Validation of CT brain perfusion methods using a realistic dynamic head phantom

Medical Physics

Volumn 38, Issue 6, 2011, Pages 3212-3221

  Riordan, Alan J ^a   Prokop, Mathias ^a,b   Viergever, Max A ^a   Dankbaar, Jan Willem ^a   Smit, Ewoud J ^a   De Jong, Hugo W A M ^a  

^a UNIVERSITY MEDICAL CENTER UTRECHT   (Netherlands)

^b RADBOUD UNIVERSITY NIJMEGEN   (Netherlands)

Author keywords

brain CT; CT perfusion; phantom

Indexed keywords

BRAIN; BRAIN MAPPING; CARDIOVASCULAR SYSTEM; MAGNETIC RESONANCE IMAGING; PHANTOMS;

ATTENUATION CURVE; BRAIN CT; BRAIN PARENCHYMA; BRAIN PERFUSION; CT PERFUSION; GOOD CORRELATIONS; HIGH RESOLUTION; RECONSTRUCTION PARAMETERS;

COMPUTERIZED TOMOGRAPHY;

EID: 79958827940     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.3592639     Document Type: Article

References (33)

1. E. Klotz and M. Konig, Perfusion measurements of the brain: using dynamic CT for the quantitative assessment of cerebral ischemia in acute stroke., Eur. J. Radiol. 30, 170-184 (1999). 10.1016/S0720-048X(99)00009-1 (Pubitemid 29343734)
2. T. E. Mayer, Dynamic CT perfusion imaging of acute stroke., Amer. J. Neuroradiol. 21, 1441-1449 (2000).
3. M. H. Lev, Utility of perfusion-weighted CT imaging in acute middle cerebral artery stroke treated with intra-arterial thrombolysis-Prediction of final infarct volume and clinical outcome., Stroke 32, 2021-2027 (2001). 10.1161/hs0901.095680 (Pubitemid 32868090)
4. B. D. Murphy, White matter thresholds for ischemic penumbra and infarct core in patients with acute stroke: CT perfusion study., Radiology 247, 818-825 (2008). 10.1148/radiol.2473070551
5. K. Nambu, R. Takehara, and T. Terada, A method of regional cerebral blood perfusion measurement using dynamic CT with an iodinated contrast medium., Acta Neurol. Scand. 93, 28-31 (1996). 10.1111/j.1600-0404.1996.tb00537.x (Pubitemid 26180504)
6. M. Wintermark, W. S. Smith, N. U. Ko, M. Quist, P. Schnyder, and W. P. Dillon, Dynamic perfusion CT: Optimizing the temporal resolution and contrast volume for calculation of perfusion CT parameters in stroke patients., Amer. J. Neuroradiol. 25, 720-729 (2004). (Pubitemid 38657652)
7. K. Kudo, Differences in CT perfusion maps generated by different commercial software: Quantitative analysis by using identical source data of acute stroke patients., Radiology 254, 200-209 (2010). 10.1148/radiol.254082000
8. T. Teslow and R. Robb, X-ray computed tomographic (CT) phantom designed for the development of techniques for measurement of myocardial perfusion., Phys. Med. Biol. 36, 1407-1413 (1991). 10.1088/0031-9155/36/10/007
9. B. Ebrahimi, S. Swanson, and T. Chupp, A microfabricated phantom for quantitative MR perfusion measurements: Validation of singular value decomposition deconvolution method., IEEE Trans. Biomed. Eng. 57, 2730-2736 (2010). 10.1109/TBME.2010.2055866
10. A. Maciak, A capillary-based perfusion phantom for the simulation of brain perfusion for MRI., Rofo 182, 883-890 (2010).
11. U. Haberland, A biological phantom for contrast-media-based perfusion studies with CT., Invest. Radiol. 44, 676-682 (2009). 10.1097/RLI. 0b013e3181afbb03
12. M. Sasaki, K. Kudo, K. Ogasawara, and S. Fujiwara, Tracer delay-insensitive algorithm can improve reliability of CT perfusion imaging for cerebrovascular steno-occlusive disease: Comparison with quantitative single-photon emission CT., Amer. J. Neuroradiol. 30, 188-193 (2009). 10.3174/ajnr.A1274
13. L. Axel, A method for calculating brain blood flow with a CT dynamic scanner., Adv. Neurol. 30, 67-71 (1981).
14. L. Ostergaard, R. M. Weisskoff, D. A. Chesler, C. Gyldensted, and B. R. Rosen, High resolution measurement of cerebral blood flow using intravascular tracer bolus passages.1. Mathematical approach and statistical analysis., Magn. Reson. Med. 36, 715-725 (1996). 10.1002/mrm.v36:5 (Pubitemid 26376710)
15. O. Wu, L. Ostergaard, R. M. Weisskoff, T. Benner, B. R. Rosen, and A. G. Sorensen, Tracer arrival timing-insensitive technique for estimating flow in MR perfusion-weighted imaging using singular value decomposition with a block-circulant deconvolution matrix., Magn. Reson. Med. 50, 164-174 (2003). 10.1002/mrm.v50:1 (Pubitemid 36841872)
16. K. Kudo, Perfusion mismatch analyzer., version 3.0.0.0, http://asist.umin.jp/index-e.htm, Published November 2006, Updated March 2010, Accessed March 2010.
17. A. M. Dale, B. Fischl, and M. I. Sereno, Cortical surface-based analysis-I. Segmentation and surface reconstruction., Neuroimage 9, 179-194 (1999). 10.1006/nimg.1998.0395 (Pubitemid 29369874)
18. B. Fischl and A. M. Dale, Measuring the thickness of the human cerebral cortex from magnetic resonance images., Proc. Natl. Acad. Sci. U. S. A. 97, 11050-11055 (2000). 10.1073/pnas.200033797
19. B. Fischl, A. Liu, and A. M. Dale, Automated manifold surgery: Constructing geometrically accurate and topologically correct models of the human cerebral cortex., IEEE Trans. Med. Imag. 20, 70-80 (2001). 10.1109/42.906426 (Pubitemid 32293421)
20. Freesurfer image analysis suite: http://surfer.nmr.mgh.harvard.edu/.
21. P. J. Koopmans, R. Manniesing, W. J. Niessen, M. A. Viergever, and M. Barth, MR venography of the human brain using susceptibility weighted imaging at very high field strength., Magn. Reson. Mater. Phys. Biol. Med. 21, 149-158 (2008).
22. P. Meier and K. L. Zierler, On the theory of the indicator-dilution method for measurement of blood flow and volume., J. Appl. Physiol. 6, 731-744 (1954).
23. K. L. Zierler, Equations for measuring blood flow by external monitoring of radioisotopes., Circ. Res. 16, 309 321 (1965).
24. J. Bredno, M. E. Olszewski, and M. Wintermark, Simulation model for contrast agent dynamics in brain perfusion scans., Magn. Reson. Med. 64, 280-290 (2010). 10.1002/mrm.22431
25. L. M. Parkes, W. Rashid, D. T. Chard, and P. S. Tofts, Normal cerebral perfusion measurements using arterial spin labeling: Reproducibility, stability, and age and gender effects., Magn. Reson. Med. 51, 736-743 (2004). 10.1002/mrm.v51:4 (Pubitemid 38420450)
26. I. van der Schaaf, E. J. Vonken, A. Waaijer, B. Velthuis, M. Quist, and T. van Osch, Influence of partial volume on venous output and arterial input function., Amer. J. Neuroradiol. 27, 46-50 (2006). (Pubitemid 46939882)
27. O. A. Larsen and N. A. Lassen, Cerebral hematocrit in normal man., J. Appl. Physiol. 19, 571 574 (1964).
28. F. Sakai, Regional cerebral blood-volume and hematocrit measured in normal human volunteers by single-photon emission computed-tomography., J. Cereb. Blood Flow Metab. 5, 207-213 (1985). 10.1038/jcbfm.1985.27 (Pubitemid 15123206)
29. M. Reivich, Blood flow metabolism couple in brain., Res. Pub. Assoc. Res. Nerv. Ment. Dis. 53 125-140 (1974).
30. M. A. Weinstein, P. M. Duchesneau, and W. J. Macintyre, White and gray-matter of brain differentiated by computed tomography., Radiology 122, 699-702 (1977). (Pubitemid 8037747)
31. K. A. Hossmann, Viability thresholds and the penumbra of focal ischemia., Ann. Neurol. 36, 557-565 (1994). 10.1002/ana.v36:4
32. M. Wintermark, Simultaneous measurements of regional cerebral blood flows by perfusion-CT and stable xenon-CT: A validation study., Amer. J. Neuroradiol. 22, 905-914 (2001). (Pubitemid 32436235)
33. K. Kudo, Difference in tracer delay-induced effect among deconvolution algorithms in CT perfusion analysis: Quantitative evaluation with digital phantoms., Radiology 251, 241-249 (2009). 10.1148/radiol.2511080983