Longitudinal Analysis of Spontaneous Mechanical Activities in Resting Leg Musculature Assessed by Diffusion-Weighted Imaging: Preliminary Results
Martin Schwartz1,2, Günter Steidle1, Petros Martirosian1, Thomas Küstner1,2,3, Jürgen Machann1,4,5, Anja Böhm4,5,6, Cora Weigert4,5,6, Bin Yang2, and Fritz Schick1

1Section on Experimental Radiology, Department of Diagnostic and Interventional Radiology, University Hospital of Tübingen, Tübingen, Germany, 2Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany, 3School of Biomedical Engineering & Imaging Sciences, King’s College London, St. Thomas’ Hospital, London, United Kingdom, 4Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany, 5German Center for Diabetes Research (DZD), Tübingen, Germany, 6Department of Endocrinology and Diabetology, Angiology, Nephrology and Clinical Chemistry, University Hospital Tübingen, Tübingen, Germany


Accurate quantification and grading of spontaneous mechanical activity of musculature of healthy and non-healthy subjects as measurable by single-shot diffusion-sensitive MRI requires certain long-term stability in order to reflect changes in the underlying muscular condition. Up to now, no longitudinal studies have been conducted, thus short- as well as long-term variation in the same subject under examination is unknown. This work examines the impact of the time of day when the examination takes places as well as long-term changes over 23-62 months in several subjects.


Spontaneous mechanical activities of the human musculature (SMAM1) have shown a high correlation to muscular electrical activity2 as well as anatomical fiber orientation3. SMAMs can be quantitatively assessed by diffusion-weighted imaging (DWI). To reveal temporal changes for a progressive quantification of the same subjects, as well as to distinguish between healthy population and subgroups with different metabolic or neuromuscular condition, the longitudinal behavior of spontaneous activities is of interest to ensure reliable grading and to reduce bias by systematic errors, e.g., time point of measurement during the day. Therefore, a data base with longitudinal measurements from a small cohort with 13 subjects is evaluated for the first time in this work. Furthermore, short-term variation was analyzed in order to assess the influence of the measurement time point on activity distribution.


A data base of 46 individual DWI time-series measurements from 13 subjects (age: 36.5±11.5 years, BMI: 26.8±2.9 kg/m²) were retrospectively evaluated. All measurements were conducted on 3 T MR systems (MAGNETOM Trio, Skyra, Prismafit, Vida, Siemens Healthcare, Erlangen, Germany) with a 15-channel Tx/Rx knee-coil or body-array coils. Series of 500 repetitions of transverse images were recorded at the maximum diameter of the right calf or in the middle position of the right thigh in supine position with a prototype diffusion-weighted stimulated-echo EPI (STE-DWI) sequence or a diffusion-weighted Stejskal-Tanner spin-echo EPI (SE-DWI) sequence. Measurement parameters: matrix size: 64-80 × 64-80, FoV: 190-240 × 190-240 mm², TE: 26 ms (STE-DWI), 53 ms (SE-DWI), TR: 500 ms, slice-thickness: 6 mm, b-value: 100 s/mm², SPAIR for fat suppression and mixing time TM: 145 ms (STE-DWI). Subjects were sorted regarding date of measurement and time point in three different subsets. These subsets are given in Table 1: Short-term: Three subjects with DWI measurements on the same day (in the morning, noon and evening). Medium-term: 12 subjects with DWI measurements within one year, whereas 7 subjects were from a diabetes prevention study with an exercise training intervention between both measurements. The training program lasted 8 weeks and consisted of three supervised exercise sessions per week. Each training session consisted of 30 min of bicycle ergometer exercise and 30 min walking on a treadmill at 80% of VO2peak. Long-term: Four subjects with DWI measurements over 23-62 months. Care was taken that all subjects rest before DWI measurement and that imaging parameters which can influence the sensitivity of the MR sequence to image spontaneous activities, e.g., excitation scheme, b-value and mixing time, were in consensus within one subject. Data processing: First, all DWI within a time-series were co-registered. Therefore, a common space reference image was calculated based on principle component analysis. Subsequently, all images were registered on this reference image by a Local All-Pass registration4,5. SMAMs in DWI were evaluated by a semi-automated graph-based segmentation approach6. Evaluation: Gross movements of the musculature were manually discarded before further evaluation. Number of events and event count maps (ECM) were assessed to analyze the temporal behavior of spontaneous activities.

Results & Discussion:

Intra-day spontaneous activity distribution is evaluated for three subjects in Fig. 1A. Only minor variability is revealed for Subject #1 and #3, whereas one time point of Subject #2 shows increased activity. ECMs in Fig. 1B show that the same muscular regions are active in the morning, noon as well as evening. Mean time-difference between DWI measurements for the medium-term evaluation was 91±58 days. Number of SMAM-affected DWIs and ECMs are depicted in Fig. 2 for healthy subjects and exercise program attendees (dashed). Activity seems not to be influenced by the exercise program in this special population. Evaluation of the long-term analysis is depicted in Fig. 3. Subject #2 shows an increase in activity, but spontaneous activity was already high four years ago in comparison to other subjects. Moreover, spontaneous activity is present in the same muscular regions over years.


For the first time, long-term behavior of spontaneous activity assessed by DWI was evaluated. This work reveals only moderate variation of the frequency of spontaneous muscular activities for most subjects over a time-period from several hours to years. Hence, quantification of spontaneous activity can be potentially utilized as additional information in progressive and longitudinal studies. Moreover, spontaneous activity seems not to be correlated to the MR system, since different systems were utilized for image acquisition. Due to the small amount of subjects, larger cohort studies based on this work should be conducted to get detailed insight in the long-term behavior and influencing factors.


We thank Stemmer, A., Siemens Healthcare GmbH, for his valuable technical support on this project. This work was supported and funded by the German Research Foundation (DFG) under Grants SCHI 498/11‐1 and YA 28/16‐1 and in part by a grant (01GI0925) from the German Federal Ministry of Education and Research (BMBF) to the German Center for Diabetes Research (DZD e.V.).


[1]: Steidle G, Schick F. Addressing spontaneous signal voids in repetitive single-shot DWI of musculature: spatial and temporal patterns in the calves of healthy volunteers and consideration of unintended muscle activities as underlying mechanism. NMR Biomed 2015;28(7):801-10.

[2]: Schwartz M, Steidle G, Martirosian P, Ramos-Murguialday A, Preißl H, Stemmer A, Yang B, Schick F. Spontaneous mechanical and electrical activities of human calf musculature at rest assessed by repetitive single-shot diffusion-weighted MRI and simultaneous surface electromyography. Magn Reson Med 2018 May;79(5):2784-2794. doi: 10.1002/mrm.26921.

[3]: Schwartz M, Martirosian P, Steidle G, Erb M, Stemmer A, Yang B, Schick F. Volumetric assessment of spontaneous mechanical activities by simultaneous multi-slice MRI techniques with correlation to muscle fiber orientation. NMR Biomed 2018 Nov;31(11):e3959. doi: 10.1002/nbm.3959.

[4]: Gilliam C, Küstner T, Blu T. 3D Motion Flow Estimation using Local All-Pass Filters. Proc. IEEE Int. Symp. Biomed. Imag. (ISBI) 2016, April 2016, Prague, Czech Republic.

[5]: Küstner T, Neumann V, Schwartz M, Würslin C, Martirosian P, Gatidis S, Schwenzer NF, Schick F, Yang B, Schmidt H. An MR Motion Correction toolbox for registration and evaluation. Proceedings of the Annual Meeting ISMRM 2016, May 2016, Singapore.

[6]: Schwartz M, Steidle G, Martirosian P, Yang B, Schick F. Graph-based segmentation of signal voids in time series of diffusion-weighted images of musculature in the human lower leg. Proceedings of the Annual Meeting ISMRM 2016, May 2016, Singapore.


Table 1: Group composition of the three studies. Time between measurements ranges from 4 hours to 5 years.

Figure 1: Evaluation of spontaneous activities from DWI measurements on the same day. A: Number of SMAM-affected DWI in 500 repetitions for all three subjects. B: ECMs of all three measurements and all subjects. Note: The same muscular region is active during the day within the same subjects, e.g., the whole musculus soleus for Subject #2 and lateral edge of musculus soleus for Subject #1. (Note: the number of SMAMs in 500 DWI repetitions is color-coded: transparent/blue: no or small activity; red: high activity)

Figure 2: Evaluation of spontaneous activities from DWI during several days (21-175). A: Number of SMAM-affected DWI in 500 repetitions for all subjects (dashed: special group with exercise program between date of measurement; color: different subjects). B: Exemplary ECMs of three subjects. Note: Activity in Subject #3 is slightly reduced after exercise program; however, activity is still very high. (Note: the number of SMAMs in 500 DWI repetitions is color-coded: transparent/blue: no or small activity; red: high activity)

Figure 3: Evaluation of spontaneous activities from DWI measurements over several years. A: Number of SMAM-affected DWI in 500 repetitions. B: ECMs of all four subjects of the first and last measurement. Only Subject #2 shows a distinct increase in activity, however, spontaneous activity was already high compared to other subjects in the first measurement. Spontaneous activity is present in the same muscular regions over several years. (Note: the number of SMAMs in 500 DWI repetitions is color-coded: transparent/blue: no or small activity; red: high activity)

Proc. Intl. Soc. Mag. Reson. Med. 27 (2019)