All-systolic non-ECG-gated myocardial perfusion MRI: Feasibility of multi-slice continuous first-pass imaging

PURPOSE

To develop and test the feasibility of a new method for non-ECG-gated first-pass perfusion (FPP) cardiac MR capable of imaging multiple short-axis slices at the same systolic cardiac phase.

METHODS

A magnetization-driven pulse sequence was developed for non-ECG-gated FPP imaging without saturation-recovery preparation using continuous slice-interleaved radial sampling. The image reconstruction method, dubbed TRACE, used self-gating based on reconstruction of a real-time image-based navigator combined with reference-constrained compressed sensing. Data from ischemic animal studies (n = 5) was used in a simulation framework to evaluate temporal fidelity. Healthy subjects (n = 5) were studied using both the proposed approach and the conventional method to compare the myocardial contrast-to-noise ratio (CNR). Patients (n = 2) underwent adenosine stress studies using the proposed method.

RESULTS

Temporal fidelity of the developed method was shown to be sufficient at high heart-rates. The healthy volunteers studies demonstrated normal perfusion and no dark-rim artifacts. Compared with the conventional scheme, myocardial CNR for the proposed method was slightly higher (8.6 ± 0.6 versus 8.0 ± 0.7). Patient studies showed stress-induced perfusion defects consistent with invasive angiography.

CONCLUSION

The presented methods and results demonstrate feasibility of the proposed approach for high-resolution non-ECG-gated FPP imaging of 3 myocardial slices at the same systolic phase, and indicate its potential for achieving desirable image quality (high CNR and no dark-rim artifacts).

Radiofrequency field inhomogeneity compensation in high spatial resolution magnetic resonance spectroscopic imaging

Clinical magnetic resonance spectroscopy imaging (MRSI) is a non-invasive functional technique, whose mathematical framework falls into the category of linear inverse problems. However, its use in medical diagnostics is hampered by two main problems, both linked to the Fourier-based technique usually implemented for spectra reconstruction: poor spatial resolution and severe blurring in the spatial localization of the reconstructed spectra. Moreover, the intrinsic ill-posedness of the MRSI problem might be worsened by (i) spatially dependent distortions of the static magnetic field (B0) distribution, as well as by (ii) inhomogeneity in the power deposition distribution of the radiofrequency magnetic field (B1). Among several alternative methods, slim (Spectral Localization by IMaging) and bslim (B0 compensated slim) are reconstruction algorithms in which a priori information concerning the spectroscopic target is introduced into the reconstruction kernel. Nonetheless, the influence of the B1 field, particularly when its operating wavelength is close to the size of the human organs being studied, continues to be disregarded. starslim (STAtic and Radiofrequency-compensated slim), an evolution of the slim and bslim methods, is therefore proposed, in which the transformation kernel also includes the B1 field inhomogeneity map, thus allowing almost complete 3D modelling of the MRSI problem. Moreover, an original method for the experimental determination of the B1 field inhomogeneity map specific to the target under evaluation is also included. The compensation capabilities of the proposed method have been tested and illustrated using synthetic raw data reproducing the human brain.

Data-driven MRSI spectral localization via low-rank component analysis

Magnetic resonance spectroscopic imaging (MRSI) is a powerful tool capable of providing spatially localized maps of metabolite concentrations. Its utility, however, is often depreciated by spectral leakage artifacts resulting from low spatial resolution measurements through an effort to reduce acquisition times. Though model-based techniques can help circumvent these drawbacks, they require strong prior knowledge, and can introduce additional artifacts when the underlying models are inaccurate. We introduce a novel scheme in which a generative model is estimated from the raw MRSI data via a regularized variational framework that minimizes the model approximation error within a measurement-prescribed subspace. As additional a priori information, our approach relies only upon a measured field inhomogeneity map at high spatial resolution. We demonstrate the feasibility of our approach on both synthetic and experimental data.

Highly undersampled phase-contrast flow measurements using compartment-based k-t principal component analysis

The applicability of cine blood flow measurements in a clinical setting is often compromised by the long scan times associated with phase-contrast imaging. In this work, we propose an extension to the k-t principal component analysis method and demonstrate that by definition of spatial compartment-dependent temporal basis functions, significant improvements in reconstruction accuracy can be achieved relative to the original k-t principal component analysis and k-t SENSE formulations. Using this method, it is shown that prospective nominal undersampling of up to 16 corresponding to a net acceleration factor of 8 including training data acquisition can be realized while keeping the error in stroke volume below 5%. As a practical application, the acquisition of cine flow data in the aorta is demonstrated permitting assessment of two-dimensional velocity images and pulse wave velocities at 100 frames per second in a single breathhold per slice.

BSLIM: spectral localization by imaging with explicit B0 field inhomogeneity compensation

Magnetic resonance spectroscopy imaging (MRSI) is an attractive tool for medical imaging. However, its practical use is often limited by the intrinsic low spatial resolution and long acquisition time. Spectral localization by imaging (SLIM) has been proposed as a non-Fourier reconstruction algorithm that incorporates spatial a priori information about spectroscopically uniform compartments. Unfortunately, the influence of the magnetic field inhomogeneity--in particular, the susceptibility effects at tissues' boundaries--undermines the validity of the compartmental model. Therefore, we propose BSLIM as an extension of SLIM with field inhomogeneity compensation. A B0-field inhomogeneity map, which can be acquired rapidly and at high resolution, is used by the new algorithm as additional a priori information. We show that the proposed method is distinct from the generalized SLIM (GSLIM) framework. Experimental results of a two-compartment phantom demonstrate the feasibility of the method and the importance of inhomogeneity compensation.

Multiple region MRI

Traditional Fourier MR imaging (FT MRI) utilizes the Whittaker-Kotel'nikov-Shannon (WKS) sampling theorem. This theorem specifies the spatial frequency components which need to be measured to reconstruct an image with a known field of view (FOV). In this paper, we generalize this result in order to find the optimal k-space sampling for images that vanish except in multiple, possibly non-adjacent regions within the FOV. This provides the basis for "multiple region MRI" (mrMRI), a method of producing such images from a traction of the k-space samples required by the WKS theorem. Image reconstruction does not suffer from noise amplification and can be performed rapidly with fast Fourier transforms, just as in conventional FT MRI. The mrMRI method can also be used to reconstruct images that have low spatial-frequency components throughout the entire FOV and high spatial frequencies (i.e. edges) confined to multiple small regions. The greater efficiency of mrMRI sampling can be parlayed into increased temporal or spatial resolution whenever the imaged objects have signal or "edge" intensity confined to multiple small portions of the FOV. Possible areas of application include MR angiography (MRA), interventional MRI, functional MRI, and spectroscopic MRI. The technique is demonstrated by using it to acquire Gd-enhanced first-pass 3D MRA images of the carotid arteries without the use of bolus-timing techniques.

Biochemical heterogeneity in hysterectomized uterus measured by 31P NMR using SLIM localization

Ultrasound and magnetic resonance imaging show contrast between the inner and outer myometrium, which is useful in the diagnosis of gynecological disorders. To determine whether the image contrast is associated with biochemical differences between these myometrial regions, phosphorus metabolite concentrations in the inner one third of the myometrium (the junctional zone; JZ) were compared with the outermost one third of the myometrium (OM) in hysterectomized uteri using 31P spectral localization by imaging (SLIM). The technique was validated by comparing the results of SLIM with the results of standard Fourier-encoded spectroscopic imaging (FSI) analysis using phantoms, and by nonlocalized spectroscopy on biopsies taken from the same hysterectomy specimens. As expected theoretically, SLIM yielded better localization than FSI, as judged by spectral intensity and leakage measurements on phantom compartments of known composition. SLIM localization revealed that the JZ has a higher intracellular phosphomonoester (PME) concentration than does the OM, which was confirmed by nonlocalized spectroscopy, and that there is very little NMR-visible phosphorus in the cervix.