Helical Multidetector Row Quantitative Computed Tomography (QCT) Precision

      Rationale and Objectives

      The impact of varying image acquisition parameters on the precision of measurements using quantitative computed tomography is currently based on studies performed before the advent of helical image acquisition and multidetector-row scanners. The aim of this study was to evaluate helical multidetector-row quantitative computed tomography to determine the factors contributing to the overall precision of measurements on quantitative computed tomography conducted using current vintage computed tomographic (CT) scanners.

      Materials and Methods

      The effects of CT protocol parameters (x-ray tube voltage and current, pitch, gantry rotation speed, detector configuration, table height, and reconstruction algorithm) and short-term scanner variation were examined on two commercially available quantitative CT (QCT) systems (ie, a combination of reference phantoms and analysis software) using seven multidetector-row CT scanners (available from a single vendor) operated in helical mode. Combined with simulated patient repositioning using three ex vivo spine specimens, precision (coefficient of variation) estimates were made on the basis of three scenarios: “best case,” “routine case,” and “worst case.”


      The overall best-case QCT precision was 1.4%, provided that no changes were permitted to the bone mineral density (BMD) scan protocol. Routine-case examination (with a BMD reference phantom in place) that permitted some variation in the x-ray tube current and table speed produced a precision of 1.8%. Without any constraints on the clinical QCT examinations, the worst-case precision was estimated at 3.6%.


      Although small in appearance, these errors are for single time points and may increase substantially when monitoring changes through QCT measurements over several time points. This calls for increased caution and attention to detail whenever using helical multidetector-row quantitative computed tomography for the assessment of BMD change.

      Key Words

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        • Genant H.K.
        Current assessment of osteoporosis: proceedings of an international symposium convened during ECR'95 in Vienna, Austria.
        Eur J Radiol. 1995; 20: 163-164
        • Raggi P.
        • Bellasi A.
        • Ferramosca E.
        • et al.
        Pulse wave velocity is inversely related to vertebral bone density in hemodialysis patients.
        Hypertension. 2007; 49: 1278-1284
        • Bousson V.
        • Le Bras A.
        • Roqueplan F.
        • et al.
        Volumetric quantitative computed tomography of the proximal femur: relationships linking geometric and densitometric variables to bone strength.
        Osteoporos Int. 2006; 17: 855-864
        • Mylona M.
        • Leotsinides M.
        • Alexandrides T.
        • et al.
        Comparison of DXA, QCT and trabecular structure in beta-thalassaemia.
        Eur J Haematol. 2005; 74: 430-437
        • Rehman Q.
        • Lang T.
        • Modin G.
        • et al.
        Quantitative computed tomography of the lumbar spine, not dual x-ray absorptiometry, is an independent predictor of prevalent vertebral fractures in postmenopausal women with osteopenia receiving long-term glucocorticoid and hormone-replacement therapy.
        Arthrit Rheum. 2002; 46: 1292-1297
        • Guglielmi G.
        • van Kuijk C.
        • Li J.
        • et al.
        Influence of anthropometric parameters and bone size on bone mineral density using volumetric quantitative computed tomography and dual x-ray absorptiometry at the hip.
        Acta Radiol. 2006; 47: 574-580
        • McCullough C.H.
        • Ulzheimer S.
        • Halliburton S.S.
        • et al.
        Coronary artery calcium: a multi-institutional, multimanufacturer international standard for quantification at cardiac CT.
        Radiology. 2007; 243: 527-538
        • Hong C.
        • Pilgram T.K.
        • Zhu F.
        • et al.
        Improving mass measurement of coronary artery calcification using threshold correction and thin collimation in multi-detector row computed tomography: in vitro experiment.
        Acad Radiol. 2003; 10: 969-977
        • Parr D.G.
        • Stoel B.C.
        • Stolk J.
        • et al.
        Influence of calibration on densitometric studies of emphysema progression using computed tomography.
        Am J Respir Crit Care Med. 2004; 170: 883-890
        • Buckley J.M.
        • Loo K.
        • Motherway J.
        Comparison of quantitative computed tomography-based measures in predicting vertebral compressive strength.
        Bone. 2007; 40: 767-774
        • Keaveny T.M.
        • Donley D.W.
        • Hoffmann P.F.
        • et al.
        Effects of teriparatide and alendronate on vertebral strength as assessed by finite element modeling of QCT scans in women with osteoporosis.
        J Bone Miner Res. 2007; 22: 149-157
        • Lian K.-C.
        • Lang T.F.
        • Keyak J.H.
        • et al.
        Differences in hip quantitative computed tomography (QCT) measurements of bone mineral density and bone strength between glucocorticoid-treated and glucocorticoid-naive postmenopausal women.
        Osteoporos Int. 2005; 16: 642-650
        • Crawford R.P.
        • Cann C.E.
        • Keaveny T.M.
        • et al.
        Finite element models predict in vitro vertebral body compressive strength better than quantitative computed tomography.
        Bone. 2003; 33: 744-750
        • Cann C.E.
        Quantitative CT applications: comparison of current scanners.
        Radiology. 1987; 162: 257-261
        • Ebbesen E.N.
        • Thomsen J.S.
        • Beck-Nielsen H.
        • et al.
        Lumbar vertebral body compressive strength evaluated by dual-energy x-ray absorptiometry, quantitative computed tomography, and ashing.
        Bone. 1999; 25: 713-724
        • Kaneko T.S.
        • Pejcic M.R.
        • Tehranzadeh J.
        • et al.
        Relationships between material properties and CT scan data of cortical bone with and without metastatic lesions.
        Med Eng Phys. 2003; 25: 445-454
        • Wigderowitz C.A.
        • Paterson C.R.
        • Dashti H.
        • et al.
        Prediction of bone strength from cancellous structure of the distal radius: can we improve on DXA?.
        Osteoporos Int. 2000; 11: 840-846
        • Snyder S.M.
        • Schneider E.
        Estimation of mechanical properties of cortical bone by computed tomography.
        J Orthop Res. 1991; 9: 422-431
        • Gampp S.
        • Jergas M.
        • Lang P.
        • et al.
        Quantitative CT assessment of the lumbar spine and radius in patients with osteoporosis.
        AJR Am J Roentgenol. 1996; 167: 133-140
        • Dougherty G.
        Quantitative CT in the measurement of bone quantity and bone quality for assessing osteoporosis.
        Med Eng Phys. 1996; 18: 557-568
      1. Brassow F. Correlations between breaking load and CT absorption values of vertebral bodies. Eur J Radiol 198; 22:99–101.

        • Genant H.K.
        Quantitative computed tomography: update 1987.
        Calcif Tissue Int. 1987; 41: 179-186
      2. Image Analysis.
        Image Analysis, Columbia, KY2003
      3. Mindways Software.
        Mindways Software, Austin, TX2005
        • Gluer C.C.
        • Blake G.
        Accurate assessment of precision errors: how to measure the reproducibility of bone densitometry techniques.
        Osteoporos Int. 1995; 5: 262-270
        • Bevington P.R.
        • Robinson D.K.
        Data reduction and error analysis for physical sciences.
        in: 3rd ed. McGraw-Hill, New York2002: 48
        • Kachigan S.
        Statistical analysis: an interdisciplinary introduction to univariate & multivariate methods.
        Radius, New York1986
        • Genant H.K.
        • Cann C.E.
        • Ettinger B.
        • et al.
        Quantitative computed tomography for spinal mineral assessment: current status.
        J Compt Assist Tomogr. 1985; 9: 602-604
        • Chafetz N.
        • Genant H.K.
        Computed tomography of the lumbar spine.
        Orthop Clin North Am. 1983; 14: 147-169
        • Hawkinson J.
        • Timins J.
        • Angelo D.
        • et al.
        Technical white paper: bone densitometry.
        J Am Coll Radiol. 2007; 4: 320-327
        • Cann C.E.
        • Genant H.K.
        Precise measurement of vertebral mineral content using computed tomography.
        J Comput Assist Tomogr. 1980; 4: 493-500
        • Goodwin P.N.
        Methodologies for the measurement of bone density and their precision and accuracy.
        Semin Nucl Med. 1987; 17: 293-304
        • Jergas M.
        • Genant H.K.
        Current methods and recent advances in the diagnosis of osteoporosis.
        Arthrit Rheum. 1993; 36: 1649-1662
        • Lenchik L.
        • Shi R.
        • Register T.C.
        • et al.
        Measurement of trabecular bone mineral density in the thoracic spine using cardiac gated quantitative computed tomography.
        J Comput Assist Tomogr. 2004; 28: 134-139
        • Wong M.
        • Papa A.
        • Lang T.
        • et al.
        Validation of thoracic quantitative computed tomography as a method to measure bone mineral density.
        Calcif Tissue Int. 2005; 76: 7-10
        • Hirbe A.
        Skeletal complications of breast and prostate cancer therapies.
        in: Favus M.J. Primer on the metabolic bone diseases and disorders of mineral metabolism. American Society for Bone, Washington, DC2006: 390-395
        • Link T.M.
        • Koppers B.B.
        • Licht T.
        • et al.
        In vitro and in vivo spiral CT to determine bone mineral density: initial experience in patients at risk for osteoporosis.
        Radiology. 2004; 231: 805-811