Sex, age, and IDD are independently associated with paraspinal muscles FSF; only sex and age influence psoas FSF.

Purpose Quantitative T1, T2, T2*, and fat fraction (FF) maps are promising imaging biomarkers for the assessment of liver disease, however these are usually acquired in sequential scans. Here we propose an extended MR fingerprinting (MRF) framework enabling simultaneous liver T1, T2, T2*, and FF mapping from a single ~14 s breath‐hold scan. Methods A gradient echo (GRE) liver MRF sequence with nine readouts per TR, low flip angles (5‐15°), varying magnetisation preparation and golden angle radial trajectory is acquired at 1.5T to encode T1, T2, T2*, and FF simultaneously. The nine‐echo time‐series are reconstructed using a low‐rank tensor constrained reconstruction and used to fit T2*, B0 and to separate the water and fat signals. Water‐ and fat‐specific T1, T2, and M0 are obtained through dictionary matching, whereas FF estimation is extracted from the M0 maps. The framework was evaluated in a standardized T1/T2 phantom, a water‐fat phantom, and 12 subjects in comparison to reference methods. Preliminary clinical feasibility is shown in four patients. Results The proposed water T1, water T2, T2*, and FF maps in phantoms showed high coefficients of determination (r2 > 0.97) relative to reference methods. Measured liver MRF values in vivo (mean ± SD) for T1, T2, T2*, and FF were 671 ± 60 ms, 43.2 ± 6.8 ms, 29 ± 6.6 ms, and 3.2 ± 2.6% with biases of 92 ms, −7.1 ms, −1.4 ms, and 0.63% when compared to conventional methods. Conclusion A nine‐echo liver MRF sequence allows for quantitative multi‐parametric liver tissue characterization in a single breath‐hold scan of ~14 s. Future work will aim to validate the proposed approach in patients with liver disease.

No single-level FSF or CSA is representative of the whole lumbar spine. A standardized multi-level evaluation of the paraspinal musculature should be used in future research.

No abstract

Purpose -In medical applications, it is crucial to evaluate the geometric accuracy of rapid prototyping (RP) models. Current research on evaluating geometric accuracy has focused on identifying two or more specific anatomical landmarks on the original structure and the RP model, and comparing their corresponding linear distances. Such kind of accuracy metrics is ambiguous and may induce misrepresentations of the actual errors. The purpose of this paper is to propose an alternative method and metrics to measure the accuracy of RP models. Design/methodology/approach -The authors propose an accuracy metric composed of two different approaches: a global accuracy evaluation using volumetric intersection indexes calculated over segmented Computed Tomography scans of the original object and the RP model. Second, a local error metric that is computed from the surfaces of the original object and the RP model. This local error is rendered in a 3D surface using a color code, that allow differentiating regions where the model is overestimated, underestimated, or correctly estimated. Global and local error measurements are performed after rigid body registration, segmentation and triangulation. Findings -The results show that the method can be applied to different objects without any modification, and provide simple, meaningful and precise quantitative indexes to measure the geometric accuracy of RP models. Originality/value -The paper presents a new approach to characterize the geometric errors in RP models using global indexes and a local surface distribution of the errors. It requires minimum human intervention and it can be applied without any modification to any kind of object.

No abstract

The hemodynamic parameters from 4D flow datasets have shown promising diagnostic value in different cardiovascular pathologies. However, the behavior of these parameters can be affected when the 4D flow data are corrupted by respiratory motion. The purpose of this work was to perform a quantitative comparison between hemodynamic parameters computed from 4D flow cardiac MRI both with and without respiratory self-gating. We considered 4D flow MRI data from 15 healthy volunteers (10 men and 5 women, 30.40 ± 6.23 years of age) that were acquired at 3T. Using a semiautomatic segmentation process of the aorta, we obtained the hemodynamic parameters from the 4D flow MRI, with and without respiratory self-gating. A statistical analysis, using the Wilcoxon signed-rank test and Bland–Altman, was performed to compare the hemodynamic parameters from both acquisitions. We found that the calculations of the hemodynamic parameters from 4D flow data that were acquired without respiratory self-gating showed underestimated values in the aortic arch, and the descending and diaphragmatic aorta. We also found a significant variability of the hemodynamic parameters in the ascending aorta of healthy volunteers when comparing both methods. The 4D flow MRI requires respiratory compensation to provide reliable calculations of hemodynamic parameters.

No abstract