  MRI systems are traditionally engineered to produce close to idealized
performance, enabling a simplified pulse sequence design philosophy. An example
of this is control of eddy currents produced by gradient fields; usually these
are compensated by pre-emphasizing demanded waveforms. This process typically
happens invisibly to the pulse designer, allowing them to assume the achieved
gradient waveform will be as desired. Whilst convenient, this imposes stricter
limits on the sequence design than the hardware can handle (for example,
pre-emphasis adds an additional overhead to amplifiers). This strategy can be
undesirable particularly for lower performance or resource-limited hardware.
Instead we explore the use of a 'digital twin' (i.e. an end-to-end model of the
scanner system) to optimize control inputs, resulting in sequences that
inherently compensate for known imperfections. We explore digital twin
optimization specifically for gradient system imperfections as an exemplar.
This is first explored in simulations using a simple exponential eddy current
model, then experimentally using an empirical gradient impulse response
function on a 7T MRI system. When unconstrained, digital twin optimization
reproduces classic pre-emphasis. When strict hardware constraints are imposed
(simulating lower performance hardware), it identifies novel sequences for
scenarios where classic pre-emphasis would be unachievable. Experimentally, the
optimization approach was demonstrated to substantially reduce ghosting effects
in echo planar images on a 7T system. Digital twin optimization may allow more
efficient use of hardware by taking a whole system approach. Ultimately this
could enable the use of cheaper hardware without loss of performance.
