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1000
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Abstract/Summary
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<jats:title>Abstract</jats:title><jats:sec>
<jats:title>Objective</jats:title>
<jats:p>With modern optimization methods, free optimization of parallel transmit pulses together with their gradient waveforms can be performed on-line within a short time. A toolbox which uses PyTorch’s autodifferentiation for simultaneous optimization of RF and gradient waveforms is presented and its performance is evaluated.</jats:p>
</jats:sec><jats:sec>
<jats:title>Methods</jats:title>
<jats:p>MR measurements were performed on a 9.4T MRI scanner using a 3D saturated single-shot turboFlash sequence for <jats:inline-formula><jats:alternatives><jats:tex-math>$$B_1^+$$</jats:tex-math><mml:math xmlns:mml='http://www.w3.org/1998/Math/MathML'>
<mml:msubsup>
<mml:mi>B</mml:mi>
<mml:mn>1</mml:mn>
<mml:mo>+</mml:mo>
</mml:msubsup>
</mml:math></jats:alternatives></jats:inline-formula> mapping. RF pulse simulation and optimization were done using a Python toolbox and a dedicated server. An RF- and Gradient pulse design toolbox was developed, including a cost function to balance different metrics and respect hardware and regulatory limits. Pulse performance was evaluated in GRE and MPRAGE imaging. Pulses for non-selective and for slab-selective excitation were designed.</jats:p>
</jats:sec><jats:sec>
<jats:title>Results</jats:title>
<jats:p>Universal pulses for non-selective excitation reduced the flip angle error to an NRMSE of (12.3±1.7)% relative to the targeted flip angle in simulations, compared to (42.0±1.4)% in CP mode. The tailored pulses performed best, resulting in a narrow flip angle distribution with NRMSE of (8.2±1.0)%. The tailored pulses could be created in only 66 s, making it feasible to design them during an experiment. A 90° pulse was designed as preparation pulse for a satTFL sequence and achieved a NRMSE of 7.1%. We showed that both MPRAGE and GRE imaging benefited from the pTx pulses created with our toolbox.</jats:p>
</jats:sec><jats:sec>
<jats:title>Conclusion</jats:title>
<jats:p>The pTx pulse design toolbox can freely optimize gradient and pTx RF waveforms in a short time. This allows for tailoring high-quality pulses in just over a minute.</jats:p>
</jats:sec>
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1000
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Hinweis
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DeepGreen-ID: 59d74fc3901645e39ae77cf67475bccd ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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