Source: https://patents.google.com/patent/US9980665B2/en
Timestamp: 2019-10-17 13:07:27
Document Index: 492831008

Matched Legal Cases: ['art 114', 'art 114', 'art 114', 'art 114', 'art 114', 'Application No. 61', 'art 300', 'art 401', 'art 401', 'art 401', 'art 401']

US9980665B2 - Methods and systems to calculate time of mechanical activation using characterization motion data area strains - Google Patents
Methods and systems to calculate time of mechanical activation using characterization motion data area strains Download PDF
US9980665B2
US9980665B2 US14/703,764 US201514703764A US9980665B2 US 9980665 B2 US9980665 B2 US 9980665B2 US 201514703764 A US201514703764 A US 201514703764A US 9980665 B2 US9980665 B2 US 9980665B2
US14/703,764
US20150313482A1 (en
2014-05-05 Priority to US201461988779P priority Critical
2015-05-04 Priority to US14/703,764 priority patent/US9980665B2/en
2015-11-05 Publication of US20150313482A1 publication Critical patent/US20150313482A1/en
2018-05-29 Publication of US9980665B2 publication Critical patent/US9980665B2/en
230000000142 dyskinetic Effects 0 claims description 7
230000003483 hypokinetic Effects 0 claims description 8
238000004137 mechanical activation Methods 0 abstract claims description title 26
A method and system is provided for determining the mechanical activation of a region of interest. The system and method include using a triangulation technique algorithm to generate at least one triangle within a region of interest, wherein the triangle is formed from map points acquired from an intravascular mapping tool. The system and method further include calculating an area strain for each triangle, determining abnormal areas of the region of interest, and excluding triangles that include the abnormal area. Further, the system and method include determining a mechanical activation time for the region of interest based on the remaining triangles.
The present application relates to and claims priority from the following application: U.S. provisional application Ser. No. 61/988,779, filed May 5, 2014, titled “METHODS AND SYSTEMS TO CALCULATE TIME OF MECHANICAL ACTIVATION USING CHARACTERIZATION MOTION DATA AREA STRAINS” which is expressly incorporated herein by reference in their entirety in the present application.
Systems have been proposed to characterize the motion of the heart, specifically on the qualitative techniques of characterizing motion. However, the systems proposed thus far do not offer sufficient information to prepare acquired characterization data for strain analysis. A need remains for methods and system that can offer more information about calculating strain from characterization data.
In accordance with an embodiment herein, a method is provided for determining the mechanical activation of a region of interest. The method includes using a triangulation technique algorithm to generate at least one triangle within a region of interest, wherein the triangle is formed from map points acquired from an intravascular mapping tool. The method further includes calculating an area strain for each triangle, determining abnormal areas of the region of interest, and excluding triangles that include the abnormal area. Further, the method includes determining a mechanical activation time for the region of interest based on the remaining triangles.
FIG. 5 illustrates map points within a segmented left ventricle in accordance with an embodiment herein.
FIG. 6 illustrates a sub-divided region of interest within a three dimensional (3D) visualization of map points from a point cloud data set of the LV, in accordance with an embodiment disclosed herein.
FIG. 7 illustrates a segment selected as a region of interest that is subdivided or segment divided into triangles, in accordance with an embodiment disclosed herein.
FIG. 8 illustrates the overall area strain curves for walls of a region of interest, in accordance with an embodiment disclosed herein.
FIG. 9 illustrates a bullseye plot that summarizes the MAT determined from FIG. 8 for each wall, in accordance with an embodiment disclosed herein.
FIG. 10 illustrates a flow chart for determining the mechanical activation of a region of interest, in accordance with an embodiment disclosed herein.
FIG. 11 illustrates a system for analyzing motion data in accordance with an embodiment.
U.S. patent application Ser. No. 14/328,523, filed Jul. 10, 2014, titled “METHOD AND SYSTEM TO MEASURE CARDIAC MOTION USING A CARDIOVASCULAR NAVIGATION SYSTEM”,
U.S. patent application 61/988,771, filed May 5, 2014, titled “CARDIAC RESYNCHRONIZATION SYSTEM AND METHOD” having docket number A14P3006, and
FIG. 1 illustrates a cardiovascular navigation system (CNS) 110, of an embodiment, for use in imaging an anatomical region of a patient 112, such as, a heart 114. A medical tool 116 is placed within the anatomical region, such as for example, an electrophysiological (EP) mapping catheter (e.g., a guidewire), or a catheter generally described or shown in U.S. Pat. No. 7,881,769, which is expressly incorporated herein by reference. The medical tool 116 includes a plurality of electrophysiological sensors 152 that may be placed on the endocardial or epicardial surface of the left ventricle (LV) of the heart 114. The electrophysiological sensors 152 may be attached to the distal or proximal end of the medical tool 116, or any point in between. The electrophysiological sensors 152 measure a position and an electrical potential or an electric current of biological cells and tissues. The electrophysiological sensors 152 transmit the position and electrical potential information to an electronic control unit (ECU) 126. For example, the electrophysiological sensors 152 may be positioned by the medical tool 116 to measure point specific (PS) motion data for a plurality of map points of the wall of the heart 114. It should be understood, however, that the electrophysiological sensors 152 could be used in a variety of anatomical regions or alternative map points within the heart 114 or other organs in which motion characterization may be of interest. Additionally or alternatively, the electrophysiological sensors 152 may be replaced by separate motion sensors and electrical sensors. The motion sensors in contact with the region of interest (e.g., the LV of the heart 114) measuring the position sensors as well as the electrical sensors that are measuring the PS motion data of the region of interest. Optionally, the ECU 126 may receive the PS motion data and electrical sensor measurements simultaneously from the motion sensors and electrical sensors.
The imaging system 118 may include a C-arm support structure 128, a radiation emitter 130, and a radiation detector 132. The emitter 130 and detector 132 are disposed on opposite ends of the support structure 128 and disposed on opposite sides of the patient 112 as the patient 112 lays on an operation table 134. The emitter 130 and detector 132 define a field of view 136 and are positioned such that the field of view 136 includes the anatomical region of interest as the patient 112 lays on the operation table 134. The imaging system 118 is configured to capture images of anatomical features and other objects within the field of view 136. The support structure 128 may have freedom to rotate about the patient 112 as shown by lines 138 and 140. The support structure 128 may also have freedom to slide along lines 142 and 144 (e.g., along the cranio-caudal axis of the patient 112) and/or along lines 146 and 148 (e.g., perpendicular to the cranio-caudal axis of the patient 112). Rotational and translational movement of the support structure 128 yields corresponding rotational and translational movement of the field of view 136. Additionally or alternatively, the navigation system 120 may adjust the navigation coordinates of the position of the medical tool 116 to compensate for changes in the C-arm support structure 128 and respiratory movements of the patient as disclosed in the U.S. Provisional Application No. 61/910,630, entitled, “METHOD TO MEASURE CARDIAC MOTION USING A CARDIOVASCULAR NAVIGATION SYSTEM,” which is expressly incorporated herein by reference in its entirety.
FIG. 2 illustrates a method 200 performed in accordance with embodiments herein for assigning map points to anatomical segments of the heart and subdividing a region of interest into triangles. Throughout the present application, examples are provided in connection with mapping the left ventricle (LV). It should be recognized that the operations described herein may be used to map other regions of the heart. When mapping other regions of interest in the heart, different reference points and landmarks may be used.
Beginning at 202, a mapping tool (e.g., the medical tool 116) is introduced into the patient 112 proximate to a region of interest (e.g., the LV). Images are displayed to the user through the display 158. The images may be collected from various diagnostic imaging modalities (e.g. fluoroscopy, X-ray, MR, ultrasound, CT, PET, SPECT and the like) from the imaging system 118. Information from the navigation system 120, regarding the mapping tool, is combined with the images of the region of interest, and graphical representations are displayed of the mapping tool, in combination with the diagnostic image(s) on the display 158. For example, the mapping tool may be displayed superimposed upon the diagnostic image(s). By way of example, the physician may utilize intravascular mapping tool that is configured to be inserted proximate to the heart, endocardially and/or epicardially. The physician maneuvers the mapping tool between multiple locations of interest that are proximate to select areas on interior and/or exterior surfaces of the heart. For example, the physician may manipulate a mapping tool within the left ventricle and/or right ventricle to collect endocardial mapping data associated with interior surfaces of the chambers of the heart.
Additionally or alternatively, the physician may maneuver the mapping tool along one or more veins that extend about an exterior of a select region/chamber of the heart, such as the right ventricle and/or left ventricle, to collect epicardial mapping data. The medical tool may acquire point specific (PS) motion data of the heart at numerous map points positioned along the walls of the various chambers during at least one cardiac cycle.
FIG. 3 illustrates a graphical representation of a portion of a heart 300 with a medical tool 302 positioned to acquire PS motion data. For example, the medical tool 302 may be used to acquire PS motion data for a plurality of map points 308-310 associated with a heart wall 306. The PS motion data forms a portion of a point cloud data set. The point cloud data set may include all data collected by the medical tool 302, which may include information other than PS motion data. The term “point specific” is used to indicate that the motion data is associated with a single select location on the heart wall. The data values represent positions of the single select location over one or more cardiac cycles. The example of FIG. 3 shows three map points of interest 308-310 along the heart wall. Optionally, more or fewer map points of interest may be designated to expand the point cloud data set. The medical tool 302, which may correspond the medical tool 116 of FIG. 1 with the plurality of electrophysiology sensors 152, is positioned directly against the heart wall 306 at one or more points of interest 308-310. The tool 302 measures movement of the one or more points over a select period of time. In the example of FIG. 3, the tool 302 is shown positioned against map points 308-310 at different points in time.
Optionally, the navigation system 120 may adjust PS motion data within the point cloud data set based on motion waveforms. A motion waveform represents the motion of a map point during a cardiac cycle as defined by the PS motion data. For example, the PS motion data may be adjusted temporally equalized by “stretching” motion waveforms that have shorter cycle lengths until the shorter motion waveform subsets have a length equal to a predetermined or common time interval. The common time interval may be predetermined, or automatically selected, such as by choosing a length corresponding to the longest, shortest, or average length of the motion waveforms defined by the PS motion data within the point cloud data set. The time interval may be set to begin at a point in time defined by a global signal such as the peak of the R-wave as detected by using the Electrocardiogram (ECG) or Intracardiac Electrogram (IEGM) signals. Optionally, the time interval may be defined to begin based on another global marker of electrical activity (e.g., the T-wave, P-wave).
Additionally or alternatively, the navigation system 120 may apply a rotation technique to the motion waveform to correct for non-periodicity, such as the rotation techniques described in U.S. application Ser. No. 14/328,513. A periodic motion waveform of a map point during the cardiac cycle has, at the start and end of the cardiac cycle, approximately the same measured displacement or position. Non-periodicity may occur from errors in the acquired PS motion data for the map point that defines the motion waveform. For example, if the electrophysiological sensor 152 is not maintained directly against the heart wall during the entire cardiac cycle, the PS motion data may drift.
FIG. 4 illustrates a graph 400 for a motion waveform 405 that is defined by a plurality of PS motion data associated with a select map point (e.g., the map point 308 in FIG. 3). The motion waveform 405 represents a displacement of the map point with respect to a vertical axis 410 over time as denoted along a horizontal axis 414. A cardiac cycle 412 is represented between start 401 and end 402. At the start 401 of the cardiac cycle 412, the motion waveform 405 has a first measured displacement as shown by horizontal dashed line 408. At the end 402 of the cardiac cycle 412, the motion waveform 405 has a second measured displacement as shown by horizontal dashed line 416. The difference in the displacements (relative to the vertical axis 410) of the motion waveform 405 at the start 401 and the end 402 of the cardiac cycle 412 indicates that the motion waveform 405 is non-periodic. A rotation technique may be applied to generate a rotated motion waveform 406 that is periodic, such as disclosed in U.S. application Ser. No. 14/328,513. The rotation technique shifts the PS motion data from the motion waveform 405 until defining the rotated motion waveform 406. The rotated waveform 406 has a common measured displacement at the start 401 and end 402 of the cardiac cycle 412. The common measured displacement corresponds to dashed line 408.
Returning to FIG. 2, at 204, the method designates anatomic landmarks by defining apical, basal, and circumferential landmarks within the point cloud data set. The anatomical landmarks may be designated through manual operations by the user. Additionally or alternatively, the anatomical landmarks may be designated through automatic calculations based on analysis of the point cloud data set, for example, as described in U.S. patent application Ser. No. 14/270,191, filed May 5, 2014, titled “METHOD AND SYSTEM TO AUTOMATICALLY ASSIGN MAP POINTS TO ANATOMICAL SEGMENTS”, which is incorporated by reference in its entirety. The landmarks are located at various locations based upon the shape and nature of the region of interest. For example, at least one landmark is located proximate to, or at, the apex of the region of interest. Another landmark is located at, or proximate to, a middle of a base of the region of interest, while another landmark is located circumferentially from the base at an outer limit of the region of interest. For example, when the region of interest represents the right or left ventricle, the apex landmark represents the apex of the RV or LV. The basal landmark represents the base of the RV or LV and the circumferential landmark represents the left or right ventricular outflow tract.
At 208, the method 200 assigns map points to the circumferential segments as defined at 206. In order to automatically assign each map point, the method determines a corresponding segment of the anatomical map. To do so, in at least one embodiment, the method defines a reference line between the basal landmark and circumferential landmark. The circumferential location of each map point (θm) at a predefined point in the cardiac cycle, such as at the peak of the QRS complex, is compared against the circumferential landmark (θLVOT). A tolerance may be used such as (θLVOT−π/6—tolerance)<θm≤(θLVOT+π/6+tolerance). Each map point is assigned to the corresponding wall segment, where the circumferential landmark is used to identify a reference wall segment, such as the anteroseptal wall segment. Upon definition of the segment boundaries of the first wall segment, with the option of including a circumferential tolerance, the definitions of the other wall segments include the subsequent addition or subtraction of multiples of tolerance (e.g. π/3+tolerance) until the entire circumference of a region of interest (e.g, LV) is assigned to the appropriate wall segment.
At 210, the method calculates longitudinal the segment boundaries. At 212, the method assigns map points to the segments based on the longitudinal segment boundaries. For example, the method performs segmentation along the long axis for definition of apical vs. mid-ventricular vs. basal points. The longest available length of the long axis (LLong Axis) is determined. An apical portion (AP) parameter is then defined which determines the extent of the apical segments and LLong Axis is divided by AP, such that any point with a longitudinal coordinate less than LLong Axis/AP is assigned to the apex. A typical value for AP may be 3, in which the apical segments cover ⅓ of the length of the entire wall from apex to base. Next, the remaining points with longitudinal coordinates less than
At 214, the map points are stored in a data storage with associated segment assignments. Additionally or alternatively, the navigation system 120 may calculate circumferential and longitudinal segment boundaries, for the point cloud data set, based on the apical, basal and circumferential landmarks as disclosed in U.S application Ser. No. 14/270,191.
FIG. 5 illustrates a three dimensional (3D) visualization of map points 510 located along the LV. The visualization 500 may be displayed on the display 158 in FIG. 1. FIG. 5 illustrates the left ventricular of the heart divided into segments 520 (not all segments shown) by circumferential segment boundaries 512 (not all boundaries are shown) and longitudinally segment boundaries 514 (not all boundaries are shown). It should be noted in alternative embodiments the number of circumferential and longitudinal segments may be fewer than or greater than shown in FIG. 5. Optionally, the three dimensional visualization 500 may include a graphical marker for an apical landmark, a basal landmark, and circumferential landmarks (e.g., septal, anterior-septal, anterior). The map points 510 are assigned to the segments in accordance with the operations at 208 and 210. In particular, as one example, the map points 510 a-b are assigned to an associated segment 520 a based on the location of the map points 510 a-b, while map points 510 c-d are assigned to the segment 520 b.
Additionally or alternatively, the map points (as described above) may be based on a cylindrical coordinate system. For example, the map points 510 may be oriented based on a longitudinal axis 522, a polar or radial axis 524 with an origin approximate to the apex, and an angular coordinate or azimuth from the radial axis 524. It should be noted, in alternative embodiments the coordinate system may be oriented or have an origin on other landmarks within the region of interest, for example, the base, septal, or the like. Optionally, the coordinate system may be oriented or have an origin external to the region of interest (e.g., the heart), for example based on a reference external to the patient such as the transmitter assembly 150.
Optionally, a subset of the map points 510 may be assigned to multiple segments 520 based on the distance of the map points from at least one of the longitudinal and/or circumferential segment boundaries 512 and 514. For example, the map point 510 d may be assigned to both the segments 520 a and 520 b based on the proximity to the circumferential segment boundary 512.
In accordance with some embodiments, the navigation system 120 may build a matrix (e.g., Matrix 1) based on the Cartesian coordinates of the map points within the segments and/or the wall, where x11, y11, and z11 is the first x, y, and z position, respectively, at the first map point in the segment and/or the wall. Position x12, y12, z12 is the second x, y, and z position, respectively, at the first map point in the segment and/or the wall position, X1n, y1n, Z1n is the nth x, y, and z position, respectively, at the first map point in the segment and/or wall. Position xmn, ymn, zmn is the nth x, y, and z position, respectively, at mth map point in the segment and/or the wall.
[ x 11 y 11 z 11 x 12 y 12 z 12 … x 1 ⁢ n y 1 ⁢ n z 1 ⁢ n x 21 y 21 z 21 … … x mn y mn z mn ] ( Matrix ⁢ ⁢ 1 )
The navigation system 120 may perform a factorization of the matrix (M) following Equation 1, where the variable U, of equation 1, is a unitary matrix, the variable S is a diagonal matrix containing singular values on the diagonal, and V* is a conjugate transpose of a unitary matrix V.
M=U·S·V* (Equation 1)
The navigation system 120 may create a new matrix, Sk, from the matrix S by maintaining a number of samples, k, representing the largest singular values within in the matrix S and setting the rest of the singular values to zero. Once the matrix Sk is determined, the navigation system 120, may determine a new matrix Mfilt from Equation 2. Once Mfilt is determined, the navigation system 120 may separate Mfilt back into x, y, z and use the filtered x, y, z, data for further analysis.
Mf ilt =U·S k ·V* (Equation 2)
Returning to FIG. 2, at 215, optionally, a 3D visualization 500 of the map points 510 is displayed (e.g. on the display 158 in FIG. 1) with associated segments 520.
At 216 the method 200 selects a region of interest from the point cloud data set. For example, the navigation system 120 may automatically, or the clinician (via the operator system interface 154) may manually, select a region of interest for further analysis in accordance with embodiments herein. By way of example, the user may use a mouse, curser and/or keyboard of the system interface 154 to “click on”, draw around or otherwise designate the region of interest. The region of interest may be located within a segment, a plurality of segments, a portion of/entire apical region, a portion of/entire mid-ventricular region, a portion of/entire basal region, entire surface of the LV or RV, or the like.
At 218, the method 200 forms a triangulation area that includes a set of map points from the point cloud data set corresponding to the region of interest. The triangulation area corresponds to the region of interest. The triangulation area is defined by the set of map points within the region of interest. For example, the navigation system 120 may determine boundaries of the triangulation area based on positions of one or more of the select map points within the region of interest. The set of map points within the triangulation area may identify the map points to be used by the navigation system 120 to form one or more triangles as described at 220.
At 220, the method 200 uses a triangulation technique, such as the DeLaunay triangulation algorithm, to generate at least one triangle within the triangulation area formed from at least a portion of the set of map points. For example, attention is directed to FIG. 6 to further discuss the operation at 220. FIG. 6 illustrates a visualization 600 of a set of map points. In the example of FIG. 6, the user has selected a region of interest within the segment 608. The segment 608 is bounded by circumferential segment boundaries 608 and longitudinal segment boundaries 604. It should be noted, although the region of interest is shown as the segment 608 in FIG. 6, the region of interest may be within a segment, a plurality of segments, a portion of/entire apical region, a portion of/entire mid-ventricular region, a portion of/entire basal region, entire surface of the LV or RV, or the like.
The navigation system 120 may apply a triangulation technique algorithm (TTA) (e.g., DeLaunay triangulation algorithm) to generate non-overlapping triangles 610-614 within a triangulation area corresponding to the region of interest (e.g., the segment 608). The TTA may maximize the minimum angle of the triangles to avoid skinny triangles. Each of the non-overlapping triangles 610-614 are formed from map points 602 a-e within the segment 608. For example, the triangle 610 is formed from map points 602 a-c. It should be noted that non-overlapping or overlapping triangles may be generated by the navigation system 120 using the TTA as further disclosed in U.S. Provisional Application 61/988,767, titled “METHOD AND SYSTEM TO SUBDIVIDE A MAPPING AREA FOR MECHANICAL ACTIVATION ANALYSIS”, which is expressly incorporated herein in its entirety.
The navigation system 120 may determine and equalize cycle lengths (CL) of the x, y, z ensemble average data at the three triangle vertices (A,B,C) as disclosed in U.S. Provisional Application 61/988,763, titled “METHOD AND SYSTEM TO EQUALIZING CARDIAC CYCLE LENGTH BETWEEN MAP POINTS”, which is expressly incorporated herein by reference in its entirety. From the ensemble average data, the navigation system 120 may calculate the three distances between the three vertices of triangles in 3-D space and determine an area of each triangle from equations 3 and 4 below. For example, the triangle 610 is formed from the vertices or map points 602 a-c represented as A, B, and C respectively in Equations 3 and 4 below.
p = AB + A ⁢ ⁢ C + BC 2 ( Equation ⁢ ⁢ 3 ) A = p ⁡ ( p - AB ) ⁢ ( p - A ⁢ ⁢ C ) ⁢ ( p - BC ) ( Equation ⁢ ⁢ 4 )
The navigation system 120 may determine the distance between the map points 602 a-b, 602 b-c, and 602 a,c shown as variables AB, BC, and AC, respectively. From the distance between the map points 602 a-c, the navigation system may determine the area of the triangle 610 using the equations 3 and 4. The navigation system 120 may further determine the area of the triangles 610-614 within the region of interest (e.g., the segment 608) to determine an area strain for each triangle 610-614.
The area strain (εA) of the triangles 610-614 over the cardiac cycle may be determined using Equation 5 below.
ɛ A = A - A o A o ( Equation ⁢ ⁢ 5 )
Optionally, the navigation system 120 may define an area strain curve of each triangle 610-614 dependent on time. The variable A of Equation 5 represents an instantaneous area of the triangle 610-614 at a moment of time during the cardiac cycle. The variable Ao of Equation 5 represents an initial area of the tissue in the triangle at some pre-defined temporal reference or time during the cardiac cycle. For example, the pre-defined temporal reference may be a time corresponding to a peak of the surface ECG R-wave.
FIG. 10 illustrates operations of a method 1000 that are further illustrated in connection with FIGS. 7-9. The method 1000 may be used to determine the mechanical activation of a region of interest. The method 1000, for example, may employ structures or aspects of various embodiments (e.g., systems and/or methods) discussed herein (e.g., the CNS 110 in FIG. 1). In various embodiments, certain steps (or operations) may be omitted or added, certain steps may be combined, certain steps may be performed simultaneously, certain steps may be performed concurrently, certain steps may be split into multiple steps, certain steps may be performed in a different order, or certain steps or series of steps may be re-performed in an iterative fashion. It should be noted, other methods may be used, in accordance with an embodiment herein.
At 1002, the method 1000 uses a triangulation technique algorithm (TTA) to generate at least one triangle within a region of interest as explained in connection with FIG. 2.
At 1004, the method 1000 calculates an area strain for each triangle. For example, as described above from equation 5 and as described below in relation to FIG. 7. For example, the calculating operation may include calculating cycle lengths associated with map points corresponding to vertices of a first geometric area, calculating distances between the vertices, determining an area of the geometric area based on the distances between the map points corresponding to the vertices, and determining the area strain of the geometric area over at least one cardiac cycle.
At 1006, the method 1000 determines one or more abnormal areas within the region of interest. The geometric areas that are separate and distinct from the abnormal geometric areas represent valid geometric areas utilized when determining the mechanical activation time.
Optionally, at 1007, the method 1000 may display (e.g. on the display 158 in FIG. 1) that an area is abnormal.
At 1008, the method 1000 excludes triangle that include the abnormal area(s). At 1010, the method 1000 determines a mechanical activation time for the region of interest based on the remaining triangles as described in connection with FIGS. 7-9. By way of example, the excluding operation excludes map points based on at least one of a morphology of the geometric area, a presence of sharp spikes in the area strain associated with the corresponding geometric area, a size of the geometric area, a variability of cycle length within the geometric area or variation in electrical tissue characteristics associated with the geometric area. Optionally, at 1012, the method 1000 displays the activation time, for example, on the display 158 shown in FIG. 1.
FIG. 7 illustrates a segment 750 selected as a region of interest that is subdivided or segment divided into triangles 752. The segment 750 maybe presented on the display 158. The triangles 752 are shown on the display 158 in 2D space formed by map points 702 using the TTA as described above at 1002. Each triangle 752 includes a corresponding area strain curve 756 calculated by the navigation system 120 as described above at 1004 in FIG. 10 and displayed on display 158. Optionally, the navigation system 120 may use a graphical marker or color, whether an area strain curve 756 is included in the MAT analysis (e.g., blue) or excluded (e.g., magenta).
The determination of the abnormal area(s) at 1006 may be performed in several manners. For example, the navigation system 120 may exclude one or more of the triangles used to determine the mechanical activation time (MAT) based on the morphology of the triangle, the presence of sharp spikes, the size of the triangle, the variability of the CL, and/or variation in electrical tissue characteristics as described further below. The triangles that are not excluded represent valid or included triangles and are associated with normal tissue areas.
Abnormal areas may be based on morphology because the morphology of a triangle may be unusual due to issues with acquiring the PS motion data at one or more vertices forming the triangle. Data issues include poor catheter contact, catheter slippage, and other such procedural inconsistencies. Morphology of each triangle can be evaluated by finding a correlation coefficient between the area strain curve of the triangle being evaluated and a template chosen at the beginning of the analysis process. If the correlation coefficient is below some predetermined threshold (e.g. 0.7), the triangle is excluded from analysis as an abnormal area.
Alternatively or in addition, abnormal areas may be based on the peaks of the area strain curve. The navigation system 120 may determine a number of local peaks of the area strain curve. If the number of peaks exceed a threshold such as, for example three, the morphology of the triangle may be considered abnormal and the triangle may be excluded by the navigation system 120 for determining MAT.
Presence of sharp spikes within the area strain curve may indicate some electrical or mechanical interference during the data collection of the PS motion data. A spike may be determined by the navigation system 120 as having a slope above a predetermined threshold. Optionally, the navigation system 120 may determine whether a spike is present by finding a second time derivative of the area strain curve, dividing the resulting curve by the difference between a maximum and minimum of the curve (e.g., peak to peak value), measuring the area under the resulting curve, and comparing the area of the curve against a predetermined threshold. If a spike is detected in the area strain curve, the triangle with the corresponding area strain curve may be excluded from the MAT analysis.
A triangle having an area below a set threshold may be excluded from MAT analysis as an abnormal area. The area of the triangle may correspond to the distance between the vertices or map points that form the triangle. If a triangle area is too small, then the behavior of such a triangle may not be representative of the contractile patterns. Triangles with areas below some predetermined threshold (e.g. 1 square millimeter), as measured at a reference time such as, for example, the R-wave on the ECG, may be excluded from further MAT analysis as abnormal areas.
Abnormal areas may be identified based on variability of the CL. The CL can vary greatly during the duration of data collection due to factors such as sedation and drug administration during the mapping procedure. Even though CLs are equalized earlier in the data analysis process, if a triangle combines points whose original CLs were vastly different, the area strain curve may be affected. The navigation system 120 may compare the data of the original CLs, prior to equalization, at each triangle vertex. Triangles with a difference between the shortest CL and the longest CL of more than a select threshold (e.g. 100 millisecond) may be excluded by the navigation system 120 from further MAT analysis.
The region of interest may include or be a portion of a heart chamber. The heart chamber may include areas of scarring or exhibiting low activity, which are likely to exhibit different types of movement or variable electrical tissue characteristics than areas without scarring or low electrical activity. Optionally, the navigation system 120 may adjust the TTA or manually combine map points that cover similar types of tissue into avoidance triangles. Additionally or alternatively, the area of the avoidance triangles may include border zones because the contractile patterns of such triangles may not be meaningful. The navigation system 120 may measure the voltage of the triangles or at the map points forming the triangles. In a triangle where some map points have a voltage below a certain threshold (e.g. 0.5 V) and some map points in the triangle have a voltage above that threshold, the triangle should be excluded from further analysis.
Additionally or alternatively, the navigation system 120 may measure conduction velocity between the map points forming the triangle. If there is large variability (e.g. >1.5 m/sec) between the conduction velocities, it may be an indication of mixed tissue characteristics and the navigation system 120 may exclude the triangle from further MAT analysis as an abnormal area.
Additionally or alternatively, triangles may be excluded from further MAT analysis for having an area under the curve that is larger than a select size. Preferably, normally-contracting myocardium involves the areas of the triangles decreasing as the heart squeezes inward with the area strain curve decreasing during the cardiac cycle. If the area strain curve increases during the cardiac cycle, the area under the curve will be positive and large. This type of behavior can be indicative of an area of dyskinesia, abnormal heart movement, or errors with data collection. Therefore, if the area under the area strain curve exceeds some threshold (e.g. 10 square millimeters), the triangle may be excluded from further MAT analysis as an abnormal area. Optionally, the navigation system 120 may indicate or note to the clinician via the display 158 that the triangle may be dyskinetic or otherwise an abnormal area.
For example, returning to FIG. 7, the triangle 752 a formed from the map points 702 c-e has a calculated area strain curve 756 a. The navigation system 120 may determine that the area under the strain curve 756 a exceeds a predetermined threshold and represents a dyskinesia, abnormal heart movement, or errors with data collection. The navigation system 120 may exclude the triangle 752 a from the MAT analysis as an abnormal area. Further, the navigation system 120 may change the graphical marker or color (e.g., from blue to magenta) of the triangle 752 a or the area strain curve 756 a to indicate that the triangle 752 a is excluded from further MAT analysis. Optionally, the navigation system 120 may determine if any of the triangle vertices also have a voltage below a certain threshold (0.5 V), to confirm dyskinesia. If the triangle vertices do not, the triangle may be excluded from analysis as an abnormal area by the navigation system 120 for further MAT analysis, but not considered dyskinetic.
As explained above, the preferable behavior of the area strain curve in healthy tissue is to decrease beyond some threshold and then return to a baseline. If the area strain curve does not increase as described above, but also does not decrease substantially, this area may be classified as hypokinetic, or exhibiting little movement. If the area strain curve does not reach a certain predetermined minimum threshold (e.g., such as −0.1), the triangle may be excluded from further analysis and the area of this triangle can be noted as being hypokinetic.
For example, the triangle 752 b formed from the map points 702 a-c has a calculated area strain curve 756 b. The navigation system 120 may determine that the area strain curve 756 b does not reach a certain predetermined minimum threshold. The navigation system 120 may exclude the triangle 752 b from the MAT analysis as an abnormal area. Further, the navigation system 120 may change the graphical marker or color (e.g., from blue to magenta) of the triangle 752 b or the area strain curve 756 b to indicate that the triangle 752 b is excluded from further MAT analysis.
For both dyskinesia and hypokinesia, certain portions of the heart, such as the septum or the LV outflow tract, may be prone to exhibiting less movement or inverse movement. Optionally, if the navigation system 120 determines that triangles fall into these areas, the navigation system 120 may adjust the thresholds corresponding to the triangles to determine whether the tissue within the triangle is dyskinetic or hypokinetic.
The triangles that are not excluded correspond to normal areas also referred to as included or valid triangles. Once the abnormal triangles have been excluded by the navigation system 120 as described above, the remaining included triangles may be combined to find the MAT for region of interest. The mechanical activation may be the time when the area strain curve begins to decrease (activation onset), the time when the area strain curve reaches its minimum or some percentage of its minimum or the like. One algorithm for finding the activation onset is to find when the second multipoint time derivative of the area strain curve reaches its minimum.
The time of mechanical activation may be found for each individual triangle based on the area strain curve. Optionally, the times may be combined together into the time of mechanical activation of the region containing the triangles. This may be done by taking a weighted or regular average of the individual triangle times of mechanical activation. The weights may be proportional to the area of the triangle, such that if the total area of a region, found by adding the areas of all the triangles in that region at some reference time point is ATOTAL and the area of the triangle being analyzed is ATRIANGLE at the same reference time point, the weight this triangle is assigned equals ATRIANGLE/ATOTAL.
Additionally or alternatively, after the triangles have equalized CL, the individual triangle area curves may be summed together, converted to the area strain curve, and the time of mechanical activation may be found for the entire sum.
Optionally, a percentage of area that is dyskinetic, hypokinetic, or simply excluded for earlier noted reasons may be calculated for each region of interest by dividing the sums of the dyskinetic, hypokinetic, or excluded triangle areas by the total area of the region (sum of all triangle areas in the region).
FIG. 8 illustrates the overall area strain curves 800 for walls (e.g., antero-septal, anterior, lateral, posterior, inferior, septal) of the region of interest. The overall area strain curves 800 were formed by summing the are a strain curves of the remaining triangles (e.g., 752) (triangle not excluded by the navigation system 120) for each wall. The MAT or time of mechanical activation 802 is indicated on each of the overall area strain curves 800. For example, the navigation system 120 determined that the MAT 802 occurs when the overall area strain curve 800 reaches 90% of the minimum. It should be noted, in embodiments the MAT 802 may be determined higher or below 90%.
FIG. 9 illustrates a bullseye plot 900 that summarizes the MAT 802 determined from FIG. 8 for each wall 902-912, which may be generated by the navigation system 120 on the display 158 at 1012 of FIG. 10. A number 916 represents the MAT 802 for the corresponding wall 902-912. A bracket number 914 indicates the percentage of the area of the wall 902-912 that is excluded from the MAT analysis. For example, the MAT of the inferior wall 912 was determined to occur at 482 milliseconds, and 14% of the area of the inferior wall 912 was excluded from the MAT analysis. Optionally, the bulls-eye plot 900 may be color coded 918 indicating a time continuum shift. For example, red 918 a may indicate the earliest activating segment and/or wall and purple 918 b the latest activating segment and/or wall.
FIG. 11 illustrates a functional block diagram of an embodiment of an electronic control unit (ECU) 1400 that is operated in accordance with the processes described herein to analyze motion data and to interface with the CNS 110. The ECU 1400 may be a workstation, a portable computer, a PDA, a cell phone and the like. The ECU 1400 includes an internal bus that connects/interfaces with a Central Processing Unit (CPU) 1402, ROM 1404, RAM 1406, a hard drive 1408, the speaker 1410, a printer 1412, a CD-ROM drive 1414, a floppy drive 1416, a parallel I/O circuit 1418, a serial I/O circuit 1420, the display 1422, a touch screen 1424, a standard keyboard connection 1426, custom keys 1428, and a telemetry subsystem 1430. The internal bus is an address/data bus that transfers information between the various components described herein. The hard drive 1408 may store operational programs as well as data, such as waveform templates and detection thresholds.
The CPU 1402 typically includes a microprocessor, a micro-controller, or equivalent control circuitry, and may interface with the CNS 110. The CPU 1402 may include RAM or ROM memory, logic and timing circuitry, state machine circuitry, and I/O circuitry to interface with the CNS 110. The display 1422 (e.g., may be connected to the video display 1432). The touch screen 1424 may display graphic information relating to the CNS 110. The display 1422 displays various information related to the processes described herein. The touch screen 1424 accepts a user's touch input 1434 when selections are made. The keyboard 1426 (e.g., a typewriter keyboard 1436) allows the user to enter data to the displayed fields, as well as interface with the telemetry subsystem 1430. Furthermore, custom keys 1428 turn on/off 1438 (e.g., EVVI) the ECU 1400. The printer 1412 prints copies of reports 1440 for a physician to review or to be placed in a patient file, and speaker 1410 provides an audible warning (e.g., sounds and tones 1442) to the user. The parallel I/O circuit 1418 interfaces with a parallel port 1444. The serial I/O circuit 1420 interfaces with a serial port 1446. The floppy drive 1416 accepts diskettes 1448. Optionally, the floppy drive 1416 may include a USB port or other interface capable of communicating with a USB device such as a memory stick. The CD-ROM drive 1414 accepts CD ROMs 1450.
The CPU 1402 is configured to analyze PS motion data collected by the CNS 110 for a plurality of map points to determine a point cloud data set of the map points stored on data storage (e.g., ROM 1404, RAM 1406, hard drive 1408). The CPU 1402 includes a segmentation analysis circuit module 1464 that is configured to automatically assign segment identifiers (IDs), which are associated with segments of the heart separated by circumferential and longitudinal boundaries, to the map points based on a position of the map point from the point cloud data set. The CPU 1402 also includes a position waveform generation circuit module 1462 that may generate position waveforms of selected reference locations based a coordinate system (e.g., Cartesian coordinate system, cylindrical coordinate system, or the like) as described herein. The CPU 1402 also includes a strain analysis circuit module 1468 that may determine the strain (e.g., linear or longitudinal strain, radial strain, circumferential strain), as explained herein.
One or more of the operations described above in connection with the methods (e.g. the method 200, the method 1000) may be performed and/or executed using one or more processors. The different devices in the systems described herein may represent one or more processors, and two or more of these devices may include at least one of the same processors. In one embodiment, the one or more operations described herein in connection to the method 200 and/or the method 1000 may represent actions performed when one or more processors (e.g., of the devices described herein) are hardwired to perform the methods or portions of the methods described herein, and/or when the processors (e.g., of the devices described herein) operate according to one or more software programs that are written by one or more persons of ordinary skill in the art to perform the operations described in connection with the methods.
1. A method for determining the mechanical activation of a region of interest, the method comprising:
obtaining, using one or more processors, map point data associated with map points on a region of interest, the map point data representing at least one of motion or electrical activity data at the map points;
assigning, using the one or more processors, the map points to non-overlapping geometric areas within the region of interest;
calculating, using the one or more processors, an area strain for each geometric area based on the map point data for the map points of the associated geometric area;
analyzing, using the one or more processors, a characteristic of the geometric areas to distinguish normal geometric areas from abnormal geometric areas based on whether the characteristic exhibits abnormal traits;
excluding, using the one or more processors, map point data associated with the abnormal geometric area;
determining, using the one or more processors, a mechanical activation time for the region of interest based on the map points for the normal geometric areas that were not excluded; and
displaying the mechanical activation time for the region of interest.
2. The method of claim 1, wherein the abnormal areas are at least one of a hypokinetic area or dyskinetic area.
3. The method of claim 1, wherein the assigning operation generates the geometric areas as nonoverlapping triangular areas from at least a portion of the map points, where vertices of the triangular areas correspond to the map points.
4. The method of claim 1, wherein the geometric areas that are separate and distinct from the abnormal geometric areas represent valid geometric areas utilized when determining the mechanical activation time.
5. The method of claim 1, wherein the excluding operation marks the abnormal geometric areas as invalid geometric areas.
6. The method of claim 1, wherein the excluding operation excludes map points based on at least one of a morphology of the geometric area, a presence of sharp spikes in the area strain associated with the corresponding geometric area, a size of the geometric area, a variability of cycle length within the geometric area or variation in electrical tissue characteristics associated with the geometric area.
7. The method of claim 1, wherein the calculating operation includes calculating cycle lengths associated with map points corresponding to vertices of a first geometric area, calculating distances between the vertices, determining an area of the geometric area based on the distances between the map points corresponding to the vertices, and determining the area strain of the geometric area over at least one cardiac cycle.
a data storage configured to store map point data collected by an intravascular mapping tool configured to be inserted into at least one of the endocardial or epicardial space, the mapping tool maneuvered to select locations proximate to surfaces of the heart, while collecting the map point data at map points to form a point cloud data set during at least one cardiac cycle, the map point data representing at least one of motion or electrical activity data at the map points; and
assign the map points to non-overlapping geometric areas within the region of interest;
calculate an area strain for each geometric area based on the map point data for the map points of the associated geometric area;
analyze a characteristic of the geometric areas to distinguish normal geometric areas from abnormal geometric areas based on whether the characteristic exhibits abnormal traits;
exclude the map point data associated with the abnormal geometric area;
determine a mechanical activation time for the region of interest based on the map points for the normal geometric areas that were not excluded and display the mechanical activation for the region of interest.
9. The system of claim 8, wherein the abnormal areas are at least one of a hypokinetic area or dyskinetic area.
10. The system of claim 8, wherein the processor uses a triangulation technique algorithm to generate the geometric areas as nonoverlapping triangular areas from at least a portion of the map points, where vertices of the triangular areas correspond to the map points.
11. The system of claim 8, wherein the geometric areas that are separate and distinct from, the abnormal geometric areas represent valid geometric areas utilized when determining the mechanical activation time.
12. The system of claim 8, wherein the processor marks the abnormal geometric areas as invalid geometric areas.
13. The system of claim 8, wherein the processor excludes map points based on at least one of a morphology of the geometric area, a presence of sharp spikes in the area strain associated with the corresponding geometric area, a size of the geometric area, a variability of cycle length within the geometric area or variation in electrical tissue characteristics associated with the geometric area.
14. The system of claim 8, wherein the processor calculates cycle lengths associated with map points corresponding to vertices of a first geometric area, calculating distances between the vertices, determining an area of the geometric area based on the distances between the map points corresponding to the vertices, and determining the area strain of the geometric area over at least one cardiac cycle.
US14/703,764 2014-05-05 2015-05-04 Methods and systems to calculate time of mechanical activation using characterization motion data area strains Active 2036-08-09 US9980665B2 (en)
US201461988779P true 2014-05-05 2014-05-05
US14/703,764 US9980665B2 (en) 2014-05-05 2015-05-04 Methods and systems to calculate time of mechanical activation using characterization motion data area strains
US20150313482A1 US20150313482A1 (en) 2015-11-05
US9980665B2 true US9980665B2 (en) 2018-05-29
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US14/703,764 Active 2036-08-09 US9980665B2 (en) 2014-05-05 2015-05-04 Methods and systems to calculate time of mechanical activation using characterization motion data area strains
US (1) US9980665B2 (en)
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