Device, System, and Method for Imaging and Tissue Characterization of Ablated Tissue

• US 20140180273A1
• Filed: 12/20/2013
• Published: 06/26/2014
• Est. Priority Date: 12/21/2012
• Status: Active Grant

• Current Assignee: Volcano Corporation (Koninklijke Philips N.V.)
• Original Assignee: Volcano Corporation (Koninklijke Philips N.V.)
• Inventors: Nair, Anuja
• Granted Patent: US 9,615,878 B2
• Time in Patent Office: Days
• US Class Current: 606/34
• CPC Class Codes: A61B 18/1492 having a flexible, catheter-like structure, e.g. for heart ablation A61B18/1477 takes precedence
• CPC Class Codes: A61B 2018/00214 Expandable means emitting energy, e.g. by elements carried thereon
• CPC Class Codes: A61B 2018/00267 having a basket shaped structure
• CPC Class Codes: A61B 2018/00404 Blood vessels other than those in or around the heart
• CPC Class Codes: A61B 2018/00434 Neural system
• CPC Class Codes: A61B 2018/00511 Kidney
• CPC Class Codes: A61B 2018/00577 Ablation
• CPC Class Codes: A61B 2018/00684 using lookup tables
• CPC Class Codes: A61B 2018/1253 monopolar
• CPC Class Codes: A61B 2018/126 bipolar
• CPC Class Codes: A61B 2090/3735 Optical coherence tomography [OCT]
• CPC Class Codes: A61B 2090/3784 both receiver and transmitter being in the instrument or receiver being also transmitter
• CPC Class Codes: A61B 5/0075 by spectroscopy, i.e. measuring spectra, e.g. Raman spectroscopy, infrared absorption spectroscopy A61B5/0071 takes precedence
• CPC Class Codes: A61B 8/0891 for diagnosis of blood vessels
• CPC Class Codes: A61B 8/12 in body cavities or body tracts, e.g. by using catheters catheters per se A61M25/00
• CPC Class Codes: A61N 7/022 intracavitary

Abstract

Disclosed herein is a system for ablating and characterizing tissue. The system comprises an ablation element configured to emit ablative energy toward a tissue of interest, an imaging apparatus configured to emit energy and collect imaging data including reflected signals from the tissue of interest, and a characterization application. The characterization application comprises a signal analyzer for analyzing the imaging data and determining one or more signal properties from the reflected signals, and a correlation processor configured to associate the one or more signal properties to pre-determined tissue signal properties of different tissue components through a pattern recognition technique. The pre-determined tissue signal properties are embodied in a database, and the correlation processor is configured to identify a tissue component and an ablation level of the tissue of interest based on the pattern recognition technique.

Claims

1. A system for ablating and characterizing tissue, the system comprising:

an ablation element configured to emit ablative energy toward a tissue of interest;

an imaging apparatus configured to emit energy and collect imaging data including reflected signals from the tissue of interest; and

a characterization application comprising;

a signal analyzer for analyzing the imaging data and determining one or more signal properties from the reflected signals; and

a correlation processor configured to associate the one or more signal properties to pre-determined tissue signal properties of different tissue components through a pattern recognition technique wherein the pre-determined tissue signal properties are embodied in a database, the correlation processor further configured to identify a tissue component and an ablation level of the tissue of interest based on the pattern recognition technique.

2. The system of claim 1, wherein the imaging apparatus includes more than one imaging modality and the characterization application is configured to collect imaging data via more than one imaging modality.

3. The system of claim 2, wherein the signal analyzer is configured to analyze more than one type of imaging data to determine signal properties associated with each imaging modality, and the correlation processor is configured to identify the tissue component and the ablation level of the tissue of interest based on associating the signal properties to pre-determined tissue signal properties of different tissue components and different ablation levels for the different imaging modalities.

4. The system of claim 2, wherein the correlation processor is configured to recognize the type of imaging modality employed by the imaging apparatus and to use the corresponding pre-determined tissue signal properties to identify a tissue component of the object based on the pattern recognition technique.

5. The system of claim 1, wherein the pre-determined tissue signal properties are embodied in the database as a classification tree having branch node conditions based on the pre-determined tissue signal properties and one or more leaf nodes that identify the tissue component and the ablation level.

6. The system of claim 5, wherein the correlation processor is configured to traverse the classification tree to a leaf node based on the pattern recognition technique of comparing the one or more signal properties from the reflected signals to the branch node conditions.

7. The system of claim 1, wherein the pre-determined tissue signal properties are embodied in the database as an artificial neural network having one or more nodes that identify a tissue component.

8. The system of claim 1, wherein the pre-determined tissue signal properties are embodied in the database as a regression tree having branch node conditions based on the pre-determined tissue signal properties and one or more leaf nodes that identify a tissue component.

9. The system of claim 1, wherein the pattern recognition technique used by the correlation processor includes a random forest classifier.

10. The system of claim 1, further including secondary parameters embodied in the database, the secondary parameters each associated with particular pre-determined tissue signal properties, wherein the correlation processor uses the secondary parameters to more accurately associate the signal properties to the pre-determined tissue signal properties associated with the secondary parameters.

11. The system of claim 10, wherein the secondary parameters comprise at least one of the tissue type of the tissue of interest, the anatomic region of the tissue of interest, a frequency of energy employed by the imaging apparatus, and pre-existing health conditions of the patient.

12. The system of claim 1, further including border detection logic configured to determine borders of the tissue of interest from the reflected signals, wherein the signal analyzer logic selectively analyzes substantially only the imaging data within the borders.

13. The system of claim 1, further including diagnostic logic for generating an assessment as to the level of ablation based on the identified tissue components and the identified ablation levels of the tissue of interest, wherein the diagnostic logic is configured to generate a score indicative of the level of ablation.

14. An apparatus for intravascular neuromodulation and imaging, comprising:

an elongate, hollow body including a proximal portion and a distal portion, the distal portion including a distal tip, the body configured to have an unexpanded condition wherein the distal portion and the distal tip are in contact with each other, and an expanded condition wherein the distal portion and the distal tip are spaced apart from each other;

an expandable structure configured to have an expanded condition and an unexpanded condition, the expandable structure disposed in an unexpanded condition within the distal portion and proximal to the distal tip, the expandable structure including at least one support arm;

an imaging apparatus positioned on the body; and

at least one ablative element positioned on the at least one support arm of the expandable structure.

15. The apparatus of claim 14, further comprising a sensor positioned on the at least one support arm of the expandable structure.

16. The apparatus of claim 15, wherein the sensor comprises at least one of a temperature sensor and a chemical sensor.

17. The apparatus of claim 15, wherein the sensor is positioned adjacent to the at least one ablative element.

18. The apparatus of claim 14, wherein the imaging apparatus is positioned within the expandable structure on the body.

19. A method of ablating and characterizing one or more tissue components of a scanned object in a patient, the method comprising:

positioning a catheter including an ablative element and an imaging apparatus adjacent a region of interest of the scanned object;

directing ablative energy from an ablative element toward the region of interest;

receiving reflected signals from an imaging apparatus scanning the region of interest;

determining one or more signal properties of the region of interest from the reflected signals;

associating the one or more signal properties to pre-determined signal properties of tissue components of an object similar to the scanned object wherein the pre-determined signal properties comprise classification conditions stored in a data structure; and

identifying one or more tissue components and their corresponding levels of ablation based on the associating.

20. The method of claim 19, wherein the pre-determined signal properties comprise branch node conditions based on the pre-determined signal properties and one or more leaf nodes identifying a type of tissue component having a particular level of ablation.

21. The method of claim 19, wherein the reflected signals include a plurality of backscattered scan lines and the determining step includes determining signal properties for a plurality of segments from the plurality of scan lines.

22. The method of claim 19, wherein the receiving step includes collecting reflected signals by a plurality of imaging modalities.

23. The method of claim 19, wherein the receiving step includes collecting reflected signals from at least one of a carotid body, vascular plaque, and a nerve.

24. The method of claim 19, wherein associating the one or more signal properties to pre-determined signal properties of tissue components of an object similar to the scanned object includes selecting the pre-determined tissue properties based on secondary parameters associated with the object.