TITLE:
Spectral Hounsfield Units - A New Radiological Concept
AUTHORS:
Michael Anthony Hurrell FRANZCR DIC; Department of Radiology, Christchurch School of
Medicine and Health Sciences, University of Otago, Christchurch.
Michael James Clark BSc; Department of Physics and Astronomy, University of Canterbury,
Christchurch.
Anthony Philip Howard Butler FRANZCR PhD; Department of Radiology, Christchurch School of
Medicine and Health Sciences, University of Otago, Christchurch; Department of Electrical and
Computer Engineering, University of Canterbury, Christchurch; European Organisation for Nuclear
Research (CERN), Geneva, Switzerland.
Nicholas James Cook PhD; Department of Bioengineering and Medical Physics, Christchurch
Hospital, Canterbury District Health Board, Christchurch.
Michael Campbell, PhD; Medipix Collaboration, CERN, Geneva, Switzerland.
Georgy A Chelkov; Joint Institute for Nuclear Research, Dubna, Moscow Region, Russia.
Abstract
With the advent of new photon counting chips that have energy resolution capabilities, spectral
(multi-energy) CT is now on the clinical horizon. It is therefore important that radiologists
appreciate how attenuation variation with kilovoltage will affect CT density measurements. While
radiologists learn about linear attenuation curves during radiology training, they do not usually have
any need for a detailed understanding of this in their current imaging practice. However spectral CT
requires a paradigm shift in how radiologists think about CT density. Because radiologists are
already familiar with Hounsfield units (HU), it is proposed that a modified HU be used that includes
the centre-point of the energy band used to obtain the image, as a conceptual bridge between
conventional CT and spectral CT. One possible annotation would be HU(median keV).
Introduction
Since its advent as a clinical tool in the late 1970s computed tomography (CT) has seen successive
improvements in resolution and speed, with a recent technological leap occurring with the
development of multi-slice helical CT in the last decade. The most recent change has been the
introduction of dual energy CT, while the future is likely to bring full spectral (multi-energy) CT
scanners.
In the 1990s a highly sensitive, high resolution photon detector chip was developed for research
experiments at CERN (European Organization for Nuclear Research), the international particle
physics facility in Geneva. A subsequent photon counting chip designed for medical applications
(Medipix) was developed at CERN and has now reached its third version1. Although only 14mm
square in size, this chip has remarkable properties: it can quantify x-rays more accurately than
previous electronic detector systems, measuring individual photon energies with greater sensitivity,
at kilohertz sampling rates2, and at very high resolution (each detector pixel is 0.055 mm square)
compared to current CT scanners3.
In 2006 a collaboration between CERN and the University of Canterbury designed and built the
MARS (Medipix All Resolution System) CT scanner using the Medipix2 chip. This prototype small
animal scanner uses the variation in linear attenuation coefficients across the x-ray energy spectrum
to characterise different materials of radiological importance (Fig. 1). The use of statistical methods
to sort materials within MARS images has been demonstrated previously (Fig. 2)4, highlighting the
value added to medical images by the energy information.
Now that spectral CT images are a practical reality, the issue of region of interest (ROI)
measurement reproducibility and reliability needs to be addressed. With conventional CT the
radiologist measures attenuation in Hounsfield units (HUs). While it is assumed that this
measurement is reproducible, the attenuation measurement is affected by the incident x-ray
spectrum. Just as linear attenuation coefficients vary across the energy spectrum, HUs would also
be expected to behave in a similar fashion. The purpose of this study was to verify that this
behaviour is seen with spectroscopic photon counting scanners and to suggest an appropriate unit of
measurement to denote this effect. In addition, technical difficulties with quantitative measurements
of spectral data need to be identified in order to direct future work.
Method
MARS CT images were obtained of water, a concentrated solution of calcium chloride with a
calcium concentration approximating that of bone, and diluted iodinated contrast (Omnipaque® 300
mg I/ml 1:6 dilution with water. The MARS scanner was configured with a Medipix2 photon
counting chip with a gallium-arsenide sensor layer. The x-ray tube voltage was set to 75 kVp, and
the Medipix chip energy bins were assigned between 14.45, 18.00, 21.50, 25.00, 28.60, 32.00,
35.60, 39.20 keV, and the maximum photon energy of 75 keV.
The images were processed using a flat field and interpolated to remove dead pixels using
MATLAB® version 2007b5. The cone beam reconstructions were performed with Octopus version
8.26.
Images were converted into Hounsfield Unit images using calibration points of air (-1000 HU) and
water (0 HU). Regions of interest were measured from the images of the iodinated contrast and the
CaCl2 solutions and compared to known calculated values derived from mass attenuation
coefficients7 using weighted addition8.
Results
The experimental setup is demonstrated by the MARS CT slice in Fig. 3. The calculated Hounsfield
units are shown in Table 1. The graphs comparing calculated and measured HUs for iodinated
contrast and calcium chloride solutions are shown in Figs. 4 and 5.
The graphs demonstrate an appropriate spectral response for the HUs, with the measured values
mirroring the calculated values. For the two energy bins between 32 and 39.2 keV, the iodine HU
curve is at its steepest, corresponding to the 33 keV K-edge of iodine. The calcium curve shows the
expected rise in HU below 39 keV.
Discussion
These graphs broadly confirm the expected variation in HU over the x-ray spectrum below 75 keV.
However, the portions of the HU curves below 25 keV are disproportionately reduced. We believe
this to be due to the energy response of the detector.
The energy response of photon counting detector is complex and depends on the sensor layer, the
manufacturing process, and charge sharing between pixels.. Like all x-ray detectors, the efficiency
of the sensor layer bonded onto the Medipix chip varies with energy. However, being a photon
counting pixel detector, Medipix suffers from charge sharing and other artefacts associated with the
charge collection process. Complex detector assemblies such as Medipix also have fluorescence
photons from tin (29.1 keV K-edge) and silver (25.5 keV K-edge) used in the bump bonds that
attach the sensor layer to the CMOS chip below.
In pixelated photon counting detectors, charge sharing results in photons of a particular energy
being miscounted in adjacent pixels at lower energy levels. For Medipix2 this has been well
described and modelled. While there are methods for deconvolving the charge sharing effect,
fluorescence photons, and sensor efficiency, these methods tend to introduce noise9. Importantly,
the new Medipix3 chip corrects for charge sharing within the detector electronics by a method
known as “charge summing” for individual events10. Given that “charge summing” in Medipix3 is
low noise and that the MARS-CT scanner is designed to house Medipix3 detectors when they
become available, future work will focus on integrating Medipix3 into our system rather than on
correcting for this problem by deconvolution.
As charge sharing tends to incorrectly assign high energy photons to lower energy bins, the effect is
most pronounced at lower energies. The effect on HU is difficult to predict because the calculation
of HU is determined by the attenuation of the two reference materials, air and water, both of which
are affected by charge sharing.
Thus, our plotted HU at high energies agree well with known linear attenuation values. For
example, the K-edge of iodine is clearly visible and the decreasing HU of calcium with increasing
keV are both clearly seen. However for low energies below 20keV, the measured HU diverge from
the calculated HU due to charge sharing effects. This misrepresentation of photon energies is borne
out by measurements of an incident x-ray spectrum using Medipix2 that have been compared to
predicted values (Fig. 6).
In the CT images at different energies, calcium varied in its density from 3063 HU to 5190 HU. It is
proposed that HU measurements should include the mean energy they were obtained at; in this
example using calcium, the densities should more accurately be referred to as 3063 HU (57 keV)
and 5190 HU (27 keV) respectively.
Future work will incorporate image processing to maximise contrast differences between different
materials across the range of energies, or alternatively transform data to specifically identify
different physical materials using techniques such as principal components analysis11 12 13.
Conclusion
Spectral or multi-energy CT is a novel technique that has its origins in dual energy CT and has
become feasible with new photon counting chips such as the Medipix detector. By demonstrating
that HU varies with energy we have shown that for spectral CT HUs it is important to specify the
energy at which the HUs are calculated.
Mass Attenuation curves of several radiologically relevant elements
Mass Attenuation Coefficients (cm 2/g) μ/ρ
10000
Barium
Water
Iodine
1000
Calcium
100
10
1
0.1
0
20
40
60
Energy (keV)
Fig. 1. Attenuation curves of several radiologically relevant elements7.
80
100
Fig. 2. Transverse images of a mouse abdomen at low keV and high keV, and the resulting principle
components analysis image identifying separately the iodine contrast in gut (yellow) and calcium in
the vertebra (blue-green). Note how calcium is less dense at higher keV. (From Butler PH et al.
2008, with permission)
Fig. 3. Full spectrum MARS CT slice of vials containing iodinated contrast, water, CaCl 2 (from
largest to smallest diameter vial), secured with plastic wrap.
5000
Theoretical Iodine Solution
Experimental Iodine Solution
Hounsfield Scale (HU)
4000
3000
2000
1000
0
10
20
30
40
50
60
70
80
Energy (keV)
Fig. 4. Comparison of calculated and actual relative HU curves for iodinated contrast solution.
12000
Theoretical CaCl2 Solution
Experimental CaCl2 Solution
Hounsfield Scale (HU)
10000
8000
6000
4000
2000
0
10
20
30
40
50
60
70
80
Energy (keV)
Fig. 5. Comparison of calculated and actual relative HU curves for calcium chloride solution.
Fig. 6. The effect of charge sharing on detector response using Medipix2. The incident x-ray beam
was produced by scatter from a perspex object. The shift of the measured spectrum to the left
compared to a Monte Carlo simulation model is due to charge sharing. This result is in keeping with
previously published data from other groups. (Courtesy of Hansjorg Zeller, University of
Canterbury).
Energy
Bin (keV)
CaCl2
Iodinated
contrast
14.518.0
18.021.5
21.525.0
25.028.0
28.032.0
32.035.6
35.639.2
39.2-75.0
4169.8
4167.4
4916.6
5190.2
4815.2
4262.8
3787.0
3063.0
1484.1
1485.9
1775.7
2023.4
2262.6
3244.4
4577.3
3719.43
Table 1. HUs for the calcium chloride and iodinated contrast solutions by energy bin.
References