Purpose. Methods and Materials

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1 A systematic approach for the objective evaluation of low-contrast performance in MDCT: combination of a fullreference image fidelity metric and a software phantom Poster No.: C-1496 Congress: ECR 2012 Type: Scientific Paper Authors: C. von Falck 1, T. Rodt 1, S. Waldeck 2, B. Meyer 1, F. Wacker 1, H.- O. Shin 1 ; 1 Hannover/DE, 2 Koblenz/DE Keywords: Computer applications, Research, CT, Observer performance DOI: /ecr2012/C-1496 Any information contained in this pdf file is automatically generated from digital material submitted to EPOS by third parties in the form of scientific presentations. References to any names, marks, products, or services of third parties or hypertext links to thirdparty sites or information are provided solely as a convenience to you and do not in any way constitute or imply ECR's endorsement, sponsorship or recommendation of the third party, information, product or service. ECR is not responsible for the content of these pages and does not make any representations regarding the content or accuracy of material in this file. As per copyright regulations, any unauthorised use of the material or parts thereof as well as commercial reproduction or multiple distribution by any traditional or electronically based reproduction/publication method ist strictly prohibited. You agree to defend, indemnify, and hold ECR harmless from and against any and all claims, damages, costs, and expenses, including attorneys' fees, arising from or related to your use of these pages. Please note: Links to movies, ppt slideshows and any other multimedia files are not available in the pdf version of presentations. Page 1 of 8

2 Purpose To assess the feasibility of an objective approach for the evaluation of low-contrast detectability in MDCT by combining a virtual phantom containing simulated lesions with an image quality metric. Methods and Materials A low-contrast phantom for MDCT (Fig. 1) was scanned on a 64-slice MDCT scanner at 4 different dose levels (25, 50, 100, 200mAs; no dose modulation, tube voltage=120kvp, rotation time=0.8s). The datasets were reconstructed with a slice-thickness of 0.625mm and a reconstruction increment of 0.5mm using the standard kernel. Virtual round hypodense low-contrast lesions (20HU object contrast) based on real CT data were inserted into the datasets using the medical image processing application framework MeVisLab 2.2. The sliding-thin-slab algorithm was then applied to the image data with an increasing slice-thickness from 1 to 15 slices using ImageJ For each dataset containing simulated lesions a lesion-free counterpart was reconstructed and postprocessed in the same manner. The low-contrast performance of all datasets was determined using a full-reference image quality metric (MS-SSIM*) by comparing a dataset containing the virtual lesion with its lesion-free counterpart. The results were validated against a reader-study. Images for this section: Page 2 of 8

3 Fig. 1: Photograph of the low-contrast phantom Page 3 of 8

4 Fig. 2: MeVisLab Network for lesion simulation Page 4 of 8

5 Results For all dose levels and lesion sizes there was no statistically significant difference between the slab thicknesses with optimal lesion detectability as determined by the image quality metric as compared to the ready study (p<0.05). The intraclass correlation coefficient was 0.72, 0.82, 0.90 and 0.84 for lesion diameters of 4mm, 5mm, 8mm and 10mm, respectively. The use of the sliding-thin-slab algorithm improves lesion detectability by a factor between 1.2 and 2.7 when compared with the original axial dataset. Images for this section: Fig. 3: This figure illustrates the dependency of the lesion detectability (given as the similarity index determined with the MS-SSIM* metric) on the slab thickness as created with the STS algorithm. It is clearly seen, that the optimal slice thickness is dependent on the size of the lesion and increases with increasing lesion diameter. Furthermore, it can be appreciated that the absolute detectability of the low-contrast lesions generally improves with increasing size and increasing radiation dose. Page 5 of 8

6 Conclusion The combination of a virtual phantom and a full-reference image quality metric enables the systematic and objective evaluation of low-contrast detectability in MDCT datasets and shows comparable performance to the judgment of human readers. References 1. von Falck C, Hartung A, Berndzen F, King B, Galanski M, Shin HO. Optimization of low-contrast detectability in thin-collimated modern multidetector CT using an interactive sliding-thin-slab averaging algorithm. Invest Radiol. 2008;43(4): Shin HO, Falck CV, Galanski M. Low-contrast detectability in volume rendering: a phantom study on multidetector-row spiral CT data. Eur Radiol. 2004;14(2): von Falck C, Galanski M, Shin HO. Informatics in radiology: sliding-thin-slab averaging for improved depiction of low-contrast lesions with radiation dose savings at thin-section CT. Radiographics. 2010;30(2): International Electrotechnical Commission (IEC). Medical electrical equipment Part 2-44: particular requirements for the safety of X-ray equipment for computed tomography; ImageJ image processing and analysis in Java. January 3, Available at: 6. MeVisLab - medical image processing and visualization. January 3, Available at: 7. Wang Z, Bovik AC, Sheikh HR, Simoncelli EP. Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process Apr;13(4): Rouse DM, Hemami, SS. Analyzing the role of visual structure in the recognition of natural image content with multi-scale SSIM. Proc. SPIE 2008;6806, MS SSIM Java - PlugIn for ImageJ. January 3, plugins/mssim-index.html 10. Portney L.G., Watkins M.P. Foundations of Clinical Research. Applications and Practice (1993) Appleton & Lange, Norwalk, Conneticut ISBN p Lundberg M, Grimby-Ekman A, Verbunt J, Simmonds MJ. Painrelated fear: a critical review of the related measures. Pain Res Treat. 2011;2011: Epub 2011 Nov Jaffe TA, Nelson RC, Johnson GA, et al. Optimization of multiplanar reformations from isotropic data sets acquired with 16-detector row helical CT scanner. Radiology. 2006;238: Page 6 of 8

7 13. von Falck C, Hollmann P, Rodt T, Waldeck S, Meyer B, Wacker F, Shin HO. Influence of multiplanar reformations on low-contrast performance in thin-collimated multidetector computed tomography. Invest Radiol. 2011;46(10): Dalrymple NC, Prasad SR, Freckleton MW, Chintapalli KN. Informatics in radiology (inforad): introduction to the language of three-dimensional imaging with multidetector CT. Radiographics Sep-Oct;25(5): Chao EH, Toth TL, Bromberg NB, et al. A statistical method of defining low contrast detectability. Radiology. 2000;217(suppl S): Prieto G, Guibelalde E, Chevalier M, Turrero A. Use of the cross-correlation component of the multiscale structural similarity metric (R* metric) for the evaluation of medical images. Med Phys Aug;38(8): Prieto G, Chevalier M, Guibelalde E. A CDMAM Image Phantom Software Improvement for Human Observer Assessment. In Proc. Digital Mammography / IWDM, 2008, pp ASTM, E , ASTM standard test method for measurement of computed tomography (CT) performance. 19. Burgess AE. Visual perception studies and observer models in medical imaging. Semin Nucl Med Nov;41(6): Lee H, Lee KH, Kim KJ, Park S, Seo J, Shin YG, Kim B. Advantage in image fidelity and additional computing time of JPEG2000 3D in comparison to JPEG2000 in compressing abdomen CT image datasets of different section thicknesses. Med Phys Aug;37(8): Kim KJ, Kim B, Mantiuk R, Richter T, Lee H, Kang HS, Seo J, Lee KH. A comparison of three image fidelity metrics of different computational principles for JPEG2000 compressed abdomen CT images. IEEE Trans Med Imaging Aug;29(8): Kim KJ, Lee KH, Kang HS, Kim SY, Kim YH, Kim B, Seo J, Mantiuk R. Objective index of image fidelity for JPEG2000 compressed body CT images. Med Phys Jul;36(7): Kim B, Lee KH, Kim KJ, Mantiuk R, Hahn S, Kim TJ, Kim YH. Prediction of perceptible artifacts in JPEG 2000-compressed chest CT images using mathematical and perceptual quality metrics. AJR Am J Roentgenol Feb;190(2): Kim B, Lee KH, Kim KJ, Mantiuk R, Bajpai V, Kim TJ, Kim YH, Yoon CJ, Hahn S. Prediction of perceptible artifacts in JPEG2000 compressed abdomen CT images using a perceptual image quality metric. Acad Radiol Mar;15(3): Personal Information Dr. Christian von Falck Department of Diagnostic and Interventional Radiology Page 7 of 8

8 Hannover Medical School Carl-Neuberg-Strasse Hannover phone: +49 (0) fax: +49 (0) Falck.Christian.von@mh-hannover.de Page 8 of 8