Systems and methods for estimating and removing magnetic resonance imaging gradient field-induced voltages from electrophysiology signals

Patent metadata

Field	Value
Publication number	US-2017181709-A1
Application number	US-201515325323-A
Country	US
Kind code	A1
Filing date	Jul 10, 2015
Priority date	Jul 11, 2014
Publication date	Jun 29, 2017
Grant date	—

Abstract

Systems and methods for estimating time-dependent voltages that are induced in electrophysiological monitoring systems by magnetic field gradients generated during a magnetic resonance imaging (“MRI”) scan are provided. The gradient-induced voltages are subsequently removed from signals acquired with the electrophysiological monitoring system during an MRI scan. As an example, the electrophysiological monitoring system can include an electrocardiography (“ECG”) system, an electroencephalography (“EEG”) system, an electromyography (“EMG”) system, a voltage device tracking (“VDT”) system, and so on. The gradient-induced voltages are estimated using a two-step procedure in which a learning algorithm is used to determine fitting parameters to be used in a model of the gradient-induced voltages. The fitting parameters are then used together with the model to extract the gradient- induced voltages from signals acquired during an MRI scan. The gradient-induced voltages can then be removed from the acquired signals.

First claim

1 . A method for correcting electrophysiology signals by removing voltages induced by magnetic field gradients generated by a magnetic resonance imaging (MRI) system, the steps of the method comprising:
(a) providing gradient waveforms; (b) computing derivatives of the provided gradient waveforms; (c) acquiring electrophysiology signals from a subject positioned in the MRI system while the MRI system is generating magnetic field gradients based on the provided gradient waveforms; (d) estimating fitting parameters for a physical model of gradient-induced voltages; (e) estimating voltages induced by the generated magnetic field gradients by fitting the provided gradient waveforms, the computed derivatives of the gradient waveforms, and the estimated fitting parameters to the physical model of gradient-induced voltages; and (f) removing the estimated gradient-induced voltages from the acquired electrophysiology signals.

2 . The method as recited in claim 1 , wherein step (d) includes estimating the fitting parameters by adaptively filtering the acquired electrophysiology signals.

3 . The method as recited in claim 1 , wherein step (d) includes estimating the fitting parameters by:
(i) providing an estimate of gradient-induced voltages associated with the provided gradient waveforms; and (ii) fitting the provided gradient waveforms, the computed derivatives of the gradient waveforms, and the estimate of the gradient-induced voltages to the physical model of the gradient-induced voltages.

4 . The method as recited in claim 3 , wherein providing the estimate of gradient-induced voltages includes:
(i) providing training electrophysiology signal data acquired from the subject while the MRI system is generating magnetic field gradients based on the provided gradient waveforms; (ii) providing template electrophysiology signal data acquired from the subject while the MRI system is not generating magnetic field gradients; and (iii) computing the estimate of gradient-induced voltages based on the provided training electrophysiology signal data and the provided template electrophysiology signal data.

5 . The method as recited in claim 4 , wherein computing the estimate of gradient-induced voltages includes subtracting the training electrophysiology signal data and the template electrophysiology signal data.

6 . The method as recited in claim 4 , wherein the provided template electrophysiology signal data is the electrophysiology signal data acquired in step (c).

7 . The method as recited in claim 1 , wherein the electrophysiology signals include at least one of electrocardiography (ECG) signals, intracardiac electrocardiogram (EGM) signals, electroencephalography (EEG) signals, electromyography (EMG) signals, voltage device tracking (VDT) signals, or a combination thereof.

8 . A system for correcting electrophysiology signals affected by magnetic field gradients generated by a magnetic resonance imaging (MRI) system, the system comprising:
an input configured to receive electrophysiology signals acquired from a subject positioned in an MRI system; at least one processor configured to:
i) to receive gradient waveforms from the input;
ii) compute derivatives of the received gradient waveforms;
iii) estimate fitting parameters for a physical model of gradient-induced voltages;
iv) estimate voltages induced by the generated magnetic field gradients by fitting the gradient waveforms, the computed derivatives of the gradient waveforms, and the estimated fitting parameters of the physical model of gradient-induced voltages;
v) remove the estimated gradient-induced voltages from the acquired electrophysiology signals to produce corrected electrophysiology signals; and
vi) generate a report using the corrected electrophysiology signals.

9 . The system as recited in claim 9 , wherein the at least one processor is further configured to estimate the fitting parameters by adaptively filtering the acquired electrophysiology signals.

10 . The system as recited in claim 9 , wherein the at least one processor is further configured to estimate the fitting parameters by:
a) providing an estimate of gradient-induced voltages associated with the provided gradient waveforms; and b) fitting the provided gradient waveforms, the computed derivatives of the gradient waveforms, and the estimate of the gradient-induced voltages to the physical model of the gradient-induced voltages.

11 . The system as recited in claim 10 , wherein the at least one processor is configured to provide the estimate of gradient-induced voltages by:
a) providing training electrophysiology signal data acquired from the subject while the MRI system is generating magnetic field gradients based on the provided gradient waveforms; b) providing template electrophysiology signal data acquired from the subject while the MRI system is not generating magnetic field gradients; and c) computing the estimate of gradient-induced voltages based on the provided training electrophysiology signal data and the provided template electrophysiology signal data.

12 . The system as recited in claim 11 , wherein computing the estimate of gradient-induced voltages includes subtracting the training electrophysiology signal data and the template electrophysiology signal data.

13 . The system as recited in claim 11 , wherein the at least one processor is further configured to direct acquisition of the electrophysiology signals from the subject to generate the training electrophysiology signal data, the template electrophysiology signal data, or both.

14 . The system as recited in claim 8 , wherein the electrophysiology signals include at least one of electrocardiography (ECG) signals, intracardiac electrocardiogram (EGM) signals, electroencephalography (EEG) signals, electromyography (EMG) signals, voltage device tracking (VDT) signals, or a combination thereof.

Assignees

• Brigham And Women'S Hospital Inc
• Univ Georgia

Inventors

• Wang Wei
• Zhang Hualei
• Schmidt Ehud J
• Tse Tsz Ho

Classifications

• A61B5/33

  specially adapted for cooperation with other devices · CPC title

• A61B5/055

  involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging · CPC title

• A61B5/0488

  Human Necessities · mapped topic

• A61B5/0402

  Human Necessities · mapped topic

• A61B5/7217 Primary

  of noise originating from a therapeutic or surgical apparatus, e.g. from a pacemaker · CPC title