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DOI: 10.1055/s-0033-1335152
Upgrade to lterative Image Reconstruction (lR) in MDCT lmaging: A Clinical Study for Detailed Parameter Optimization Beyond Vendor Recommendations Using the Adaptive Statistical lterative Reconstruction Environment (ASIR) Part2: The Chest
System-Upgrade auf iterative Bildrekonstruktion (lR) in der MDCT-Bildgebung: Eine klinische Studie zur detaillierten Parameteroptimierung jenseits der Herstellerempfehlungen am Beispiel der adaptiven statistischen iterativen Rekonstruktionsumgebung (ASIR): Teil 2: Der ThoraxPublikationsverlauf
27. Juni 2012
14. Februar 2013
Publikationsdatum:
21. Mai 2013 (online)
![](https://www.thieme-connect.de/media/roefo/201307/lookinside/thumbnails/10.1055-s-0033-1335152-1.jpg)
Abstract
Purpose: To compare the image quality in dose-reduced 64-row CT of the chest at different levels of adaptive statistical iterative reconstruction (ASIR) to full-dose baseline examinations reconstructed solely with filtered back projection (FBP) in a realistic upgrade scenario.
Materials and Methods: A waiver of consent was granted by the institutional review board (IRB). The noise index (NI) relates to the standard deviation of Hounsfield units in a water phantom. Baseline exams of the chest (NI = 29; LightSpeed VCT XT, GE Healthcare) were intra-individually compared to follow-up studies on a CT with ASIR after system upgrade (NI = 45; Discovery HD750, GE Healthcare), n = 46. Images were calculated in slice and volume mode with ASIR levels of 0 – 100 % in the standard and lung kernel. Three radiologists independently compared the image quality to the corresponding full-dose baseline examinations (-2: diagnostically inferior, -1: inferior, 0: equal, + 1: superior, + 2: diagnostically superior). Statistical analysis used Wilcoxon’s test, Mann-Whitney U test and the intraclass correlation coefficient (ICC).
Results: The mean CTDIvol decreased by 53 % from the FBP baseline to 8.0 ± 2.3 mGy for ASIR follow-ups; p < 0.001. The ICC was 0.70. Regarding the standard kernel, the image quality in dose-reduced studies was comparable to the baseline at ASIR 70 % in volume mode (-0.07 ± 0.29, p = 0.29). Concerning the lung kernel, every ASIR level outperformed the baseline image quality (p < 0.001), with ASIR 30 % rated best (slice: 0.70 ± 0.6, volume: 0.74 ± 0.61).
Conclusion: Vendors’ recommendation of 50 % ASIR is fair. In detail, the ASIR 70 % in volume mode for the standard kernel and ASIR 30 % for the lung kernel performed best, allowing for a dose reduction of approximately 50 %.
Zusammenfassung
Ziel: Zielsetzung war im Rahmen eines System-Upgrades ein Vergleich der Bildqualität dosis-reduzierter 64-Zeilen CT´s des Thorax, die mit unterschiedlichem Einfluss von Adaptiver Statistischer Iterativer Rekonstruktion (ASIR) rekonstruiert wurden, mit Voll-Dosis-Voruntersuchungen, welche mittels gefilterter Rückprojektion (FBP) rekonstruiert wurden.
Material und Methoden: Die Ethikkommission hatte keine Bedenken. Der Rauschindex (NI) bezieht sich auf die Standardabweichung in einem Wasserphantom. Baseline-Untersuchungen des Thorax (NI = 29; LightSpeed VCT XT, GE) wurden nach System-Upgrade intra-individuell mit Follow-Up-Untersuchungen eines CT mit ASIR verglichen (NI = 45; Discovery HD750, GE), n = 46. Im Standard- und Lung-Kernel wurden Bilder mit 0 – 100 % ASIR-Einfluss sowohl im Slice- als auch im Volumen-Modus berechnet. Drei Radiologen verglichen die Bildqualität mit der jeweiligen Voll-Dosis-Baseline (-2: diagnostisch schlechter, -1: schlechter, 0: gleich, + 1: besser, + 2: diagnostisch besser). Zur Analyse wurden der Wilcoxon, der Mann-Whitney-U-Test und die Intra-Class-Correlation’s Koeffizient (ICC) verwendet.
Ergebnisse: Im Vergleich zur FBP-Baseline verringerte sich der durchschnittliche CTDIvol der ASIR-Follow-Ups um 53 % auf 8,0 ± 2,3 mGy (p < 0,001, ICC = 0,70). Mit Standard-Kernel war die durchschnittliche Bildqualität der dosis-reduzierten Studien mit denen der Baseline bei ASIR 70 % im Volumen-Modus (-0.07 ± 0.29, p = 0.29) vergleichbar. Für den Lung-Kernel war die Bildqualität jeder ASIR-Stufe besser als die der Baseline (p < 0.001), mit den besten Ergebnissen bei ASIR 30 % (slice: 0.70 ± 0.6, volume: 0.74 ± 0.61).
Schlussfolgerung: Die Herstellerempfehlung von 50 % ASIR ist in Ordnung. Im Detail waren aber mit dem Standard-Kernel und ASIR 70 % im Volumen-Modus und mit dem Lung-Kernel und ASIR 30 % die besten Ergebnisse zu erreichen und erlauben eine Dosiseinsparung von etwa 50 %.
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References
- 1 Hall EJ, Brenner DJ. Cancer risks from diagnostic radiology. Br J Radiol 2008; 81 (965) 362-378
- 2 Brenner DJ, Elliston CD. Estimated radiation risks potentially associated with full-body CT screening. Radiology 2004; 232: 735-738
- 3 Galanski M, Nagel HD, Stamm G. CT-Expositionspraxis in der Bundesrepublik Deutschland. Fortschr Röntgenstr 173 (2001) R1-66
- 4 Kubo T, Lin PJ, Stiller W et al. Radiation dose reduction in chest CT: a review. Am J Roentgenol Am J Roentgenol 2008; 190: 335-43
- 5 Dougeni E, Faulkner K, Panayiotakis G. A review of patient dose and optimisation methods in adult and paediatric CT scanning. Eur J Radiol. [Review]. 2012; 81: e665-683
- 6 Ghoshhajra BB, Engel LC, Karolyi M et al. Cardiac Computed Tomography Angiography With Automatic Tube Potential Selection: Effects on Radiation Dose and Image Quality. J Thorac Imaging 2013; 28 (1) 40-48
- 7 Gosch D, Stumpp P, Kahn T et al. Performance of an automatic dose control system for CT: anthropomorphic phantom studies. Fortschr Röntgenstr 183 (2011) 154-162
- 8 Nagel HD, Stumpp P, Kahn T et al. Performance of an automatic dose control system for CT: specifications and basic phantom tests. Fortschr Röntgenstr 183 (2011) 60-67
- 9 Thibault JB, Sauer KD, Bouman CA et al. A three-dimensional statistical approach to improved image quality for multislice helical CT. Med Phys 2007; 34: 4526-4544
- 10 Fleischmann D, Boas FE. Computed tomography--old ideas and new technology. Eur Radiol 2011; 21: 510-517
- 11 Kropil P, Lanzman RS, Walther C et al. Dosisreduktion und Bildqualitat in der MDCT des Oberbauchs: Potenzial eines adaptiven Nachverarbeitungsfilters. Fortschr Röntgenstr 2010; 182: 248-253
- 12 Kropil P, Cohnen M, Andersen K et al. Bildqualitat in der Multidetektor-CT der Nasennebenhohlen: Potenzial zur Dosisreduktion bei Anwendung eines adaptiven Nachverarbeitungsfilters. Fortschr Röntgenstr 2010; 182: 973-978
- 13 Leipsic J, Nguyen G, Brown J et al. A prospective evaluation of dose reduction and image quality in chest CT using adaptive statistical iterative reconstruction. Am J Roentgenol Am J Roentgenol 2010; 195: 1095-1099
- 14 Qi LP, Li Y, Tang L et al. Evaluation of dose reduction and image quality in chest CT using adaptive statistical iterative reconstruction with the same group of patients. Br J Radiol 2012; 85 (1018) e906-e911
- 15 Yanagawa M, Honda O, Yoshida S et al. Adaptive statistical iterative reconstruction technique for pulmonary CT: image quality of the cadaveric lung on standard- and reduced-dose CT. 2010; 17: 1259-1266
- 16 Prakash P, Kalra MK, Digumarthy SR et al. Radiation dose reduction with chest computed tomography using adaptive statistical iterative reconstruction technique: initial experience. J Comput Assist Tomogr 2010; 34: 40-45
- 17 Prakash P, Kalra MK, Ackman JB et al. Diffuse lung disease: CT of the chest with adaptive statistical iterative reconstruction technique. Radiology 2010; 256: 261-269
- 18 Singh S, Kalra MK, Gilman MD et al. Adaptive statistical iterative reconstruction technique for radiation dose reduction in chest CT: a pilot study. Radiology 2011; 259: 565-573
- 19 Hara AK, Paden RG, Silva AC et al. Iterative reconstruction technique for reducing body radiation dose at CT: feasibility study. Am J Roentgenol Am J Roentgenol 2009; 193: 764-771
- 20 Honda O, Yanagawa M, Inoue A et al. Image quality of multiplanar reconstruction of pulmonary CT scans using adaptive statistical iterative reconstruction. Br J Radiol 2011; 84: 335-341
- 21 Prakash P, Kalra MK, Kambadakone AK et al. Reducing abdominal CT radiation dose with adaptive statistical iterative reconstruction technique. Invest Radiol 2010; 45: 202-210
- 22 Heilbron BG, Leipsic J. Submillisievert coronary computed tomography angiography using adaptive statistical iterative reconstruction – a new reality. Can J Cardiol 2010; 26: 35-36
- 23 Mueck FG, Korner M, Scherr MK et al. Upgrade to iterative image reconstruction (IR) in abdominal MDCT imaging: a clinical study for detailed parameter optimization beyond vendor recommendations using the adaptive statistical iterative reconstruction environment (ASIR). Fortschr Röntgenstr 2012; 184: 229-238
- 24 Kalra MK, Maher MM, Blake MA et al. Multidetector CT scanning of abdomen and pelvis: a study for optimization of automatic tube current modulation technique in 120 subjects [abstract]. In: Radiological Society of North America Scientific Assembly and Annual Meeting Program. Oak Brook, III: Radiological Society of North America; 2003: 294
- 25 McCollough CH, Bruesewitz MR, Kofler JM et al. CT dose reduction and dose management tools: overview of available options. Radiographics 2006; 26: 503-512
- 26 Samei E, Badano A, Chakraborty D et al. Assessment of display performance for medical imaging systems: executive summary of AAPM TG18 report. Med Phys 2005; 32: 1205-1225
- 27 EUR 16262. Quality criteria for computed tomography. Available at: http://www.drs.dk/guidelines/ct/quality/download/eur16262.w51 Accessed March 25 ee.
- 28 Zarb F, Rainford L, McEntee MF. AP diameter shows the strongest correlation with CTDI and DLP in abdominal and chest CT. Radiat Prot Dosimetry 2010; 140: 266-273
- 29 Deak ZDP, Wirth S, Reiser MF et al. Comparing the effect of two different CT detectors of different generations on image noise (IN): a phantom study. Abstract accepted for RSNA meeting 2011.
- 30 Tsukagoshi S, Ota T, Fujii M et al. Improvement of spatial resolution in the longitudinal direction for isotropic imaging in helical CT. Phys Med Biol 2007; 52: 791-801
- 31 Pontana F, Duhamel A, Pagniez J et al. Chest computed tomography using iterative reconstruction vs filtered back projection (Part 2): image quality of low-dose CT examinations in 80 patients. Eur Radiol 21 (2011) 636-643
- 32 Yamada Y, Jinzaki M, Hosokawa T et al. Dose reduction in chest CT: Comparison of the adaptive iterative dose reduction 3D, adaptive iterative dose reduction, and filtered back projection reconstruction techniques. Eur J Radiol 2012; 81 (12) 4185-4195
- 33 Katsura M, Matsuda I, Akahane M et al. Model-based iterative reconstruction technique for radiation dose reduction in chest CT: comparison with the adaptive statistical iterative reconstruction technique. Eur Radiol 2012; 22 (8) 1613-1623