Oliver Chaudry1,2, Andreas Friedberger3, Alexandra Grimm3, Michael Uder4, Armin Michael Nagel3,4, Wolfgang Kemmler3, Klaus Engelke5,3. 1. Department of Medicine 3, Friedrich-Alexander-Universität Erlangen-Nürnberg and University Hospital Erlangen, Ulmenweg 18, 91054, Erlangen, Germany. oliver.chaudry@imp.uni-erlangen.de. 2. Institute of Medical Physics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Henkestrasse 91, 91052, Erlangen, Germany. oliver.chaudry@imp.uni-erlangen.de. 3. Institute of Medical Physics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Henkestrasse 91, 91052, Erlangen, Germany. 4. Institute of Radiology, Friedrich-Alexander-Universität Erlangen-Nürnberg and University Hospital Erlangen, Maximiliansplatz 3, 91054, Erlangen, Germany. 5. Department of Medicine 3, Friedrich-Alexander-Universität Erlangen-Nürnberg and University Hospital Erlangen, Ulmenweg 18, 91054, Erlangen, Germany.
Abstract
OBJECTIVE: To develop a precise semi-automated segmentation of the fascia lata (FL) of the thigh to quantify IMAT volume in T1w MR images and fat fraction (FF) in Dixon MR images. MATERIALS AND METHODS: A multi-step segmentation approach was developed to identify fibrous structures of the FL and combining them into a closed 3D surface. 23 healthy young men with low and 50 elderly sarcopenic men with moderate levels of IMAT were measured by T1w and 6pt Dixon MRI at 3T. 20 datasets were used to determine reanalysis precision errors. IMAT volume was compared using the new FL segmentation versus an easier to segment but less accurate, tightly fitting envelope of the thigh muscle ensemble. RESULTS: The segmentation was successfully applied to all 73 datasets and took about 7 min per 28 slices. In particular, in elderly subjects, it includes a large amount of adipose tissue below the FL typically not accounted for in other segmentation approaches. Inter- and intra-operator RMS-CVs were 0.33% and 0.14%, respectively, for IMAT volume and 0.04% and 0.02%, respectively, for FFMT. DISCUSSION: The FL segmentation is an important step to quantify IMAT with high precision and may be useful to investigate effects of aging and treatment on changes of IMAT and FF. ClinicalTrials.gov identifier NCT2857660, August 5, 2016. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT2857660, August 5, 2016.
OBJECTIVE: To develop a precise semi-automated segmentation of the fascia lata (FL) of the thigh to quantify IMAT volume in T1w MR images and fat fraction (FF) in Dixon MR images. MATERIALS AND METHODS: A multi-step segmentation approach was developed to identify fibrous structures of the FL and combining them into a closed 3D surface. 23 healthy young men with low and 50 elderly sarcopenic men with moderate levels of IMAT were measured by T1w and 6pt Dixon MRI at 3T. 20 datasets were used to determine reanalysis precision errors. IMAT volume was compared using the new FL segmentation versus an easier to segment but less accurate, tightly fitting envelope of the thigh muscle ensemble. RESULTS: The segmentation was successfully applied to all 73 datasets and took about 7 min per 28 slices. In particular, in elderly subjects, it includes a large amount of adipose tissue below the FL typically not accounted for in other segmentation approaches. Inter- and intra-operator RMS-CVs were 0.33% and 0.14%, respectively, for IMAT volume and 0.04% and 0.02%, respectively, for FFMT. DISCUSSION: The FL segmentation is an important step to quantify IMAT with high precision and may be useful to investigate effects of aging and treatment on changes of IMAT and FF. ClinicalTrials.gov identifier NCT2857660, August 5, 2016. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT2857660, August 5, 2016.
Authors: Gustav J Strijkers; Ericky C A Araujo; Noura Azzabou; David Bendahan; Andrew Blamire; Jedrek Burakiewicz; Pierre G Carlier; Bruce Damon; Xeni Deligianni; Martijn Froeling; Arend Heerschap; Kieren G Hollingsworth; Melissa T Hooijmans; Dimitrios C Karampinos; George Loudos; Guillaume Madelin; Benjamin Marty; Armin M Nagel; Aart J Nederveen; Jules L Nelissen; Francesco Santini; Olivier Scheidegger; Fritz Schick; Christopher Sinclair; Ralph Sinkus; Paulo L de Sousa; Volker Straub; Glenn Walter; Hermien E Kan Journal: J Neuromuscul Dis Date: 2019
Authors: Mansour Ghasemikaram; Oliver Chaudry; Armin M Nagel; Michael Uder; Franz Jakob; Wolfgang Kemmler; Matthias Kohl; Klaus Engelke Journal: Geroscience Date: 2021-01-15 Impact factor: 7.713
Authors: Klaus Engelke; Mansour Ghasemikaram; Oliver Chaudry; Michael Uder; Armin M Nagel; Franz Jakob; Wolfgang Kemmler Journal: Aging Clin Exp Res Date: 2022-05-28 Impact factor: 4.481
Authors: Mansour Ghasemikaram; Klaus Engelke; Matthias Kohl; Simon von Stengel; Wolfgang Kemmler Journal: Nutrients Date: 2021-05-01 Impact factor: 5.717