, Francois Lintz2, Cesar de Cesar Netto3, Alexej Barg4, Arne Burssens5 and Scott Ellis6
(1)
Department for Foot and Ankle Surgery, Hospital Rummelsberg, Schwarzenbruck, Germany
(2)
Foot and Ankle Surgery Centre, Clinique de l’Union, Toulouse, France
(3)
Department of Orthopedics and Rehab, University of Iowa, Iowa City, IA, USA
(4)
University Orthopedic Center, University of Utah, Salt Lake City, UT, USA
(5)
Department of Orthopedics and Trauma, University Hospital of Ghent, Ghent, OVL, Belgium
(6)
Department of Orthopedic Surgery, Hospital for Special Surgery, New York, NY, USA
Keywords
WBCTCone beamCTRadiographs
Introduction
Cone beam is a recent technology, published in 1998 by Mozzo et al. [1]. It first was used in the dental and cranial arena. It took 15 years for the technology to gradually replace panoramic radiographs in the clinical setting and completely in preoperative planning. In orthopedics, the use of cone beam CT (CBCT) was first published in 2011 by Zbijewski et al. [2], and the first mention of weight-bearing was in a 2013 paper by Tuominen et al. [3].
A cone beam is a rotating XR, where the center of rotation is the investigated object, the photon source is at one end of the diameter axis, and the target (a digital silicon detector panel) at the other. The target is continuously projected with the photons which have traversed the object, and the result is an intermingled array of lines and shades called a sinogram (Fig. 19.1), which has to be interpreted using mathematical transforms (the Fournier, which reconstructs multiple simple sinus functions from a single complex one) and the Radon, which reconstructs a set of 3D coordinates.
Fig. 19.1
Sinogram
The result is a 3D cylindrical volume or field of view (FOV), which varies in diameter between 10 cm and 40 cm (Fig. 19.2). This is divided into smaller cubes or voxels: the 3D equivalent of 2D pixels. The side of each voxel is usually around 0.3 mm (slab thickness). The resolution depends essentially on the density of receptors on the target panel but also on software and memory capabilities. A typical FOV contains several hundred million voxels. Each voxel has four dimensions including a set of three coordinates (x, y, z) and a value for the radiodensity, given as the Hounsfield unit (HU). For example, the radiodensity of air is −1000 HU.
Fig. 19.2
Typical field of view
Acquisition time is typically under a minute. In terms of radiation exposure, 3,9 a CBCT scan with a small, single foot FOV is around 2 Micro Sieverts (mSV) and a large FOV bilateral foot scan around 6 mSV. As a comparison, US daily background exposure is around 8 mSV, 1 mSV for an extremity conventional XR, 2 mSV for a chest XR, and 25 mSV–100 mSV (or typically 70 mSV for an ankle scan) for an extremity CT. In terms of size, a typical machine will weigh around 250 kg and fit in a 1 m Å~1 m footprint (Fig. 19.3).
Fig. 19.3
Typical WBCT machine footprint
How It Works
It is a real 3D technology, which reconstructs 3D models from the information contained in stacked up 2D transverse slabs of the anatomy, much like a conventional CT scan. In the case of cone beam CT, however, a fan beam (instead of a linear one) is projected through the anatomy. The result is called a sinogram. This is the continuous projection of the anatomy on the target (a standard flat panel detector) which faces the X-ray source on the other side of the patient’s foot and ankle. To decipher this image back to a 3D volume, mathematical algorithms based on the Radon and the Fourier transforms are necessary. Fourier tells us how to distinguish multiple signals piled up together. Radon tells us how to calculate or back-project the coordinates of each pixels and therefore reconstruct the whole volume, slice after slice. However, in cone beam CT, the X-ray source only performs a single revolution around the anatomy, as compared to a conventional CT which spirals around (Fig. 19.4).
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