Object:A method is proposed for generating schemes of diffusion gradient orientations which allow the diffusion tensor to be reconstructed from partial data sets in clinical DT-MRI, should the acquisition be corrupted or terminated before completion because of patient motion.
Materials and methods: A general energy-minimization electrostatic model was developed in which the interactions between orientations are weighted according to their temporal order during acquisition. In this report, two corruption scenarios were specifically considered for generating relatively uniform schemes of 18 and 60 orientations, with useful subsets of 6 and 15 orientations. The sets and subsets were compared to conventional sets through their energy, condition number and rotational invariance. Schemes of 18 orientations were tested on a volunteer.
Results: The optimized sets were similar to uniform sets in terms of energy, condition number and rotational invariance, whether the complete set or only a subset was considered. Diffusion maps obtained in vivo were close to those for uniform sets whatever the acquisition time was. This was not the case with conventional schemes, whose subset uniformity was insufficient.
Conclusion: With the proposed approach, sets of orientations responding to several corruption scenarios can be generated, which is potentially useful for imaging uncooperative patients or infants.
Le Bihan D, Mangin JF, Poupon C, Clark CA, Pappata S, Molko N, Chabriat H (2001) Diffusion tensor imaging: concepts and applications. J Magn Reson Imag 13:534–546CrossRefGoogle Scholar
Basser PJ (1995) Inferring microstructural features and the physiological state of tissues from diffusion-weighted images. NMR Biomed 8:333–344PubMedCrossRefGoogle Scholar
Basser PJ, Mattiello J, Le Bihan D (1994) Estimation of the effective self-diffusion tensor from the NMR spin echo. J Magn Reson B 103:247–254PubMedCrossRefGoogle Scholar
Basser PJ, Mattiello J, Le Bihan D (1994) Diffusion tensor tensor spectroscopy and imaging. Biophys J 66:259–267PubMedCrossRefGoogle Scholar
Conturo TE, McKinstry RC, Akbudak E, Robinson BH (1996) Encoding of anisotropic diffusion with tetrahedral gradients: a general mathematical diffusion formalism and experimental results. Magn Reson Med 35:399–412PubMedGoogle Scholar
Basser PJ, Pierpaoli C (1998) A simplified method to measure the diffusion tensor from seven MR images. Magn Reson Med 39:928–934PubMedCrossRefGoogle Scholar
Papadakis NG, Xing D, Huang CL, Hall LD, Carpenter TA (1999) A comparative study of acquisition schemes for diffusion tensor imaging using MRI. J Magn Reson 137:67–82PubMedCrossRefGoogle Scholar
Papadakis NG, Xing D, Houston GC, Smith JM, Smith MI, James MF, Parsons AA, Huang CL, Hall LD, Carpenter TA (1999) A study of rotationally invariant and symmetric indices of diffusion anisotropy. Magn Reson Imag 17:881–892CrossRefGoogle Scholar
Jones DK, Horsfield MA, Simmons A (1999) Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging. Magn Reson Med 42:515–525PubMedCrossRefGoogle Scholar
Papadakis NG, Murrills CD, Hall LD, Huang CL, Carpenter TA (2000) Minimal gradient encoding for robust estimation of diffusion anisotropy. Magn Reson Imag 18:671–679CrossRefGoogle Scholar
Skare S, Hedehus M, Moseley ME, Li TQ (2000) Condition number as a measure of noise performance of diffusion tensor data acquisition schemes with MRI. J Magn Reson 147:340–352PubMedCrossRefGoogle Scholar
Hasan KM, Parker DL, Alexander AL (2001) Comparison of gradient encoding schemes for diffusion-tensor MRI. J Magn Reson Imag 13:769–780CrossRefGoogle Scholar
Batchelor PG, Atkinson D, Hill DL, Calamante F, Connelly A (2003) Anisotropic noise propagation in diffusion tensor MRI sampling schemes. Magn Reson Med 49:1143–1151PubMedCrossRefGoogle Scholar
Jones DK (2004) The effect of gradient sampling schemes on measures derived from diffusion tensor MRI: a Monte Carlo study. Magn Reson Med 51:807–815PubMedCrossRefGoogle Scholar
Akkerman EM (2003) Efficient measurement and calculation of MR diffusion anisotropy images using the Platonic variance method. Magn Reson Med 49:599–604PubMedCrossRefGoogle Scholar
Hasan KM, Narayana PA (2003) Computation of the fractional anisotropy and mean diffusivity maps without tensor decoding and diagonalization: theoretical analysis and validation. Magn Reson Med 50:589–598PubMedCrossRefGoogle Scholar
Madi S, Hasan KM, Narayana PA (2005) Diffusion tensor imaging of in vivo and excised rat spinal cord at 7 T with an icosahedral encoding scheme. Magn Reson Med 53:118–125PubMedCrossRefGoogle Scholar
Xing D, Papadakis NG, Huang CL, Lee VM, Carpenter TA, Hall LD (1997) Optimised diffusion-weighting for measurement of apparent diffusion coefficient (ADC) in human brain. Magn Reson Imag 15:771–784CrossRefGoogle Scholar
Dubois J, Poupon C, Cointepas Y, Lethimonnier F, Le Bihan D (2004) Diffusion gradient orientation schemes for DTI acquisitions with unquiet subjects. In: Proceedings of the 12th annual meeting of ISMRM, #443Google Scholar
Cook PA, Boulby PA, Symms MR, Alexander DC (2005) Optimal acquisition order of diffusion-weighted measurements on a sphere. In: Proceedings of the 13th annual meeting of ISMRM, #1303Google Scholar