I TUOI DATI
I TUOI ORDINI
N. prodotti: 0
Totale ordine: € 0,00
I TUOI ABBONAMENTI
I TUOI ARTICOLI
THE QUARTERLY JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
Rivista di Medicina Nucleare e Imaging Molecolare
A Journal on Nuclear Medicine and Molecular Imaging
Affiliated to the and to the International Research Group of Immunoscintigraphy
Indexed/Abstracted in: Current Contents/Clinical Medicine, EMBASE, PubMed/MEDLINE, Science Citation Index (SciSearch), Scopus
Impact Factor 2,413
The Quarterly Journal of Nuclear Medicine and Molecular Imaging 2016 Marzo;60(1):40-7
Preclinical validation of automated dual-energy X-ray absorptiometry and computed tomography-based body composition measurements
Joke DEVRIESE 1, Laurence BEELS 2, Christophe VAN DE WIELE 2, Alex MAES 2, Olivier GHEYSENS 2, Hans POTTEL 1 ✉
1 Department of Public Health and Primary Care, Kulak, KU Leuven campus Kortrijk, Kortrijk, Belgium; 2 Department of Nuclear Medicine, AZ Groeninge Hospital, Kortrijk, Belgium
BACKGROUNDː The aim of this study was to determine and validate a set of Hounsfield unit (HU) ranges to segment computed tomography (CT) images into tissue types and to test the validity of dual-energy X-ray absorptiometry (DXA) tissue segmentation on pure, unmixed porcine tissues.
METHODSː This preclinical prospective study was approved by the local ethical committee. Different quantities of porcine bone tissue (BT), lean tissue (LT) and adipose tissue (AT) were scanned using DXA and CT. Tissue type segmentation in DXA was performed via the standard clinical protocol and in CT through different sets of HU ranges. Percent coefficients of variation (%CV) were used to assess precision while % differences of observed masses were tested against zero using the Wilcoxon signed-rank Test.
RESULTSː Total mass DXA measurements differ little but significantly (P=0.016) from true mass, while total mass CT measurements based on literature values show non-significant (P=0.69) differences of 1.7% and 2.0%. BT mass estimates with DXA differed more from true mass (median -78.2 to -75.8%) than other tissue types (median -11.3 to -8.1%). Tissue mass estimates with CT and literature HU ranges showed small differences from true mass for every tissue type (median -10.4 to 8.8%).
CONCLUSIONː The most suited method for automated tissue segmentation is CT and can become a valuable tool in quantitative nuclear medicine.