JP2012511998A - Measuring the degree of myocardial injury - Google Patents

Abstract

The ST deviation amount (STDV) parameter is determined based on the magnitude of the ST deviation observed by the electrode in the ECG device and the area associated with the electrode. For example, the STDV can be calculated by multiplying the area coefficient obtained using the electrode density of the region by the ST deviation magnitude. STDV values obtained from multiple electrodes are used to determine the total STDV. In addition, a method is provided for the physician to interpret the total STDV value. In some embodiments, the diagnostic threshold and classification variation can be obtained from a database of total STDV values from multiple patients with established diagnostic results. When the new patient is suffering from MI by comparing the total STDV value of the new patient with the diagnostic threshold and the variation range of classification to determine whether the new patient suffers from myocardial infarction (MI) In the new patient's medical condition can be classified.
[Selection] Figure 7

Description

  The present invention generally measures (quantifies) the degree of cardiac muscle injury in various regions of a patient's heart based on data collected from an array of electrodes on an electrocardiograph (ECG). Regarding the method. The disclosure further relates to a method for classifying the overall degree of myocardial injury in a patient and a method for diagnosing myocardial infarction (MI) based on the classification of the overall degree of myocardial injury.

  An ECG is a device that includes a plurality of electrodes applied to the skin of a patient's chest. These electrodes measure electrical activity in different areas of the myocardium. ECG is a useful tool for diagnosing various heart diseases such as MI and ischemia. In the case of acute MI (also known as a heart attack), ECG can be useful to identify damage to the myocardium.

  The electrical signal recorded by the electrodes can be traced with a standard grid. An example is shown in FIG. In such a grid, time is represented in the horizontal direction, progressing from left to right, and voltage is represented in the vertical direction. In the specific example shown in FIG. 1, each square has a width of 0.04 seconds and a height of 0.1 mV.

  FIG. 1 shows an exemplary ECG waveform of a normal heartbeat (or heartbeat cycle). As shown, each pulse comprises a P wave 110, a QRS complex 120, and a T wave 130. The portion 140 of the trace between the P wave and the QRS complex is known as the PQ segment, and the portion 150 of the trace between the QRS complex and the T wave is known as the ST segment. In this example, a small U wave 160 can also be seen, but in general, a normal heartbeat does not always see a U wave. The baseline voltage of the ECG waveform is known as an equipotential line and is shown as line 170 in FIG. In general, an equipotential line is determined according to a portion in the trace from after the T wave to before the P wave.

  Myocardial injury can be indicated by rising and falling ST segments of the ECG waveform. An ST segment is said to be rising when the potential is higher compared to the PQ segment of the waveform. An exemplary waveform showing ST rise is shown in FIG. 2A. The distance d1 between the ST segment potential 210 and the PQ segment potential 220 represents the magnitude of the rise. Similarly, an ST segment is said to be falling when the potential is lower compared to the PQ segment. An exemplary waveform showing ST descent is shown in FIG. 2B. The magnitude of the drop is represented by the distance d2 between the ST segment potential 230 and the PQ segment potential 240.

  ST deviation is often associated with heart failure. For example, elevation is often associated with ST elevation myocardial infarction (STEMI) and decline is often associated with ischemia. Ischemia can be a precursor to developing into MI. Conventionally, a 12-lead EGC has been used to detect such an abnormality. However, because of the relatively small number of electrodes (generally 10), a 12-lead EGC can only indicate the presence of STEMI and most affected areas (eg, septum, anterior, side). is there. Detecting STEMI with only two electrodes often makes it difficult to obtain sufficient information about the location and extent of the fault. In addition, the 12-lead ECG places most of the electrodes on the front of the chest, which limits the reliability in identifying STEMI occurring in other areas. For example, 12-lead EGC is known to overlook STEMI occurring on the back of the heart.

  Because of these limitations of 12-lead EGC, other imaging techniques (imaging modality) such as angiograms, MRIs, and echocardiograms are used to estimate the area of affected heart tissue. ) Was used. These imaging methods require specialized equipment and interpretation, which is more costly and inconvenient for the patient.

  In order to provide more comprehensive information about the electrical activity of the heart, EGC devices with more electrodes, for example 40-100 electrodes, have recently been developed. This technique is sometimes referred to as body surface mapping (BSM). This technique uses a large electrode array that covers the patient's torso. An example BSM configuration is shown in FIGS. 3A and 3B. FIG. 3A shows electrodes 310 and 320 applied to the front of the chest region. FIG. 3B shows the electrode 330 applied to the back of the chest region. Further examples of BSM configurations and devices are described in detail in US Pat. Nos. 5,419,337 and 6,055,448.

  According to a first aspect of the present invention, a method for measuring the degree of myocardial injury is provided. The method comprises the steps of ST excursion (deviation) based on electrocardiographic data obtained from at least one electrode in an electrocardiograph and associated with at least one region of the heart. Determining a size, determining an area coefficient associated with the at least one region, the area coefficient for the at least one electrode, the magnitude of ST deviation, and the area coefficient And calculating an ST deviation amount for the at least one electrode based at least in part.

  According to some further embodiments of the present invention, there is provided a computer readable medium having computer-executable instructions for performing the method described above.

  According to some further embodiments of the present invention, a method for diagnosing a patient based on the total ST deviation is provided. The method includes obtaining a total ST deviation for the patient based on size and area information gathered from an array of electrodes attached to the patient; and from a plurality of patients having established diagnostic results. Using one or more total ST deviation data to obtain one or more diagnostic thresholds, and comparing the total ST deviation of the patient with the diagnostic threshold.

  According to some further embodiments of the present invention, a system is provided for measuring the extent of myocardial injury based on electrocardiographic data obtained from a patient. The system includes at least one electrode applied to a patient, the magnitude of ST deviation based on electrocardiograph data obtained from the at least one electrode associated with at least one region of the heart. Determining an area factor for the at least one electrode, the area factor associated with the at least one region, and determining at least a portion of the magnitude of ST deviation and the area factor. And one or more processors programmed to calculate an ST deviation for the at least one electrode.

Fig. 5 shows a normal heartbeat ECG waveform traced on a standard grid. An ECG waveform showing ST rise is shown. An ECG waveform showing ST descent is shown. Fig. 2 shows an array of electrodes attached to the front of the human torso. Fig. 2 shows an array of electrodes attached to the back of the human torso. An example of ST deviation (STDV) for one electrode is shown. An example of ST deviation (STDV) for one electrode is shown. An example of the total ST deviation amount for a plurality of electrodes is shown. An example of the total ST deviation amount for a plurality of electrodes is shown. Fig. 3 shows the front part of an exemplary BSM device for obtaining ECG data. Fig. 4 shows a rear portion of an exemplary BSM device for obtaining ECG data. An exemplary arrangement of electrodes divided into four regions is shown. It is the flowchart explaining the method of calculating total STDV. It is the flowchart explaining the method of diagnosing a patient. The total STDV value of a patient with a diagnostic result determined to be MI or a diagnostic result determined to be non-MI is shown. The total STDV value of a patient with a diagnostic result determined to be MI or a diagnostic result determined to be non-MI is shown. The total STDV value of a patient with a diagnostic result determined to be MI or a diagnostic result determined to be non-MI is shown. The total STDV value of a patient with a diagnostic result determined to be MI or a diagnostic result determined to be non-MI is shown. FIG. 3 is a three-dimensional view of an exemplary case showing ST elevation and / or decline. FIG. 3 is a three-dimensional view of an exemplary case showing ST elevation and / or decline. FIG. 3 is a three-dimensional view of an exemplary case showing ST elevation and / or decline. FIG. 3 is a three-dimensional view of an exemplary case showing ST elevation and / or decline. FIG. 3 is a three-dimensional view of an exemplary case showing ST elevation and / or decline. FIG. 3 is a three-dimensional view of an exemplary case showing ST elevation and / or decline. FIG. 3 is a three-dimensional view of an exemplary case showing ST elevation and / or decline. FIG. 3 is a three-dimensional view of an exemplary case showing ST elevation and / or decline. FIG. 7 is a schematic diagram of an exemplary computer that can implement aspects of the invention.

  In this application, the invention is not limited to the details of the arrangements and structures of the components that will become apparent in the following description or illustrated in the drawings. The invention is capable of other embodiments and of being practiced or carried out in various ways. Moreover, the language and terminology used herein is for the purpose of description and should not be regarded as limiting. In the claims, the terms “including”, “comprising”, “having”, “comprising”, “accompanying”, and the use of these variations are the matters listed below and the matters concerned Is intended to encompass the equivalents and further matters.

  Applicants understand that BSM technology can be improved by providing a method of measuring the degree of cardiac damage based on data collected from an array of electrodes. This may allow a physician to select an appropriate treatment for a patient diagnosed with MI based on the severity of the MI. In addition, it may be used to assess a patient's condition before and after a percutaneous coronary intervention (PCI) procedure. BSM-based methods for measuring the degree of heart damage compared to other imaging techniques such as angiograms, MRI, and echocardiograms are cheaper and more convenient. possible.

  Furthermore, Applicants understand that the data obtained from BSM electrode arrays has two aspects or features. That is, the affected area is indicated by, for example, the distribution of the electrodes from which ST deviation is detected and the magnitude of ST deviation detected by each electrode. A measurement with only one of these two features may not provide sufficient information. For example, in the case of only the number of areas, it may be clear how much the obstacle has spread, but it may not be possible to indicate the severity of the disorder in the affected area. Similarly, measurements based solely on the magnitude of ST excursion (eg, measuring the most severe excursion observed by one electrode) may overlook a minor but wide range of obstacles.

  According to some embodiments of the present invention, a new parameter called ST deviation volume (STDV) is used to assess the extent of myocardial injury. The STDV parameter combines both area and size information. As the name suggests, based on the area of the heart associated with an individual electrode and the magnitude of the ST deviation detected by that electrode, the STDV of that electrode can be determined. As an example, the STDV for an electrode can be calculated by multiplying the magnitude of the ST excursion detected by the electrode by the area factor associated with that electrode. Scale or otherwise adjust the magnitude of the ST deviation based on the position of the electrode on the patient's torso, and thus the distance between the electrode and the heart, as described in more detail below. be able to. Further, the area factor associated with the electrode under consideration can be determined in several different ways, for example by using the number of electrodes associated with the same heart region as the electrode under consideration. In one embodiment, a first electrode associated with a densely worn region (i.e., a cardiac region with a number of electrodes associated with it) is a low density worn region (i.e. It has a smaller area factor than the second electrode associated with the heart region (with only a few electrodes associated with it). Instead, each heart region can be projected onto the area of the patient's torso, so the density of the electrodes in the area of the torso where a particular electrode is placed is used to determine the area factor for that particular electrode. Also good.

  In some further embodiments, the total STDV may be determined by taking into account STDV values obtained from multiple electrodes. For example, the total STDV may be calculated as the sum of all STDV values, both rising and falling, obtained from all electrodes in the electrode array. In this case, the total STDV may be referred to as the total STDV. Instead, the total STDV may be calculated as the sum of all STDV values obtained from the electrodes that detected an increase in STDV. In this case, the total STDV may be referred to as a total ST increase (total STEV). Similarly, the total STDV may be calculated as the sum of all the STDV values obtained from the electrodes that detected a decrease in STDV. In this case, the total STDV may be referred to as a total ST descent amount (total STDpV).

  Under some circumstances, total STEV and total STDpV may be more convenient than total STDV. For example, Applicants understand that the ST rising area is often accompanied by a reverse ST falling area on the opposite side of the torso. When diagnosing a patient for STEMI, comparing the patient's total STEV with a database of total STEV values may provide more information. Similarly, when diagnosing a patient for ischemia, comparing the patient's total STDpV values to a database of total STDpV values may provide more information.

  In addition, applicants understand that there is a need for a way for physicians to interpret total STDV values. According to some embodiments of the invention, total STDV values from patients with established diagnostic results (MI or non-MI) are collected and stored in a database. Diagnostic results may be obtained using well-established methods such as testing for troponin levels in the blood. In some embodiments, a diagnostic threshold that determines whether a patient is suffering from MI may be obtained based on the total STDV from both confirmed MI patients and confirmed non-MI patients. In another embodiment, the total STDV values of confirmed MI patients may be sorted to identify a range of variation representing the upper / middle / lower third. To diagnose a new patient, the total STDV value of the new patient is compared with the diagnostic threshold to determine whether the new patient is suffering from MI and the new patient is suffering from MI In some cases, the new patient's illness may be classified as severe, moderate, or mild based on the top / medium / bottom variation. Next, an appropriate treatment (eg, aggressive vs. moderate) may be selected based on the diagnostic results and classification.

  In some further embodiments, different databases may be maintained for total STDV, STEV, and / or total STDpV. These databases may be used to classify patients with different diagnostic results. For example, when the diagnosis result is STEMI, the total STEV value of the patient may be compared with the value in the database of the total STEV. Similarly, if the diagnostic result is ischemia, the patient's total STDpV value may be compared with the value in the database of total STDpV.

  Furthermore, since some non-MI illnesses may also result in ST elevation, applicants have found that it may be desirable to remove STDV values from non-MI patients suffering from these illnesses from the database. I understand. One such illness, namely the left bundle branch block (LBBB), will be further described later.

  Although some embodiments have been outlined above, it should be understood that they are not limited to such examples. For example, the area factor used to calculate the STDV for an individual electrode may be obtained using another suitable method without being based on electrode density. Further, the above-described variation range of classification may correspond to two divisions, four divisions, or some other decomposition instead of three divisions.

  Referring to FIGS. 4A-B, an example of STDV for one electrode is shown. As already described, the STDV for one electrode can be determined based on the magnitude of the ST excursion detected by the electrode and the area factor associated with the electrode. Any suitable technique may be used to determine the magnitude of the ST excursion, and the invention is not limited in this respect. For example, any point, such as point J (also known as ST0, ie, the point where the QRS complex intersects the ST segment), ST60 (60 ms after ST0), or ST80 (80 ms after ST0) The ST deviation may be measured at the standard point.

  In some embodiments, the area factor associated with the electrode may depend on the position of the electrode on the patient's torso. For example, the area factor can be determined by the density of the electrode in the region of the cylinder where the electrode is located. In some embodiments, the area factor of the first electrode in the densely loaded region may be smaller than the area factor of the second electrode in the lowly loaded region. . The reason is that the first electrode is monitoring a smaller area of the heart compared to the second electrode. However, as already described, it should be understood that the present invention is not limited to any particular method for determining the area factor for an electrode.

  FIG. 4A represents the STDV of the first electrode. The first electrode detects a 3 mm ST rise and is associated with an area factor of one. As a result, the STDV for the first electrode is 3 mm. In this embodiment, the area coefficient is obtained by taking the ratio of the electrode density (represented by EDh) in the most dense region to the electrode density (represented by EDr) in the region of the electrode. More specifically, the first electrode is arranged in the most dense region or a region having the same density as the most dense region. Therefore, the area coefficient A is simply 1.

FIG. 4B represents the STDV of the second electrode. The second electrode detects an ST rise of 0.75 mm and is associated with an area factor of 4. The second electrode regions with the highest density (e.g., 16 electrodes per dm ²⁾ as compared to, is located at an area having a lower density (e.g., four electrodes per dm ²⁾ Yes. Therefore, the area factor for the second electrode can be calculated as follows.

A = EDh / EDr = 16/4 = 4
As a result, the STDV for the second electrode is STDV = d × A = 0.75 × 4 = 3 mm. Even if the first electrode detects an ST rise of a much greater magnitude than the second electrode, the STDV for the second electrode is the same as the STDV for the first electrode.

  It should be understood that the area factor in the example shown in FIGS. 4A-B is a density ratio, and thus is unitless, but the invention is not limited in this respect. The area factor may be calculated in any suitable manner, and as a result of the area factor calculation method, the area factor may have any unit. In general, the area factor provides information regarding the width of the myocardial injury, and the area factor may not correspond to any physical measurement of the area.

  Similarly, the electrode STDV may also have any suitable unit. In the embodiment shown in FIGS. 4A and 4B, STDV is the product of ST deviation and unitless area factor, so STDV may have the same units as ST deviation. However, in other embodiments, the STDV may have other units or may be treated as a unitless quantity.

  5A-B show examples of total STDV for a plurality of electrodes. FIG. 5A shows eight columns, each column representing an STDV for one electrode. The height of each column represents the magnitude of ST rise detected by the corresponding electrode. For example, the pillar 510 has a height of 1.25, indicating that the electrode corresponding to the pillar 510 has detected an ST rise 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. Further, the eight electrodes may be arranged in the same region of the patient's torso, for example, the most closely worn region so that the area factor of each electrode is 1. Adding all of the STDV values, the total STDV for the 8 electrodes in FIG. 5A is calculated to be 3.75 mm.

  FIG. 5B also shows eight pillars. The eight columns correspond to the eight electrodes, respectively. The magnitude of ST elevation detected by these eight electrodes ranges from 0.25 mm to 0.5 mm. For example, the column 520 has a height of 0.5, indicating that the electrode corresponding to the column 520 has detected an ST rise of 0.5 mm. As in FIG. 5A, each electrode is associated with an area factor of one. As a result, the total STDV for the eight electrodes in FIG. 5B is also 3.75 mm.

  As shown in FIGS. 5A-B, the total STDV (or in general, the total STDV) is larger for patients with a larger ST excursion, shown only in a small area, and for a wider but smaller ST deviation. It can provide a meaningful way to compare with another patient who has a position. For example, the data shown in FIG. 5A shows a relatively severe ST excursion at one electrode, ie, the electrode corresponding to column 510. In contrast, the data shown in FIG. 5B shows a relatively light ST excursion of no more than 0.5 mm across all eight electrodes. In other words, the maximum excursion (1.25 mm) in FIG. 5A is much larger than the maximum excursion (0.5 mm) in FIG. 5B, but the myocardial disorder in FIG. 5B is more extensive than the myocardial disorder in FIG. 5A. It is. Thus, the overall extent of the disorder can be effectively compared in the two cases. In this way, the total STDV parameter allows the physician to determine the pathology of a patient suffering from MI by comparing the total STDV value from the patient with the total STDV value of a patient with a confirmed diagnostic result. It may be possible to evaluate more accurately.

  Referring to FIG. 6A, a front portion 600a of an exemplary BSM device is shown. The front portion 600a includes an array of 65 electrodes. When all of the array is attached to the patient's torso, the rows of different electrodes in the array can be placed in different anatomical regions. For example, electrodes 1-7 may be placed on the right front side of the patient's chest. On the other hand, electrodes 56-58, V6, and 60-61 can be placed under the patient's left arm. FIG. 6B shows a rear portion 600b of an exemplary BSM device. The rear portion 600b includes 16 electrodes. When applied to a patient, electrodes 62-71 may be placed on the patient's back, electrodes 62-64 may be placed on the left side of the patient's spine, and electrodes 68-71 may be placed on the right side of the patient's spine. Electrodes 72-77 may be placed under the patient's right arm.

  In some embodiments, the electrodes may be grouped into different groups based on their position on the patient's torso. Next, it may be determined by this grouping whether the ST deviation data collected from each of the electrodes is processed and incorporated into the total STDV value and how it is done.

  In one embodiment, at least some electrodes of a BSM device are divided into four regions: an anterior, an inferior, a posterior, and a right ventricle (RV). Also good. For example, in the BSM device of FIGS. 6A and 6B, the 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 front region (shown as 610 and 612 in FIG. 6A). The electrodes 7, 15-17, 25-27, 35-37, 45-47, 54, 55, 60 and 61 can belong to the lower 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). The electrodes 62-71 can belong to the rear region 640. The electrodes in each of these areas may monitor the corresponding area of the heart indicated by the group name. Furthermore, this arrangement is shown in FIG. 6C. FIG. 6C shows all electrodes from FIGS. 6A and 6B grouped into four regions: ANT, INF, RV, and POST.

  As shown in FIGS. 6A-C, the electrodes are more densely distributed in the front region as compared to the rear region. As already mentioned, these electrode densities may not be taken into account when calculating the total STDV.

  Applicants understand that the electrodes in these different regions may be placed at different distances from the heart when applied to the patient's torso. Thus, the level of signal attenuation from the heart to the body surface to which the electrode is attached can be different. For example, electrodes in the anterior region may be physically closer to the heart compared to electrodes in other regions, and thus may have a larger ECG morphology. To compensate for this effect, ST deviation thresholds may be selected for each of the regions. The highest threshold is associated with the front region. For example, the front threshold may be 1.5 mm. The rear threshold may be 0.5 mm. The lower threshold may be 1.0 mm. The RV threshold may be 0.9 mm.

  Within each region, ST elevations below the corresponding threshold may be considered normal. If an ST rise above the corresponding threshold is observed, the adjusted (or excess) magnitude can be calculated by subtracting the corresponding threshold from the raw magnitude. For example, if the front electrode detects a 2 mm raw size ST rise, it will have an adjusted size of 0.5 mm (obtained by subtracting the 1.5 mm front threshold). It may be reported and used in the calculation of STDV. On the other hand, if the rear electrode detects a 1.5 mm raw size ST rise, it is adjusted to 1.0 mm (obtained by subtracting the 0.5 mm rear threshold). May be reported and used in the STDV calculation.

  Similarly, the ST descent may be calculated by reporting only the magnitude of the ST descent exceeding the threshold. For each region, the same threshold as for ST rise may be used, or a different threshold may be chosen. For example, if 1.0 mm is selected as the front threshold for ST descent, a 1.5 mm ST descent from the front region may be reported as an adjusted ST descent of 0.5 mm.

  The thresholds listed above may provide desirable adjustments that reflect different levels of signal attenuation, but it should be further understood that other suitable values may be used. In addition, different sets of thresholds may be determined for different populations of patients. For example, a diagnostic threshold suitable for a male patient and a diagnostic threshold suitable for a female patient may be slightly different. Similarly, the diagnostic threshold may be adjusted according to age, weight, and / or other factors.

  Instead of or in addition to adjusting the ST excursion magnitude using a threshold, it may be beneficial to scale the ST excursion magnitude using various scaling factors. Similar to the threshold, the scaling factor can also depend on the region. The scaling factor can be selected to counteract the effects of different levels of signal attenuation. For example, the ST deviation from the rear region may be scaled up three times. The magnitude of ST deviation from the lower region may be increased by a factor of 1.5. The ST deviation from the RV region may be enlarged 1.67 times. The magnitude of the ST deviation from the front region may not be changed (or may be scaled by 1). When calculating the total STDV, it may be helpful to select an appropriate scaling factor for that particular region to ensure that the desired weight is given to ST deviations from that particular region. However, it should be understood that the present invention is not limited to the method of determining the scaling factor and may not use the scaling factor. Further, the magnitude of the ST deviation to be scaled may be a raw measurement from the electrode or may have already been adjusted using a region threshold.

  In some embodiments, the scaling factor may be determined by taking a ratio of the region thresholds. For example, the scaling factor for a particular region may be the ratio of the front threshold and the particular region threshold. In the above example, the front threshold (represented by RTa) may be 1.5 mm. The lower threshold (RTi) may be 1.0 mm. Thus, the scaling factor for the lower region can be calculated as follows.

S = RTa / RTi = 1.5 / 1 = 1.5
If the bottom electrode detects an ST excursion of 0.5 mm, the scaled ST excursion magnitude of 0.75 (obtained by multiplying 0.5 mm by a factor of 1.5) is It may be reported and used in the calculation of STDV. Thus, scaling the magnitude of the ST excursion can give a value equal to the value from the front region to values from other regions.

  As already described, the adjustment and scaling techniques may be used alone or in combination. According to some embodiments, first the threshold is used to adjust the magnitude of the raw ST excursion and then the scaling factor is used to determine the adjusted ST excursion magnitude. Calculate the STDV for one electrode by scaling. Such an embodiment is described below in connection with FIG. FIG. 7 illustrates a method for calculating the total STEV.

  Referring to FIG. 7, in step 700, the process begins by setting the variable TSTEV to zero. Use this variable as an accumulator to calculate the total STEV. After this initial step, the process enters a loop to process ECG data obtained from multiple electrodes. In step 710, an electrode that has not yet been processed is selected to obtain ECG data from that electrode from an appropriate source. For example, ECG data may be obtained in real time from a patient, or it may be retrieved from a memory device that stores previously obtained ECG data. In step 720, it is determined whether the selected electrode exhibits ST rise. If no ST rise is indicated, the selected electrode is skipped and the process continues to step 780. On the other hand, if the selected electrode shows an ST rise, the process is split into two sub-processes 721 and 722. Sub-processes 721 and 722 may be performed in parallel or alternately in any suitable manner. In step 730 in sub-process 721, the ST rise magnitude d is determined for the selected electrode. Within sub-process 722, at step 735, the region associated with the selected electrode is determined. For example, the region can be front, back, bottom, or RV. After step 735, the sub-process is further divided into two sub-processes 736 and 737. Sub-processes 736 and 737 may also be performed in parallel or alternately in any suitable manner. In step 740 in sub-process 736, for example, the ratio of the electrode density (EDh) in the most dense region to the electrode density (EDr) in the selected electrode region is associated with the selected electrode. An area coefficient A is determined. Instead, the area coefficient calculated in advance may be simply searched. Within sub-process 737, step 745 determines a region threshold RT for the selected electrode region. Thereafter, in step 750, for example, the scaling factor S for the region is determined by taking the ratio of the threshold value (RTa) of the front region and the threshold value (RT) of the selected electrode region. Instead, a pre-calculated scaling factor may be searched.

When steps 730, 740, 750 are complete, the process proceeds to step 760. In step 760, the STEV for the selected electrode is calculated as follows. That is, when d is less than or equal to RT, STEV = 0, otherwise
STEV = (d−RT) × S × A
It is.

  In step 770, this STEV is added to the accumulator TSTEV. Thereafter, the process moves to a decision block at step 780 to determine whether there are at least one electrode to be processed. If so, the process loops back to step 710. Otherwise, report the total STEV and the process ends.

  It should be understood that many variations of the process shown in FIG. 7 are within the spirit and scope of the present invention. For example, the process of FIG. 7 can be modified to calculate the total STDpV instead of the total STEV. To that end, step 720 may be modified to process the electrode when and only if the electrode shows ST descent. Step 730 may be modified so that magnitude d is the magnitude of the observed ST drop as a positive amount. Similarly, the process of FIG. 7 can be modified to calculate the total STDV. For example, step 720 may simply be deleted to process all electrodes. Steps 730 and 760 are changed so that d is the magnitude of the rise when the electrode shows ST rise, and d is the magnitude of the fall when the electrode shows ST fall. May be. In both cases, the magnitude d is a positive amount.

  As already described, some embodiments of the invention provide a way for a physician to interpret the total STDV value. In one such embodiment, total STEV values from patients with established diagnostic results (MI or non-MI) are collected and stored in a database. Diagnostic results may be obtained using well-established methods such as testing for troponin levels in the blood. The total STEV values of confirmed MI patients may be sorted to identify various fluctuation thresholds. For example, a threshold for diagnosing whether a patient is suffering from MI may be determined. Further, a threshold value representing the upper third / midth / lower third of the MI may be determined. An exemplary method for diagnosing new patients using these thresholds will now be described in connection with FIG.

  FIG. 8 illustrates the process of determining whether a patient is suffering from MI and selecting an appropriate treatment based on the diagnostic results. In particular, the patient's total STEV value is compared to a diagnostic threshold to determine whether the patient is suffering from MI. If the conclusion is yes, then the patient's illness is classified as severe, moderate, or mild by further comparing the patient's total STEV value to one or more other diagnostic thresholds. Next, an appropriate treatment (eg, aggressive versus moderate) may be selected based on the diagnostic results and classification.

  In step 810, the patient's total STEV is obtained, for example, by calculating the patient's total STEV from the patient's ECG data or by retrieving it from the database. In step 820, it is determined whether the patient's total STEV exceeds the MI threshold. If the conclusion is yes, the patient is determined to have MI and the process proceeds to step 830. Otherwise, the patient is determined not to have MI and the process ends. In step 830, it is determined whether the patient's total STEV exceeds the upper third threshold. If the conclusion is yes, it is determined that the patient is suffering from severe MI, and active treatment is recommended at step 835, after which the process ends. Otherwise, in step 840, it is determined whether the patient's total STEV exceeds the median third threshold. If the conclusion is yes, the patient is determined to have moderate MI. In that case, moderate treatment is recommended in step 845, after which the process ends. Otherwise, it is determined that the patient is suffering from mild MI and the process then proceeds to step 850 where it is recommended to continue monitoring the patient.

  Referring now to FIGS. 9-12, a method for constructing a database comprising total STDV values from patients with established diagnostic results (MI or non-MI) to determine various diagnostic thresholds, Describe in more detail.

  The embodiment shown in FIGS. 9-12 is based on a database containing approximately 400 cases. The 400 cases include approximately 50% confirmed MI cases and 50% confirmed non-MI cases. Approximately two-thirds of the data is from male patients and one-third is from female patients. In addition, the database has a percentage of cases with other illnesses. Cases with other diseases are, for example, LBBB with and without MI, early repolarization, left ventricular hypertrophy (LVH), pericarditis, right bundle branch block (RBBB) .

  It should be understood 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 percentage of patients from different demographic groups and / or any particular percentage of patients with different illnesses. Furthermore, in this example, the comparison between STDV values of different patients is important because the STDV values are obtained in a consistent manner for all patients, even though STDV is treated as a unitless quantity. is there.

  Each case in the database has an MI or non-MI diagnostic result established by the troponin test. For each case, two versions of the total STEV were calculated for each of the four regions: front, back, bottom, and RV. In the first version, ST elevation was measured with reference to the equipotential line (or baseline). In the second version, the next threshold (hereinafter ST0 filter threshold): 1.5 for the front, 0.5 for the rear, 1 for the bottom, 0.9 for RV The ST elevation was measured based on Similarly, two versions of the total STDpV were calculated. That is, the total STDpV based on the equipotential line and the total STDpV based on the ST0 filter threshold.

  As already mentioned, it may be desirable to weight the contributions of the four regions before incorporating them into the grand total. For example, in the illustrated embodiment, both area and scaling factors are used. Specifically, the area factor is 1 for the front, bottom, and RV, and 4 for the rear. The scaling factor is 1 for the front, 1.5 for the bottom, 1.67 for RV, and 3 for the rear.

  In FIG. 9, the number of cases against total STEV is plotted. Here, the total STEV is calculated from the ST rise measured with reference to the baseline. The two curves represent data from confirmed MI patients and data from confirmed non-MI patients, respectively. As shown, approximately the same number of MI and non-MI patients have a total STEV value of 50. As a result, it may be difficult to determine whether a patient suffers from MI based solely on the total STEV calculated relative to the baseline.

Employing the ST0 filter threshold, a much clearer separation is observed between MI and non-MI. FIG. 10 shows the number of cases plotted against the total STEV based on the ST0 filter threshold. As shown, few non-MI patients show a total STEV value of 25 or greater relative to the ST0 filter threshold. Thus, since the chosen ST0 filter threshold provides a clear separation between MI and non-MI cases, this proves that the ST0 filter threshold was chosen correctly. Further, it may be reliable to use 25 as a diagnostic threshold for determining whether a patient suffers from MI. A summary of the data plotted in FIG. 10 is further shown in Table 1 below. Breakpoints are given for both the quartile and the triad. As can be derived from the table, in this example, only a quarter of all non-MI patients show a total STEV value of 0.8 or higher. In contrast, three-quarters of all MI patients show a total STEV value of 6.5 or higher.

  In this example, when an LBBB case is removed from the data generating a non-MI curve, a clearer separation is observed between MI and non-MI. Patients with LBBB may show ST elevation in the front region even if they do not suffer from MI. Thus, if LBBB cases are removed from the non-MI portion of the database, the separation between the MI and non-MI curves can be even greater. FIG. 11 shows the number of cases plotted against the total STEV based on the ST0 filter threshold. LBBB patient data has been removed from non-MI data. As shown, the non-MI curve is approximately parallel to the Y-axis, and few non-MI patients exhibit a total STEV value of 15 or greater relative to the ST0 filter threshold.

  Another disease called early repolarization is also known to be associated with ST elevation. Applicant understands that removing the case of early repolarization from the database may not change the shape of the curve very much. In addition, Applicants understand that leaving early repolarization in the database can provide further information. For example, if a patient is diagnosed with early repolarization and shows a total STEV in the bottom third of confirmed MI, the patient is not suffering from MI. Can be allowed. However, if the patient's total STEV falls in the middle third, there is still suspicion of MI and more evidence may be needed.

In the same manner as ST rise, data of ST fall may be collected and plotted. FIG. 12 shows the MI and non-MI curves for both the total STEV (as a positive amount) and the total STDpV (as a negative amount). As can be seen from FIG. 12, there is good symmetry between STEV and STDpV. Further, Table 2 shows an overview of the total STDpV data plotted in FIG. 12, using breakpoints for both the quartile and the triad. Again, a significant difference is shown between MI and non-MI. Only a quarter of all non-MI patients show a total STDpV value of 0.4 or greater. In contrast, three-quarters of all MI patients show a total STEV value of 0.5 or greater.

  Figures 13-20 are three-dimensional representations of exemplary cases. FIGS. 13, 15, and 17 show examples of total STEVs of confirmed MI cases that fall in the bottom third, the middle third, and the top third, respectively. ing. Here, the magnitude of the ST deviation is taken with reference to the equipotential line. 14, 16, and 18 show the same case, but the ST deviation is taken with reference to the ST0 filter threshold as described above. In particular, FIGS. 13 and 14 show a case with a relatively mild increase in pervasiveness (0.82 mm in the posterior region) with a corresponding total STEV value of about 8, which is 3 minutes from the bottom. Enter 1 of. FIGS. 15 and 16 show a case with moderate diffuse elevation (2 mm in the lower region) with a total STEV value of about 20, which falls in the middle third. Figures 17 and 18 show a case with a relatively severe increase in pervasiveness (5.5 mm in the anterior region) with a total STEV value of about 56, which is one third from the top. enter.

  As can be seen from these figures, the total STEV value can be helpful to the physician. For example, the cases shown in FIGS. 15 and 16 may appear severe because the ST deviation is widespread. However, FIGS. 17 and 18 show a very severe ST elevation concentrated in the anterior region, and the total STEV value suggests that the cases of FIGS. 15 and 16 are not as severe as the cases of FIGS. is doing.

  Figures 19 and 20 show cases with early repolarization. Here, the magnitude of the ST deviation is taken with reference to the equipotential line and the ST0 threshold. This case shows a relatively mild and compact rise (2.44 mm in the front region). The total STEV value is 7, which falls into the third of the bottom. As already mentioned, once a patient is diagnosed with early repolarization, if the total STEV is in the bottom third, it may be allowed to be MI, but the total If STEV is in the middle third, it may be necessary to gather more evidence.

  The above-described embodiments of the present invention can be implemented in any of a number of ways. For example, 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 group of processors, regardless of whether it is provided on one computer or distributed among multiple computers. Further, the various methods or processes described generally herein may be encoded as software executable on one or more processors using any one of various operating systems or platforms. .

  In this regard, a single encoded using one or more programs that, when executed on one or more computers or other processors, perform the methods of implementing the various embodiments of the invention described above. A computer readable medium or a plurality of computer readable media (eg, circuitry in a computer memory, one or more floppy disks, a compact disk, an optical disk, a magnetic tape, flash memory, a field programmable gate array, or other semiconductor device) The present invention can be embodied as a configuration or other tangible computer storage medium). The one or more computer readable media may be portable. Accordingly, one or more programs stored on one or more computer readable media may be loaded onto one or more different computers or other processors to implement various aspects of the invention as described above. can do.

  FIG. 21 is a schematic diagram of an exemplary computer 2100. Aspects of the invention may be implemented on computer 2100. The computer 2100 includes a processor or processing unit 2101 and a memory 2102. Memory 2102 can include both volatile and non-volatile memory. Further, the computer 2100 includes a storage device 2105 (eg, one or more disk drives) in addition to the system memory 2102. Memory 2102 may store one or more instructions for programming processing unit 2101 to perform any of the functions described herein. As already described, the computer referred to herein can include any device having a programmed processor. Any device includes any of a rack mount computer, desktop computer, laptop computer, tablet computer, or a number of devices that may not generally be considered a computer. Many devices that may not generally be considered computers include programmed processors (eg, PDAs, MP3 players, mobile phones, wireless headphones, etc.).

  The computer 2100 may have one or more input devices and output devices, such as devices 2106 and 2107 shown in FIG. These devices can be used in particular to provide a user interface. Examples of output devices that can be used to provide a user interface include a printer or display screen for providing output visually, and a speaker or other sound generating device for providing output audibly. Including. Examples of input devices that can be used for the user interface include a keyboard and a pointing device. The pointing device is, for example, a mouse, a touch pad, or a digitized tablet. As another example, a computer may receive input information through speech recognition or in other audible formats.

  Further, the computer 2100 may include a network interface card (eg, 2118a-c) to allow communication via various networks (eg, 2119a-c). Examples of networks include a local area network or a wide area network, such as a corporate network or the Internet. Such a network can be based on any suitable technology, can operate according to any suitable protocol, and can include a wireless network, a wired network, or a fiber optic network.

  Various aspects of the invention may be used alone, in combination, or in various configurations not specifically described in the above embodiments. For example, aspects described in one embodiment may be combined in any manner with aspects described in other embodiments.

  Thus, while several aspects of at least one embodiment of the present invention have been described, it should be understood that various changes, 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 present invention. Accordingly, the foregoing description and drawings are exemplary.

  110 ... P wave, 120 ... QRS group, 130 ... T wave, 140 ... Part of trace between P wave and QRS group, 150 ... Between QRS group and T wave 160 ... U wave, 170 ... Equipotential line, 210,230 ... ST segment, 220,240 ... PQ segment, 310,320,330 ... electrode, 510,520 ... pillar, 600a ... Front part, 600b ... Rear part, 610, 612 ... Front region, 620 ... Lower region, 630a, 630b ... RV region, 640 ... Rear region, 2100 ... Computer.

Claims (40)

A computer-implemented method for measuring the degree of myocardial injury,
Determining the magnitude of ST excursion based on electrocardiographic data obtained from at least one electrode in the electrocardiograph and associated with at least one electrode associated with at least one region of the heart; ,
Determining an area factor for the at least one electrode, the area factor associated with the at least one region;
Calculating an ST deviation amount for the at least one electrode based at least in part on the magnitude of the ST deviation and the area factor;
Storing the ST deviation in a computer-readable storage medium;
A method comprising: The front region has a first area factor;
The rear region has a second area factor,
The method of claim 1, wherein the first area factor is smaller than the second area factor.   The method of claim 1, wherein the area factor is selected based on a size of the at least one region and a number of electrodes associated with the at least one region. Displaying a representation of the ST deviation with respect to the at least one electrode;
The method of claim 1, further comprising: The magnitude of ST deviation is a scaled magnitude of ST deviation;
Determining an unscaled magnitude of ST excursion based on the electrocardiograph data obtained from the at least one electrode;
Determining a scaling factor associated with the at least one electrode;
Calculating the scaled magnitude of ST excursion by at least partially scaling the unscaled magnitude of ST excursion using the scaling factor;
The method of claim 1, wherein the scaled magnitude of ST excursion is obtained at least in part. The front region has a first scaling factor;
The rear region has a second scaling factor;
6. The method of claim 5, wherein the first scaling factor is smaller than the second scaling factor. The magnitude of ST deviation is an adjusted magnitude of ST deviation;
Based on the electrocardiograph data obtained from the at least one electrode, an unadjusted magnitude of ST excursion is determined;
Determining a threshold associated with the at least one electrode;
By calculating the adjusted magnitude of ST excursion by at least partially subtracting the threshold from the unadjusted magnitude of ST excursion;
The method of claim 1, wherein the adjusted magnitude of ST excursion is obtained at least in part. The front region has a first threshold;
The rear region has a second threshold;
The method of claim 7, wherein the first threshold is greater than the second threshold. The electrocardiograph comprises a plurality of electrodes,
The method
Calculating an ST deviation for each of the plurality of electrodes;
Calculating a total ST excursion amount based at least in part on the ST excursion amount for each of the plurality of electrodes;
The method of claim 1, further comprising:   The method of claim 9, wherein the total ST excursion is calculated by adding the ST excursion for each of the plurality of electrodes. The electrocardiograph comprises a plurality of electrodes,
The method
Calculating an ST deviation for each of the plurality of electrodes;
Calculating a total ST increase amount based at least in part on the ST deviation amount for each of the plurality of electrodes that has detected an ST increase;
The method of claim 1, further comprising:   The method according to claim 11, wherein the total ST increase is calculated by adding the ST deviation amount for each of the plurality of electrodes in which ST increase is detected. The electrocardiograph comprises a plurality of electrodes,
The method
Calculating an ST deviation for each of the plurality of electrodes;
Calculating a total ST descent amount based at least in part on the ST excursion amount for each of the plurality of electrodes that has detected ST descent;
The method of claim 1, further comprising:   The method according to claim 13, wherein the total ST descending amount is calculated by adding the ST deviation amount for each of the plurality of electrodes in which ST descending is detected. A device comprising a computer readable storage medium encoded with computer executable instructions comprising:
Instructions executed by the computer, when executed, perform a method of measuring the degree of myocardial injury;
The method
Determining the magnitude of ST excursion based on electrocardiographic data obtained from at least one electrode in the electrocardiograph and associated with at least one electrode associated with at least one region of the heart; ,
Determining an area factor for the at least one electrode, the area factor associated with the at least one region;
Calculating an ST deviation amount for the at least one electrode based at least in part on the magnitude of the ST deviation and the area factor;
device. The front region has a first area factor;
The rear region has a second area factor,
The device of claim 15, wherein the first area factor is less than the second area factor.   16. The device of claim 15, wherein the area factor is selected based on a size of the at least one region and a number of electrodes associated with the at least one region. The magnitude of ST deviation is a scaled magnitude of ST deviation;
Determining an unscaled magnitude of ST excursion based on the electrocardiograph data obtained from the at least one electrode;
Determining a scaling factor associated with the at least one electrode;
By calculating the scaled magnitude of the ST excursion by at least partially scaling the initial magnitude of the ST excursion using the scaling factor,
The device of claim 16, wherein the scaled magnitude of ST excursion is obtained at least in part. The front region has a first scaling factor;
The rear region has a second scaling factor;
The device of claim 18, wherein the first scaling factor is less than the second scaling factor. The magnitude of ST deviation is an adjusted magnitude of ST deviation;
Based on the electrocardiograph data obtained from the at least one electrode, an unadjusted magnitude of ST excursion is determined;
Determining a threshold associated with the at least one electrode;
By calculating the adjusted magnitude of ST excursion by at least partially subtracting the threshold from the unadjusted magnitude of ST excursion;
16. The device of claim 15, wherein the adjusted magnitude of ST excursion is obtained at least in part. The front region has a first threshold;
The rear region has a second threshold;
21. The device of claim 20, wherein the first threshold is greater than the second threshold. The electrocardiograph comprises a plurality of electrodes,
The method
Calculating an ST deviation for each of the plurality of electrodes;
Calculating a total ST excursion amount based at least in part on the ST excursion amount for each of the plurality of electrodes;
The device of claim 15, further comprising:   23. The device of claim 22, wherein the total ST deviation is calculated by adding the ST deviation for each of the plurality of electrodes. The electrocardiograph comprises a plurality of electrodes,
The method
Calculating an ST deviation for each of the plurality of electrodes;
Calculating a total ST increase amount based at least in part on the ST deviation amount for each of the plurality of electrodes that has detected an ST increase;
The device of claim 15, further comprising:   25. The device of claim 24, wherein the total ST increase is calculated by adding the ST deviation for each of the plurality of electrodes that detected ST increase. The electrocardiograph comprises a plurality of electrodes,
The method
Calculating an ST deviation for each of the plurality of electrodes;
Calculating a total ST descent amount based at least in part on the ST excursion amount for each of the plurality of electrodes that has detected ST descent;
The device of claim 15, further comprising:   27. The device of claim 26, wherein the total ST descent amount is calculated by adding the ST deviation amount for each of the plurality of electrodes that have detected ST descent. A method of diagnosing a patient based on a total ST deviation amount,
Obtaining a total ST deflection for the patient based on size and area information collected from an array of electrodes attached to the patient;
Retrieving a total ST excursion data from a plurality of patients having a confirmed diagnosis result from a computer readable storage medium;
Using the total ST deviation data to obtain one or more diagnostic thresholds;
Comparing the total ST deviation of the patient with the diagnostic threshold;
A method comprising: The diagnostic threshold comprises a first diagnostic threshold for determining whether the patient suffers from myocardial infarction (MI);
The first diagnostic threshold value is obtained based on data of the first total ST deviation amount from the confirmed MI patient and data of the second total ST deviation amount from the confirmed non-MI patient. 30. The method of claim 28.   30. The method of claim 29, wherein third total ST excursion data from a patient suffering from a disease other than MI is removed from the second total ST excursion data.   32. The method of claim 30, wherein the disease other than MI is a left leg block. Selecting a treatment for the patient based on a comparison result between the total ST deviation of the patient and the diagnostic threshold;
30. The method of claim 28, further comprising: A system for measuring the degree of myocardial damage based on electrocardiograph data obtained from a patient,
Determining the magnitude of the ST deviation based on electrocardiograph data obtained from the at least one electrode applied to the patient and associated with at least one region of the heart; And
Determining an area factor for the at least one electrode and associated with the at least one region;
Calculating an ST deviation amount for the at least one electrode based at least in part on the magnitude of the ST deviation and the area factor;
One or more processors programmed to
system. The magnitude of ST deviation is a scaled magnitude of ST deviation;
The one or more processors are:
Determining an unscaled magnitude of ST excursion based on the electrocardiograph data obtained from the at least one electrode;
Determining a scaling factor associated with the at least one electrode;
Calculating the scaled magnitude of ST excursion by at least partially scaling the unscaled magnitude of ST excursion using the scaling factor;
34. The system of claim 33, further programmed as follows. The magnitude of ST deviation is an adjusted magnitude of ST deviation;
The one or more processors are:
Based on the electrocardiograph data obtained from the at least one electrode, an unadjusted magnitude of ST excursion is determined;
Determining a threshold associated with the at least one electrode;
Calculating the adjusted magnitude of ST excursion by at least partially subtracting the threshold from the unadjusted magnitude of ST excursion;
34. The system of claim 33, further programmed as follows. The system further comprises a plurality of electrodes attached to the patient;
The one or more processors are:
Calculating an ST deviation for each of the plurality of electrodes;
Calculating a total ST deviation for the patient based at least in part on the ST deviation for each of the plurality of electrodes;
34. The system of claim 33, further programmed as follows. The one or more processors are:
Comparing one or more diagnostic thresholds obtained using total ST deviation data from a plurality of patients having a confirmed diagnostic result to the total ST deviation of the patient;
40. The system of claim 36, further programmed as follows. The diagnostic threshold comprises a first diagnostic threshold for determining whether the patient suffers from myocardial infarction (MI);
The first diagnostic threshold value is obtained based on data of the first total ST deviation amount from the confirmed MI patient and data of the second total ST deviation amount from the confirmed non-MI patient. 38. The system of claim 37. The one or more processors are:
Selecting a treatment for the patient based on a comparison result between the total ST deviation of the patient and the one or more diagnostic thresholds;
38. The system of claim 37, further programmed as follows. A system for measuring the degree of myocardial damage based on electrocardiograph data obtained from a plurality of electrodes arranged on a chest region of a patient,
The plurality of electrodes form an array covering a substantial portion of the chest region;
The system
Based on the electrocardiograph data obtained from each of the plurality of electrodes, for each of the plurality of electrodes, a raw magnitude of ST deviation is determined,
For each of the plurality of electrodes, determine an area factor, a threshold, and a scaling factor;
Using the threshold for each of the plurality of electrodes and the scaling factor to calculate a modified magnitude of ST excursion for each of the plurality of electrodes;
Calculating an ST deviation amount for each of the plurality of electrodes based at least in part on the area factor for each of the plurality of electrodes and the modified magnitude of the ST deviation;
Calculating a total ST deviation for the patient based at least in part on the ST deviation for each of the plurality of electrodes;
One or more processors programmed to
system.

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