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1.  Characteristics, changes and influence of body composition during a 4486 km transcontinental ultramarathon: results from the Transeurope Footrace mobile whole body MRI-project 
BMC Medicine  2013;11:122.
Background
Almost nothing is known about the medical aspects of runners doing a transcontinental ultramarathon over several weeks. The results of differentiated measurements of changes in body composition during the Transeurope Footrace 2009 using a mobile whole body magnetic resonance (MR) imager are presented and the proposed influence of visceral and somatic adipose and lean tissue distribution on performance tested.
Methods
22 participants were randomly selected for the repeated MR measurements (intervals: 800 km) with a 1.5 Tesla MR scanner mounted on a mobile unit during the 64-stage 4,486 km ultramarathon. A standardized and validated MRI protocol was used: T1 weighted turbo spin echo sequence, echo time 12 ms, repetition time 490 ms, slice thickness 10 mm, slice distance 10 mm (breath holding examinations). For topographic tissue segmentation and mapping a modified fuzzy c-means algorithm was used. A semi-automatic post-processing of whole body MRI data sets allows reliable analysis of the following body tissue compartments: Total body volume (TV), total somatic (TSV) and total visceral volume (TVV), total adipose (TAT) and total lean tissue (TLT), somatic (SLT) and visceral lean tissue (VLT), somatic (SAT) and visceral adipose tissue (VAT) and somatic adipose soft tissue (SAST). Specific volume changes were tested on significance. Tests on difference and relationship regarding prerace and race performance and non-finishing were done using statistical software SPSS.
Results
Total, somatic and visceral volumes showed a significant decrease throughout the race. Adipose tissue showed a significant decrease compared to the start at all measurement times for TAT, SAST and VAT. Lean adipose tissues decreased until the end of the race, but not significantly. The mean relative volume changes of the different tissue compartments at the last measurement compared to the start were: TV −9.5% (SE 1.5%), TSV −9.4% (SE 1.5%), TVV −10.0% (SE 1.4%), TAT −41.3% (SE 2.3%), SAST −48.7% (SE 2.8%), VAT −64.5% (SE 4.6%), intraabdominal adipose tissue (IAAT) −67.3% (SE 4.3%), mediastinal adopose tissue (MAT) −41.5% (SE 7.1%), TLT −1.2% (SE 1.0%), SLT −1.4% (SE 1.1%). Before the start and during the early phase of the Transeurope Footrace 2009, the non-finisher group had a significantly higher percentage volume of TVV, TAT, SAST and VAT compared to the finisher group. VAT correlates significantly with prerace training volume and intensity one year before the race and with 50 km- and 24 hour-race records. Neither prerace body composition nor specific tissue compartment volume changes showed a significant relationship to performance in the last two thirds of the Transeurope Footrace 2009.
Conclusions
With this mobile MRI field study the complex changes in body composition during a multistage ultramarathon could be demonstrated in detail in a new and differentiated way. Participants lost more than half of their adipose tissue. Even lean tissue volume (mainly skeletal muscle tissue) decreased due to the unpreventable chronic negative energy balance during the race. VAT has the fastest and highest decrease compared to SAST and lean tissue compartments during the race. It seems to be the most sensitive morphometric parameter regarding the risk of non-finishing a transcontinental footrace and shows a direct relationship to prerace-performance. However, body volume or body mass and, therefore, fat volume has no correlation with total race performances of ultra-athletes finishing a 4,500 km multistage race.
doi:10.1186/1741-7015-11-122
PMCID: PMC3668188  PMID: 23657091
Magnetic resonance imaging; MRI; Body mass; Body volume; Body composition; Running; Marathon; Ultramarathon; Performance; Adipose tissue; Body fat; Lean tissue; Visceral; Somatic; Topography; Segmentation; Mapping
2.  The Transeurope Footrace Project: longitudinal data acquisition in a cluster randomized mobile MRI observational cohort study on 44 endurance runners at a 64-stage 4,486km transcontinental ultramarathon 
BMC Medicine  2012;10:78.
Background
The TransEurope FootRace 2009 (TEFR09) was one of the longest transcontinental ultramarathons with an extreme endurance physical load of running nearly 4,500 km in 64 days. The aim of this study was to assess the wide spectrum of adaptive responses in humans regarding the different tissues, organs and functional systems being exposed to such chronic physical endurance load with limited time for regeneration and resulting negative energy balance. A detailed description of the TEFR project and its implemented measuring methods in relation to the hypotheses are presented.
Methods
The most important research tool was a 1.5 Tesla magnetic resonance imaging (MRI) scanner mounted on a mobile unit following the ultra runners from stage to stage each day. Forty-four study volunteers (67% of the participants) were cluster randomized into two groups for MRI measurements (22 subjects each) according to the project protocol with its different research modules: musculoskeletal system, brain and pain perception, cardiovascular system, body composition, and oxidative stress and inflammation. Complementary to the diverse daily mobile MR-measurements on different topics (muscle and joint MRI, T2*-mapping of cartilage, MR-spectroscopy of muscles, functional MRI of the brain, cardiac and vascular cine MRI, whole body MRI) other methods were also used: ice-water pain test, psychometric questionnaires, bioelectrical impedance analysis (BIA), skinfold thickness and limb circumference measurements, daily urine samples, periodic blood samples and electrocardiograms (ECG).
Results
Thirty volunteers (68%) reached the finish line at North Cape. The mean total race speed was 8.35 km/hour. Finishers invested 552 hours in total. The completion rate for planned MRI investigations was more than 95%: 741 MR-examinations with 2,637 MRI sequences (more than 200,000 picture data), 5,720 urine samples, 244 blood samples, 205 ECG, 1,018 BIA, 539 anthropological measurements and 150 psychological questionnaires.
Conclusions
This study demonstrates the feasibility of conducting a trial based centrally on mobile MR-measurements which were performed during ten weeks while crossing an entire continent. This article is the reference for contemporary result reports on the different scientific topics of the TEFR project, which may reveal additional new knowledge on the physiological and pathological processes of the functional systems on the organ, cellular and sub-cellular level at the limits of stress and strain of the human body.
Please see related articles: http://www.biomedcentral.com/1741-7015/10/76 and http://www.biomedcentral.com/1741-7015/10/77
doi:10.1186/1741-7015-10-78
PMCID: PMC3409063  PMID: 22812450
3.  Automatic detection of the carotid artery boundary on cross-sectional MR image sequences using a circle model guided dynamic programming 
Background
Systematic aerobe training has positive effects on the compliance of dedicated arterial walls. The adaptations of the arterial structure and function are associated with the blood flow-induced changes of the wall shear stress which induced vascular remodelling via nitric oxide delivered from the endothelial cell. In order to assess functional changes of the common carotid artery over time in these processes, a precise measurement technique is necessary. Before this study, a reliable, precise, and quick method to perform this work is not present.
Methods
We propose a fully automated algorithm to analyze the cross-sectional area of the carotid artery in MR image sequences. It contains two phases: (1) position detection of the carotid artery, (2) accurate boundary identification of the carotid artery. In the first phase, we use intensity, area size and shape as features to discriminate the carotid artery from other tissues and vessels. In the second phase, the directional gradient, Hough transform, and circle model guided dynamic programming are used to identify the boundary accurately.
Results
We test the system stability using contrast degraded images (contrast resolutions range from 50% to 90%). The unsigned error ranges from 2.86% ± 2.24% to 3.03% ± 2.40%. The test of noise degraded images (SNRs range from 16 to 20 dB) shows the unsigned error ranging from 2.63% ± 2.06% to 3.12% ± 2.11%. The test of raw images has an unsigned error 2.56% ± 2.10% compared to the manual tracings.
Conclusions
We have proposed an automated system which is able to detect carotid artery cross sectional boundary in MRI sequences during heart cycles. The accuracy reaches 2.56% ± 2.10% compared to the manual tracings. The system is stable, reliable and results are reproducible.
doi:10.1186/1475-925X-10-26
PMCID: PMC3083378  PMID: 21477378

Results 1-3 (3)