Note : Les descriptions sont présentées dans la langue officielle dans laquelle elles ont été soumises.
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MEASUREMENT OF EXTENT OF CARDIAC MUSCLE INJURY
BACKGROUND OF THE INVENTION
1. Field of Disclosure
The present disclosure relates generally to methods for quantifying the extent
of
cardiac muscle injury in various regions of a patient's heart based on data
collected
from an array of electrodes in an electrocardiograph (ECG). The disclosure
also relates
to methods for classifying the overall extent of cardiac muscle injury in a
patient and for
diagnosing myocardial infarction (MI) based on the classification of the
overall extent of
cardiac muscle injury.
2. Discussion of the Related Art
An ECG is a device comprising a plurality of electrodes applied to the skin of
a
patient in the thoracic region. These electrodes measure electrical activities
in different
areas of the cardiac muscle. An ECG is a useful tool for diagnosing various
cardiac
disorders, such as MI and ischemia. In the case of acute MI (also known as
heart
attack), an ECG may be useful for identifying the damage to the cardiac
muscle.
The electrical signal recorded by an electrode may be traced on a standard
grid,
an example of which is shown in FIG. 1. On such a grid, time is represented
horizontally, progressing from left to right, and voltage is represented
vertically. In the
particular example shown in FIG. 1, each square has a width of 0.04 sec and a
height
of 0.1 mV.
FIG. 1 illustrates an exemplary ECG waveform of a normal heartbeat (or cardiac
cycle). As shown, each beat comprises a P wave 110, a QRS complex 120 and a T
wave 130. A portion 140 of the trace between the P wave and the QRS complex is
known as the PQ segment, and a portion 150 of the trace between the QRS
complex
and the T wave is known as the ST segment. A small U wave 160 is also visible
in this
example, although in general U waves are not always visible in normal
heartbeats. The
baseline voltage of the ECG waveform is known as the isoelectric line and is
shown as
line 170 in FIG. 1. Typically, the isoelectric line is determined according to
the portion
of the trace following the T wave and preceding the next P wave.
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Cardiac muscle injury may be indicated by an elevation or depression of the ST
segment of an ECG waveform. The ST segment is said to be elevated if it is at
higher
potential compared to the PQ segment of the waveform. An exemplary waveform
exhibiting ST elevation is shown in FIG. 2A, where the magnitude of elevation
is
represented by the distance d1 between the potential of the ST segment 210 and
the
potential of the PQ segment 220. Similarly, the ST segment is said to be
depressed if it
is at lower potential compared to the PQ segment. An exemplary waveform
exhibiting
ST depression is shown in FIG. 2B, where the magnitude of depression is
represented
by the distance d2 between the potential of the ST segment 230 and the
potential of the
PQ segment 240.
ST deviation is often associated with cardiac injury. For example, elevation
is
often associated with ST elevation myocardial infarction (STEMI), and
depression is
often associated with ischemia, which may be a pre-cursor to evolving MI.
Traditionally,
a 12-lead ECG is used to detect such abnormalities. However, due to the
relatively
small number of electrodes (typically 10), a 12-lead ECG can only indicate the
presence
of STEMI and the general area that is affected (e.g., septal, anterior,
lateral). Often,
STEMI is detected on as few as 2 electrodes, making it difficult to obtain
sufficient
information regarding the location and extent of the injury. In addition, a 12-
lead ECG
places most of the electrodes on the front of the chest, resulting in limited
reliability in
identifying STEMI occurring in other areas. For example, the 12-lead ECG has
been
known to miss STEMI occurring at the back surface of the heart.
Due to these limitations of a 12-lead ECG, other imaging modalities, such as
angiogram, MRI, and echocardiogram, have been used to estimate the area of
affected
cardiac tissue. These imaging methods require specialized equipment and
interpretation, and are therefore more costly and inconvenient for the
patient.
More recently, ECG devices with more electrodes, for example, 40 to 100
electrodes, have been developed to provide more comprehensive information on
the
electrical activity of the heart. This technique, which is sometimes referred
to as body
surface mapping (BSM), uses a large array of electrodes to cover a patient's
torso. An
example of a BSM arrangement is illustrated in FIGs. 3A and 3B, with FIG. 3A
showing
electrodes 310 and 320 applied to the front of the thoracic region and FIG. 3B
showing
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electrodes 330 applied to the back of the thoracic region. Further examples of
BSM
arrangements and devices are described in detail in U.S. Patents No. 5,419,337
and
No. 6,055,448.
Brief Summary of the Invention
In accordance with some embodiments of the invention, a method for quantifying
an extent of cardiac muscle injury is provided. The method comprises
determining a
magnitude of ST deviation based on electrocardiographic data obtained from at
least
one electrode in an electrocardiograph, the at least one electrode being
associated with
at least one region of a heart; determining an area factor for the at least
one electrode,
the area factor being associated with the at least one region; and computing
an ST
deviation volume for the at least one electrode, based, at least in part, on
the magnitude
of ST deviation and the area factor.
In accordance with some further embodiments of the invention, a computer-
readable medium having computer-executable instructions for carrying out the
above
method is provided.
In accordance with some further embodiments of the invention, a method for
diagnosing a patient based on aggregate ST deviation volume is provided. The
method
comprises: obtaining an aggregate ST deviation volume of the patient based on
magnitude and area information collected from an array of electrodes applied
to the
patient; obtaining one or more diagnostic thresholds using aggregate ST
deviation
volume data from a plurality of patients with confirmed diagnoses; and
comparing the
aggregate ST deviation volume of the patient against the diagnostic
thresholds.
In accordance with some further embodiments of the invention, a system for
quantifying an extent of cardiac muscle injury based on electrographic data
obtained
from a patient is provided. The system comprises one or more processors
programmed
to: determine a magnitude of ST deviation based on electrocardiographic data
obtained
from at least one electrode applied to the patient, the at least one electrode
being
associated with at least one region of a heart; determine an area factor for
the at least
one electrode, the area factor being associated with the at least one region;
and
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compute an ST deviation volume for the at least one electrode, based, at least
in part,
on the magnitude of ST deviation and the area factor.
Brief Description of the Drawings
FIG. 1 shows an ECG waveform of a normal heart beat traced on a standard
grid;
FIG. 2A shows an ECG waveform exhibiting ST elevation;
FIG. 2B shows an ECG waveform exhibiting ST depression;
FIG. 3A shows an array of electrodes applied to the front of a human torso;
FIG. 3B shows an array of electrodes applied to the back of a human torso;
FIGs. 4A-B show examples of ST deviation volume (STDV) for a single
electrode;
FIGs. 5A-B show examples of aggregate ST deviation volume for a plurality of
electrodes;
FIGs. 6A and 6B show, respectively, an anterior portion and a posterior
portion
of an exemplary BSM device for obtaining ECG data;
FIG. 6C shows an exemplary arrangement of electrodes into four regions;
FIG. 7 is a flow chart illustrating a method for calculating aggregate STDV;
FIG. 8 is a flow chart illustrating a method for diagnosing a patient;
FIGs. 9-12 illustrate aggregate STDV values of patients with confirmed MI or
confirmed non-MI diagnoses;
FIG. 13-20 are three-dimensional illustrations of example cases exhibiting ST
elevation and/or depression; and
FIG. 21 is a schematic illustration of an exemplary computer on which aspects
of
the invention may be implemented.
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DETAILED DESCRIPTION
This invention is not limited in its application to the details of
construction and the
arrangement of components set forth in the following description or
illustrated in the
drawings. The invention is capable of other embodiments and of being practiced
or of
being carried out in various ways. Also, the phraseology and terminology used
herein
is for the purpose of description and should not be regarded as limiting. In
the claims,
the use of "including," "comprising," "having," "containing," "involving," and
variations
thereof, is meant to encompass the items listed thereafter and equivalents
thereof as
well as additional items.
The Applicant has appreciated that BSM techniques may be enhanced by
providing a method for quantifying the extent of cardiac injury based on data
collected
from an array of electrodes. This may enable a physician to select an
appropriate
treatment for a patient diagnosed with MI based on the severity of the MI. It
may also
be used to assess a patient's condition before and after a percutaneous
coronary
intervention (PCI) procedure. Compared to other imaging modalities such as
angiogram, MRI, and echocardiogram, a BSM-based method for quantifying the
extent
of cardiac injury may be less expensive and more convenient.
The Applicant has further appreciated that data obtained from a BSM electrode
array may have two aspects or dimensions: the areas affected, for example, as
indicated by the distribution of electrodes detecting ST deviation, and the
magnitudes of
ST deviation detected by the individual electrodes. A measurement comprising
only
one of these two dimensions may not provide sufficient information. For
example, a
simple area count may reveal how wide spread the injury is, but may fail to
indicate the
severity of injury in the affected areas. Likewise, a measurement based solely
on the
magnitudes of ST deviation (e.g., taking the most severe deviation observed by
a single
electrode) may miss a mild but wide-spread injury.
In accordance with some embodiments of the invention, a new parameter, called
ST deviation volume (STDV), is used to assess the extent of cardiac muscle
injury. The
STDV parameter combines both area and magnitude information. As its name
suggests, the STDV of an individual electrode may be determined based on an
area of
the heart associated with the electrode and the magnitude of ST deviation
detected by
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the electrode. For instance, the STDV of an electrode may be calculated by.
multiplying
the magnitude of ST deviation detected by the electrode with an area factor
associated
with the electrode. As will be discussed in greater detail below, the
magnitude of ST
deviation may be scaled, or otherwise adjusted, based on the location of the
electrode
on the patient's torso and therefore the distance between the electrode and
the heart.
The area factor associated with the electrode may also be determined in a
number of
different ways, for example, by using the number of electrodes that are
associated with
the same region of the heart as the present electrode. In one embodiment, a
first
electrode that is associated with a densely populated region (i.e., a region
of the heart
to which many electrodes are associated) has a smaller area factor than a
second
electrode that is associated with a sparsely populated region (i.e., a region
of the heart
to which few electrodes are associated). Alternatively, each region of the
heart may be
projected to a region of the patient's torso, so that an area factor for a
particular
electrode may be determined using the density of electrodes in the region of
the torso in
which the particular electrode resides.
In some further embodiments, an aggregate STDV may be determined by
considering STDV values obtained from a plurality of electrodes. For example,
an
aggregate STDV may be computed as the sum of all STDV values, both elevation
and
depression, obtained from all electrodes in an electrode array. In this case,
the
aggregate STDV may be referred to as a total STDV. Alternatively, an aggregate
STDV
may be computed as the sum of all STDV values obtained from electrodes
detecting
STDV elevation. In this case, the aggregate STDV may be referred to as a total
ST
elevation volume (total STEV). Similarly, an aggregate STDV may be computed as
the
sum of all STDV values obtained from electrodes detecting STDV depression. In
this
case, the aggregate STDV may be referred to as a total ST depression volume
(total
STDpV).
Under some circumstances, total STEV and total STDpV may be more useful
than total STDV. For example, the Applicant has recognized that an area of ST
elevation is often accompanied by a reciprocal area of ST depression on the
opposite
side of the torso. If a patient is diagnosed with STEMI, it may be more
informative to
compare the patient's total STEV against a database of total STEV values.
Likewise, if
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a patient diagnosed with ischemia, it may be more informative to compare the
patient's
total STDpV against a database of total STDpV values.
The Applicant has also appreciated the need for a method by which a physician
may interpret an aggregate STDV value. In accordance with some embodiments of
the
invention, aggregate STDV values from patients with confirmed diagnoses (Ml or
non-
MI) are collected and stored in a database. The diagnoses may be obtained
using a
well-established method, such as testing for Troponin levels in the blood. In
some
embodiments, a diagnostic threshold for determining whether a patient is
suffering from
MI may be obtained based on aggregate STDV values from both confirmed MI and
confirmed non-MI patients. In a further embodiment, the aggregate STDV values
of
confirmed MI patients may be sorted, and bands representing the
top/middle/bottom
thirds may be identified. To diagnose a new patient, the aggregate STDV value
of the
new patient may be compared against the diagnostic threshold to determine
whether
the new patient suffers from MI, and if so, to classify the new patient's
condition as
severe, medium, or mild, based on the top/middle/bottom bands.. An appropriate
treatment (e.g., aggressive vs. moderate) may then be selected based on the
diagnosis
and classification.
In some further embodiments, separate databases may be maintained for total
STDV, total STEV, and/or total STDpV. These databases may be used for
classifying
patients with different diagnoses. For example, if the diagnosis is STEMI,
then the
patient's total STEV value may be compared against values in the total STEV
database.
Likewise, if the diagnosis is ischemia, then the patient's total STDpV value
may be
compared against values in the total STDpV database.
The Applicant has further appreciated that, since some non-MI conditions may
also lead to ST elevation, it may be desirable to exclude from the database
STDV
values from non-MI patients suffering from those conditions. One such
condition, left
bundle branch block (LBBB), will be further discussed below.
It should be appreciated that, although some embodiments are summarized
above, such examples are non-limiting. For example, the area factor used to
compute
STDV for an individual electrode may be obtained using another suitable
method,
without relying on the density of electrodes. Furthermore, the classification
bands
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discussed above may correspond to halves, quarters, or some other breakdown,
as
opposed to thirds.
Turning to FIGs. 4A-B, examples of STDV for a single electrode are
illustrated.
As discussed above, STDV for a single electrode may be determined based on an
ST
deviation magnitude detected by the electrode and an area factor associated
with the
electrode. The ST deviation magnitude may be determined using any suitable
technique, as the invention is not limited in this respect. For example, the
ST deviation
may be measured at any of the standard points such as the J point (also known
as STO,
the point at which the QRS complex meets the ST segment), ST60 (60 msec after
STO), or ST80 (80 msec after STO).
In some embodiments, the area factor associated with the electrode may depend
on the location of the electrode on the patient's torso. For example, the area
factor may
depend on the density of electrodes in the region of the torso in which the
electrode is
located. In some embodiments, the area factor of a first electrode in a
densely
populated region may be smaller than that of a second electrode in a sparsely
populated region, because the first electrode monitors a smaller area of the
heart
compared to the second electrode. However, as mentioned above, it should be
appreciated that the invention is not limited to any particular method for
determining an
area factor for an electrode.
FIG. 4A represents the STDV of a first electrode that is detecting an ST
elevation
of 3 mm and is associated with an area factor of 1. As a result, the STDV for
the first
electrode is 3 mm. In this embodiment, the area factor is obtained by taking a
ratio of
the electrode density in the most dense region (denoted EDh) and the electrode
density
in the region of the electrode (denoted EDr). More particularly, the first
electrode may
be located in the most dense region, or in a region with the same density as
the most
dense region. Therefore, the area factor A is simply 1.
FIG. 4B represents the STDV of a second electrode that is detecting an ST
elevation of 0.75 mm and is associated with an area factor of 4. The second
electrode
may be located in a region with lower density (e.g., 4 electrodes per dm2),
compared to
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the region with the highest density (e.g., 16 electrodes per dm2). Thus, the
area factor
for the second electrode can be computed as:
A=EDh/EDr=16/4=4.
As a result, the STDV for the second electrode is STDV = d * A = 0.75 * 4 = 3
mm, which
is the same as the STDV for the first electrode, even though the first
electrode is
detecting ST elevation of a much higher magnitude than the second electrode.
It should be appreciated that, although the area factors in the examples shown
in
FIGs 4A-B are ratios of densities and therefore unitless, the invention is not
limited in
this respect. An area factor may be computed in any suitable way, and may have
any
suitable unit as a result of the method by which it is computed. In general,
an area
factor provides information regarding the breadth of cardiac muscle injury,
and it need
not correspond to any physical measurement of area.
Similarly, the STDV of an electrode may also have any suitable unit. In the
embodiments illustrated in FIGs. 4A and 4B, STDV has the same unit as ST
deviation,
because the former is a product of the latter with a unitless area factor. In
other
embodiments, however, STDV may have other units, or may be treated as a
unitless
quantity.
FIGs. 5A-B illustrate examples of total STDV for a plurality of electrodes.
FIG.
5A shows eight columns, each representing STDV for one electrode. The height
of
each column represents the magnitude of ST elevation detected by the
corresponding
electrode. For example, column 510 has a height of 1.25, indicating that the
electrode
corresponding to column 510 detects an ST elevation of 1.25 mm. As shown in
FIG.
5A, the eight corresponding electrodes detect various levels of ST elevation,
ranging
from 0 mm to 1.25 mm. Moreover, the eight electrodes may be located in the
same
region of the patient's torso, for example, in the most densely populated
region, so that
the area factor for each electrode is 1. Summing all of the STDV values, the
.total STDV
for the eight electrodes in FIG. 5A is computed to be 3.75 mm.
FIG 5B also shows eight columns that correspond respectively to eight
electrodes. The magnitudes of ST elevation detected by these eight electrodes
range
from 0.25 mm to 0.5 mm. For example, column 510 has a height of 0.5,
indicating that
the electrode corresponding to column 520 detects an ST elevation of 0.5 mm.
As with
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FIG. 5A, each electrode is associated with an area factor of 1. As a result,
the total
STDV for the eight electrodes in FIG. 5B is also 3.75mm.
As shown in FIGs 5A-B, total STDV (or, in general, aggregate STDV) may
provide a meaningful way of comparing a patient with a larger ST deviation
that is only
exhibited in a small area against another patient with a widespread but small
ST
deviation. For example, the data shown in FIG. 5A indicates a relatively
severe ST
deviation at one electrode, namely, the electrode corresponding to column 510.
By
contrast, the data shown in FIG. 5B indicates a relatively mild ST deviation.
of at most
0.5 mm across all eight electrodes. In other words, while the maximum
deviation in
FIG. 5A (1.25 mm) is much high than that in FIG. 5B (0.5 mm), the cardiac
muscle
injury is more widespread in FIG. 5B than it is in FIG. 5A. Therefore, the
overall extent
of injury may, in fact, be comparable in the two cases. In this way, an
aggregate STDV
parameter may allow a physician to assess more accurately the condition of a
patient
suffering from MI, by comparing an aggregate STDV value from the patient
against
aggregate STDV values of patients with confirmed diagnoses.
Turning to FIG. 6A, an anterior portion 600a of an exemplary BSM device is
shown, comprising an array of 65 electrodes. When the entire array is applied
to a
patient's torso, different electrode columns in the array may be located in
different
anatomical regions. For example, electrodes 1-7 may be located on the right
hand side
on the front of the patient's chest, whereas electrodes 56-58, V6, and 60-61
may be
located under the patient's left arm. FIG. 6B shows a posterior portion 600b
of the
exemplary BSM device, comprising 16 electrodes. When applied to the patient,
electrodes 62-71 may be located on the patient's back, with electrodes 62-65
to the left
of the patient's spine and electrodes 68-71 to the right of the patient's
spine. Electrodes
72-77 may be located under the patient's right arm.
In some embodiments, electrodes may be organized into different groups based
on their respective locations on the patient's torso. This grouping may in
turn determine
whether and how the ST deviation data collected from each of the electrodes is
processed and incorporated into an aggregate STDV value.
In one embodiment, at least some electrodes of a BSM device may be divided
into four regions: anterior, inferior, posterior, and right ventricle (RV).
For example, in
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the BSM device of FIGs. 6A and 6B, electrodes 8, 18-21,V2, 23, 24, 28-32, V3,
34, 38-
43, V4, 48-52, V5, 56-58, and V6 may belong to the anterior region (shown as
610 and
612 in FIG. 6A); electrodes 7, 15-17, 25-27, 35-37, 45-47, 54, 55, 60, and 61
may
belong to the inferior region 620; electrodes 1-6, 9-11, V1, 13, 14, and 72-77
may
belong to the RV region (shown as 630a in FIG. 6A and 630b in FIG. 6B); and
electrodes 62-71 may belong to the posterior region 640. Electrodes in each of
these
regions may monitor a corresponding region of the heart as indicated by the
name of
the group. This arrangement is further illustrated in FIG. 6C, showing all
electrodes
from FIGs 6A and 6B grouped into four regions: ANT, INF, RV, and POST.
As shown in FIGs. 6A-C, electrodes are more densely distributed in the
anterior
region compared to the posterior region. As discussed above, these densities
of
electrodes may be taken into account when computing aggregate STDV.
The Applicant has appreciated that, when applied to a patient's torso,
electrodes
in these different regions may be located at different distances from the
heart. This
may lead to different levels of signal attenuation from the heart to the body
surface
where the electrodes are attached. For example, electrodes in the anterior
region
maybe physically closer to the heart compared to electrodes in other regions,
and
therefore may have larger ECG morphologies. To compensate for this effect, an
ST
deviation threshold may be chosen for each of the regions, with a highest
threshold
being associated with the anterior region. For example, the anterior threshold
may be
1.5 mm, the posterior threshold may be 0.5 mm, the inferior threshold may be
1.0 mm,
and the RV threshold may be 0.9 mm.
Within each region, an ST elevation below the corresponding threshold may be
considered normal. If an ST elevation above the corresponding threshold is
observed,
an adjusted (or exceedance) magnitude may be computed by subtracting the
corresponding threshold from the raw magnitude. For example, if an anterior
electrode
detects an ST elevation of raw magnitude 2 mm, an adjusted magnitude of 0.5 mm
(obtained by subtracting the anterior threshold of 1.5 mm) may be reported and
used in
the calculation of STDV. On the other hand, if a posterior electrode detects
an ST
elevation of raw magnitude 1.5 mm, an adjusted magnitude of 1.0 mm (obtained
by
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subtracting the Posterior threshold of 0.5 mm) may be reported and used in the
calculation of STDV.
ST depression may be computed similarly, by reporting only the magnitude of
depression in excess of a threshold. For each region, the same threshold may
be used
as for ST elevation, or a different threshold may be chosen. For example, an
anterior
threshold for ST depression may be selected to be 1.0 mm, so that an ST
depression of
1.5 mm from the anterior region may be reported as an adjusted ST depression
of 0.5
mm.
It should be appreciated that, while the threshold values listed above may
provide desirable adjustments that reflect different levels of signal
attenuation, other
suitable values may also be used. Also, different sets of thresholds may be
determined
for different patient populations. For example, diagnostic thresholds suitable
for male
patients may be slightly different from those suitable for female patients.
Similarly,
diagnostic thresholds may be adjusted according to age, weight, and/or other
factors.
Instead of, or in addition to, using thresholds to adjust ST deviation
magnitudes,
it may be beneficial to scale ST deviation magnitudes using various scaling
factors. As
with the thresholds, scaling factors may also be region dependent and may be
selected
to counteract the effect of different levels of signal attenuation. For
example, ST
deviation magnitudes from the Posterior region may be scaled up by a factor of
3, ST
deviation magnitude from the Inferior region may be scaled up by a factor of
1.5, ST
deviation magnitude from the RV region may be scaled up by a factor of 1.67,
and ST
deviation magnitudes from the anterior region may be unchanged (or scaled by a
factor
of 1). Selecting an appropriate scaling factor for a particular region may
help to ensure
that a desired weighting is given to ST deviations from the region when
calculating an
aggregate STDV. However, it should be appreciated that the invention is not
limited to
the method by which scaling factors are determined, nor to the use of scaling
factors.
Also, the ST deviation magnitudes being scaled may be raw measurements from
the
electrodes, or they may be already adjusted using regional thresholds.
In some embodiments, scaling factors may be determined by taking a ratio of
regional thresholds. For example, the scaling factor of a particular region
may be a
ratio of the anterior threshold and the threshold for the particular region.
In the example
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described above, the anterior threshold (denoted RTa) may be 1.5 mm, and the
inferior
threshold (RTi) may be 1.0 mm. Thus, the scaling factor for the inferior
region may be
calculated as:
S = RTa / RTi = 1.5 /1 = 1.5.
If an inferior electrode is detecting an ST deviation of 0.5 mm, a scaled ST
deviation
magnitude of 0.75 (obtained by multiplying 0.5 mm by the factor of 1.5) may be
reported
and used in the calculation of STDV. Scaling ST deviation magnitudes in this
way may
give values from other regions equal weighting as those from the anterior
region.
As mentioned above, the techniques of adjusting and scaling may be used alone
or in combination. In accordance with some embodiments, STDV for a single
electrode
is calculated by first adjusting a raw ST deviation magnitude using a
threshold and
thereafter scaling the adjusted ST deviation magnitude using a scaling factor.
Such an
embodiment is described below in connection with FIG. 7, which illustrates a
method for
computing total STEV.
Referring to FIG. 7, the process begins at step 700 by setting a variable
TSTEV
to zero. This variable will be used as an accumulator for computing the total
STEV.
After this initial step, the process enters into a loop to process ECG data
obtained from
a plurality of electrodes. At step 710, an electrode that has not yet been
processed is
selected, and ECG data from that electrode is obtained from a suitable source.
For
example, the ECG data may be obtained in real time from a patient, or it may
be
retrieved from a memory device storing previously obtained ECG data. At step
720, it is
determined whether the selected electrode exhibits ST elevation. If not, the
selected
electrode is skipped, and the process continues to step 780. If, on the other
hand, the
selected electrode does exhibit ST elevation, the process is broken up into
two sub-
processes 721 and 722, which may be executed in parallel or interleaved in any
suitable manner. At step 730 of sub-process 721, a magnitude d of ST elevation
is
determined for the selected electrode. In sub-process 722, a region associated
with the
selected electrode is determined at step 735. For example, the region may be
anterior,
posterior, inferior, or RV. After step 735, the sub-process is further divided
into two
sub-processes, 736 and 737, which again may be executed in parallel or
interleaved in
any suitable manner. At step 740 of sub-process 736, an area factor A
associated with
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the selected electrode is determined, for example, by taking a ratio of the
electrode
density in the most dense region (EDh) and the electrode density in the region
of the
selected electrode (EDr). Alternatively, a pre-computed area factor may simply
be
retrieved. In sub-process 737, a regional threshold RT is determined for the
region of
the selected electrode at step 745. Thereafter, at step 750, a scaling factor
S for the
region is determined, for example, by taking a ratio of the threshold for the
anterior
region (RTa) and the threshold for the region of the selected electrode (RT).
Alternatively, a pre-computed scaling factor may be retrieved.
Once steps 730, 740, and 750 have been completed, the process proceeds to
step 760, where STEV for the selected electrode is computed as follows: if d
is less
than or equal to RT, then STEV = 0; otherwise,
STEV=(d-RT)*S*A.
At step 770, this STEV is added to the accumulator TSTEV. After that, the
process
moves to the decision block at step 780 to determine if there is at least one
more
electrode to be processed. If so, the process loops back to step 710;
otherwise, the
total STEV is reported and the process ends.
It is to be appreciated that many variations of the process shown in FIG. 7
are
also within the scope and spirit of the invention. For example, the process of
FIG. 7 can
be modified to compute total STDpV, instead of total STEV. To that end, step
720 may
be modified so that an electrode is processed if and only if it exhibits ST
depression.
Step 730 may be modified so that the magnitude d is a magnitude of the
observed ST
depression, as a positive quantity. Similarly, the process of FIG. 7 can be
modified to
compute total STDV. For example, step 720 may simply be eliminated so that all
electrodes are processed, and steps 730 and 760 may be modified so that d is
the
magnitude of elevation if the electrode is exhibiting ST elevation, and is the
magnitude
of depression if the electrode is exhibiting ST depression. In both cases, d,
being a
magnitude, is a positive quantity.
As discussed above, some embodiments of the invention also provide a method
by which a physician may interpret an aggregate STDV value. In one such
embodiment, total STEV values from patients with confirmed diagnoses (MI or
non-MI)
are collected and stored in a database. The diagnoses may be obtained using a
well-
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established method, such as testing for Troponin levels in the blood. The
total STEV
values of confirmed MI patients may be sorted, and various band thresholds may
be
identified. For example, a threshold for diagnosing whether a patient is
suffering from
MI may be determined. In addition, thresholds representing the
top/middle/bottom
thirds of MI may also be determined. An exemplary method for diagnosing a new
patient using these thresholds will now be discussed in connection with FIG.
8.
FIG. 8 shows a process for determining whether a patient suffers from MI and
for
selecting an appropriate treatment based on the diagnosis. Particularly, the
total STEV
value of the patient is compared against a diagnostic threshold to determine
whether
the patient suffers from MI. If the conclusion is yes, the total STEV value of
the patient
is further compared against one or more other diagnostic thresholds to
classify the
patient's condition as severe, medium, or mild. An appropriate treatment
(e.g.,
aggressive vs. moderate) may then be selected based on the diagnosis and
classification.
At step 810, a patient's total STEV is obtained, for example, by calculating
it from
the patient's ECG data or by retrieving it from a database. At step 820, it is
determined
whether the patient's total STEV exceeds the MI threshold. If the conclusion
is yes,
then the patient is determined to be suffering from MI and the process
proceeds to step
830. Otherwise, the patient is determined not to be suffering from MI and the
process
ends. At step 830, it is determined whether the patient's total STEV exceeds
the top
third threshold. If the conclusion is yes, then the patient is determined to
be suffering
from severe MI, and aggressive treatment is recommended at step 835 and the
process
ends thereafter. Otherwise, it is determined at step 840 whether the patient's
total
STEV exceeds the middle third threshold. If the conclusion is yes, then the
patient is
determined to be suffering from medium MI. In that case, moderate treatment is
recommended at step 845, and thereafter the process ends. Otherwise, the
patient is
determined to be suffering from mild MI, and the process continues to step
850, where
it is recommended that the patient continue to be monitored.
Turning now to FIGs. 9-12, methods for building a database comprising
aggregate STDV values from patients with confirmed diagnoses (MI or non-MI)
and for
determining various diagnostic thresholds are described in greater detail.
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The embodiments illustrated in FIGs 9-12 are based on a database containing
approximately 400 cases. The 400 cases contain approximately 50% confirmed MI
and
50% confirmed non-MI cases. Approximately two thirds of the data is from male
patients, and one third is from female patients. Furthermore, the database has
a
proportion of cases with other conditions, such as LBBB with and without MI,
early
repolarization, left ventricular hypertrophy (LVH), pericarditis, and right
bundle branch
block (RBBB).
It should be appreciated that the database is not limited to the number and
composition of cases described in this example. For example, the database is
not
limited to any particular proportions of patients from different demographic
groups
and/or with different medical conditions. Furthermore, even though STDV is
treated as
a unitless quantity in this example, a comparison between STDV values of
different
patients is still meaningful, because the STDV values are obtained in a
consistent
manner across all patients.
Each of the cases in the database has an MI or a non-MI diagnosis that is
confirmed by Troponin testing. For each case, two versions of total STEV were
calculated for each of four regions, anterior, posterior, inferior, and RV. In
the first
version, ST elevation was measured with respect to the isoelectric line (or
baseline). In
the second version, ST elevation was measured with respect to the following
thresholds
(hereinafter STO Filter thresholds): 1.5 for anterior, 0.5 for posterior, 1
for inferior, and
0.9 for RV. Similarly, two versions of total STDpV were calculated, one with
respect to
the isoelectric line and another with respect to the STO Filter thresholds.
As discussed earlier, it may be desirable that the contributions of the four
regions
are weighted before they are incorporated into an aggregate. Thus, in the
illustrated
embodiments, both area factors and scaling factors are used. Specifically, the
area
factors are: 1 for anterior, inferior and RV, and 4 for posterior. The scaling
factors are:
1 for anterior, 1.5 for inferior, 1.67 for RV, and 3 for posterior.
In FIG. 9, the number of cases is plotted against total STEV, where total STEV
is computed from ST elevation measured with respect to baseline. The two
curves
represent, respectively, data from confirmed MI patients and data from
confirmed non-
MI patients. As shown, there are roughly the same number of MI and non-MI
patients
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with a total STEV value of 50. As a result, it may be difficult to determine,
solely based
on total STEV computed with respect to baseline, whether a patient is
suffering from MI.
A much clearer separation between MI and non-MI is observed when the STO
Filter thresholds are adopted. FIG. 10 shows the number of cases being plotted
against
total STEV with respect to STO Filter thresholds. As shown, very few non-MI
patients
exhibit a total STEV value of 25 or higher with respect to STO Filter
thresholds. This,
therefore, demonstrates that the chosen STO Filter thresholds have been
correctly
chosen as they open up clear separation between the MI and non-Ml cases.
Furthermore, it may be reliable to use 25 as a diagnostic threshold for
determining
whether a patient is suffering from MI. The data plotted in FIG. 10 is further
summarized in Table 1 below. Cutoff points for both quartiles and thirds are
given. As
can be deduced from the table, only a quarter of all non-MI patients exhibit a
total STEV
value of 0.8 or higher in this example. By contrast, three quarters of all MI
patients
exhibit a total STEV value of 6.5 or higher.
MI cases Non MI
Cases
1st Quartile 6.5 0
2nd Quartile 14.8 0
3rd Quartile 34 0.8
Lower Third <8.4 0
Middle Third 8.4-26.9 0-0.08
Upper Third >26.9 >0.08
Table 1. Comparison of Total STEV
In this example, an even clearer separation between MI and non-MI is observed
when LBBB cases are removed from the data from which the non-MI curve was
generated. LBBB patients may exhibit ST elevation in the anterior region, even
if they
are not suffering from MI. Therefore, when LBBB cases are excluded from the
non-MI
portion of the database, the separation between the MI and non-MI curves may
become
even larger. FIG. 11 shows the number of cases being plotted against total
STEV with
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respect to STO Filter thresholds, with LBBB patient data excluded from non-MI
data. As
shown, the non-MI curve is now almost parallel with the Y axis and very few
non-MI
patients exhibit a total STEV value of 15 or higher with respect to STO Filter
thresholds.
Another condition, called early repolarization, is also known to be associated
with
ST elevation. The Applicant has recognized that removing early repolarization
cases
from the database may not alter the shapes of the curves noticeably. The
Applicant
has further recognized that leaving early repolarization in the database may
provide
further information. For example, if a patient is diagnosed with early
repolarization and
exhibits total STEV in the lower third of confirmed MI, it may be acceptable
to assume
that the patient is not suffering from MI. However, if the total STEV of the
patient is in
the middle third, then MI is still suspected and more evidence may be needed.
ST depression data may be collected and plotted in a similar way as ST
elevation. FIG. 12 shows MI and non-MI curves for both total STEV (as positive
quantities) and total STDpV (as negative quantities). As can be seen from FIG.
12,
there is good symmetry between STEV and STDpV. Table 2 further summarizes the
total STDpV data plotted in FIG. 12, with cutoff points for both quartiles and
thirds.
Again, a significant difference between MI and non-MI is demonstrated. Only a
quarter
of all non-MI patients exhibit a total STDpV value of 0.4 or higher. By
contrast, three
quarters of all MI patients exhibit a total STEV value of 0.5 or higher.
MI cases Non MI
Cases
1st Quartile 0.5 0
2nd Quartile 6.1 0
3rd Quartile 23.9 0.4
Lower Third <2.1 0
Middle Third 2.1-14.8 0-0.04
Upper Third >14.8 >0.04
Table 2. Comparison of Total STDpV
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FIGs. 13-20 are three-dimensional representations of exemplary cases. FIGs.
13, 15, and 17 show, respectively, examples with total STEV in the low,
middle, and
upper thirds of confirmed MI cases, where the ST deviation magnitudes are
taken with
respect to the isoelectric line. FIGs. 14, 16, and 18 show the same cases, but
with ST
deviation magnitudes taken with respect to the STO Filter thresholds as
described
above. In particular, FIGs. 13 and 14 illustrate a case with relatively mild
diffuse
elevation (0.82 mm in the posterior region), and the corresponding total STEV
value is
around 8, which is in the lower third. FIGs. 15 and 16 illustrate a case with
moderate
diffuse elevation (2 mm in the inferior region), and the total STEV value is
around 20,
which is in the middle third. FIGs. 17 and 18 illustrate a case with
relatively severe
diffuse elevation (5.5 mm in the anterior region), and the total STEV values
is around
56, which is in the upper third.
As can be seen from these figures, total STEV values may be valuable to a
physician. For example, the case shown in FIGs. 15 and 16 may appear severe
because the ST deviation is widespread. However, total STEV values suggest it
is less
severe than the case of FIGs. 17 and 18, which exhibits very severe ST
elevation
concentrated in the anterior region.
FIGs. 19 and 20 show a case with early repolarization, where the ST deviation
magnitudes are taken, respectively, with respect to the isoelectric line and
with respect
to the STO thresholds. This case shows relatively mild compact elevation (2.44
mm in
the anterior region), and the total STEV value is 7, which is in the lower
third. As
described above, if the patient is diagnosed with early repolarization, it may
be
acceptable to rule out MI when total STEV is in the lower third, but more
evidence may
need to be collected when total STEV is in the middle third.
The above-described embodiments of the invention can be implemented in any
of numerous ways. For example; the embodiments may be implemented using
hardware, software or a combination thereof. When implemented in software, the
software code can be executed on any suitable processor or collection of
processors,
whether provided in a single computer or distributed among multiple computers.
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Also, the various methods or processes outlined herein may be coded as
software that
is executable on one or more processors that employ any one of a variety of
operating
systems or platforms.
In this respect, the invention may be embodied as a computer readable medium
or multiple computer readable media (e.g., a computer memory, one or more
floppy
discs, compact discs, optical discs, magnetic tapes, flash memories, circuit
configurations in Field Programmable Gate Arrays or other semiconductor
devices, or
other tangible computer storage medium) encoded with one or more programs
that,
when executed on one or more computers or other processors, perform methods
that
implement the various embodiments of the invention discussed above. The
computer
readable medium or media can be transportable, such that the program or
programs
stored thereon can be loaded onto one or more different computers or other
processors
to implement various aspects of the present invention as discussed above.
FIG. 21 is a schematic illustration of an exemplary computer 2100 on which
aspects of the invention may be implemented. The computer 2100 includes a
processor or processing unit 2101 and a memory 2102 that can include both
volatile
and non-volatile memory. The computer 2100 also includes storage 2105 (e.g.,
one or
more disk drives) in addition to the system memory 2102. The memory 2102 can
store
one or more instructions to program the processing unit 2101 to perform any of
the
functions described herein. As mentioned above, the reference herein to a
computer
can include any device having a programmed processor, including a rack-mounted
computer, a desktop computer, a laptop computer, a tablet computer or any of
numerous devices that may not generally be regarded as a computer, which
include a
programmed processor (e.g., a PDA, an MP3 Player, a mobile telephone, wireless
headphones, etc.).
Computer 2100 may have one or more input and output devices, such as
devices 2106 and 2107 illustrated in FIG. 21. These devices can be used, among
other
things, to present a user interface. Examples of output devices that can be
used to
provide a user interface include printers or display screens for visual
presentation of
output and speakers or other sound generating devices for audible presentation
of
output. Examples of input devices that can be used for a user interface
include
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keyboards, and pointing devices, such as mice, touch pads, and digitizing
tablets. As
another example, a computer may receive input information through speech
recognition
or in other audible format.
Computer 2100 may also comprise network interface cards (e.g., 2118a-c) to
enable communication via various networks (e.g., 2119a-c). Examples of
networks
include a local area network or a wide area network, such as an enterprise
network or
the Internet. Such networks may be based on any suitable technology and may
operate according to any suitable protocol and may include wireless networks,
wired
networks or fiber optic networks.
Various aspects of the invention may be used alone, in combination, or in a
variety of arrangements not specifically discussed in the embodiments
described in the
foregoing. For example, aspects described in one embodiment may be combined in
any manner with aspects described in other embodiments.
Having thus described several aspects of at least one embodiment of this
invention, it is to be appreciated that various alterations, modifications,
and
improvements will readily occur to those skilled in the art. Such alterations,
modifications, and improvements are intended to be within the spirit and scope
of the
invention. Accordingly, the foregoing description and drawings are by way of
example
only.
What is claimed is:
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