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DOI: 10.1148/radiol.2421052066
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(Radiology 2007;242:109-119.)
© RSNA, 2007


Experimental Studies

Multi–Detector Row CT Attenuation Measurements: Assessment of Intra- and Interscanner Variability with an Anthropomorphic Body CT Phantom1

Bernard A. Birnbaum, MD, Nicole Hindman, MD2, Julie Lee, MD3 and James S. Babb, PhD

1 From the Department of Radiology, New York University Medical Center, 560 First Ave, IRM 232, New York, NY 10016. Received December 19, 2005; revision requested February 9, 2006; revision received April 6; final version accepted May 8. Address correspondence to B.A.B. (e-mail: bernard.birnbaum{at}nyumc.org).

Purpose: To determine the dependence of absolute computed tomographic (CT) attenuation values on multi–detector row CT scanner type, convolution kernel, and tube current by using an anthropomorphic phantom.

Materials and Methods: A customized phantom was designed with tissue-equivalent materials to simulate contrast material–enhanced liver, spleen, pancreas, aorta, kidney, 0- and 50-HU cylindric renal cysts, muscle, and fat. The phantom was scanned with five multi–detector row CT scanners (LightSpeed QXi, GE Healthcare, Milwaukee, Wis; MX8000, Philips Medical Systems, Best, the Netherlands; and Volume Zoom, Sensation 16 and Sensation 64, Siemens Medical Solutions, Forchheim, Germany) on five separate occasions with 120 kVp, low and high tube current settings, 3.00–3.75-mm section thickness, 50% overlap, and standard and high-spatial-resolution kernels. Standardized regions of interest (ROIs) were used to obtain 3510 attenuation measurements. Attenuation dependence on scanner, kernel, and tube current was evaluated by using F tests derived with mixed-model regression. Within the mixed-model framework, the Tukey honestly significant difference procedure and a Bonferroni multiple comparison correction were used to assess differences among imaging regimens and tube current settings, respectively, in terms of tissue attenuation and ROI standard deviation.

Results: Tube current had no significant effect (P > .4) on observed tissue attenuation. Significant (P < .0001) differences were observed between imaging regimens with respect to mean attenuation for each tissue type. Convolution kernel modification had an inconsistent effect on tissue attenuation, depending on the scanner. All multi–detector row CT scanners displayed intrascanner variability in tissue attenuation (minimum range: 8.4 HU for fat tissue with the Sensation 16; maximum range: 63.4 HU for liver tissue with the Sensation 64). The scanners behaved differently at the lower range of the CT number scale, where 0-HU cyst attenuation ranged from –15.7 to 23.9 HU and one vendor's equipment showed significantly lower mean attenuation values.

Conclusion: CT attenuation values vary significantly between different manufacturers' multi–detector row CT scanners, among different generations of multi–detector row CT scanning equipment, and with individual combinations of scanner and convolution kernel.

Supplemental material: http://radiology.rsnajnls.org/cgi/content/full/242/1/109/DC1

© RSNA, 2007




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