Laser interstitial thermal therapy in the operating room
Examples of the presently disclosed technology provide new systems and methods for real-time temperature propagation and tissue damage visualization during laser interstitial thermal therapy (LITT) procedures that do not rely on real-time MR imaging. Accordingly, examples enable performance of LITT procedures in regular operating rooms lacking MR-equipment—thereby reducing costs and improving availability for LITT procedures. Examples achieve these advantages by leveraging “discretized” patient-specific 3D brain structure representations to perform numerical methods for solving partial differential equations that estimate real-time (or close to real-time) temperature propagation within a patient's brain during a LITT procedure.
1 . A non-magnetic resonance (MR)-guided method for visualizing temperature propagation during a laser interstitial thermal therapy (LITT) procedure, comprising:
adapting a shape-constrained deformable brain model to a scan of a patient's brain to generate patient-specific 3D brain structure representations;
discretizing the patient-specific 3D brain structure representations into volumetric elements;
assigning tissue properties to the discretized volumetric elements based on the discretized volumetric elements' associated patient-specific 3D brain structure representations;
defining boundary conditions for estimating a temperature propagation vector based on laser ablation-related information obtained during the LITT procedure;
based on the defined boundary conditions and the assigned tissue properties, computing temperature propagation within the patient's brain during the LITT procedure; and
displaying a visual representation of the computed temperature propagation during the LITT procedure.
2 . The non-MR guided method of claim 1 , wherein computing the temperature propagation within the patient's brain during the LITT procedure comprises:
iteratively computing temperatures associated with the discretized volumetric elements over multiple time steps.
3 . The non-MR guided method of claim 2 , wherein assigning tissue properties to the discretized volumetric elements based on the discretized volumetric elements' associated brain structures comprises:
iteratively, for the multiple time steps, assigning tissue properties to the discretized volumetric elements based on the discretized volumetric elements' associated patient-specific 3D brain structure representations and the iteratively computed temperatures associated with the discretized volumetric elements.
4 . The non-MR guided method of claim 1 , wherein the shape-constrained deformable brain model comprises a computerized 3D representation of a non-patient-specific human brain that preserves vertex-based correspondence during adaption to patient scans.
5 . The non-MR guided method of claim 1 , further comprising:
estimating tissue damage within the patient's brain during the LITT procedure based on the computed temperature propagation; and
displaying a visual representation of the estimated tissue damage within the patient's brain during the LITT procedure.
6 . The non-MR guided method of claim 1 , wherein the laser ablation-related information comprises at least one of:
location of a diffusion tip of a laser within the patient's brain;
an estimated direction vector for a laser beam emitted from the diffusion tip; and
settings of the laser during the LITT procedure.
7 . The non-MR guided method of claim 1 , wherein the visual representation of the computed temperature propagation within the patient's brain during the LITT procedure comprises a color-coded heat map that dynamically changes color based on the computed temperature propagation.
8 . The non-MR guided method of claim 1 , wherein assigning the tissue properties to the discretized volumetric elements based on the discretized volumetric elements' associated patient-specific 3D brain structure representations comprises:
assigning, to discretized volumetric elements of a first patient-specific 3D brain structure representation of the patient-specific 3D brain structure representations, a first set of tissue properties; and
assigning, to discretized volumetric elements of a second patient-specific 3D brain structure representation of the patient-specific 3D brain structure representations, a second set of tissue properties.
9 . The non-MR guided method of claim 1 , wherein the tissue properties comprise at least one of thermal conductivity coefficients and perfusion coefficients.
10 . A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of a computing system, cause the computing system to perform a method comprising:
adapting a shape-constrained deformable organ model to a scan of a patient's organ to generate patient-specific 3D anatomical structure representations representing anatomical structures of the patient's organ;
discretizing the patient-specific 3D anatomical structure representations into volumetric elements;
assigning tissue properties to the discretized volumetric elements based on the discretized volumetric elements' associated patient-specific 3D anatomical structure representations;
defining boundary conditions for estimating a temperature propagation vector based on laser ablation-related information obtained during a laser interstitial thermal therapy (LITT) procedure;
based on the defined boundary conditions and the assigned tissue properties, computing temperature propagation within the patient's organ during the LITT procedure; and
displaying a visual representation of the computed temperature propagation during the LITT procedure.
11 . The non-transitory computer-readable storage medium of claim 10 , wherein computing the temperature propagation within the patient's organ during the LITT procedure comprises:
iteratively computing temperatures associated with the discretized volumetric elements over multiple time steps.
12 . The non-transitory computer-readable storage medium of claim 11 , wherein assigning tissue properties to the discretized volumetric elements based on the discretized volumetric elements' associated patient-specific 3D anatomical structure representations comprises:
iteratively, for the multiple time steps, assigning tissue properties to the discretized volumetric elements based on the discretized volumetric elements' associated patient-specific 3D anatomical structure representations and the iteratively computed temperatures associated with the discretized volumetric elements.
13 . The non-transitory computer-readable storage medium of claim 10 , wherein the shape-constrained deformable organ model comprises a computerized 3D representation of a non-patient-specific organ corresponding with the patient's organ that preserves vertex-based correspondences during adaption to patient scans.
14 . The non-transitory computer-readable storage medium of claim 10 , wherein the method further comprises:
estimating tissue damage within the patient's organ during the LITT procedure based on the computed temperature propagation; and
displaying a visual representation of the estimated tissue damage within the patient's organ during the LITT procedure.
15 . The non-transitory computer-readable storage medium of claim 10 , wherein the laser ablation-related information comprises:
location of a diffusion tip of a laser within the patient's organ;
an estimated direction vector for a laser beam emitted from the diffusion tip; and
settings of the laser during the LITT procedure.
16 . The non-transitory computer-readable storage medium of claim 10 , wherein the visual representation of the computed temperature propagation within the patient's organ during the LITT procedure comprises a color-coded heat map that dynamically changes color based on the computed temperature propagation.
17 . The non-transitory computer-readable storage medium of claim 10 , wherein assigning the tissue properties to the discretized volumetric elements based on the discretized volumetric elements' associated patient-specific 3D anatomical structure representations comprises:
assigning, to discretized volumetric elements of a first patient-specific 3D anatomical structure representation of the patient-specific 3D anatomical structure representations, a first set of tissue properties; and
assigning, to discretized volumetric elements of a second patient-specific 3D anatomical structure representation of the patient-specific 3D anatomical structure representations, a second set of tissue properties.
18 . The non-transitory computer-readable storage medium of claim 10 , wherein the tissue properties comprise at least one of thermal conductivity coefficients and perfusion coefficients.
19 . A system comprising:
at least one processor; and
a memory storing instructions that, when executed by the at least one processor, cause the system to perform a method comprising:
adapting a shape-constrained deformable brain model to a scan of a patient's brain to generate patient-specific 3D brain structure representations;
discretizing the patient-specific 3D brain structure representations into volumetric elements;
assigning tissue properties to the discretized volumetric elements based on the discretized volumetric elements' associated patient-specific 3D brain structure representations;
defining boundary conditions for estimating a temperature propagation vector based on laser ablation-related information obtained during a laser interstitial thermal therapy (LITT) procedure;
based on the defined boundary conditions and the assigned tissue properties, computing temperature propagation within the patient's brain during the LITT procedure;
based on the computed temperature propagation, estimating tissue damage within the patient's brain during the LITT procedure; and
displaying a visual representation of the estimated tissue damage during the LITT procedure.
20 . The system of claim 19 , wherein the shape-constrained deformable brain model comprises a computerized 3D representation of a non-patient-specific human brain that preserves vertex-based correspondence during adaption to patient scans.