RELATED APPLICATIONS

This application is a 35 U.S.C. § 371 national stage application of PCT Application No. PCT/EP2018/084640, filed on Dec. 12, 2018, which claims priority from Great Britain Patent Application No. 1720789.5 filed on Dec. 13, 2017, the contents of which are incorporated herein by reference in their entireties. The above-referenced PCT International Application was published in the English language as International Publication No. WO 2019/115650 A1 on Jun. 20, 2019.

TECHNICAL FIELD

The present disclosure relates to a method and apparatus for analysing images. More particularly, but not exclusively, the present disclosure relates to a system and method for scoring motion of a heart wall.

BACKGROUND

Two-dimensional (2D) echocardiography is an imaging technique through which the motion of the heart can be assessed under different conditions, for example resting or stress conditions. The analysis may be performed under other conditions including, for example, an intermediate stress stage and/or a recovery stage. This can highlight areas of the heart that are hypo- or dysfunctional, and can thus identify patients in which medical intervention may be necessary. A typical model of the left ventricle comprises sixteen (16) segments which are visible using different 2D images of the heart. Other models of the left ventricle may, for example, comprise seventeen (17) segments. The apical inferior segment, mid inferior segment, basal inferior segment, apical anterior segment, mid anterior segment and basal anterior segment are visible in an apical two chamber image. The apical septum segment, mid septum segment, basal septum segment, apical lateral segment, mid lateral segment and basal lateral segment are visible in an apical four chamber image. The anteroseptum segment, inferoseptum segment, mid inferior segment, mid anterior segment, anterolateral segment and inferolateral segment are visible in a parasternal short axis image. The apical lateral segment, the mid inferolateral segment, basal inferolateral segment, the apical septum segment, the mid septum segment, and the basal septum segment are visible in an apical three chamber image (or parasternal long axis image). The behaviour of each segment can be viewed in different sections of the left ventricle. The motion of each segment of the myocardium under different conditions (such as resting and stress conditions) is currently determined by interpretation of the 2D echocardiography data by an expert cardiologist. This is performed in a categorical manner. For example, each section of the myocardial wall may be classified as having one of the following reference wall motion scores: normal (“1”), hypokinetic (“2”), akinetic (“3”), dyskinetic (“4”), and unable to score (“X”). Other classifications may be used, for example defining five (5) or seven (7) discrete scores for each segment. The known techniques rely on subjective classification and may prove a time consuming exercise.

It has been recognised that image quantification tools need to allow for the following: (i) changing underlying disease pathophysiology over time; (ii) disease pathology variations with geographical location and changing nature of the patient population being referred for the test; and (iii) the changing understanding of what is defined as disease or what is disease causing.

At least in certain embodiments, the present invention seeks to provide an improved method and apparatus for analysing images.

SUMMARY OF THE INVENTION

Aspects of the present invention relate to a system for scoring motion of a heart wall, a method of scoring motion of a heart wall, and a non-transitory computer-readable medium as claimed in the appended claims.

According to an aspect of the present invention there is provided a system for scoring motion of a heart wall, the system comprising:an imaging system operable to acquire a first image of the heart wall at a first time and a second image of the heart wall at a second time;a processor configured to:identify a first set of contour data in the first image;identify a second set of contour data in the second image;in dependence on the first and second sets of contour data, define at least one element representing a cardiac cyclic change in a section of the heart wall;analyse each element to generate at least one metric; andcompare the at least one metric with a reference data model to score the motion of the corresponding section of the heart wall.

At least in certain embodiments, the system described herein may partially or completely automate scoring of the wall motion in dependence on the first and second images. Furthermore, the system described herein may implement a scoring system which is continuous, rather than a categorical model. At least in certain embodiments, the motion of the heart wall may be scored on a substantially continuous scale. The scoring may be performed in dependence on one metric or in dependence on a plurality of metrics.

Each element represents a change in a cardiac cyclic parameter of a section of the heart wall. The elements are each defined in at least two dimensions. In a variant, the elements could each be defined in three dimensions.

The at least one element represents a cardiac cyclic change of a section of the heart wall. The heart wall may be modelled by a plurality of segments. Each element may represent the cardiac cyclic change in one of said segments. Alternatively, each element may represent the cardiac cyclic change in a portion of one of said segments (i.e. in a subsegment). It will be understood that the elements may be unrelated to the segments of a conventional model. For example, the elements may subdivide the heart wall into eight (8) regions.

The system may score motion of a ventricle of the heart. For example, the system may score motion of a left ventricle of the heart. As described herein, the left ventricle of the heart may be modelled by sixteen (16) segments. Each element may represent the cardiac cyclic change in one of the segments of an internal wall of the left ventricle. Alternatively, each element may represent the cardiac cyclic change in a portion of one of said segments (i.e. in a subsegment) of an internal wall of the left ventricle.

The reference data model may be predefined. The reference data model may be generated in dependence on analysis of historic data, for example derived from analysis of a plurality of images acquired for multiple individuals. The at least one metric generated for each element may be compared with the reference data model for a corresponding section of the heart wall. The reference data model may be generated for each segment of a model of the heart wall. The at least one metric may be compared with the reference data model for a corresponding segment of the heart wall.

The first set of contour data may comprise a plurality of first contour points. The first contour points may be connected to each other to form a first contour. The first contour points may be connected to each other by a straight line and/or a curved line. The first contour may comprise a first continuous curve.

The second set of contour data may comprise a plurality of second contour points. The second contour points may be connected to each other to form a second contour. The second contour points may be connected to each other by a straight line and/or a curved line. The second contour may comprise a second continuous curve.

The first set of contour data may be identified in dependence on user inputs, for example user inputs to specify contour points in the first and second images. Alternatively, the processor may be configured to analyse the first and second images to identify the first and second sets of contour data. The processor may, for example, utilise image processing techniques to identify the first and second sets of contour data. The image processing techniques may, for example, comprise motion segmentation to identify the first and second contour points; and/or boundary detection techniques to identify the first and second contour points and/or the first and second contours.

The processor may be configured to identify a plurality of pairs of contour points. Each pair of contour points may relate to a corresponding feature in the first and second sets of contour data. Each pair may consist of corresponding first and second contour points. The first and second contour points may relate to a single feature present in the first and second sets of contour data.

Each element may comprise at least first and second pairs of contour points. The contour points making up each pair may define vertices of the element.

The analysis of each element comprises determining a distance between the contour points in each pair and calculating a mean distance between the contour points for each element. The mean distance of each element may be normalised to a total perimeter of the first or second sets of contour data.

Each element may comprise opposing first and second sides corresponding to motion trajectories of the contour points.

The analysis of each element may comprise determining an area of the element. The area may correspond to an area enclosed by the first and second sets of contour data. The area may, for example, correspond to an area between end-diastolic and end-systolic contours. The determined area may be normalised. For example, the area of each element may be normalised to the total area of the end-diastolic data points.

The analysis of each element may comprise determining a rectangularity of each element. The rectangularity of each element may be calculated as the ratio between the area of each element and the area of its minimum bounding rectangle.

The analysis of each element may comprise determining a solidity of each element. A solidity of each element may be calculated as the ratio between the element's area and the area of its convex hull.

The processor may be configured to perform scoring on a continuous scale. The processor may be configured to output a score to classify or grade the heart wall motion. Alternatively, or in addition, the processor may be configured to output an RGB value to represent the scoring as a colour.

The imaging system may be configured to generate three-dimensional images. The first and second images may be three-dimensional images. The at least one element may be defined in three dimensions. The imaging system may be configured to generate two-dimensional images. The first and second images may comprise two-dimensional images of the heart wall. The at least one element may be defined in two dimensions.

Each element may comprise an irregular shape, for example comprising one or more curved sides. Alternatively, each element may comprise a polygon.

The processor may be configured to score the motion of the heart wall during at least one condition. The processor may be configured to score the motion of the heart wall during a plurality of conditions. The scoring may be performed during one or more of the following set: a rest condition, a stress condition, an intermediate stress condition, a recovery condition and so on. The imaging system may be operable to acquire first and second images of the heart wall under stress conditions. The imaging system may be operable to acquire first and second images of the heart wall under rest conditions. The scoring may be performed in respect of the images acquired under different conditions, for example under stress and rest conditions.

The first image may comprise an end systole image and the second image may comprise an end diastole image. The first set of contour data may comprise end systole contour data and the second set of contour data may comprise end diastole data.

According to a further aspect of the present invention there is provided a method of scoring motion of a heart wall, the method comprising:acquiring a first image of the heart wall at a first time and a second image of the heart wall at a second time;identifying a first set of contour data in the first image;identifying a second set of contour data in the second image;in dependence on the first and second sets of contour data, defining at least one element representing a cardiac cyclic change in a section of the heart wall;analysing each element to generate at least one metric; andcomparing the at least one metric with a reference data model to score the motion of the corresponding section of the heart wall.

The method may comprise identifying a plurality of pairs of contour points. Each pair of contour points may relate to corresponding features in the first and second sets of contour data.

Each element may comprise at least first and second pairs of contour points. The contour points in each pair may define vertices of the element.

The analysis of each element may comprise determining a distance between the contour points in each pair and calculating a mean distance between the contour points for each element.

The method may comprise determining motion trajectories of each contour point. The motion trajectories may be determined with reference to the first and second images, for example by comparing the position of the contour points in each pair. Alternatively, or in addition, the motion trajectories may be generated in dependence on one or more interim images acquired between said first and second times. Each element may comprise opposing first and second sides corresponding to motion trajectories of the image elements.

The analysis of each element may comprise determining an area of the element. The area may correspond to an area enclosed by the first and second sets of contour data. The area may, for example, correspond to an area between end-diastolic and end-systolic contours. The determined area may be normalised. For example, the area of each element may be normalised to the total area of the end-diastolic data points.

The analysis of each element may comprise determining a rectangularity of each element. The rectangularity of each element may be calculated as the ratio between the area of each element and the area of its minimum bounding rectangle.

The analysis of each element may comprise determining a solidity of each element. A solidity of each element may be calculated as the ratio between the element's area and the area of its convex hull.

The scoring may be performed on a continuous scale.

The first and second images may comprise three-dimensional images of the heart wall. The first and second images may comprise two-dimensional images of the heart wall.

Each element may comprise a polygon. The polygon may be defined in two dimensions or three dimensions.

The method may comprise scoring the motion of the heart wall during a rest condition and during a stress condition.

The first image may comprise an end systole image and the second image may comprise an end diastole image. The first set of contour data may comprise end systole contour data and the second set of contour data may comprise end diastole data.

According to a further aspect of the present invention there is provided a system for generating a reference data model, the system comprising a processor configured to:analyse a plurality of sets of echocardiograph images, each set comprising at least first and second echocardiograph images, the analysis comprising identifying an end systolic image and an end diastolic image within each set;compare the end systolic image and the end diastolic image in each set to identify a cardiac cyclic change;calculate at least one metric in dependence on the identified cardiac cyclic change in respect of each set;acquire outcome data associated with at least some of the sets of echocardiograph images; andcompile the reference data model in dependence on the calculated metrics and the associated outcome data.

According to a further aspect of the present invention there is provided a method of generating a reference data model, the method comprising:analysing a plurality of sets of echocardiograph images, each set comprising at least first and second echocardiograph images, the analysis comprising identifying an end systolic image and an end diastolic image within each set;comparing the end systolic image and the end diastolic image in each set to identify a cardiac cyclic change;in respect of each set, calculate at least one metric in dependence on the identified cardiac cyclic change;acquiring outcome data associated with at least some of the sets of echocardiograph images; andcompiling the reference data model in dependence on the calculated metrics and the associated outcome data.

According to a further aspect of the present invention there is provided a non-transitory computer-readable medium having a set of instructions stored therein which, when executed, cause a processor to perform the method described herein.

Any control unit or controller described herein may suitably comprise a computational device having one or more electronic processors. The system may comprise a single control unit or electronic controller or alternatively different functions of the controller may be embodied in, or hosted in, different control units or controllers. As used herein the term “controller” or “control unit” will be understood to include both a single control unit or controller and a plurality of control units or controllers collectively operating to provide any stated control functionality. To configure a controller or control unit, a suitable set of instructions may be provided which, when executed, cause said control unit or computational device to implement the control techniques specified herein. The set of instructions may suitably be embedded in said one or more electronic processors. Alternatively, the set of instructions may be provided as software saved on one or more memory associated with said controller to be executed on said computational device. The control unit or controller may be implemented in software run on one or more processors. One or more other control unit or controller may be implemented in software run on one or more processors, optionally the same one or more processors as the first controller. Other suitable arrangements may also be used.

Within the scope of this application it is expressly intended that the various aspects, embodiments, examples and alternatives set out in the preceding paragraphs, in the claims and/or in the following description and drawings, and in particular the individual features thereof, may be taken independently or in any combination. That is, all embodiments and/or features of any embodiment can be combined in any way and/or combination, unless such features are incompatible. The applicant reserves the right to change any originally filed claim or file any new claim accordingly, including the right to amend any originally filed claim to depend from and/or incorporate any feature of any other claim although not originally claimed in that manner.

