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Is it possible to kill the radiation risk issue in computed tomography?

Published:March 09, 2020DOI:https://doi.org/10.1016/j.ejmp.2020.02.017

      Highlights

      • It is hoped that CT imaging industry will create an agenda such that 100 mSv+ doses will not be seen anymore.
      • Making X-rays more monochromatic and tailoring to individual patient’s task will be needed.
      • Tube voltage modulation, filter thickness modulation and adaptive bow-tie filters will contribute significantly.
      • Photon counting detector technology will play a big role.
      • Deep learning will most likely replace iterative reconstruction techniques.
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      References

        • Rehani M.M.
        What makes and keeps radiation risks associated with CT a hot topic?.
        AJR Am J Roentgenol. 2015; 204: W234-W235https://doi.org/10.2214/AJR.14.12860
        • McCollough C.H.
        Computed tomography technology-and dose-in the 21st century.
        Health Phys. 2019; 116: 157-162https://doi.org/10.1097/HP.0000000000000997
        • Rehani M.M.
        • Szczykutowicz T.P.
        • Zaidi H.
        CT is still not a low-dose imaging modality.
        Med Phys. 2019; https://doi.org/10.1002/mp.14000
        • Rehani M.M.
        • Yang K.
        • Melick E.R.
        • Heil J.
        • Šalát D.
        • Sensakovic W.F.
        • et al.
        Patients undergoing recurrent CT scans: assessing the magnitude.
        Eur Radiol. 2019; https://doi.org/10.1007/s00330-019-06523-y
        • Brambilla M.
        • Vassileva J.
        • Kuchcinska A.
        • Rehani M.M.
        Multinational data on cumulative radiation exposure of patients from recurrent radiological procedures: call for action.
        Eur Radiol. 2019; https://doi.org/10.1007/s00330-019-06528-7
        • Ruehm W.
        • Harisson R.M.
        High CT doses return to the agenda.
        Radiat Environ Biophys. 2020; 59: 3-7https://doi.org/10.1007/s00411-019-00827-9
        • Rehani M.M.
        • Melick E.R.
        • Alvi R.M.
        • Khera R.D.
        • Batool-Anwar S.
        • Neilan T.G.
        • et al.
        Patients undergoing recurrent CT exams: assessment of patients with non-malignant diseases, reasons for imaging and imaging appropriateness.
        Eur Radiol. 2019; https://doi.org/10.1007/s00330-019-06551-8
        • Remedios D.
        Cumulative radiation dose from multiple CT examinations: stronger justification, fewer repeats, or dose reduction technology needed?.
        Eur Radiol. 2020; https://doi.org/10.1007/s00330-019-06624-8
        • Lell M.M.
        • Kachelriess M.
        Recent and upcoming technological developments in computed tomography: high speed, low dose, deep learning, multienergy.
        Invest Radiol. 2020; 55: 8-19https://doi.org/10.1097/RLI.0000000000000601
        • Leyendecker P.
        • Faucher V.
        • Labani A.
        • Noblet V.
        • Lefebvre F.
        • Magotteaux P.
        • et al.
        Prospective evaluation of ultra-low-dose contrast-enhanced 100-kV abdominal computed tomography with tin filter: effect on radiation dose reduction and image quality with a third-generation dual-source CT system.
        Eur Radiol. 2019; 29: 2107-2116
        • Taguchi K.
        • Iwanczyk J.S.
        Vision 20/20: single photon counting x-ray detectors in medical imaging.
        Med Phys. 2013; 40100901
        • Klein L.
        • Dorn S.
        • Amato C.
        • Heinze S.
        • Uhrig M.
        • Schlemmer H.-P.
        • Kachelriess M.
        • Sawall S.
        Effects of detector sampling on noise reduction in a clinical photon counting whole-body CT.
        Invest Radiol. 2020; 55: 111-119https://doi.org/10.1097/RLI.0000000000000616
        • Wang G.
        • Ye J.C.
        • Mueller K.
        • Fessler J.A.
        Image reconstruction is a new frontier of machine learning.
        IEEE Trans Med Imaging. 2018; 37: 1289-1296
        • Akagi M.
        • Nakamura Y.
        • Higaki T.
        • Narita K.
        • Honda Y.
        • Zhou J.
        • et al.
        Deep learning reconstruction improves image quality of abdominal ultra-high-resolution CT.
        Eur Radiol. 2019; 29: 6163-6171https://doi.org/10.1007/s00330-019-06170-3