METHOD FOR DETERMINING TREATMENTS USING PATIENT-SPECIFIC LUNG MODELS AND COMPUTER METHODS

• US 20120072193A1
• Filed: 05/27/2010
• Published: 03/22/2012
• Est. Priority Date: 05/29/2009
• Status: Active Grant

• Current Assignee: Fluidda Respi
• Original Assignee: Fluidda Respi
• Inventors: De Backer, Jan
• Granted Patent: US 8,886,500 B2
• Time in Patent Office: Days
• US Class Current: 703/2
• CPC Class Codes: A61B 5/085 Measuring impedance of respiratory organs or lung elasticity
• CPC Class Codes: A61M 16/00 Devices for influencing the respiratory system of patients by gas treatment, e.g. mouth-to-mouth respiration; Tracheal tubes stimulating the respiratory movement by mechanical, pneumatic or electrical means, iron lungs combined with gas breathing means A61H31/00
• CPC Class Codes: A61M 16/021 operated by electrical means A61M16/202 – A61M16/205 take precedence
• CPC Class Codes: A61M 2210/1039 Lungs
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

The present invention concerns a method for determining optimised parameters for mechanical ventilation, MV, of a subject, comprising: a) obtaining data concerning a three-dimensional image of the subject'"'"'s respiratory system; b) calculating a specific three-dimensional structural model of the subject'"'"'s lung structure from the image data obtained in step a); c) calculating a specific three-dimensional structural model of the subject'"'"'s airway structure from the image data obtained in step a); d) calculating a patient-specific three-dimensional structural model of the subject'"'"'s lobar structure from the lung model obtained in step b); e) modeling by a computer, the air flow through the airway, using the models of the airway and lobar structure of the subject obtained in steps c) and d) at defined MV parameters; f) modeling by a computer, the structural behavior of the airway and the interaction with the flow, using the models of the airway and lobar structure of the subject obtained in steps b) and c) at defined MV parameters; g) determining the MV parameters which lead to a decrease in airway resistance and hence an increase in lobar mass flow for the same driving pressures according to the model of step d), thereby obtaining optimized MV parameters. It also relates to a method for assessing the efficacy of a treatment for a respiratory condition.

Claims

1. A method for determining optimised parameters for mechanical ventilation, MV, of a subject, comprising:

a) obtaining data concerning a three-dimensional image of the subjects respiratory system,

b) calculating a specific three-dimensional structural model of the subject'"'"'s lung structure from the image data obtained in step a),

c) calculating a specific three-dimensional structural model of the subject'"'"'s airway structure from the image data obtained in step a),

d) calculating a patient-specific three-dimensional structural model of the subject'"'"'s lobar structure from the lung model obtained in step b),

e) modeling by a computer, the air flow through the airway, using the models of the airway and lobar structure of the subject obtained in steps c) and d) at defined MV parameters;

f) modeling by a computer, the structural behavior of the airway and the interaction with the flow, using the models of the airway and lobar structure of the subject obtained in steps b) and c) at defined MV parameters, and

g) determining the MV parameters which lead to a decrease in airway resistance and hence an increase in lobar mass flow for the same driving pressures according to the model of step d), thereby obtaining optimized MV parameters.

2. Method according to claim 1, wherein the image data of step a) is CT or MRI scan data.

3. Method according to claim 1, wherein the structural model of step c) is calculated using segmentation principles.

4. Method according to claim 1, wherein the model of step d) is calculated using lobar segmentation.

5. Method according to claim 1, wherein the modeling of step e) comprises computational fluid dynamics incorporating solving the Navier-Stokes equations numerically.

6. Method according to claim 5, wherein the lobar structure determined in step d) is used to determine boundary conditions for computational fluid dynamics.

7. Method according to claim 6, wherein

the data of step a) concerns three dimensional images of the respiratory system at total lung capacity, TLC and at functional residual capacity, FRC,

model of the lung structure in step b) and model of the lobar structure in step d) are calculated both at TLC and FRC,

to determine mass flow rate towards each lobe and subsequently the boundary conditions for said computational fluid dynamics.

8. Method according to claim 1, wherein the modeling of step f) comprises Finite Element Analysis, FEA.

9. Computer program stored on a computer readable medium, configured to perform the method as defined in claim 1.

10. A method for assessing the efficacy of a treatment for a respiratory condition in a subject comprising the steps of:

a) obtaining data concerning a pre-treatment three-dimensional image of the subject'"'"'s respiratory system, and a post-treatment three-dimensional image of the subject'"'"'s respiratory system,

b) calculating a specific three-dimensional structural model of the subject'"'"'s lung structure from each of the pre- and post-treatment image data obtained in step a),

c) calculating a specific three-dimensional structural model of the subject'"'"'s airway structure from each of the pre- and post-treatment image data obtained in step a),

d) calculating a patient-specific three-dimensional structural model of the subject'"'"'s lobar structure from each of the pre- and post-treatment lung structure models obtained in step b),

e) modeling by a computer, the air flow through the airway at pre- and post-treatment states, using the respective pre- and post-treatment models of the airway and lobar structure of the subject obtained in steps c) and d);

f) modeling by a computer, the structural behavior of the airway and the interaction with the flow at pre- and post-treatment states, using the respective pre- and post-treatment models of the airway and lobar structure of the subject obtained in steps c) and d);

g) comparing the modeled airflow and structural behaviour pre- and post-treatment to determine the efficacy of a treatment, wherein an efficacious treatment is one that decreases the airway resistance, thereby increasing the lobar mass for the same driving pressure, thereby determining the efficacy of the treatment for the respiratory condition.

11. Method according to claim 10, wherein an increased efficacy is further defined by an increase in mass flow rate towards well-perfused areas.

12. Method according to claim 10, wherein the image data of step a) is CT or MRI scan data.

13. Computer readable medium comprising a computer program comprising instructions for performing a method according to claim 10.

14. Method according to claim 10, wherein the structural model of step c) is calculated using segmentation principles.

15. Method according to claim 10, wherein the model of step d) is calculated using lobar segmentation.

16. Method according to claim 10, wherein the modeling of step e) comprises computational fluid dynamics incorporating solving the Navier-Stokes equations numerically.

17. Method according to claim 16, wherein the lobar structure determined in step d) is used to determine boundary conditions for computational fluid dynamics.

18. Method according to claim 17, wherein

the data of step a) concerns three dimensional images of the respiratory system at total lung capacity, TLC and at functional residual capacity, FRC,

model of the lung structure in step b) and model of the lobar structure in step d) are calculated both at TLC and FRC,

to determine mass flow rate towards each lobe and subsequently the boundary conditions for said computational fluid dynamics.

19. Method according to claim 10, wherein the modeling of step f) comprises Finite Element Analysis, FEA.