MRI-Derived Biomarkers Related to Sarcopenia: A Systematic Review

MRI allows quantitatively assessing muscle quantity and quality.

To summarize the role of MRI as a noninvasive technique for the identification of in vivo surrogate biomarker of sarcopenia.

Systematic review.

In April 2019, a systematic literature search (Medline/EMBASE) was performed to identify articles on the topic at issue.

No field strength or sequence restrictions.

After a literature search, study design, aim, sample size, demographics, magnetic field strength, imaged body region, MRI sequences, and imaging biomarker were extracted.

Data are presented as frequencies and percentages.

From 69 records identified through search query, 18 articles matched the inclusion criteria. All articles were published from 2012 and had a mainly prospective design (14/18, 78%). Sample size ranged from 9 to 284 subjects, for a total of 1706 enrolled subjects. Healthy subjects were enrolled or retrospectively selected in 8/18 (44%) articles, corresponding to 658 (39%) healthy subjects. Magnetic field strength was 1.5 or 3T in 14/18 (78%) studies. The most analyzed body regions were the thigh (7/18, 39%) and the trunk (6/18, 33%). Stratifying studies according to their aim, 13/18 (72%) studies focused on muscle quality and quantity, 3/18 (17%) studies on outcome prediction, and 2/18 articles (11%) addressed both aims. A wide set of MRI biomarkers have been proposed. Muscle cross-sectional area was the most used for muscle quantity estimation, while quantitative biomarkers of muscle fat content or fiber architecture were proposed to assess muscle quality.

The proposed biomarkers were assessed using different MRI sequences for different body regions in different subjects/patient cohorts, pointing out a lack of standardization on this topic. Future studies should test and compare the performance of proposed MRI biomarkers for sarcopenia characterization and quantification using a standardized experimental setup.

1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1117-1127.