The use of the modulation transfer function for comparison and image quality assessment of commercially available hybrid PET-CT scanners

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1 The use of the modulation transfer function for comparison and image quality assessment of commercially available hybrid PET-CT scanners Poster No.: C-2943 Congress: ECR 2010 Type: Topic: Scientific Exhibit Physics in Radiology Authors: A. Samartzis 1, I. Kalatzis 1, G. Fountos 1, D. Cavouras 1, I. Datseris 1, E. Kounadi 1, L. Papaspyrou 1, I. Kandarakis 1, G. Nikiforidis 2 ; 1 Athens/GR, 2 Patras/GR Keywords: DOI: PET/CT, Line Spread Function (LSF), Modulation Transfer Function (MTF) /ecr2010/C-2943 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 15

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3 Purpose Aim of our study was to implement a new method for the determination of the Modulation Transfer Function (MTF) in order to evaluate the performance of hybrid PET - CT systems, with a fast and low cost method, based on easily accessible materials to the physicist in the hospital. The key to this approach was the preparation of a novel and highly homogeneous - high activity film flood source, using Fluorine18 as the positrons emitting nuclide. Methods and Materials The source was prepared by immersing silica gel matrix, on Al foils and silica gel matrix on plastic base, in 18 FDG bath solution. In all incubation experiments, the films were thoroughly immersed in a standardized volume (100 ml) of water for injection containing the radiopharmaceutical solution and they were incubated for a specified time period of 5 minutes. In the case of the silica gel matrix on plastic base a cup of oral opaque was added. At the end of incubation, the films were dry-blotted and subsequently they were placed between Poly methyl methacrylate (PMMA) blocks of various thickness, prior to imaging. In terms of homogeneity both films gave comparable results, so they were placed tightly in the middle of 16 ( ) cm 3 and 20 ( ) cm 3 PMMA blocks -to simulate HEAD and BODY- in horizontal and vertical position. The phantoms were imaged in a GE Discovery ST and in a Siemens Biograph 6 hybrid PET/CT systems by using their standard imaging protocols for whole body and brain (Figure 1). The transaxials and the sagittal slices of the head phantom with the film flood source in horizontal position are shown on Figure 2. The MTF was then calculated through Fourier transformation of the line spread function (LSF) profile of the film, imaged as a line in CT reconstruction [6]. The low dose CT image of the silica gel matrix on Al foil and it's the line spread function are shown in Figure 3. The third graph is the Modulation transfer Function and number's correspond to it's 2 and 5 percent level. One important parameter is the nyquist frequency witch depends on the size of the displayed field of view. In all our experiments MTF's clearly drop to the cutoff frequency well below the nyquist frequency. By applying the same approach to PET image (Figure 4), the effects of different reconstruction algorithms, use of septa and the shape of the scanned object on MTF Page 3 of 15

4 were investigated in both scanners. The coincidence in the fused PET and CT image were investigated as well. Images for this section: Fig. 1: picture of the head phantom with the film food source in it. Page 4 of 15

5 Fig. 2: transaxials and sagittal slices of the head phantom with the film flood source in horizontal position Fig. 3: Modulation Transfer Function calculation of the CT image Page 5 of 15

6 Fig. 4: Modulation Transfer Function calculation of the PET image Page 6 of 15

7 Results The GE system can acquire PET data in 3D and in 2D mode, that is with the septa extended. The LSF of the source within the body phantom scanned in WB 2D PET is shown in Figure 1. The SIEMENS Biograph does not have septa and it acquires PET data only in 3D. In Figure's 2 and 3 the MTF's of the WB 3D and BRAIN 3D PET protocols are shown respectively for the GE and the SIEMENS system. In figure 4 calculated results for the Modulation Transfer Function, obtained from the PET 3D brain protocol are shown for different reconstruction algorithms / filters for the GE system. The transaxial slice of the source in horizontal position was used for the MTF determination. In all algorithms the technique of Fourier rebining (FORE) has been applied to convert the 3D collected data onto a set of parallel sinograms so they can be reconstructed using the conventional 2D filtered back projection methods. The iterative reconstructions are better than the Filtered Back Projection. Good low frequency response is needed to outline the coarse details of the image and is important for presentation and detection of relatively large but low contrast lesions. Good high frequency response is necessary to portray fine details and sharp edges. This is of obvious importance for small objects but also sometimes for larger objects because of the importance of edges and sharp borders for detection of low contrast objects and for accurate assessment of their size and shape. By using the 3D brain protocol and FORE filtered back projection with Hanning filter, the MTFs for different plexiglass width's from the transsaxial slice of the source in horizontal position were computed (Figure 5). While low frequency response is similar there is some differentiation in the high frequency area, as the plexiglass block thickness increases. In addition by this method the shift between the CT and the PET images in fusion can be calculated in both axis. This is possible by scanning the two channels of the fused image, (grey which represents the CT data and the red which represents the PET data). By plotting the corresponding Line Spread Functions in the same graph the shift between the CT and the PET image in fusion can be evaluated (Figure 6). The shift between the two images, for the GE system, was less than two millimetres and that has been confirmed also with the manufacturer's test for the PET and the CT image registration. Similar results were observed for the saggital slice, when the phantom was placed horizontally and for the transverse and coronal slices, when the phantom was placed vertically. Our results are comparable with the results from previous work done for the determination of the MTF in computed tomography [6]. Page 7 of 15

8 The comparison of the two systems showed an advantage of the SIEMENS Biograph, due scintillator material and smaller crystal dimensions. Although further evaluation of our method is required, it provides an easy means to evaluate the frequency response of each kernel available. Images for this section: Fig. 1: GE Discovery ST: WB 2D, Recon: FORE OS-EM, Iterations: 2, Subsets: 30, ( ) Page 8 of 15

9 Fig. 2: Top: GE Discovery ST: WB 3D, Recon: FORE Iterative, Iterations: 5, Subsets: 32, ( ), Bottom: SIEMENS Biograph 6: WB 3D, Recon: Iterative, Iterations: 4, Subsets: 8, ( ). Page 9 of 15

10 Fig. 3: Top: GE Discovery ST: BRAIN 3D, Recon: FORE Iterative, Iterations: 4, Subsets: 48, ( ), Bottom: SIEMENS Biograph 6: BRAIN 3D, Recon: Iterative, Iterations: 6, Subsets: 10, ( ). Page 10 of 15

11 Fig. 4: Modulation Transfer Function of images reconstructed with different algorithms/ filters Page 11 of 15

12 Fig. 5: Modulation Transfer Function of different plexiglass width's Page 12 of 15

13 Fig. 6: shift between the CT and the PET image in fusion Page 13 of 15

14 Conclusion The method presented here is novel and easy to implement. It requires inexpensive and easily accessible materials, available to the medical physicist in the Hospital. Is robust to aliasing, and is more resilient to noise due to greater data averaging than conventional Point Spread Function (PSF)-integration. Finally, it can be used in quality assurance testing for the determination of the MTF in PET/CT systems. References 1. Coleman M, King M A, Glick S J, Knesaurek K and Penney B C, (1989) Investigation of the stationarity of the modular transfer func-tion and the scatter fraction in conjugate view SPECT restoration fil-tering IEEE Trans of Nucl Sci 36: Bischof C L and Ehrhardt J C, (1977) Modulation transfer function of the EMI CT head scanner Med Phys 4: Nickoloff E L and Riley R, (1985) A simplified approach for modula-tion transfer function determinations in computed tomography Med Phys 12: Droege R T and Morin R L, (1982) A practical method to measure the MTF of CT scanners Med Phys 9: Borasi G, Castellani G, Domenichini R, Franchini M, Granta M, Torresin A, and Tosi G, (1984) Image quality and dose in computerized tomography:evaluation of four CT scanners Med Phys 11: Boone J M, (2001) Determination of the presampled MTF in com-puted tomography Med Phys 28: Ohkubo M, Wada S, Matsumoto T and Nishizawa K, (2006) An effective method to verify line and point spread functions measured in computed tomography Med Phys 33: Dainty J C and Shaw R, (1974) Image Science Academic, London 9. Nusynowitz ML, Benedetto AR. (1975) Simplified method for deter-mining the modulation transfer function for the scintillation camera. J Nucl Med 16: Wieczorek H, (2006) SPECT image quality and quantification, 2006 IEEE Nuclear scince symposium conference record 11. Starck S, Bath M, Carlsson S, (2005) The use of detective quantum Efficiency (DQE) in evaluating the performance of gamma camera systems. Phys. Med. Biol. 50 (2005) Page 14 of 15

15 Personal Information Alexandros Samartzis Medical Physicist Nuclear Medicine and PET/CT Dpt 'Evaggelismos" General Hospital of Athens Ypsiladou 45-47, Athens Greece. Phone: FAX: Page 15 of 15