Prog Med Phys.  2021 Mar;32(1):1-17. 10.14316/pmp.2021.32.1.1.

Basic Physical Principles and Clinical Applications of Computed Tomography

Affiliations
  • 1Development Headquarter, FutureChem Co., Ltd, Korean Institute of Radiological & Medical Sciences (KIRAMS), Seoul, Korea
  • 2Division of Applied RI, Korean Institute of Radiological & Medical Sciences (KIRAMS), Seoul, Korea

Abstract

The evolution of X-ray computed tomography (CT) has been based on the discovery of X-rays, the inception of the Radon transform, and the development of X-ray digital data acquisition systems and computer technology. Unlike conventional X-ray imaging (general radiography), CT reconstructs cross-sectional anatomical images of the internal structures according to X-ray attenuation coefficients (approximate tissue density) for almost every region in the body. This article reviews the essential physical principles and technical aspects of the CT scanner, including several notable evolutions in CT technology that resulted in the emergence of helical, multidetector, cone beam, portable, dual-energy, and phase-contrast CT, in integrated imaging modalities, such as positronemission-tomography一CT and single-photon-emission-computed-tomography一CT, and in clinical applications, including image acquisition parameters, CT angiography, image adjustment, versatile image visualizations, volumetric/surface rendering on a computer workstation, radiation treatment planning, and target localization in radiotherapy. The understanding of CT characteristics will provide more effective and accurate patient care in the fields of diagnostics and radiotherapy, and can lead to the improvement of image quality and the optimization of exposure doses.

Keyword

Computed tomography; Physical principle; Clinical application; Technical aspects; Radiation dose

Figure

  • Fig. 1 First clinical computed tomography (CT) image (80×80 image matrix obtained from the Atkinson Morley Hospital, London, UK) of the brain acquired in 1971 (a) [9,10], brain CT image acquired recently (512×512 image matrix, Siemens SOMATOM Plus 4 [Siemens medical systems, Erlangen, Germany]) with a more advanced CT scanner (b).

  • Fig. 2 X-ray beam attenuations passing through of an object (left) and intensity of an X-ray beam passing through an object with multiple different linear attenuation coefficients (μ1, μ2, μ3, μ4) (right).

  • Fig. 3 Computed tomography image reconstruction methods. (a) Simple back projection algorithm method, (b) filtered back projection algorithm method, and (c) Fourier transform algorithm method.

  • Fig. 4 Hounsfield scale of computed tomography (CT) numbers for various tissues.

  • Fig. 5 Structure and mechanism of (a) dual-energy computed tomography (CT) system (adopt two X-ray tubes and corresponding detector arrays) and (b) detector-based spectral CT system (single X-ray tube and two layers within detector arrays).

  • Fig. 6 Domestic commercial computed tomography (CT) scanners. (a) NanoFocusRay’s gantry of the rotational microct system (NanoFocusRay Co., Ltd., Seoul, Korea; 2008). (b) Vatech’s conical beam dental CT (PaX-13D Green Premium) (Vatech Co., Ltd., Seoul, Korea; 2012). (c) Diagnostic CT Scanner (NExCT 7) (Samsung Electronics Co. Ltd., Suwon, Korea; 2015).

  • Fig. 7 (a) Anatomical planes in human, multiplanar reconstruction computed tomography images, such as (b) coronal and (c) sagittal converted from (d) axial.

  • Fig. 8 Computed tomography (CT) image windowing (a), chest CT scan displayed according to the adjustment of bone, mediastinal, and lung windows (b). HU, Hounsfield unit; WW, window width; WL, window level.

  • Fig. 9 Computed tomography images shown in Fig. 8 above indicate how the adjustment of the window width changes the contrast of the image, narrow window width (a) and wide window width (b).

  • Fig. 10 . (a) American Association of Physicists in Medicine CT performance phantom model 76-410. (b) American College of Radiology CT 464 phantom designed to examine a broad range of image quality parameters.


Reference

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