Fast 1 H spectroscopic imaging using steady state free precession and spectral–spatial RF pulses

Quantification of liver fat: A comprehensive review

Fat accumulation in the liver causes metabolic diseases such as obesity, hypertension, diabetes or dyslipidemia by affecting insulin resistance, and increasing the risk of cardiac complications and cardiovascular disease mortality. Fatty liver diseases are often reversible in their early stage; therefore, there is a recognized need to detect their presence and to assess its severity to recognize fat-related functional abnormalities in the liver. This is crucial in evaluating living liver donors prior to transplantation because fat content in the liver can change liver regeneration in the recipient and donor. There are several methods to diagnose fatty liver, measure the amount of fat, and to classify and stage liver diseases (e.g. hepatic steatosis, steatohepatitis, fibrosis and cirrhosis): biopsy (the gold-standard procedure), clinical (medical physics based) and image analysis (semi or fully automated approaches). Liver biopsy has many drawbacks: it is invasive, inappropriate for monitoring (i.e., repeated evaluation), and assessment of steatosis is somewhat subjective. Qualitative biomarkers are mostly insufficient for accurate detection since fat has to be quantified by a varying threshold to measure disease severity. Therefore, a quantitative biomarker is required for detection of steatosis, accurate measurement of severity of diseases, clinical decision-making, prognosis and longitudinal monitoring of therapy. This study presents a comprehensive review of both clinical and automated image analysis based approaches to quantify liver fat and evaluate fatty liver diseases from different medical imaging modalities.

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.

Interleaved narrow-band PRESS sequence with adiabatic spatial-spectral refocusing pulses for 1H MRSI at 7T

Proton magnetic resonance spectroscopic imaging ((1)H MRSI) is a useful technique for measuring metabolite levels in vivo, with Choline (Cho), Creatine (Cre), and N-Acetyl-Aspartate (NAA) being the most prominent MRS-detectable brain biochemicals. (1)H MRSI at very high fields, such as 7T, offers the advantages of higher SNR and improved spectral resolution. However, major technical challenges associated with high-field systems, such as increased B(1) and B(0) inhomogeneity as well as chemical shift localization (CSL) error, degrade the performance of conventional (1)H MRSI sequences. To address these problems, we have developed a Position Resolved Spectroscopy (PRESS) sequence with adiabatic spatial-spectral (SPSP) refocusing pulses, to acquire multiple narrow spectral bands in an interleaved fashion. The adiabatic SPSP pulses provide magnetization profiles that are largely invariant over the 40% B(1) variation measured across the brain at 7T. Additionally, there is negligible CSL error since the transmit frequency is separately adjusted for each spectral band. in vivo (1)H MRSI data were obtained from the brain of a normal volunteer using a standard PRESS sequence and the interleaved narrow-band PRESS sequence with adiabatic refocusing pulses. In comparison with conventional PRESS, this new approach generated high-quality spectra from an appreciably larger region of interest and achieved higher overall SNR.