- AutorIn
- Nicolas Linder
- Alexander Schaudinn
- Nikita Garnov
- Matthias Blüher
- Arne Dietrich
- Tatjana Schütz
- Stefanie Lehmann
- Ulf Retschlag
- Thomas Karlas
- Thomas Kahn
- Harald Busse
- Titel
- Age and gender specific estimation of visceral adipose tissue amounts from radiological images in morbidly obese patients
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:15-qucosa-205619
- Quellenangabe
- Scientific Reports 6:22261 doi: 10.1038/srep22261
- Erstveröffentlichung
- 2016
- Abstract (EN)
- Image-based quantifications of visceral adipose tissue (VAT) volumes from segmented VAT areas are increasingly considered for risk assessment in obese patients. The goal of this study was to determine the power of partial VAT areas to predict total VAT volume in morbidly obese patients (BMI > 40 kg/m2) as a function of gender, age and anatomical landmarks. 130 morbidly obese patients (mean BMI 46.5 kg/m2; 94 females) underwent IRB-approved MRI. Total VAT volumes were predicted from segmented VAT areas (of single or five adjacent slices) at common axial landmark levels and compared with the measured ones (VVAT-T, about 40 slices between diaphragm and pelvic floor). Standard deviations σ1 and σ5 of the respective VAT volume differences served as measures of agreement. Mean VVAT-T was 4.9 L for females and 8.1 L for males. Best predictions were found at intervertebral spaces L3-L4 for females (σ5 = 688 ml, σ1 = 832 ml) and L1-L2 for males (σ5 = 846 ml, σ1 = 992 ml), irrespective of age. In conclusion, VAT volumes in morbidly obese patients can be reliably predicted by multiplying the segmented VAT area at a gender-specific lumbar reference level with a fixed scaling factor and effective slice thickness.
- Andere Ausgabe
- Link zur Originalpublikation in der Zeitschrift Scientifc reports
Link: http://dx.doi.org/10.1038/srep22261 - Freie Schlagwörter (DE)
- Viszeralfett, Adipositas, Magnetresonanztomographie
- Freie Schlagwörter (EN)
- visceral adipose tissue (VAT), obesity, magnetic resonance imaging
- Klassifikation (DDC)
- 610
- Herausgeber (Institution)
- Universität Leipzig
- Verlag
- Nature Publ., London
- URN Qucosa
- urn:nbn:de:bsz:15-qucosa-205619
- Veröffentlichungsdatum Qucosa
- 23.06.2016
- Dokumenttyp
- Artikel
- Sprache des Dokumentes
- Englisch