Gradient Slew Rate
Measure signed piecewise-linear gradient slew from timestamped mT/m samples; mT/m per ms equals T/m/s and between-sample excursions are not observable.
Description
Gradient slew is the rate of change of gradient strength.
Gradient slew is the rate of change of gradient strength. With mT/m and ms, the numerical quotient equals T/m/s.
The tool returns intervalSlewTeslaPerMeterSecond (interval slew tesla per meter second); maximumAbsoluteSlew (maximum absolute slew). Input measurements and model parameters are supplied by the caller; the tool computes the stated summary rather than acquiring those measurements.
When to use Gradient Slew Rate
Use Gradient Slew Rate when you already have timesMs, gradientMilliTeslaPerMeter and want intervalSlewTeslaPerMeterSecond, maximumAbsoluteSlew. This is useful for checking a supplied calculation, documenting a measurement convention, or comparing observations prepared on the same basis.
How to use Gradient Slew Rate and understand its results
- Enter timesMs, gradientMilliTeslaPerMeter using the field table below. Match the units, ordering and data boundaries described in the calculation.
- Run the tool after checking the stated bounds and matching paired observations or categories. A malformed request gives a tool error rather than a usable measurement.
- Read intervalSlewTeslaPerMeterSecond, maximumAbsoluteSlew. Use the calculation and interpretation below to distinguish amounts, ratios, signs and decision flags where applicable.
- Review the supplied parameters and assumptions before using the result in a report or comparing it with another observation.
| Input field | Meaning | Value type and bounds | Requirement |
|---|---|---|---|
| timesMs | Times ms | list of number | Required |
| gradientMilliTeslaPerMeter | Gradient milli tesla per meter | list of number | Required |
Use aligned gradients and strictly increasing times. Return signed interval averages and their maximum absolute value.
slew[i] = (G[i+1]−G[i])/(timeMs[i+1]−timeMs[i]) The symbols refer to the supplied quantities or generated values described above; unit conversions and comparison boundaries follow the stated implementation.
{
"input": {
"timesMs": [
0,
1,
3
],
"gradientMilliTeslaPerMeter": [
0,
10,
-10
]
},
"output": {
"intervalSlewTeslaPerMeterSecond": [
10,
-10
],
"maximumAbsoluteSlew": 10
}
}Limitations and assumptions
Finite differences do not measure unresolved ramp peaks. No hardware-limit or peripheral-stimulation compliance is assessed.
Numerical inputs must be finite. The tool checks its declared input shape and calculation constraints; those checks do not verify the quality, calibration or representativeness of the supplied observations.
Alternative or Complementary methods
Peripheral Nerve Stimulation Threshold: Screen a supplied gradient ramp against an externally calibrated strength-duration model; coil geometry, body coupling and multi-axis effects are not modeled, so this is not a patient safety determination. Cartesian K-Space Trajectory: Integrate two-axis piecewise-linear gradients by trapezoids into Cartesian k-space from a zero origin; refocusing sign changes must already be applied to supplied gradients.
Methodological background: RAD229: MRI signal and sequence lecture notes.1
References
-
RAD229: MRI signal and sequence lecture notes — Brian Hargreaves and colleagues, Stanford University
Similar or alternative tools
- Peripheral Nerve Stimulation Threshold
Screen a supplied gradient ramp against an externally calibrated strength-duration model; coil geometry, body coupling and multi-axis effects are not modeled, so this is not a patient safety determination.
- Cartesian K-Space Trajectory
Integrate two-axis piecewise-linear gradients by trapezoids into Cartesian k-space from a zero origin; refocusing sign changes must already be applied to supplied gradients.