HYBRID SPECTROSCOPY IMAGING SYSTEM FOR INTRAOPERATIVE EPILEPTIC CORTEX DETECTION

• US 20170340212A1
• Filed: 05/27/2016
• Published: 11/30/2017
• Est. Priority Date: 05/27/2016
• Status: Active Grant

• Current Assignee: The Florida International University Board of Trustees (State University System of Florida)
• Original Assignee: The Florida International University Board of Trustees (State University System of Florida)
• Inventors: Lin, Wei-Chiang, Song, Yinchen
• Granted Patent: US 10,580,129 B2
• Time in Patent Office: Days
• CPC Class Codes: A61B 5/0042 for the brain
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/14553 specially adapted for cerebral tissue
• CPC Class Codes: A61B 5/725 using specific filters therefor, e.g. Kalman or adaptive filters A61B5/316 take precedence
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• 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 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: G06T 2207/30016 Brain
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06V 10/143 Sensing or illuminating at different wavelengths
• CPC Class Codes: G06V 2201/031 of internal organs
• 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 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Methods and systems that detect and differentiate epileptogenic from eloquent and normal cortices are provided. A method for identifying epileptogenic cortices in a brain may include detecting areas in the brain that are undergoing cerebral blood volume low frequency oscillations, detecting areas in the brain that are undergoing blood oxygenation low frequency oscillations; mapping clusters of the brain in which the cerebral blood volume low frequency oscillations are negatively correlated with the blood oxygenation low frequency oscillations, and analyzing the time based relationship between the clusters of the brain that are undergoing negatively correlated low frequency oscillations to determine cause areas, which are areas of the brain that are causing negatively correlated low frequency oscillations to occur elsewhere.

Claims

1. A method for identifying epileptogenic cortices in a brain, surgical planning, and epileptogenic resection, the method comprising:

detecting areas in the brain that are undergoing cerebral blood volume low frequency oscillations;

detecting areas in the brain that are undergoing blood oxygenation low frequency oscillations;

mapping clusters of the brain in which the cerebral blood volume low frequency oscillations are negatively correlated with the blood oxygenation low frequency oscillations; and

analyzing a time based relationship between the clusters of the brain that are undergoing negatively correlated low frequency oscillations to determine cause areas, which are areas of the brain that are causing negatively correlated low frequency oscillations to occur elsewhere.

2. The method according to claim 1, further comprising:

identifying the cause areas as potential epileptogenic cortex and using the identified cause areas for surgical planning or guiding epileptogenic resection intraoperatively.

3. The method according to claim 2, wherein the detecting of areas in the brain that are undergoing cerebral blood volume low frequency oscillations and the detecting of areas in the brain that are undergoing blood oxygenation low frequency oscillations is accomplished by capturing images of a surface of the brain within a wavelength range of from about 300 nm to about 800 nm.

4. The method according to claim 3, wherein the detecting of areas in the brain that are undergoing cerebral blood volume low frequency oscillations is accomplished by analyzing images within a wavelength range of from about 400 nm to about 595 nm, and wherein the detecting of areas in the brain that are undergoing blood oxygenation low frequency oscillations is accomplished by analyzing images having a wavelength range of from about 640 to about 750 nm.

5. The method according to claim 2, wherein the detecting of areas in the brain that are undergoing cerebral blood volume low frequency oscillations and the detecting of areas in the brain that are undergoing blood oxygenation low frequency oscillations is accomplished by capturing images of a surface of the brain with a wavelength band that is indicative of cerebral blood volume and capturing images of the surface of the brain with a wavelength band that is indicative of blood oxygenation.

6. The method according to claim 5, wherein the capturing images of the surface of the brain with the wavelength band that is indicative of cerebral blood volume and the capturing images of the surface of the brain with the wavelength band that is indicative of blood oxygenation includes using a dichroic mirror.

7. The method according to claim 6, wherein the capturing images of the surface of the brain with the wavelength band that is indicative of cerebral blood volume and the capturing images of the surface of the brain with the wavelength band that is indicative of blood oxygenation is accomplished using bandpass filters in addition to the dichroic mirror.

8. The method according to claim 2, wherein the method is performed on a patient having focal epilepsy.

9. The method according to claim 2, wherein the detecting of areas in the brain that are undergoing cerebral blood volume low frequency oscillations and the detecting of areas in the brain that are undergoing blood oxygenation low frequency oscillations is accomplished using a non-invasive imaging modality.

10. The method according to claim 9, wherein the non-invasive imaging modality is functional magnetic resonance imaging.

11. The method according to claim 2, wherein hardware, software, or a combination of hardware and software is used to separate a wavelength band that is indicative of hemoglobin oxygenation from a wavelength band that is indicative of cerebral blood volume.

12. The method according to claim 5, further comprising co-registering, cropping, and smoothing the images.

13. The method according to claim 2, wherein the low frequency oscillations are in a range of from about 0.02 Hz to about 0.1 Hz

14. A system for identifying epileptogenic cortices in a brain, the system comprising:

a means for identifying areas in the brain that are exhibiting cerebral blood volume low frequency oscillations;

a means for identifying areas in the brain that are exhibiting blood oxygenation low frequency oscillations;

a means for identifying clusters of the brain that are exhibiting a negative correlation (negatively correlated areas) between the cerebral blood volume low frequency oscillations and the blood oxygenation low frequency oscillations; and

a means for identifying one or more cause areas, wherein the cause areas are negatively correlated areas that propagate or cause negatively correlated low frequency oscillations to occur in other areas of the brain.

15. The system according to claim 14, wherein the means for identifying areas in the brain that are exhibiting cerebral blood volume low frequency oscillations and the means for identifying areas in the brain that are exhibiting blood oxygenation low frequency oscillations includes a non-invasive imaging modality.

16. The system according to claim 15, wherein the non-invasive imaging modality is functional magnetic resonance imaging.

17. The system according to claim 14 wherein the means for identifying areas in the brain that are exhibiting cerebral blood volume low frequency oscillations and the means for identifying areas in the brain that are exhibiting blood oxygenation low frequency oscillations each include at least one of:

one or more image recording devices suitable for capturing images of a surface of the brain over time;

one or more processors suitable for separating the images into a wavelength band that is indicative of hemoglobin oxygenation and a wavelength band that is indicative of cerebral blood volume concentration; and

one or more processors suitable for identifying low frequency oscillations within the hemoglobin oxygenation indicative wavelength band and suitable for identifying low frequency oscillations within the cerebral blood volume indicative wavelength band.

18. The system according to claim 14, wherein the means for identifying clusters in the brain that are exhibiting cerebral blood volume low frequency oscillations and blood oxygenation low frequency oscillations includes:

a dichroic mirror suitable for separating a wavelength band that is indicative of hemoglobin oxygenation and a wavelength band that is indicative of cerebral blood volume concentration; and

a first image recording device positioned to capture wavelengths transmitted through the dichroic mirror and a second image recording device positioned to capture wavelengths that are reflected by the dichroic mirror.

19. The system according to claim 18, wherein the dichroic mirror has a transmission wavelength range of from about 400 nm to 595 nm and a reflection wavelength range of from about 640 nm to 750 nm.

20. The system according to claim 19, wherein the means for identifying areas in the brain that are exhibiting cerebral blood volume low frequency oscillations and the means for identifying areas in the brain that are exhibiting blood oxygenation low frequency oscillations further includes:

a first bandpass filter that is approximately a 500 nm bandpass filter; and

a second bandpass filter that is approximately a 700 nm bandpass filter, and

wherein each of the first bandpass filter and the second bandpass filter is positioned between the dichroic mirror and its respective image recording device.