Method, system and apparatus for automatically evaluating resection accuracy

• US 10,026,174 B2
• Filed: 01/07/2015
• Issued: 07/17/2018
• Est. Priority Date: 01/07/2015
• Status: Active Grant

• Current Assignee: Synaptive Medical (Barbados) Inc.
• Original Assignee: Synaptive Medical (Barbados) Inc.
• Inventors: Piron, Cameron Anthony, Panther, Alex
• Primary Examiner(s): Bayat, Ali
• Application Number:
  US15/535,227
• Publication Number:
  US 20170358083A1
• Time in Patent Office: 1,287 Days
• CPC Class Codes: A61B 2034/2051 Electromagnetic tracking systems
• CPC Class Codes: A61B 2034/2055 Optical tracking systems
• CPC Class Codes: A61B 2090/365 augmented reality, i.e. correlating a live optical image with another image
• CPC Class Codes: A61B 2090/374 NMR or MRI
• CPC Class Codes: A61B 2090/3979 infrared
• CPC Class Codes: A61B 2576/026 for the brain
• CPC Class Codes: A61B 34/20 Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis
• CPC Class Codes: A61B 34/30 Surgical robots
• CPC Class Codes: A61B 90/361 Image-producing devices, e.g. surgical cameras
• CPC Class Codes: G06T 2207/10088 Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/30016 Brain
• CPC Class Codes: G06T 2207/30096 Tumor; Lesion
• CPC Class Codes: G06T 7/0016 involving temporal comparison
• 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

Abstract

A method of automatically evaluating resection accuracy, is provided. The method includes preoperatively obtaining a first image of a volume of patient tissue using an imaging modality configured according to a scanning parameter, and storing the scanning parameter. An identifier of a target region corresponding to a target portion of the volume is received and stored in association with the first image. A second image is obtained of a resected tissue sample from the volume, using the imaging modality configured according to the scanning parameter. Based on a comparison of the first image and the second image, a determination is made whether the entire target region is represented in the second image. The method includes controlling an output device to present an indication, based on the determination, of whether the tissue sample contains the entire target portion.

Claims

1. A method of automatically evaluating resection accuracy, comprising:

preoperatively obtaining a first image of a volume of patient tissue using an imaging modality configured according to a scanning parameter, wherein obtaining the first image comprises sending an instruction including the scanning parameter to a first imaging device, and wherein the first imaging device is a first MRI scanner;

the scanning parameter defining a first imaging protocol implemented with the first imaging modality to acquire the first image;

storing the scanning parameter in a memory;

receiving and storing, in association with the first image, an identifier of a target region corresponding to a target portion of the volume;

responsive to resection of a tissue sample from the volume, obtaining a second image of the tissue sample using the imaging modality configured according to the scanning parameter for implementing the first imaging protocol to acquire the second image, wherein obtaining the second image comprises sending an instruction including the scanning parameter to a second imaging device, and wherein the second imaging device is a second MRI scanner;

determining, based on a comparison of the first image and the second image, whether the entire target region is represented in the second image; and

controlling an output device to present an indication, based on the determination, of whether the tissue sample contains the entire target portion.

2. The method of claim 1, wherein the determining includes registering the second image to the first image.

3. The method of claim 1, wherein the second image is obtained intraoperatively.

4. The method of claim 1, wherein the second image is obtained postoperatively.

5. The method of claim 1, wherein the target portion is a tumor.

6. The method of claim 1, further comprising:

receiving, from a tracking system, a plurality of locations of a surgical instrument within the volume of patient tissue;

computing a tracked portion of the volume encompassed by the locations;

assessing whether the target portion is contained within the tracked portion; and

controlling the output device to present the indication based on the determining and the assessing.

7. A computing device for automatically evaluating resection accuracy;

comprising;

a memory;

an output device; and

a processor interconnected with the memory and the output device, the processor configured to;

preoperatively obtain a first image of a volume of patient tissue using an imaging modality configured according to a scanning parameter, by sending an instruction including the scanning parameter to a first imaging device, wherein the first imaging device is a first MRI scanner;

the scanning parameter defining a first imaging protocol implemented with the first imaging modality to acquire the first image;

store the scanning parameter in the memory;

receive and store, in association with the first image, an identifier of a target region corresponding to a target portion of the volume;

responsive to resection of a tissue sample from the volume, obtain a second image of the tissue sample using the imaging modality configured according to the scanning parameter for implementing the first imaging protocol to acquire the second image, by sending an instruction including the scanning parameter to a second imaging device, wherein the second imaging device is a second MRI scanner;

determine, based on a comparison of the first image and the second image, whether the entire target region is represented in the second image; and

control the output device to present an indication, based on the determination, of whether the tissue sample contains the entire target portion.

8. The computing device of claim 7, the processor further configured to determine whether the entire target region is represented in the second image by registering the second image to the first image.

9. The computing device of claim 7, the processor further configured to obtain the second image intraoperatively.

10. The computing device of claim 7, the processor further configured to obtain the second image postoperatively.

11. The computing device of claim 7, wherein the target portion is a tumor.

12. The computing device of claim 7, the processor further configured to:

receive, from a tracking system, a plurality of locations of a surgical instrument within the volume of patient tissue;

compute a tracked portion of the volume encompassed by the locations;

assess whether the target portion is contained within the tracked portion; and

control the output device to present the indication based on the determining and the assessing.

13. The computing device of claim 7, wherein the output device includes a display.