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DOI 10.1007/s10334-016-0580-1

Медицинская библиотека · Magma (New York, N.Y.) · 2016

Application of the limited-memory quasi-Newton algorithm for multi-dimensional, large flip-angle RF pulses at 7T.

Vinding Mads S, Brenner Daniel, Tse Desmond H Y, Vellmer Sebastian, Vosegaard Thomas, Suter Dieter, Stöcker Tony, Maximov Ivan I

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Аннотация

OBJECTIVE

Ultrahigh field MRI provides great opportunities for medical diagnostics and research. However, ultrahigh field MRI also brings challenges, such as larger magnetic susceptibility induced field changes. Parallel-transmit radio-frequency pulses can ameliorate these complications while performing advanced tasks in routine applications. To address one class of such pulses, we propose an optimal-control algorithm as a tool for designing advanced multi-dimensional, large flip-angle, radio-frequency pulses. We contrast initial conditions, constraints, and field correction abilities against increasing pulse trajectory acceleration factors.

MATERIALS AND

METHODS

On an 8-channel 7T system, we demonstrate the quasi-Newton algorithm with pulse designs for reduced field-of-view imaging with an oil phantom and in vivo with scans of the human brain stem. We used echo-planar imaging with 2D spatial-selective pulses. Pulses are computed sufficiently rapid for routine applications.

RESULTS

Our dataset was quantitatively analyzed with the conventional mean-square-error metric and the structural-similarity index from image processing. Analysis of both full and reduced field-of-view scans benefit from utilizing both complementary measures.

CONCLUSION

We obtained excellent outer-volume suppression with our proposed method, thus enabling reduced field-of-view imaging using pulse trajectory acceleration factors up to 4.

Для цитирования: Vinding Mads S, Brenner Daniel, Tse Desmond H Y, Vellmer Sebastian, Vosegaard Thomas, Suter Dieter, Stöcker Tony, Maximov Ivan I. Application of the limited-memory quasi-Newton algorithm for multi-dimensional, large flip-angle RF pulses at 7T.. Magma (New York, N.Y.). 2016. DOI: 10.1007/s10334-016-0580-1.

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