Systems and methods for optimizing transcranial ultrasound focusing

Systems and methods for predicting a phase correction of ultrasound waves transmitted from one or more transducer elements and traversing a patient's skull into a target region utilizing data of the patient's skull include predicting a first beam path of the ultrasound waves traversing the skull based at least in part on the target location; computationally determining structural characteristics of the skull along the first beam path based on the acquired imaging data; and predicting a second beam path of the ultrasound waves traversing the skull based at least in part on the determined structural characteristics, thereby accounting for refraction resulting from the skull.

FIELD OF THE INVENTION

The present invention relates, generally, to therapeutic ultrasound focusing and, more particularly, to systems and methods for optimizing ultrasound focusing through a non-uniform tissue, such as the skull, at a target location.

BACKGROUND

Focused ultrasound (i.e., acoustic waves having a frequency greater than about 20 kiloHertz) can be used to image or therapeutically treat internal body tissues within a patient. For example, ultrasound waves may be used in applications involving ablation of tumors, thereby eliminating the need for invasive surgery, targeted drug delivery, control of the blood-brain barrier, lysing of clots, and other surgical procedures. During tumor ablation, a piezoceramic transducer is placed externally to the patient, but in close proximity to the tissue to be ablated (i.e., the target). The transducer converts an electronic drive signal into mechanical vibrations, resulting in the emission of acoustic waves. The transducer may be geometrically shaped and positioned along with other such transducers so that the ultrasound energy they emit collectively forms a focused beam at a “focal zone” corresponding to (or within) the target tissue region. Alternatively or additionally, a single transducer may be formed of a plurality of individually driven transducer elements whose phases can each be controlled independently. Such a “phased-array” transducer facilitates steering the focal zone to different locations by adjusting the relative phases among the transducers. As used herein, the term “element” means either an individual transducer in an array or an independently drivable portion of a single transducer. Magnetic resonance imaging (MRI) may be used to visualize the patient and target, and thereby to guide the ultrasound beam.

The noninvasive nature of ultrasound surgery is particularly appealing for the treatment of brain tissue. Moreover, coherent, non-invasive focusing of ultrasound through the human skull has been considered as a tool for targeted drug delivery to the brain, improved thrombolytic stroke treatment, blood flow imaging, the detection of internal bleeding, and tomographic brain imaging. However, the human skull has been a barrier to the clinical realization of many of these applications. Impediments to transcranial procedures include strong distortions caused by irregularities in the skull's shape, density, and thickness, which contribute toward destroying the ultrasound focus, displacing the focus from a desired target location, and/or decreasing the ability to spatially register received diagnostic information.

Accordingly, there is a need for an approach that predicts the effects on the ultrasound beam traversing the skull and based thereon optimizes ultrasound focusing at a desired target location.

SUMMARY

The present invention provides, in various embodiments, systems and methods for estimating, using an acoustic ray model, one or more beam paths of ultrasound waves transmitted from one or more transducer elements to a target location through the patient's skull; the estimated beam path is then compared against the location of the target to determine a deviation therebetween. If the deviation is above a predetermined threshold (e.g., where a clinically significant effect is observed), an updated beam path may be estimated based at least in part on the previously predicted beam path and the determined deviation. This adjustment process may be iteratively performed until the deviation of the estimated beam path from the desired target location is below the predetermined threshold and/or reaches a minimum. A treatment protocol (e.g., parameter(s) associated with the ultrasound beams) corresponding to the minimal deviation (or the deviation below the threshold) may be executed during a focused ultrasound procedure to treat the target region.

In addition, a focusing algorithm may be implemented to determine the phases (and, optionally, amplitudes) associated with the transducer elements based on the path between the elements and target region such that constructive interference (i.e., a focus) of the ultrasound waves from the transducer elements occurs at the target region.

Accordingly, embodiments of the present invention may effectively eliminate (or at least reduce) focus smearing and/or a locational deviation between the target region and the focus of ultrasound beams resulting from the skull; this may ensure accurate delivery of ultrasound energy to the target region for increased treatment efficacy as well as avoiding damage to healthy tissue surrounding the target region. While developed mostly for non-invasive brain surgery and imaging, the approach of the invention may also be applied to other parts of the body requiring the penetration of ultrasound through a bone or cartilage interface.

Accordingly, in one aspect, the invention pertains to a method of transmitting ultrasound waves from one or more transducer elements and traversing a patient's skull into a target region utilizing data of the patient's skull. In various embodiments, the method includes (a) predicting a first beam path of the ultrasound waves traversing the skull into the target region based at least in part on a location of the target region; (b) computationally determining structural characteristics of the skull along the first beam path based on the skull data; (c) predicting a second beam path of the ultrasound waves traversing the skull based at least in part on the determined structural characteristics; (d) updating the second beam path of the ultrasound waves based at least in part on at least one of a deviation between the second beam path and the location of the target region or the second beam path; and (e) activating the transducer element(s) in accordance with a treatment protocol. The treatment protocol may include an amplitude and/or a phase shift associated with the transducer element(s). In addition, the method may include activating the transducer element(s) based at least in part on the determined second beam path. In some embodiments, the method further includes step (f) computationally updating the structural characteristics of the skull based at least in part on the second beam path prior to performing step (d). In some embodiments, the method further includes activating multiple transducer elements in accordance with the treatment protocol so as to generate a focus at the target region. In addition, the method may include, prior to step (e), (f) computationally determining a second deviation between the updated second beam path and the location of the target region; (g) determining whether the second deviation is above a predetermined threshold and, if so, (h) updating the updated second beam path of the ultrasound waves based at least in part on the second deviation; steps (f)-(h) may be iteratively performed until a stopping condition is satisfied. The stopping condition may occur when (i) the second deviation is below the predetermined threshold, (ii) a number of iterations exceeds a predetermined limit, and/or a change in the second deviation between two iterations is below a predetermined minimum.

In one implementation, the first beam path is or comprises one or more straight lines connecting the transducer element(s) to the target region. In addition, the skull data may be CT imaging data and the structural characteristics may be represented by a CT value extracted from the CT imaging data. The ultrasound waves may be transmitted from multiple transducer elements. In one embodiment, the second beam path of the ultrasound waves is adjusted by altering relative phases of the ultrasound waves emitted from the transducer elements. The method may further include computing amplitudes and/or phase shifts associated with the transducer elements so as to generate a focus at the target region. The skull's multiple layers may be considered in generating the focus; additionally, step (b) may include computationally determining structural characteristics of the skull layers based on the skull data, and step (c) may include predicting the second beam path of the ultrasound waves based at least in part on the determined structural characteristics of the skull layers. In one implementation, soft tissue located between the transducer element(s) and the skull is modeled as one of the skull layers. Information about the soft tissue may be acquired using any suitable imaging modality (e.g., an MRI apparatus).

In various embodiments, the method further includes establishing a relationship between the structural characteristics of multiple skull regions and speeds of ultrasound waves traversing the skull regions. The method may include determining a first speed of ultrasound for waves traversing the skull based on, for example, the relationship and the structural characteristics determined in step (b). In addition, the method may include determining a second speed of ultrasound for waves traversing brain and a third speed of ultrasound for waves traversing a medium located between the transducer element(s) and the skull. The third speed of ultrasound waves may be determined based at least in part on the temperature of the medium. In one embodiment, the second beam path is predicted based at least in part on the first, second and third speeds of ultrasound waves.

In some embodiments, the deviation determination step includes computing the shortest distance between the second beam path and the location of the target. In addition, the method may further include computing one or more angles between the first line(s) connecting the transducer element(s) to the location of the target region and the second line(s) connecting the transducer element(s) to a point (e.g., a point having a shortest distance to the location of the target region) on the second beam path; and updating the second beam path of the ultrasound waves based on the computed angle(s).

In another aspect, the invention relates to a system for transmitting ultrasound waves traversing a patient's skull into a target region. In various embodiments, the system includes an ultrasound transducer having one or more transducer elements for transmitting ultrasound waves; and a controller, operably coupled to the ultrasound transducer and imaging system. The controller is configured to (a) acquire data of the patient's skull; (b) predict a first beam path of the ultrasound waves traversing the skull into the target region based at least in part on a location of the target region; (c) computationally determine structural characteristics of the skull along the first beam path based on the skull data; (d) predict a second beam path of the ultrasound waves traversing the skull based at least in part on the determined structural characteristics; (e) update the second beam path of the ultrasound based at least in part on at least one of a deviation between the second beam path and the location of the target region or the second beam path; and (f) activate the transducer element(s) in accordance with a treatment protocol. The treatment protocol may include an amplitude and/or a phase shift associated with the transducer element(s). In addition, the controller may be further configured to activate the transducer element(s) based at least in part on the determined second beam path. In some embodiments, the controller, prior to performing step (e), is further configured to computationally update the structural characteristics of the skull based at least in part on the second beam path. In some embodiments, the controller is further configured to activate multiple transducer elements in accordance with the treatment protocol so as to generate a focus at the target region. In addition, the controller, prior to performing step (f), may be further configured to (g) computationally determine a second deviation between the updated second beam path and the location of the target region; (h) determine whether the second deviation is above a predetermined threshold and, if so, (i) update the updated second beam path of the ultrasound waves based at least in part on the second deviation; the controlled may be configured to perform steps (g)-(i) iteratively until a stopping condition is satisfied. The stopping condition may occur when (i) the second deviation is below the predetermined threshold, (ii) a number of iterations exceeds a predetermined limit, and/or a change in the second deviation between two iterations is below a predetermined minimum.

In one implementation, the controller is configured to predict the first beam path using one or more straight lines connecting the transducer element(s) to the target region. In addition, the system may include an imaging system comprising a computer tomography device for acquiring the skull data; the structural characteristics are represented by a CT value extracted from the imaging data acquired using the computer tomography device. The ultrasound transducer may include multiple transducer elements. In one embodiment, the controller is further configured to update the second beam path of the ultrasound waves by altering relative phases of the ultrasound waves emitted from the transducer elements. In another embodiment, the controller is further configured to compute amplitudes and/or phase shifts associated with the transducer elements so as to generate a focus at the target region. In various embodiments, the skull includes multiple layers, and the controller is further configured to computationally determine structural characteristics of the skull layers based on the imaging data in step (c) and predict the second beam path of the ultrasound waves based at least in part on the determined structural characteristics of the skull layers in step (d). In one implementation, the controller is further configured to model soft tissue located between the transducer element(s) and the skull as one of the skull layers.

In various embodiments, the controller is further configured to establish a relationship between the structural characteristics of multiple skull regions and speeds of ultrasound waves traversing the skull regions. The controller may be further configured to determine a first speed of ultrasound waves traversing the skull based on, for example, the relationship and the structural characteristics determined in step (b). In addition, the controller may be further configured to determine a second speed of ultrasound waves traversing brain tissue inside the skull and a third speed of ultrasound waves traversing a medium located between the transducer element(s) and the skull. The controller may be further configured to determine the third speed of ultrasound waves based at least in part on the temperature of the medium. In one embodiment, the controller is further configured to predict the second beam path based at least in part on the first, second and third speeds of ultrasound waves.

In some embodiments, the controller is further configured to compute the shortest distance between the second beam path and the location of the target so as to determine the deviation. In addition, the controller may be further configured to compute one or more angles between the first line(s) connecting the transducer element(s) to the location of the target region and the second line(s) connecting the transducer element(s) to a point (e.g., a point having a shortest distance to the location of the target region) on the second beam path; and update the second beam path of the ultrasound waves based on the computed angle(s).

Another aspect of the invention relates to a method of predicting the phase correction of ultrasound waves transmitted from one or more transducer elements and traversing a patient's skull into a target region utilizing data of the patient's skull. In various embodiments, the method includes predicting a first beam path of the ultrasound waves traversing the skull into the target region based at least in part on a location of the target region; computationally determining structural characteristics of the skull along the first beam path based on the skull data; an predicting a second beam path of the ultrasound waves traversing the skull based at least in part on the determined structural characteristics, thereby accounting for refraction resulting from the skull.

In yet another aspect, the invention pertains to a system for predicting the phase correction of ultrasound waves traversing a patient's skull into a target region. In various embodiments, the system includes an ultrasound transducer having one or more transducer elements for transmitting the ultrasound waves and a controller operably coupled to the imaging system. The controller is configured to acquire data of the patient's skull; predict a first beam path of the ultrasound waves traversing the skull into the target region based at least in part on a location of the target region; computationally determine structural characteristics of the skull along the first beam path based on the skull data; and predict a second beam path of the ultrasound waves traversing the skull based at least in part on the determined structural characteristics, thereby accounting for refraction resulting from the skull.

As used herein, the terms “approximately” and “substantially” mean±10%, and in some embodiments, ±5%. “Clinically significant” means having an undesired (and sometimes the lack of a desired) effect on tissue that is considered significant by clinicians, e.g., the onset of damage thereto. Reference throughout this specification to “one example,” “an example,” “one embodiment,” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the example is included in at least one example of the present technology. Thus, the occurrences of the phrases “in one example,” “in an example,” “one embodiment,” or “an embodiment” in various places throughout this specification are not necessarily all referring to the same example. Furthermore, the particular features, structures, routines, steps, or characteristics may be combined in any suitable manner in one or more examples of the technology. The headings provided herein are for convenience only and are not intended to limit or interpret the scope or meaning of the claimed technology.

DETAILED DESCRIPTION

FIG. 1Aillustrates an exemplary ultrasound therapy system100for focusing ultrasound onto a patient's brain through the skull. The system100includes a phased array102of transducer elements104, a beamformer106driving the phased array102, a controller108in communication with the beamformer106, and a frequency generator110providing an input electronic signal to the beamformer106. In various embodiments, the system further includes an imager112, such as a magnetic resonance imaging (MRI) device, a computer tomography (CT) device, a positron emission tomography (PET) device, a single-photon emission computed tomography (SPECT) device, or an ultrasonography device, for determining anatomical characteristics of the skull114of a patient116.

The array102may have a curved (e.g., spherical or parabolic) shape suitable for placing it on the surface of the skull114, or may include one or more planar or otherwise shaped sections. Its dimensions may vary, depending on the application, between millimeters and tens of centimeters. The transducer elements104of the array102may be piezoelectric ceramic elements, and may be mounted in silicone rubber or any other material suitable for damping the mechanical coupling between the elements104. Piezo-composite materials, or generally any materials capable of converting electrical energy to acoustic energy, may also be used. To assure maximum power transfer to the transducer elements104, the elements104may be configured for electrical resonance at 50Ω, matching input connector impedance. In addition, the system may include a transducer-adjustment mechanism117(e.g., a motor, a gimbal, or other manipulator that permits mechanical and/or electrical adjustment of the orientation (e.g., an angle or a position) and/or translation (if desired) of ultrasound beams emitted from the transducer array102and/or individual transducer elements104therein. For example, the transducer-adjustment mechanism117may physically rotate the transducer elements104around one or more axes thereof and/or move the elements104with respect to the skull114to a desired location. Alternatively or additionally, the transducer-adjustment mechanism117may adjust the orientation of the ultrasound beam electronically by changing the beam path via the beamformer106, which responsively alters the relative phases of the transducer elements so as to change the beam path. In some embodiments, the transducer-adjustment mechanism117is responsive to a communication from the controller108.

The transducer array102is coupled to the beamformer106, which drives the individual transducer elements104so that they collectively produce a focused ultrasonic beam or field. For n transducer elements, the beamformer106may contain n driver circuits, each circuit including or consisting of an amplifier118and a phase delay circuit120; drive circuit drives one of the transducer elements104. The beamformer106receives a radio frequency (RF) input signal, typically in the range from 0.1 MHz to 1.0 MHz, from the frequency generator110, which may, for example, be a Model DS345 generator available from Stanford Research Systems. The input signal may be split into n channels for the n amplifiers118and delay circuits120of the beamformer106. In some embodiments, the frequency generator110is integrated with the beamformer106. The radio frequency generator110and the beamformer106are configured to drive the individual transducer elements104of the transducer array102at the same frequency, but at different phases and/or different amplitudes.

The amplification or attenuation factors α1-αnand the phase shifts a1-animposed by the beamformer106serve to transmit and focus ultrasonic energy through the patient's skull114onto a selected region of the patient's brain, and account for wave distortions induced in the skull114and soft brain tissue. The amplification factors and phase shifts are computed using the controller108, which may provide the computational functions through software, hardware, firmware, hardwiring, or any combination thereof. For example, the controller108may utilize a general-purpose or special-purpose digital data processor programmed with software in a conventional manner, and without undue experimentation, in order to determine the phase shifts and amplification factors necessary to obtain a desired focus at the target region. In certain embodiments, the computation is based on detailed information about the characteristics (e.g., structure, thickness, density, etc.) of the skull114. Such information may be obtained from the imager112. Image acquisition may be three-dimensional or, alternatively, the imager112may provide a set of two-dimensional images suitable for reconstructing a three-dimensional image of the skull114from which thicknesses and densities can be inferred. Image-manipulation functionality may be implemented in the imager112, in the controller108, or in a separate device.

System100may be modified in various ways within the scope of the invention. For example, for diagnostic applications, the system may further include a detector device (not shown) that measures transmitted or reflected ultrasound, and which may provide the signals it receives to the controller108for further processing. The reflection and transmission signals may also be used as feedback for the phase and amplitude adjustments of the beamformer106. The system100may contain a mechanical positioner for arranging the array102of transducer elements104with respect to the patient's skull114. In order to apply ultrasound therapy to body parts other than the brain, the transducer array102may take a different, e.g., a cylindrical, shape. In some embodiments, the transducer elements104are mounted movably and rotatably, providing mechanical degrees of freedom that can be exploited to improve focusing properties. Such movable transducers may be adjusted by conventional actuators, which may be driven by a component of controller108or by a separate mechanical controller.

In various embodiments, the imager112is an MRI apparatus. With reference toFIG. 1B, the MRI apparatus132may include a cylindrical electromagnet134, which generates the requisite static magnetic field within a bore136of the electromagnet134. During medical procedures, a patient is placed inside the bore136on a movable support table138. A region of interest140within the patient (e.g., the patient's head) may be positioned within an imaging region142wherein the electromagnet134generates a substantially homogeneous field. A set of cylindrical magnetic field gradient coils143may also be provided within the bore136and surrounding the patient. The gradient coils143generate magnetic field gradients of predetermined magnitudes, at predetermined times, and in three mutually orthogonal directions. With the field gradients, different spatial locations can be associated with different precession frequencies, thereby giving an MR image its spatial resolution. An RF transmitter coil144surrounding the imaging region142emits RF pulses into the imaging region142to cause the patient's tissues to emit magnetic-resonance (MR) response signals. Raw MR response signals are sensed by the RF coil144and passed to an MR controller146that then computes an MR image, which may be displayed to the user. Alternatively, separate MR transmitter and receiver coils may be used. Images acquired using the MRI apparatus132may provide radiologists and physicians with a visual contrast between different tissues and detailed internal views of a patient's anatomy that cannot be visualized with conventional x-ray technology.

The MRI controller146may control the pulse sequence, i.e., the relative timing and strengths of the magnetic field gradients and the RF excitation pulses and response detection periods. The MR response signals are amplified, conditioned, and digitized into raw data using a conventional image-processing system, and further transformed into arrays of image data by methods known to those of ordinary skill in the art. Based on the image data, a treatment target region (e.g., a tumor in the brain) may be identified. The image-processing system may be part of the MRI controller146, or may be a separate device (e.g., a general-purpose computer containing image-processing software) in communication with the MRI controller146. In addition, the MRI controller146may be combined with the transducer controller108into an integrated system control facility. In addition, the ultrasound systems100may be displaced within the bore106and integrated with the MRI apparatus132.

Referring toFIG. 2A, a typical human skull114has multiple tissue layers, including an external layer202, a bone marrow layer204, and an internal layer or cortex206; each layer of the skull114may be highly irregular in shape, thickness and density, and unique to a patient. As a result, when the ultrasound waves emitted from the system100encounter the skull114, part of the incident acoustic energy may be reflected at the interfaces208,210,212; the remaining energy may be partially absorbed, and partially refracted and propagated through the skull114depending on the frequency of the waves and the material characteristics and structural inhomogeneity of the skull114. Because the frequency of the ultrasound waves is controllable, the effects of wave propagation through the skull114and the generated focal zone of the waves may be estimated in accordance with the structural inhomogeneity of the skull114as further described below.

In various embodiments, the structural inhomogeneity of the skull114is characterized using an indicator determined based on images acquired using the imager112. For example, the indicator may be a quantified skull density obtained from CT images.FIG. 2Billustrates an acoustic ray220traveling through a CT volume222representing a skull region to the target region214in the brain. In some embodiments, pixel values224(typically measured in “Hounsfield units,” “CT values,” or “CT numbers”) along the path of the ray220and spanning the distance between the target region214and each transducer element104are determined and arranged to form a CT intensity profile for each skull region222. In various embodiments, the acquired pixel values224along the path of the acoustic ray220are averaged; the average CT value thus represents an average skull density along the path of the acoustic ray220for the skull region222.

In various embodiments, an acoustic ray model is implemented to compute a speed of ultrasound waves, CS, in the skull region, and thereby determine a beam path of ultrasound waves penetrating therein. Referring toFIG. 2C, the acoustic ray model may simulate the skull114as a single layer230defined by multiple regions232; each region is characterized by its material properties (e.g., an average skull density) represented by an average of the CT values measured in the region as described above. To determine the speed of ultrasound waves traversing each skull region232, a relationship between the average CT value of each region232and the speed of ultrasound waves, CS, may be first empirically established from a pre-clinical study, a pre-treatment procedure, and/or from known literature. For example, in a pre-clinical study, a sensor234may be placed at an inner surface236of the modeled single-layer skull230for measuring a travel time, Δt, of an ultrasound pulse penetrating a skull region232. The speed of ultrasound waves in the skull region232may be computed based on the detected ultrasound travel time and the thickness of the skull region232acquired from, for example, the CT images. The sensor234may be placed along the entire inner skull surface236and detecting the travel time associated with each skull region232; based thereon, the speed of ultrasound waves transmitting various skull regions232can be computed. Because the speed of sound in a material typically correlates to the density thereof, and the density of each skull region232may be characterized using the average of CT values measured in each region232, a relationship between the average of CT values in a skull region and the speed of ultrasound waves therein may be established.

For example, the relationship between the averages of CT values and speeds of ultrasound waves in the skull regions may be a polynomial equation—e.g., the speed of ultrasound waves is a polynomial function of the measured CT values. For example, referring toFIG. 2D, the relationship can be as simple as a linear polynomial obtained using a regression approach:
CS=a+b×ρCT
where CSand ρCTrepresent the speed of ultrasound waves and averaged CT value associated with the skull region, respectively, and a and b are coefficients determined using the regression approach. Accordingly, when an averaged CT value associated with a specific skull region232is acquired from the CT images, the speed of ultrasound waves, CS, traversing this specific skull region can be determined based on the polynomial equation. Generally, the computed speed of ultrasound waves in the skull is in a range between 2,000 m/s and 3,000 m/s.

While an average of the CT values measured in a skull region is utilized herein to represent the average skull density, other indicator may be used to characterize the structural inhomogeneity of the skull. For example, the indicator may include a skull density ratio as described in U.S. Patent Publication No. 2016/0184026, the entire disclosure of which is hereby incorporated by reference.

In addition, the density of brain tissue and the speed of ultrasound waves, CB, in brain tissue may be measured and/or estimated in accordance with the approach described above for the skull tissue. A different brain region may have the same or different speed of ultrasound waves therein, depending on the density of the brain region. A relationship between the density of brain tissue and the speed of ultrasound waves in brain tissue may also be determined based on the approach described above. Alternatively, information about the brain tissue may be acquired from known literature. For example, the speed of sound in brain tissue, CB, has been reported to be approximately 1,545 m/s. In one implementation, the acoustic ray model simulates the brain tissue as a homogeneous soft material and the speed of ultrasound waves therein has the same value, 1,545 m/s, across the entire region. The acoustic ray model may then predict the ultrasound beam path in the skull and brain tissue based on the speeds of ultrasound waves therein as further described below.

Referring toFIG. 3A, prior to estimating the ultrasound beam path in the skull and brain tissue, the acoustic ray model may first identify the location of the target region302(e.g., a tumor in the brain) using, for example, MRI image data. In addition, the acoustic ray model may define boundaries304,306of the skull by, for example, fitting planes to skull edges illustrated in CT image data. In various embodiments, the MRI image data of the skull, brain, and/or transducer elements is utilized to register the CT image data, transducer geometry and/or anatomical characteristics of the skull and brain. Exemplary registration approaches for images acquired using various modalities are provided, for example, in U.S. patent application Ser. Nos. 14/879,235 and 15/155,171, the entire disclosures of which are hereby incorporated by reference. In addition, the acoustic ray model may define the skull as multiple regions308, where each of the skull regions308is related to or corresponds to a particular transducer element104or a grouping of elements. Based on the application, the transducer elements104may be exposed in air or mounted within a casing filled with a medium (e.g., water).

In various embodiments, the acoustic ray model initially simulates an ultrasound beam path310from the transducer element (or group of transducer element) to the target region302as a straight line; this initial simulation neglects refraction of the ultrasound waves traversing the skull region. An entry point, S1, of the ultrasound beam310into the skull region and an exit point, S2, of the ultrasound beam310from the skull region can be identified using the skull boundaries304,306and a straight line extending from the transducer element to the target. In one embodiment, the acoustic ray model acquires CT skull imaging data to extract CT values associated with the skull region located along the beam path310between the entry point S1and exit point S2. By averaging the extracted CT values and utilizing the relationship between the averaged CT values and speeds of ultrasound waves as described above (e.g., a polynomial equation as depicted inFIG. 2D), the speed of ultrasound waves, CS, along the beam path310in the skull can be determined.

In addition, the acoustic ray model may acquire a speed of ultrasound waves, CM, in the medium312located between the transducer elements104and the skull; this information may be obtained either by a sensor measurement as described above using a time-of-flight approach or by lookup from the known literature. Subsequently, the acoustic ray model may determine the beam path of ultrasound waves in the skull region308based on the speeds of ultrasound waves, CMand CS, in the medium and skull region, respectively.

In one embodiment, the acoustic ray model utilizes Snell's law to predict the beam path of ultrasound waves traversing the skull region towards the target. For example, referring toFIG. 3B, the angle of incidence, θ1, of the ultrasound wave320transmitted from a transducer element104(or a grouping of elements) onto a skull region322can be computed based on information about the geometry of the transducer element104and the transducer element location and orientation relative to the skull regions322as well as the location of the target region302. The angle of refraction, θ2, of the ultrasound wave310at the entry point S1of the skull may be computed using Snell's law:

sin⁡(θ1)sin⁡(θ2)=cMcS
where cMand cSare speeds of ultrasound waves in the medium and skull, respectively. Similarly, an angle of refraction, θ3, of the ultrasound wave at the exit point S2′ of the skull may be computed as:

sin⁡(θ2)sin⁡(θ3)=cScB
where cBis the speed of ultrasound waves in the brain tissue. Because the acoustic ray model simulates the skull as a single layer structure, refraction within the skull region may be neglected.

In various embodiments, the acoustic ray model assumes the brain tissue to be homogeneous; accordingly, based on the angle of refraction, θ3, at the exit point S2′ of the skull, the ultrasound beam path322in the brain tissue can be determined. In various embodiments, the acoustic ray model further identifies a point T′ on the beam path322that has the shortest distance Δ to the target region T. If the distance Δ is above a first predetermined threshold, the deviation of the predicted beam path322from the target location T is too large to allow a focusing algorithm to efficiently predict a correction phase shift associated with the element S so as to ensure a contribution thereof at the focus in the target region is positive (i.e., in phase with the other elements). In such circumstances, a coarser correction and/or an alternative approach may be required. For example, new images of the target region and/or the skull may be acquired to provide better imaging quality and image analysis may be performed on the new images to more accurately determine the target location and/or characteristics of the skull; the speeds of ultrasound waves in the medium, skull and/or brain tissue may be estimated using another approach; the acoustic ray model may be modified to more accurately predict the ultrasound beam path penetrating the skull to the target region; or the transducer position may be changed.

If the shortest distance between the target region and predicted beam path322is below the first predetermined threshold, the deviation is acceptably small and the focusing algorithm may be used to efficiently predict a correction phase shift associated with the element S, thereby ensuring a positive contribution at the focus in the target region. In various embodiments, the deviation Δ is further compared against a second predetermined threshold—corresponding, for example, to a deviation too small to have a clinically significant effect (e.g., damage to tissue outside a safety margin around the target) or, in other embodiments, too small to be measured; if the deviation is below the second predetermined threshold, it indicates that the deviation of the beam path322from the target location is insignificant. Accordingly, the transducer elements may be activated to create a focal zone along the updated beam path322during a focused ultrasound procedure. If, however, the distance Δ is above the second predetermined threshold, an acoustic-path searching procedure may be performed to eliminate (or at least reduce) the deviation, thereby optimizing the ultrasound phase at the target region. Referring toFIG. 3C, in various embodiments, the acoustic-path searching procedure first determines an angle Φ between the initial straight-line beam path310and a line324connecting the transducer element S to the point T′ on the predicted beam path322that accounts for wave refraction in the skull and brain tissue. Because the deviation Δ is substantially smaller than the distance from the transducer element to the target region, the angle Φ (in radians) may be approximated as follows:

Subsequently, the acoustic ray model updates the estimated ultrasound beam path from the transducer element through the corresponding skull region to the target to be on a beam path330that has an angle Φ with respect to the initial beam path310. Using the updated beam path330from the transducer element, an updated entry point, S1″, and the associated angle of incidence, θ1″, and angle of refraction, θ2″, of the ultrasound wave at the updated entry point S1″ can be recomputed. Subsequently, an updated exit point, S2″, and angle of refraction, θ3″, of the ultrasound wave at the updated exit point S2″ may be determined using Snell's law as described above. The beam path in brain tissue may then be adjusted based on the updated angle of refraction θ3, and the shortest distance Δ″ from the target region to the updated beam path330can be computed. Again, if the shortest distance Δ″ is below the second predetermined threshold, the deviation of the expected beam path330from the target location is insignificant; accordingly, the transducer elements may be activated to create a focal zone along the updated beam path330during a focused ultrasound procedure. If, however, the distance Δ″ is above the second predetermined threshold, the acoustic-path searching procedure may be iteratively performed until the deviation Δ″ falls below the second threshold. For example, referring toFIG. 3D, the acoustic-path searching procedure may determine an angle Φ′ between the initial straight-line beam path310and a line334connecting the transducer element S to the point T″. Again, because the deviation Δ″ is substantially smaller than the distance from the transducer element to the target region, the angle Φ′ may be approximated as:

The acoustic ray model then updates the estimated ultrasound beam path to be on a beam path340that has an angle Φ′ with respect to the initial beam path310. Subsequently, an updated deviation Δ′″ of the beam path340from the target region can be determined.

AlthoughFIGS. 3A-3Ddepict the patient's skull as a single-layer tissue, the skull may be modeled as a multilayer structure (e.g., three layers). In the multilayer model, the ultrasound ray may be refracted multiple times in the skull region on the way to the target. Again, the beam path may be updated based on the distance between the ray in the brain and the target location. In addition, the initial beam path310may be determined using any suitable approach other than the straight-line method as described above. For example, the initial entry point S1of the ultrasound beam310may be identified as a point through which a tangent line to the skull region is perpendicular to the element surface. Subsequently, Snell's law as described may be implemented to predict the beam path of ultrasound waves traversing the skull region towards the target.

Alternatively and/or additionally, in some embodiments, the correction is iteratively performed until the deviation of the beam path from the target region is minimized. For example, assuming the shortest distances between the predicted beam paths and target region are Δ1, Δ2, and Δ3for the nth, (n+1)th, and (n+2)thiterations of correction, respectively, if Δ1>Δ2and Δ3>Δ2, the deviation is minimized at the (n+1)thiteration. Accordingly, the phase correction associated with the transducer element may be performed according to the beam path predicted in the (n+1)thiteration. In addition, the iterative acoustic-path searching procedure may be terminated when other conditions are met. For example, the searching procedure may be stopped when too may iterations (e.g., more than 20 times) have been performed or when the improvement of the deviation between two successive iterations is too small (e.g., Δn−Δn+1<0.1 mm).

The acoustic ray model may sequentially or simultaneously predict multiple ultrasound beam paths, each associated with waves traversing a different skull region from a corresponding transducer element (or a grouping of corresponding elements). Based on the predicted beam paths and their deviation from the target, the acoustic-path searching procedure may be iteratively performed until the beam paths substantially coincide with the target region. To ensure the focus of the ultrasound waves is at the target region, the focus algorithm may determine the phase shift associated with each transducer element such that the ultrasound beams traversing the multiple skull regions collectively form a constructive focal zone at the target region. In one embodiment, the phase shift associated with each transducer element is determined based on the path between the transducer element and the target location and/or and/or the speed of ultrasound waves in each region along the path. In addition, the phases of ultrasound beams whose paths are not found and/or not considered optimal (e.g., not substantially coinciding with the target region) may not be synchronized between the transmitting transducer elements. Therefore, these beams may be out of phase and destructively interfere to avoid damage to healthy tissue surrounding the target region. If one or more undesired hot spots are generated, various approaches may be implemented to reduce them without substantially reducing the ultrasound intensity at the target region. Exemplary approaches are provided, for example, in U.S. patent application Ser. No. 15/404,412, the entire disclosure of which is hereby incorporated by reference.

FIG. 4Aillustrates an approach for predicting the beam path(s) of ultrasound waves traversing a skull region into the brain tissue in accordance with various embodiments. In a first step402, images of the patient's head are acquired using an imager; the images may include the skull and/or a target region to be treated. In a second step404, the images are processed to determine the location of the target as well as indicators (e.g., CT values) characterizing the structural inhomogeneity of the skull and the effects of the inhomogenities on ultrasound propagation; each indicator may be associated with one region of the skull and the regions collectively cover the anticipated region of the skull through which the ultrasound waves travel prior to reaching the target region. In a third step406, an acoustic ray model initially simulates the beam path of an ultrasound wave from the transducer elements to the target region as, for example, a straight line. Based on the initial simulation, an entry point of the beam entering the skull and an exit point of the beam exiting the skull are determined. In a fourth step408, skull CT values along the beam path between the entry and exit points are extracted from the imaging data, and an average of the extracted CT values is computed. In a fifth step410, the speed of ultrasound waves associated with the averaged CT value in the skull is determined based on the relationship correlating the CT value and the speed of ultrasound waves in the skull established in, for example, a pre-clinical study; such data is readily available or straightforwardly generated without undue experimentation.

Optionally, the speed of ultrasound waves in the brain tissue may be computed using a similar approach. In addition, a medium such as water typically intervenes between the transducer elements and the patient's skin, in which case the speed of ultrasound waves in that medium is computed based on the properties of the medium. In a sixth step412, the beam paths of ultrasound waves transmitted from the elements to the target region are predicted based on the speeds of ultrasound waves in the medium, skull and brain tissue. The ultrasound beam paths may then be compared with the target location to determine a deviation therebetween.

FIG. 4Billustrates an approach for minimizing the deviation of the predicted beam path from the target region. In various embodiments, after the ultrasound beam path in the skull and brain tissue has been determined as described in step412, the deviation of the predicted ultrasound beam path from the target region is computed (in a step414). If the deviation is larger than a first predetermined threshold (as defined above), various approaches, such as acquiring new images of the target region and/or skull, using a different approach to acquire speeds of sound in the medium, skull and/or brain tissue, adjusting the acoustic ray model and/or using another approach for estimating the ultrasound beam path, may be used to generate a new beam path (in a step416). If the deviation is smaller than the first predetermined threshold but larger than a second predetermined threshold (again as described above), the angle between the initial beam path and a line connecting the transducer element to a point T′ on the predicted beam path that accounts for wave refraction in the skull and brain tissue is computed; the point T′ is defined as the closest point to the target along the predicted beam path (in a step418). Subsequently, the acoustic ray model updates the predicted ultrasound beam path to be on a path that has the computed angle relating to the initial beam path (in a step420). Steps408-414may be implemented to determine a new ultrasound beam path traversing the skull region and the deviation between the newly predicted beam path and target region. The deviation between the newly predicted ultrasound beam path and the target region may be computed as described above. Accordingly, steps408-420may be iteratively performed until the deviation is below the second predetermined threshold or reaches a minimum. In a step422, a focusing algorithm may determine phase shifts associated with the transducer elements and the target such that the ultrasound waves traversing the skull collectively form a constructive focal zone at the target region. In a step424, the transducer elements are activated based on a treatment protocol including, for example, the determined phase shifts and parameters that generate maximal coherency at the target.

Methods for predicting ultrasound beam paths in the skull and brain tissue in accordance herewith can be implemented using a suitable image-processing and control facility (e.g., a controller of the imager, and/or an ultrasound system, or a separate external controller or other computational entity or entities) in communication with the treatment apparatus (e.g., the beam former setting the phases and amplitudes of an ultrasound transducer array and/or the motor or manipulator setting the orientations of the transducer array)100and the imaging apparatus112. The image-processing and control facility may be implemented in any suitable combination of hardware, software, firmware, or hardwiring.FIG. 5illustrates an exemplary embodiment where the facility is provided by a suitably programmed general-purpose computer500. The computer includes a central processing unit (CPU)502, system memory504, and non-volatile mass storage devices506(such as, e.g., one or more hard disks and/or optical storage units). The computer500further includes a bidirectional system bus508over which the CPU502, memory504, and storage devices506communicate with each other and with internal or external input/output devices, such as traditional user interface components510(including, e.g., a screen, a keyboard, and a mouse) as well as the treatment apparatus512, the imaging apparatus514, and (optionally) any sensors516measuring the travel time of ultrasound waves through various skull and/or brain regions.

The system memory504contains instructions, conceptually illustrated as a group of modules, that control the operation of CPU502and its interaction with the other hardware components. An operating system518directs the execution of low-level, basic system functions such as memory allocation, file management and operation of mass storage devices506. At a high level, one or more service applications provide the computational functionality required for image-processing and ultrasound beam path prediction. For example, as illustrated, the system may include a conventional image-analysis module520for acquiring image data received from the imaging apparatus514, and based thereon identifying a location of the target region, determining the distance between the target region (e.g., its center of mass) and at least a portion of the treatment apparatus512, and/or extracting an indicator characterizing tissue inhomogeneity; a speed-of-sound-determining module522for determining the speed of ultrasound waves traversing various regions of the skull and/or brain tissue based on an empirical pre-clinical study, a sensor measurement performed in a pre-treatment procedure, and/or reports obtained from known literature; a beam-path-predicting module524for predicting the ultrasound waves in the skull and/or brain tissue in accordance with the techniques described above; and a deviation-determining module526for computing, in the manner set forth above, a deviation from the prediction beam path to the target location and comparing the computed deviation with predetermined thresholds.

In addition, the system may include a beam-adjustment module528for computing amplitudes, phase shifts and/or other parameters of the treatment apparatus to account for refraction in the skull and/or brain tissue so as to generate a focus at the target location. For example, the beam-adjustment module528may be responsive to the deviation-determining module526and, based on the determined deviation, may thereby compute correction of ultrasound parameter(s) necessary to reduce or eliminate the deviation. The correction may then be transmitted to the transducer-adjustment mechanism117, which acts mechanically or via beamformer106. The mode of action may depend on the magnitude of the required adjustment (e.g., mechanical for coarse adjustment and electronic for fine adjustment) and/or the configuration selected for the transducer-adjustment mechanism. In addition, the phase shifts may be determined based on the path between the treatment apparatus and the target location identified by the image-analysis module520. The computed parameters may then be communicated to the ultrasound controller for activating the transducer array. The various modules may be programmed in any suitable programming language, including, without limitation, high-level languages such as C, C++, C #, Ada, Basic, Cobra, Fortran, Java, Lisp, Perl, Python, Ruby, or Object Pascal, or low-level assembly languages; in some embodiments, different modules are programmed in different languages.

In addition, the term “controller” used herein broadly includes all necessary hardware components and/or software modules utilized to perform any functionality as described above; the controller may include multiple hardware components and/or software modules and the functionality can be spread among different components and/or modules.