A low-cost density reference phantom for computed tomography

Zachary H. Levinea

Photon Physics Group, National Institute for Standards and Technology, Gaithersburg,

Maryland 20899-8410

Mingdong Li

Institute for Physical Science and Technology, University of Maryland, College Park, Maryland 20742

Anthony P. Reeves

Department of Electrical and Computer Engineering, Cornell University, Ithaca, New York 14853

David F. Yankelevitz

Weill Medical College, Cornell University, New York, New York 10065

Joseph J. Chen and Eliot L. Siegel

Department of Radiology, University of Maryland Medical Center, Baltimore, Maryland 21201-1595

Adele Peskin

Mathematical and Computational Science Division, National Institute for Standards and Technology,

Boulder, Colorado 80305-3328

Diana N. Zeiger

Polymers Division, National Institute for Standards and Technology, Gaithersburg, Maryland 20899-8453

Received 28 August 2008; revised 17 October 2008; accepted for publication 24 November 2008;

published 7 January 2009

The authors characterized a commercially available foam composed of polyurethane and polyisocyanurate which is marketed for modeling parts in the aircraft, automotive, and related industries.

The authors found that the foam may be suitable for use as a density reference standard in the range

below −400 Hounsfield units. This range is coincident with the density of lung tissue. The foam

may be helpful in making the diagnosis of lung disease more systematic. © 2009 American Association of Physicists in Medicine. DOI: 10.1118/1.3049596

Key words: lung CT, lung computed tomography, foam phantom, radio density phantom

I. INTRODUCTION

The radio densities of tissues as reported by CT machines

show uncertainties which may have clinical significance for

the diagnosis of lung disease. A machine-to-machine variability of 5% has been reported1 and the effect of reconstruction algorithm was shown to have a variability of up to 9.4%

in the radio density of emphysema.2 One approach to reduce

the variability is to image reference materials in every scan.

There has been considerable effort to create materials

which match the radio density of human tissue, including

lung tissue, over several decades.3–5 Typically, a complex,

synthetic material is derived which is suitable for use in a

wide range of exposure conditions. While very suitable for a

range of purposes, such materials may be too scarce or costly

for widespread use in medical CT imaging. As CT scanners

become more widely deployed, they replace the traditional x

ray as a primary diagnostic tool in the workup of lung diseases as well as for continued monitoring. CT imaging has

been used to diagnose several diseases of the lungs including

cancer, tuberculosis, cystic fibrosis, pneumonia, mesothelioma, chronic obstructive pulmonary disease COPD, overdistension, asthma, and emphysema. In general, diseases

which involve air trapping or increases in lung density can

be quantified by this technique. Asthma and emphysema are

two examples of dysfunction in air trapping. For increases in

lung density, there are certain types of interstitial infections

and interstitial edema. We can use these types of calibration

devices to track progression or improvement. Many diseases

ranging from allergic reactions to drug reactions, inhalation

injury, and infection can cause changes in lung density, and it

would be possible to more accurately describe whether these

change over time.

In a series of papers aimed at making a density standard

for lung tissue, Kemerink et al.6–8 studied commercially

available polyethene foam with densities of 37–186 kg/m3

,

corresponding to a range of −965 to −825 HU, and found

that by using sample volumes on the order of 50 mm3

, it was

possible to obtain a density standard with a standard deviation of 3–6 HU depending on the machine Here, HU stands

for Hounsfield units.9 Their material overlaps the lower end

of the range of radio densities required for lung diseases. For

example, in the case of emphysema, −960 HU has been used

as a cutoff for diseased areas.10,11 However, in a study of

lung overdistension a range of values from −912 HU to just

over −300 HU was reported,12 whereas in a study of lung

nodules a median value of 38 HU was reported.13 Of course,

the reported radio density of lung tissue depends on the state

of inspiration; this effect can exceed 100 HU.14

In this technical note, we report similar results on a commercially available1 composite foam based on polyurethane,

which is commonly used for floatation devices and packing

materials, and polyisocyanate, which is commonly used for

286 Med. Phys. 36 „2..., February 2009 0094-2405/2009/36„2.../286/3/$25.00 © 2009 Am. Assoc. Phys. Med. 286
building insulation. The available density range is somewhat

different, namely, 66–656 kg/m3. Whereas the polyethene

used earlier had a density below that of the majority of lung

tissue,10 this will be much less of an issue with the higher

density foam studied in this work. The product is typically

used by manufacturers to model aircraft or automotive parts

and will be called “modeling foam” in this paper. We consider this material to be of “low cost” in the sense that it is

sold in individual sheets of 48960.75 in.3 1.22 m

2.44 m19 mmfor hundreds of U.S. dollars per sheet.

An individual sheet would provide enough material for hundreds of individual phantoms. In practice the costs of characterizing the materials would be greater than the cost of the

material itself.

II. MEASUREMENTS

The materials used were eight samples of the modeling

foam with densities stated by the manufacturer to be 4, 6, 8,

10, 12, 15, 18, and 20 lb/ft3

, which correspond to 66, 109,

124, 154, 181, 250, 285, and 303 kg/m3

. Foams with nominal densities of 30 and 40 lb/ft3 are also sold, which correspond to densities of 480 and 640 kg/m3

, respectively.We

had small portions 8819 mm3

of three of the samples

examined by micro-CT specifically using a SkyScan 1172.

The sample was reconstructed with cubic voxels 0.0124 mm

on a side. In this experiment, the x-ray tube voltage was 40

kV and the current was 0.25 mA. A typical slice from the

reconstructed image is shown in Fig. 1. The size of the

bubbles is larger in the less dense foams. The denser foams

have smaller bubbles, but even the least dense foam in this

study has bubbles comparable in size to medical CT pixels.

We measured the densities. Since the samples were rectilinear blocks roughly 20312719 mm3

, we obtained the

density from the weight, as measured on a scale, divided by

the volume, found as the product of the length, width, and

thickness as measured by a caliper. The radio density was

also obtained from a Siemens Sensation 64 CT scanner using

an x-ray tube voltage of 120 kV and a current of 84 mA. All

of the samples were scanned at the same time to ensure uniform exposure conditions. The helical CT scans were performed using a 0.75 mm slice thickness and a duration of

500 s. The data were reconstructed with the proprietary software SYNGO CT 2006A using the “abdomen-pelvis” protocol.

The radio density is shown in Fig. 2 as a function of the

measured density as well as the nominal density. The uncertainty in the radio density was obtained by considering 12

cubes of 131313 voxels each, chosen from the interiors

of each sample. Each voxel is 0.770.770.75 mm3

. The

spatial resolution is about 1 mm. For the mean, all the data

were averaged. For the standard deviation of the mean, the

standard deviation of the means of each of the 12 cubes was

chosen. Short-range correlations prevent the use of the standard formula that the standard deviation of the mean is the

standard deviation divided by the number of observation

points. We find that the standard formula underestimates the

fluctuations by an amount suggesting that cubes of 33

3 voxels are the smallest size to be considered statistically

independent.The best fit line to the radio density versus

measured density has a slope of 0.950.01HU/kg/m3



and an intercept of −10035HU, with the uncertainties

at 95% confidence intervals. The linear fit is excellent as it is

within all of the individual uncertainties of the data. A slope

just under unity is typical for a polymer, and the intercept is

TABLE I. The densities of the foam as designated by the manufacturer nominaland as measured.

Nominal density

lb/ft3



Nominal density

kg/m3

Measured density

kg/m3

4 64 66

6 96 109

8 128 124

10 160 154

12 192 181

15 240 250

18 288 285

20 320 303

FIG. 1. Micro-CT images of foam samples with nominal densities of 4, 12,

and 20 lb/ft3

, which correspond to 66, 181, and 303 kg/m3, acquired by

Micro Photonics, Inc. using a SkyScan 1172. The voxel size is 0.0124 mm

per side. The samples are separated by cellophane tape which is visible in

the image. The size of the bubbles is larger in the less dense foams.

FIG. 2. The radio density of eight foams as a function of the measured

density crossed error barsand the nominal density solid circles. The

indicated uncertainties are shown at three times the 95% confidence intervals considering total uncertainties for the density and statistical uncertainties for the radio density. The symbols are shown at an enlarged size to

make them a reasonable size.The total uncertainty in the density with 95%

confidence is 2 kg/m3

.

287 Levine et al.: Density reference for CT 287

Medical Physics, Vol. 36, No. 2, February 2009
consistent with the defined value1 of −1000 HU. For reference, we show the relation of the measured densities to the

nominal densities in Table I. Given our uncertainties, 5 HU

may be distinguished with 95% confidence using our sample

volume of 20 cm3 by using the data presented in Fig. 2.

Similar results were presented earlier by Kemerink et al. for

polyethene foams10,12 over an overlapping but lower density

range.

III. CONCLUSIONS

A commercially available polymer foam may be used as a

density reference standard in a density range which includes

the lung tissue. While the concept of using a polymer foam

for this purpose was studied earlier by Kemerink et al.,

10,12

here we have shown that a different material is also suitable,

used micro-CT to estimate the bubble sizes, shown that the

density range may be extended, and demonstrated a high

degree of linearity between density and radio density.

Although we studied rectilinear blocks of foam, because

the foam was designed to be machined to simulate industrial

parts, it could be machined into biomimetic shapes for use in

complex phantoms.

ACKNOWLEDGMENTS

The authors are pleased to acknowledge helpful discussions, support, and encouragement from Ramalingam Chellappa, Nancy Chen, Charles Clark, Steven Grantham, Karen

Kafadar, and Lisa Karam in performing this work. The authors thank Edward Hagley and Bruce Norman for technical

assistance. The authors thank Jon Flint for supplying the

samples. This work was supported by the NIST Grant No.

70NANB4H1120 M.L., NIH/NCI Grant No.

R33CA101110-4 A.P.R., NIH Grant No. R01-CA-078905

D.F.Y., and congressional appropriations. The micro-CT

work presented in this paper was performed under contract

by Micro Photonics, Inc.

a

Present address: 100 Bureau Dr., NIST, Gaithersburg, MD 20899-8410,

Tel.: 301-975-5453, Fax: 301-208-6937. Author to whom correspondence should be addressed. Electronic mail: zlevine@nist.gov

1

The product LAST-A-FOAM is manufactured by The General Plastics

Corporation. See http://www.generalplastics.com  products on a tab

FR-7100 Modeling Foam. Commercial products or services are not recommended or endorsed by the authors or their institutions. They may not

be the best available for the purpose.

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