ArticleNMR in biomedicine2024
Significant age-related differences between lower leg muscles of older and younger female subjects detected by ultrashort echo time magnetization transfer modeling.
Article in NMR in biomedicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Quantitative ultrashort echo time (UTE) magnetic resonance imaging of femoral trabecular bone in aging and osteoporosis.European radiology · 2026Article
- Assessment of vastus medialis muscle quality in knee osteoarthritis using ultrashort echo time magnetization transfer MR imaging.Skeletal radiology · 2025Article
- Evaluation of Magnetization Transfer Contrast Sequences: Application to Monitor Age-Related Differences in Muscle Macromolecular Fraction.Tomography (Ann Arbor, Mich.) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Magnetization transfer (MT) magnetic resonance imaging (MRI) can be used to estimate the fraction of water and macromolecular proton pools in tissues. MT modeling paired with ultrashort echo time acquisition (UTE-MT modeling) has been proposed to improve the evaluation of the myotendinous junction and fibrosis in muscle tissues, which the latter increases with aging. This study aimed to determine if the UTE-MT modeling technique is sensitive to age-related changes in the skeletal muscles of the lower leg. Institutional review board approval was obtained, and all recruited subjects provided written informed consent. The legs of 31 healthy younger (28.1 ± 6.1 years old, BMI = 22.3 ± 3.5) and 20 older (74.7 ± 5.5 years old, BMI = 26.7 ± 5.9) female subjects were imaged using UTE sequences on a 3 T MRI scanner. MT ratio (MTR), macromolecular fraction (MMF), macromolecular T2 (T2-MM), and water T2 (T2-W) were calculated using UTE-MT modeling for the anterior tibialis (ATM), posterior tibialis (PTM), soleus (SM), and combined lateral muscles. Results were compared between groups using the Wilcoxon rank sum test. Three independent observers selected regions of interest (ROIs) and processed UTE-MRI images separately, and the intraclass correlation coefficient (ICC) was calculated for a reproducibility study. Significantly lower mean MTR and MMF values were present in the older compared with the younger group in all studied lower leg muscles. T2-MM showed significantly lower values in the older group only for PTM and SM muscles. In contrast, T2-W showed significantly higher values in the older group. The age-related differences were more pronounced for MMF (-17 to -19%) and T2-W (+20 to 47%) measurements in all muscle groups compared with other investigated MR measures. ICCs were higher than 0.93, indicating excellent consistency between the ROI selection and MRI measurements of independent readers. As demonstrated by significant differences between younger and older groups, this research emphasizes the potential of UTE-MT MRI techniques in evaluating age-related skeletal muscle changes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.