw projection data. Therefore, as demonstrated in both digital Shepp-Logan and physical head phantom studies, consistent reconstruction performances are achieved using the same algorithm parameters on scans with different noise levels and∕or on different objects. On the contrary, the penalty weight in a TV regularization based method needs to be fine-tuned in a large range (up to seven times) to maintain the reconstructed image quality. The improvement of ABOCS on computational efficiency is demonstrated in the comparisons with adaptive-steepest-descent-projection-onto-convex-sets (ASD-POCS), an existing CS reconstruction algorithm also using constrained optimization. ASD-POCS alternatively minimizes the TV objective using adaptive steepest descent (ASD) and the data fidelity error using projection onto convex sets (POCS). For similar image qualities of the Shepp-Logan phantom, ABOCS requires less computation time than ASD-POCS in MATLAB by more than one order of magnitude.We propose ABOCS for CBCT reconstruction. As compared to other published CS-based algorithms, our method has attractive features of fast convergence and consistent parameter settings for different datasets. These advantages have been demonstrated on phantom studies.

Dataset Information

Accelerated Wideband Myocardial Perfusion Pulse Sequence with Compressed Sensing Reconstruction for Myocardial Blood Flow Quantification in Patients with a Cardiac Implantable Electronic Device.

Publications

Accelerated Wideband Myocardial Perfusion Pulse Sequence with Compressed Sensing Reconstruction for Myocardial Blood Flow Quantification in Patients with a Cardiac Implantable Electronic Device.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets