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Novel registration-based framework for CT angiography in lower legs

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Abstract

Proper subtraction and visualization of contrast-enhanced blood vessels in lower extremities using computed tomography angiography (CTA) is based on precise masking of all non-contrasted structures in the area, and it is the main prerequisite for correct diagnosis and decision on treatment for peripheral arterial occlusive disease (PAOD). Because of possible motion of patients during the CTA examination, precise elimination of non-contrasted tissues, including bones, calcifications, and soft tissue, is still very challenging for lower legs, that is, from knees to toes. We propose novel registration-based framework for detection and correction of the motion in lower legs, which typically occurs between and during CTA pre-contrast and post-contrast acquisitions. Within the framework, two registration cores are proposed as alternatives, and resulting CTA subtraction images are compared with Advanced Vessel Analysis considered one of the reference commercial tools among clinical applications for CTA of lower extremities. The CTA subtraction images of 55 patients examined for PAOD are evaluated visually by four expert observers on the Philips Extended Brilliance Workspace using four criteria assessing the overall robustness of tested methods. According to the complex evaluation, the proposed framework enabled valuable improvements of CTA examination of lower legs.

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References

  1. Cachier P, Pennec X, Ayache N (1999) Fast non-rigid matching by gradient descent: study and improvements of the demons algorithm. INRIA Tech. Rep

  2. Cernic S, Pozzi Mucelli F, Pellegrin A et al (2009) Comparison between 64-row CT angiography and digital subtraction angiography in the study of lower extremities: personal experience. Radiol Med (Torino) 114:1115–1129

    Article  CAS  Google Scholar 

  3. Chin AS, Rubin GD (2006) CT angiography of peripheral arterial occlusive disease. Tech Vasc Interv Radiol 9:143–149

    Article  PubMed  Google Scholar 

  4. Dean SM (2008) Atypical ischemic lower extremity ulcerations: a differential diagnosis. Vasc Med 13:47–54

    Article  PubMed  Google Scholar 

  5. Fleischmann D, Hallett RL, Rubin GD (2006) CT angiography of peripheral arterial disease. J Vasc Interv Radiol 17:3–26

    Article  PubMed  Google Scholar 

  6. Jan J, Malinsky M, Peter R, Ourednicek P (2010) Improved disparity based image processing in 3D CT subtractive angiography. In: Annual international conference of the IEEE 2010 on engineering in medicine and biology society (EMBC), pp 3610–3613

  7. Jan J, Malinsky M, Peter R, Ourednicek P (2011) Flexible 3D disparity based registration as background for improved CT angiography vessel representation. Kaunas, pp 69–71

  8. Kang Yan, Engelke K, Kalender WA (2003) A new accurate and precise 3-D segmentation method for skeletal structures in volumetric CT data. IEEE Trans Med Imaging 22:586–598. doi:10.1109/TMI.2003.812265

    Article  PubMed  Google Scholar 

  9. Klein S, Pluim JPW, Staring M, Viergever MA (2009) Adaptive stochastic gradient descent optimization for image registration. Int J Comput Vision 81:227–239

    Article  Google Scholar 

  10. Klein S, Staring M, Murphy K et al (2010) Elastix: a toolbox for intensity-based medical image registration. IEEE Trans Med Imaging 29:196–205

    Article  PubMed  Google Scholar 

  11. Kroon DJ, Slump CH (2009) MRI modality transformation in demon registration. In: IEEE international symposium on biomedical imaging: from nano to macro, 2009. ISBI’09. pp 963–966

  12. Lee IJ, Chung JW, Hong H et al (2011) Subtraction CT angiography of the lower extremities: single volume subtraction versus multi-segmented volume subtraction. Acad Radiol 18:902–909

    Article  PubMed  Google Scholar 

  13. Lepäntalo M, Tukiainen E (2002) Advanced leg salvage. Perspect Vasc Surg Endovasc Therapy 15:27–41

    Article  Google Scholar 

  14. Lin PH, Bechara C, Kougias P et al (2009) Assessment of aortic pathology and peripheral arterial disease using multidetector computed tomographic angiography. Vasc Endovasc Surg 42:583–598

    Article  Google Scholar 

  15. Liu L, Raber D, Nopachai D et al (2008) Interactive separation of segmented bones in CT volumes using graph cut. Med Image Comput Comput Assist Interv 11:296–304

    PubMed  Google Scholar 

  16. Maksimov D, Finkel F, Dietz T et al (2004) An interactive application for removal of bone information in CT-angiography. Proceedings of 17th IEEE symposium on computer-based medical systems, 2004 (CBMS 2004). pp 396–401

  17. Modersitzki J (2004) Numerical methods for image registration. Oxford Univ Press, Oxford

    Google Scholar 

  18. Otsu N (1975) A threshold selection method from gray-level histograms. Automatica 11:23–27

    Google Scholar 

  19. Ourednicek P, Jan J, Malinsky M, Peter R (2010) Piece-wise rigid registration as a way to improvement of CT angiographic image data. In: Proceedings of ESR congress Vienna

  20. Pardo X, Carreira M, Mosquera A, Cabello D (2001) A snake for CT image segmentation integrating region and edge information. Image Vis Comput 19:461–475

    Article  Google Scholar 

  21. Pearson K (1909) Determination of the coefficient of correlation. Science 30:23–25

    Article  PubMed  CAS  Google Scholar 

  22. Peter R, Malinsky M, Jan J, Ourednicek P (2010) Novel automated 3D registration in CT subtraction angiography. Proceedings of biosignal 2010: analysis of biomedical signals and images, Brno University of Technology, pp 133–137

  23. Raman R, Napel S, Beaulieu CF et al (2002) Automated generation of curved planar reformations from volume data: method and evaluation. Radiology 223:275–280

    Article  PubMed  Google Scholar 

  24. Schernthaner R, Stadler A, Lomoschitz F et al (2008) Multidetector CT angiography in the assessment of peripheral arterial occlusive disease: accuracy in detecting the severity, number, and length of stenoses. Eur Radiol 18:665–671

    Article  PubMed  CAS  Google Scholar 

  25. Sedgewick R (1998) Algorithms in C, 3rd edn. Part of Chapter XVI. Algorithms in C, pp 662–691

  26. Staring M (2008) Intrasubject registration for change analysis in medical imaging. Dissertation Thesis, University Medical Center Utrecht

  27. Staring M, Klein S, Pluim JPW (2007) A rigidity penalty term for nonrigid registration. Med Phys 34:4098–4108

    Article  PubMed  Google Scholar 

  28. Straka M, Dela Cruz W, Blackmon C et al (2004) Rapid detection of group B streptococcus and Escherichia coli in amniotic fluid using real-time fluorescent PCR. Infect Dis Obstet Gynecol 12:109–114

    Article  PubMed  CAS  Google Scholar 

  29. Thirion JP (1998) Image matching as a diffusion process: an analogy with Maxwell’s demons. Med Image Anal 2:243–260

    Article  PubMed  CAS  Google Scholar 

  30. Tvrdik J (2002) Controlled random search algorithm with alternating heuristics. Automa 1:54–57

    Google Scholar 

  31. Wang H, Dong L, O’Daniel J et al (2005) Validation of an accelerated ‘demons’ algorithm for deformable image registration in radiation therapy. Phys Med Biol 50:2887

    Article  PubMed  CAS  Google Scholar 

  32. Wang LI, Greenspan M, Ellis R (2006) Validation of bone segmentation and improved 3-D registration using contour coherency in CT data. IEEE Trans Med Imaging 25:324–334

    Article  PubMed  Google Scholar 

  33. Zahlten C, Jurgens H, Evertsz CJ et al (1995) Portal vein reconstruction based on topology. Eur J Radiol 19:96–9100

    Article  PubMed  CAS  Google Scholar 

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Acknowledgments

The project has been supported by Philips Nederland and in its initial phase also by the research center DAR No. 1M0572 sponsored by the Ministry of Education (Czech Republic). Obtaining CT image data from J. Frydrych, M.D., (Hospital in Jablonec-nad-Nisou, CZ), Prof. J. Danes (from Department of Radiology, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague), cooperation of T. Holceplova, M.D. (Hospital J. Hradec, CZ) in the evaluation phase, and access to Philips EBW workstation via the Philips channels is highly acknowledged.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Brno University of Technology, Brno, Czech Republic

    Roman Peter, Milos Malinsky & Jiri Jan

  2. International Clinical Research Center, St. Anne’s University Hospital Brno, Brno, Czech Republic

    Roman Peter

  3. Department of Imaging Methods, St. Anne’s University Hospital Brno, Brno, Czech Republic

    Petr Ourednicek

  4. Faculty of Medicine, Masaryk University, Brno, Czech Republic

    Petr Ourednicek

  5. Philips Medical Systems Nederland BV, Veenpluis 4-6, 5680, DA Best, The Netherlands

    Petr Ourednicek

  6. Department of Radiology, First Faculty of Medicine, Charles University, Prague, Czech Republic

    Lukas Lambert

  7. General University Hospital, Prague, Czech Republic

    Lukas Lambert

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  1. Roman Peter
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  2. Milos Malinsky
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  3. Petr Ourednicek
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  4. Lukas Lambert
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  5. Jiri Jan
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Correspondence to Roman Peter.

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Peter, R., Malinsky, M., Ourednicek, P. et al. Novel registration-based framework for CT angiography in lower legs. Med Biol Eng Comput 51, 1079–1089 (2013). https://doi.org/10.1007/s11517-013-1085-y

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  • DOI: https://doi.org/10.1007/s11517-013-1085-y

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