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Purpose: Determine the correct mathematical phase description for balanced steady‐state free precession (bSSFP) signals in multi‐compartment systems. Theory and Methods: Based on published bSSFP signal models, different phase descriptions can be formulated: one predicting the presence and the other predicting the absence of destructive interference effects in multi‐compartment systems. Numerical simulations of bSSFP signals of water and acetone were performed to evaluate the predictions of these different phase descriptions. For experimental validation, bSSFP profiles were measured at 3T using phase‐cycled bSSFP acquisitions performed in a phantom containing mixtures of water and acetone, which replicates a system with two signal components. Localized single voxel MRS was performed at 7T to determine the relative chemical shift of the acetone‐water mixtures. Results: Based on the choice of phase description, the simulated bSSFP profiles of water‐acetone mixtures varied significantly, either displaying or lacking destructive interference effects, as predicted theoretically. In phantom experiments, destructive interference was consistently observed in the measured bSSFP profiles of water‐acetone mixtures, supporting the theoretical description that predicts such interference effects. The connection between the choice of phase description and predicted observation enables unambiguous experimental identification of the correct phase description for multi‐compartment bSSFP profiles, which is consistent with the Bloch equations. Conclusion: The study emphasizes that consistent phase descriptions are crucial for accurately describing multi‐compartment bSSFP signals, as incorrect phase descriptions result in erroneous predictions. [ABSTRACT FROM AUTHOR]

This article discusses the importance of glioma tumor grading in providing prognostic information and guiding treatment decisions. The World Health Organization (WHO) has standardized the glioma grading system, which includes morphological characteristics, histological findings, and molecular markers. Artificial intelligence (AI) can assist in glioma grading by analyzing radiomics features extracted from MRI images. A comparative study was conducted to evaluate the performance of different machine learning algorithms for glioma grading using the old and new WHO classification systems. The results showed that the XGBoost algorithm performed well, particularly with the WHO 2021 grading system. The article emphasizes the need for further research and the development of robust and reproducible radiomics models for glioma grading. [Extracted from the article]

Background: Pseudo‐spiral Cartesian sampling with compressed sensing reconstruction has facilitated highly accelerated 4D flow magnetic resonance imaging (MRI) in various cardiovascular structures. However, unlike echo planar imaging (EPI)‐accelerated 4D flow MRI, it has not been validated in whole‐heart applications. Hypothesis: Pseudo‐spiral 4D flow MRI (PROUD [PROspective Undersampling in multiple Dimensions]) is comparable to EPI in robustness of valvular flow measurements and remains comparable as the undersampling factor is increased and scan time reduced. Study Type: Prospective. Population: Twelve healthy subjects and eight patients with valvular regurgitation. Field Strength/Sequence: 3.0 T; PROUD and EPI 4D flow sequences, 2D flow and balanced steady‐state free precession sequences. Assessment Valvular blood flow was quantified using valve tracking. PROUD‐ and EPI‐based measurements of aortic (AV) and pulmonary (PV) flow volumes and left and right ventricular stroke volumes were tested for agreement with 2D MRI‐based measurements. PROUD reconstructions with undersampling factors (R) of 9, 14, 28, and 56 were tested for intervalve consistency (per valve, compared to the other valves) and preservation of peak velocities and E/A ratios. Statistical Tests: We used repeated measures ANOVA, Bland‐Altman, Wilcoxon signed rank, and intraclass correlation coefficients. P < 0.05 was considered statistically significant. Results: PROUD and EPI intervalve consistencies were not significantly different both in healthy subjects (valve‐averaged mean difference [limits of agreement width]: 3.2 ± 0.8 [8.7 ± 1.1] mL/beat for PROUD, 5.5 ± 2.9 [13.7 ± 2.3] mL/beat for EPI, P = 0.07) and in patients with valvular regurgitation (2.3 ± 1.2 [15.3 ± 5.9] mL/beat for PROUD, 0.6 ± 0.6 [19.3 ± 2.9] mL/beat for EPI, P = 0.47). Agreement between EPI and PROUD was higher than between 4D flow (EPI or PROUD) and 2D MRI for forward flow, stroke volumes, and regurgitant volumes. Up to R = 28 in healthy subjects and R = 14 in patients with valvular regurgitation, PROUD intervalve consistency remained comparable to that of EPI. Peak velocities and E/A ratios were preserved up to R = 9. Conclusion: PROUD is comparable to EPI in terms of intervalve consistency and may be used with higher undersampling factors to shorten scan times further. Level of Evidence: 1 Technical Efficacy Stage: 2 [ABSTRACT FROM AUTHOR]

This is in line with previously reported predictions[[7], [9]] that focused on differentiating between CPP and non-CPP patients, rather than specifically on ICPP and PPP, without the use of MRI data. Puberty in girls typically starts between the ages of 8 and 13 and is characterized by the onset of breast development and the first menstrual period.[1] However, some girls may experience early onset of puberty, a condition known as precocious puberty (PP), which can be categorized as gonadotropin-releasing hormone (GnRH)-dependent or GnRH-independent. [Extracted from the article]

Introduction: Time‐resolved three‐dimensional phase contrast MRI (4D flow) of aortic blood flow requires acceleration to reduce scan time. Two established techniques for highly accelerated 4D flow MRI are k‐t principal component analysis (k‐t PCA) and compressed sensing (CS), which employ either regular or random k‐space undersampling. The goal of this study was to gain insights into the quantitative differences between k‐t PCA‐ and CS‐derived aortic blood flow, especially for high temporal resolution CS 4D flow MRI. Methods: The scan protocol consisted of both k‐t PCA and CS accelerated 4D flow MRI, as well as a 2D flow reference scan through the ascending aorta acquired in 15 subjects. 4D flow scans were accelerated with factor R = 8. For CS accelerated scans, we used a pseudo‐spiral Cartesian sampling scheme, which could additionally be reconstructed at higher temporal resolution, resulting in R = 13. 4D flow data were compared with the 2D flow scan in terms of flow, peak flow and stroke volume. A 3D peak systolic voxel‐wise velocity and wall shear stress (WSS) comparison between k‐t PCA and CS 4D flow was also performed. Results: The mean difference in flow/peak flow/stroke volume between the 2D flow scan and the 4D flow CS with R = 8 and R = 13 was 4.2%/9.1%/3.0% and 5.3%/7.1%/1.9%, respectively, whereas for k‐t PCA with R = 8 the difference was 9.7%/25.8%/10.4%. In the voxel‐by‐voxel 4D flow comparison we found 13.6% and 3.5% lower velocity and WSS values of k‐t PCA compared with CS with R = 8, and 15.9% and 5.5% lower velocity and WSS values of k‐t PCA compared with CS with R = 13. Conclusion: Pseudo‐spiral accelerated 4D flow acquisitions in combination with CS reconstruction provides a flexible choice of temporal resolution. We showed that our proposed strategy achieves better agreement in flow values with 2D reference scans compared with using k‐t PCA accelerated acquisitions. [ABSTRACT FROM AUTHOR]

Purpose: 3D time‐resolved (4D) phase contrast MRI can be used to study muscle contraction. However, 3D coverage with sufficient spatiotemporal resolution can only be achieved by interleaved acquisitions during many repetitions of the motion task, resulting in long scan times. The aim of this study was to develop a compressed sensing accelerated 4D phase contrast MRI technique for quantification of velocities and strain rate of the muscles in the lower leg during active plantarflexion/dorsiflexion. Methods: Nine healthy volunteers were scanned during active dorsiflexion/plantarflexion task. For each volunteer, we acquired a reference scan, as well as 4 different accelerated scans (k‐space undersampling factors: 3.14X, 4.09X, 4.89X, and 6.41X) obtained using Cartesian Poisson disk undersampling schemes. The data was reconstructed using a compressed sensing pipeline. For each scan, velocity and strain rate values were quantified in the gastrocnemius lateralis, gastrocnemius medialis, tibialis anterior, and soleus. Results: No significant differences in velocity values were observed as a function acceleration factor in the investigated muscles. The strain rate calculation resulted in one positive (s+) and one negative (s−) eigenvalue, whereas the third eigenvalue (s3) was consistently 0 for all the acquisitions. No significant differences were observed for the strain rate eigenvalues as a function of acceleration factor. Conclusions: Data undersampling combined with compressed sensing reconstruction allowed obtainment of time‐resolved phase contrast acquisitions with 3D coverage and quantitative information comparable to the reference scan. The 3D sensitivity of the method can help in understanding the connection between muscle architecture and muscle function in future studies. [ABSTRACT FROM AUTHOR]

The cover image is based on the Research Article I Pseudo-spiral sampling and compressed sensing reconstruction provides flexibility of temporal resolution in accelerated aortic 4D flow MRI: A comparison with k-t principal component analysis i by Lukas M. Gottwald et al., https://doi.org/10.1002/nbm.4255. [Extracted from the article]

Magnetic resonance imaging (MRI) can potentially be used for non-invasive screening of patients with stable angina pectoris to identify probable obstructive coronary artery disease. MRI-based coronary blood flow quantification has to date only been performed in a 2D fashion, limiting its clinical applicability. In this study, we propose a framework for coronary blood flow quantification using accelerated 4D flow MRI with respiratory motion correction and compressed sensing image reconstruction. We investigate its feasibility and repeatability in healthy subjects at rest. Fourteen healthy subjects received 8 times-accelerated 4D flow MRI covering the left coronary artery (LCA) with an isotropic spatial resolution of 1.0 mm 3 . Respiratory motion correction was performed based on 1) lung-liver navigator signal, 2) real-time monitoring of foot-head motion of the liver and LCA by a separate acquisition, and 3) rigid image registration to correct for anterior-posterior motion. Time-averaged diastolic LCA flow was determined, as well as time-averaged diastolic maximal velocity (V MAX ) and diastolic peak velocity (V PEAK ). 2D flow MRI scans of the LCA were acquired for reference. Scan-rescan repeatability and agreement between 4D flow MRI and 2D flow MRI were assessed in terms of concordance correlation coefficient (CCC) and coefficient of variation (CV). The protocol resulted in good visibility of the LCA in 11 out of 14 subjects (six female, five male, aged 28 ± 4 years). The other 3 subjects were excluded from analysis. Time-averaged diastolic LCA flow measured by 4D flow MRI was 1.30 ± 0.39 ml/s and demonstrated good scan-rescan repeatability (CCC/CV = 0.79/20.4%). Time-averaged diastolic V MAX (17.2 ± 3.0 cm/s) and diastolic V PEAK (24.4 ± 6.5 cm/s) demonstrated moderate repeatability (CCC/CV = 0.52/19.0% and 0.68/23.0%, respectively). 4D flow- and 2D flow-based diastolic LCA flow agreed well (CCC/CV = 0.75/20.1%). Agreement between 4D flow MRI and 2D flow MRI was moderate for both diastolic V MAX and V PEAK (CCC/CV = 0.68/20.3% and 0.53/27.0%, respectively). In conclusion, the proposed framework of accelerated 4D flow MRI equipped with respiratory motion correction and compressed sensing image reconstruction enables repeatable diastolic LCA flow quantification that agrees well with 2D flow MRI., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Blanken, Schrauben, Peper, Gottwald, Coolen, van Wijk, Piek, Strijkers, Planken, van Ooij and Nederveen.)