Sampling requirements in DCE-MRI based analysis of high grade gliomas: Simulations and clinical results

Journal of Magnetic Resonance Imaging

Volumn 37, Issue 4, 2013, Pages 818-829

  Larsson, Christopher ^a,b   Kleppestø, Magne ^b   Rasmussen, Inge ^b   Salo, Raimo ^b   Vardal, Jonas ^a,b   Brandal, Petter ^c   Bjørnerud, Atle ^b,d  

^a UNIVERSITY OF OSLO   (Norway)

^b OSLO UNIVERSITY HOSPITAL   (Norway)

^c OSLO UNIVERSITY HOSPITAL   (Norway)

^d UNIVERSITY OF OSLO   (Norway)

Author keywords

DCE sequence optimization; DCE MRI; glioma; temporal resolution; Tofts model

Indexed keywords

GADOBUTROL;

ADULT; AGED; ARTICLE; CLINICAL ARTICLE; CONTRAST ENHANCEMENT; DYNAMIC CONTRAST ENHANCED MAGNETIC RESONANCE IMAGING; FEMALE; GLIOMA; HUMAN; IMAGE ANALYSIS; IMAGE QUALITY; KINETICS; MALE; MATHEMATICAL MODEL; NUCLEAR MAGNETIC RESONANCE IMAGING; NUCLEAR MAGNETIC RESONANCE SCANNER; PRIORITY JOURNAL; SIMULATION;

EID: 84875414834     PISSN: 10531807     EISSN: 15222586     Source Type: Journal    
DOI: 10.1002/jmri.23866     Document Type: Article

References (37)

1. Larsson HB, Stubgaard M, Frederiksen JL, Jensen M, Henriksen O, Paulson OB,. Quantitation of blood-brain barrier defect by magnetic resonance imaging and gadolinium-DTPA in patients with multiple sclerosis and brain tumors. Magn Reson Med 1990; 16: 117-131. (Pubitemid 20353802)
2. Tofts PS,. Modeling tracer kinetics in dynamic Gd-DTPA MR imaging. J Magn Reson Imaging 1997; 7: 91-101. (Pubitemid 28365643)
3. Tofts PS, Brix G, Buckley DL, et al. Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusable tracer: standardized quantities and symbols. J Magn Reson Imaging 1999; 10: 223-232. (Pubitemid 29463104)
4. Sorensen AG, Batchelor TT, Zhang WT, et al. A "vascular normalization index" as potential mechanistic biomarker to predict survival after a single dose of cediranib in recurrent glioblastoma patients. Cancer Res 2009; 69: 5296-5300.
5. Patankar TF, Haroon HA, Mills SJ, et al. Is volume transfer coefficient (K(trans)) related to histologic grade in human gliomas? AJNR Am J Neuroradiol 2005; 26: 2455-2465.
6. Haris M, Gupta RK, Singh A, et al. Differentiation of infective from neoplastic brain lesions by dynamic contrast-enhanced MRI. Neuroradiology 2008; 50: 531-540. (Pubitemid 351763583)
7. Bisdas S, Naegele T, Ritz R, et al. Distinguishing recurrent high-grade gliomas from radiation injury: a pilot study using dynamic contrast-enhanced MR imaging. Acad Radiol 2011; 18: 575-583.
8. Thompson G, Mills SJ, Stivaros SM, Jackson A,. Imaging of brain tumors: perfusion/permeability. Neuroimaging Clin N Am 2010; 20: 337-353.
9. Wen PY, Macdonald DR, Reardon DA, et al. Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group. J Clin Oncol 2010; 28: 1963-1972.
10. Harrer JU, Parker GJ, Haroon HA, et al. Comparative study of methods for determining vascular permeability and blood volume in human gliomas. J Magn Reson Imaging 2004; 20: 748-757. (Pubitemid 39426068)
11. Larsson HB, Courivaud F, Rostrup E, Hansen AE,. Measurement of brain perfusion, blood volume, and blood-brain barrier permeability, using dynamic contrast-enhanced T(1)-weighted MRI at 3 tesla. Magn Reson Med 2009; 62: 1270-1281.
12. Roberts C, Issa B, Stone A, Jackson A, Waterton JC, Parker GJ,. Comparative study into the robustness of compartmental modeling and model-free analysis in DCE-MRI studies. J Magn Reson Imaging 2006; 23: 554-563.
13. Sourbron SP, Buckley DL,. On the scope and interpretation of the Tofts models for DCE-MRI. Magn Reson Med 2011; 66: 735-745.
14. Stupp R, Hegi ME, van den Bent MJ, et al. Changing paradigms-an update on the multidisciplinary management of malignant glioma. Oncologist 2006; 11: 165-180. (Pubitemid 43261763)
15. Lopata RG, Backes WH, van den Bosch PP, van Riel NA,. On the identifiability of pharmacokinetic parameters in dynamic contrast-enhanced imaging. Magn Reson Med 2007; 58: 425-429. (Pubitemid 47267663)
16. Larsson HB, Rosenbaum S, Fritz-Hansen T,. Quantification of the effect of water exchange in dynamic contrast MRI perfusion measurements in the brain and heart. Magn Reson Med 2001; 46: 272-281. (Pubitemid 32703272)
17. Bjornerud A, Emblem KE,. A fully automated method for quantitative cerebral hemodynamic analysis using DSC-MRI. J Cereb Blood Flow Metab 2010; 30: 1066-1078.
18. Rohde GK, Barnett AS, Basser PJ, Marenco S, Pierpaoli C,. Comprehensive approach for correction of motion and distortion in diffusion-weighted MRI. Magn Reson Med 2004; 51: 103-114. (Pubitemid 38095707)
19. Ziegelitz D, Starck G, Mikkelsen IK, et al. Absolute quantification of cerebral blood flow in neurologically normal volunteers: dynamic-susceptibility contrast MRI-perfusion compared with computed tomography (CT)-perfusion. Magn Reson Med 2009; 62: 56-65.
20. Murase K,. Efficient method for calculating kinetic parameters using T-1-weighted dynamic contrast-enhanced magnetic resonance imaging. Magn Reson Med 2004; 51: 858-862. (Pubitemid 38420465)
21. Press WH, Teukolski SA, Vetterling WT, Flannery BP,. Numerical recipes in C. The art of scientific computing. 2nd edition. Cambridge: Cambridge Uinversity Press; 1992. 681 p.
22. Henderson E, Rutt BK, Lee TY,. Temporal sampling requirements for the tracer kinetics modeling of breast disease. Magn Reson Imaging 1998; 16: 1057-1073. (Pubitemid 29196842)
23. Singh A, Rathore RK, Haris M, Verma SK, Husain N, Gupta RK,. Improved bolus arrival time and arterial input function estimation for tracer kinetic analysis in DCE-MRI. J Magn Reson Imaging 2009; 29: 166-176.
24. Likar B, Viergever MA, Pernus F,. Retrospective correction of MR intensity inhomogeneity by information minimization. IEEE Trans Med Imaging 2001; 20: 1398-1410. (Pubitemid 34125147)
25. Chang CI, Du Y, Wang J, Guo SM, Thouin PD,. Survey and comparative analysis of entropy and relative entropy thresholding techniques. IEE Proc Vision Signal Processing 2006; 153: 837-850. (Pubitemid 44838040)
26. Studholme C, Hill DLG, Hawkes DJ,. An overlap invariant entropy measure of 3D medical image alignment. Pattern Recognit 1999; 32: 71-86.
27. Barboriak DP, MacFall JR, Viglianti BL, Dewhirst Dvm MW,. Comparison of three physiologically-based pharmacokinetic models for the prediction of contrast agent distribution measured by dynamic MR imaging. J Magn Reson Imaging 2008; 27: 1388-1398. (Pubitemid 351770694)
28. Jackson A, Kassner A, Zhu XP, Li KL,. Reproducibility of T2* blood volume and vascular tortuosity maps in cerebral gliomas. J Magn Reson Imaging 2001; 14: 510-516. (Pubitemid 33029536)
29. Emblem KE, Nedregaard B, Nome T, et al. Glioma grading by using histogram analysis of blood volume heterogeneity from MR-derived cerebral blood volume maps. Radiology 2008; 247: 808-817.
30. Goh V, Halligan S, Hugill JA, Gartner L, Bartram CI,. Quantitative colorectal cancer perfusion measurement using dynamic contrast-enhanced multidetector-row computed tomography: effect of acquisition time and implications for protocols. J Comput Assist Tomogr 2005; 29: 59-63. (Pubitemid 40194439)
31. Michaely HJ, Sourbron SP, Buettner C, Lodemann KP, Reiser MF, Schoenberg SO,. Temporal constraints in renal perfusion imaging with a 2-compartment model. Invest Radiol 2008; 43: 120-128.
32. Leach MO, Brindle KM, Evelhoch JL, et al. The assessment of antiangiogenic and antivascular therapies in early-stage clinical trials using magnetic resonance imaging: issues and recommendations. Br J Cancer 2005; 92: 1599-1610. (Pubitemid 40756468)
33. Haacke EM, Filleti CL, Gattu R, et al. New algorithm for quantifying vascular changes in dynamic contrast-enhanced MRI independent of absolute T1 values. Magn Reson Med 2007; 58: 463-472. (Pubitemid 350154956)
34. Luypaert R, Sourbron S, de Mey J,. Validity of perfusion parameters obtained using the modified Tofts model: a simulation study. Magn Reson Med 2011; 65: 1491-1497.
35. Donaldson SB, West CM, Davidson SE, et al. A comparison of tracer kinetic models for T1-weighted dynamic contrast-enhanced MRI: application in carcinoma of the cervix. Magn Reson Med 2010; 63: 691-700.
36. Bjornerud A, Sorensen AG, Mouridsen K, Emblem KE,. T(1)- and T(2)(*)-dominant extravasation correction in DSC-MRI: part I-theoretical considerations and implications for assessment of tumor hemodynamic properties. J Cereb Blood Flow Metab 2011; 31: 2041-2053.
37. St Lawrence KS, Lee TY,. An adiabatic approximation to the tissue homogeneity model for water exchange in the brain: II. Experimental validation. J Cereb Blood Flow Metab 1998; 18: 1378-1385. (Pubitemid 28559685)