Monitoring and noise masking of thermal therapy

• US 9,271,794 B2
• Filed: 12/01/2014
• Issued: 03/01/2016
• Est. Priority Date: 08/13/2009
• Status: Active Grant

• Current Assignee: Monteris Medical Incorporated (Monteris Medical US, Inc.)
• Original Assignee: Monteris Medical Incorporated (Monteris Medical US, Inc.)
• Inventors: Tyc, Richard, Qureshi, Salman, Grant, Mark Andrew, Fernandes, Luis Filipe Silva, Carreira, Daniel Prazeres, Schellhorn, John
• Primary Examiner(s): ENTEZARI, MICHELLE M
• Application Number:
  US14/557,127
• Publication Number:
  US 20150087963A1
• Time in Patent Office: 456 Days
• US Class Current: 1/1
• CPC Class Codes: A61B 18/02 by cooling, e.g. cryogenic techniques devices for cooling specific reflex points of the body within cell-life limits A61H39/06
• CPC Class Codes: A61B 18/0206 ultrasonic, e.g. for destroying tissue or enhancing freezing
• CPC Class Codes: A61B 18/06 caused by chemical reaction , e.g. moxaburners
• CPC Class Codes: A61B 18/148 having a short, rigid shaft for accessing the inner body transcutaneously, e.g. for neurosurgery or arthroscopy
• 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 18/1815 using microwaves
• CPC Class Codes: A61B 18/22 the beam being directed along or through a flexible conduit, e.g. an optical fibre; Couplings or hand-pieces therefor
• CPC Class Codes: A61B 18/28 for heating a thermal probe or absorber
• CPC Class Codes: A61B 2017/00017 Electrical control of surgical instruments
• CPC Class Codes: A61B 2017/00911 for fields applied by a magnetic resonance imaging system
• CPC Class Codes: A61B 2017/3407 including a base for support on the body
• CPC Class Codes: A61B 2018/00017 with gas
• CPC Class Codes: A61B 2018/00023 closed, i.e. without wound contact by the fluid
• CPC Class Codes: A61B 2018/00446 Brain
• CPC Class Codes: A61B 2018/00577 Ablation
• CPC Class Codes: A61B 2018/00642 with feedback, i.e. closed loop control
• CPC Class Codes: A61B 2018/00702 Power or energy
• CPC Class Codes: A61B 2018/00791 Temperature
• CPC Class Codes: A61B 2018/00994 combining two or more different kinds of non-mechanical energy or combining one or more non-mechanical energies with ultrasound
• CPC Class Codes: A61B 2018/0212 using an instrument inserted into a body lumen, e.g. catheter
• CPC Class Codes: A61B 2018/0293 : using an instrument interstitially inserted into the body, e.g. needle
• CPC Class Codes: A61B 2018/1807 : using light other than laser radiation
• CPC Class Codes: A61B 2018/1861 : with an instrument inserted into a body lumen or cavity, e.g. a catheter
• CPC Class Codes: A61B 2018/20351 : Scanning mechanisms
• CPC Class Codes: A61B 2018/2211 : Plurality of fibres
• CPC Class Codes: A61B 2018/2261 : with scattering, diffusion or dispersion of light
• CPC Class Codes: A61B 2034/107 : Visualisation of planned trajectories or target regions
• CPC Class Codes: A61B 2034/2068 : using pointers, e.g. pointers having reference marks for determining coordinates of body points
• CPC Class Codes: A61B 2034/301 : for introducing or steering flexible instruments inserted into the body, e.g. catheters or endoscopes
• CPC Class Codes: A61B 2090/061 : for measuring dimensions, e.g. length
• CPC Class Codes: A61B 2090/374 : NMR or MRI
• 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 34/25 : User interfaces for surgical systems
• CPC Class Codes: A61B 34/71 : Manipulators operated by drive cable mechanisms
• CPC Class Codes: A61B 5/015 : By temperature mapping of body part
• CPC Class Codes: A61B 5/055 : involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: A61B 5/4839 : combined with drug delivery
• CPC Class Codes: A61B 5/742 : using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/746 : Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: A61B 90/10 : for stereotaxic surgery, e.g. frame-based stereotaxis
• CPC Class Codes: A61B 90/11 : with guides for needles or instruments, e.g. arcuate slides or ball joints
• CPC Class Codes: A61B 90/14 : Fixators for body parts, e.g. skull clamps; Constructional details of fixators, e.g. pins
• CPC Class Codes: A61N 5/0601 : Apparatus for use inside the body
• CPC Class Codes: A61N 5/062 : Photodynamic therapy, i.e. excitation of an agent
• CPC Class Codes: A61N 7/022 : intracavitary
• CPC Class Codes: G01R 33/285 : Invasive instruments, e.g. catheters or biopsy needles, specially adapted for tracking, guiding or visualization by NMR
• CPC Class Codes: G01R 33/4804 : Spatially selective measurement of temperature or pH

Abstract

Image-guided therapy of a tissue can utilize magnetic resonance imaging (MRI) or another medical imaging device to guide an instrument within the tissue. A workstation can actuate movement of the instrument, and can actuate energy emission and/or cooling of the instrument to effect treatment to the tissue. The instrument can be an MRI compatible laser probe that provides thermal therapy to, e.g., a tissue in a brain of a patient. By tracking a probe position within tissue through feedback, multiple data slices provided around the probe position can be processed to monitor treatment and view thermal data. The operator selects treatment area reference points with the assistance of noise masking.

Claims

1. A method for thermal monitoring of tissue during thermal therapy, comprising:

prior to initiation of thermal therapy,

obtaining, by processing circuitry, a plurality of magnetic resonance (MR) images of a patient, wherein

the plurality of MR images correspond to a same imaging slice captured over a time period, and

each MR image of the plurality of MR images includes respective phase data,

identifying, by the processing circuitry, a volume in the patient corresponding to a) a region of interest at which to apply thermal therapy and b) surrounding tissue,

analyzing, by the processing circuitry, pixel locations of the phase data of the plurality of MR images corresponding to the volume to identify one or more pixel locations demonstrating excessive phase noise,

determining, by the processing circuitry, a noise mask for the region of interest, wherein the noise mask excludes the one or more pixel locations demonstrating excessive phase noise, and

selecting, from the pixels included in the noise mask, a plurality of reference points, wherein

the plurality of reference points identify locations within the surrounding tissue, and

each reference point of the plurality of reference points corresponds to a particular pixel location of the phase data having a particular phase value; and

initiating monitoring of the thermal therapy, wherein monitoring comprises

receiving a current MR image of the patient,

adjusting, by the processing circuitry, the phase data of the current MR image according to the plurality of reference points, wherein adjusting the phase data of the current MR image comprises

determining, based upon at least a subset of the plurality of reference points without considering phase data corresponding to pixel locations within the region of interest, a plurality of phase drift values to correct for phase drift, and

extrapolating the phase drift values into a phase map, wherein at least a portion of the phase map corresponds to the pixel locations within the region of interest,

applying, by the processing circuitry, the phase map to the current phase data to obtain drift-adjusted phase data, and

calculating, by the processing circuitry, a temperature map using the drift-adjusted phase data, wherein the temperature map corresponds to at least the region of interest.

2. The method of claim 1, further comprising, after determining the noise mask and prior to initiating thermal therapy, displaying, on a graphical user interface, a rendering of the noise mask overlaying the volume in the patient in a first MR image of the plurality of MR images.

3. The method of claim 2, wherein selecting the plurality of reference points comprises receiving, via interaction with the graphical user interface, a respective user selection of each of the plurality of reference points from the rendering of the noise mask.

4. The method of claim 1, wherein selecting the plurality of reference points comprises automatically selecting, by the processing circuitry independently of user selection, at least a portion of the plurality of reference points.

5. The method of claim 4, further comprising receiving user input confirming acceptance of the automatically selected reference points of the plurality of reference points.

6. The method of claim 1, wherein selecting the plurality of reference points comprises verifying, by the processing circuitry, that each reference point of the plurality of reference points corresponds to a respective tissue region of a same tissue type as the remaining reference points.

7. The method of claim 1, wherein the plurality of MR images comprises at least three MR images.

8. The method of claim 1, further comprising, prior to initiation of thermal therapy:

validating, by the processing circuitry, stability of drift-adjusted phase data, wherein

validating the stability of drift-adjusted phase data comprises

obtaining a present MRI image of the volume;

computing, at every location within the volume, a respective temperature difference from a reference tissue temperature, wherein computing the respective temperature difference comprises adjusting the phase data of the present MR image according to the plurality of reference points;

applying, to the respective temperature differences, a temperature variance threshold to identify a plurality of noisy locations; and

illustrating, on a graphical user interface, a rendering of a temperature mask overlaying the volume in the patient, wherein the noisy locations are specified by visual indications.

9. The method of claim 8, wherein the noisy locations are indicated by transparent portions of a color overlay.

16. The method of claim 8, further comprising;

receiving, through a user interface responsive to illustrating the rendering of the temperature mask, user input modifying the plurality of reference points, wherein the user input corresponds to at least one of a) a deletion of a first reference point of the plurality of reference points, and b) an addition of a new reference point to the plurality of reference points; and

repeating validation of stability of the drift-adjusted phase data using the modified plurality of reference points.

17. The method of claim 8, further comprising receiving, through a user interface prior to validating the stability of the drift-adjusted phase data, the reference tissue temperature.

20. The method of claim 6, wherein the tissue type is brain tissue.

10. A system for thermal monitoring of tissue during thermal therapy, comprising:

a processor in communication with a display and a magnetic resonance (MR) imaging device; and

a memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to;

prior to initiation of thermal therapy,

obtain, from the MR imaging device, a plurality of magnetic resonance (MR) images of a patient, wherein

the plurality of MR images correspond to a same imaging slice over a time period, and

each MR image of the plurality of MR images includes respective magnetic resonance (MR) phase data,

identify a volume in the patient corresponding to a) a region of interest at which to apply thermal therapy and b) surrounding tissue, wherein the plurality of MR images comprises respective magnetic resonance (MR) image data representing a portion of the volume including a portion of the region of interest, and

determine a plurality of reference points, wherein

the plurality of reference points identify locations within the surrounding tissue, and

each reference point of the plurality of reference points corresponds to a particular pixel location of the phase data having a particular phase value; and

initiate monitoring of thermal therapy, wherein monitoring comprises

receiving, from the MR imaging device, a current MR image of the patient,

calculating a plurality of phase drift values associated with the plurality of reference points, wherein the phase drift values are based upon phase values of each respective reference point of the plurality of reference points over successive magnetic resonance (MR) phase data of the current MR image and a former MR image without considering phase data corresponding to pixel locations within the region of interest,

extrapolating the phase drift values of the plurality of reference points into a phase map, wherein at least a portion of the phase map corresponds to the pixel locations within the region of interest,

applying the phase map to the MR phase data of the current MR image to obtain drift-compensated phase data,

calculating a temperature map based upon the drift-compensated phase data, wherein the temperature map corresponds to at least the region of interest, and

presenting, on the display, a rendering of the MR image including a graphical representation of temperatures in the region of interest according to the temperature map.

11. The system of claim 10, wherein the graphical representation of temperatures comprises a color overlay.

12. The system of claim 10, further comprising, prior to determining the plurality of reference points:

analyzing the respective MR phase data of each MR image of the plurality of MR images to identify a plurality of noisy data points; and

marking the plurality of noisy data points as ineligible for selection as reference points.

13. The system of claim 12, wherein identifying a particular noisy data point of the plurality of noisy data points comprises determining whether a difference of phase values of the particular noisy data point between two MR images of the plurality of MR images exceeds a threshold level.

14. The system of claim 10, wherein calculating the temperature map comprises multiplying the drift-compensated phase data by a constant and adding a baseline temperature of the volume.

15. The system of claim 14, wherein the instructions, when executed by the processor, cause the processor to receive, through a user interface, the baseline temperature.

18. The system of claim 10, wherein the plurality of reference points comprises fewer than twenty-five reference points.

19. The system of claim 10, wherein:

the plurality of reference points comprises at least eight reference points; and

extrapolating the phase drift values into the phase map comprises applying the phase drift values to the phase data using a polynomial surface fit.