Assessment of training-associated changes of the lumbar back muscle using a multiparametric MRI protocol

Front Physiol. 2024 Oct 17:15:1408244. doi: 10.3389/fphys.2024.1408244. eCollection 2024.

Abstract

Adaptations in muscle physiology due to long-term physical training have been monitored using various methods: ranging from invasive techniques, such as biopsy, to less invasive approaches, such as electromyography (EMG), to various quantitative magnetic resonance imaging (qMRI) parameters. Typically, these latter parameters are assessed immediately after exercise. In contrast, this work assesses such adaptations in a set of qMRI parameters obtained at rest in the lumbar spine muscles of volunteers. To this end, we developed a multiparametric measurement protocol to extract quantitative values of (water) T2, fat fraction, T1, and Intra Voxel Incoherent Motion (IVIM) diffusion parameters in the lumbar back muscle. The protocol was applied to 31 healthy subjects divided into three differently trained cohorts: two groups of athletes (endurance athletes and powerlifters) and a control group with a sedentary lifestyle. Significant differences in muscle water T2, fat fraction, and pseudo-diffusion coefficient linked to microcirculatory blood flow in muscle tissue were found between the trained and untrained cohorts. At the same time, diffusion coefficients (resolved along different directions) provided additional differentiation between the two groups of athletes. Specifically, the strength-trained athletes showed lower axial and higher radial diffusion components compared to the endurance-trained cohort, which may indicate muscle hypertrophy. In conclusion, utilizing multiparametric information revealed new insights into the potential of quantitative MR parameters to detect and quantify long-term effects associated with training in differently trained cohorts, even at rest.

Keywords: IVIM; diffusion; lumbar back muscle; qMRI; training.

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported by a graduate scholarship from the Friedrich-Schiller-University Jena and the state of Thuringia (Landesgraduiertenstipendium) (to MM), the Competence Center for Interdisciplinary Prevention (KIP) at the Friedrich Schiller University Jena, the German Professional Association for Statutory Accident Insurance and Prevention in the Foodstuffs Industry and the Catering Trade (BGN) (projects 1.1.7.22 & 1.1.7.23) and the German Research Foundation (Deutsche Forschungsgemeinschaft; KR 4783/2-1). We acknowledge support by the German Research Foundation Projekt-Nr. 512648189 and the Open Access Publication Fund of the Thueringer Universitaets- und Landesbibliothek Jena.