OBJECTIVE: The dystrophinopathies primarily affect males; however, female carriers of pathogenic dystrophin variants can develop skeletal muscle symptoms. This study aimed to evaluate muscle involvement and symptoms in females with dystrophinopathy using quantitative magnetic resonance imaging (MRI), functional assessments, and patient-reported outcomes.
METHODS: Controls and females with dystrophinopathy with muscle symptoms of pain, weakness, fatigue, or excessive tightness were enrolled in this cross-sectional study. Participants underwent lower extremity MRI to quantify muscle inflammation, replacement by fat, and disease asymmetry. Cardiac MRI, functional ability, muscle symptoms, and serum creatine kinase levels were also evaluated.
RESULTS: Six pediatric females with dystrophinopathy (mean age: 11.7 years), 11 adult females with dystrophinopathy (mean age: 41.3 years), and seven controls enrolled. The mean fat fraction was increased in females with dystrophinopathy compared to controls in the soleus (0.11 vs. 0.03, p = .0272) and vastus lateralis (0.16 vs. 0.03, p = .004). Magnetic resonance spectroscopy water T2, indicative of muscle inflammation, was elevated in the soleus and/or vastus lateralis in 11 of 17 individuals. North Star Ambulatory Assessment score was lower in the dystrophinopathy group compared to controls (29 vs. 34 points, p = .0428). From cardiac MRI, left ventricle T1 relaxation times were elevated in females with dystrophinopathy compared to controls (1311 ± 55 vs. 1263 ± 25 ms, p < .05), but ejection fraction and circumferential strain did not differ.
CONCLUSIONS: Symptomatic females with dystrophinopathy quantitatively demonstrate muscle replacement by fat and inflammation, along with impairments in functional ability and cardiac function. Additional research is needed to evaluate how symptoms and muscle involvement change longitudinally.

Presenting quantitative data using non-standardized color maps potentially results in unrecognized misinterpretation of data. Clinically meaningful color maps should intuitively and inclusively represent data without misleading interpretation. Uniformity of the color gradient for color maps is critically important. Maximal color and lightness contrast, readability for color vision-impaired individuals, and recognizability of the color scheme are highly desirable features. This article describes the use of color maps in five key quantitative MRI techniques: relaxometry, diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE)-MRI, MR elastography (MRE), and water-fat MRI. Current display practice of color maps is reviewed and shortcomings against desirable features are highlighted. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Spectroscopic imaging, rooted in Dixon\'s two-echo spin sequence to distinguish water and fat, has evolved significantly in acquisition and processing. Yet precise fat quantification remains a persistent challenge in ongoing research. With adequate phase characterization and correction, the fat composition models will impact measurements of fatty tissue. However, the effect of the used fat model in low-fat regions such as healthy muscle is unknown. In this study, we investigate the effect of assumed fat composition, in terms of chain length and double bond count, on fat fraction quantification in healthy muscle, while addressing phase and relaxometry confounders. For this purpose, we acquired bilateral thigh datasets from 38 healthy volunteers. Fat fractions were estimated using the IDEAL algorithm employing three different fat models fitted with and without the initial phase constrained. After data processing and model fitting, we used a convolutional neural net to automatically segment all thigh muscles and subcutaneous fat to evaluate the fitted parameters. The fat composition was compared with those reported in the literature. Overall, all the observed estimated fat composition values fall within the range of previously reported fatty acid composition based on gas chromatography measurements. All methods and models revealed different estimates of the muscle fat fractions in various evaluated muscle groups. Lateral differences changed from 0.5% to 5.3% in the hamstring muscle groups depending on the chosen method. The lowest observed left-right differences in each muscle group were all for the fat model estimating the number of double bonds with the initial phase unconstrained. With this model, the left-right differences were 0.64% ± 0.31%, 0.50% ± 0.27%, and 0.50% ± 0.40% for the quadriceps, hamstrings, and adductors muscle groups, respectively. Our findings suggest that a fat model estimating double bond numbers while allowing separate phases for each chemical species, given some assumptions, yields the best fat fraction estimate for our dataset.

UNASSIGNED: Radiation-induced damage to the organs at risk (OARs) in head-and-neck cancer (HNC) patient can result in long-term complications. Quantitative magnetic resonance imaging (qMRI) techniques such as diffusion-weighted imaging (DWI), DIXON for fat fraction (FF) estimation and T2 mapping could potentially provide a spatial assessment of such damage. The goal of this study is to validate these qMRI techniques in terms of accuracy in phantoms and repeatability in-vivo across a broad selection of healthy OARs in the HN region.
UNASSIGNED: Scanning was performed at a 3 T diagnostic MRI scanner, including the calculation of apparent diffusion coefficient (ADC) from DWI, FF and T2 maps. Phantoms were scanned to estimate the qMRI techniques bias using Bland-Altman statistics. Twenty-six healthy subjects were scanned twice in a test-retest study to determine repeatability. Repeatability coefficients (RC) were calculated for the parotid, submandibular, sublingual and tubarial salivary glands, oral cavity, pharyngeal constrictor muscle and brainstem. Additionally, a linear mixed-effect model analysis was used to evaluate the effect of subject-specific characteristics on the qMRI values.
UNASSIGNED: Bias was 0.009x10-3 mm2/s for ADC, -0.7 % for FF and -7.9 ms for T2. RCs ranged 0.11-0.25x10-3 mm2/s for ADC, 1.2-6.3 % for FF and 2.5-6.3 ms for T2. A significant positive linear relationship between age and the FF and T2 for some of the OARs was found.
UNASSIGNED: These qMRI techniques are feasible, accurate and repeatable, which is promising for treatment response monitoring and/or differentiating between healthy and unhealthy tissues due to radiation-induced damage in HNC patients.

BACKGROUND: This study evaluates the repeatability and reproducibility of fat-fraction percentage (FF%) in whole-body magnetic resonance imaging (WB-MRI) of prostate cancer patients with bone metastatic hormone naive disease.
METHODS: Patients were selected from the database of a prospective phase-II trial. The treatment response was assessed using the METastasis Reporting and Data System for Prostate (MET-RADS-P). Two operators identified a Small Active Lesion (SAL, <10 mm) and a Large Active Lesion (LAL, ≥10 mm) per patient, performing manual segmentation of lesion volume and the largest cross-sectional area. Measurements were repeated by one operator after two weeks. Intra- and inter-reader agreements were assessed via Interclass Correlation Coefficient (ICC) on first-order radiomics features.
RESULTS: Intra-reader ICC showed high repeatability for both SAL and LAL in a single slice (SS) and volumetric (VS) measurements with values ranging from 0.897 to 0.971. Inter-reader ICC ranged from 0.641 to 0.883, indicating moderate to good reproducibility. Spearman\'s rho analysis confirmed a strong correlation between SS and VS measurements for SAL (0.817) and a moderate correlation for LAL (0.649). Both intra- and inter-rater agreement exceeded 0.75 for multiple first-order features across lesion sizes.
CONCLUSIONS: This study suggests that FF% measurements are reproducible, particularly for larger lesions in both SS and VS assessments.

UNASSIGNED: Sporadic inclusion body myositis (sIBM) is the predominant idiopathic inflammatory myopathy (IIM) in older people. Limitations of classical clinical assessments have been discussed as possible explanations for failed clinical trials, underlining the need for more sensitive outcome measures. Quantitative muscle MRI (qMRI) is a promising candidate for evaluating and monitoring sIBM.
UNASSIGNED: Longitudinal assessment of qMRI in sIBM patients.
UNASSIGNED: We evaluated fifteen lower extremity muscles of 12 sIBM patients (5 females, mean age 69.6, BMI 27.8) and 12 healthy age- and gender-matched controls. Seven patients and matched controls underwent a follow-up evaluation after one year. Clinical assessment included testing for muscle strength with Quick Motor Function Measure (QMFM), IBM functional rating scale (IBM-FRS), and gait analysis (6-minute walking distance). 3T-MRI scans of the lower extremities were performed, including a Dixon-based sequence, T2 mapping and Diffusion Tensor Imaging. The qMRI-values fat-fraction (FF), water T2 relaxation time (wT2), fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ1), and radial diffusivity (RD) were analysed.
UNASSIGNED: Compared to healthy controls, significant differences for all qMRI parameters averaged over all muscles were found in sIBM using a MANOVA (p < 0.001). In low-fat muscles (FF < 10%), a significant increase of wT2 and FA with an accompanying decrease of MD, λ1, and RD was observed (p≤0.020). The highest correlation with clinical assessments was found for wT2 values in thigh muscles (r≤-0.634). Significant changes of FF (+3.0%), wT2 (+0.6 ms), MD (-0.04 10-3mm2/s), λ1 (-0.05 10-3mm2/s), and RD (-0.03 10-3mm2/s) were observed in the longitudinal evaluation of sIBM patients (p≤0.001). FA showed no significant change (p = 0.242).
UNASSIGNED: qMRI metrics correlate with clinical findings and can reflect different ongoing pathophysiological mechanisms. While wT2 is an emerging marker of disease activity, the role of diffusion metrics, possibly reflecting changes in fibre size and intracellular deposits, remains subject to further investigations.

Facioscapulohumeral muscular dystrophy (FSHD) affects roughly 1 in 7500 individuals. While at the population level there is a general pattern of affected muscles, there is substantial heterogeneity in muscle expression across- and within-patients. There can also be substantial variation in the pattern of fat and water signal intensity within a single muscle. While quantifying individual muscles across their full length using magnetic resonance imaging (MRI) represents the optimal approach to follow disease progression and evaluate therapeutic response, the ability to automate this process has been limited. The goal of this work was to develop and optimize an artificial intelligence-based image segmentation approach to comprehensively measure muscle volume, fat fraction, fat fraction distribution, and elevated short-tau inversion recovery signal in the musculature of patients with FSHD. Intra-rater, inter-rater, and scan-rescan analyses demonstrated that the developed methods are robust and precise. Representative cases and derived metrics of volume, cross-sectional area, and 3D pixel-maps demonstrate unique intramuscular patterns of disease. Future work focuses on leveraging these AI methods to include upper body output and aggregating individual muscle data across studies to determine best-fit models for characterizing progression and monitoring therapeutic modulation of MRI biomarkers.

OBJECTIVE: Fat deposition is an important marker of many metabolic diseases. As a noninvasive and convenient examination method, CT has been widely used for fat quantification. With the clinical application of photon-counting detector (PCD)-CT, we aimed to investigate the accuracy, stability, and dose level of PCD-CT using various scan settings for fat quantification.
METHODS: Eleven agar-based lipid-containing phantoms (vials with different fat fractions [FFs]; range: 0 %-100 %) were scanned using PCD-CT. Three scanning types (sequence scan, regular spiral scan with a pitch of 0.8, and high-pitch spiral scan with a pitch of 3.2), four tube voltages (90, 120, 140, and 100 kV with a tin filter), and three image quality (IQ) levels (IQ levels of 20, 40, and 80) were alternated, and each scan setting was used twice. For each scan, a 70-keV image was generated using the same reconstruction parameters. A regular spiral scan at 120 kV with IQ80 was used to transfer the CT numbers of all scans to the FF. Intraclass correlation coefficient (ICC) and Bland-Altman analysis were implemented for accuracy and agreement evaluation, and group differences were compared using analysis of variance.
RESULTS: Excellent agreement and accuracy of FF derived by PCD-CT with all scan settings was demonstrated by high ICCs (>0.9; range: 0.929-0.998, p < 0.017) and low bias (<5% range: -2.9 %-5%). The root mean square error (RMSE) between the PCD-CT-acquired FF and the reference standard ranged from 1.0 % to 5.0 %, among which the high-pitch scan at 120 kV with IQ20 accounted for the lowest RMSE (1.0 %). The spiral scan at 120 kV with IQ20 and IQ80 yielded the lowest bias (mean value: 1.19 % and 1.23 %, respectively).
CONCLUSIONS: Fat quantification using PCD-CT reconstructed at 70 keV was accurate and stable under various scan settings. PCD-CT has great potential for fat quantification using ultralow radiation doses.

[This corrects the article DOI: 10.3389/fonc.2024.1367907.].

UNASSIGNED: To assess the utility of fat fraction quantification using quantitative multi-echo Dixon for evaluating tumor proliferation and microvascular invasion (MVI) in hepatocellular carcinoma (HCC).
UNASSIGNED: A total of 66 patients with resection and histopathologic confirmed HCC were enrolled. Preoperative MRI with proton density fat fraction and R2* mapping was analyzed. Intratumoral and peritumoral regions were delineated with manually placed regions of interest at the maximum level of intratumoral fat. Correlation analysis explored the relationship between fat fraction and Ki67. The fat fraction and R2* were compared between high Ki67(>30%) and low Ki67 nodules, and between MVI negative and positive groups. Receiver operating characteristic (ROC) analysis was used for further analysis if statistically different.
UNASSIGNED: The median fat fraction of tumor (tFF) was higher than peritumor liver (5.24% vs 3.51%, P=0.012). The tFF was negatively correlated with Ki67 (r=-0.306, P=0.012), and tFF of high Ki67 nodules was lower than that of low Ki67 nodules (2.10% vs 4.90%, P=0.001). The tFF was a good estimator for low proliferation nodules (AUC 0.747, cut-off 3.39%, sensitivity 0.778, specificity 0.692). There was no significant difference in tFF and R2* between MVI positive and negative nodules (3.00% vs 2.90%, P=0.784; 55.80s-1 vs 49.15s-1, P=0.227).
UNASSIGNED: We infer that intratumor fat can be identified in HCC and fat fraction quantification using quantitative multi-echo Dixon can distinguish low proliferative HCCs.