Abstract
We hypothesized that that the summation or axial slab average intensity projection (AIP) techniques can substitute for the primary reconstruction (PR) from a raw projection data for abdominal applications. To compare with PR datasets (5-mm thick, 20% overlap) in 150 abdominal studies, corresponding summation and AIP datasets were calculated from 2-mm thick images (50% overlap). The root-mean-square error between PR and summation images was significantly greater than that between PR and AIP images (9.55 [median] vs. 7.12, p < 0.0001, Wilcoxon signed-ranks test). Four radiologists independently compared 2,000 test images (PR [as control], summation, or AIP) and their corresponding PR images to prove that the identicalness of summation or AIP images to PR images was not 1% less than the assessed identicalness of PR images to themselves (Wald-type test for clustered matched-pair data in a non-inferiority design). For each reader, both summation and AIP images were not inferior to PR images in terms of being rated identical to PR (p < 0.05). Although summation and AIP techniques produce images that differ from PR images, these differences are not easily perceived by radiologists. Thus, the summation or AIP techniques can substitute for PR for the primary interpretation of abdominal CT.
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References
Rubin GD: Data explosion: the challenge of multidetector-row CT. Eur J Radiol 36:74–80, 2000
Rubin GD: 3-D imaging with MDCT. Eur J Radiol 45(Suppl 1):S37–S41, 2003
Tamm EP, Thompson S, Venable SL, McEnery K: Impact of multislice CT on PACS resources. J Digit Imaging 15 Suppl 1:96–101, 2002
Lee KH, Lee HJ, Kim JH, Kang HS, Lee KW, Hong H, Chin HJ, Ha KS: Managing the CT data explosion: initial experiences of archiving volumetric datasets in a mini-PACS. J Digit Imaging 18:188–195, 2005
McNitt-Gray MF: AAPM/RSNA Physics tutorial for residents: topics in CT. Radiation dose in CT. Radiographics 22:1541–1553, 2002
Dalrymple NC, Prasad SR, Freckleton MW, Chintapalli KN: Informatics in radiology (infoRAD): introduction to the language of three-dimensional imaging with multidetector CT. Radiographics 25:1409–1428, 2005
Ba-Ssalamah A, Prokop M, Uffmann M, Pokieser P, Teleky B, Lechner G: Dedicated multidetector CT of the stomach: spectrum of diseases. Radiographics 23:625–644, 2003
Prokop M: Spiral and multislice computed tomography of the body, Stuttgart, Germany: Georg Tieme Verlag, 2003
Siegel E: SCAR University syllabus at the 2004 annual meeting, Great Falls, VA: Society for Computer Applications in Radiology, 2004
Lee KH, Kim YH, Hahn S, Lee KW, Kim TJ, Kang S-B, Shin JH: CT diagnosis of acute appendicitis: advantages of reviewing thin-section datasets using sliding slab average intensity projection technique. Invest Radiol 41:579–585, 2006
Napel S, Rubin GD, Jeffrey RB, Jr.: STS-MIP: a new reconstruction technique for CT of the chest. J Comput Assist Tomogr 17:832–838, 1993
van Ooijen PM, Ho KY, Dorgelo J, Oudkerk M: Coronary artery imaging with multidetector CT: visualization issues. Radiographics 23:e16, 2003
Prokop M: Multislice CT: technical principles and future trends. Eur Radiol 13(Suppl 5):M3–M13, 2003
Jeong DK, Lee KH, Kim BH, Kim KJ, Kim YH, Bajpai V, Shin YG: On-the-fly generation of multiplanar reformation images independent of CT scanner type. J Digit Imaging (in press), 2007 DOI 10.1007/s10278-007-9032-9
Wolberg G: Digital Image Warping. Los Alamitos, CA: IEEE Computer Society Press, 1990
Venema HW, Phoa SS, Mirck PG, Hulsmans FJ, Majoie CB, Verbeeten B, Jr.: Petrosal bone: coronal reconstructions from axial spiral CT data obtained with 0.5-mm collimation can replace direct coronal sequential CT scans. Radiology 213:375–382, 1999
Slone RM, Foos DH, Whiting BR, Muka E, Rubin DA, Pilgram TK, Kohm KS, Young SS, Ho P, Hendrickson DD: Assessment of visually lossless irreversible image compression: comparison of three methods by using an image-comparison workstation. Radiology 215:543–553, 2000
Gur D, Rubin DA, Kart BH, Peterson AM, Fuhrman CR, Rockette HE, King JL: Forced choice and ordinal discrete rating assessment of image quality: a comparison. J Digit Imaging 10:103–107, 1997
Larocque D: Statistical modeling and analysis for complex data problem. Berlin Heidelberg New York: Springer, 2005
Durkalski VL, Palesch YY, Lipsitz SR, Rust PF: Analysis of clustered matched-pair data for a non-inferiority study design. Stat Med 22:279–290, 2003
Cody DD: AAPM/RSNA physics tutorial for residents: topics in CT. Image processing in CT. Radiographics 22:1255–1268, 2002
Jeong YJ, Lee KS, Yoon YC, Kim TS, Chung MJ, Kim S: Evaluation of small pulmonary arteries by 16-slice multidetector computed tomography: optimum slab thickness in condensing transaxial images converted into maximum intensity projection images. J Comput Assist Tomogr 28:195–203, 2004
Slone RM, Muka E, Pilgram TK: Irreversible JPEG compression of digital chest radiographs for primary interpretation: assessment of visually lossless threshold. Radiology 228:425–429, 2003
Acknowledgment
This work was supported by the Korea Research Foundation Grant funded by the Korean Government (MOEHRD) (KRF-2006-311-D00168). We thank the radiologists who participated as readers and Sang Hyun Kim, R.T. for his assistance during image dataset preparation.
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Lee, K.H., Hong, H., Hahn, S. et al. Summation or Axial Slab Average Intensity Projection of Abdominal Thin-section CT Datasets: Can They Substitute for the Primary Reconstruction from Raw Projection Data?. J Digit Imaging 21, 422–432 (2008). https://doi.org/10.1007/s10278-007-9067-y
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DOI: https://doi.org/10.1007/s10278-007-9067-y