Keywords
dual-energy computed tomography - crystal-induced arthropathies - metal artifact reduction
- bone marrow edema - iron
The concept of spectral imaging, or dual-energy computed tomography (DECT), is an
old one, described by Godfrey Hounsfield in one of the first descriptions of CT in
1973.[1] This technique had already been suggested as a tool to differentiate tissue materials
by using different X-ray spectra. The first applications of DECT to the musculoskeletal
system date back to the late 1970s and early 1980s.[2]
[3]
[4] However, due to technological limitations, its implementation on clinical scanners
was delayed until more recent years, particularly when dual-source CT was introduced
in 2006.[5]
[6]
[7]
[8]
In the first part of this review article, we explain how DECT works including the
different technical approaches currently available on the market, as well as radiation
dose considerations.
Dual-Energy CT: How Does It Work?
DECT is based on the principle that the attenuation of tissues (reflected by their
CT attenuation number in Hounsfield units [HUs]) depends on their density, but also
on their atomic number Z, as well as on the energy of the photon beam. To understand
how DECT works, we first review the basics of the interactions of the X-ray beam with
tissues. The attenuation of tissues in CT is mainly due to two types of interactions
between the X-ray beam and tissues: the photoelectric and the Compton effects. The
Compton effect strongly depends on the electron density (ρe) of the material, which is correlated with mass density, but in the small range of
photons' energies used in CT, the Compton effect does not depend on photon energy
([Fig. 1]). The Compton effect is the main determinant of soft tissue contrast. The photoelectric
effect, in contrast, strongly depends on the effective atomic number (Zeff) of the material as well as on the energy of the photons. Lighter atoms, such as
most atoms in soft tissues and water, do not present much of a photoelectric effect
in the range of energies used in clinical CT scans. Calcium and iodine, however, are
susceptible to the photoelectric effect at lower energy levels, which can be exploited
to differentiate those materials.
Fig. 1 Interactions of the X-ray beam with tissues. Photoelectric and Compton effects of
various materials (iodine, calcium, and water) on attenuation level (μ [cm2/g]), at different energy levels. In the range of photons' energies used in computed
tomography (grayed area), the photoelectric effect, contrary to the Compton effect,
strongly depends on the effective atomic number (Zeff) of the material as well as on the energy of the photons.
As seen in [Fig. 2], the attenuation coefficient of higher Z materials such as calcium or iodine is
higher for lower beam energy levels. This is due to the photoelectric effect. In [Fig. 2], when using a single-energy level, such as the effective X-ray beam energy obtained
at 120 kV, it is not possible to differentiate tissues containing calcium or iodine
based on their attenuation level (both show CT numbers of ∼ 1,000 HU). However, when
combining the information obtained by using two different energy levels of photon
spectra (i.e., at effective energies produced when applying 80 and 140 kV), this differentiation
can be made (iodine has a higher Zeff than calcium, so its CT number is higher at a lower beam energy). To show graphically
the influence of the Zeff on CT numbers, it is convenient to represent the CT numbers at high and low energies
as shown in [Fig. 3]. Because the photoelectric effect is highly dependent on Zeff, the higher the Zeff, the steeper the slope. The slope is a characteristic of the material, and the location
of the value of a given pixel along this slope depends on density. Using these properties
one can:
Fig. 2 Attenuation level (computed tomography number) of various components depending on
the X-ray beam energy. The attenuation of higher Z materials such as calcium or iodine
depends on beam energy levels, due to the photoelectric effect. This property can
be used to differentiate those materials by combining the information obtained with
two different energy levels of photons spectra.
Fig. 3 Influence of the effective atomic number Zeff on the attenuation (HU). The x-axis represents the HU value of a voxel at 140 kVp;
the y-axis represents the HU value at 80 kVp. Each component is characterized by its
slope, depending on Zeff. The location of the value of a given voxel along this slope depends on the density
of its components. The computed tomography (CT) number of water and soft tissues (which
have comparable Zeff values) is not energy dependent. Thus CT numbers of soft tissues will remain almost
constant when varying the X-ray beam energy (thin dashed line). The location on this
line will only depend on the density of the tissue (compare fat and soft tissue).
For components with higher Zeff, the photoelectric effect will come into play, and attenuation will be higher for
lower energy levels (the higher the Zeff, the steeper the slope).
-
Decompose attenuation coefficients into two basis-material components and generate
basis-material density images[9] ([Fig. 4])
-
Decompose the measured attenuation coefficients into Compton and photoelectric effects[10]
[11]
-
Measure the Zeff and ρe of each voxel[11]
[12] ([Fig. 5])
-
Synthesize virtual monochromatic images at the desired energy level[13]
[14]
[15] ([Fig. 6])
Fig. 4 A 35-year-old man referred by an orthopedic surgeon for acute pain and swelling in
his left foot. (a) Conventional polychromatic computed tomography (CT) image shows indeterminate soft
tissue masses around the first (arrowheads) and fifth (arrows) metatarsophalangeal
joints, as well as the base of the fifth metatarsal bone, with CT numbers ranging
from 150 to 200 HU and suggestive of gouty tophi. Basis-material (uric acid [b] versus calcium hydroxyapatite [c]) decomposition of dual-energy computed tomography data confirm the diagnosis of
acute gout, with monosodium urate deposits of variable densities (arrows and arrowheads)
visible on uric acid maps (b) and little calcium seen on the corresponding calcium
hydroxyapatite images (c).
Fig. 5 A 40-year-old woman with no medical or family history, presenting with painless progressive
swelling of both ankles. (a) Conventional computed tomography image of the right ankle shows diffuse nonspecific
involvement of the Achilles and peroneal tendons. (b) Dual-energy computed tomography data offer the opportunity to measure the effective
Z (Zeff) of each voxel, allowing in this case to differentiate the normal tendon containing
primarily water molecules (yellow histogram) from the abnormal tendon infiltrated
by fatty tissue/xanthomas (red histogram).
Fig. 6 A 27-year-old man with a history of tibial fracture treated with intramedullary nailing,
presenting with chronic pain in the medial compartment of his right knee. Sagittal-reformatted
virtual monoenergetic computed tomography arthrogram images at (a) 40 and (b) 140 keV (window level/width, 400/2000 HU, for both) reconstructed from dual-energy
computed tomography (DECT) data. Note the gradual disappearance of intra-articular
contrast material (25% iodine dilution, arrowheads), and the progressive reduction
of streak metal artifacts (arrows), with increasing X-ray beam energy (adapted from
Omoumi et al. article on DECT article Part 2 in this issue).[17]
To separate attenuation coefficients into two basis-material components and generate
basis-material density images, we must remember that the CT number of water is not
energy dependent. Thus CT numbers of soft tissues (with Zeff values comparable to that of water) remain almost constant when varying the X-ray
beam energy.
An example may illustrate the principle. A voxel contains a fraction fA of material A and fraction fB of material B. The goal is to assess fA and fB. To answer this, one must solve the simple set of two equations with two unknowns:
CTHigh = fA CT(A)High + fB CT(B)High
CTLow = fA CT(A)Low + fB CT(B)Low
CTHigh and CTLow are the CT numbers of the voxel measured, respectively, at high and low energies,
so CT(A)High is the CT number of material A at high energy, and so on.
To get the best material characterization, DECT should be performed in these conditions:
-
Use two monochromatic (only one X-ray energy) beams with very different energy levels
-
Acquire both data sets simultaneously
-
Get images with the same quantity of photons on the detectors
However, CT technology is based on the use of conventional X-ray tubes that produce
a spectrum of photons. The production of X-rays with this quite old technology remains
the state of the art, but the use of a spectrum instead of monochromatic photons is
associated with several limitations. The first one is beam hardening, which introduces
a variation of the effective X-ray energy that depends on the quantity and type of
material the beam will have to pass through. The second major limitation is the separation
of the effective energies because X-ray spectra will always contain a fraction of
low-energy photons. Another limitation of DECT resides in the need for heavy postprocessing,
which is being standardized but remains time consuming.[16]
[18]
Three main types of algorithms are currently in use to postprocess DECT data sets[16]: (1) Image optimization algorithms usually provide three sets of images: two sets
of monoenergetic images (typically at 80 or 100 keV and 140 keV), as well as an “optimum
contrast” image from nonlinear blending of the low-energy images (providing high contrast)
and high-energy images (providing low noise). (2) Differentiation algorithms allow
the subtraction of a certain material from the data set, or the differentiation between
two materials, through color coding, for example. (3) Quantification algorithms are
based on three-material decompositions and for example can provide color-coded images
of iodine content in postcontrast examinations.
The current spectral imaging or DECT techniques are based on the principles detailed
in [Table 1]. Each approach has advantages and drawbacks that must be considered carefully. To
date, no study has compared the diagnostic performance of these different techniques.
Table 1
Basic principles, advantages, and disadvantages of currently available spectral imaging
or dual-energy computed tomography techniques
|
Spectral imaging technique (manufacturer)
|
Main advantages
|
Main limitations
|
|
|
Sequential scans at low and high kilovolts (typically 80 and 140 kV)
(All CT scanners with particular filtering strategies including Toshiba)
|
- Possible optimization of X-ray spectra to increase effective energy difference
- Possible to get similar X-ray numbers at detector level
|
- Risk of patient motion between scans (projection data not paired)
|
|
|
Dual-source CT (two X-ray tubes): low and high kilovolts acquired simultaneously
(Siemens)
|
- Possible optimization of X-ray spectra to increase effective energy difference
- Possible to get similar X-ray numbers at detector level
- Radiation dose can be optimized through tube current modulation
|
- Projection data not paired (slight difference in acquisition time of the two data
sets)
- Space limitation inside the gantry (first-generation dual-source CT)
|
|
|
Rapid kilovolt switching (typically 80 and 140 kV)
(GE)
|
- Projection pairs possible by interpolation
|
- Impossible optimization of X-ray spectra to increase effective energy difference
- Complex generator control
- Tube current modulation not available
- Difficult to get similar X-ray numbers at detector level
|
|
|
One kilovolt with energy-discriminating detector (the top layer absorbs low-energy
X-rays, whereas the bottom layer absorbs high-energy X-rays)
(Philips)
|
- Perfectly paired projection data
|
- Imperfect energy discrimination
- Difficult to get similar X-ray numbers at detector level
|
|
|
One kilovolt with two filters in X-ray beam to achieve spectral separation (gold and
tin filters)
(Siemens)
|
- Projection pairs possible by interpolation
|
- Limited optimization of X-ray spectra to increase effective energy difference
- Difficult to get similar X-ray numbers at detector level
|
Abbreviation: CT, computed tomography.
Radiation Dose Considerations in DECT
The radiation exposure required for DECT depends on the technology used. As discussed
by Henzler et al, multiple studies have shown that dual-source DECT does not lead
to increased radiation dose compared with conventional single-energy multidetector
computed tomography. These data were mainly gathered from cardiac and chest applications.[19] This seems to also hold true for musculoskeletal applications. It has been shown
that detection of bone marrow lesions in the knee and the ankle with dual-source DECT,
using the virtual noncalcium technique, could be performed with a dose-neutral protocol
(compared with conventional CT), taking advantage of the small cross-sectional scan
area of the knee, compared with body applications.[20]
[21] For peripheral joints, a slight increase in radiation dose might not be a problem
because the effective dose to these small anatomical structures, away from any radiosensitive
organs, is negligible.[22]
With dual-source DECT, radiation dose reductions strategies include tube current modulation
and the use of tin filters with the high-energy spectrum (to get rid of lower energy
quanta and optimize the separation between the high- and low-energy spectra). The
increased contrast of the lower energy spectrum can also be used to compensate for
increased noise (keeping contrast-to-noise ratio levels constant).
For single-source DECT with rapid kilovolt switching, the radiation dose is usually
higher than conventional monoenergetic CT, with ratios up to three times more radiation.[23] When matched for image quality assessed by low-contrast detectability, the radiation
dose remains roughly 22% and 14% higher with single-source DECT with rapid kilovolt
switching compared with conventional monoenergetic CT (evaluated for head and body
examinations).[24] This is at least partly due to the nonavailability of tube current modulation with
the rapid kilovolt switching technique.
For both dual-source and rapid kilovolt switching techniques, further radiation dose
reduction is possible in various musculoskeletal conditions with the association of
iterative reconstruction techniques with newer generation scanners[16]
[25]
[26]
[27] (see the dose optimization articles by Omoumi et al in this issue).[28]
[29] For other techniques of DECT, there is no or only scarce literature addressing radiation
dose issues.
Conclusion
With its unique ability to differentiate basis materials by their atomic number, DECT
has opened new perspectives in imaging. Used appropriately, it should not lead to
an increase in radiation dose. Several image reconstruction algorithms have been developed
to improve image contrast (i.e., by generating monoenergetic images), to characterize
or subtract certain materials in the image, as well as to perform automatized volumetric
measurements.
