Application of quantitative magnetization transfer magnetic resonance imaging for characterization of dry-cured hams

Rotator cuff muscle fibrosis can be assessed using ultrashort echo time magnetization transfer MRI with fat suppression

Muscle degeneration following rotator cuff tendon tearing is characterized by fatty infiltration and fibrosis. While tools exist for the characterization of fat, the ability to noninvasively assess muscle fibrosis is limited. The purpose of this study was to evaluate the capability of quantitative ultrashort echo time T1 (UTE-T1) and UTE magnetization transfer (UTE-MT) mapping with and without fat suppression (FS) for the differentiation of injured and control rotator cuff muscles and for the detection of fibrosis. A rat model of chronic massive rotator cuff tearing (n = 12) was used with tenotomy of the right supraspinatus and infraspinatus tendons and silicone implants to prevent healing. Imaging was performed on a 3-T scanner, and UTE-T1 mapping with and without FS and UTE-MT with and without FS for macromolecular fraction (MMF) mapping was performed. At 20 weeks postinjury, T1 and MMF were measured in the supraspinatus and infraspinatus muscles of the injured and contralateral, internal control sides. Histology was performed and connective tissue fraction (CTF) was measured, defined as the area of collagen-rich extracellular matrix divided by the total muscle area. Paired t-tests and correlation analyses were performed. Significant differences between injured and control sides were found for CTF in the supraspinatus (mean ± SD, 14.5% ± 3.9% vs. 11.3% ± 3.7%, p = 0.01) and infraspinatus (17.0% ± 5.4% vs. 12.5% ± 4.6%, p < 0.01) muscles, as well as for MMF using UTE-MT FS in the supraspinatus (9.7% ± 0.3% vs. 9.5% ± 0.2%, p = 0.04) and infraspinatus (10.9% ± 0.8% vs. 10.1% ± 0.5%, p < 0.01) muscles. No significant differences between sides were evident for T1 without or with FS or for MMF using UTE-MT. Only MMF using UTE-MT FS was significantly correlated with CTF for both supraspinatus (r = 0.46, p = 0.03) and infraspinatus (r = 0.51, p = 0.01) muscles. Fibrosis occurs in rotator cuff muscle degeneration, and the UTE-MT FS technique may be helpful to evaluate the fibrosis component, independent from the fatty infiltration process.

Robust Assessment of Macromolecular Fraction (MMF) in Muscle with Differing Fat Fraction Using Ultrashort Echo Time (UTE) Magnetization Transfer Modeling with Measured T1

Magnetic resonance imaging (MRI) is widely regarded as the most comprehensive imaging modality to assess skeletal muscle quality and quantity. Magnetization transfer (MT) imaging can be used to estimate the fraction of water and macromolecular proton pools, with the latter including the myofibrillar proteins and collagen, which are related to the muscle quality and its ability to generate force. MT modeling combined with ultrashort echo time (UTE-MT modeling) may improve the evaluation of the myotendinous junction and regions with fibrotic tissues in the skeletal muscles, which possess short T2 values and higher bound-water concentration. The fat present in muscle has always been a source of concern in macromolecular fraction (MMF) calculation. This study aimed to investigate the impact of fat fraction (FF) on the estimated MMF in bovine skeletal muscle phantoms embedded in pure fat. MMF was calculated for several regions of interest (ROIs) with differing FFs using UTE-MT modeling with and without T1 measurement and B1 correction. Calculated MMF using measured T1 showed a robust trend, particularly with a negligible error (<3%) for FF < 20%. Around 5% MMF reduction occurred for FF > 30%. However, MMF estimation using a constant T1 was robust only for regions with FF < 10%. The MTR and T1 values were also robust for only FF < 10%. This study highlights the potential of the UTE-MT modeling with accurate T1 measurement for robust muscle assessment while remaining insensitive to fat infiltration up to moderate levels.

Optimization of the image acquisition procedure in low-field MRI for non-destructive analysis of loin using predictive models

The use of low-field magnetic resonance imaging (LF-MRI) scanners has increased in recent years. The low economic cost in comparison to high-field (HF-MRI) scanners and the ease of maintenance make this type of scanner the best choice for nonmedical purposes. However, LF-MRI scanners produce low-quality images, which encourages the identification of optimization procedures to generate the best possible images. In this paper, optimization of the image acquisition procedure for an LF-MRI scanner is presented, and predictive models are developed. The MRI acquisition procedure was optimized to determine the physicochemical characteristics of pork loin in a nondestructive way using MRI, feature extraction algorithms and data processing methods. The most critical parameters (relaxation times, repetition time, and echo time) of the LF-MRI scanner were optimized, presenting a procedure that could be easily reproduced in other environments or for other purposes. In addition, two feature extraction algorithms (gray level co-occurrence matrix (GLCM) and one point fractal texture algorithm (OPFTA)) were evaluated. The optimization procedure was validated by using several evaluation metrics, achieving reliable and accurate results (r > 0.85; weighted absolute percentage error (WAPE) lower than 0.1%; root mean square error of prediction (RMSEP) lower than 0.1%; true standard deviation (TSTD) lower than 2; and mean absolute error (MAE) lower than 2). These results support the high degree of feasibility and accuracy of the optimized procedure of LF-MRI acquisition. No other papers present a procedure to optimize the image acquisition process in LF-MRI. Eventually, the optimization procedure could be applied to other LF-MRI systems.