Value of Cardiac Cine MRI in Comparison to Contrast Transcranial Doppler Sonography for Patent Foramen Ovale Assessment in Patients with Cerebral Disorders

Purpose: To investigate the clinical feasibility of diagnosing and classifying patent foramen ovale (PFO) in patients with cerebral disorders by cardiac cine MRI (CCMRI) without contrast.Materials and Methods: Forty-four patients (24 males and 20 females; mean age, 41.3 years; range, 21–64 years) with cerebral disorders underwent contrast transcranial Doppler sonography (cTCD) and non-enhanced CCMRI examinations between October 2019 and March 2020. CCMRI was performed with a 3.0T magnetic resonance (MR) scanner using the OBL FIESTA CINE 4CH sequence. The scanning direction was perpendicular to the interatrial septum (IAS). The obtained MR images were analyzed by AW station 4.4. Pseudo-color coding was performed based on the different phases. The blood shunt condition was observed and recorded, noting the PFO length and width and whether it was complicated by IAS aneurysm or secondary septum thickening.Results: Thirty-nine of the 44 patients with cerebral disorders were confirmed to have right-to-left shunt by cTCD, and 37 of them were diagnosed with PFO by CCMRI. Two of the five remaining patients were also diagnosed with PFO by CCMRI. Compared with cTCD as a standard, CCMRI assessment resulted in the following: sensitivity, 94.9%; specificity, 60.0%; accuracy, 90.9%; positive predictive value, 94.9%; negative predictive value, 60.0%; area under the curve, 0.774. Using pseudo-color coding, a right-to-left color jet was observed in 34 patients, and a two-way shunt was found in five. IAS aneurysm and secondary septum thickening were found in five and three patients (11.4% and 6.8%), respectively. The maximum PFO diameters ranged from 1.7 to 16.8 mm, and the mean diameter was 5.4 ± 3.4 mm.Conclusion: The noninvasive CCMRI without contrast proved an excellent method for PFO identification, evaluation, and classification, with high sensibility (92.85%) and concordance (90.9%) compared to cTCD.

Joint Reconstruction Framework of Compressed Sensing and Nonlinear Parallel Imaging for Dynamic Cardiac Magnetic Resonance Imaging

Compressed Sensing (CS) and parallel imaging are two promising techniques that accelerate the MRI acquisition process. Combining these two techniques is of great interest due to the complementary information used in each. In this study, we propose a new reconstruction framework for dynamic cardiac imaging that takes advantage of both CS-based dynamic imaging and one nonlinear parallel imaging technique. The method decouples the reconstruction process into two sequential steps: use CS to reconstruct a series of aliased dynamic images from the highly undersampled k-space data; use nonlinear GRAPPA method, one nonlinear technique of parallel imaging, to reconstruct the original dynamic images from the k-space data that has been reconstructed by CS. The sampling scheme of the proposed method is designed to simultaneously satisfy the incoherent undersampling requirement for CS and the structured undersampling requirement for nonlinear parallel imaging. Four in vivo experiments of dynamic cardiac cine MRI were carried out with retrospective undersampling to evaluate the performance of the proposed method. Experiments show the proposed method of dynamic cardiac cine MRI is superior at reducing aliasing artifacts and preserving the spatial details and temporal variations, when compared with k-t FOCUSS and k-t FOCUSS with sensitivity encoding, using the same numbers of measurements. The proposed joint reconstruction framework effectively combines the CS method and one nonlinear technique of parallel imaging, and improves the image quality of dynamic cardiac cine MRI reconstruction when comparing to the state-of-the-art methods.

Segmentation of Biventricle in Cardiac Cine MRI via Nested Capsule Dense Network

Cardiac magnetic resonance image (MRI) has been widely used in diagnosis of cardiovascular diseases because of its noninvasive nature and high image quality. The evaluation standard of physiological indexes in cardiac diagnosis is essentially the accuracy of segmentation of left ventricle (LV) and right ventricle (RV) in cardiac MRI. In this paper, we propose a novel Nested Capsule Dense Network (NCDN) structure based on the FC-DenseNet model and capsule convolution-capsule deconvolution. Different from the traditional symmetric single codec network structure such as U-net, NCDN uses multiple codecs instead of a single codec to achieve multi-resolution, which makes it possible to save more spatial information and improve the robustness of the model. The proposed model is tested on three datasets that includes York University Cardiac MRI dataset, Automated Cardiac Diagnosis Challenge (ACDC-2017), and local dataset. The results show that the proposed NCDN outperforms the state-of-the-art methods.

Elastic AlignedSENSE for Dynamic MR Reconstruction: A Proof of Concept in Cardiac Cine

Numerous methods in the extensive literature on magnetic resonance imaging (MRI) reconstruction exploit temporal redundancy to accelerate cardiac cine. Some of them include motion compensation, which involves high computational costs and long runtimes. In this work, we proposed a method—elastic alignedSENSE (EAS)—for the direct reconstruction of a motion-free image plus a set of nonrigid deformations to reconstruct a 2D cardiac sequence. The feasibility of the proposed approach was tested in 2D Cartesian and golden radial multi-coil breath-hold cardiac cine acquisitions. The proposed approach was compared against parallel imaging compressed sense (sPICS) and group-wise motion corrected compressed sense (GWCS) reconstructions. EAS provides better results on objective measures with considerable less runtime when an acceleration factor is higher than 10×. Subjective assessment of an expert, however, invited proposing the combination of EAS and GWCS as a preferable alternative to GWCS or EAS in isolation.