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Magnetic resonance tissue quantification using optimal bSSFP pulse-sequence design

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Abstract

We propose a merit function for the expected contrast to noise ratio in tissue quantifications, and formulate a nonlinear, nonconvex semidefinite optimization problem to select locally-optimal balanced steady-state free precession (bSSFP) pulse-sequence design variables. The method could be applied to other pulse sequence types, arbitrary numbers of tissues, and numbers of images. To solve the problem we use a mixture of a grid search to get good starting points, and a sequential, semidefinite, trust-region method, where the subproblems contain only linear and semidefinite constraints. We give the results of numerical experiments for the case of three tissues and three, four or six images, in which we observe a better increase in contrast to noise than would be obtained by averaging the results of repeated experiments. As an illustration, we show how the pulse sequences designed numerically could be applied to the problem of quantifying intraluminal lipid deposits in the carotid artery.

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References

  • Albert A (1969) Conditions for positive and nonnegative definiteness in terms of pseudoinverses. SIAM J Appl Math 17:434–440

    Article  MathSciNet  Google Scholar 

  • Ben Tal A, Nemirovski A (2001) Lectures on modern convex optimization. Analysis, algorithms and engineering applications. MPS/SIAM Series on Optimization, vol 1. SIAM, Philadelphia

    MATH  Google Scholar 

  • Berstekas DP (1995) Nonlinear programming. Athena Scientific, USA

    Google Scholar 

  • Carr HY (1958) Steady-state free precession in nuclear magnetic resonance. Phys Rev 112:1693–1701

    Article  Google Scholar 

  • Conn AR, Goud NIM, Toint PL (2000) Trust region methods. MPS–SIAM series on optimization

  • Dixon WT (1984) Simple proton spectroscopic imaging. Radiology 153:189–194

    Google Scholar 

  • Freeman R, Hill HDW (1971) Phase and intensity anomalities in Fourier transform NMR. J Magn Reson 4:366–383

    Google Scholar 

  • Freund RW, Jarre F (2003) A sensitivity analysis and a convergence result for a sequential semidefinite programming method. In: Numerical analysis manuscript, No 03-4-09. Bell Laboratories, Murray Hill

    Google Scholar 

  • Glover G (1991) Multipoint Dixon technique for water and fat proton and susceptibility imaging. J Magn Reson Imaging 1:521–530

    Article  Google Scholar 

  • Haacke EM, Brown RW, Thompson MR, Venkatesan R (1999) Magnetic resonance imaging, physical principles and sequence design. Wiley–Liss, New York

    Google Scholar 

  • Hanicke W, Vogel HU (2003) An analytical solution for the SSFP signal in MRI. Magn Reson Med 49:771–775

    Article  Google Scholar 

  • Hargreaves BA, Vasanawala SS, Pauly JM, Nishimura DG (2001) Characterization and reduction of the transient response in steady-state MR imaging. Magn Reson Med 46:149–158

    Article  Google Scholar 

  • Hargreaves BA, Vasanawala SS, Nayak KS, Brittain JH, Hu BS, Nishimura DG (2003) Fat-suppressed steady-state free precession imaging using phase detection. Magn Reson Med 50:210–213

    Article  Google Scholar 

  • Horn RA, Johnson CR (1985) Matrix analysis. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  • Huang TY, Chung HW, Wang FN, Ko CW, Chen CY (2004) Fat and water separation in balanced steady-state free precession using the Dixon method. Magn Reson Med 51:243–247

    Article  Google Scholar 

  • Jardim SVB, Figueiredo MAT (2003) Automatic contour estimation in fetal ultrasound images. IEEE International Conference on Image Processing ICIP, Barcelona, Spain, (2), pp 1065–1068

  • Jaynes ET (1955) Matrix treatment of nuclear induction. Phys Rev 98(4):1099–1105

    Article  Google Scholar 

  • Kruk S, Wolkowicz H (1998) SQ2P, sequential quadratic constrained quadratic programming. In: Advances in nonlinear programming. Kluwer Academic, Dordrecht, pp 177–204

    Google Scholar 

  • Liang ZP, Lauterbur PC (1999) Principles of magnetic resonance imaging. IEEE Press Series in Biomedical Engineering

  • Mardia KV, Kent JT, Bibby JM (1979) Multivariate analysis. Academic, San Diego

    MATH  Google Scholar 

  • Oppelt A, Graumann R, BarfußH, Fischer H, Hartl W, Schajor W, (1986) FISP—a new fast MRI sequence. Electromedica (English edn) 54:15–18

    Google Scholar 

  • Reeder SB, Wen ZF, Yu HZ, Pineda AR, Gold GE, Markl M, Pelc NJ (2004) Multicoil Dixon chemical species separation with an iterative lest-squares estimation method. Magn Reson Med 51:35–45

    Article  Google Scholar 

  • Rybicki FJ, Mulkern RV, Robertson RL, Robson CD, Chung T, Ma J (2001) Fast three-point Dixon MR imaging of the retrobulbar space with low-resolution images for phase correction: comparison with fast spin-echo inversion recovery imaging. Am J Neuroradiol 22:179–1802

    Google Scholar 

  • Salibi N, Brown MA (1998) Clinical MR spectroscopy: first principles. Wiley–Liss, New York

    Google Scholar 

  • Scheffler K (1999) A pictorial description of steady states in fast magnetic resonance imaging. Concept Magn Res 11:291–304

    Article  Google Scholar 

  • Scheffler K (2003) On the transient phase of balanced SSFP sequences. Magn Reson Med 49:781–783

    Article  Google Scholar 

  • Sturm JF (1999) Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones. Optim Methods Software 11–12:625–653

    MathSciNet  Google Scholar 

  • Sturm JF (2002) Implementation of interior point methods for mixed semidefinite and second order cone optimization problems. Optim Methods Software 17(6):1105–1154

    Article  MATH  MathSciNet  Google Scholar 

  • Sutton BP, Noll DC, Fessler JA (2003) Fast, iterative image reconstruction for MRI in the presence of field inhomogeneities. IEEE Trans Med Imaging 22(2):178–188

    Article  Google Scholar 

  • Vasanawala SS, Pauly JM, Nishimura DG (2000) Linear combination steady-state free precession MRI. Magn Reson Med 43:82–90

    Article  Google Scholar 

  • Zur Y, Stokar S, Bendel P (1988) An analysis of fast imaging sequences with steady-state transverse magnetization refocusing. Magn Reson Med 6:175–193

    Article  Google Scholar 

Download references

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Correspondence to Christopher Kumar Anand.

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Anand, C.K., Sotirov, R., Terlaky, T. et al. Magnetic resonance tissue quantification using optimal bSSFP pulse-sequence design. Optim Eng 8, 215–238 (2007). https://doi.org/10.1007/s11081-007-9009-z

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  • DOI: https://doi.org/10.1007/s11081-007-9009-z

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