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      Three-material decomposition with dual-layer spectral CT compared to MRI for the detection of bone marrow edema in patients with acute vertebral fractures

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          To assess whether bone marrow edema in patients with acute vertebral fractures can be accurately diagnosed based on three-material decomposition with dual-layer spectral CT (DLCT).

          Materials and methods

          Acute ( n = 41) and chronic ( n = 18) osteoporotic thoracolumbar vertebral fractures as diagnosed by MRI (hyperintense signal in STIR sequences) in 27 subjects (72 ± 11 years; 17 women) were assessed with DLCT. Spectral data were decomposed into hydroxyapatite, edema-equivalent, and fat-equivalent density maps using an in-house-developed algorithm. Two radiologists, blinded to clinical and MR findings, assessed DLCT and conventional CT independently, using a Likert scale (1 = no edema; 2 = likely no edema; 3 = likely edema; 4 = edema). For DLCT and conventional CT, accuracy, sensitivity, and specificity for identifying acute fractures (Likert scale, 3 and 4) were analyzed separately using MRI as standard of reference.


          For the identification of acute fractures, conventional CT showed a sensitivity of 0.73–0.76 and specificity of 0.78–0.83, whereas the sensitivity (0.93–0.95) and specificity (0.89) of decomposed DLCT images were substantially higher. Accuracy increased from 0.76 for conventional CT to 0.92–0.93 using DLCT. Interreader agreement for fracture assessment was high in conventional CT (weighted κ [95% confidence interval]; 0.81 [0.70; 0.92]) and DLCT (0.96 [0.92; 1.00]).


          Material decomposition of DLCT data substantially improved accuracy for the diagnosis of acute vertebral fractures, with a high interreader agreement. This may spare patients additional examinations and facilitate the diagnosis of vertebral fractures.

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          Most cited references 21

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          Dual- and Multi-Energy CT: Principles, Technical Approaches, and Clinical Applications.

          In x-ray computed tomography (CT), materials having different elemental compositions can be represented by identical pixel values on a CT image (ie, CT numbers), depending on the mass density of the material. Thus, the differentiation and classification of different tissue types and contrast agents can be extremely challenging. In dual-energy CT, an additional attenuation measurement is obtained with a second x-ray spectrum (ie, a second "energy"), allowing the differentiation of multiple materials. Alternatively, this allows quantification of the mass density of two or three materials in a mixture with known elemental composition. Recent advances in the use of energy-resolving, photon-counting detectors for CT imaging suggest the ability to acquire data in multiple energy bins, which is expected to further improve the signal-to-noise ratio for material-specific imaging. In this review, the underlying motivation and physical principles of dual- or multi-energy CT are reviewed and each of the current technical approaches is described. In addition, current and evolving clinical applications are introduced.
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            Dual-energy CT-based monochromatic imaging.

            We summarize how virtual monochromatic images are synthesized from dual-energy CT using image-domain and projection-domain methods. The quality of virtual monochromatic images is compared with that of polychromatic single-energy images acquired at different tube potentials and the same radiation dose. Clinical applications of dual-energy CT-based virtual monochromatic imaging are reviewed, including beam-hardening correction, contrast and noise optimization, metal artifact reduction, and material differentiation. Virtual monochromatic images synthesized from dual-energy CT data have the potential to reduce beam-hardening artifacts and to provide quantitative measurements. If there is no desire to obtain material-specific information or to correct for metal or beam-hardening artifacts from the dual-energy data, however, it is better to perform a conventional single-energy scan at the optimal tube potential.
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              Incident vertebral fractures and mortality in older women: a prospective study.

              Older persons who have prevalent vertebral fractures have an increased risk of mortality. It is not known whether incident vertebral fractures are also associated with an increased risk of mortality. To determine whether older women with incident vertebral fractures have an increased risk of mortality, we conducted a prospective cohort study of 7233 community-dwelling older women aged 65 years or older who were enrolled in the Study of Osteoporotic Fractures. We measured incident vertebral fractures by radiographic morphometry of paired lateral spine X-rays taken an average of 3.7 years apart. We also collected information on baseline prevalent vertebral fractures; calcaneal bone density; anthropometric measures; and demographic, medical history, and lifestyle variables. Overall mortality was assessed and confirmed by receipt of death certificates. Over an average of 3.7 years, 389 (5.4%) women developed at least one incident vertebral fracture. During an additional 8 years of follow-up, 1617 (22%) women died. Women with at least one new fracture had an age-adjusted 32% increased risk of mortality (RH=1.32; 95% CI=1.10-1.58, P=0.003) compared to those without incident vertebral fractures. After adjustment for weight loss, physical frailty markers, and nine other predictors of mortality, there was no longer an independent association between incident vertebral fractures and mortality (RH=1.06; 95% CI=0.88 1.28). Older women with incident vertebral fractures have an increased risk of mortality that may be explained by weight loss and physical frailty.

                Author and article information

                Skeletal Radiol
                Skeletal Radiol
                Skeletal Radiology
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                25 May 2018
                25 May 2018
                : 47
                : 11
                : 1533-1540
                [1 ]ISNI 0000000123222966, GRID grid.6936.a, Department of Radiology, Klinikum rechts der Isar, , Technical University of Munich, ; Ismaninger Str. 22, 81675 Munich, Germany
                [2 ]ISNI 0000000123222966, GRID grid.6936.a, Department of Neuroradiology, Klinikum rechts der Isar, , Technical University of Munich, ; Munich, Germany
                [3 ]ISNI 0000000123222966, GRID grid.6936.a, Physics Department & Munich School of BioEngineering, , Technical University of Munich, ; Munich, Germany
                © The Author(s) 2018

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                Funded by: FundRef, Bundesministerium für Bildung und Forschung;
                Award ID: 13GW0072C
                Funded by: FundRef, Deutsche Forschungsgemeinschaft;
                Award ID: GRK 2274
                Scientific Article
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                © ISS 2018


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