U.S. patent application number 14/214960 was filed with the patent office on 2014-07-17 for multi-dimensional image reconstruction.
This patent application is currently assigned to Biosensors International Group, Ltd.. The applicant listed for this patent is Biosensors International Group, Ltd.. Invention is credited to Michael Nagler, Benny Rousso.
Application Number | 20140200447 14/214960 |
Document ID | / |
Family ID | 34794366 |
Filed Date | 2014-07-17 |
United States Patent
Application |
20140200447 |
Kind Code |
A1 |
Rousso; Benny ; et
al. |
July 17, 2014 |
MULTI-DIMENSIONAL IMAGE RECONSTRUCTION
Abstract
Apparatus for radiation based imaging of a non-homogenous target
area having distinguishable regions therein, comprises: an imaging
unit configured to obtain radiation intensity data from a target
region in the spatial dimensions and at least one other dimension,
and an image four-dimension analysis unit analyzes the intensity
data in the spatial dimension and said at least one other dimension
in order to map the distinguishable regions. The system typically
detects rates of change over time in signals from
radiopharmaceuticals and uses the rates of change to identify the
tissues. In a preferred embodiment, two or more
radiopharmaceuticals are used, the results of one being used as a
constraint on the other.
Inventors: |
Rousso; Benny;
(Rishon-LeZion, IL) ; Nagler; Michael; (Tel-Aviv,
IL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Biosensors International Group, Ltd. |
Hamilton |
|
BM |
|
|
Assignee: |
Biosensors International Group,
Ltd.
Hamilton
BM
|
Family ID: |
34794366 |
Appl. No.: |
14/214960 |
Filed: |
March 16, 2014 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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11656548 |
Jan 23, 2007 |
8676292 |
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14214960 |
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11034007 |
Jan 13, 2005 |
7176466 |
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11656548 |
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60535830 |
Jan 13, 2004 |
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Current U.S.
Class: |
600/432 ;
600/431 |
Current CPC
Class: |
A61B 6/481 20130101;
A61M 5/007 20130101; A61B 6/4057 20130101; G01T 1/166 20130101;
A61B 6/486 20130101; G01T 1/161 20130101; A61B 6/4258 20130101;
A61B 90/39 20160201; A61B 6/5217 20130101; A61B 6/5241
20130101 |
Class at
Publication: |
600/432 ;
600/431 |
International
Class: |
A61B 6/00 20060101
A61B006/00; A61M 5/00 20060101 A61M005/00; A61B 19/00 20060101
A61B019/00 |
Claims
1. A method of characterizing tissue, comprising: imaging a tissue
using a first marker; imaging the tissue using a second marker; and
characterizing the tissue by analyzing a difference between image
data obtained from said imaging using a first marker and imaging
using a second marker.
2. A method according to claim 1, wherein imaging a tissue
comprises generating a series of images of the tissue from
different views.
3. A method according to claim 1, wherein imaging a tissue
comprises generating a series of images at different time
intervals.
4. A method according to claim 1, analyzing a difference between
image data obtained from said imaging using a first marker and
imaging using a second marker comprises superimposing images
obtained from said imaging a tissue using a first marker and
imaging the tissue using a second marker.
5. A method according to claim 1, wherein imaging a tissue using a
first marker comprises identifying a region of interest in the
tissue and wherein imaging the tissue using a second marker
comprises imaging said region of interest.
6. A method according to claim 1, analyzing a difference between
image data obtained from said imaging using a first marker and
imaging using a second marker comprises constraining image date
obtained from imaging using a second marker by image data obtained
from imaging using a first marker.
7. A method according to claim 1, further comprising injecting a
patient with said first and second marker simultaneously.
8. A method according to claim 1, further comprising injecting a
patient with said first and second marker at different times.
9. A method according to claim 1, wherein characterizing the tissue
comprises identifying if the tissue is diseased or
non-diseased.
10. A method according to claim 1, wherein analyzing further
classifying the image data of from each voxel based on correlation
and assessing the most probable tissue classification for each
voxel.
11. A method according to claim 1, wherein said imaging is tuned
according to expected photon count from said tissue.
12. A method according to claim 1, wherein at least one of said
first marker and second marker is analyzed for its kinetic
properties.
13. A method according to claim 1, further comprising imaging the
tissue using at least one additional marker and wherein said
analyzing comprises analyzing a difference between image data
obtained from said imaging using a first marker, imaging using a
second marker and imaging using at least one additional marker.
14. A system for characterizing tissue, the apparatus comprising: a
first imager for imaging tissue using a first marker; a second
imager for imaging tissue using a second marker; and an analyzing
circuit for analyzing image date from said first and second imager
and characterizing the imaged tissue based on said analysis.
15. A system according to claim 14, wherein said first and second
imager are adapted to image tissue from different views.
16. A system according to claim 14, wherein said analyzing circuit
analyzes image data obtained at different time intervals.
17. A system according to claim 14, wherein said analyzing circuit
superimposes images obtained from said first imager and images
obtained from said second imager.
18. A system according to claim 14, wherein said analyzing circuit
further analyzes image data obtainer from said first imager to
identify a region of interest and wherein said second imager images
said region of interest.
19. A system according to claim 14, wherein said analyzing circuit
constrains image data obtained from said second imager by image
data obtained from said first imager.
20. A system according to claim 14, wherein said analyzing circuit
identifies if said tissue is diseased or non-diseased.
21. A system according to claim 14, wherein the system further
comprises a library of patterns for different cell types and
wherein said analyzing circuit classifies image data from voxels
based on correlation for assessing a tissue classification for each
voxel.
22. A system according to claim 14, wherein said analyzing circuit
further tunes said first and second imager according to expected
photon count from said tissue.
23. A system according to claim 14, wherein said analyzing
comprises analyzing the kinetic properties of at least one of said
first and second marker.
24. A system according to claim 14, further comprising at least one
additional imager for imaging tissue using at least one additional
marker and wherein said analyzing circuit analyzes image date from
said first, second and at least one additional imager.
Description
RELATED APPLICATIONS
[0001] This application is a continuation of U.S. patent
application Ser. No. 11/656,548 filed Jan. 23, 2007, which is a
continuation of U.S. patent application Ser. No. 11/034,007 filed
Jan. 13, 2005, now U.S. Pat. No. 7,176,466, which claims the
benefit of priority of U.S. Provisional Patent Application No.
60/535,830 filed Jan. 13, 2004. The contents of the above
applications are all incorporated by reference as if fully set
forth herein in their entirety.
FIELD AND BACKGROUND OF THE INVENTION
[0002] The present invention relates to multi-dimensional image
reconstruction and, more particularly, but not exclusively to such
image reconstruction based on a diffuse radioactive source or
sources.
[0003] Radiological imaging is generally carried out on a living
target, which of course means a mix of tissues in close proximity,
if not actually overlapping. The general procedure is to feed the
patient with one or more radioactive markers prior to the imaging
process. The radioactive markers are taken up by the digestive
system and pass into the bloodstream. From the bloodstream the
marker passes into the different tissues at varying rates depending
on the tissue type. Some tissues absorb markers faster than others
and some tissues absorb certain markers faster than others.
Furthermore certain tissues flush out the markers faster than
others, and again the rate of flushing out may also depend on the
kind of marker being used.
[0004] As a result, radioactive marking in fact creates a dynamic
system in the body in which the relative darkness of a given tissue
is related to a time factor. The radiologist knows that if he wants
a good image of say the liver following application of a given
marker then he should wait a certain number of hours from
application of the marker before taking the image. Even so, the
liver is not differentiated clearly from the other tissues.
[0005] Examples of radiopharmaceuticals include monoclonal
antibodies or other agents, e.g., fibrinogen or fluorodeoxyglucose,
tagged with a radioactive isotope, e.g., 99Mtechnetium, 67gallium,
201thallium, 111indium, 123iodine, 125iodine and 18fluorine, which
may be administered orally or intravenously. The
radiopharmaceuticals are designed to concentrate in the area of a
tumor, and the uptake of such radiopharmaceuticals in the active
part of a tumor, or other pathologies such as an inflammation, is
higher and more rapid than in the tissue that neighbors the tumor.
Thereafter, a radiation-emission-measuring-probe, which may be
configured for extracorporeal or intracorporeal use, is employed
for locating the position of the active area. Another application
is the detection of blood clots with radiopharmaceuticals such as
ACUTECT from Nycomed Amersham for the detection of newly formed
thrombosis in veins, or clots in arteries of the heart or brain, in
an emergency or operating room. Yet other applications include
radioimaging of myocardial infarct using agents such as radioactive
anti-myosin antibodies, radioimaging specific cell types using
radioactively tagged molecules (also known as molecular imaging),
etc.
[0006] The usual preferred emission for such applications is that
of gamma rays, which emission is in the energy range of
approximately 11-511 KeV. Beta radiation and positrons may also be
detected.
[0007] Radioactive-emission imaging is performed with a
radioactive-emission-measuring detector, such as a room
temperature, solid-state CdZnTe (CZT) detector, which is among the
more promising that is currently available. It may be configured as
a single-pixel or a multi-pixel detector, and may be obtained, for
example, from eV Products, a division of II-VI Corporation,
Saxonburg Pa., 16056, or from IMARAD IMAGING SYSTEMS LTD., of
Rehovot, ISRAEL, 76124, www.imarad.com, or from another source.
Alternatively, another solid-state detector such as CdTe, HgI, Si,
Ge, or the like, or a combination of a scintillation detector (such
as NaI(Tl), LSO, GSO, CsI, CaF, or the like) and a photomultiplier,
or another detector as known, may be used.
[0008] Considering the issue in greater detail, certain biological
or chemical substances such as targeted peptides, monoclonal
antibodies and others, are used for tagging specific living
molecules for diagnostic purposes. Ideally, these antibodies are
specific to the desired type of cells, based on adhering only to
specific molecular structures in which the antigene matching the
antibody is highly expressed. The use of imaging devices such as a
nuclear gamma probe or a visual video probe can detect radiation
emanating from taggants such as radionuclei or fluorescent dies
that have been appended to the antibody before being delivered to
the living body. An example is a cancerous cell of a prostate tumor
on whose membrane there is an over expression of the Prostate
Specific Membrane Antigen (PSMA). When a monoclonal antibody (Mab)
such as Capromab Pendetide (commercially available as ProstaScint
manufactured by Cytogen Corp.) is labeled with radioactive Indium
(In 111) and is systemically delivered to the body, the Mab is
carried by the blood stream and upon reaching the prostate tissue,
adheres to the PSMA. The high energy radiation photons emitted by
the radioactive Indium can be detected using a nuclear camera,
indicating the presence and the specific location of the tumor.
[0009] Unfortunately, given the complexity of living organisms, in
many instances the same antigen is also expressed in more than just
the tissue under investigation. The antibody will thus also "paint"
additional tissues such as infection areas, in addition to the
tissue of interest. The radioactive readings taken from this
additional tissue will be falsely interpreted as tumor areas,
reducing the specificity of the test being performed.
[0010] The `Target to Background` ratio that characterizes every
such antibody for a given target cell type is one of the major
issues that determine the ability to perform proper diagnosis, and
guided procedures.
[0011] Since the uptake clearance of such a marker by the various
tissues (target and background) varies over time, standard
diagnosis protocols usually recommend taking an image at the time
at which the ratio of Target emission vs. Background emission is
the highest.
[0012] In an experimental system tried out by researchers, two
markers were supplied to various patients and then images were
taken at successive intervals for each of the markers. Certain
features in the target areas showed up clearly in all images, other
features were clear for all images of one marker but faded in and
faded out for the other marker, and yet other features faded in and
out for both markers but at different times. The researchers were
able to use their knowledge of the behaviors of the two markers
with different tissues in order to identify the features in the
images.
[0013] The above system therefore relies on the knowledge of the
researchers to put together information received from multiple
images into an understanding of what the radio-imaging shows. In
the general hospital environment it is not possible to guarantee
that the necessary expertise is available, at least not for the
amount of time that such a system would require.
[0014] There is thus a widely recognized need for, and it would be
highly advantageous to have, a radiological imaging system devoid
of the above limitations.
SUMMARY OF THE INVENTION
[0015] According to one aspect of the present invention there is
provided apparatus for radiation based imaging and analysis of a
non-homogenous target area having distinguishable regions therein,
the apparatus comprising: [0016] an imaging unit configured to
obtain radiation emission data from said target region in the
spatial dimensions and at least one other dimension, and [0017] an
image multi-dimensional analysis unit associated with said imaging
unit for analyzing said obtained emission data in said spatial
dimensions and said at least one other dimension in order to
discern patterns across said dimensions.
[0018] According to a second aspect of the present invention there
is provided apparatus for radiation based imaging of a
non-homogenous target area having distinguishable regions therein,
the apparatus comprising: [0019] an imaging unit configured to
obtain radiation emission data from said target region in the
spatial dimensions and a time dimension, and [0020] an image
multi-dimensional analysis unit associated with said imaging unit
for analyzing said obtained emission data in said spatial
dimensions and said time dimension in order to discern at least one
property from a time profile of a marker in said distinguishable
regions of said target area.
[0021] According to a third aspect of the present invention there
is provided apparatus for radiation based imaging and analysis of a
target area, the apparatus comprising: [0022] an imaging unit
configured to obtain radiation emission data from said target
region in the spatial dimensions and at least one other dimension,
and [0023] an image multi-dimensional analysis unit associated with
said imaging unit for analyzing said obtained emission data in said
spatial dimensions and said at least one other dimension in order
to discern patterns within a respective target region.
[0024] According to a fourth aspect of the present invention there
is provided a method of radiation based imaging, comprising: [0025]
acquiring data; [0026] reconstructing an image from said data;
[0027] automatically detecting at least one region, in said image;
and [0028] automatic controlling at least one of said acquiring and
said reconstructing to generate an improved image, based on said
detecting.
[0029] According to a fifth aspect of the present invention there
is provided a method for improved tomographic reconstruction of
radiation intensities, comprising: [0030] initially reconstructing
at least one distinguishable region from said radiation intensities
[0031] extracting parameters associated with different properties
of said reconstructed distinguishable region; [0032] classifying
said at least one reconstructed distinguishable region by the
extracted parameters associated therewith; [0033] iteratively using
the classification of said extracted parameters to improve
delimitation of said classified reconstructed distinguishable
region, thereby to improve reconstruction thereof.
[0034] According to a sixth aspect of the present invention there
is provided a method of optimization of therapy of the human or
animal body, comprising: [0035] identifying a target region for
said therapy; [0036] applying to a patient at least one radioactive
marker; [0037] obtaining radiation emission data from said target
region in the spatial dimensions and at least one other dimension,
and [0038] analyzing said obtained emission data in spatial
dimensions and at least one other dimension in order to discern
patterns across said dimensions, thereby to characterize said
target region, and [0039] optimizing said therapy based on said
characterization.
[0040] According to a seventh aspect of the present invention there
is provided apparatus for multi-dimensional image reconstruction
based on data acquired from an imaging unit for obtaining radiation
intensity data from a target region in the spatial dimensions and
at least one other dimension, the apparatus comprising: [0041] an
image four-dimension analysis unit configured to analyze said
obtained intensity data in said spatial dimension and said at least
one other dimension in order to map at least one distinguishable
region in terms of a property, said property being that of at least
one member of the group comprising a tissue, a disease, a disease
stage and a physiological process.
[0042] Unless otherwise defined, all technical and scientific terms
used herein have the same meaning as commonly understood by one of
ordinary skill in the art to which this invention belongs. The
materials, methods, and examples provided herein are illustrative
only and not intended to be limiting.
[0043] Implementation of the method and system of the present
invention involves performing or completing certain selected tasks
or steps manually, automatically, or a combination thereof.
Moreover, according to actual instrumentation and equipment of
preferred embodiments of the method and system of the present
invention, several selected steps could be implemented by hardware
or by software on any operating system of any firmware or a
combination thereof. For example, as hardware, selected steps of
the invention could be implemented as a chip or a circuit. As
software, selected steps of the invention could be implemented as a
plurality of software instructions being executed by a computer
using any suitable operating system. In any case, selected steps of
the method and system of the invention could be described as being
performed by a data processor, such as a computing platform for
executing a plurality of instructions.
BRIEF DESCRIPTION OF THE DRAWINGS
[0044] The invention is herein described, by way of example only,
with reference to the accompanying drawings. With specific
reference now to the drawings in detail, it is stressed that the
particulars shown are by way of example and for purposes of
illustrative discussion of the preferred embodiments of the present
invention only, and are presented in order to provide what is
believed to be the most useful and readily understood description
of the principles and conceptual aspects of the invention. In this
regard, no attempt is made to show structural details of the
invention in more detail than is necessary for a fundamental
understanding of the invention, the description taken with the
drawings making apparent to those skilled in the art how the
several forms of the invention may be embodied in practice.
[0045] In the drawings:
[0046] FIG. 1 is a simplified diagram showing a single detector
detecting over a target region;
[0047] FIG. 2 is a simplified diagram showing two detector
positions (not necessarily simultaneously) allowing
three-dimensional information to be obtained from a target
region;
[0048] FIGS. 3A-3D show a series of four time absorption
characteristics for different radiopharmaceuticals within different
tissues;
[0049] FIG. 4 is a simplified schematic diagram showing a device
for driving an imaging head and allowing control of the imaging
head by the image analyzer device;
[0050] FIG. 5 is a simplified flow chart illustrating the image
analysis process carried out by the analyzer in FIG. 4 in the case
of a single marker;
[0051] FIGS. 6A-6D illustrate two sets of successive images of the
same target area taken using two different markers respectively,
according to a preferred embodiment of the present invention;
[0052] FIG. 7A is a simplified flow chart illustrating a procedure
according to a preferred embodiment of the present invention using
two or more markers for first of all identifying an organ and then
secondly determining the presence or otherwise of a pathology
within that organ;
[0053] FIG. 7B is a simplified flow chart showing a generalization
of FIG. 7A for the general case of two specific patterns;
[0054] FIG. 8 is a simplified flow chart illustrating a procedure
according to a preferred embodiment of the present invention using
two or more markers for identifying a region of low emissivity
within a target area and using that identification to control
imaging resources to better image the identified region; and
[0055] FIGS. 9A-9D illustrate two sets of successive images of the
same target area taken using two different markers, in a similar
way to that shown in FIG. 6, except that this time the regions of
interest are one inside the other.
DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0056] The present embodiments comprise an apparatus and a method
for radiation based imaging of a non-homogenous target area having
regions of different material or tissue type or pathology. The
imaging uses multi-dimensional data of the target area in order to
distinguish the different regions. Typically the multi-dimensional
data involves time as one of the dimensions. A radioactive marker
has particular time-absorption characteristics which are specific
for the different tissues, and the imaging device is programmed to
constrain its imaging to a particular characteristic.
[0057] The result is not merely an image which concentrates on the
tissue of interest but also, because it is constrained to the
tissue of interest, is able to concentrate imaging resources on
that tissue and thus produce a higher resolution image than the
prior art systems which are completely tissue blind.
[0058] The principles and operation of a radiological imaging
system according to the present invention may be better understood
with reference to the drawings and accompanying description.
[0059] Before explaining at least one embodiment of the invention
in detail, it is to be understood that the invention is not limited
in its application to the details of construction and the
arrangement of the components set forth in the following
description or illustrated in the drawings. The invention is
capable of other embodiments or of being practiced or carried out
in various ways. Also, it is to be understood that the phraseology
and terminology employed herein is for the purpose of description
and should not be regarded as limiting.
[0060] Reference is now made to FIG. 1, which illustrates a simple
Geiger counter taking an image of a target according to the prior
art. Geiger counter 10 is placed in association with target 12 and
absorbs any radioactive particles that come its way. In general the
radioactive particles arriving at the Geiger counter arrive from
somewhere within cone 14. The Geiger counter has no information as
to the depth from which the particle comes and cannot even
distinguish between particles arriving from different directions
within the cone. Thus in principle the prior art Geiger counter
gives low resolution one dimensional information.
[0061] If the counter is now moved to different positions over the
surface of the target then the data from the different positions
can be built up into a low resolution two-dimensional image.
[0062] One way of increasing the resolution of the Geiger counter
is to make it smaller. Then the cone, whilst retaining the same
geometry, gives higher resolution data.
[0063] The detector takes (y.sub.t).sub.t=1.sup.T samples to form a
data set, which would typically be a two-dimensional image of the
target from a given direction.
[0064] Reference is now made to FIG. 2, which is a simplified
diagram showing how three-dimensional information can be obtained
from the target. Parts that are the same as in previous figures are
given the same reference numerals and are not referred to again
except as necessary for understanding the present embodiment. A
second Geiger counter 16 is placed essentially at right angles to
the first Geiger counter and obtains a similar kind of image to the
first Geiger counter. However, since the two cones overlap, the
images produced can be cross-correlated to infer the presence of
hot or cold radiation sources in three dimensions.
[0065] Reference is now made to FIG. 3, which is a sequence of
graphs illustrating the different absorption characteristics for
different tissues of a given radioactive marker. Typical markers
that may be considered are Thalium 201 and Technitium 99. FIG. 3a
indicates a typical absorption characteristic of thalium 201 for
blood, thalium 201 being a particularly good marker for blood. The
marker is generally absorbed by the blood fairly rapidly following
digestion and then gradually disappears as it is taken up by the
various tissues and organs including the kidneys. Marker material
from the tissues eventually finds its way back into the blood for
excretion. That which is absorbed by the kidneys is excreted
directly and not seen again.
[0066] FIGS. 3B, 3C and 3D show time absorption characteristics for
technitium 99 for different tissues, and it will be seen that the
characteristic is generally curved but peaks at different times for
the different tissues.
[0067] The principle on which the present embodiments are based is
as follows: Considering the graphs in FIG. 3, it will be apparent
that a region belonging to a single tissue will behave in a uniform
manner as regards signal intensity. That is to say, a given marker
will be taken up and then expelled at the same rate over a given
tissue, whereas this rate will be different for other tissues. If
therefore a series of successive images are taken of the target and
the images are analyzed region by region for rates of change of
intensity, a particular desired region can be identified by virtue
of having rates of change in intensity that fit with a given
characteristic. The regions are distinguishable in this way even if
the region of interest is heavily overlapped with other
regions.
[0068] Reference is now made to FIG. 4, which shows apparatus for
radiation-based imaging of a non-homogenous target area. Apparatus
20 comprises an imaging unit 22 which itself consists of a series
of small Geiger counters 24.1 . . . 24.n arranged on an imaging
head. The imaging unit is controlled by motion controller 26 to
take readings from different locations around the target area.
Preferably, the motion of the imaging head is controlled by
software via servo-motors. In addition the motions, either of the
individual Geiger counters or of groupings of the Geiger counters,
is also controlled by software via servo-motors.
[0069] In a preferred embodiment, the signals received from the
individual Geiger counters are summed to form a three-dimensional
image of the target area. The skilled person will appreciate that
the system could also be based on a two-dimensional image. In
either case, the signals are fed to an image analyzer 28, where the
signals are analyzed to form images.
[0070] In the preferred embodiments, the image analyzer is able to
use the marker take up characteristics to compare successive images
and identify regions of particular interest, and then to
concentrate imaging resources on those regions. That is to say the
image analyzer is in fact able to control further operation of the
imager.
[0071] Reference is now made to FIG. 5, which is a simplified flow
chart illustrating the image analysis process carried out by
analyzer 28 in the case of a single marker. Preferably a series of
images of the same views are taken at different times, stage 30,
and a three-dimensional overall image of the target is formed for
each time. The analyzer then analyzes each of the three-dimensional
overall images for local intensities at different locations around
the target, stage 32. The local intensities are noted and the same
locations on the different images are superimposed in stage 34.
From the superpositioning, local rates of change of intensity
between the images may be obtained in stage 36. The rates of change
are compared with the pre-obtained characteristics for the marker
with the different tissues in stage 38, and the data are then
constrained to those localities which conform to the desired
predetermined characteristics in stage 40. As a result the imaging
process can be used to identify and concentrate on localities of
interest and data from other localities can be jettisoned.
Consequently, the image analysis is able to concentrate its
resources on the tissues of interest and a higher resolution final
image can be produced.
[0072] It will be appreciated that in many cases two types of
tissue may be superimposed, of which only one of the tissues is of
interest. In this case it is of equal importance both to exclude
the one tissue that is not of interest and to include the tissue
that is of interest. It may be that the best marker for one tissue
may not be the best marker for the other tissue. The system as
described with respect to FIGS. 4 and 5 may be adapted to use with
two or more markers, as exemplified in FIG. 6. Each marker produces
a radioactive particle of different energy level, and therefore the
data from the different markers can be collected and summed
separately to form different images. Mathematically the different
data sets obtained from the different energy level signals may be
treated as different dimensions of a multi-dimensional vector. For
each of the marker-images the appropriate characteristics are used
to identify the tissues of interest, and the results can be
cross-checked between the different markers. The different tissues
can be mapped and the image analysis can concentrate on the area of
interest. As a result the system uses both time and particle energy
as separate dimensions in addition to the spatial dimensions in
order to characterize or map the tissues.
[0073] As a result the image analysis unit is able to produce a
final result treating the various tissue regions as separate
entities. Furthermore, as the system is aware of the regions as
entities it is able to further direct the imaging process to
concentrate on the regions of interest.
[0074] An example in which regions at least partially overlap is
the heart. Generally, scans of the heart are interested in the
muscular walls of the heart. Although the chambers of the heart are
filled with blood, any signal coming from the blood is in fact
noise to this kind of scan. It is therefore advantageous to carry
out an imaging process which is able to positively identify signals
from the muscular heart walls and at the same time exclude the
blood.
[0075] Referring now to FIG. 6, and in a preferred embodiment, the
patient ingests two markers, thalium 201 and technetium 99. The
first of these is an effective blood marker and two successive
thalium images are shown in FIGS. 6a and 6b, and the second is more
effective at marking muscle tissue and two successive images
thereof are shown in FIGS. 6c and 6d. The heart is imaged at
intervals chosen both for the characteristic for thalium 201 in
blood and for the characteristic of technetium 99 in muscle. The
result is a series of images for each of the markers. The series
for thalium 201 may be constrained to show the regions of blood
quite clearly, and to filter out other regions. In here a blood
vessel is shown clearly in 6a and more faintly in 6b where the
thalium has mostly been flushed out. The series for technetium 99,
FIGS. 6c and 6d show muscle wall structures. The first of the two
images apparently shows larger structures but in fact all that it
is showing is that much technetium has not yet been absorbed in the
muscle. The second image 6d may therefore be used to constrain the
first image 6c to show only the muscle walls regions. The two
series of images may then be superimposed to filter out from the
technetium 99 images 6c and 6d anything that appears strongly in
the thalium images 6a and 6b. The filtering may additionally remove
anything that appears strongly in both images as coming from
outside the region.
[0076] In the above example, two regions were of respectively
positive and negative interest, meaning one for concentrating on
and the other for filtering out. It will be appreciated that
several regions or several tissue types may be of positive interest
or there may be any combination of regions with just one being of
positive interest. Alternatively all regions may be of positive
interest but importance may be attached to discriminating between
the different signals from the different regions.
[0077] The system is able to use the mapping to generate an image
comprising the different tissue regions as distinct entities. As a
consequence of the mapping process, the system is able to be aware
electronically of the different regions and thus control both the
imaging head and the analysis unit to concentrate their resources
on specific regions. The result is greater resolution for the
regions of interest.
[0078] The preferred embodiments may be used to expand the
information obtained from the markers, using either or both of
examining the kinetics of the markers over time and using several
markers concurrently.
[0079] In order to increase the specificity of the test, additional
second substances ("secondary substances"), with reactivity and
pharmaco-kinetics differing from those of the first substance can
be used in order to enhance the differentiation between the
different pathologies, as explained above with respect to FIG. 6.
The secondary substance, in this case thalium, ideally marks only a
subset of the population marked by the primary substance and does
so at different rates. Such a difference exists because of
different affinity to various cell types and different
participation in metabolic reactions of different tissues. The
difference is associated with the rate of marking and/or with the
location of the marking.
[0080] Upon reading the radioactive signals emanating from the
voxels stemming from different substances at different time
instances, it is possible to build for every voxel a multi
dimensional data matrix Sjk whose elements are intensity readings
taken at instances K resulting from the interaction of Substance J.
Examination of every voxel of tissue in this multidimensional space
quantifies the temporal and specific reaction of the tissue to
different substances and thus increases the probability of specific
detection of different pathologies. Furthermore, standard image
processing techniques can be used in order to more accurately
define the spatial location of different pathologies.
[0081] In addition to the method above, spatial properties that
reflect typical relationships between neighboring voxels may also
be a criteria and represented as part of the pattern of the tissue
type.
[0082] Reference is now made to FIG. 7, which illustrates an
additional statistical approach. In FIG. 7, an automatic algorithm
based on expected intensities may be used to determine if the
entire organ or region is diseased or non-diseased. Once it is
possible to become tissue-aware, as explained above, then it is no
longer necessary to carry out such analysis on a voxel-by-voxel
basis. Rather the system is able to determine where the organ lies
say using a first marker and then a second marker may be imaged
using the constraint of the organ location, the second marker being
able to locate the presence of the pathology.
[0083] Reference is now made to FIG. 8 which illustrates a method
for using the tissue aware properties of the present embodiments in
order to tune detection to match tissue or organ emissivities.
Generally, any region, no matter how much radiation it produces,
can always be imaged sufficiently simply by leaving the measuring
device in position for long enough. However, in many cases there
may be limited time available. For such cases in which there is
limited time for data acquisition, the present embodiments can be
used to identify regions that may be expected to produce less
emission. The system may then tune imaging resources or resolution
onto those tissues according to the number of photons available.
Clearly the more photons obtained the more reliable is the data,
and therefore a tissue aware system is able to concentrate more
detectors on the weaker signaling tissues.
[0084] If there are still not enough photons, or there are not
enough detectors, then another way of pooling resources is to merge
neighboring voxels (or regions). Such a procedure may reduce
resolution, but will increase the overall number of photons for
that merged region, and thus enable better classification of that
region based on a more reliable photon count. Such a compromise
enables analysis of the same collected data by ways that would
allow high resolution where there are enough photons and lower
resolutions where there are less while maintaining reliability of
the analysis.
[0085] Again the tissue regions may be identified using multiple
markers.
[0086] The above-described embodiment may lead to controlled
sensitivity levels, currently not available with radioimaging.
[0087] The concept of using multiple antibodies can be used for
therapy purposes, as in the following:
[0088] The specificity of a single antibody carrying a drug (or
radioactive therapy) determines the chance for non-target tissue to
receive the drug, and thus be subject to any toxicity of the drug.
In cases where there are several antibodies, each with limited
specificity, but with affinity to different `background` tissue, a
combination of antibodies may be used to improve the overall
specificity, and thus to reduce overall toxicity and enable higher
efficacy of treatment.
[0089] For example, if a first antibody (A1) based drug binds to
the target N1 folds its affinity to the closest non-target tissue
(B1), and a second antibody (A2) with similar drug has target
affinity which is N2 folds higher than its closest non-target
tissue (B2), then using a merged therapy will enable better target
vs. non-target specificity, which is better than N1 and N2
(assuming B1 and B2 are different).
[0090] In a more generalized embodiment, the system may include a
signal analysis module, including a library of patterns that are
typical for every cell type. Each type of cells has one or more
patterns associated with it, and the pattern determines how a set
of markers injected according to a specific protocol (dosage, time,
etc) may be expressed in that cell type. The analysis includes
classification of the readings from each voxel based on
correlation, or other statistical tools for assessing the most
probable tissue classification for each voxel.
[0091] Since there may be several cell types for a given disease
(e.g. cancer may show in several forms), the algorithm may be
optimized to determine the exact tissue type per voxel or region.
Alternatively, the algorithm may be optimized to determine the
general property of diseased/non-diseased, while taking the
specific classification only as a factor in the statistical
analysis.
[0092] It should be noted that the system may allow for various
protocols for administering the markers, where injection of the
various markers may be simultaneous, or multiple injections at
various times, as various markers have different lifetime in the
circulation.
[0093] The issue of generating imaging using two or more markers is
now considered mathematically.
[0094] An intensity distribution I, conventionally defined in terms
of radioactive emissions per seconds, is now redefined as a vector
of distributions over the volume U, forming our input space. Each
dimension of the vector is a different one of the
radiopharmaceuticals. The universal set U comprises a set of basic
elements u (e.g., pixels in two dimensional spaces, voxels in three
dimensional spaces), and I(u) is the intensity in a given basic
element u .di-elect cons. U. For j radiopharmaceuticals this
becomes I(u)(j,t) An inverse (or reconstruction) problem arises
when one cannot sample directly from I, but can sample from a given
set of views .PHI.. A projection .phi..di-elect cons..PHI. is
defined by the set of probabilities {.phi.(u):u.di-elect cons.U},
where .phi. (u) is the probability of detecting a radioactive
emission from a voxel u, as defined by viewing parameters, such as
the physical and geometrical properties of the detecting unit, as
well as the attenuation parameters of the viewed volume U, and the
time parameters. A measurement is obtained by choosing a view
.phi..di-elect cons..PHI., and then sampling according to the
viewing parameters.
[0095] For j radiopharmaceuticals or markers and k detectors, the
probability of seeing a particle becomes .phi.jk (u)
[0096] In the following analysis, I is the intensity of a
radioactive substance, and the viewing parameters include the
geometrical properties of a collimated detecting unit and the
detecting unit's position and orientation with respect to volume U.
The number of radioactive emissions counted by the detecting unit
within a time interval is a Poisson distribution, where .phi. (u)
is the detection probability of a photon emitted from voxel
u.di-elect cons.U and the mean of the distribution is the weighted
sum .SIGMA.u.di-elect cons.U.phi.(u)I(u).
[0097] For the case of the kth detector a measurement
Yk=.SIGMA.u.di-elect cons.UXt(u), where X(U) is a Poisson
distribution.
X(j,k,t)(u)=I(i,t)(u).phi.(u)jk(u).
Where Y(j,k,t)=.SIGMA.X(j,k,t)(u).
Hence Y(j,k,t))=Poisson(Y(j,k,t))
[0098] The projection set is thus defined by a matrix .PHI., whose
rows are the projections of the chosen views. I is a vector of
densities (specified per each element in U), and (.PHI.I is a
vector of respective effective intensity levels for the views in
the set. A vector of measurements y is obtained by a random sample
from each view (according to the associated Poisson distribution).
As discussed above, there are various known reconstruction methods
that provide estimators for I given the projections .PHI. and the
measurements y.
[0099] Using the above mathematics the problem is solved (an image
created) one of the vectors say once an hour. The rates of change
are determined. Simultaneously the problem is solved for another of
the vectors at similar time intervals and the rates of change are
determined. Then a stage of cross-identification is carried out
between the two images, so that wanted tissues as identified by
each image minus unwanted tissues identified by each image are
concentrated on to form a new image. Cross-identification may be an
iterative process.
[0100] In the example given above of the imaging of the heart using
one blood marker and one muscular tissue marker, the areas
identified by the blood marker are subtracted. The areas identified
by the muscle marker are added, and those tissues not identified by
either are likewise ignored as being signals from outside the
target region.
[0101] The non-homogenous target area is typically a region of
living tissue, generally belonging to a patient. The
distinguishable regions within can be different tissues, different
organs, a mixture of blood and organ tissue as with the above
example of the heart, or tissue regions exhibiting differential
pathologies.
[0102] It is expected that during the life of this patent many
relevant markers, radiological imaging devices and two and three
dimensional imaging systems will be developed and the scopes of the
corresponding terms herein, are intended to include all such new
technologies a priori.
[0103] It is appreciated that certain features of the invention,
which are, for clarity, described in the context of separate
embodiments, may also be provided in combination in a single
embodiment. Conversely, various features of the invention, which
are, for brevity, described in the context of a single embodiment,
may also be provided separately or in any suitable
subcombination.
[0104] Although the invention has been described in conjunction
with specific embodiments thereof, it is evident that many
alternatives, modifications and variations will be apparent to
those skilled in the art. Accordingly, it is intended to embrace
all such alternatives, modifications and variations that fall
within the spirit and broad scope of the appended claims. All
publications, patents and patent applications mentioned in this
specification are herein incorporated in their entirety by
reference into the specification, to the same extent as if each
individual publication, patent or patent application was
specifically and individually indicated to be incorporated herein
by reference. In addition, citation or identification of any
reference in this application shall not be construed as an
admission that such reference is available as prior art to the
present invention.
* * * * *
References