U.S. patent application number 14/771894 was filed with the patent office on 2016-01-14 for frequency optimization in ultrasound treatment.
The applicant listed for this patent is INSIGHTEC, LTD., Shuki VITEK, Kobi VORTMAN, Eyal ZADICARIO. Invention is credited to Shuki Vitek, Kobi Vortman, Eyal Zadicario.
Application Number | 20160008633 14/771894 |
Document ID | / |
Family ID | 51220604 |
Filed Date | 2016-01-14 |
United States Patent
Application |
20160008633 |
Kind Code |
A1 |
Vortman; Kobi ; et
al. |
January 14, 2016 |
FREQUENCY OPTIMIZATION IN ULTRASOUND TREATMENT
Abstract
In ultrasound therapy, the frequency of sonications can be
optimized, within a certain frequency range, to maximize the
absorption or the acoustic intensity at the target in a manner
specific to the patient.
Inventors: |
Vortman; Kobi; (Haifa,
IL) ; Vitek; Shuki; (Haifa, IL) ; Zadicario;
Eyal; (Tel Aviv-Yafo, IL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
VORTMAN; Kobi
VITEK; Shuki
ZADICARIO; Eyal
INSIGHTEC, LTD. |
Haifa
Haifa
Tel-Aviv-Yafo
Tirat Carmel |
|
IL
IL
IL
IL |
|
|
Family ID: |
51220604 |
Appl. No.: |
14/771894 |
Filed: |
March 6, 2014 |
PCT Filed: |
March 6, 2014 |
PCT NO: |
PCT/IB2014/000920 |
371 Date: |
September 1, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61773394 |
Mar 6, 2013 |
|
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Current U.S.
Class: |
601/2 |
Current CPC
Class: |
A61B 2090/374 20160201;
A61N 2007/0073 20130101; A61N 2007/0078 20130101; A61N 7/02
20130101; A61N 7/00 20130101 |
International
Class: |
A61N 7/00 20060101
A61N007/00 |
Claims
1. A patient-specific frequency-optimization method for ultrasound
therapy of a target within the patient, the method comprising: (a)
for at least one segment of an ultrasound transducer and for each
of a plurality of ultrasound frequencies within a test range,
sonicating the target and measuring a parameter correlated with an
amount of ultrasound energy absorbed in the target; and (b) for
each said at least one segment, selecting for subsequent ultrasound
therapy, among the frequencies within the test range, a frequency
corresponding to a value of the measured parameter that itself
corresponds to a maximum amount of ultrasound energy absorbed in
the target.
2. The method of claim 1, further comprising, following frequency
selection in step (b), driving the at least one segment at the
selected frequency and at a therapeutic energy level to thereby
sonicate the target, the therapeutic energy level exceeding an
energy level of sonications applied in step (a).
3. The method of claim 1, further comprising defining a plurality
of segments within the ultrasound transducer based, at least in
part, on an anatomy of the patient.
4. The method of claim 3, wherein steps (a) and (b) are performed
for each of the segments, the method further comprising, during
ultrasound therapy, driving the segments together, each at its
respective selected frequency.
5. The method of claim 1, wherein the plurality of frequencies
within the test range is defined dynamically based, at least in
part, on a value of the parameter measured for a previously tested
frequency.
6. The method of claim 1, wherein the parameter is selected from
the group consisting of a power, an energy, an intensity, an
acoustic force, a tissue displacement, and a temperature.
7. The method of claim 1, wherein the parameter is measured using
thermometry.
8. A system for selecting a patient-specific frequency for
ultrasound therapy of a target within the patient, the system
comprising: an ultrasound transducer and an associated controller
capable of driving the transducer at any frequency within a test
range of frequencies so as to sonicate the target; a measurement
facility for measuring a parameter correlated with an amount of
ultrasound energy absorbed in the target; and a computational
facility for (i) causing the ultrasound transducer controller to
drive at least one segment of the transducer sequentially at each
of a plurality of frequencies within the test range so as to
sonicate the target, (ii) causing the measuring facility to measure
a parameter correlated with an amount of ultrasound energy absorbed
in the target for each of the frequencies, and (iii) for each of
the at least one segment, selecting for subsequent
focused-ultrasound therapy, among the frequencies within the test
range, a frequency corresponding to a value of the measured
parameter that itself corresponds to a maximum amount of ultrasound
energy absorbed in the target.
9. The system of claim 8, wherein the measurement facility
comprises a magnetic-resonance imaging apparatus.
10. The system of claim 8, wherein the ultrasound transducer
comprises a plurality of segments.
11. The system of claim 10, wherein the controller is configured to
cause the ultrasound transducer, during ultrasound therapy, to
drive the segments together, each at its respective selected
frequency.
12. A patient-specific frequency-optimization method for ultrasound
therapy of a target within the patient, the method comprising:
defining a plurality of segments within an ultrasound transducer
array; and separately for each of the segments, driving the segment
successively at each of a plurality of frequencies within a test
frequency range so as to sonicate the target, and measuring a
parameter correlated with an amount of ultrasound energy absorbed
in the target for each of the frequencies; and for each of the
plurality of frequencies, combining values of the parameter
measured for the plurality of segments into a total parameter value
correlated with a total amount of ultrasound energy absorbed in the
target; and selecting for subsequent focused-ultrasound therapy,
among the plurality of frequencies, a frequency corresponding to a
value of the measured total parameter that itself corresponds to a
maximum total amount of ultrasound energy absorbed in the
target.
13. The method of claim 12, wherein the parameter is selected from
the group consisting of a power, an energy, an intensity, an
acoustic force, a tissue displacement, or a temperature.
14. The method of claim 12, wherein the parameter is measured using
thermometry.
15. The method of claim 12, wherein the parameters is measured
using acoustic radiation force imaging.
16. A system for selecting a patient-specific frequency for
ultrasound therapy of a target within the patient, the system
comprising: an ultrasound transducer comprising a plurality of
segments, and an associated controller capable of driving each of
the transducer segments at any of a plurality of frequencies within
a range of frequencies so as to sonicate the target; a measurement
facility for measuring a parameter correlated with an amount of
ultrasound energy absorbed in the target; and a computational
facility for (i) causing the ultrasound transducer controller to
separately drive each of the segments sequentially at each of a
plurality of frequencies within a test range so as to sonicate the
target, (ii) causing the measurement facility to measure a
parameter correlated with an amount of ultrasound energy absorbed
in the target for each of the frequencies, (iii) for each of the
plurality of frequencies, combining values of the parameter
measured for the plurality of segments into a total parameter value
correlated with a total amount of ultrasound energy absorbed in the
target, and (iv) selecting for subsequent focused-ultrasound
therapy, among the plurality of frequencies, an optimal frequency
corresponding to a value of the measured total parameter that
itself corresponds to a maximum total amount of ultrasound energy
absorbed in the target.
17. The system of claim 16, wherein the measurement facility
comprises a magnetic-resonance imaging apparatus.
18. The system of claim 16, wherein the measured parameter is a
tissue displacement.
19. The system of claim 16, wherein the controller is configured to
cause the ultrasound transducer, during ultrasound therapy, to
drive the segments together at the selected optimal frequency.
Description
CROSS-REFERENCE TO RELATED APPLICATION
[0001] This application claims priority to and the benefit of, and
incorporates herein by reference in its entirety, U.S. Provisional
Patent Application No. 61/773,394, filed on Mar. 6, 2013.
TECHNICAL FIELD
[0002] The present invention relates, generally, to
focused-ultrasound therapy, and more particularly to systems and
methods for optimizing the ultrasound frequency for increased
energy deposition at the target.
BACKGROUND
[0003] 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, ultrasonic waves may be used to ablate tumors, eliminating
the need for the patient to undergo invasive surgery. For this
purpose, a piezo-ceramic transducer is placed external to the
patient, but in close proximity to the tissue to be ablated (the
"target"). The transducer converts an electronic drive signal into
mechanical vibrations, resulting in the emission of acoustic waves
(a process hereinafter referred to as "sonication"). The transducer
may be shaped so that the waves converge in a focal zone.
Alternatively or additionally, the transducer may be formed of a
plurality of individually driven transducer elements whose phases
(and, optionally, amplitudes) can each be controlled independently
from one another and, thus, can be set so as to result in
constructive interference of the individual acoustic waves in the
focal zone. Such a "phased-array" transducer facilitates steering
the focal zone to different locations by adjusting the relative
phases between the transducers. Magnetic resonance imaging (MRI)
may be utilized to visualize the focus and target in order to guide
the ultrasound beam.
[0004] FIG. 1 illustrates an exemplary MRI-guided
focused-ultrasound system 100. The system 100 includes a plurality
of ultrasound transducer elements 102, which are arranged in an
array at the surface of a housing 104. The array may comprise a
single row or a matrix, or generally any arrangement, of transducer
elements 102. The array may have a curved (e.g., spherical or
parabolic) shape, as illustrated, 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 elements 102 may be piezoelectric ceramic elements, or
be made of piezo-composite materials or any other materials capable
of converting electrical energy to acoustic energy. To damp the
mechanical coupling between the elements 102, they may be mounted
on the housing 104 using silicone rubber or any other suitable
damping material.
[0005] The transducer elements 102 are driven via separate drive
channels by a control facility 106. For n transducer elements 102,
the control facility 106 may contain n control circuits each
comprising an amplifier and a phase delay circuit, with each
control circuit driving one of the transducer elements 102. The
control facility may split a radio-frequency (RF) input signal,
typically in the range of 0.1 MHz to 4 MHz, into n channels for the
n control circuits. In conventional systems, the control facility
106 is configured to drive the individual transducer elements 102
of the array at the same frequency, but at different phases and
different amplitudes so that they collectively produce a focused
ultrasound beam at a desired location. The control facility 106
desirably provides computational functionality, which may be
implemented in software, hardware, firmware, hardwiring, or any
combination thereof, to compute the required phases and amplitudes
for a desired focus location; these phase/amplitude computations
may include corrections that compensate for aberrations resulting
from ultrasound reflection or refraction at tissue interfaces or
propagation in tissue having various acoustic parameters, which may
be determined based, e.g., on computer tomography (CT) or other
images of the anatomical region of interest. In general, the
control facility 106 may include several separable apparatus, such
as a frequency generator, a beamformer containing the amplifier and
phase delay circuitry, and a computer (e.g., a general-purpose
computer) performing the computations and communicating the phases
and amplitudes for the individual transducers 102 to the
beamformer. Such systems are readily available or can be
implemented without undue experimentation.
[0006] The system 100 further includes an MRI apparatus 108 in
communication with the control facility 106. An exemplary apparatus
108 is illustrated in more detail in FIG. 2. The apparatus 108 may
include a cylindrical electromagnet 204, which generates a static
magnetic field within a bore 206 of the electromagnet 204. During
medical procedures, a patient is placed inside the bore 206 on a
movable support table 208. A region of interest 210 within the
patient (e.g., the patient's head) may be positioned within an
imaging region 212 wherein the magnetic field is substantially
homogeneous. A radio-frequency (RF) transmitter coil 214
surrounding the imaging region 212 emits RF pulses into the imaging
region 212, and receives MR response signals emitted from the
region of interest 210. The MR response signals are amplified,
conditioned, and digitized into raw data using an image-processing
system 216, 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 region (e.g., a tumor) is identified. The
ultrasound phased array 220, disposed within the bore 206 of the
MRI apparatus and, in some embodiments, within the imaging region
212, is then driven so as to focus ultrasound into the treatment
region. The MRI apparatus 108 facilitates visualizing the focus 112
based on an effect it has on the sonicated tissue. For example, any
of a variety of MRI-based thermometry methods may be employed to
observe the temperature increase resulting from ultrasound
absorption in the focus region. Alternatively, MR-based acoustic
radiation force imaging (ARFI) may be used to measure the tissue
displacement in the focus. Such measurements of the focus can serve
as feedback for driving the ultrasound transducer array 220.
[0007] The goal of focused-ultrasound treatment is generally to
maximize the amount of energy absorbed at the target while
minimizing the exposure of healthy tissue surrounding the target,
as well as tissues along the path between transducer and target, to
ultrasound. The degree of ultrasound absorption in tissue is a
function of frequency, given by:
I=I.sub.0e.sup.-2.alpha.fz (1),
where I.sub.0 is the ultrasound intensity at the point of entry
into the tissue (measured in W/cm.sup.2), is the intensity after
beam propagation through the tissue over a distance z (which is
measured in cm), f is the frequency of the ultrasound (measured in
MHz), and a is the absorption coefficient at that frequency
(measured in cm.sup.-1MHz.sup.-1). The higher the product .alpha.f,
the greater the degree of absorption in the target region will be,
but the higher will also be the fraction of ultrasound that is
absorbed on the way to, and therefore never reaches, the target
region. This trade-off can be captured by the fraction E.sub.T of
ultrasound energy absorbed along 1 cm of target tissue at a tissue
depth z (i.e., after beam propagation through a distance z of the
tissue):
E.sub.T=e.sup.-2.alpha.fz(1-e.sup.-2.alpha.f1 cm) (2).
In conventional ultrasound treatment procedures, the ultrasound
frequency is selected based on the above relation to maximize
E.sub.T. This approach, however, fails to account for the effect of
other ultrasound-tissue interactions that affect the energy
deposition at the focus, such as reflection, refraction, and
scattering. In some circumstances, such interactions are
substantial; for example, when focusing ultrasound into the brain,
the beam can be subject to multiple reflections off and between the
cortical layers, as illustrated in FIG. 3. Accordingly, the ability
to refine the frequency selection in order to improve energy
deposition at the target would improve the performance and safety
of ultrasound treatment.
SUMMARY
[0008] The present invention relates to focused-ultrasound
treatment methods that involve determining an optimal
frequency--i.e., one that maximizes the absorption or the acoustic
intensity at the target--within a certain frequency range, as well
as systems for implementing such methods. (The terms "optimal,"
"optimizing," "maximum," "maximizing", etc., as used herein,
generally involve a substantial improvement (e.g., by more than
10%, more than 20%, or more than 30%) over the prior art, but do
not necessarily mean that they achieve the best theoretically
possible frequency, energy absorption, etc. Rather, optimizing the
frequency, or maximizing the energy at the target, involves
selecting the best frequency practically discernible within the
limitations of the utilized technology and method.) The invention
is based on the recognition that the amount of ultrasound energy
absorbed at the target site is greatly affected by tissue
interaction mechanisms other than absorption, and can be
significantly improved by selecting an ultrasound frequency that
deviates from the conventionally calculated absorption-based
frequency.
[0009] Accordingly, embodiments of the present invention take
multiple ultrasound-tissue interactions into account in selecting
the treatment frequency. In principle, this can be accomplished
computationally, by simulating the interactions of the ultrasound
beam with the patient's tissues at various frequencies, using, for
example, a finite-element method. The simulation may be based on a
detailed tissue model as acquired, e.g., by computer tomography or
ultrashort echo-time (TE) MRI; the model generally includes
multiple tissue types or layers (e.g., for ultrasound focusing into
the skull, layers of cortical bone, bone marrow, and soft brain
tissue) and characterizes their respective material properties. It
has been observed, however, that the optimal frequency varies
greatly from person to person despite similar target sites, and
often in a manner that either cannot be adequately captured with
current tissue imaging and modeling techniques or is
computationally so expensive as to be impractical. Therefore, in
preferred embodiments, the optimal frequency is determined
experimentally and individually for each patient. This may be done,
prior to treatment, by measuring ultrasound absorption in the
target (or a quantity indicative thereof) at several frequencies
within a specified range (generally at energy levels low enough to
not cause any damage to the tissue), and identifying the optimal
frequency based on the measurements. This method accounts
implicitly for all (known or unknown) contributing factors to the
amount of ultrasound energy absorbed at the target. Alternatively,
if a particular mechanism, such as reflection, is found to dominate
the attenuation of ultrasound between the transducer and the
target, the effect of that mechanism may be experimentally
quantified, and the frequency selected so as to minimize the
effect. For example, when focusing ultrasound into the brain, the
beam can be subject to multiple reflections off and between the
cortical layers; in this scenario, one way to optimize the
frequency is to measure the total skull reflectance (summing over
contributions from all the reflected beams), and selecting the
frequency for which the reflected beam is minimized.
[0010] Accordingly, in one embodiment, the invention pertains to a
patient-specific frequency-optimization method for ultrasound
therapy of a target within the patient. The method involves
sonicating the target and measuring (e.g., using thermometry) a
parameter (e.g., power, energy, intensity, acoustic force, tissue
displacement, and temperature) associated with the amount of
ultrasound energy absorbed in the target for each of a plurality of
ultrasound frequencies within a test range. In some embodiments,
the transducer includes multiple segments (which may be defined,
e.g., based at least in part on the patient's anatomy), and the
parameter is measured for each test frequency and each segment.
Among the frequencies within the test range, a frequency
corresponding to the value of the measured parameter that itself
corresponds to the maximum amount of ultrasound energy absorbed in
the target is selected (for the entire transducer or each segment).
In some embodiments, the plurality of frequencies within the test
range is defined dynamically based, at least in part, on a value of
the parameter measured for a previously tested frequency. Following
frequency selection, the transducer (or transducer segments) may be
driven at the selected frequency (or frequencies) and at a
therapeutic energy level to thereby sonicate the target; the
therapeutic energy level typically exceeds the energy level of
sonications applied during testing. In multi-segment embodiments,
the segments may be driven sequentially (e.g., cyclically) or
simultaneously, each at its respective selected frequency.
[0011] A further aspect is directed to a system for selecting a
patient-specific frequency for ultrasound therapy of a target
within the patient. The system includes an ultrasound transducer
and an associated controller capable of driving the transducer at
any frequency within a test range of frequencies so as to sonicate
the target, as well as a measurement facility (e.g., an MRI
apparatus) for measuring a parameter correlated with the amount of
ultrasound energy absorbed in the target. The system further has a
computational facility for (i) causing the ultrasound transducer
controller to drive one or more segments of the transducer
sequentially at each of a plurality of frequencies within the test
range so as to sonicate the target, (ii) causing the measuring
facility to measure a parameter correlated with the amount of
ultrasound energy absorbed in the target for each of the
frequencies, and (iii) for each of the segments, selecting for
subsequent focused-ultrasound therapy, among the frequencies within
the test range, a frequency corresponding to the value of the
measured parameter that itself corresponds to a maximum amount of
ultrasound energy absorbed in the target. In embodiments where the
ultrasound transducer has a plurality of segments, the controller
may be configured to cause the ultrasound transducer, during
ultrasound therapy, to drive the segments together, each at its
respective selected frequency. Alternatively, the segments may be
driven sequentially, e.g., cyclically.
[0012] Yet another aspect provides a patient-specific
frequency-optimization method for ultrasound therapy of a target
that involves defining a plurality of segments within an ultrasound
transducer array, and, separately for each of the segments, driving
the segment successively at each of a plurality of frequencies
within a test frequency range so as to sonicate the target. For
each sonication, a parameter correlated with the amount of
ultrasound energy absorbed in the target (e.g., power, energy,
intensity, acoustic force, tissue displacement, and/or temperature)
is measured for each frequency (e.g., using thermometry or acoustic
radiation force imaging). The values of the parameter measured for
the plurality of segments may be combined, for each of the
plurality of frequencies, into a total parameter value correlated
with the total amount of ultrasound energy absorbed in the target.
Among the plurality of frequencies, the frequency corresponding to
the value of the measured total parameter that itself corresponds
to a maximum total amount of ultrasound energy absorbed in the
target is then selected for subsequent therapy.
[0013] In a further aspect, a system for selecting a
patient-specific frequency for ultrasound therapy of a target
within the patient is provided. The system includes an ultrasound
transducer comprising a plurality of segments and an associated
controller capable of driving each of the transducer segments at
any of a plurality of frequencies within a range of frequencies so
as to sonicate the target, as well as a measurement facility (e.g.,
an MRI apparatus) for measuring a parameter correlated with an
amount of ultrasound energy absorbed in the target (such as, e.g.,
tissue displacement). Further, the system includes a computational
facility for (i) causing the ultrasound transducer controller to
separately drive each of the segments sequentially at each of a
plurality of frequencies within a test range so as to sonicate the
target, (ii) causing the measurement facility to measure a
parameter correlated with an amount of ultrasound energy absorbed
in the target for each of the frequencies, (iii) for each of the
plurality of frequencies, combining values of the parameter
measured for the plurality of segments into a total parameter value
correlated with the total amount of ultrasound energy absorbed in
the target, and (iv) selecting for subsequent focused-ultrasound
therapy, among the plurality of frequencies, an optimal frequency
corresponding to the value of the measured total parameter that
itself corresponds to the maximum total amount of ultrasound energy
absorbed in the target. The controller may be configured to cause
the ultrasound transducer, during ultrasound therapy, to drive the
segments together at the selected optimal frequency.
BRIEF DESCRIPTION OF THE DRAWINGS
[0014] The foregoing and the following detailed description will be
more readily understood when taken in conjunction with the
drawings, in which:
[0015] FIG. 1 schematically illustrates an MRI-guided focused
ultrasound system in accordance with various embodiments;
[0016] FIG. 2 illustrates an MRI system in accordance with various
embodiments;
[0017] FIG. 3 illustrates reflection of ultrasound by tissue
boundaries located between the transducer and the treatment target
in a brain-treatment scenario;
[0018] FIG. 4 is a flow chart illustrating a method for optimizing
the sonication frequency in accordance with various
embodiments;
[0019] FIGS. 5A and 5B are graphs of the experimentally determined
and the predicted dependence of energy absorption from the
frequency for an exemplary treatment scenario;
[0020] FIG. 6 illustrates partitioning of an ultrasound transducer
for brain treatment in accordance with one embodiment;
[0021] FIG. 7 is a flow chart illustrating a method for optimizing
the sonication frequencies of multiple transducer segments
separately in accordance with various embodiments; and
[0022] FIG. 8 is a block diagram illustrating a system for
optimizing sonication frequency in accordance with various
embodiments.
DETAILED DESCRIPTION
[0023] In various embodiments, the present invention provides
methods for optimizing the frequency of sonications in
focused-ultrasound procedures for a particular patient; an
exemplary method is illustrated in FIG. 4. After the treatment
configuration has been set up and the patient has been placed in or
relative to the ultrasound transducer and imaging apparatus 108
(e.g., as depicted in FIG. 2), images of the relevant tissue region
may be acquired and processed to identify the target therein (step
400). Then, relative phase and/or amplitude settings of the
ultrasound transducer elements 102 that result in a beam focused at
the target may be computed based on the relative position of the
transducer and target and any a-priori knowledge and/or
image-derived information about the intervening tissues (step 402).
The phase and/or amplitude settings may be refined experimentally
before, after, and/or at one or more times during the
frequency-optimization process based on observations of the focus
quality and/or the focus location relative to the target (step
404); methods for computational and experimental phase/amplitude
determinations and adjustments are well-known to those of skill in
the art. The transducer is then driven in accordance with the
determined phase and amplitude settings to sonicate the target.
[0024] To optimize the frequency of the ultrasound, the target is
sonicated sequentially at different "test frequencies" within a
"test range" of frequencies, and for each tested frequency, a
parameter indicative of energy absorption in the target is
measured. The test range may span the entire range of frequencies
suitable for ultrasound treatment (e.g., in various embodiments,
0.1 MHz to 4 MHz), but is typically a much smaller sub-range
thereof in which the optimal frequency is to be expected. Such a
sub-range may be determined, e.g., based on computational estimates
of the optimal frequency, the results of simulations, or empirical
data acquired for the same organ or tissue in another patient. The
frequencies to be tested may be distributed uniformly or
non-uniformly over the test range. In various embodiments, the
density of test frequencies increases with closer proximity to an
estimated optimal frequency. The test range and the test
frequencies therein may be predetermined, or adjusted dynamically
during the optimization process. For example, in one embodiment,
testing is initially performed at large frequency intervals (e.g.,
in steps of 20 kHz) over a large test range (e.g., from 600 to 750
kHz) to determine a sub-range of frequencies resulting in high
energy absorption at the target, and the optimum frequency is
thereafter determined within the sub-range by testing at smaller
intervals (e.g., in steps of 10 kHz or 5 kHz). In another
embodiment, testing is performed for a sub-set of pre-determined
potential test frequencies, each actual test frequency being
selected from the set of potential test frequencies based on the
results of previous tests.
[0025] Thus, optimizing the frequency involves iteratively setting
a test frequency (step 406), sonicating the target at the selected
frequency (step 408), and quantitatively assessing the resulting
energy absorption at the target (step 410) using, e.g., MRI
thermometry to measure the temperature increase in the target
resulting from the absorbed energy, MR-ARFI to measure the tissue
displacement resulting from acoustic pressure at the target,
ultrasound detection to measure the intensity of the ultrasound
that is reflected (i.e., not absorbed), or generally any
experimental technique for measuring a parameter that correlates
with energy absorption at the target in a known and predictable
manner. The maximum (in the case of, e.g., temperature or pressure)
or minimum (in the case of, e.g., reflection) of the measured
parameter is then determined to identify the test frequency at
which energy absorption at the target is maximized (step 412).
Following frequency optimization, the phase and/or amplitude
settings of the phased-array transducer may be adjusted to optimize
the focus for the selected frequency. Treatment may then commence
at the optimum frequency and phase/amplitude settings (step
414).
[0026] The utility of frequency optimization in accordance herewith
derives from the fact that energy absorption varies significantly
and often nonmonotonically with frequency and the optimum frequency
for a particular patient is typically unpredictable. For example,
FIG. 5A illustrates the ultrasound peak intensity measured at a
number of frequencies between 600 kHz and 760 kHz for an ex-vivo
skull by a hydrophone placed inside the skull. As shown, the peak
intensity achieved at 600 kHz is about 50% higher than that at 720
kHz, and the peak intensity at 740 kHz is more than 30% higher than
that at 720 kHz. Such large variations in intensity over short
frequency ranges are surprising when compared to the intensity
variation with frequency that results from absorption only, as
modeled with equation (2). (FIG. 5B shows, for example, the
fraction of energy E.sub.T absorbed at a 1 cm target located 6 cm
inside soft tissue having an absorption coefficient of .alpha.=0.06
Napiers/cm/MHz (which is approximated for brain tissue) using
equation (2); as can be seen, the absorbed energy varies smoothly
as a function of ultrasound frequency and does not contain a sudden
drop such as the experimentally found minimum at 720 Hz reflected
in FIG. 5A.) A similar measurement for a different skull may reveal
similarly high variations in peak intensity, but generally with a
different frequency-dependency (e.g., different frequencies at
which the intensity is minimized or maximized).
[0027] In certain treatment scenarios, ultrasound waves propagating
towards the target from different directions may encounter a highly
variable anatomy, such as different thicknesses of tissue layers
and different acoustic impedances. For example, during transcranial
ultrasound treatment procedures, acoustic beams coming from
different directions may encounter cortical skull bone of different
thicknesses, bone marrow of different thicknesses, etc., as well as
variability of absorption coefficients in the soft tissue. In
various other clinical scenarios, some of the soft tissue may have
much higher calcification contents than expected and, thus, a much
higher attenuation in the near field. In these cases, overall
energy deposition at the target may be improved by optimizing the
frequency separately for different regions or segments of the
transducer array, and then driving the transducer, simultaneously
or sequentially, at multiple frequencies for the different
segments, rather than at a single frequency for the whole
transducer.
[0028] The partitioning of the transducer array (or grouping of
transducer elements) for such segment-based frequency optimization
may be based on the similarity of the relevant paths through the
anatomy for different transducer elements, the ability to generate
a focus of sufficiently high quality with each transducer segment
(which depends, e.g., on the total number of elements in the
segment), and, ultimately, the combined therapeutic effect provided
by all transducer segments. If, for example, the array is divided
into too many segments that are too small (in an attempt to
maximize the benefits of frequency optimization), the individual
segments may fail to generate sufficiently sharp foci because they
no longer have effective focusing ability, and the beam will
disperse. FIG. 6 illustrates a suitable partitioning of an
approximately semi-spherical transducer used for brain-tumor
treatment. In the depicted embodiment, the transducer array is
divided into seven segments, a central "cap" and six similarly
sized surrounding "tiles." In general, the transducer may have more
or fewer segments; typical transducer divisions include between
three and fifteen segments.
[0029] FIG. 7 illustrates a method for optimizing the frequencies
of a multi-segment transducer. After the target within the patient
has been identified (e.g., based on images) in step 400 and the
transducer segments have been defined (step 700), the focus of each
segment may be separately optimized by setting and adjusting the
relative phases and/or amplitudes between the transducer elements
of that segment (steps 402, 404) so as to generate a high-quality
focus at the target location, and further determining the frequency
dependence, within a test range, of energy absorption at the target
in the manner described above (steps 406, 408, 410). In some
embodiments, the optimum frequency (i.e., the frequency that
maximizes energy absorption at the target) is identified separately
for each segment (step 412); to treat the target, the separately
optimized transducer segments may then be driven sequentially or
together, each at its own optimum frequency (step 702). For
example, the segments may be driven separately and cyclically such
that ultrasound from segments driven at different frequencies does
not destructively interfere, and at the same time that energy
deposited in the target does not significantly dissipate during
each sonication cycle. In alternative embodiments, a single
frequency that maximizes the overall absorption of ultrasound
energy received from the various segments is inferred from the
individual measured frequency dependencies in a manner explained
further below (step 704), and the various segments, although tested
separately, are all driven at that same, overall-optimal frequency
during treatment (step 706). Driving the segments at a single,
common frequency may, advantageously, result in a smaller focus
with higher peak intensity as it ensures constructive interference
of the ultrasound waves from different segments.
[0030] Various techniques can be used to measure energy absorption
in the target--directly or indirectly via a related physical
quantity--to then maximize the amount of energy absorbed via
selection of an optimal frequency. One approach is to monitor the
temperature at the target, which increases proportionally to the
amount of energy absorbed. Thermometry methods may be based, e.g.,
on MRI, and may utilize a system such as that depicted in FIG. 2,
in conjunction with suitable image-processing software. Among
various methods available for MR thermometry, the proton resonance
frequency (PRF) shift method is often the method of choice due to
its excellent linearity with respect to temperature change,
near-independence from tissue type, and temperature map acquisition
with high spatial and temporal resolution. The PRF shift method
exploits the phenomenon that the MR resonance frequency of protons
in water molecules changes linearly with temperature. Since the
frequency change with temperature is small, only -0.01 ppm/.degree.
C. for bulk water and approximately -0.0096 to -0.013 ppm/.degree.
C. in tissue, the PRF shift is typically detected with a
phase-sensitive imaging method in which the imaging is performed
twice: first to acquire a baseline PRF phase image prior to a
temperature change and then to acquire a second phase image after
the temperature change, thereby capturing a small phase change that
is proportional to the change in temperature. A map of temperature
changes may then be computed from the MR images by determining, on
a pixel-by-pixel basis, phase differences between the baseline
image and the treatment image, and converting the phase differences
into temperature differences based on the PRF temperature
dependence while taking into account imaging parameters such as the
strength of the static magnetic field and echo time (TE) (e.g., of
a gradient-recalled echo). Various alternative or advanced methods
may be used to compensate for patient motion, magnetic-field
drifts, and other factors that affect the accuracy of PRF-based
temperature measurements; suitable methods known to those of skill
in the art include, e.g., multibaseline and referenceless
thermometry.
[0031] Using PRF-based or any other suitable thermometry method,
the optimal ultrasound frequency within a specified range can be
determined by driving the transducer successively at a number of
different frequencies (e.g., at specified frequency intervals
within the selected range), while keeping the power and duration
(or, more generally, the total transmitted energy) the same, to
focus ultrasound at the target site of a particular patient, and
measuring the temperature increase at the target for each such
sonication. This is done prior to treatment; thus, in order to
avoid tissue damage, the ultrasound transducer is driven at much
lower power than subsequently during treatment (while being high
enough to obtain a meaningful signal-to-noise ratio). Further, to
ensure the comparability of the measurements for different
frequencies, each temperature increase is preferably measured
against a similar baseline temperature. This can be accomplished by
waiting a sufficient amount of time following each sonication to
let the tissue cool back down to a temperature approximately equal
to the baseline temperature and using sufficiently low energy such
that effects on the tissue due to temperature changes are limited
(e.g., clinically insignificant). When the temperature increase has
been measured at the various discrete frequencies within the range
of interest, the frequency for which the temperature increase is
maximum is selected for operating the transducer during subsequent
treatment. In embodiments where the frequency is optimized
separately for multiple transducer segments, this procedure is
performed for each segment. During treatment, the various segments
may be driven together or alternately (e.g., cycling through the
segments), each at its respective optimum frequency.
[0032] Another quantity usefully related to ultrasound energy
absorption in tissue is the temporary local displacement of that
tissue due to acoustic radiation pressure, which is highest at the
focus (where the waves converge and highest intensity is achieved).
The ultrasound pressure creates a displacement field that directly
reflects the acoustic field. The displacement field can be
visualized, using a technique such as MR-ARFI, by applying
transient-motion or displacement-sensitizing magnetic field
gradients to the imaging region by gradient coils, which are part
of standard MRI apparatus (such as apparatus 108 depicted in FIG.
2) and are typically located near the cylindrical electromagnet
204. When the ultrasound pulse is applied in the presence of such
gradients, the resulting displacement is directly encoded into the
phase of the MR response signal. For example, the gradient coils
and transducer may be configured such that the ultrasound pulse
pushes material near the focus towards regions of the magnetic
field with higher field strengths. In response to the resulting
change in the magnetic field, the phase of the MR response signal
changes proportionally, thereby encoding in the signal the
displacement caused by the ultrasound radiation pressure. Further
detail about MR-ARFI is provided in U.S. patent application Ser.
No. 12/769,059, filed on Apr. 28, 2010, the entire disclosure of
which is hereby incorporated herein by reference.
[0033] For a given transducer arrangement, the tissue displacement
measured with MR-ARFI is directly proportional to the ultrasound
intensity. Advantageously, the energies required to obtain good
displacement signals are very small compared to typical therapeutic
energies (and are achieved by sonication for very short periods,
e.g., about 20 ms), rendering ARFI a suitable candidate for
pre-treatment optimizations. However, the displacement forces
generated by ultrasound waves coming from different directions
partially cancel each other. Therefore, when using MR-ARFI to tune
the frequency for maximum energy absorption at the focus, the
frequency is preferably optimized separately for multiple
transducer segments--each covering not too large a solid
angle--even when a single frequency is selected in the end to drive
the entire transducer array; the overall optimal frequency is
derived from the optimal frequencies for the individual segments by
combining them in a suitable manner (as explained below). (In
contrast to radiation forces, thermal energies attributable to
different segments and ultrasound wave directions accumulate
without cancellations. Thus, when using thermometry for frequency
optimization, the procedure may be performed on the transducer
array as a whole.)
[0034] Since the purpose of various embodiments is to find the
optimal treatment frequency for a specific patient by a procedure
that is part of the treatment flow, that procedure is preferably
short, e.g., on the order of several minutes. This is achievable
with ARFI if neither the number of transducer segments nor the
number of discrete frequencies tested is too large. For example, to
determine the best frequency for a curved (e.g., hemispherical)
ultrasound transducer used in brain tumor treatment, the transducer
may be divided, e.g., into seven segments (a cap and six tiles, as
illustrated in FIG. 6) or even in only four segments (a cap and
three tiles). The segments may be defined based on generic criteria
such as the solid angles they cover, or based on more detailed
criteria regarding, e.g., the particular patient's anatomy. Tissue
displacement may be measured for each segment at about ten
different frequencies or less, for example, at nine frequencies at
20 kHz intervals within a range from 600 kHz to 760 kHz (as shown
in FIG. 5A). Denoting the number of segments with Ns and the number
of discrete frequencies with N.sub.f, a total of NsN.sub.f
measurements are required.
[0035] For each segment, a single scan covering all frequencies may
be performed at a lateral plane (or multiple, e.g., three, parallel
planes) passing through the focus of that segment (which may be
slightly displaced from the theoretical focus location achieved
when all segments operate together). The MR scan is synchronized
with ultrasound pulses that generate the tissue displacement. In
some cases, the relative phases between the elements of the
transducer segment are corrected, e.g., based on CT images or other
a-priori knowledge, to compensate, e.g., for bone variability.
Using a state-of-the-art focused-ultrasound/MR-ARFI system, this MR
scan requires, in one embodiment, about 20 seconds of preparation
(e.g., download of the PSD and pre-scan for optimizing scanning
parameters), about 3 seconds to obtain a reference image for ARFI,
and about 3 seconds per frequency to generate a focus and measure
the resulting tissue displacement (amounting to 27 seconds for 9
frequencies). The total time for determining the optimal frequency
for one segment is, thus, less than one minute; efficiency gains
can result from a common overhead and a common reference used for
all frequencies. (The computational time to process the data is
negligible compared with the time for acquiring the measurements.)
The total time required for an entire transducer having seven
segments is on the order of seven minutes in the above example.
[0036] The tissue displacements measured for all segments and
frequencies may be stored in an N.sub.f.times.N.sub.s array
D.sub.ij, where row i corresponds to frequency f.sub.i, and column
j corresponds to transducer segment j. If the segments are to be
driven at different frequencies, the optimal frequencies are
determined by finding the maximum entry i in each column D.sub.i 1,
D.sub.i 2, . . . D.sub.i Ns, and selecting frequency f.sub.i for
the corresponding segment.
[0037] If a single optimum frequency is to be determined for the
transducer as a whole, the entries across the columns in each line
i (i.e., for each frequency f.sub.i) are combined into new values
D.sub.combined.sub.--.sub.i that capture the contributions of all
the segments. If different segments are driven at different total
powers (e.g., proportional to their respective areas) during the
measurements, the individual measured displacements D.sub.ij are
typically first normalized accordingly. Then, the combined
displacements D.sub.combined.sub.--.sub.i are computed in one of
several ways that result in values well-correlated to the combined
therapeutic effect of all segments (some, but not all of which have
physical interpretations). For example, in some embodiments, the
combined displacement value is calculated by summing over the
square roots of the individual displacements and squaring the
result, yielding a value proportional to the total peak intensity
at the focus (provided that the relative phasing between the
sub-foci generated with different segments is correct, which can be
assured by computer-tomography-based corrections):
D combined _ i = ( j = 1 N s D ij ) 2 ##EQU00001##
In other embodiments, the combined displacement value is simply the
sum of the absolute values of individual displacements, and is
proportional to the total power applied in the focus region:
D combined _ i = ( j = 1 N s D ij ) ##EQU00002##
In yet another embodiment, the L.sub.2-norm of the displacement
vector D.sub.i is calculated:
D combined _ i = j = 1 N s ( D ij ) 2 ##EQU00003##
In which manner the combined displacement is calculated may depend,
e.g., on which parameter is to be optimized (e.g., peak pressure or
total power). The above three embodiments are merely examples;
similarly, other norms (or variations that are not norms) may be
used as long as they correlate with the combined contribution of
the segments. The elements of the combined vector D.sub.combined
are proportional (or correlated) to the total heat depositions at
the various frequencies. Thus, the optimal frequency for the
transducer can be determined by identifying the frequency at which
the maximum combined displacement will occur. Of course,
determining an overall-optimal frequency from measurements taken
separately for multiple segments is not limited to measurements of
tissue displacement; in embodiments where a parameter other than
tissue displacement is used as an indicator for the energy
disposition at the target, measurements of this parameters can be
similarly combined across segments to find an overall optimum.
[0038] The approach described above can be implemented with a
suitable computational facility operating in conjunction with one
more ultrasound transducers and apparatus (e.g., an MRI apparatus)
for measuring the energy deposited at the focus, or another
parameter indicative thereof. The computational facility may be
implemented in hardware (e.g., circuitry), software, firmware, or
any suitable combination thereof, and may be integrated with the
ultrasound controller (e.g., control facility 106 of FIG. 1) and/or
the imaging apparatus or other device for measuring energy
deposition at the target (e.g., image-processing system 216 of FIG.
2), or provided as a separate device in communication
therewith.
[0039] In some embodiments, the computational facility is
implemented with a suitably programmed general-purpose computer;
FIG. 8 shows an exemplary embodiment. The computer 800 includes one
or more processors 802 (e.g., a CPU) and associated system memory
804 (e.g., RAM, ROM, and/or flash memory), user input/output
devices (such as a screen 806 and a keyboard, mouse, etc. 808), and
typically one or more (typically non-volatile) storage media 810
(e.g., a hard disk, CCD, DVD, USB memory key, etc.) and associates
drives. The various components may communicate with each other and
with external devices (such as the ultrasound transducer and/or the
imaging apparatus) via one or more system buses 812.
[0040] The system memory 804 contains instructions, conceptually
illustrated as a group of modules, that control the operation of
the processor 802 and its interaction with the other hardware
components. An operating system 820 directs the execution of
low-level, basic system functions such as memory allocation, file
management and operation of the peripheral devices. At a higher
level, one or more service applications provide the computational
functionality required for frequency optimization in accordance
herewith. For example, as illustrated, the system may include an
image-processing module 822 that allows analyzing images from the
MRI (or other imaging) apparatus to identify the target therein and
visualize the focus to ensure that it coincides with the target; a
transducer-control module 824 for computing the relative phases and
amplitudes of the transducer elements based on the target location
as well as for controlling ultrasound-transducer operation during
both frequency optimization and treatment; and a
frequency-optimization module 826 providing functionality to
acquire data about the frequency-dependence of the energy
absorption at the target and select an optimum frequency (or
multiple respective optimum frequencies for various transducer
segments) based thereon. More specifically, a test sub-module 828
may determine and/or receive input specifying the test range and
test frequencies, direct the transducer-control module 824 to
sequentially sonicate the target at these frequencies, and receive
and/or analyze image or other data that allows quantifying the
energy absorbed at the target for each sonication. Based on this
information, a frequency-selection module 830 may determine the
frequency or frequencies (for multiple individually optimized
segments) that maximize energy absorption at the target, or combine
the measurements of the absorption-related parameter across
transducer segments (e.g., by computing one of the norms discussed
above) to find a frequency that maximizes the overall amount of
energy absorbed at the target.
[0041] Of course, the depicted organization of the computational
functionality into various modules is but one possible way to group
software functions; as a person of skill in the art will readily
appreciate, fewer, more, or different modules may be used to
facilitate frequency-optimization in accordance herewith. However
grouped and organized, software may be programmed in any of a
variety of suitable programming languages, including, without
limitation, C, C++, Fortran, Pascal, Basic, Python, an assembly
language, or combinations thereof. Furthermore, as an alternative
to software instructions executed by a general-purpose processor,
some or all of the functionality may be provided with programmable
or hard-wired custom circuitry, including, e.g., a digital signal
processor, programmable gate array, application-specific integrated
circuit, etc.
[0042] The terms and expressions employed herein are used as terms
and expressions of description and not of limitation, and there is
no intention, in the use of such terms and expressions, of
excluding any equivalents of the features shown and described or
portions thereof. In addition, having described certain embodiments
of the invention, it will be apparent to those of ordinary skill in
the art that other embodiments incorporating the concepts disclosed
herein may be used without departing from the spirit and scope of
the invention. For example, instead of MR-based thermometry or
ARFI, any non-invasive imaging technique capable of measuring the
(physical or therapeutic) effect of the acoustic beam at the focus
may generally be used to select an optimal frequency (or multiple
optimal frequencies for different segments) in accordance herewith.
Accordingly, the described embodiments are to be considered in all
respects as only illustrative and not restrictive.
* * * * *