Treatment outcome prediction for lung volume reduction procedures

• US 9,504,529 B2
• Filed: 02/24/2014
• Issued: 11/29/2016
• Est. Priority Date: 02/24/2014
• Status: Active Grant

• Current Assignee: VIDA Diagnostics, Inc.
• Original Assignee: VIDA Diagnostics, Inc.
• Inventors: Raffy, Philippe, Yin, Youbing
• Primary Examiner(s): Cattungal, Sanjay
• Application Number:
  US14/188,005
• Publication Number:
  US 20150238270A1
• Time in Patent Office: 1,009 Days
• Field of Search: 600473-480, 382128-132
• US Class Current: 1/1
• CPC Class Codes: A61B 17/00234 for minimally invasive surgery A61B17/0218, A61B17/0469, A61B17/12013, A61B17/1285, A61B17/29, A61B17/320016 take precedence
• CPC Class Codes: A61B 2017/00809 Lung operations
• CPC Class Codes: A61B 2034/104 Modelling the effect of the tool, e.g. the effect of an implanted prosthesis or for predicting the effect of ablation or burring
• CPC Class Codes: A61B 2034/105 Modelling of the patient, e.g. for ligaments or bones
• CPC Class Codes: A61B 34/10 Computer-aided planning, simulation or modelling of surgical operations
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 6/5217 extracting a diagnostic or physiological parameter from medical diagnostic data
• CPC Class Codes: A61B 90/37 Surgical systems with images on a monitor during operation
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G16H 20/40 relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Systems and methods for displaying a predicted outcome of a lung volume reduction procedure for a patient including a user interface, a processor, and programing operable on the processor for displaying a predicted outcome of the bronchoscopic lung volume reduction procedure on the user interface, wherein displaying the predicted outcome of the lung volume reduction procedure includes receiving patient data comprising volumetric images of the patient, analyzing the volumetric images to identify one or more features correlated to treatment outcome prediction, predicting an outcome for a treatment modality or treatment device using the one or more identified features, and displaying the predicted outcome on the user interface.

Claims

1. A system for displaying a predicted outcome of a lung volume reduction procedure for a patient comprising:

a user interface;

a processor;

programing operable on the processor for displaying a predicted outcome of the bronchoscopic lung volume reduction procedure on the user interface;

wherein displaying the predicted outcome of the lung volume reduction procedure comprises;

receiving patient data comprising volumetric images of the patient;

analyzing the volumetric images to identify one or more features correlated to treatment outcome prediction;

predicting an outcome for a treatment modality or treatment device using the one or more identified features; and

displaying the predicted outcome on the user interface.

2. The system of claim 1 further comprising receiving a selected treatment location within the airway tree from a user and predicting an outcome for a treatment modality or treatment device at the selected location using the one or more identified features.

3. The system of claim 1 wherein displaying the predicted outcome of the lung volume reduction procedure further comprises receiving a selected treatment modality from the user, and wherein predicting an outcome for a treatment modality comprises predicting an outcome for the treatment modality selected by the user.

4. The system of claim 1 wherein predicting an outcome for a treatment modality comprises predicting a plurality of outcomes for a plurality of treatment modalities, and wherein displaying the predicted outcome on the user interface comprises displaying the plurality of treatment outcomes for the plurality of treatment modalities on the user interface.

5. The system of claim 1 further comprising programming operable on the processor for analyzing the volumetric images to identify lobes, sublobes and an airway tree of the lungs and displaying a three dimensional model of the patient'"'"'s lungs on the display.

6. The system of claim 1 wherein the predicted outcome comprises a numerical value representing a probability of success.

7. The system of claim 6 wherein success comprises a lung volume reduction greater than a threshold value.

8. The system of claim 1 wherein the predicted outcome comprises a numerical value representing a probability of pneumothorax.

9. The system of claim 1 wherein the predicted outcome comprises a first numerical value representing a probability of lung volume reduction greater than a threshold value and a second numerical value representing a probability of pneumothorax.

10. The system of claim 1 wherein the one or more features includes a feature corresponding to fissure integrity.

11. The system of claim 1 wherein analyzing the volumetric images to identify one or more features correlated to treatment outcome prediction comprises measuring low attenuation clusters.

12. The system of claim 1 wherein analyzing the volumetric images to identify one or more features correlated to treatment outcome prediction comprises measuring peripheral vessel volume.

13. A system for displaying an outcome of a lung volume reduction procedure for a patient comprising:

a user interface;

a processor;

programming operable on the processor for displaying a predicted outcome of the bronchoscopic lung volume reduction procedure on a user interface;

wherein displaying the predicted outcome of the lung volume reduction procedure comprises;

receiving patient data comprising volumetric images of the patient;

analyzing the volumetric images to identify lobes and airway tree of the lungs;

analyzing the volumetric images to identify one or more features correlated to treatment outcome prediction;

displaying a three dimensional model of the patient'"'"'s lungs;

receiving a selected treatment location within the airway tree from a user;

predicting an outcome for a treatment modality or treatment device at the selected location using the one or more identified features; and

displaying the predicted outcome on the user interface.

14. The system of claim 13 wherein displaying the predicted outcome of the lung volume reduction procedure further comprises receiving a selected treatment modality or treatment device from the user, and wherein predicting an outcome for a treatment modality comprises predicting an outcome for the treatment modality or treatment device selected by the user.

15. The system of claim 13 wherein predicting an outcome for a treatment modality or treatment device comprises predicting a plurality of outcomes for a plurality of treatment modalities or treatment devices, and wherein displaying the predicted outcome on the user interface comprises displaying the plurality of treatment outcomes for the plurality of treatment modalities on the user interface.

16. The system of claim 13 wherein the predicted outcome comprises a numerical value representing a probability.

17. The system of claim 16 wherein the predicted outcome comprises a probability of success.

18. The system of claim 13 wherein predicting an outcome for the selected treatment modality using one or more identified features comprises comparing the one or more features identified in the patient lungs to a database to predict an outcome of treatment at the selected location with the selected treatment modality.

19. The system of claim 18 wherein the database comprises a set of outcomes for lung volume reduction procedures for a group of individuals using the selected treatment modality and further comprises a set of volumetric images or one or more features identified in the volumetric images for the group of individuals, wherein the identified features in the volumetric images of the group of individuals are the same features as the identified features in the volumetric images of the patient.

20. The system of claim 13 wherein displaying the predicted outcome of the lung volume reduction procedure further comprises displaying a probability of a successful treatment outcome and a probability of an adverse event for a plurality of lung volume reduction treatment modalities and receiving a selection of a treatment modality from a user.

21. A method of planning a lung volume reduction procedure for a patient using a treatment planning and outcome system, the system comprising a processor and a user interface, the method comprising:

observing a three dimensional model of the patient'"'"'s lungs on the user interface generated by the processor using patient data comprising volumetric images;

selecting a treatment modality;

selecting a treatment location;

observing a predicted outcome on the user interface, wherein the predicted outcome is generated by the using outcome predictors determined using the patient data.

22. The method of claim 21 wherein the method further comprises observing a predicted outcome for a plurality of treatment modalities generated by the processor and displayed on the user interface prior to selecting a treatment modality.

23. A system for selecting patients for lung cancer screening comprising:

a user interface;

a processor;

programing operable on the processor for displaying a lung cancer risk or a recommendation for lung cancer screening;

wherein displaying the lung cancer risk or the recommendation for lung cancer screening comprises;

receiving patient data comprising volumetric images of the patient;

analyzing the volumetric images to identify one or more features correlated to lung cancer;

predicting a likelihood of lung cancer using the one or more identified features; and

displaying the predicted likelihood of lung cancer on the user interface or displaying the recommendation for lung cancer screening, wherein the recommendation for lung cancer screening is determined by the system using the predicted likelihood of lung cancer.