Patent Publication Number: US-2023135309-A1

Title: Method and device for monitoring a flow of a fluid in a vessel

Description:
TECHNICAL FIELD 
     The various aspects and variations thereof relate to tracking of flow of a fluid through a vessel of a living being. 
     BACKGROUND 
     For determining various parameters of a cardiovascular system, like fractional flow reserve, flow velocity of blood in a coronary vessel may be required. The flow velocity may be determined as described in “ TIMI Frame Count ” by C. Michael Gibson e.a. as published in Circulation 1996; 93: 879-888. 
     SUMMARY 
     It is preferred to provide an efficient basis for tracking of a bolus of contrast dye in a vessel in a body and in a coronary vessel in particular. To this end, in a first aspect, a method of monitoring a flow of a fluid in a vessel of a body of a living being is provided. The method comprises obtaining a first image data set representing the vessel filled with a first fluid, the first image data set comprising at least one first image frame and the first fluid contrasting with matter surrounding the vessel and obtaining a second image data set representing the vessel substantially void of the first fluid, the second image data set comprising at least one second image frame. Based on the first image data set and the second image set, an estimated location of the vessel in the second image set is estimated; and monitoring presence in the second data set of contrasting image data at the estimated location of the vessel is monitored. 
     A vessel filled with contrast dye is well visible using imaging technology like computer tomography and x-ray imaging. With image data of the vessel acquired while the vessel is filled provides data on geometry and location of the vessel. Based thereon, an estimate of at least one of geometry and location of the vessel in the second image data set may be provided. Subsequently, while tracking progress of contrast dye in the second image data set by detecting image pixels with contrasting image data for one or more image may only, firstly or primarily be done at and, optionally, around, the estimated location and geometry of one or more images of the second image data set. This means that not all pixel of images in the second image data set may have to be analysed for tracking progress of the contrast dye through the vessel. 
     In a variation, the first data set comprises a multitude of first image frames, the first image frames having been acquired consecutively in time; and the second data set comprises a multitude of second image frames, the second image frames having been acquired consecutively in time. In this variation, the method further comprises tracking, in the first data set, the vessel over time and estimating, based on the tracking, over time, a location of the vessel in the second frames of the second data set. The estimation of at least one of the geometry and location of the vessel may be done statically and this variation relates to tracking of at least one of the geometry and location over time. In particular a coronary vessel moves and changes in shape over the course of a heartbeat, for which reason it may be preferred to track the vessel over time and estimate geometry and/or location over time. 
     In another variation, the first data set is acquired over a first time interval relative to a heartbeat sequence, the second data set is acquired over a second time interval relative to the heartbeat sequence and the first time interval and the second time interval cover at least one equivalent part of the heartbeat sequence. With both the first image data set and the second image data set comprising equivalent parts or equivalent phases of a hearts, both the image data sets may be aligned over time, such that at least one of location and geometry of the vessel may for example be estimated in an image of the second set, based on an image in the first in set at an equivalent moment in a heartbeat sequence, at which moment it is probable that at least one of geometry and location of the vessel is substantially the same in the second set as it is depicted in the first set. 
     In a further variation, the first timer interval and the second timer interval cover at least one heartbeat sequence. An advantage thereof is that the image sets cover a full sequence, providing generally all possible shapes and locations of the vessel, as possibly modified by the heartbeat. 
     Again another variation comprises aligning the first image data set and the second image data set based on heartbeat sequence data associated with the first image data set and the second image data set, associating frames in the first image data set and the second image data set with a particular phase in the heartbeat sequence and estimating, over time, estimated locations of the vessel in the second frames of the second image data set based on locations of the vessel in the first frames of the first image data set having substantially the same phase in the heartbeat sequence associated therewith as with the second frames. This variation is a practical implementation of the previous ones, reducing complexity and increasing accuracy of the estimation. 
     In a further variation, the first image data set and the second image data set have electrocardiogram data as heartbeat sequence data associated therewith. An advantage is that an ECG provides easy to process and well-known data on phases in a heartbeat sequence. 
     In yet a further variation, heartbeat sequence data is derived from image frame data in at least one of the first image data set and the second image data set. For example, from a shape of a coronary vessel, a phase in a heartbeat sequence may be estimated, as such shape varies in a periodic way over the sequence of a heartbeat. The moment in the sequence may be obtained by (directly) comparing the obtained image to one or more reference images. Additionally or alternatively, the applicable image may be provided to a trained neural network or other artificial intelligence capable of at least one of image recognition and image classification. 
     In yet another variation, the tracking of the vessel over time comprises identifying a multitude of points of interest distributed on a representation of the vessel in the first image frames and tracking locations of the points of interest in the applicable image over time. 
     Again a further variation comprises reconstructing the vessel geometry over time. Whereas this variation may consume a considerable amount of memory and processing power, it may provide more accuracy. 
     In yet again a further variation, the reconstructing comprises determining a centreline of the vessel in the image data. By representing the vessel by means of a centreline only, an efficient representation may be provided. Alternatively, the centreline may be used as a basis for a more advanced or more sophisticated representation of the vessel. 
     Another variation further comprises reconstructing a vessel geometry based on the first image data set and estimating a location of the vessel in the second image set based on the first image data set and the reconstructed vessel geometry. With a vessel geometry available, estimation of the vessel location and locations of multiple points of the vessel geometry in particular, only a few points of the vessel location in the second image data set need to be identified, for example estimated, upon which the vessel geometry may be fit to those locations. As a result, the full location of the full geometry is efficiently estimated. 
     In yet another variation, the first image set comprises a first image subset comprising at least a first image acquired under a first angle relative to the living being; and a second image subset comprising at least a second image acquired under a second angle relative to the living being; in this variation, the reconstructed vessel geometry is a three-dimensional geometry. With a three-dimensional representation, more accuracy may be provided. 
     In yet again another variation, the second image set comprises a first image subset comprises at least a first image acquired under the first angle relative to the living being; and a second image subset comprises at least a second image acquired under the second angle relative to the living being; in this variation, the estimated location of the vessel in the second image set is a three-dimensional location. With a three-dimensional representation of the location, more accuracy may be provided. 
     A further variation further comprises determining a first length of the vessel as depicted by the first image subset, determining a second length of the vessel as depicted by the second image subset, determining a natural length of the reconstructed vessel, selecting the first image subset if the first length is closer to the natural length or selecting the second image subset if the second length is closer to the natural length, estimating the location of the vessel in the second image data set based on the subset of the first dataset of which the length is closest to the natural length. A longer length enables analysis with a higher resolution. 
     In another variation, the location in the second image data set is determined based on the image subset corresponding to the image subset of the first image data set depicting a length closest to the natural length. This may also provide an improved resolution. 
     In yet a further implementation, the vessel is filling with the first fluid while the second dataset is acquired. This variation allows for determining transit time of a front of a bolus with contrast dye. With this data, transit velocity of a body fluid through the vessel, for example blood, may be determined. In a coronary vessel, this transit velocity or flow rate may be used for determining fractional flow reserve of a vessel, or a related or derivative value of the fractional flow reserve. 
     In again another variation, the second image data set is acquired prior in time relative to the acquiring the first image data set. This variation requires contrast dye as an example of the first fluid or first liquid to be inserted in the vessel only once for the analysis in accordance with the first aspect. 
     The first aspect, with all its variations indicated above and below, may be employed in a method of determining vessel fluid flow velocity of a fluid in a vessel segment of a body of a human or another mammal. The method comprises obtaining a natural length model of the vessel representing a length of the length of the vessel in accordance with the method according to any variation of the first aspect, obtaining a two-dimensional model of the vessel segment based on the first image dataset, dividing the two-dimensional model in vessel sections, receiving the second dataset comprising a multitude of second image frames, the second image frames having been acquired consecutively in time, based on the images of the second dataset, assigning, for each image of the set, at least one intensity value to each vessel section, identifying, in a first image related to a first moment in time, a first vessel section, based on an intensity criterion, identifying, in a second image related to a second moment in time, a second vessel section, based on the intensity criterion, the second moment in time being later than the first moment in time and the second vessel section being distal to the first vessel section, obtaining a propagation length by relating the first vessel section and the second vessel section to the natural length and determining a vessel fluid flow velocity based on the propagation length, and a difference between the first moment in time and the second moment in time. 
     A second aspect provides a computer programme product comprising computer executable code that cause a computer, when the instructions are loaded in a memory connected to a processing unit comprised by the computer, cause the computer to execute the method according to the first aspect or any of the variations discussed above and below. 
     A third aspect provides a non-transitional medium having stored thereon the computer programme product according to the second aspect. 
     A fourth aspect provides a device for monitoring a flow of a fluid in a vessel of a body of a living being. The device comprises an input module arranged to obtain a first image data set representing the vessel filled with a first fluid, the first image data set comprising at least one first image frame and the first fluid contrasting with matter surrounding the vessel; and obtain a second image data set representing the vessel substantially void of the first fluid, the second image data set comprising at least one second image frame; and a processing unit arranged to: estimate, based on the first image data set and the second image set, an estimated location of the vessel in the second image set; and monitor presence in the second image data set of contrasting image data at the estimated location of the vessel. As such, the fourth aspect also relates to a device for executing the method according to the first aspect or any variation thereof. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The various aspects and implementations thereof will now be discussed in further detail in conjunction with drawings. In the drawings: 
         FIG.  1   : shows a system for image acquisition and processing; 
         FIG.  2   : shows a flowchart; and 
         FIG.  3   : shows two images of a cardiovascular structure. 
     
    
    
     DETAILED DESCRIPTION 
       FIG.  1    shows an electronic medical data acquisition and processing system  100  as an example of the second aspect. The system  100  or parts thereof may be found in a cardiac catheterisation laboratory of a clinic or a hospital. The system  100  comprises an X-ray image acquisition module comprising a first X-ray source  126  and a second X-ray source  128 , a first X-ray detector  122  arranged to receive X-ray data from the first X-ray source  126  and a second X-ray sensor  124  arranged to receive X-ray data from the second X-ray source  128 . The first X-ray source  126 , the second X-ray sensor  124 , the first X-ray detector  122  and the second X-ray sensor  124  are arranged to obtain images of a cardiovascular structure  180  under an angle relative to one another. The angle is preferably between 25° and 45°, more preferably between 30° and 40°. 
     The first X-ray detector  122  and the second X-ray detector  124  are connected to data acquisition module  116  of an electronic computing device  110 . The electronic computing device further comprises a processing unit  112 , a storage module  114  and a peripherals I/O controller  118 . The processing unit  112 , which may be implemented as a microprocessor, microcontroller or other electronic data processing device, is arranged to control the various part of the electronic computing device  110  and the system  100  and arranged to execute the method according to the first aspect and implementations thereof. 
     The storage module  114  is arranged for storing data thereon, for example acquired by the computing device  110  from the various other parts of the system  100 , either directly or after processing by the processing unit  112 . The storage unit  114 , as at least partially implemented as a non-transitional storage medium, is further arranged for storing computer executable code which allow the processing unit  112  to execute the method according to the first aspect and implementations thereof. 
     The system  100  further comprises, in this implementation as an option, a heartbeat data acquisition module  130  comprising an ECG acquisition contact pad  132 , a control unit  134  comprising a pulse sensor  136  and a clock unit  138 . The heartbeat data acquisition module  130  is arranged to obtain data related to heartbeat and heartbeat phase data in particular as a function of time. The pulse sensor  136  may be a photoplethysmography unit or another sensor arranged to determine pulse of a person. The control unit  134  is arranged to relate the data acquired by means of the ECG acquisition contact pad  132  and the pulse sensor  136  to time, for example by adding a timestamp. 
     The system  100  comprises a pressure tip  148  as another blood pressure measurement module, which corresponds to the intracoronary distal pressure. The pressure tip  148 , which is connected to a coronary wire, transmits the pressure to the data acquisition module  116 , from a coronary artery  182  of the cardiovascular structure  180  as an example of a coronary vessel or blood vessel in general via a catheter  146  inserted in a body of a mammal, like a human being. Additionally, the tip of the coronary catheter  146 , placed into the ostium of the coronary artery under scrutiny  182 , senses the proximal pressure into the vessel, which corresponds to the aortic pressure. Furthermore, the catheter  146  may be used to insert contrast dye  150  in the coronary artery  182  or another vessel of a body. 
     The peripherals I/O controller  118  is arranged to connect the computing device  110  and the various components thereof to input device like a keyboard  142  or a touch screen for receiving data like user input. The peripherals I/O controller  118  is arranged to connect the computing device  110  and the various components thereof to output devices like an electronic display  144  and other output devices arranged to provide a user with data on processed or unprocessed data received by the computing device  110 . 
     As shown in  FIG.  1   , the catheter  146  and the pressure wire  148  are inserted in the coronary artery  182 . In the coronary artery  182 , narrowings  190  are present. The stenotic areas result in narrowing in the various vessels of the coronary vascular structure  180 , which, in turn results in pressure drops at the various stenotic areas. Subsequently, the pressure drops result in reduced perfusion of myocardial tissues, which leads to reduced physical condition of the person under scrutiny. The cardiovascular structure  180  shown by  FIG.  1    may be a hypothetical structure and is not necessarily a representation of an actual anatomical structure. 
     The further functionality of the system  100  and parts thereof discussed above will be further elucidated in conjunction with a flowchart  200  depicted by  FIG.  2   . The procedure depicted by the flowchart  200  is executed by the system  100  and the electronic computing device  110  in particular, controlled by the processing unit  112 . To provide this functionality, the processing unit  112  may be programmed by means of a computer programme product comprising computer executable code. The computer programme product may be stored on the storage unit  114  as an electronic memory, which may be a non-transitory memory. The various parts of the flowchart  200  are briefly summarised below.
           202  start of the procedure     204  acquire first subset of second image data set     206  acquire second subset of second image data set     208  acquire first subset of first image data set     210  acquire second subset of first image data set     212  obtain heartbeat phase data     214  link image data to heartbeat phase data     216  identify vessel in first subset of first image data set     218  identify vessel in second subset of first image data set     220  obtain sensor difference angle between first and second subsets     222  reconstruct three-dimensional vessel geometry     224  determine three-dimensional vessel length     226  determine two-dimensional vessel length first subset     228  determine two-dimensional vessel length second subset     230  link vessel geometry to time     232  link vessel geometry to a location in an image frame in the first data set     234  associate frames of the second data set to frame of the first data set (based on HB)     236  link reconstructed vessel geometry and location to image data of the second image data set     238  monitor image data in the second data set     238  end procedure       

     The procedure starts in a terminator  202  and continues to step  204  in which a first subset of a second image data set is acquired. In step  204 , a second subset of image of the second image data set is acquired. The second image data set is acquired while the contrast dye  150  is provided to the coronary artery  182 . As such, the second image data set is acquired while the contrast dye  150  is gradually filling up the coronary artery  182 . The first subset of the second image data set is acquired by means of the first X-ray source  126  and the first X-ray sensor  122  and the second subset of the second image data set is acquired by means of the second X-ray source  128  and the second X-ray sensor  124 . The first subset and the second subset of the second image data set preferably comprise a multitude of X-ray image frames, acquired at regular intervals in time, as the contrast dye  150  progresses in the coronary artery  182 . 
     In one embodiment, the first X-ray sensor  122  and the second X-ray sensor  124  acquire data at the same moment, for example by acquiring images at substantially the same moment in time. As such, the first subset and the second subset of the second dataset may be streams of image frames. 
     In step  208 , a first subset of a first image dataset is acquired and in step  210 , a second subset of the first image dataset is acquired. 
     The first image data set is acquired while the contrast dye  150  is present through the full length of the coronary artery  182 . The second image data set may be acquired prior to the first image data set, allowing second data to be acquired while the coronary artery  182  gradually fills with the contrast dye and to subsequently allow first data, for the first image data set, to be acquired while the coronary artery  182  is substantially full with the contrast dye  150 . Working the other way around is possible as well, but would require the coronary artery  182  to be flushed after acquiring the first image data set to get the contrast dye  150  out of the coronary artery  182 . The flushing would be required to allow acquisition of the second image data set while the contrast dye  150  is gradually filling the coronary artery  182 . 
     The first subset of the first image data set is acquired by means of the first X-ray source  126  and the first X-ray sensor  122  and the second subset of the first image data set is acquired by means of the second X-ray source  128  and the second X-ray sensor  124 . The first subset and the second subset of the first image data set preferably comprise a multitude of X-ray image frames, acquired at regular intervals in time, as the contrast dye  150  progresses in the coronary artery  182 . 
     In one embodiment, the first X-ray sensor  122  and the second X-ray sensor  124  acquire data at the same moment, for example by acquiring images at substantially the same moment in time. As such, the first subset and the second subset of the first dataset may be streams of image frames. 
     In certain embodiment, no two X-ray sources and no two X-ray sensors are present. In such case, the first subsets and the second subsets are acquired at different intervals in time. 
     In step  212 , heartbeat data of the person under scrutiny is acquired, in this example in parallel to acquisition of the image data. The heartbeat data is acquired by means of the heartbeat data acquisition module  130 . The heartbeat data thus acquired is lined up to the image data in step  214 . The linking of data may be established in various ways. One option is to assign a momentary ECG value to an image frame acquired at the same moment. Another options is to provide ECG data in a metafile, provided with time data and to provide the image frames of the image data sets with time data such that it matches time data of the ECG data. Additionally or alternatively to ECG data, also photoplethysmography data may be used. 
     In step  216 , the coronary artery  182  is identified in the first subset of the first image data set.  FIG.  3    shows a first image frame  300 ′ and a second image frame  300 ″. The first image frame  300 ′ is part of the first subset of the first image data set and the second image frame  300 ″ is part of the second subset of the second image data set. The coronary artery  182  is in the first image frame  300 ′ visible as artery image  182 ′ and in the second image frame  300 ″ visible as artery image  182 ″. As such, the coronary artery  182  is identified in the first subset of the first image data set and in the second subset of the first image data set, in step  218 . 
     The coronary artery  182  may be defined in one frame of the first subset, but also from frame to frame, thus tracking the coronary artery  182  from frame to frame to obtain the geometry and location of the coronary artery  182  over time. With such tracking, the full geometry of the coronary artery  182  may be followed from image to image. In another implementation, specific points of the coronary artery  182  or locations on a centreline may be followed from frame to frame. The data acquired by following movements of the points of interest from frame to frame may subsequently be used to reconstruct the coronary artery geometry in one or more frames. 
     In step  220 , the data acquisition angle between the first X-ray detector  122  and the second X-ray sensor  124  is obtained. Using the image data of the coronary artery  182  and the data acquisition angle, the processing unit  112  reconstructs a three-dimensional vessel geometry of the coronary artery  182 . In one example, the centreline of the coronary artery  182  is reconstructed in an electronic data file. Additionally or alternatively, a full three-dimensional structure of the coronary artery  182  is reconstructed. 
     In step  224 , the length of the thus reconstructed coronary artery  182  is determined. In one example, the length is determined from the aorta to the final point of the vessel. In step  226 , the length of the vessel as depicted by first subset of the first image dataset is determined, for example as depicted by the first image frame  300 ′. And in step  228 , the length of the vessel as depicted by second subset of the first image dataset is determined, for example as depicted by the second image frame  300 ″. The length of the three-dimensional reconstruction is generally the longest, as the natural vessel length. 
     In step  230 , the vessel geometry is linked to timing data. With series of two images acquired at the same moment, from different angles, over a period, a series of three-dimensional reconstructions may be provided. And with timing data as discussed above, each reconstruction may be linked to a moment in time and/or a specific part of a heartbeat cycle. Additionally or alternatively, geometry characteristics like centreline of the vessel identified in the first subset and the second subset of the first set of image data may be linked to timing data. 
     In step  232 , the vessel geometry thus reconstructed—once or multiple times over time—is linked to locations in the image frames of the first subset and the second subset of the first set of image data. In one example, the location of the centreline is associated with the image frames; additionally or alternatively, the full three-dimensional geometry is linked to the image frames. 
     In step  234 , frames of the second set of image data are linked to frames of the first set of image data. The linking is preferably done based on timing data. In particular, frames of the second set of image data are linked to frames of the first set of image data using data related to a phase of a heartbeat. Determining a phase of the heartbeat may be based on the momentary ECG value and, optionally, on analysing the ECG value over time. As such, the P-wave, Q-wave, R-wave and other characteristic points of the ECG data in timing data specifically acquired with the first set of image data and the characteristic ECG data point acquired with the second set of image data may be used to associate particular frames with particular moment or phases in a heartbeat cycle. 
     Based on the ECG data characteristics, an image frame of the first set of image data may be linked to an image from the second set of image data. More in particular, an image frame of the first subset of the first set of image data may be linked to an image from of the first subset of the second set of image data and an image frame of the second subset of the first set of image data may be linked to an image from of the second subset of the second set of image data. For this matching of frames, it is useful that both the first set of image data and the second set of image data are acquired during the same phases of a heartbeat or overlapping parts of the sequence. It may be even more useful if the acquisition periods for both sets cover at least one heartbeat sequence or more. 
     Whereas ECG data may be conveniently acquired using relatively common equipment, the heartbeat phase data may be acquired in other ways. In one example, pulse data may be obtained using an optical pulse meter. In another example, the heartbeat phase data may be obtained by analysing image data of the second set of image data. The shape of the location of the coronary artery  182 , filled with contrast dye, varies of time during the heartbeat sequence. Hence, from at least one of the shape and location of the coronary artery  182  in frames of the second set of image data, a phase in the heartbeat sequence may be determined. This determination may be executed by means of a model, by comparing image data acquired to stored image data, by means of a trained neural network, other, or a combination thereof. 
     Subsequently, with the geometry of the coronary artery  281  for frames of the first set of image data known and location of the coronary artery  281  in the frames of the first set of image data known and frames of the first set of image data associated with frames of the second set of image data, geometry and location of the coronary artery  281  may be reconstructed in frames of the second set of image data, based on known data. The geometry and location of the coronary artery  182  may be reconstructed in the first subset and the second subset of the second set of image data or in only one of them. 
     To make efficient use of processing power, the geometry and location of the coronary artery  182  is reconstructed only in the first subset or second subset of the second set of image data. In step  224 , step  226  and step  228 , lengths of various images of the coronary artery  182  have been determined. In one implementation, the geometry and location of the coronary artery  182  is reconstructed only in the set that depicts the coronary artery  182  with a length closest to that of the lengths of the three-dimensional reconstruction of the coronary artery  182 . In one example, this may be the subset that depicts the coronary artery having the longest length. The lengths used for this may be lengths of single—corresponding—frames from the first subset and the second subset. Alternatively, as the length of the coronary artery  182  may vary during a heartbeat, a mean or median value of the lengths may be used for this step. 
     As the coronary artery  281  is in the frames of the second set of image data not filled with contrast dye  150  or at least not fully filled, the coronary artery is not visible in the frames of the second set of image data and the reconstruction yields a ghost image of the coronary artery  281 . It is noted that the location of the coronary artery  182  thus reconstructed in the frames of the second set of image data may not necessarily be the actual location of the coronary artery  182 , but is rather an estimation of the location. 
     With the geometry and location of the coronary artery estimated in at least one of the first subset and second subset of the second set of image data available, the procedure proceeds to step  238 , in which image data at and optionally near the estimated geometry and location of the coronary artery is monitored for change of intensity. For example, change of contrast may be evaluated at a pre-determined distance from a centreline of the reconstructed vessel. If the full vessel is reconstructed or a volumetric, three dimensional representation of the vessel is reconstructed or a two-dimensional reconstruction with a surface in a two dimensional space is provided, an area, volume, vessel width or other entity is monitored at a monitoring distance from the vessel, which monitoring distance is based on the volume or surface of the vessel at a particular location. The relation between the monitoring distance and the area, width or volume of the reconstructed vessel may for example be linear. 
     As contrast dye proceeds from a proximal point of the coronary artery  182 —generally the aorta—to a distal point of the coronary artery  182 —generally the endpoint —, the contrast of the image data changes along the estimated centreline of the coronary artery  182  in the frames of the second set of image data. In one example, only frames of the first subset are monitored, alternatively or additionally, frames of the second subset of the second set of image data are monitored. In one example, the subset is monitored in which frames depicted the coronary artery with the longest length and/or the length closest to the natural length of the coronary artery  182 . 
     With the monitoring of change of intensity from frame to frame, over time, progress of the contrast dye in the coronary vessel  182  may be monitored. Subsequently, the velocity of fluid—contrast dye as well as blood—may be determined. This may, for example, be executed as discussed in patent application PCT/NL2021/050635.