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DOI: 10.1160/ME9040
Motion Artifact Reducing Reconstruction of 4D CT Image Data for the Analysis of Respiratory Dynamics
Publication History
Publication Date:
20 January 2018 (online)
![](https://www.thieme-connect.de/media/10.1055-s-00035037/200703/lookinside/thumbnails/10-1160-me9040-1.jpg)
Summary
Objectives: Respiratory motion represents a major problem in radiotherapy of thoracic and abdominal tumors. Methods for compensation require comprehensive knowledge of underlying dynamics. Therefore, 4D (= 3D + t) CT data can be helpful. But modern CT scanners cannot scan a large region of interest simultaneously. So patients have to be scanned in segments. Commonly used approaches for reconstructing the data segments into 4D CT images cause motion artifacts. In orderto reduce the artifacts, a new method for 4D CT reconstruction is presented. The resulting data sets are used to analyze respiratory motion.
Methods: Spatiotemporal CT image sequences of lung cancer patients were acquired using a multi-slice CT in cine mode during free breathing. 4D CT reconstruction was done by optical flow based temporal interpolation. The resulting 4D image data were compared with data generated bythe commonly used nearest neighbor reconstruction. Subsequent motion analysis is mainly concerned with tumor mobility.
Results: The presented optical flow-based method enables the reconstruction of 3D CT images at arbitrarily chosen points of the patient’s breathing cycle. A considerable reduction of motion artifacts has been proven in eight patient data sets. Motion analysis showed that tumor mobility differs strongly between the patients.
Conclusions: Due to the proved reduction of motion artifacts, the optical flow-based 4D CT reconstruction offers the possibility of high-quality motion analysis. Because the method is based on an interpolation scheme, it additionally has the potential to enable the reconstruction of 4D CT data from a lesser number of scans.
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References
- 1 Hanley J, Debois MM, Mah D, Mageras GS, Raben A, Rosenzweig K. et al. Deep inspiration breath-hold technique for lung tumors: the potential value of target immobilization and reduced lung density in dose escalation. Int J Radiat Oncol Biol Phys 1999; 45 (03) 603-611.
- 2 Wilson EM, Williams FJ, Lyn BE, Wong JW, Aird EGA. Validation of active breathing control in patients with non-small-cell lung cancer to be treated with CHARTWEL. Int J Radiat Oncol Biol Phys 2003; 57 (03) 864-874.
- 3 Kubo HD, Hill BC. Respiration gated radiotherapy treatment: a technical study. Phys Med Biol 1996; 41 (01) 83-91.
- 4 Mageras GS, Yorke E, Rosenzweig K, Braban L, Keatley E, Ford E. et al. Fluoroscopic evaluation of diaphragmatic motion reduction with a respiratory gated radiotherapy system. J Appl Clin Med Phys 2001; 02 (04) 191-200.
- 5 Keall PJ, Kini VR, Vedam SS, Mohan R. Motion adaptive x-ray therapy: a feasibility study. Phys Med Biol 2001; 46 (01) 1-10.
- 6 Schweikard A, Glosser G, Bodduluri M, Murphy MJ, Adler JR. Robotic motion compensation for respiratory movement during radiosurgery. Comput Aided Surg 2000; 05 (04) 263-277.
- 7 Dawson L, Balter JM. Interventions to reduce organ motion effects in radiation delivery Semin Radat Oncol. 2004; 14: 65-75.
- 8 Low DA, Nystrom M, Kalinin E, Parikh P, Demp-sey JF, Bradley JD. et al. A method for the reconstruction of four-dimensional synchronized CT scans acquired during free breathing. Med Phys 2003; 30 (06) 1254-1263.
- 9 Pan T, Lee T, Rietzel E, Chen GTY. 4D-CT imaging of a volume influenced by respiratory motion on multi-slice CT. Med Phys 2004; 31 (02) 333-340.
- 10 Vedam SS, Keall PJ, Kim VR, Mostafavi H, Shukla HP, Mohan R. Acquiring a four-dimensional computed tomography dataset using an external respiratory signal. Phys Med Biol 2003; 48 (01) 45-62.
- 11 Keall PJ, Starkschall G, Shukla H, Forster KM, Ortiz V, Stevens CW. et al. Acquiring 4D thoracic CT scans using amultislice helical method. Phys Med Biol 2004; 49 (10) 2053-2067.
- 12 McCollough CH, Bruesewitz MR, Daly TR, Zink FE. Motion artifacts in subsecond conventional CT and electron-beam CT: pictorial demonstration of temporal resolution. Radiographics 2000; 20 (06) 1675-1681.
- 13 Lu W, Parikh PJ, El Naqa IM, Nystrom MM, Hubenschmidt JP, Wahab SH. et al. Quantitation of the reconstruction quality of a four-dimensional computed tomography process for lung cancer patients. Med Phys 2005; 32 (04) 890-901.
- 14 Seppenwoolde Y, Shirato H, Kitamura K, Shimizu S, van Herk M, Lebesque JV. et al. Precise and real-time measurement of 3D tumor motion in lung due to breathing and heartbeat, measured during radiotherapy. Int J Radiat Oncol Biol Phys 2002; 53 (04) 822-834.
- 15 Ehrhardt J, Säring D, Handels H. Stucture-preserving Interpolation of Temporal and Spatial Image Sequences Using an Optical Flow-based Method. Methods Inf Med 2007; 46: 300-307.
- 16 Horn BKP, Schunk BG. Determining optical flow. Artificial Intelligence 1981; 17: 185-203.
- 17 Barron JL, Fleet DJ, Beauchemin SS. Performance of optical flow techniques. Int J Comp Vision 1994; 12: 43-77.
- 18 Ehrhardt J, Handels H, Plötz W, Pöppl SJ. Atlas-based recognition of anatomical structures and landmarks and the automatic computation of orthopedic parameters. Methods Inf Med 2004; 43 (04) 391-397.
- 19 Fischer B, Modersitzki J. Intensity-based image registration with a guaranteed one-to-one point match. Methods Inf Med 2004; 43 (04) 327-330.
- 20 Thirion JP. Imagematchingasadiffusionprocess: an analogy with Maxwell’s demons. Med Image Anal 1998; 02 (03) 243-260.
- 21 Matej S, Furuie S, Herman G. Relevance of statistically significant differences between reconstruction algorithms. IEEE Trans Image Proc 1996; 05 (03) 554-556.
- 22 Ibanez L, Schroeder W. The ITK Software Guide. Kitware Inc.. 2004
- 23 Schroeder W, Martin K, Lorensen B. The Visualization Toolkit, Third Edition. Kitware Inc.. 2004
- 24 Langen KM, Jones DT. Organ motion and its management. Int J Radiat Oncol Biol Phys 2001; 50 (01) 265-278.
- 25 Schoebinger M, Plathow C, Wolf I, Kauczor H, Meinzer H. Quantification of tumor mobility during the breathing cycle using 3D dynamic MRI. Manduca A, Amini AA. Medical Imaging 2006: Physiology, Function, and Structure from Medical Images. Proc. SPIE Vol. 6143; Feb 2006. San Diego, USA: 2006: 61430P-1-61430P-8.