Conductivity reconstruction based on inverse finite element measurements in a tissue monitoring system

• US 20030216630A1
• Filed: 08/23/2002
• Published: 11/20/2003
• Est. Priority Date: 01/25/2002
• Status: Active Grant

• Current Assignee: Inotech Medical Systems Incorporated
• Original Assignee: Inotech Medical Systems Incorporated
• Inventors: Jersey-Willuhn, Karen, Soleimani, Manuchehr
• Granted Patent: US 7,169,107 B2
• Time in Patent Office: Days
• US Class Current: 600/407
• CPC Class Codes: A61B 2562/0215 Silver or silver chloride containing
• CPC Class Codes: A61B 5/0536 Impedance imaging, e.g. by tomography
• CPC Class Codes: A61B 5/412 Detecting or monitoring sepsis
• CPC Class Codes: A61B 5/445 Evaluating skin irritation or skin trauma, e.g. rash, eczema, wound, bed sore
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61M 2205/52 with memories providing a history of measured variating parameters of apparatus or patient
• CPC Class Codes: A61M 5/16836 by sensing tissue properties at the infusion site, e.g. for detecting infiltration detecting tissue temperature for diagnostic purposes A61M39/0247

Abstract

An impedance model of tissue is useful for describing conductivity reconstruction in tissue. Techniques for determining and mapping conductivity distribution in tissue supply useful information of anatomical and physiological status in various medical applications. Electrical Impedance Tomography (EIT) techniques are highly suitable for analyzing conductivity distribution. Electrical characteristics of tissue include resistive elements and capacitive elements. EIT techniques involve passing a low frequency current through the body to monitor various anatomical and physiological characteristics. The system can interrogate at multiple frequencies to map impedance. Analytical techniques involve forward and inverse solutions to boundary value analysis to tissue characteristics.

Claims

1. An imaging apparatus comprising:

a control unit capable of coupling to a plurality of electrodes, the control unit capable of controlling the electrodes to sense one or more parameters indicative of tissue condition;

an interrogating process executable on the control unit that generates an interrogation signal for application to the electrodes;

a measuring process executable on the control unit that measures a response evoked by the interrogation signal; and

a pattern recognition process executable on the control unit that analyzes the response evoked by the interrogation signal and executes forward and inverse solutions to a boundary value analysis to determine tissue characteristics.

2. An imaging apparatus according to claim 1 wherein:

the interrogation signal is a current passed through one or more electrodes and the measuring process measures a voltage signal at one or more electrodes to determine impedance.

3. An imaging apparatus according to claim 1 wherein:

the interrogation signal is a voltage applied to one or more of the electrodes and the measuring process measures a current signal at one or more electrodes to determine impedance.

4. An imaging apparatus according to claim 1 wherein:

the pattern recognition process calculates a potential distribution of a domain given a known conductivity distribution and a known current source for the boundary conditions in a forward problem and measures a voltage for a known current injection pattern in an inverse problem.

5. An imaging apparatus according to claim 1 wherein:

the pattern recognition process uses a regularized Newton-Raphson method to optimize an ill-posed inverse problem for imaging and tissue mapping.

6. An imaging apparatus according to claim 1 further comprising:

an iterative process that combines a forward problem and an inverse problem, iterations including;

estimating conductance and calculating voltage,

comparing the calculated voltage with a measured voltage,

adjusting conductivity and calculating a new estimated voltage, and

iterating until the calculated and measured voltages are within a specified criteria.

7. An imaging apparatus according to claim 1 wherein:

the pattern recognition process calculates a predicted voltage based on a finite element model using a known conductivity.

8. An imaging apparatus according to claim 1 further comprising:

a potentiometric sensor capable of testing electrolytes and selected ions by measuring a voltage gradient across a metabolic sample; and

a pattern recognition process that analyzes tissue based on the voltage gradients.

9. An imaging apparatus according to claim 1 further comprising:

means for determining an initial conductivity distribution;

means for solving a forward boundary value problem to determine a predicted voltage using a finite element model;

means for comparing the predicted voltage with voltages calculated from the finite element model;

means for repeating the forward boundary value problem and the comparison of predicted and calculated voltages until a predetermined criteria is met;

means for calculating the Jacobian; and

means for solving a full matrix inverse boundary value problem using information obtained from the forward problem;

10. An imaging apparatus according to claim 9 wherein:

the initial conductivity distribution is presumed to be zero.

11. An imaging apparatus according to claim 9 further comprising:

means for updating the conductivity using a regularized inverse of the Jacobian.

12. An imaging apparatus according to claim 9 further comprising:

means for calculating the Jacobian using a regularization matrix that penalized extreme changes in conductivity and corrects instability in reconstruction at a cost of producing artificially smooth images.

13. An imaging apparatus according to claim 9 wherein:

the inverse boundary value problem calculates a conductivity distribution given a current set of current injection patterns and a set of measured voltages.

14. An imaging apparatus according to claim 9 wherein:

the forward boundary value problem calculates voltages given a known current injection pattern and a measured conductivity distribution.

15. An imaging apparatus according to claim 1 wherein:

the imaging apparatus executes a multiple-frequency analysis.

16. An imaging method comprising:

determining an initial conductivity distribution;

solving a forward boundary value problem to determine a predicted voltage using a finite element model;

comparing the predicted voltage with voltages calculated from the finite element model;

repeating the forward boundary value problem and the comparison of predicted and calculated voltages until a predetermined criteria is met;

calculating the Jacobian; and

solving a full matrix inverse boundary value problem using information obtained from the forward problem;

17. An imaging method according to claim 16 further comprising:

calculating the Jacobian using a regularization matrix that penalized extreme changes in conductivity and corrects instability in reconstruction at a cost of producing artificially smooth images.

18. An imaging method according to claim 16 further comprising:

executing a multiple-frequency analysis.

19. An imaging apparatus comprising:

a control unit capable of coupling to one or more sensors, the control unit capable of controlling the sensors to sense one or more parameters indicative of tissue condition;

a measuring process executable on the control unit that measures a signal indicative of tissue condition from the one or more sensors; and

a pattern recognition process executable on the control unit that analyzes the measured signal and executes forward and inverse solutions to a boundary value analysis to determine tissue characteristics.

20. An imaging apparatus according to claim 19 further comprising:

a thermography sensor wherein the pattern recognition process forms an image based on tissue temperature signals.