U.S. patent application number 13/044948 was filed with the patent office on 2011-06-30 for system and methods of deep brain stimulation for post-operation patients.
This patent application is currently assigned to VANDERBILT UNIVERSITY. Invention is credited to Pierre-Francois Dominique D'haese, Benoit M. Dawant, Peter E. Konrad.
Application Number | 20110160800 13/044948 |
Document ID | / |
Family ID | 38288165 |
Filed Date | 2011-06-30 |
United States Patent
Application |
20110160800 |
Kind Code |
A1 |
Dawant; Benoit M. ; et
al. |
June 30, 2011 |
SYSTEM AND METHODS OF DEEP BRAIN STIMULATION FOR POST-OPERATION
PATIENTS
Abstract
A method for programming a deep brain stimulator implanted in a
target region of a brain of a living subject for optimal
stimulation, wherein the deep brain stimulator comprises at least
one electrode having a plurality of electrode contacts spaced apart
from each other, and any portion of the brain of the living subject
is identifiable by a set of corresponding spatial coordinates. In
one embodiment, the method comprises the steps of creating an
efficacy atlas in which any spatial coordinates for a position in a
target region of the brain of the living subject are related to a
position with corresponding atlas coordinates in the efficacy
atlas, and each position in the atlas coordinates of the efficacy
atlas is associated with an efficacy of stimulation at a
corresponding position in the spatial coordinates of the brain of
the living subject; acquiring a position of each electrode contact
of the at least one electrode in the spatial coordinates of the
brain of the living subject; mapping the acquired position of each
electrode contact of the at least one electrode in the spatial
coordinates of the brain of the living subject onto a corresponding
position in the efficacy atlas so as to determine the efficacy of
stimulation at the acquired position in the spatial coordinates of
the brain of the living subject; and selecting one or more
electrode contacts having the highest efficacy for stimulation.
Inventors: |
Dawant; Benoit M.;
(Nashville, TN) ; D'haese; Pierre-Francois Dominique;
(Nashville, TN) ; Konrad; Peter E.; (Old Hickory,
TN) |
Assignee: |
VANDERBILT UNIVERSITY
Nashville
TN
|
Family ID: |
38288165 |
Appl. No.: |
13/044948 |
Filed: |
March 10, 2011 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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11653599 |
Jan 16, 2007 |
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13044948 |
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60758882 |
Jan 13, 2006 |
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Current U.S.
Class: |
607/59 |
Current CPC
Class: |
A61N 1/0534 20130101;
A61N 1/36082 20130101 |
Class at
Publication: |
607/59 |
International
Class: |
A61N 1/36 20060101
A61N001/36 |
Goverment Interests
STATEMENT OF FEDERALLY-SPONSORED RESEARCH
[0003] The present invention was made with Government support under
a contract No. 1R21 CA89657-01A2 awarded by NIH/NCI. The United
States Government may have certain rights to this invention
pursuant to this grant.
Claims
1-14. (canceled)
15. A system for programming a deep brain stimulator implanted in a
target region of a brain of a living subject for optimal
stimulation, wherein the deep brain stimulator comprises at least
one electrode having a plurality of electrode contacts spaced apart
from each other, and wherein any portion of the brain of the living
subject is identifiable by a set of corresponding spatial
coordinates, comprising: (a) an efficacy atlas in which each
position in the atlas coordinates of the efficacy atlas is
associated with an efficacy of stimulation at a corresponding
position in the spatial coordinates of the brain of the living
subject; (b) means for acquiring a position of each electrode
contact of the at least one electrode in the spatial coordinates of
the brain of the living subject; and (c) a controller at least
communicatable with the efficacy atlas and adapted for mapping the
acquired position of each electrode contact of the at least one
electrode in the spatial coordinates of the brain of the living
subject onto a corresponding position in the atlas coordinates of
the efficacy atlas so as to determine the efficacy of stimulation
at the acquired position in the spatial coordinates of the brain of
the living subject, and selecting one or more electrode contacts
having the highest efficacy for stimulation.
16. The system of claim 15, wherein the efficacy of stimulation at
a position in the spatial coordinates of the brain of the living
subject is (a) proportional to a percent of loss of rigidity,
L.sub.R; (b) proportional to a therapeutic window that equals to
the difference between a voltage, V, applied to the position for
achieving the loss of rigidity and a voltage, V.sup.SE, applied to
the position for which side effects occur; and (c) inversely
proportional to the voltage V.
17. The system of claim 16, wherein the efficacy of stimulation at
a position is corresponding to the probability of the stimulation
to be clinically effective at the position.
18. The system of claim 15, further comprising a data storage
device for storing the efficacy atlas, the data storage device
configured to be in communication with the controller.
19. The system of claim 18, further comprising a database stored in
the data storage device, wherein the database comprises an
electrophysiological atlas containing electrophysiological
information acquired from a brain of each of a population of living
subjects and related to atlas coordinates of the
electrophysiological atlas.
20. The system of claim 19, wherein the atlas coordinates of the
efficacy atlas are substantially coincident with the atlas
coordinates of the electrophysiological atlas.
21. The system of claim 19, wherein the electrophysiological
information comprises at least intra-operative information for each
of the population of living subjects.
22. The system of claim 21, wherein the intra-operative information
comprises at least specific information associated with at least
one stimulation electrode, wherein the information includes
voltages applied to the at least one stimulation electrode, a
response of a living subject undergoing treatment to the
stimulation, differences in voltage between disappearance of
symptoms and appearance of side effects, and a position of the at
least one stimulation electrode.
23. The system of claim 22, wherein the response of the living
subject undergoing treatment to the stimulation includes loss of
rigidity, location where the loss of rigidity is observed,
appearance of side effects, and/or location affected by these side
effects.
24. The system of claim 23, wherein the efficacy atlas is created
by the steps of: (a) obtaining stimulation data corresponding to a
target region in which a deep brain stimulator is implanted from
the database, wherein the stimulation data comprise M.times.N sets
of intra-operatively acquired stimulation signals, {V.sub.ij,
L.sub.ij.sup.R, V.sub.ij.sup.SE}, and their corresponding
stimulation positions, {x.sub.j, y.sub.j, z.sub.j}, wherein i=1, 2,
. . . , M, M being a positive integer and the number of the
population of living subjects from which the stimulation signals
are acquired and stored in the database, and j=1, 2, . . . , N, N
being a positive integer and the number of positions at which the
stimulation takes place for each of the population of living
subjects, and wherein V.sub.ij, L.sub.ij.sup.R, V.sub.ij.sup.SE are
a stimulation voltage, a percent of loss of rigidity caused by the
stimulation voltage, and a voltage for which side effects occur,
respectively, at the j-th stimulation position of the i-th living
subject; (b) choosing a local efficacy of stimulation, E.sub.ij, at
the j-th stimulation position (x.sub.j, y.sub.j, z.sub.j) for the
i-th living subject with a Gaussian curve, F.sub.ij, in the form
of: wherein the local F ij = E ij * exp [ - ( x j 2 + y j 2 + z j 2
2 V ij 2 ) ] , ##EQU00008## efficacy of stimulation E ij = L ij R *
( V ij SE - V ij ) * 1 V ij ; ##EQU00009## and wherein the height
of the Gaussian curve F.sub.ij is a function of the local efficacy
of stimulation E.sub.ij, and the radius of the Gaussian curve
F.sub.ij is a function of the stimulation voltage V.sub.ij; (c)
repeating step (b) for each of the population of living subjects,
i=1, 2, . . . , M, so as to obtain M sets of Gaussian curves
{F.sub.ij} for the j-th stimulation position (x.sub.j, y.sub.j,
z.sub.j); (d) averaging the M sets of Gaussian curves {F.sub.ij} to
obtain an efficacy of stimulation at the j-th stimulation position
(x.sub.j, y.sub.j, z.sub.1), which is equal to the mean value of
the M sets of Gaussian curves {F.sub.ij}; and (e) repeating steps
(b)-(d) for each of the stimulation positions, j=1, 2, . . . , N,
to obtain N efficacies of stimulation respectively for the N
stimulation positions, thereby creating the efficacy atlas.
25. The system of claim 24, wherein the efficacy atlas comprises at
least one stimulation map having at least one stimulation region
related to the target region of the brain of the living subject for
optimal stimulation.
26. The system of claim 21, wherein the intra-operative information
comprises at least specific information associated with a deep
brain stimulator implanted in a target region of a brain of a
living subject, wherein the specific information includes a
position of each electrode contact of the deep brain stimulator,
and a voltage, frequency and pulse width of stimulation at the
position.
27. The system of claim 26, wherein the acquiring means comprises a
device for obtaining the position of each electrode contact of the
at least one electrode from the database.
28. The system of claim 15, wherein the acquiring means comprises a
device for acquiring the position of each electrode contact of the
at least one electrode post-operatively from the target region of
the brain of the living subject in which the deep brain stimulator
is implanted.
29. The system of claim 15, further comprising a non-rigid
registration algorithm stored in a memory that is in communication
with the controller.
30-36. (canceled)
37. A system for programming a deep brain stimulator implanted in a
target region of a brain of a living subject for optimal
stimulation, wherein the deep brain stimulator comprises at least
one electrode having a plurality of electrode contacts spaced apart
from each other, and wherein any portion of the brain of the living
subject is identifiable by a set of corresponding spatial
coordinates, comprising: (a) a data storage device; (b) a database
stored in the data storage device, comprising an
electrophysiological atlas containing electrophysiological
information acquired from each of the population of living subjects
and related to atlas coordinates of the electrophysiological atlas;
and (c) a controller in communication with the data storage device
and adapted for programmably interfacing with the database for
creating an efficacy atlas in which a position in atlas coordinates
of the efficacy atlas is related to a corresponding position in
spatial coordinates of the brain of the living subject, and vice
versa, and each position in atlas coordinates of the efficacy atlas
is associated with an efficacy of stimulation at a corresponding
position in spatial coordinates of the brain of the living
subject.
38. The system of claim 37, wherein the efficacy atlas comprises at
least one stimulation map having at least one stimulation region
related to the target region of the brain of the living subject for
optimal stimulation.
39. The method of claim 37, wherein the atlas coordinates of the
efficacy atlas are substantially coincident with the atlas
coordinates of the electrophysiological atlas.
40. The system of claim 37, wherein the controller is adapted for
programmably mapping a position of each electrode contact of the at
least one electrode in the spatial coordinates of the brain of the
living subject onto a corresponding position in the atlas
coordinates of the efficacy atlas so as to determine the efficacy
of stimulation at the acquired position in the spatial coordinates
of the brain of the living subject, and selecting one or more
electrode contacts having the highest efficacy for stimulation.
41. A system for programming a deep brain stimulator implanted in a
target region of a brain of a living subject for optimal
stimulation, wherein the deep brain stimulator comprises at least
one electrode having a plurality of electrode contacts spaced apart
from each other, and wherein any portion of the brain of the living
subject is identifiable by a set of corresponding spatial
coordinates, comprising: (a) a data storage device; and (b) an
efficacy atlas stored in the data storage device, wherein each
position in atlas coordinates of the efficacy atlas is associated
with an efficacy of stimulation at a corresponding position in
spatial coordinates of the brain of the living subject.
42. The system of claim 41, wherein the efficacy atlas comprises at
least one stimulation map having at least one stimulation region
related to the target region of the brain of the living subject for
optimal stimulation.
43. The system of claim 41, further comprising a controller in
communication with the data storage device and adapted for
programmably mapping a position of each electrode contact of the at
least one electrode in the spatial coordinates of the brain of the
living subject onto a corresponding position in the atlas
coordinates of the efficacy atlas so as to determine the efficacy
of stimulation at the acquired position in the spatial coordinates
of the brain of the living subject, and selecting one or more
electrode contacts having the highest efficacy for stimulation.
44. Software stored on a computer readable medium for causing a
computing system to perform functions comprising: (a) creating an
efficacy atlas in which a position in atlas coordinates of the
efficacy atlas is related to a corresponding position in spatial
coordinates of the brain of the living subject, and each position
in the atlas coordinates of the efficacy atlas is associated with
an efficacy of stimulation at a corresponding position in the
spatial coordinates of the brain of the living subject; (b)
acquiring a position of each electrode contact of the at least one
electrode in the spatial coordinates of the brain of the living
subject; (c) mapping the acquired position of each electrode
contact of the at least one electrode in the spatial coordinates of
the brain of the living subject onto a corresponding position in
the atlas coordinates of the efficacy atlas so as to determine the
efficacy of stimulation at the acquired position in the spatial
coordinates of the brain of the living subject; and (d) selecting
one or more electrode contacts having the highest efficacy for
stimulation.
Description
CROSS-REFERENCE TO RELATED PATENT APPLICATION
[0001] This application claims the benefit, pursuant to 35 U.S.C.
.sctn.119(e), of U.S. provisional patent application Ser. No.
60/758,882, filed Jan. 13, 2006, entitled "SYSTEM AND METHODS OF
DEEP BRAIN STIMULATION FOR POST-OPERATION PATIENTS," by Benoit M.
Dawant, Pierre-Francois Dominique D'Haese, and Peter E. Konrad,
which is incorporated herein by reference in its entirety.
[0002] Some references, which may include patents, patent
applications and various publications, are cited and discussed in
the description of this invention. The citation and/or discussion
of such references is provided merely to clarify the description of
the present invention and is not an admission that any such
reference is "prior art" to the invention described herein. All
references cited and discussed in this specification are
incorporated herein by reference in their entireties and to the
same extent as if each reference was individually incorporated by
reference. In terms of notation, hereinafter, "[n]" represents the
nth reference cited in the reference list. For example, [7]
represents the 7th reference cited in the reference list, namely,
P. F. D'Haese, E. Cetinkaya, P. E. Konrad, C. Kao, B. M. Dawant,
"Computer-aided placement of deep brain stimulators: from planning
to intraoperative guidance" IEEE Transactions on Medical Imaging,
vol. 24 (11), pp. 1469-78, November 2005.
FIELD OF THE INVENTION
[0004] The present invention generally relates to deep brain
stimulation, and in particular to system and methods of deep brain
stimulation for post-operation patients.
BACKGROUND OF THE INVENTION
[0005] Since its first Food and Drug Administration (FDA) approval
in 1998, deep brain stimulation (DBS) has gained significant
popularity in the treatment of a variety of brain-controlled
disorders, including movement disorders [3, 4]. The therapy of the
DBS has significant applications in the treatment of tremor,
rigidity, and drug induced side effects in patients with
Parkinson's disease and essential tremor. Such treatment involves
placement of a DBS electrode lead through a burr hole drilled in
the patient's skull, and then applying appropriate stimulation
signals through the electrode lead to the physiological target.
[0006] Usually, after the surgery of DBS implantation, the patient
leaves the hospital with the stimulation system such as an internal
pulse generator turned off, since transient lesional effects
associated with microscopic brain edema caused by the surgery may
interfere with DBS programming and lead to multiple adjustments in
the parameter settings. The stimulation system is turned on
typically about 1-5 weeks after the surgery is performed, for
stimulation. This allows the patient to recover from the surgery
and provides enough time for the transient lesional effects to
resolve. The stimulation is accomplished by programmably applying
appropriate stimulation signals to one or more electrode contacts
of each implanted electrode. Thus, finding the optimal programming
parameters so that it efficiently stimulates the target of interest
is crucial to the BDS. Detailed principles and methods used to
select the optimal programming parameters have been presented by
different authors [1, 2].
[0007] Briefly, the first step in postoperative programming is the
examination of the effectiveness and side effects induced by each
individual contact. The electrode contacts are sequentially
evaluated in a monopolar configuration in an effort to determine
the contact that produces best compromise. Frequency and pulse
width of the stimulation signals are typically kept at constant
settings of about 130-180 Hz and about 60-120 .mu.s, respectively.
Amplitude is steadily increased to the tolerance level of the
patient or until side effects occur. Repeating motor evaluation is
then performed to assess the efficacy of stimulation. About ten to
15 minutes are allowed to pass between trials of separate contacts
to allow the effects from previous stimulations to disappear. If a
satisfactory result cannot be achieved with monopolar stimulation,
more complex arrays including bipolar, tri-polar, quadric-polar, or
multiple cathodes are tried. The initial programming session, as
described above, can take several hours and requires continuous
feedback from the patient to ascertain the degree benefits and to
identify any side effects. This can be very taxing, especially when
patients are kept off of medication for long periods of time.
Furthermore, optimal programming may take several trials over many
months to achieve, which can be frustrating to both patients and
their attending health care professionals.
[0008] Automated selection of the optimal contact would facilitate
the programming process and reduce the length of time required to
determine optimum programming and thus be beneficial to the
patients.
[0009] Therefore, a heretofore unaddressed need exists in the art
to address the aforementioned deficiencies and inadequacies.
SUMMARY OF THE INVENTION
[0010] In one aspect, the present invention relates to a method for
programming a deep brain stimulator implanted in a target region of
a brain of a living subject for optimal stimulation, where the deep
brain stimulator comprises at least one electrode having a
plurality of electrode contacts spaced apart from each other, and
any portion of the brain of the living subject is identifiable by a
set of corresponding spatial coordinates.
[0011] In one embodiment, the method includes the steps of (i)
creating an efficacy atlas in which any spatial coordinates for a
position in a target region of the brain of the living subject are
related to a position with corresponding atlas coordinates in the
efficacy atlas, and each position in the atlas coordinates of the
efficacy atlas is associated with an efficacy of stimulation at a
corresponding position in the spatial coordinates of the brain of
the living subject; (ii) acquiring a position of each electrode
contact of the at least one electrode in the spatial coordinates of
the brain of the living subject; (iii) mapping the acquired
position of each electrode contact of the at least one electrode in
the spatial coordinates of the brain of the living subject onto a
corresponding position in the efficacy atlas so as to determine the
efficacy of stimulation at the acquired position in the spatial
coordinates of the brain of the living subject; and (iv) selecting
one or more electrode contacts having the highest efficacy for
stimulation.
[0012] In one embodiment, the mapping step is performed with a
non-rigid registration algorithm.
[0013] In one embodiment, the efficacy atlas comprises at least one
stimulation map having at least one stimulation region
corresponding to the target region of the brain of the living
subject for optimal stimulation.
[0014] The efficacy of stimulation at a position is corresponding
to the probability of the stimulation to be clinically effective at
the position. In one embodiment, the efficacy of stimulation at a
position in the spatial coordinates of the brain of the living
subject is (1) proportional to a percent of loss of rigidity,
L.sup.R; (2) proportional to a therapeutic window that equals to
the difference between a voltage, V, applied to the position for
achieving the loss of rigidity and a voltage, V.sup.SE, applied to
the position for which side effects occur; and (3) inversely
proportional to the voltage V.
[0015] In one embodiment, the creating step comprises the steps of:
[0016] (a). obtaining stimulation data corresponding to a target
region in which a deep brain stimulator is implanted from a
database, where the stimulation data comprise M.times.N sets of
intra-operatively acquired stimulation signals, {V.sub.ij,
L.sub.ij.sup.R, V.sub.ij.sup.SE}, and their corresponding
stimulation positions, {x.sub.j, y.sub.j, z.sub.j}, where i=1, 2, .
. . , M, M being a positive integer and the number of a population
of living subjects from which the stimulation signals are acquired
and stored in the database, and j=1, 2, . . . , N, N being a
positive integer and the number of positions at which the
stimulation takes place for each of the population of living
subjects, and where V.sub.ij, L.sub.ij.sup.R, V.sub.ij.sup.SE are a
stimulation voltage, a percent of loss of rigidity caused by the
stimulation voltage, and a voltage for which side effects occur,
respectively, at the j-th stimulation position of the i-th living
subject; [0017] (b). choosing a local efficacy of stimulation,
E.sub.ij, at the j-th stimulation position (x.sub.j, y.sub.j,
z.sub.j) for the i-th living subject with a Gaussian curve,
F.sub.ij, in the form of:
[0017] F ij = E ij * exp [ - ( x j 2 + y j 2 + z j 2 2 V ij 2 ) ] ,
##EQU00001##
where the local efficacy of stimulation
E ij = L ij R * ( V ij SE - V ij ) * 1 V ij , ##EQU00002##
and the height of the Gaussian curve F.sub.ij is a function of the
local efficacy of stimulation E.sub.ij, and the radius of the
Gaussian curve F.sub.ij is a function of the stimulation voltage
V.sub.ij; [0018] (c). repeating step (b) for each of the population
of living subjects, i=1, 2, . . . , M, so as to obtain M sets of
Gaussian curves {F.sub.ij} for the j-th stimulation position
(x.sub.j, y.sub.j, z.sub.j); [0019] (d). averaging the M sets of
Gaussian curves {F.sub.ij} to obtain an efficacy of stimulation at
the j-th stimulation position (x.sub.j, y.sub.j, z.sub.j), which is
equal to the mean value of the M sets of Gaussian curves
{F.sub.ij}; and [0020] (e). repeating steps (b)-(d) for each of the
stimulation positions, j=1, 2, . . . , N, to obtain N efficacies of
stimulation respectively for the N stimulation positions, thereby
creating the efficacy atlas.
[0021] The database includes an electrophysiological atlas
containing electrophysiological information acquired from each of
the population of living subjects and related to atlas coordinates
of the electrophysiological atlas. The atlas coordinates of the
efficacy atlas is substantially coincident with the atlas
coordinates of the electrophysiological atlas.
[0022] The electrophysiological information comprises at least
intra-operative information for each of the population of living
subjects. In one embodiment, the intra-operative information
comprises at least specific information associated with at least
one stimulation electrode, where the specific information includes
voltages applied to the at least one stimulation electrode, a
response of a living subject undergoing treatment to the
stimulation, differences in voltage between disappearance of
symptoms and appearance of side effects, and a position of the at
least one stimulation electrode, where the response of the living
subject undergoing treatment to the stimulation includes loss of
rigidity, location where the loss of rigidity is observed,
appearance of side effects, and/or location affected by these side
effects. In another embodiment, the intra-operative information
comprises at least specific information associated with a deep
brain stimulator having at least one electrode, where the specific
information includes a position of each electrode contact of the at
least one electrode, and a voltage, frequency and pulse width of
stimulation at the position.
[0023] In one embodiment, the acquiring step has the step of
obtaining the position of each electrode contact of the at least
one electrode from the database. In another embodiment, the
acquiring step has the step of acquiring the position of each
electrode contact of the at least one electrode post-operatively
from the target region of the brain of the living subject in which
the deep brain stimulator is implanted.
[0024] In another aspect, the present invention relates to a system
for programming a deep brain stimulator implanted in a target
region of a brain of a living subject for optimal stimulation,
where the deep brain stimulator comprises at least one electrode
having a plurality of electrode contacts spaced apart from each
other, and any portion of the brain of the living subject is
identifiable by a set of corresponding spatial coordinates.
[0025] In one embodiment, the system has an efficacy atlas in which
each position in the atlas coordinates of the efficacy atlas is
associated with an efficacy of stimulation at a corresponding
position in the spatial coordinates of the brain of the living
subject; means for acquiring a position of each electrode contact
of the at least one electrode in the spatial coordinates of the
brain of the living subject; and a controller at least communicable
with the efficacy atlas and adapted for mapping the acquired
position of each electrode contact of the at least one electrode in
the spatial coordinates of the brain of the living subject onto a
corresponding position in the atlas coordinates of the efficacy
atlas so as to determine the efficacy of stimulation at the
acquired position in the spatial coordinates of the brain of the
living subject, and selecting one or more electrode contacts having
the highest efficacy for stimulation. In one embodiment, the
efficacy atlas is created by steps (a)-(e) as disclosed above.
[0026] In one embodiment, the efficacy atlas comprises at least one
stimulation map having at least one stimulation region related to
the target region of the brain of the living subject for optimal
stimulation.
[0027] The efficacy of stimulation at a position is corresponding
to the probability of the stimulation to be clinically effective at
the position. In one embodiment, the efficacy of stimulation at a
position in the spatial coordinates of the brain of the living
subject is (1) proportional to a percent of loss of rigidity,
L.sup.R; (2) proportional to a therapeutic window that equals to
the difference between a voltage, V, applied to the position for
achieving the loss of rigidity and a voltage, V.sup.SE, applied to
the position for which side effects occur; and (3) inversely
proportional to the voltage V.
[0028] Furthermore, the system has a non-rigid registration
algorithm stored in a memory that is in communication with the
controller.
[0029] Moreover, the system has a data storage device for storing
the efficacy atlas, the data storage device configured to be in
communication with the controller.
[0030] Additionally, the system has a database stored in the data
storage device, where the database comprises an
electrophysiological atlas containing electrophysiological
information acquired from a brain of each of a population of living
subjects and related to atlas coordinates of the
electrophysiological atlas. In one embodiment, the atlas
coordinates of the efficacy atlas is substantially coincident with
the atlas coordinates of the electrophysiological atlas.
[0031] In one embodiment, the electrophysiological information
comprises at least intra-operative information for each of the
population of living subjects. In one embodiment, the
intra-operative information comprises at least specific information
associated with at least one stimulation electrode, where the
specific information includes voltages applied to the at least one
stimulation electrode, a response of a living subject undergoing
treatment to the stimulation, differences in voltage between
disappearance of symptoms and appearance of side effects, and a
position of the at least one stimulation electrode, where the
response of the living subject undergoing treatment to the
stimulation includes loss of rigidity, location where the loss of
rigidity is observed, appearance of side effects, and/or location
affected by these side effects. In another embodiment, the
intra-operative information comprises at least specific information
associated with a deep brain stimulator implanted in a target
region of a brain of a living subject, where the specific
information includes a position of each electrode contact of the
deep brain stimulator, and a voltage, frequency and pulse width of
stimulation at the position.
[0032] In one embodiment, the acquiring means comprises a device
for obtaining the position of each electrode contact of the at
least one electrode from the database. In another embodiment, the
acquiring means comprises a device for acquiring the position of
each electrode contact of the at least one electrode
post-operatively from the target region of the brain of the living
subject in which the deep brain stimulator is implanted.
[0033] In yet another aspect, the present invention relates to a
method for programming a deep brain stimulator implanted in a
target region of a brain of a living subject for optimal
stimulation, where the deep brain stimulator comprises at least one
electrode having a plurality of electrode contacts.
[0034] In one embodiment, the method includes the step of creating
an efficacy atlas in which a position in atlas coordinates of the
efficacy atlas is related to a corresponding position in spatial
coordinates of the brain of the living subject, and each position
in atlas coordinates of the efficacy atlas is associated with an
efficacy of stimulation at a corresponding position in spatial
coordinates of the brain of the living subject. In one embodiment,
the efficacy atlas is created according to steps (a)-(e) disclosed
above.
[0035] In one embodiment, the efficacy atlas comprises at least one
stimulation map having at least one stimulation region related to
the target region of the brain of the living subject for optimal
stimulation.
[0036] The method further includes the steps of mapping a position
of each electrode contact of the at least one electrode in the
spatial coordinates of the brain of the living subject onto a
corresponding position in the atlas coordinates of the efficacy
atlas so as to determine the efficacy of stimulation at the
acquired position in the spatial coordinates of the brain of the
living subject; and selecting one or more electrode contacts having
the highest efficacy for stimulation, where the mapping step is
performed with a non-rigid registration algorithm.
[0037] In a further aspect, the present invention relates to a
system for programming a deep brain stimulator implanted in a
target region of a brain of a living subject for optimal
stimulation, where the deep brain stimulator comprises at least one
electrode having a plurality of electrode contacts spaced apart
from each other, and where any portion of the brain of the living
subject is identifiable by a set of corresponding spatial
coordinates.
[0038] In one embodiment, the system has a data storage device; a
database stored in the data storage device, comprising an
electrophysiological atlas containing electrophysiological
information acquired from each of the population of living subjects
and related to atlas coordinates of the electrophysiological atlas;
and a controller in communication with the data storage device and
adapted for programmably interfacing with the database for creating
an efficacy atlas in which a position in atlas coordinates of the
efficacy atlas is related to a corresponding position in spatial
coordinates of the brain of the living subject, and vice versa, and
each position in atlas coordinates of the efficacy atlas is
associated with an efficacy of stimulation at a corresponding
position in spatial coordinates of the brain of the living
subject.
[0039] The controller is also adapted for programmably mapping a
position of each electrode contact of the at least one electrode in
the spatial coordinates of the brain of the living subject onto a
corresponding position in the atlas coordinates of the efficacy
atlas so as to determine the efficacy of stimulation at the
acquired position in the spatial coordinates of the brain of the
living subject, and selecting one or more electrode contacts having
the highest efficacy for stimulation.
[0040] The efficacy atlas comprises at least one stimulation map
having at least one stimulation region related to the target region
of the brain of the living subject for optimal stimulation. The
atlas coordinates of the efficacy atlas is substantially coincident
with the atlas coordinates of the electrophysiological atlas.
[0041] In yet a further aspect, the present invention relates to a
system for programming a deep brain stimulator implanted in a
target region of a brain of a living subject for optimal
stimulation, where the deep brain stimulator comprises at least one
electrode having a plurality of electrode contacts, and where any
portion of the brain of the living subject is identifiable by a set
of corresponding spatial coordinates. In one embodiment, the system
includes a data storage device; and an efficacy atlas stored in the
data storage device, where each position in atlas coordinates of
the efficacy atlas is associated with an efficacy of stimulation at
a corresponding position in spatial coordinates of the brain of the
living subject.
[0042] The system further includes a controller in communication
with the data storage device and adapted for programmably mapping a
position of each electrode contact of the at least one electrode in
the spatial coordinates of the brain of the living subject onto a
corresponding position in the atlas coordinates of the efficacy
atlas so as to determine the efficacy of stimulation at the
acquired position in the spatial coordinates of the brain of the
living subject, and selecting one or more electrode contacts having
the highest efficacy for stimulation.
[0043] In one aspect, the present invention relates to software
stored on a computer readable medium for causing a computing system
to perform functions comprising: (i) creating an efficacy atlas in
which a position in atlas coordinates of the efficacy atlas is
related to a corresponding position in spatial coordinates of the
brain of the living subject, and each position in the atlas
coordinates of the efficacy atlas is associated with an efficacy of
stimulation at a corresponding position in the spatial coordinates
of the brain of the living subject; (ii) acquiring a position of
each electrode contact of the at least one electrode in the spatial
coordinates of the brain of the living subject; (iii) mapping the
acquired position of each electrode contact of the at least one
electrode in the spatial coordinates of the brain of the living
subject onto a corresponding position in the atlas coordinates of
the efficacy atlas so as to determine the efficacy of stimulation
at the acquired position in the spatial coordinates of the brain of
the living subject; and (iv) selecting one or more electrode
contacts having the highest efficacy for stimulation.
[0044] These and other aspects of the present invention will become
apparent from the following description of the preferred embodiment
taken in conjunction with the following drawings, although
variations and modifications therein may be affected without
departing from the spirit and scope of the novel concepts of the
disclosure.
BRIEF DESCRIPTION OF THE DRAWINGS
[0045] The patent or application file contains at least one drawing
executed in color. Copies of this patent or patent application
publication with color drawing(s) will be provided by the Patent
and Trademark Office upon request and payment of the necessary
fee.
[0046] The accompanying drawings illustrate one or more embodiments
of the invention and, together with the written description, serve
to explain the principles of the invention. Wherever possible, the
same reference numbers are used throughout the drawings to refer to
the same or like elements of an embodiment, and wherein:
[0047] FIG. 1 shows intra-operatively selected DBS target positions
(for the right STN) mapped onto an atlas according to one
embodiment of the present invention, where the target positions are
projected onto the axial (a) and sagittal (b) slices passing
through the centroid of the clusters, and contours showing the
anatomic structures are obtained from the Shaltenbrand-Wahren
atlas;
[0048] FIG. 2 shows a color-coded electrophysiological atlas map
corresponding to the spike rate, i.e., the number of spikes/second,
according to one embodiment of the present invention, where red
color areas (210L, and 210R) correspond to the regions of anatomic
structures in which the spike rate has high values, blue color
areas (220L and 220R) correspond to the regions of anatomic
structures in which the spike rate has low values, and a small
white circle (230L and 230R) corresponds to the optimal target
point (position) in the atlas;
[0049] FIG. 3 shows color-coded electrophysiological atlas maps
corresponding to different extracted features according to one
embodiment of the present invention: (a) a burst index map; (b) a
pause ratio map; (c) a pause index map; (d) a power spectral
density map, (e) a mean value map of the fifth detail component of
the wavelet decomposition, and (f) a standard deviation map of the
fifth detail component of the wavelet decomposition, where red
color areas correspond to the regions of anatomic structures in
which the corresponding extracted feature has high values, blue
color areas correspond to the regions of anatomic structures in
which the corresponding extracted feature has low values, and a
small white circle corresponds to the optimal target point
(position) in the atlas;
[0050] FIG. 4 shows several features histogram extracted on a usual
path while targeting the STN from the features maps according to
one embodiment of the present invention, where Thalamus (THAL), STN
and SNr are manually labeled, and the curves are corresponding to
the number of spikes (410), the burst index (420), the power
spectral density (430), the pause ratio (440), the pause index
(450) and the standard deviation of the fifth component of the
wavelet decomposition (460), respectively;
[0051] FIG. 5 shows stimulation maps according to one embodiment of
the present invention, where red color areas correspond to the
regions of anatomic structures in which the stimulation has a high
probability to get desired stimulation results, blue color areas
correspond to the regions of anatomic structures in which the
stimulation has a low probability to get desired stimulation
results, white color areas correspond to the regions of anatomic
structures in which the stimulation has the highest probability to
get desired stimulation results, and the star represents the
optimal position in the atlas at which the implant is placed when
targeting the STN;
[0052] FIG. 6 shows the position of a four-contact electrode lead
implanted into a brain of a patient mapped onto a stimulation map
according to one embodiment of the present invention, where the
contact that has been used for programming is in a black color;
[0053] FIG. 7 shows a three-dimensional (3D) view of the positions
of three four-contact electrode leads respectively implanted into
brains of three patients mapped onto the stimulation atlas, where
the contacts used for programming are in a black color; and
[0054] FIG. 8 schematically shows one example of a quadric-polar
deep brain stimulator that can be utilized to practice the present
invention.
DETAILED DESCRIPTION OF THE INVENTION
[0055] The present invention is more particularly described in the
following examples that are intended as illustrative only since
numerous modifications and variations therein will be apparent to
those skilled in the art. Various embodiments of the invention are
now described in detail. Referring to the drawings of FIGS. 1-8,
like numbers indicate like components throughout the views. As used
in the description herein and throughout the claims that follow,
the meaning of "a", "an", and "the" includes plural reference
unless the context clearly dictates otherwise. Also, as used in the
description herein and throughout the claims that follow, the
meaning of "in" includes "in" and "on" unless the context clearly
dictates otherwise. Moreover, titles or subtitles may be used in
the specification for the convenience of a reader, which shall have
no influence on the scope of the present invention. Additionally,
some terms used in this specification are more specifically defined
below.
DEFINITIONS
[0056] The terms used in this specification generally have their
ordinary meanings in the art, within the context of the invention,
and in the specific context where each term is used.
[0057] Certain terms that are used to describe the invention are
discussed below, or elsewhere in the specification, to provide
additional guidance to the practitioner in describing the apparatus
and methods of the invention and how to make and use them. For
convenience, certain terms may be highlighted, for example using
italics and/or quotation marks. The use of highlighting has no
influence on the scope and meaning of a term; the scope and meaning
of a term is the same, in the same context, whether or not it is
highlighted. It will be appreciated that the same thing can be said
in more than one way. Consequently, alternative language and
synonyms may be used for any one or more of the terms discussed
herein, nor is any special significance to be placed upon whether
or not a term is elaborated or discussed herein. Synonyms for
certain terms are provided. A recital of one or more synonyms does
not exclude the use of other synonyms. The use of examples anywhere
in this specification, including examples of any terms discussed
herein, is illustrative only, and in no way limits the scope and
meaning of the invention or of any exemplified term. Likewise, the
invention is not limited to various embodiments given in this
specification. Furthermore, subtitles may be used to help a reader
of the specification to read through the specification, which the
usage of subtitles, however, has no influence on the scope of the
invention.
[0058] As used herein, "about" or "approximately" shall generally
mean within 20 percent, preferably within 10 percent, and more
preferably within 5 percent of a given value or range. Numerical
quantities given herein are approximate, meaning that the term
"about" or "approximately" can be inferred if not expressly
stated.
[0059] As used herein, the term "living subject" refers to a human
being such as a patient, or an animal such as a lab testing
monkey.
[0060] As used herein, "target," "target of interest," and "target
region" are synonyms in the specification and refer to an object of
stimulation in a deep brain of a living subject for treatment of a
brain-controlled disorder.
[0061] As used herein, "stimulation" refers to increase temporarily
the activity of a body organ or part thereof responsive to an input
signal to the body organ or part.
[0062] The terms "project," "map," "register," and "transform," as
used herein, are synonyms in the specification and refer to a
transformation of a point of interest from a source image volume to
a target image volume, and vice versa.
[0063] The terms "place," "implant," and "insert," as used herein,
are synonyms in the specification and refer to put or embed a
device, such as a microelectrode recording lead, macrostimulation
lead, and/or a deep brain stimulator, into a target region of a
brain of a living subject.
OVERVIEW OF THE INVENTION
[0064] The description will be made as to the embodiments of the
present invention in conjunction with the accompanying drawings of
FIGS. 1-8. In accordance with the purposes of this invention, as
embodied and broadly described herein, this invention, in one
aspect, relates to a system for programming a deep brain stimulator
implanted in a target region of a brain of a living subject for
optimal stimulation. The deep brain stimulator includes at least
one electrode having a plurality of electrode contacts spaced apart
from each other.
[0065] The post-operative neurological management of patients with
the STN-DBS for Parkinson's disease is a complex and dynamic
process that involves optimizing the stimulation parameters and
decreasing the anti-parkinsonian medication while assessing the
interactions of both treatment modalities. Neurologists who treat
patients undergoing DBS therapy must have expert knowledge of the
electroanatomy of the subthalamic area and be familiar with the
medical treatment of motor and non-motor symptoms. In clinical
practice, finding the optimal programming parameters can be a
challenging and time-consuming process. The present invention,
among other things, discloses a computerized system to facilitate
one of the bottlenecks of DBS therapy: the IPG (Internal Pulse
Generator) programming. This system includes an efficacy atlas that
is created from a database. The database includes an
electrophysiological atlas (deformable physiological atlas) built
on more than 300 pieces of intra-operative information acquired
from 30 Parkinson's patients and of a non-rigid registration
algorithm used to map these data into the atlas. By correlating the
position of each electrode contact of a stimulation electrode
implanted in a target region of a brain of a patient with the
information contained in the atlas, one can determine which of the
contacts has the highest probability (efficacy) to be the most
clinically effective.
[0066] In the electrophysiological atlas, any spatial coordinates
of the brain of a patient are related to atlas coordinates in the
atlas in a way such that the electrophysiological information
associated with spatial coordinates from which it is acquired in
the brain of the patient can be related to atlas coordinates in the
atlas, and vice versa. The intra-operative information for each
patient comprises at least specific information associated with at
least one stimulation electrode. The specific information includes,
but is not limited to, voltages applied to the at least one
stimulation electrode, a response of the patient undergoing
treatment to the stimulation, differences in voltage between
disappearance of symptoms and appearance of side effects, and a
position of the at least one stimulation electrode. The response of
the patient undergoing treatment to the stimulation includes loss
of rigidity, location where the loss of rigidity is observed,
appearance of side effects, and/or location affected by these side
effects. Additionally, the intra-operative information for each
patient also includes at least specific information associated with
a deep brain stimulator implanted in a target region of the brain
of the patient, where the specific information includes information
about a position of each electrode contact of the deep brain
stimulator, and a voltage, frequency and pulse width of stimulation
at the position.
[0067] The efficacy of stimulation at a position in the spatial
coordinates of a brain of a patient is corresponding to the
probability of the stimulation to be clinically effective at the
position. In general, the efficacy of stimulation at a position is
(1) proportional to a percent of loss of rigidity, L.sup.R; (2)
proportional to a therapeutic window that equals to the difference
between a voltage, V, applied to the position for achieving the
loss of rigidity and a voltage, V.sup.SE, applied to the position
for which side effects occur; and (3) inversely proportional to the
voltage V. A position is regarded as an optimal stimulation
position if the percentage of the loss of rigidity L.sup.R is high,
the applied voltage V is low, and the difference between V.sup.SE
and V is large. In other words, the stimulation of an electrode
contact at such a position has the highest probability to be the
most clinically effective.
[0068] According to the present invention, an efficacy atlas is
created from the electrophysiological atlas. In the efficacy atlas,
a position in atlas coordinates in the efficacy atlas is related to
a corresponding position in spatial coordinates in a target region
of a brain of a patient, and each position in the atlas coordinates
of the efficacy atlas is associated with an efficacy of stimulation
at a corresponding position in the spatial coordinates of the brain
of the patient. The atlas coordinates of the efficacy atlas is
substantially coincident with the atlas coordinates of the
electrophysiological atlas. The efficacy atlas has at least one
stimulation map having at least one stimulation region related to
the target region of the brain of the patient for optimal
stimulation.
[0069] Specifically, the creation of the efficacy map is as
follows: at first, stimulation data corresponding to a target
region in which a deep brain stimulator is implanted are obtained
from the database (electrophysiological atlas). The stimulation
data include M.times.N sets of intra-operatively acquired
stimulation signals, {V.sub.ij, L.sub.ij.sup.R, V.sub.ij.sup.SE},
and their corresponding stimulation positions, {x.sub.j, y.sub.j,
z.sub.j}, mapped onto the electrophysiological atlas, where i=1, 2,
. . . , M, M being a positive integer and the number of a
population of patients from which the stimulation signals are
acquired and stored in the database, In this example, M=30. j=1, 2,
. . . , N, N being a positive integer and the number of positions
at which the stimulation takes place for each of the population of
patients. V.sub.ij, L.sub.ij.sup.R, V.sub.ij.sup.SE are a
stimulation voltage, a percent of loss of rigidity caused by the
stimulation voltage, and a voltage for which side effects occur,
respectively, at the j-th stimulation position of the i-th
patient.
[0070] Secondly, a local efficacy of stimulation, E.sub.ij, at the
j-th stimulation position (x.sub.j, y.sub.j, z.sub.j) for the i-th
patient is modeled with a Gaussian curve, F.sub.ij. The Gaussian
curve is defined to be the form of:
F ij = E ij * exp [ - ( x j 2 + y j 2 + z j 2 2 V ij 2 ) ] ,
##EQU00003##
where the local efficacy of stimulation
E ij = L ij R * ( V ij SE - V ij ) * 1 V ij , ##EQU00004##
and the height of the Gaussian curve F.sub.ij is a function of the
local efficacy of stimulation E.sub.ij, and the radius of the
Gaussian curve F.sub.ij is a function of the stimulation voltage
V.sub.ij.
[0071] Then, repeatedly modeling the efficacy of stimulation at the
j-th stimulation position (x.sub.j, y.sub.j, z.sub.j) for each of
the population of patients, i=1, 2, . . . , M, results in M sets of
Gaussian curves {F.sub.ij} for the j-th stimulation position
(x.sub.j, y.sub.j, z.sub.j). The M sets of Gaussian curves
{F.sub.ij} are averaged to obtain an efficacy of stimulation at the
j-th stimulation position (x.sub.j, y.sub.j, z.sub.j), which is
equal to the mean value of the M sets of Gaussian curves
{F.sub.ij}.
[0072] Repeating the above processes for each of the stimulation
positions, j=1, 2, . . . , N, to obtain N efficacies of stimulation
respectively at the N stimulation positions, thereby creating an
efficacy atlas in which any spatial coordinates of the brain of the
patient are related to atlas coordinates of the efficacy atlas, and
each position in the atlas coordinates of the efficacy atlas is
associated with an efficacy of stimulation at a corresponding
position in the spatial coordinates of the brain of the
patient.
[0073] Accordingly, a point (position) with a small stimulation
voltage and a high percentage of the loss of rigidity is thus
associated with a curve with a small standard deviation and large
amplitude. In other words, a point (position) associated with a
curve that has a small standard deviation and large amplitude has a
large but localized effect on the atlas, while a point (position)
with a large standard deviation has a smaller impact that extends
over a larger region.
[0074] Furthermore, the system includes a controller at least
communicable with the efficacy atlas and adapted for mapping the
position of each electrode contact of the at least one electrode in
the spatial coordinates of the brain of the patient onto a
corresponding position in the atlas coordinates of the efficacy
atlas so as to determine the efficacy of stimulation at the
acquired position in the spatial coordinates of the brain of the
patient, and selecting one or more electrode contacts having the
highest efficacy for stimulation.
[0075] The position of each electrode contact of the at least one
electrode in the spatial coordinates of a brain of a patient can be
obtained directly from the database or acquired post-operatively
from the target region of the brain of the patient in which the
deep brain stimulator is implanted.
[0076] The mapping process is performed with a non-rigid
registration algorithm.
[0077] Additionally, the system has a data storage device for
storing the efficacy atlas, the data storage device configured to
be in communication with the controller.
[0078] Another aspect of the present invention relates to a method
for programming a deep brain stimulator implanted in a target
region of a brain of a patient for optimal stimulation, where the
deep brain stimulator comprises at least one electrode having a
plurality of electrode contacts, and any portion of the brain of
the patient is identifiable by a set of corresponding spatial
coordinates.
[0079] The method, in one embodiment, includes the following steps:
at first, an efficacy atlas is created form the database, such that
any spatial coordinates for a position in a target region of the
brain of the patient are related to a position with corresponding
atlas coordinates in the efficacy atlas, and each position in the
atlas coordinates of the efficacy atlas is associated with an
efficacy of stimulation at a corresponding position in the spatial
coordinates of the brain of the patient. Secondly, a position of
each electrode contact of the at least one electrode in the spatial
coordinates of the brain of the patient is acquired. Next, the
acquired position of each electrode contact of the at least one
electrode in the spatial coordinates of the brain of the patient is
mapped onto a corresponding position in the efficacy atlas so as to
determine the efficacy of stimulation at the acquired position in
the spatial coordinates of the brain of the patient. Then, one or
more electrode contacts having the highest efficacy are selected
for stimulation.
[0080] An alternative aspect of the present invention relates to
software stored on a computer readable medium for causing a
computing system to perform functions comprising: (i) creating an
efficacy atlas in which a position in atlas coordinates of the
efficacy atlas is related to a corresponding position in spatial
coordinates of the brain of the patient, and each position in the
atlas coordinates of the efficacy atlas is associated with an
efficacy of stimulation at a corresponding position in the spatial
coordinates of the brain of the patient; (ii) acquiring a position
of each electrode contact of the at least one electrode in the
spatial coordinates of the brain of the patient; (iii) mapping the
acquired position of each electrode contact of the at least one
electrode in the spatial coordinates of the brain of the patient
onto a corresponding position in the atlas coordinates of the
efficacy atlas so as to determine the efficacy of stimulation at
the acquired position in the spatial coordinates of the brain of
the patient; and (iv) selecting one or more electrode contacts
having the highest efficacy for stimulation. These and other
aspects of the present invention are more specifically described
below.
IMPLEMENTATIONS AND EXAMPLES OF THE INVENTION
[0081] Without intent to limit the scope of the invention,
exemplary methods and their related results according to the
embodiments of the present invention are given below. Note that
titles or subtitles may be used in the examples for convenience of
a reader, which in no way should limit the scope of the invention.
Moreover, certain theories are proposed and disclosed herein;
however, in no way they, whether they are right or wrong, should
limit the scope of the invention so long as the invention is
practiced according to the invention without regard for any
particular theory or scheme of action.
Patients and Data Collection
[0082] In one embodiment of the present invention, a population of
thirty (30) PD patients undergoing DBS therapy was chosen to gather
data for evaluating the invented method. Each patient, or a living
subject of study, was assigned a number from P1 to P30 as his or
her identification. The data was collected with Vanderbilt
University Institutional Review Board (IRB) approval (Vanderbilt
University IRB No. 010809). Specifically, a set of X-ray computed
tomography (CT) and magnetic resonance (MR) image volumes were
acquired pre-operatively for each patient with the patient
anesthetized and head secured to the table to minimize motion.
Typically, the CT images were acquired at kvp=120 V, exposure=350
mas, 512.times.512 voxels ranging in size from 0.49 to 0.62 mm, and
slice thickness from 1 mm to 2 mm; and the MR images were acquired
with a 1.5 T GE Signa scanner at 3D SPGR volumes, TR: 12.2, TE:
2.4, dimension 256.times.256.times.124 voxels, typical voxels
dimensions 0.85.times.0.85.times.1.3 mm.sup.3.
[0083] The surgical procedures as well as pre- and post-operative
evaluations were identical for all the thirty patients. Among them,
seventeen of these were followed for a period of at least six (6)
months after their DBS implantation and had optimal programming
parameters determined by their neurologist or neurosurgeon. The
remaining thirteen (13) patients had not gotten long enough
follow-ups to achieve stable programming.
[0084] Surgical planning and operative procedures performed at
Vanderbilt University were described in detail in [7]. Briefly,
pre-operative target identification was performed automatically
using an atlas-based method. The automatically predicted targets
were then checked by the functional neurosurgeon. Each location of
the automatically predicted targets was then refined
intra-operatively based on the surgical team's interpretation of
electrophysiological recordings and responses to stimulations. The
surgical team usually included a neurosurgeon, a neurophysiologist,
and a neurologist.
[0085] The operative procedures in one embodiment, were performed
with a miniature stereotactic frame, for example, StarFix
microTargeting Platform.RTM. (FHC, Inc., Bowdoinham, Me.), instead
of a standard stereotactic frame. The StarFix microTargeting
Platform.RTM. is also referred as a platform hereinafter. During
the surgery, a micro-positioning drive, such as microTargeting.RTM.
drive, from FHC, Inc., was mounted on the StarFix platform.
Recording and stimulating (electrode) leads were then inserted into
the target of interest through guiding tubes of the
microTargeting.RTM. drive. The StarFix platform was uniquely
designed, based on pre-operatively acquired CT images from the
patient such that the pre-operative predicted target was located on
the central track. Details on the platform, including a study of
its accuracy that shows it to be at least as accurate as standard
frames were described in [8]. The position of the electrode lead
was read from the micro-positioning device and converted into a (x,
y, z) position in CT coordinates. The position of each contact of
the electrode lead was then computed using the geometry of the
electrode lead and the final intra-operative position of the center
of the DBS implant in CT coordinates. In one embodiment, the DBS
implants used for these patients were the Medtronic 3389
Quadripolar Lead.RTM. (Medtronic, Inc., Minneapolis, Minn.), where
the size of each contact is 0.5 mm and the gaps between two
adjacent contacts are 0.5 mm. Other DBS implants can also be
utilized to practice the present invention.
[0086] It should be noted that according to the present invention,
the data collection, atlas and DBS programming are independent of
what frame (platform) or frame-less based system one uses to
implant the DBS leads.
Rigid and Non-Rigid Registration Algorithms
[0087] According to the present invention, all information acquired
from a population of patients needs to be mapped an atlas. The
atlas is a common frame of reference in which the position of each
individual DBS can be recorded. Creation of the atlas requires
registering individual image volumes to a common reference volume,
which corresponds to the spatial normalization of each individual
brain image. Two types of registrations algorithms, rigid and
non-rigid, are utilized to achieve this goal. The rigid
registration algorithm is required to register MR and CT image
volumes of the same patient. It is necessary because, as described
above, the intra-operative positions of the electrode contacts
provided by the micro-positioning drive are in CT coordinates. The
algorithm used to register MR and CT images of the same patient is
an independent implementation of a standard Mutual
Information-based algorithm [5]. This algorithm has been validated
using the data sets provided by the Retrospective Image
Registration Evaluation Project (RIRE) at Vanderbilt University
[7]. Non-rigid registration is required to register patient data to
the atlas and vice versa. In one embodiment, non-rigid registration
is performed on MR image volumes using an algorithm proposed
recently [6]. This algorithm computes a deformation field that is
modeled as a linear combination of radial basis functions with
finite support. The similarity measure used in the algorithm is the
mutual information between the images. In practice, two
transformations (one from the atlas to the patient and the other
from the patient to the atlas) are computed simultaneously, which
are constrained to be inverses of each other.
[0088] The validation of non-rigid registration algorithms is an
open-ended problem. However, it has been has demonstrated the
ability to register accurately MR volumes for STN-DBS implantation,
where twenty-one (21) patents with a total of thirty-nine (39)
electrodes were evaluated, and the final intra-operative positions
of the implants were respectively mapped onto the atlas [77]. FIG.
1 shows the atlas coordinates projected from the spatial
coordinates of the DBS positions acquired intra-operatively from
the right STN on (a) axial and (b) sagittal views (similar results
were found for the left side). Each circle 110 corresponds to an
atlas position of a final DBS target projected onto the atlas. To
orient the reader, contours 120 of anatomic structures obtained
from the Schaltenbrand-Wahren atlas were superimposed onto the MR
slice passing through the centroid of the cloud of points. This was
done by registering manually the Schaltenbrand-Wahren atlas to the
atlas according to the present invention using the Voxim software
(IVS Solutions AG, Chemnitz, Germany). FIG. 1 shows that the final
target points 110 chosen intra-operatively cluster tightly around
the same sub-region of the STN, as would be expected. This, in
turn, indicates that the patient's image volumes can be accurately
registered to the atlas.
Electrophysiological Atlas Maps
[0089] According to the present invention, an atlas is created to
contain electrophysiological information acquired from a population
of patients. In the electrophysiological atlas, any spatial
coordinates of the brain of a patient are related to atlas
coordinates in the atlas in a way such that the
electrophysiological information associated with spatial
coordinates from which it is acquired in the brain of the patient
can be related to atlas coordinates in the atlas, and vice
versa.
[0090] The acquired electrophysiological information at least
includes intra-operative information for each patient. The
intra-operative information may include information associated with
one or more microelectrodes, where the information includes
microelectrode recordings, a position of the microelectrode
recordings, a label of a structure in which the microelectrode
recordings is located, and others. The microelectrode recordings
can be characterized by a firing rate that measures tonic activity
and indices that measures phasic activity, where the indices
include a burst index, a pause ratio, a pause index, and an
interspike interval histogram. Other characteristic features may
also be extracted from the microelectrode recordings and can also
be utilized. The intra-operative information may also includes
information associated with one or more stimulation electrodes,
where the information includes voltages applied to the at least one
stimulation electrode, a response of a target of interest
undergoing treatment to the stimulation, differences in voltage
between disappearance of symptoms and appearance of side effects, a
position of the at least one stimulation electrode, a final
intra-operative target position of a deep brain stimulator to be
placed, and any mixture thereof. The response of the target of
interest undergoing treatment to the stimulation includes loss of
rigidity, location where the loss of rigidity is observed,
appearance of side effects, and/or location affected by these side
effects. The information may be used for the surgical team to
optimize the final portion of a DBS implant and DBS programming for
a patient.
[0091] The intra-operative information may have information
associated with one or more deep brain stimulators implanted in the
brain of each patient. The information may include the positions of
the one or more deep brain stimulators in post-operative CT images,
optimal settings of the one or more deep brain stimulators, overall
assessment of the patient after implant of the one or more deep
brain stimulators, and the likes.
[0092] Because the image coordinates of the points (positions) at
which the (electrophysiological information) signals are recorded
are known, one can extract features from these acquired signals,
and then map the value of these extracted features onto the
electrophysiological atlas. In one embodiment, the
electrophysiological atlas corresponds to a database. In the
database, each signal is stored with its spatial coordinates in the
image volume and its corresponding coordinates in the
electrophysiological atlas. The database can be accessed by queries
and returns for example a list of records, and each of the queries
is pointed to a file that contains a signal. These signals can be
processed and features extracted. The extracted features are then
stored in that database and can be accessed in the same way. This
permits the creation of multiple atlases in the database, each for
a corresponding feature.
[0093] It has been known that the boundaries of nuclei and
subnuclei are not visible in anatomic CT and MR images but that
these boundaries are inferred intra-operatively from MERs and
responses to stimulations. Thus, these extracted features can be
used to detect structures of interest and/or boundaries of the
structures. For example, according to the present invention these
boundaries of nuclei and subnuclei can be resolved and visualized
in the electrophysiological atlas, based on these features
extracted from MER signals, as shown in FIG. 2. In these figures,
regions that correspond to low and high values for some of these
features are identified in the electrophysiological atlas. To
generate these maps, the features have been computed for each
signal of each patient, mapped onto the electrophysiological atlas,
and then averaged over the number of the signals. FIG. 2 shows a
color coded atlas map that corresponds to the spike rate, i.e., the
number of spikes/second. In this atlas map, areas 210L and 210R (in
a red color) correspond to the regions of anatomic structures where
the spike rate extracted from MER signals recorded in the regions
has high values, while areas 220L and 220R (in a blue color)
correspond to the regions of anatomic structures where the spike
rate extracted from MER signals recorded in the regions has low
values. The optimal target point (position) in the atlas is shown
with a small circle 230 (in a white color). This atlas map shows
that a region having high values of the spike rate corresponds to
the STN, as shown by the contours obtained from the
Schaltenbrand-Wahren atlas. It is noted that a small misalignment
of these STN contours and the region of high spike rate on the
right side, which is attributed to the difficulty of registering
the Schaltenbrand-Wahren atlas with the MR volume.
[0094] Since the correspondence between patient and atlas
coordinates has been established in the electrophysiological atlas,
one can query the database for individual extracted features and/or
any combinations of the extracted features and visualized them in
the electrophysiological atlas. The extracted features include, for
example, the spike frequency, PSD, BI (burst index), PI (pause
index), PR (pause ratio), CV (coefficient of variation), mISI (mean
interspike interval) and FR (firing rate). Other features can be
extracted as new features extraction algorithms are developed,
making the electrophysiological atlas completely dynamic.
Additionally, the electrophysiological atlas can be populated with
newly acquired electrophysiological information from new patients,
and therefore is updatable.
[0095] FIG. 3 shows color-coded electrophysiological atlas maps
corresponding to different extracted features including (a) a burst
index map; (b) a pause ratio map; (c) a pause index map; (d) a
power spectral density map, (e) a mean value map of the fifth
detail component of the wavelet decomposition, and (f) a standard
deviation map of the fifth detail component of the wavelet
decomposition. In these features maps, red color areas, e.g., 310C,
correspond to the regions of anatomic structures where the
corresponding extracted feature extracted from signals recorded in
the regions has high values, while blue color areas, e.g., 320C,
correspond to the regions of anatomic structures in which the
corresponding extracted feature extracted from signals recorded in
the regions has low values. A small white circle, e.g., 330C,
corresponds to the optimal target point (position) in the atlas.
The map of the pause index shown in FIG. 3c presents good
discrimination between STN and SNr nuclei, where a continuous green
region around the STN 340C and a lower, a redder zone corresponds
to the SNr region 350C. Clearly, this does not appear in FIG. 3d.
These maps could add information that will help to discriminate
sub-structures of sub-electrophysiological regions. FIGS. 3e and 3f
show the mean and standard deviation of the fifth detail wavelet
component. Both figures present similar clustering. Theses maps are
useful to discriminate between STN (substantially high values) and
SNR (high values) from the rest of the signals.
[0096] FIG. 4 shows the same results in an alternative way. Each
curve represents one feature along the same track from a regular
entry point to the STN on the atlas going from -10 mm to +5 mm
around the target. Thalamus, STN and SNR were manually labeled
based on the signals. These curves in FIG. 4 are the number of
spikes 410, the burst index 420, the power spectral density 430,
the pause ratio 440, the pause index 450 and the standard deviation
of the fifth component of the wavelet decomposition 460,
respectively. Curve for the number of spikes 410, BI 420 or the
fifth wavelet component 460 shows patterns corresponding to the
manual labels. Accordingly, each feature can be used for
microelectrode recording discrimination.
Intra-Operative Efficacy Atlas
[0097] Intra-operative micro- or macro-stimulation is used to
determine suitable targets in which the stimulation induces the
best improvement of motor symptoms, especially rigidity and tremor
without adverse effects. While targeting the STN, the stimulation
is applied approximately every 2 mm along the track, starting at
the boundary of the STN, which is determined by micro-electrode
recordings (MERs) acquired prior to the stimulation. At every
position, the stimulation is typically performed with voltages
starting at 0.5 V up to 5 V by 0.5 V increments. The effect of the
stimulation on rigidity, muscle tone, bradykinesia, paresthesias,
muscle contraction, eye movements and subjective sensations are
assessed for every applied voltage. The optimal voltage is
determined at each position and the percentage of the loss of
rigidity is recorded for this voltage. Because the intra-operative
coordinates of a patient's electrode can be mapped onto the atlas,
any information acquired intra-operatively can be projected onto
the atlas. This, in turn, permits the creation of a number of
statistical maps relating spatial coordinates in the atlas to
characteristics measured intra-operatively. As shown above, maps of
features extracted from MERs can be created visually, where the
maps of the mean spike rate can be used to define the boundary of
the STN in the atlas.
[0098] According to the present invention, a stimulation map can be
created to associate each atlas position with an efficacy of
stimulation at a corresponding stimulation position at which an
electrode contact is located. The stimulation map provides useful
information to the neurologist for programming. In one embodiment,
an efficacy of stimulation at a stimulation position is defined as
being (1) inversely proportional to a voltage, V, applied to the
stimulation position; (2) proportional to the percentage of loss of
rigidity, L.sup.R, caused by the applied voltage V, and (3)
proportional to a therapeutic window that equals to the difference
in voltage required to achieve the loss of rigidity (V) and the
voltage for which side effects occur (V.sup.SE), that is the
efficacy of stimulation at a stimulation position is defined in the
form of:
E = L R * ( V SE - V ) * 1 V . ##EQU00005##
A stimulation position is regarded as an optimal stimulation
position if the percentage of the loss of rigidity L.sup.R is high,
the applied voltage V is low, and the difference between V.sup.SE
and V is large. In other words, the stimulation of an electrode
contact at such a position has the highest probability to be the
most clinically effective.
[0099] By applying procedures similar to those of generating a
feature map in the electrophysiological atlas as disclosed above, a
stimulation map can be created in which each position in the atlas
is associated with an efficacy of stimulation at a corresponding
stimulation position at which an electrode contact is located. FIG.
5 shows stimulation regions mapped onto the atlas according to one
embodiment of the present invention. In these maps shown in FIGS.
5a-5c, areas 510A-510C (in a red color) correspond to the regions
of anatomic structures in which the stimulation has a high efficacy
(probability) to get desired stimulation results, areas 520A-520C
(in a blue color) correspond to the regions of anatomic structures
in which the stimulation has a low efficacy (probability) to get
desired stimulation results, while areas 530A-530C (in a white
color) correspond to the regions of anatomic structures in which
the stimulation has the highest efficacy (probability) to get
desired stimulation results. The star 540A-540C represents the
optimal position in the atlas at which the implant is placed when
targeting the STN.
[0100] Alternatively, the stimulation map can be created with each
stimulation point in the atlas being modeled by a Gaussian curve;
where the height of the curve is a function of the efficacy and the
radius a function of the stimulation voltage. Specifically, the
creation of an efficacy map is as follows: at first, stimulation
data corresponding to a target region in which a deep brain
stimulator is implanted are obtained from a database
(electrophysiological atlas). The stimulation data comprise
M.times.N sets of intra-operatively acquired stimulation signals,
{V.sub.ij, L.sub.ij.sup.R, V.sub.ij.sup.SE}, and their
corresponding stimulation positions, {x.sub.j, y.sub.j, z.sub.j},
mapped onto the electrophysiological atlas, where i=1, 2, . . . ,
M, M being a positive integer and the number of a population of
patients from which the stimulation signals are acquired and stored
in the database, In one embodiment, M=30. j=1, 2, . . . , N, N
being a positive integer and the number of positions at which the
stimulation takes place for each of the population of patients.
V.sub.ij, L.sub.ij.sup.R, V.sub.ij.sup.SE are a stimulation
voltage, a percent of loss of rigidity caused by the stimulation
voltage, and a voltage for which side effects occur, respectively,
at the j-th stimulation position of the i-th patient.
[0101] Secondly, a local efficacy of stimulation, E.sub.ij, at the
j-th stimulation position (x.sub.j, y.sub.j, z.sub.j) for the i-th
patient is modeled with a Gaussian curve, F.sub.ij. The Gaussian
curve F.sub.ij is defined to be the form of:
F ij = E ij * exp [ - ( x j 2 + y j 2 + z j 2 2 V ij 2 ) ] ,
##EQU00006##
where the local efficacy of stimulation
E ij = L ij R * ( V ij SE - V ij ) * 1 V ij , ##EQU00007##
and the height of the Gaussian curve F.sub.ij is a function of the
local efficacy of stimulation E.sub.ij, and the radius of the
Gaussian curve F.sub.ij is a function of the stimulation voltage
V.sub.ij.
[0102] Then, repeatedly modeling the efficacy of stimulation at the
j-th stimulation position (x.sub.j, y.sub.j, z.sub.j) for each of
the population of patients, i=1, 2, . . . , M, results in M sets of
Gaussian curves {F.sub.ij} for the j-th stimulation position
(x.sub.j, y.sub.j, z.sub.j). The M sets of Gaussian curves
{F.sub.ij} are averaged to obtain an efficacy of stimulation at the
j-th stimulation position (x.sub.j, y.sub.j, z.sub.j), which is
equal to the mean value of the M sets of Gaussian curves
{F.sub.ij}.
[0103] Repeating the above processes for each of the stimulation
positions, j=1, 2, . . . , N, to obtain N efficacies of stimulation
respectively at the N stimulation positions, thereby creating an
efficacy atlas in which any spatial coordinates of the brain of the
patient are related to atlas coordinates of the efficacy atlas, and
each position in the atlas coordinates of the efficacy atlas is
associated with an efficacy of stimulation at a corresponding
position in the spatial coordinates of the brain of the
patient.
[0104] Accordingly, a point (position) with a small stimulation
voltage and a high percentage of the loss of rigidity is thus
associated with a curve with a small standard deviation and large
amplitude. In other words, a point (position) associated with a
curve that has a small standard deviation and large amplitude has a
large but localized effect on the atlas, while a point (position)
with a large standard deviation has a smaller impact that extends
over a larger region.
[0105] Referring to FIG. 6, stimulation maps is shown according to
one embodiment of the present invention. In these maps shown in
FIGS. 6a and 6b, areas 610A and 610B (in a red color) correspond to
the regions of anatomic structures in which the stimulation has a
high efficacy (probability) to get desired stimulation results,
while areas 620A and 620B (in a blue color) correspond to the
regions of anatomic structures in which the stimulation has a low
efficacy (probability) to get desired stimulation results. As shown
in FIG. 6a, each position of four contacts 632A, 634A, 636A and
638A of the electrode lead implanted into a brain of a patient is
mapped onto the stimulation map. In this exemplar example, contacts
634A and 634B are used for programming is in black. To alleviate
the symptoms, the contact tension is about 1 V.
[0106] FIG. 7 shows a perspective view of a 3D stimulation map for
three patients with each patient having a four-contact electrode
implanted in the target region. In FIG. 7, stimulation region 710
(in a red color) represents the iso-surface in the efficacy map
that corresponds to an iso-intensity value of 85%. Spheres 722,
724, 726 and 728 respectively represent the four contacts of the
electrode implanted in the target region of a first patient.
Spheres 732, 736 and 738 respectively represent the three contacts
(one is not shown) of the electrode implanted in the target region
of a second patient. Spheres 742, 746 and 748 respectively
represent the three contacts (one is not shown) of the electrode
implanted in the target region of a third patient. For the
electrode implanted in the target region of the first patient,
spheres 722 is the contact that has been selected by the
neurologist as the optimum contact, while the electrode implanted
in the target region of the third patient, spheres 746 is the
contact that has been selected by the neurologist as the optimum
contact. The map shows that for these cases, the neurologist has
chosen the electrode contact that has the highest probability of
being effective as predicted by the efficacy map according to the
present invention. To alleviate the symptoms the contact tension
for the three cases is around 1 V.
Atlas-Based Contact Selection
[0107] Once the efficacy atlas is created, it can be used
post-operatively to assist the neurologist in selecting the optimum
contact for stimulation. To achieve this, a position of each
electrode contact of a stimulation lead implanted into a target
region of a brain of a patient needs to be known, and then is
mapped onto the efficacy atlas so as to determine its efficacy of
stimulation at the position. This can be done by querying the
database for the final position of each electrode contact of the
stimulation lead implanted in the target region of the brain of the
patient, or by acquiring post-operatively the position of each
electrode contact of the stimulation lead implanted in the target
region of the brain of the patient. The contact that falls into the
stimulation regions on the atlas corresponding to the highest
probability of good efficacy would be the optimum contact for
stimulation.
RESULTS AND DISCUSSION
[0108] Table 1 lists quantitative results obtained with the method
according to the present invention. The efficacy probability from
the atlas was correlated to each contact in the 17 subjects
included in this exemplary embodiment. The DBS leads implanted in
these patients are a Medtronic 3389 Quadripolar Lead.RTM., which
has four contacts C0, C1, C2 and C3. Each of the four contacts C0,
C1, C2 and C3 has a length, d.sub.1, which is about 0.5 mm, and the
distance, d.sub.2, between two neighboring contacts, for example,
C0 and C1, is about 0.5 mm, as shown in FIG. 8.
[0109] In Table 1, the numbers in bold and italic are the contacts
selected by the neurologist. Contacts are numbered from C0 (distal
contact) to C3 (proximal contact). The column labeled "V" is the
amplitude of the therapeutic voltage.
TABLE-US-00001 TABLE 1 The table shows, for 17 STN patients, the
likelihood of the four contacts to get good stimulation results.
Left Right Patient C0 C1 C2 C3 V C0 C1 C2 C3 V P0 0.47 0.61 1.1 0.1
0.2 0.3 1.1 P1 0.18 0.53 0.71 2.2 0.2 0.6 0.7 2.2 P2 0.53 0.84 0.61
2.4 0.4 0.7 1.0 1.7 P3 0.64 0.78 0.27 1.5 0.2 0.4 1.0 1.3 P4 0.06
0.07 0.24 1.5 0.3 0.6 0.4 1.8 P5 0.01 0.11 0.12 1.8 P6 0.74 0.74
0.47 1.5 0.4 0.7 0.7 1.5 P7 0.65 0.59 0.21 1.6 0.7 0.9 1.0 1.7 P8
0.80 0.47 0.10 1.4 P9 0.73 0.98 2.3 0.8 0.8 0.4 2.2 P10 0.72 0.84
0.59 3.2 0.3 0.6 0.4 3.2 P11 0.59 0.85 0.65 1.8 0.2 0.4 0.9 1.5 P12
0.60 0.49 0.11 2.1 0.2 0.4 2.7 P13 0.9 0.9 2.3 P14 0.47 0.84 0.84
0.8 NI 0.1 0.4 1.0 P15 0.73 0.80 0.40 1.5 0.3 0.7 0.6 1.5 P16 0.85
0.92 0.69 1.8 0.3 0.6 0.6 1.8 P17 0.2 0.7 1.0 3.2 The number in
bold and italic shows the contact that was selected as the best one
by the neurologist. Contacts are numbered from C0 (bottom contact)
to C3 (top contact). The implant used for these patients is a
Medtronic 3389 implant. The size of the contact is 0.5 mm and the
gap between the contacts is 0.5 mm.
[0110] Results presented in Table 1 show that about 60% of the
contacts selected by the neurologist are the contacts with the
highest efficacy probability in the efficacy atlas. This indicates
the feasibility of using a statistical atlas to facilitate the
programming process. A more detailed analysis of this process also
suggests that using predictions from the efficacy atlas shortens
the time required to reach stable programming. For example,
programming notes from the neurologists for patient P3 showed that
contact C1 was tried first on the right side before moving to C2
which produced better results. For patient P11 the C0 contacts were
first tried on both sides before moving to contacts C2. A similar
trend had been observed for the left implant in patient P12, where
the neurologist tried the stimulation of the contacts from contact
C3 to C2. For patient P15, contact C1 on the left side was observed
to have a better effect on rigidity than contact C2.
[0111] For a few cases, the optimal electrode predicted by the
atlas has been tried and rejected. For example, in patient P16,
contacts C0 and C1 were tried but not selected because these caused
significant side effects. These effects were reduced with contact
C3 but this particular patient still has significant rigidity and
bradykinesia.
[0112] In the present invention, among other things, a method for
programming a deep brain stimulator for optimal stimulation and a
computerized system utilized the method are disclosed, which
facilitate one of the bottlenecks of DBS therapy: the IPG (Internal
Pulse Generator) programming. This is achieved by creating an
efficacy atlas from an electrophysiological atlas, where each
position in the atlas coordinates in the efficacy atlas is
associated with an efficacy of stimulation at a corresponding
position in spatial coordinates of a brain of a patient, and then
correlating the position of each electrode contact of a stimulation
electrode implanted in the brain of the patient with a
corresponding efficacy contained in the efficacy atlas so as to
determine which of the contacts has the highest probability
(efficacy) to be the most clinically effective.
[0113] Additional improvements may be made. First, a prospective
validation study is initiated. Rather than verifying that the
electrode is the optimal one after programming has been completed,
the optimal contact is proposed to the neurologist at the time of
initial programming. This approach has been applied when developing
and validating the automatic pre-operative target prediction for
DBS implantation [7]. Second, at the time of programming, the
neurologist is provided with a 3D display of the position of the
electrodes in the efficacy map overlaid on high resolution MR
images. This permits correlation of these positions with anatomy,
thereby facilitating spatial orientation and navigation between the
contacts. Third, as the number of patients increases, maps of side
effects would be created. Currently, only is a crude definition of
efficacy used: reduction in rigidity weighted by the therapeutic
voltage window (i.e., the difference between the voltage required
to suppress the symptoms and voltage inducing side effects). This
definition would be refined to improve the way side effects are
taken into consideration. To achieve this, maps of side effects
would be created. This permits an automatic multi-parameter
optimization procedure that will minimize side effects while
maximizing the positive effects of the stimulation. Finally, the
electric field produced by a specific stimulation configuration is
modeled and this electric field is superimposed on the efficacy and
side effect maps. This permits the neurologist to visualize
interactively the effect of parameter settings on the region being
affected and facilitate multi-electrode programming.
[0114] The foregoing description of the exemplary embodiments of
the invention has been presented only for the purposes of
illustration and description and is not intended to be exhaustive
or to limit the invention to the precise forms disclosed. Many
modifications and variations are possible in light of the above
teaching.
[0115] The embodiments were chosen and described in order to
explain the principles of the invention and their practical
application so as to enable others skilled in the art to utilize
the invention and various embodiments and with various
modifications as are suited to the particular use contemplated.
Alternative embodiments will become apparent to those skilled in
the art to which the present invention pertains without departing
from its spirit and scope. Accordingly, the scope of the present
invention is defined by the appended claims rather than the
foregoing description and the exemplary embodiments described
therein.
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