title: Comparison of QCT-derived and DXA-derived areal bone mineral density and T scores.
abstract: Two-dimensional areal bone mineral density (aBMD) of the proximal femur measured by three-dimensional quantitative computed tomography (QCT) in 91 elderly women was compared to dual-energy X-ray absorptiometry (DXA) aBMD results measured in the same patients. The measurements were highly correlated, though QCT aBMD values were marginally lower in absolute units. Transformation of the QCT aBMD values to T score values using National Health and Nutrition Examination Survey (NHANES) DXA-derived reference data improved agreement and clinical utility.
  
  
  BACKGROUND
  World Health Organization guidelines promulgate aBMD (g cm(-2)) measurement of the proximal femur for the diagnosis of bone fragility. In recent years, there has been increasing interest in QCT to facilitate understanding of three-dimensional bone structure and strength.
  
  
  OBJECTIVE
  To assist in comparison of QCT-derived data with DXA aBMD results, a technique for deriving aBMD from QCT measurements has been developed.
  
  
  METHODS
  To test the validity of the QCT method, 91 elderly females were scanned on both DXA and CT scanners. QCT-derived DXA equivalent aBMD (QCT(DXA) aBMD) was calculated using CTXA Hip software (Mindways Software Inc., Austin, TX, USA) and compared to DXA-derived aBMD results.
  
  
  RESULTS
  Test retest analysis indicated lower root mean square (RMS) errors for CTXA; F test between CTXA and DXA was significantly different at femoral neck (FN) and trochanter (TR) (p < 0.05). QCT underestimates DXA values by 0.02 +/- 0.05 g cm(-2) (total hip, TH), 0.01 +/- 0.04 g cm(-2) (FN), 0.03 +/- 0.07 g cm(-2) (inter-trochanter, IT), and 0.02 +/- 0.05 g cm(-2) (TR). The RMS errors (standard error of estimate) between QCT and DXA T scores for TH, FN, IT, and TR were 0.36, 0.40, 0.39, and 0.49, respectively.
  
  
  CONCLUSIONS
  This study shows that results from QCT aBMD appropriately adjusted can be evaluated against NHANES reference data to diagnose osteoporosis.
authors.affiliation: Medical Technology and Physics, Sir Charles Gairdner Hospital, Perth, Australia.
authors.forename: B C C
authors.initials: BC
authors.lastname: Khoo
authors.forename: K
authors.initials: K
authors.lastname: Brown
authors.forename: C
authors.initials: C
authors.lastname: Cann
authors.forename: K
authors.initials: K
authors.lastname: Zhu
authors.forename: S
authors.initials: S
authors.lastname: Henzell
authors.forename: V
authors.initials: V
authors.lastname: Low
authors.forename: S
authors.initials: S
authors.lastname: Gustafsson
authors.forename: R I
authors.initials: RI
authors.lastname: Price
authors.forename: R L
authors.initials: RL
authors.lastname: Prince
mesh_terms: D015502:Absorptiometry, Photon / Q000379:methods*; D000369:Aged, 80 and over; D015519:Bone Density / Q000502:physiology*; D005260:Female; D005269:Femur / Q000000981:diagnostic imaging* / Q000503:physiopathology; D005272:Femur Neck / Q000000981:diagnostic imaging / Q000503:physiopathology; D006801:Humans; D010024:Osteoporosis / Q000000981:diagnostic imaging* / Q000503:physiopathology; D015203:Reproducibility of Results; D014057:Tomography, X-Ray Computed / Q000379:methods*