GB2564673A

GB2564673A - Method and apparatus

Info

Publication number: GB2564673A
Application number: GB1711561.9A
Authority: GB
Inventors: Lewis Sheena; Hamilton Peter; Bankhead Peter
Original assignee: Examenlab Ltd
Current assignee: Examenlab Ltd
Priority date: 2017-07-18
Filing date: 2017-07-18
Publication date: 2019-01-23
Also published as: GB201711561D0

Abstract

A computer implemented method of identifying one or more comets in an image of a DNA comet assay, comprising obtaining edge image data identifying edges of structures in the image, obtaining mask image data identifying suprathreshold regions of the image and identifying one or more candidate comets in the image. The candidate comets each comprise a region of the image which includes both (i) a location of a circular edge identified by the edge image data and (ii) a location of a suprathreshold region identified by the mask image data, wherein the location of the circular edge in the edge image data is within the suprathreshold region in the mask image data and based on i) and ii) identifying one or more of said candidate comets as a comet. An additional invention is described that predicts the fertility of a male subject by obtaining a sperm DNA damage indicator from a sample from the subject and comparing it to a value and predicting that the subject is fertile if the DNA damage indicator is lower than said value.

Description

Method and Apparatus

Field of Invention

The present invention relates to analysis of electrophoresis assays, and in particular to methods and apparatus for analysing migration of DNA fragments, for example by analysing images obtained from electrophoresis assays.

Background

In electrophoresis an electric field is applied to a DNA sample held in a matrix, such as a gel, to induce an electrostatic force on fragments of the DNA sample. A contrast agent, such as a fluorescent dye can be used to enable images of the DNA sample. This provides images which show displacement of DNA fragments in the matrix due to the electrostatic force on those fragments from the electric field.

The displacement of DNA fragments is dependent on the electric field strength, and on the mobility of DNA fragments in the matrix. The mobility of DNA fragments in turn depends on their size, and the size of the fragments may itself be an indicator of the level of DNA damage. Samples having greater DNA damage and smaller DNA fragments are more mobile. The degree of displacement of DNA fragments from the sample under electric field enables inferences to be drawn about the level of damage in the DNA sample.

Fluorescence images of DNA electrophoresis assays show this migration of DNA fragments and it generally gives rise to a characteristic shape, referred to as a comet. DNA with a lower level of damage moves a smaller distance under the electric field, and therefore remains at the “head” of the comet. Damaged DNA moves a greater distance under the electric field, and may be smeared out into a “tail” from the head. A long, diffuse, tail indicates a higher degree of damage.

Summary of Invention

Aspects and embodiments of the invention are set out in the appended claims. These and other aspects and embodiments of the invention are also described herein.

Brief Description of Drawings

Embodiments of the disclosure will now be described, by way of example only, with reference to the accompanying drawings in which:

Figure 1 shows a schematic illustration of processing steps of an image of a DNA electrophoresis assay;

Figure 2 shows a schematic diagram of an apparatus configured to perform an example of a method such as that described with reference to Figure 1

Figure 3 shows a schematic illustration of an image of a DNA electrophoresis assay to illustrate processing to disregard candidate DNA comets;

Figure 4 illustrates a method; and

Figure 5 illustrates example comet data.

In the drawings in general, like reference numerals are used to indicate like elements.

Specific Description

Embodiments of the disclosure aim to identify comet(s) in an image of a DNA electrophoresis assay. The image may comprise one or more DNA comets and may also comprise image artefacts such as comets which are incomplete or otherwise unsuitable for analysis and other non-comet sources of image contrast.

Apparatus and methods described herein are directed to the analysis of such images to distinguish complete comets from artefacts. Embodiments aim to do this by using characteristic features of the geometry of a DNA comet. In particular, to distinguish comets from image artefacts embodiments of the disclosure identify structures having a circular edge adjacent to, for example contiguous with, a region of the image that has an intensity that is greater than a selected threshold level.

Having identified complete comet(s), and separated them from any artefact, quantitative metrics of the comet, or comets can be obtained to enable diagnostic and prognostic inferences to be drawn from the image data. These inferences include an understanding of the level of DNA damage that might be present in a sample.

DNA damage may comprise alteration in the chemical structure of DNA, for example a break in a strand of DNA. It will be understood that the DNA damage may comprise, consist of, or consist essentially of, for example DNA cross links, and/or base mismatching, and/or DNA adducts, and/or substitution of bases, which may, for example, include the insertion and/or deletion of bases. It is also to be understood that the methods, techniques, and/or apparatuses of the present description may be used to detect the fragmentation of DNA, which may comprise, consist of, or consist essentially of, for example, one or more single strand break(s), or one or more double strand break(s).

Figure 1 illustrates a computer implemented image processing method, and does so using a schematic illustration of image data at different stages of that image processing method. It will be appreciated that the apparatus which performs this method comprises an image processor, for example, digital logic. This may be implemented in any appropriate way for example by an appropriate combination of software and firmware loaded into a programmable processor. The different aspects of the image data illustrated in Figure 1 may be stored for access by this image processor in one or more areas of a computer readable data store, such as volatile memory such as random access memory, RAM, which may include on-chip cache memory. Part or all of this data may also be stored in non-volatile data storage such as hard disc drives, HDD, and solid state drives, SSD.

To briefly introduce the parts of Figure 1 - image 1a illustrates a microscope image of the DNA sample after the application of an electric field in an electrophoresis process. Such DNA may be obtained from any of a wide range of cells. Examples of such cells include cultured cells, buccal mucosal cells, prokaryotic cells .cancer cells, sperm, yeast cells and bacteria The methods and apparatus of the present disclosure may have particular utility where the cell is a sperm cell, for example a human sperm cell. Such embodiments may permit the assessment of male fertility. In some embodiments, the cell is obtained from a sample of cells, for example a sample of human cells. Obtaining the cell from a sample of cells provides a non-invasive method for the evaluation of DNA damage. It will be appreciated therefore that embodiments of the disclosure need not be practiced on the human or animal body and involve technical steps which may be carried out entirely ex vivo, and for non-therapeutic purposes such as to assist contraception.

The image shown in Figure 1A includes first and second structures 2, 10 on a background 8. The first structure 2 is a comet. The second structure 10 is an artefact, bounded by an artefact edge 14. The comet 2 has a head portion 6 and a tail portion 4. The head portion 6 of the comet is adjacent to, for example contiguous with, the tail portion 4. The comet comprises, for example is bounded by, a comet edge 12 which separates the comet from background regions of the image. It will be appreciated in the context of the present disclosure that background regions of the image may not have zero intensity, for example image noise may provide a baseline level of image intensity in these background regions.

Image 1b of Figure 1 shows edge image data including the artefact edge 14 and the comet edge 2. Image 1c of Figure 1 shows an image in which the head portion 6 of the comet 2 and an artefact 10 having a circular shape have been isolated, and other image features have been suppressed. Image 1d of Figure 1 shows mask data that labels certain areas of the image 1a as background, and others as structures 2, 10, in the image. In the mask data, the first and second structure 2, 10 have a first intensity and the background 8 has a second intensity. Image 1e of Figure 1 shows a single comet 2.

The first step of the method is to obtain the data defining the image which is to be processed. The data may comprise edge image data defining the edges of structures in the image, and mask image data identifying structures in the image having an intensity that is greater than a selected threshold. The computer processor reads the image data into an accessible memory, for example it may obtain it from a communication interface coupled to the processor. Examples of such communication interfaces include serial interfaces, which permit connections to imaging apparatus and data storage memory, and network interfaces which permit connections to remote computing devices and/or remote imaging apparatus. The obtained data may comprise the complete image, from which edge image data and mask image data is subsequently to be derived, for example by using edge detection and thresholding methods, examples of which are described later. Regardless of how the edge data and mask data are obtained, the next steps in the method illustrated in Figure 1 are to identify the location of any circular edges in the edge image data and to identify the location of any suprathreshold region in the mask image data that coincides with, e.g. is adjacent to or comprises the region bounded by a circular edge as identified in the edge image data.

Locations where such structures coincide in the two types of data are identified as candidate comet structures. These may be provided for further analysis to determine which, if any, of these so-called candidate comets is amenable to further, quantitative analysis. One way of providing the data is to store it into memory, another is to display it, for example by providing an overlay highlighting the candidate comet in the image from which the edge data and mask data were both obtained.

One embodiment of the method of Figure 1 may be summarised as follows. Firstly the image data is obtained and converted to a format that is suitable for processing, for example floating point format. This image data is used to obtain an estimate of local background signal intensity, that is to say an estimate which takes into account local spatial variations in the background of the image. This estimate of the background is then subtracted from the image data to obtain a background-subtracted image - e.g. a map of the variations in signal intensity which exceed the local background. A global estimate of the image noise is then applied to the background-subtracted image data to obtain mask data that identifies variations that exceed the local background intensity by more than the noise. The suprathreshold regions identified by this mask include comets, and many artefacts, e.g. non-comet objects and partial comets unsuitable for analytical measurement. Candidate comet heads are then identified from amongst these fragments by finding small, bright, approximately-circular regions which contain a single peak in image intensity. This is achieved by first identifying edges in the image data, then eliminating any edges which coincide with the boundaries of the image, and then taking each edge in turn and determining the ratio of its length to the area it encloses. Where this ratio indicates a circular structure (e.g. the ratio matches the ratio expected for a circle), that region of the image is identified as a candidate comet head. The next step in this image processing method is to identify those candidate comet heads which are adjacent to, e.g. contiguous with, comet fragments which extend from the candidate head in a direction selected based on the direction of the electric field used for the electrophoresis.

Figure 2 illustrates an apparatus 100 configured to perform a method such as that described above with reference to Figure 1. Figure 2 illustrates an apparatus 100 that is coupled to communicate with a local terminal 110, and with a local image capture system 112, such as a microscope, for capturing images of electrophoresis assays. In addition, in the illustration shown in Figure 2 the apparatus 100 is also coupled to communicate over a network 114, such as the internet, with remote terminals 116, 118, 120 and remote image capture system 122 for receiving image data from these remote devices, and for sending the results of analyses to them.

The apparatus 100 comprises a data interface 102 (for example an IO interface), a background determiner 104, a comet head detector 108, and a comet detector 106. The data processing elements of this apparatus 100 are coupled to communicate data between them. In particular, the data interface 102 is coupled to provide image data to the background determiner 104, the head detector 108, and the comet detector 106. The head detector 108 and the background determiner 104 are both coupled to the comet detector 106, and the comet detector 106 is coupled to provide output data to the data interface 102.

The background determiner 104 is configured to perform two principal functions. Namely (1) to determine a global noise threshold for the image, and (2) to provide a mask which identifies regions of signal above the noise floor noise and which also takes into account local variations in background intensity within the image. The background determiner 104 is configured to provide this image mask as a matrix which is the same size (e.g. has the same number of pixels and the same pixel size) as the image data. To achieve these functions, the background determiner 104 is configured to downsample the image data, and then to apply a morphological opening to that downsampled data (e.g. an erosion followed by a dilation). The structuring element used to apply that morphological opening comprises a circular image kernel having a radius which is larger than the expected half-width of a comet. Provided that the largest objects in the image are comets, the result of applying this kernel is a version of the image which includes only the background signal. The background determiner 104 may be configured to smooth this background image, for example by applying a spatial low pass filter, such as a Gaussian smoothing, to the background image. It then subtracts this (perhaps smoothed) background image from the original image data to obtain a background subtracted version of that original image. Negative values may be clipped to zero. This provides an estimate of the signal intensity in the image which ignores relatively small regions of non-background image data. The “relatively large” regions may comprise regions which are greater than a selected minimum size. The size of the “relatively small” regions may, likewise comprise regions which are smaller than that selected minimum size. This minimum size may be imposed by the size of the kernel of the morphological opening. It then subtracts the background image data from the original image data to provide subtracted image data.

The background determiner 104 is configured to apply a threshold to this subtracted image data, for example a threshold selected based on the standard deviation of the background data. This (roughly) identifies background regions of the subtracted image data - e.g. regions of the subtracted image data which do not exceed the threshold. The background determiner 104 is configured to determine an estimate of the global image noise by determining the standard deviation of the subtracted data in these background regions. It is also configured to use this estimate of the global image noise as a threshold to obtain mask image data identifying regions where the subtracted image data exceeds the local estimate of the background signal by more than the estimated global image noise. The background determiner 104 may then clean this mask data, for example with another morphological filter, such as an erosion filter to remove areas of the mask image data which indicate image structures of less than a selected size. The background detector is configured to provide the mask image data to the comet detector 106 and to the head detector 108.

The head detector 108 is configured to identify structures in the image data which have characteristics of a comet head and to provide data identifying these structures to the comet detector 106. To achieve this, the head detector 108 is configured to obtain the image data from the data interface 102 and to apply an edge finding filter to that image data. The edge finding filter may comprise having a kernel that is selected to approximate the second spatial derivative in two dimensions of a smoothing filter kernel, such as a Gaussian, for example the Laplacian (V²) of a Gaussian, which may be referred to as a Mexican Hat function. The width of this filter kernel may be selected to correspond to the expected size of a comet head. The head detector 108 is configured to determine the location of zero crossings in the filtered image data, for example by identifying adjacent pixels in the filtered image data which are of different sign. The locations of these sign changes in the filtered image data can then be used to identify the edges of structures in the image.

To locate sign changes between adjacent pixels in the filtered data, the head detector 108 may compare the sign of each pixel with the sign of an adjacent pixel in the filtered data. This may be done in at least two different image directions (e.g. row-wise and column-wise through the pixels) The sign-change data obtained in these two different directions may the be combined, for example by using a logical AND, or equivalent operation to determine the locations of a set of closed contours in the image - an edge image.

This edge image data indicates the locations of the edges of structures having a size that corresponds to the width (e.g. related to the Full Width at Half Maximum (FWHM), for example related to σ) of the smoothing filter kernel that forms the basis of the edge finding filter.

The head detector 108 is configured to step through this edge image data and, for each closed contour, to determine (a) the area enclosed by that contour and (b) the length of that contour. The length may be determined by a stepwise iteration along each contour in the zero crossing data visiting each pixel along the contour, for example the length may be determined by measuring the sum of the distances between each consecutive pairs of vertices along the contour. The area may be determined by, for example, counting the number of pixels or determining the determining the length of the contour. The head detector 108 can then determine, for each contour, the ratio between the square of its length and the area it encloses.

The head detector 108 is configured to compare this ratio with a selected allowed range to identify circular contours. For example, if the ratio is approximately 4/π, this implies that the corresponding contour in the edge-finding filtered data is circular, for example approximately circular. The head detector 108 may be configured to assign, to each contour, a circularity score indicating the closeness of this ratio to 4/π. The contours which match the circular ratio very closely are likely to be near perfect circles. The head detector 108 may be configured to provide edge data indicating the location of each of these circular contours to the comet detector 106.

The head detector 108 may be configured to arrange the edge data in a sequence. For example the data indicating the location of each circular contour may be arranged in an order which corresponds to the circularity score of that contour. For example highly circular contours may be provided earlier in the sequence.

The head detector 108 may also be configured to arrange the edge data in a sequence based on the intensity of the image data enclosed by each circular contour. For example, the head detector 108 may be configured to determine the sum of the image pixels in the image data that are encircled by the contour identified in the edge data, and to arrange the edge data in a sequence that corresponds to this summed intensity value. This may place the brightest, most intense, comet heads, earlier in the sequence than the less bright ones.

The head detector 108 may also identify circular regions in the edge data which encompass more than one intensity peak. These may be identified based on the image data. The head detector 108 may be configured to discard head regions which encompass more than one intensity peak, e.g. to remove them from the data indicating the locations of circular edges that it provides to the comet detector 106. The head detector 108 may also be configured to discard head regions in which the circularity score is lower than a selected threshold level, for example the boundary squared divided by the area is less than 4π divided by 0.7. . This may be done before retrieving intensity data or mask image data for the circular structures. This may enable the head detector 108 to avoid analysing the intensity data associated with non-circular structures.

Once the edge image data has been processed as described above, the head detector 108 is configured to provide the edge image data to the comet detector 106. The comet detector 106 is also configured to obtain, from the background determiner 104, the mask data indicating the locations of suprathreshold regions in the image data, e.g. regions where the image intensity exceeds the local background by an amount that is greater than a threshold selected based on a global estimate of the image noise.

The comet detector 106 is configured to step through the edge image data, and to use the location of each contour identified in the edge image data to lookup the value of the mask data at that location. This enables the comet detector 106 to check neighbouring pixels around that location in the mask data to determine whether the contour is located in a region of the image which also includes a suprathreshold region identified by the mask image data. The comet detector 106 is then able to determine, based on this lookup, whether the circular edge identified by the edge image data is at least partially within a suprathreshold region in the mask image data. For example, in the event that the area bounded by a circular contour identified by the edge image data is adjacent to, for example contiguous with the suprathreshold region the comet detector 106 identifies those areas together as belonging to a structure which may be a comet - a candidate comet. The comet detector 106 may be configured to step through the edge data until it has applied this analysis to each item of edge data.

The comet detector 106 may also be configured to identify the area of the suprathreshold region associated with each candidate comet, for example by counting the pixels that make it up, and to disregard candidate comets if the suprathreshold region they occupy in the mask image data is less than a selected threshold level. This threshold may be selected based on the area of the corresponding comet head associated with that candidate comet.

The comet detector 106 may then apply one or more of the following selection steps to further restrict the list of candidate comets. For example, as one selection step, the comet detector 106 may be configured to identify a bounding box which encompasses all of the comet head and all of the associated suprathreshold region. In the event that this bounding box at least partially encompasses another candidate comet, or simply overlaps with the bounding box of another candidate comet, both of those two candidate comets may be discarded (e.g. eliminated from further analysis). As another example of a selection step, the comet detector 106 may be configured to discard candidate comets if their bounding box coincides with the boundary of the image as whole. This may eliminate partial, e.g. incomplete, comets from subsequent analysis.

As another example of a selection step, the comet detector 106 may be configured to identify the direction of alignment of each candidate comet and to disregard those candidate comets in which the major dimension (their length) does not extend away from the comet head identified by the edge image data in the same direction as the electric field applied during electrophoresis. This may be done using the bounding box to identify the major dimension and its direction. A comet may be deemed to be aligned with the electric field if the angle between its major dimension and the electric field direction is less than 30°, for example less than 15°, for example less than 5°.

Figure 3 shows one example of image data including candidate comets 40, 42, 44, 46, 48, 50 and 52, identified based on the process described above, and the electric field direction 56 applied during electrophoresis. As explained above, the comet detector 106 may disregard the candidate comet based the comet’s size, the relative size of the head and the tail of the comet, and/or the comet’s position. A comet that is too small may lead to an erroneous measurement of DNA damage. In an example of a selection step, the comet detector 106 compares the size of the comet to a threshold size and a comet having a size less than the threshold size is disregarded. In the example shown in Figure 5, candidate comet 40 has a size less than a threshold size and is disregarded. In this example, the comet detector 106 measures the size of the comet from the number of pixels in the suprathreshold region. In other examples the comet detector 106 measures the area of the comet from the length and width of the comet, and/or the length of the edge of the comet. In an example, the area may be measured from the contour vertices.

As explained above, a comet that overlaps with another comet may lead to an erroneous measurement of DNA damage. In an example illustrated in Figure 3, the comet detector 106 identifies that candidate comets 42, 44 overlap, for example based on overlap of their bounding boxes, and disregards them. In an example, the convexity of the candidate comets may be measured, for example, by computing the ratio of the comet area to the area of its convex hull. For example, a value close to one may indicate that the comet region is largely convex.

A comet overlapping a boundary 58 of the image data will be partially visible in the image. The boundary of the image data corresponds to range of the image and location structures can be observed in the image. In an example, the processor measures the position of the edge of the comet and the boundary of the image. The processor disregards comets having an edge located at the boundary of the image. In the example shown in Figure 5, candidate comet 52 overlaps with the boundary 58 of the image and is therefore disregarded. The head and tail of the comet is due to the movement of DNA fragments under the electric field. A candidate comet having a tail that extends in a direction other than the direction of the electric field indicates that the candidate comet moves in an unexpected way under an electric field. In an example, the comet detector 106 measures the direction of the largest dimension of the candidate comet. The comet detector 106 calculates the difference between this direction to the direction of the applied electric field. The comet detector 106 disregards a candidate comet with the largest dimension that is not aligned with the applied electric field. In this example, the comet detector 106 compares the difference between the direction of the largest dimension of the candidate comet and the direction of the applied electric field to a threshold angle. A candidate comet having a difference greater than the threshold angle is disregarded. In the example shown in Figure 5 the electric field 56 is applied in a horizontal direction and candidate comets 48 and 50 have a largest dimension that is in a direction misaligned with the electric field.

In general the tail portion of the comet is expected to be larger than the head portion of the comet. In an example the comet detector 106 measures the size of the head portion and the size of the tail portion of the comet. The comet detector 106 then compares the size of the head portion to the size of the tail portion. The comet detector 106 disregards a candidate comet having a head portion that is larger than the tail portion. In the example shown in Figure 3, one candidate comet 54 comprises a smaller tail portion than head portion and is therefore disregarded.

In an example a bounding box may be used. This may enable a candidate comet having a short tail to be detected if it adds appreciably to the spread (for example, in the direction perpendicular to the candidate comet tail). For example, a comet having an extremely small tail, both horizontally and vertically, may be discarded.

The comet detector 106 may determine the length of the tail using the mask image data. The comet detector 106 identifies the comet using the process described with reference to Figure 1. The mask image data shows the area of this comet and the comet detector 106 distinguishes between the tail of the comet and the head of the comet using the correlation between the mask image data and the circular structure identified in the edge image data. The comet detector 106 measures the distance of the tail from the head to determine the maximum distance of the tail from the tail. The maximum distance corresponds to the maximum length of the tail.

In an example the comet detector 106 measures the change in the signal along the length of the tail. The comet detector 106 identifies the area corresponding to the tail portion as described above. The comet detector 106 then identifies the corresponding area of the microscope image. The comet detector 106 measures the change in the signal along the length of the tail. The comet detector 106 plots the change in the signal with the length of tail. The comet detector 106 determines the proportion of the DNA having a given level of damage according to the change in the magnitude of the signal along the length of the tail.

To determine the bounding box referred to above, the comet detector 106 may determine the smallest rectangular boundary that can encompass the entire comet. This may be done by, for example taking the minimum and maximum x and y coordinates of the vertices of the contour representing the comet.

The level of DNA damage may be determined, for example, based on the minimum and maximum x and y coordinates of the vertices of the contour representing the comet.

A complete cycle of operation of the apparatus 100 shown in Figure 2 will now be explained with reference to Figure 4. This method may be performed by the hardware explained above, or by any other image processing apparatus.

As a preliminary step, an electrophoresis assay is performed, and a microscope image of the assay is captured 400. This image capture step may form a part of the method, or may be performed before the method begins and may be performed remotely - e.g. in a wet lab that communicates image data to the image processing apparatus remotely, for example over a network. Wherever it is captured, the captured image is processed to obtain edge image data 402 defining the edges of structures in the image, and mask image data 406 identifying structures in the image having an intensity that is greater than a selected threshold.

The next step in the method is to identify 402 structures in the image data which have characteristics of a comet head. To achieve this, an edge finding filter may be applied to the image data. The edge finding filter may comprise the features explained above with reference to Figure 2, and as also explained above, the filtered image data produced by the edge finding filter can then be used to identify the edges of structures in the image.

Each closed contour identified in the edge image data is analysed to determine (a) the area enclosed by that contour and (b) the length of that contour. The length may be determined by a stepwise iteration along each contour in the zero crossing data visiting each pixel along the contour, and the area may be determined by counting the number of pixels encircled by the contour. For each contour, the ratio between the square of its length and the area it encloses is calculated and used to determine 404 a circularity score indicating the closeness of this ratio to 4/π. A threshold is then also applied to the edge data to exclude contours having a circularity score that is less than a selected threshold level. The edge data can then be used to identify corresponding regions of the image data (e.g. to obtain intensity data describing regions encircled by the contours identified in the edge image data). This can enable contours which encompass more than one intensity peak to be discarded. After this has been done, the remaining contours may be sorted (e.g. placed in a sequence) that is selected based on the total intensity of pixels in the image data which are bounded by that contour.

The peak intensity (maximum pixel value) within the Difference of Gaussians filtered image may be used to sort the potential comet heads. This may distinguish candidate comets. For example, a candidate comet having a high local intensity may enable determination of a comet head along with the presence of a corresponding tail in the direction of electrophoresis. In an example, the Difference of Gaussians filtered image may be used to check intensities.

To obtain 406 the mask image data, first an estimate of local background signal intensity is determined. This estimate takes into account local spatial variations in the background of the image. This estimate of the background is then subtracted from the image data to obtain a background-subtracted image - e.g. a map of the variations in signal intensity which exceed the local background. A global estimate of the image noise is then applied to the background-subtracted image data to obtain mask data that identifies variations that exceed the local background intensity by more than the noise. This defines a number of suprathreshold regions which make up the mask image data.

The location of each contour, indicated by the edge image data, is then used to identify the values of the mask image data at that location, and around that location (e.g. within a selected distance such as two or three pixels). The mask data at and around that location is then used to determine 410 whether the contour coincides with a suprathreshold region in the mask image data.

In the event that a sufficiently circular contour does coincide with (e.g. lies at least partially within) a suprathreshold region identified by the mask data, the area of the suprathreshold region is compared with a minimum area threshold and candidate comets which do not occupy a sufficiently large area are discarded. This threshold area may be selected based on the area of the comet head associated with that candidate comet - for example comets where the tail is not larger than the head may be disregarded. Other selection steps, similar to those described above with reference to Figure 2 may then also be applied to reduce the number of candidate comets. The candidate comets which pass these selection criteria may then be used in further analyses - for example to determine DNA damage.

One way to determine DNA damage is to determine a location of the head of each comet, for example using the location of the circular contour in the edge image data (e.g. the centre of that contour), and to determine the intensity of the image pixels in the comet as a function of distance from that head location - this may be done by obtaining a bounding box around the comet as explained above, and determining the total pixel intensity as a function of displacement along the major dimension of the bounding box.

Figure 5 illustrates one example of comet data obtained in this way. This data may enable the DNA damage in the comet to be quantified, for example by determining the displacement of the centre of mass (e.g. the intensity weighted position average) of the comet from the head. This may enable a DNA damage value to be assigned to the comet as a whole. The DNA damage value may be given as a percentage of the total DNA of the comet. The DNA damage value may be calculated as the mean of a plurality of DNA damage values. In some embodiments, the DNA damage value is calculated as the mean of 50 DNA damage values. In some embodiments, the DNA damage value is calculated as the mean of 100 DNA damage values. Within the comet bounding box, pixel intensities from the background-subtracted image may be added together. This may, for example, use column-by-column approach to form comet data, for example as shown in Figure 5. In some examples, negative values may be clipped to zero.

In an example, the DNA damage may be determined based on the ratio of the sum of the values within the tail region of the data (e.g. to the right of the head bounding box) to the sum of the values in the entire plot.

It will be appreciated in the context of the present disclosure that the details of the embodiments described above are amenable to a number of variations and further refinements.

As one example - the use of a morphological opening to identify background regions of the image is mentioned above. It will be appreciated in the context of the present disclosure that a morphological opening may comprise the application of an eroding filter followed by a dilating filter. The eroding filter may be used alone. One type of eroding filter comprises a so called “minimum filter”. Applying a minimum filter may comprise applying a kernel, or structuring element, to each of a plurality of areas of the image to assign each pixel within the kernel to a floor value selected based on the values of image pixels within the kernel. For example this floor value may comprise the minimum value of all of the pixels within the kernel, or another value that approximates the lower end of this distribution of pixel values. By applying this kernel an intermediate image can be obtained in which background regions of the original image (and perhaps some “foreground” regions) are assigned to the floor value.

As another example - it is mentioned above that a global estimate of the image noise is applied to the background-subtracted image data to identify suprathreshold regions of the image. It will be appreciated however that other methods of selecting a threshold may be used, and this is just one example of selecting a threshold based on the variance of the image in the background regions. Another approach may be to identify low order spatial variations, for example low order polynomial terms and/or low-pass spatial filtered data, and to subtract these from the image data to obtain backgroundsubtracted data.

As another example - the use of an edge finding filter which approximated the Laplacian of a Gaussian is mentioned above. It will be appreciated in the context of the present disclosure that this may provide a Difference of Gaussians filter, but that other kinds of edge finding filter may be used. For example any transfer function that enhances edge detail may be used - examples include a difference-of-Gaussians, Mexican-Hat, or logGabor transfer function. Much simpler transfer functions can also be used - for example, a simple high pass filter may be used to obtain a filtered version of the image in which edges can be very straightforwardly located (e.g. by the application of a threshold). The cut-off frequency of such filters may be selected based on the known size of the DNA sample, and/or the spatial resolution of the image. For example, the high pass cut off may be chosen to select only the highest one or two (discrete) spatial frequencies present in the image. A simple Gaussian roll-off can be used for this purpose.

As another example - the edge finding procedure may be conducted entirely in frequency domain, by applying one of the straightforward edge finding filters explained above, but may also be performed partially or entirely in image domain. For example a first filtered version of the image may be obtained using a smoothing kernel of a first width (in either image or frequency domain). A second first filtered version of the image may then be obtained by using a smoothing kernel of a second width, that is different from the first width (in either image or frequency domain). The first and second filtered versions of the image can then be subtracted from each other to obtain a difference image which may be functionally equivalent to the edge finding filter output.

In an example the processor may use a sample having a known level of damage in a calibration step. The processor measures the size of the comet tail in a number of samples having a known level DNA damage. The processor determines the correlation between the size of the DNA in each sample and the level of DNA damage. The processor uses this correlation to determine DNA damage on subsequent samples having an unknown level of DNA damage. The calibration step described above may also be used to identify any errors in the measurement and processing steps. The processor compares the size of the comet tail in the measurement sample to an expected size of the comet tail for a sample having a given level of damage. The processor determines whether the size of the comet tail in the measurement sample is outside of an expected range. The processor alerts the user that there may be an error in the measurement process if the size of the comet is outside of the expected range. The processor may also compare the size of the comet tail of a plurality of samples having different levels of DNA damage. The processor determines the relationship ofthe size of the comet tail to the level of DNA damage from these samples. The processor determines the difference between this relationship and an expected relationship between the level of DNA damage and comet size. The processor alerts the user that there may be an error in the measurement process if this difference is greater than a predetermined range.

Other variations and further refinements of the embodiments described above will be apparent to the skilled addressee in the context of the present disclosure.

Figure 2 illustrates communication between the apparatus 100 ofthe present disclosure, and other items of hardware such as a local display terminal, and a local image capture system, such as a microscope. Network connections are also illustrated. It will be appreciated however that whilst such additional hardware may be useful, some or all of it need not be provided together with the image processing apparatus 100. For example the image processing apparatus 100 may be provided in a network server - so no local display or data capture apparatus 100 is necessary. In addition all processing and image capture may be done locally, so the network connection is also optional.

Each of the functional elements shown in Figure 2 comprises processing logic, for example digital logic. This may be implemented in any appropriate way for example by an appropriate combination of software and firmware loaded into a programmable processor. Each element may also comprise a computer readable data store, such as volatile memory such as random access memory, RAM, which may include on-chip cache memory. Part or all of this data may also be stored in non-volatile data storage such as hard disc drives, HDD, and solid state drives, SSD. Although shown as separate functional elements it will also be appreciated that this is merely schematic, and the functionality of one or more of these elements may be distributed between different physical processors, and the functionality of two or more of them may be integrated into a single functional unit such as a processor. The computer readable data store that is used by these functional elements may also be integrated into a single unit, or a number of units, accessible to one or more of the functional elements shown in the drawings.

To the extent that certain methods may be applied to the living human or animal body, it will be appreciated that such methods may not provide any surgical or therapeutic effect. In addition, it will be appreciated that such methods may be applied ex vivo, to tissue samples that are not part of the living human or animal body. For example, the methods described herein may be practiced on meat, tissue samples, cadavers, and other nonliving objects.

With reference to the drawings in general, it will be appreciated that schematic functional block diagrams are used to indicate functionality of systems and apparatus described herein. It will be appreciated however that the functionality need not be divided in this way, and should not be taken to imply any particular structure of hardware other than that described and claimed below. The function of one or more of the elements shown in the drawings may be further subdivided, and/or distributed throughout apparatus of the disclosure. In some embodiments the function of one or more elements shown in the drawings may be integrated into a single functional unit.

The above embodiments are to be understood as illustrative examples. Further embodiments are envisaged. It is to be understood that any feature described in relation to any one embodiment may be used alone, or in combination with other features described, and may also be used in combination with one or more features of any other of the embodiments, or any combination of any other of the embodiments. Furthermore, equivalents and modifications not described above may also be employed without departing from the scope of the invention, which is defined in the accompanying claims.

In some examples, one or more memory elements can store data and/or program instructions used to implement the operations described herein. Embodiments of the disclosure provide tangible, non-transitory storage media comprising program instructions operable to program a processor to perform any one or more of the methods described and/or claimed herein and/or to provide data processing apparatus as described and/or claimed herein.

The activities and apparatus outlined herein may be implemented with fixed logic such as assemblies of logic gates or programmable logic such as software and/or computer program instructions executed by a processor. Other kinds of programmable logic include programmable processors, programmable digital logic (e.g., a field programmable gate array (FPGA), an erasable programmable read only memory (EPROM), an electrically erasable programmable read only memory (EEPROM)), an application specific integrated circuit, ASIC, or any other kind of digital logic, software, code, electronic instructions, flash memory, optical disks, CD-ROMs, DVD ROMs, magnetic or optical cards, other types of machine-readable mediums suitable for storing electronic instructions, or any suitable combination thereof.

In some examples the functionality of the computer and/or the processor may be provided by digital logic, such as field programmable gate arrays, FPGA, application specific integrated circuits, ASIC, a digital signal processor, DSP, or by software loaded into a programmable processor. The functionality of the processor and its programs may be provided in a single integrated unit, or it may be distributed between a number of processors, which may be arranged to communicate over a network, such as “cloud” computing. This may enable, for example, the processing steps of the method to be performed at a device (or devices) that are remote from the image capture and the DNA sampling apparatus.

For the evaluation of DNA damage, the cell is subjected to a DNA comet assay. The comet assay is also known as the single cell gel electrophoresis or SpermComet®. The comet assay quantifies the amount of DNA damage per sperm.

The protocol of the DNA comet assay may comprise a gel electrophoresis step. Gel electrophoresis may be run under neutral conditions or under alkaline conditions. Under neutral conditions, double strand breaks may be detected. Under alkaline conditions, double strand breaks and single strand breaks may be detected. In some embodiments, gel electrophoresis is run under alkaline conditions. For example, gel electrophoresis may be run at a pH of between about 12.7 and 13.3.

The DNA of the comet may be visualised by any method available in the art. It will be understood that the comet may be visualised using a fluorescent label, such as ethidium bromide.

The comet assay further comprises obtaining an image of the comet. Suitable methods for obtaining an image of the comet will be known to the person skilled in the art. In an example, the image data may comprise a non-saturated single-channel 16-bit TIFF image. The image may also comprise an 8-bit, 12-bit, 14-bit and/or 16-bit image.

In an example the image comprises one intensity value per pixel, i.e. it should be monochromatic. An RGB colour image may be converted to have a single channel.

In an example the spatial resolution is such that comet heads and tails occupy multiple pixels.

In an example, the DNA damage is determined based on a comparison between the intensity within the head and within the tail regions, e.g. the ratio of the total intensity within the tail vs. the total intensity within the entire comet.

The ‘comet tail %’ measurements may be ‘tail %’ measurements computed using a modified definition. This may enable data obtained using the method and apparatus described herein to be compared with other data more efficiently.

Evaluating the DNA damage of the comet may comprise assigning a DNA damage value. The DNA damage value may be given as a percentage of the total DNA of the comet. In an example, the DNA damage value may be calculated as the mean of a plurality of DNA damage values. In some embodiments, the DNA damage value is calculated as the mean of 50 DNA damage values. In some embodiments, the DNA damage value is calculated as the mean of 100 DNA damage values.

A method for determining the fertility status of a male subject is provided, for example a human male subject.

Sperm DNA damage has been identified as a major contributor to male infertility. DNA damage thresholds determined using the comet assay have been established for the diagnosis of male fertility and for the prediction of successful assisted reproductive treatment (ART).

The method may be carried out in vitro and/or on a sperm sample obtained from the subject, thereby providing a non-invasive method for the determination of the fertility status of a male.

Fertility status may refer to the ability to achieve pregnancy without ART over a period of 12 months or more of regular unprotected sexual intercourse.

As used herein, the terms “fertile” and “fertility” may refer to the ability to achieve a clinical pregnancy after less than 12 months of regular unprotected sexual intercourse

As used herein, the term “infertile” and “infertility” may refer to a disease of the reproductive system defined by the failure to achieve a clinical pregnancy after 12 months or more of regular unprotected sexual intercourse.

The fertility status of the male subject is assessed based upon the DNA damage of a comet. The fertility status may be assessed by assigning a DNA damage value and comparing the DNA damage value to one or more fertility threshold values.

The fertility threshold value may be a predetermined threshold value. A predetermined threshold value of between about 0 and about 25% DNA damage, or less than 25% DNA damage, may indicate that a male subject is fertile. A predetermined threshold value of greater than 25%, for example between about 25% and 50% may indicate that a male subject has a high risk of infertility. A predetermined threshold value of more than 50% may indicate that a male subject has a yet higher risk of infertility.

The method for determining the fertility status may further comprise selecting an assisted reproduction treatment (ART). Assisted reproduction treatment (ART) may refer to a procedure used to achieve pregnancy. ART may comprise one or more of: in vitro fertilisation (IVF), intracytoplasmic sperm injection (ICSI), and artificial insemination, which may comprise intrauterine insemination and intracervical insemination

Identifying the ART to which a male subject will most favourably respond allows the selection of the ART technique that is the most promising for achieving pregnancy. The clinical thresholds have been established for the prediction of success with ART using the Comet assay.

An appropriate ART may be selected based upon the level of DNA damage in the comet. In some embodiments, an ART is selected based upon the DNA damage value of the comet.

The inventors in the present case have found that identifying the comet as defined herein leads to a re-categorisation of the ART assigned to the male subject, with 5 out of 45 (11%) patients being re-categorised; one patient in the fertile group would be reassigned to the IVF group and four patients from the IVF group would be re-assigned to the ICSI group. Two patients would be re-categorised when using the “Tail %” measurement DNA damage, one patient from ICSI to IVF, and one from IVF to no male factor.

A DNA damage value of between about 25% and 50%, for example 26% to 50%, for example 26% to 29%. may indicate that the male subject has a high probability of success with IVF.

A DNA damage value of greater than about 50% may indicate that the male subject has a high probability of success with ICSI.

A method for the prognosis of pregnancy outcome is provided. The prognosis of pregnancy outcome is determined based upon the DNA damage of a comet. The prognosis of pregnancy outcome may be assessed by assigning a DNA damage value and comparing the DNA damage value to one or more threshold values.

A threshold value of 40% or lower DNA damage may indicate that the pregnancy will proceed to term. A threshold value of greater than 40% DNA damage may indicate that the pregnancy will not proceed to term.

Also provided is a method for the prognosis of a recurrent miscarriage. Recurrent miscarriage may refer to loss of 3 or more consecutive pregnancies up to 24 weeks of gestation. The prognosis of recurrent miscarriage is determined based upon the DNA damage of a comet. The prognosis of recurrent miscarriage may be assessed by assigning a DNA damage value and comparing the DNA damage value to one or more threshold values.

Any of the aforementioned aspects and/or embodiments and in particular the methods disclosed herein may further include generating a report. The report may comprise one or more of: a measured DNA damage value; a fertility status of a subject; a prognosis of pregnancy outcome; a prognosis of recurrent miscarriage; or any combination thereof.

Any of the aforementioned aspects and/or embodiments and in particular the methods disclosed herein may further include treating male infertility. This may include administering to a patient a treatment/therapy for male infertility (and/or one or more symptoms thereof) if the infertility of a male subject is confirmed by way of a method of the present invention. The treatment/therapy may include one or more of the following: administration of therapeutic agents; treatment by surgery; or assisted reproductive treatment.

Therapeutic agent may refer to an agent that is used for the medical treatment of a patient, for example for the treatment of a disease or a medical condition. The therapeutic agent may have a curative and/or a preventative effect. The therapeutic agent may have been the subject of medical authorisation for its use in the treatment of a patient.

In the context of the present disclosure other examples and variations of the devices and methods described herein will be apparent to a person of skill in the art. Other examples and variations are within the scope of the disclosure, as set out in the appended claims.

Claims

CLAIMS:

1. A computer implemented method of identifying one or more comets in an image of a DNA comet assay, the method comprising:

obtaining edge image data identifying edges of structures in the image; obtaining mask image data identifying suprathreshold regions of the image; identifying one or more candidate comets in the image, wherein the candidate comets each comprise a region of the image which includes both:

(i) a location of a circular edge identified by the edge image data, and (ii) a location of a suprathreshold region identified by the mask image data, wherein the location of the circular edge in the edge image data is within the suprathreshold region in the mask image data; and identifying one or more of said candidate comets as a comet.

2. The method of claim 1, comprising disregarding candidate comets comprising a suprathreshold region occupying less than a selected area of the mask image data.

3. The method of claim 1 or 2, comprising identifying background regions of the image, wherein the suprathreshold regions of the mask image data comprise areas of the image having an intensity greater than a threshold selected based on the intensity of the image in the background regions.

4. The method of claim 3, wherein identifying background regions of the image comprises applying a kernel to each of a plurality of areas of the image to assign each pixel within the kernel to a floor value selected based on the values of image pixels within the kernel to obtain a first intermediate image, and identifying background regions as regions of the image assigned to the floor value.

5. The method of claims 3 or 4, wherein the threshold is selected based on the variance of the image in the background regions, for example based on the standard deviation of the image in the background regions.

6. The method of any preceding claim wherein the edge image data is based on at least one filtered version of the image.

7. The method of claim 6 wherein the at least one filtered version of the image comprises a high pass filtered version of the image.

8. The method of claim 7 wherein the high pass filtered version of the image is obtained using a filter having a transfer function selected to enhance edge detail, for example a difference-of-Gaussians, Mexican-Hat, or log-Gabor transfer function.

9. The method of claim 6 wherein the at least one first filtered version of the image comprises a first filtered version of the image and a second filtered version of the image, and identifying the edges in the edge image data comprises subtracting the first filtered version of the image from the second filtered version of the image.

10. The method of any preceding claim, wherein the image of the DNA comet comprises an image of a DNA electrophoresis assay having an electrophoresis direction associated with the direction of the electric field applied to perform said electrophoresis; and the method comprises disregarding candidate comets having a largest dimension which is not aligned with the electrophoresis direction.

11. The method of any preceding claim, wherein the suprathreshold region comprises a comet head corresponding to the area within the circular edge and a comet tail corresponding to the suprathreshold region outside the circular edge; and the method comprises disregarding candidate comets having a comet head of greater area than the comet tail.

12. The method of any preceding claim, comprising disregarding candidate comets which overlap an outer boundary of the image data.

13. An apparatus for identifying one or more comets in an image of a DNA comet assay, the apparatus comprising a processor configured to:

obtain edge image data identifying edges of structures in the image;

obtain mask image data identifying suprathreshold regions of the image;

identify one or more candidate comets in the image, wherein the candidate comets each comprise a region of the image which includes both:

(ii) a location of a circular edge identified by the edge image data, and (ii) a location of a suprathreshold region identified by the mask image data, wherein the location of the circular edge in the edge image data is within the suprathreshold region in the mask image data; and identify one or more of said candidate comets as a comet.

14. The apparatus of claim 13 configured to perform the method of any one of claims 1 to 11.

15. The apparatus of claim 13 or 14 comprising a data store, coupled to the processor and storing at least one dataset, wherein the at least one dataset comprises an image, edge image data identifying edges of structures in the image, and mask image data identifying suprathreshold regions ofthe image.

16. The apparatus of claim 15 comprising an interface adapted to receive a plurality of input images and to store, in the data store, a plurality of said datasets wherein the image of each data set comprises one ofthe plurality of input images.

17. The apparatus of any of claims 13 to 16 further comprising an imaging device adapted to obtain an image of a DNA electrophoresis assay.

18. The apparatus of any of claims 13 to 16 comprising a communications interface adapted to make accessible, to the processor, digitally encoded images of a DNA electrophoresis assay.

19. A network server adapted to receive, over the network, at least one image of a DNA comet assay, and comprising a processor configured to:

obtain, from the at least one image, edge image data identifying edges of structures in the image, and mask image data identifying suprathreshold regions of the image;

and to identify one or more candidate comets in the image, wherein the one or more candidate comets each comprise a region ofthe image which includes both:

(iii) a location of a circular edge identified by the edge image data, and (ii) a location of a suprathreshold region identified by the mask image data, wherein the location of the circular edge in the edge image data is within the suprathreshold region in the mask image data; and to apply selection criteria to identify one or more of said candidate comets as a comet, and to disregard the remaining candidate comets.

20. The server of claim 19, wherein the server is configured to disregard candidate comets with a threshold region having an area less than a threshold value.

21. The server of claim 19 or 20, in which obtaining mask image data comprises identifying background regions of the image, and selecting a threshold based on the intensity of the image in the background regions wherein the suprathreshold regions of the mask image data comprise areas of the image having an intensity greater than the selected threshold.

22. The server of claim 21, wherein identifying background regions of the image comprises applying a kernel to each of a plurality of areas of the image to assign each pixel within the kernel to a floor value selected based on the values of image pixels within the kernel to obtain a first intermediate image, and identifying background regions as regions of the image assigned to the floor value.

23. The server of claims 21 or 22, wherein the threshold is selected based on the variance of the image in the background regions, for example based on the standard deviation of the image in the background regions.

24. The server of any of claims 19 to 23 wherein the edge image data is based on at least one filtered version of the image.

25. The server of claim 24 wherein the at least one filtered version of the image comprises a high pass filtered version of the image.

26. The server of claim 25 wherein the high pass filtered version of the image is obtained using a filter having a transfer function selected to enhance edge detail, for example a difference-of-Gaussians, Mexican-Hat, or log-Gabor transfer function.

27. The server of claim 24 wherein the at least one first filtered version of the image comprises a first filtered version of the image and a second filtered version of the image, and identifying the edges in the edge image data comprises subtracting the first filtered version of the image from the second filtered version of the image.

28. The server of claims 19 or 27, wherein the image of the DNA comet assay comprises an image of a DNA electrophoresis assay having an electrophoresis direction associated with the direction of the electric field applied to perform said electrophoresis; and the method comprises disregarding candidate comets having a largest dimension which is not aligned with the electrophoresis direction.

29. The server of claims 19 or 28, wherein the suprathreshold region comprises a comet head corresponding to the area within the circular edge and a comet tail corresponding to the suprathreshold region outside the circular edge; and the method comprises disregarding candidate comets having a comet head of greater area than the comet tail.

30. The server of claims 19 or 28, comprising disregarding candidate comets which overlap an outer boundary of the image data.

31. A method of evaluating DNA damage in a cell, comprising:

identifying a comet in an image of a DNA comet assay using the method of any of claims 1 to 12, the apparatus of any of claims 1 to 13 or the server of claim 19; and evaluating DNA damage of the comet based on the spatial distribution of image intensity within the comet.

32. The method of claim 31, wherein evaluating DNA damage of the comet comprises assigning a DNA damage value.

33. The method of claim 31 or 32 wherein the cell is a sperm cell.

34. A method for determining the fertility status of a male subject, comprising evaluating DNA damage in a DNA comet assay of a sperm sample obtained from the subject using the method of claim 33; and assessing the fertility status based upon the DNA damage of the sperm comet.

35. The method of claim 34, wherein assessing the fertility status comprises comparing the DNA damage value to one or more fertility threshold values.

36. The method of claim 35, wherein a fertility threshold value of 0-25% indicates that the male subject is fertile.

37. The method of claim 35 or 36, wherein a fertility threshold value of greater than 25% indicates that the male subject has a high risk of infertility.

38. The method of any of claims 34 to 37 further comprising selecting an assisted reproductive treatment (ART).

39. The method of claim 38, wherein in vitro fertilisation (IVF) is selected when the DNA damage value is 25-50%.

40. The method of claim 39, wherein intra-cytoplasmic sperm injection (ICSI) is selected when the DNA damage value is greater than 50%.

41. A method for the prognosis of pregnancy outcome, comprising:

evaluating DNA damage in a DNA comet assay of a sperm sample obtained from the subject using the method of claim 31 or 32; and making a prognosis of pregnancy outcome based upon the DNA damage of the comet.

42. The method of claim 41, wherein making a prognosis of pregnancy outcome comprises comparing the DNA damage value to one or more threshold values.

43. A method for the prediction of fertility of a male subject, the method comprising: reading computer readable data to obtain a sperm DNA damage indicator obtained from a sample from the subject;

comparing the sample sperm DNA damage indicator to a comparator value; and predicting that the subject is fertile in the event that the sample sperm DNA damage indicator is lower than the comparator value.

44. The method according to claim 43, wherein the sample sperm DNA damage indicator is a measure of central tendency, optionally wherein the measure of central tendency is a mean.

45. The method according to claim 43 or 44, wherein the comparator value is between about 20% and 30%, for example between about 21% and 29%, between about 22% and 28%, between about 23% and 27%, or between about 24% and 26%.

46. The method according to any one of the claims 43-45, wherein the comparator value is about 25%.

47. The method according to claim 43, wherein the method comprises:

reading from a computer memory a plurality of sperm DNA damage indicators obtained from the sample, wherein the plurality of sperm DNA damage indicators define values of a frequency distribution of sperm DNA damage of the sample; and comparing the plurality of sperm DNA damage indicators to a comparator frequency distribution.

48. The method according to claim 47, wherein the comparator frequency distribution has an exponential form, for example a form which decreases exponentially as a function of increasing DNA damage value.

49. The method according to claim 47 or 48, wherein the comparator value is between about 15% and 25%, for example between about 16% and 24%, between about 17% and 23%, between about 18% and 22%, between about 19% and 23%, between about 20% and 22%, or between about 21 % and 22%.

50. The method according to any one of claims 47 to 49, wherein the comparator value is about 20%.

51. The method according to any one of claims 47 to 50, wherein at least about 20%, at least about 25%, at least about 30%, at least about 35%, at least about 40%, at least about 45%, at least about 50%, at least about 55%, or at least about 60% of the plurality of sperm DNA damage indicators are lower than the comparator value.

52. The method according to any one of claims 47 to 51, wherein the comparator value is about 20%, and wherein at least about 30% of the plurality of sperm DNA damage indicators are lower than the comparator value.

53. The method according to any one of claims 47 to 51, wherein the comparator value is about 20%, and wherein at least about 50% of the plurality of sperm DNA damage indicators are lower than the comparator value.

54. The method according to any one of claims 43 to 53, wherein the sample sperm DNA damage indicator is obtained using a DNA comet assay.

55. The method according to any one of claims 43 to 54, further comprising:

reading computer readable data to obtain a Total Antioxidant Capacity (TAC) value obtained from the sample;

comparing the sample TAC value to a threshold TAC value; and predicting that the subject is fertile in the event that the sample TAC value is greater than the threshold TAC value.

56. The method according to claim 55, wherein the threshold TAC value is 129 μΜ Trolox Equiv./L

57. The method according to any one of claims 43-56, further comprising:

reading computer readable data to obtain a Total Oxidant Status (TOS) value obtained from the sample;

comparing the sample TOS value to a threshold TOS value; and predicting that the subject is fertile in the event that the sample TOS value is lower than the threshold TOS value.

58. The method according to claim 57, wherein the threshold TOS value is 200 pmol H2O2 Equiv./L.

59. The method according to any one of claims 43 to 58, further comprising:

reading computer readable data to obtain a TOS/TAC ratio obtained from the sample;

comparing the sample TOS/TAC ratio to a threshold TOS/TAC ratio; and predicting that the subject is fertile in the event that the sample TOS/TAC ratio is lower than the threshold TOS/TAC ratio.

60. The method according to claim 59, wherein the threshold TOS/TAC ratio is 2.

61. The method according to any one of claims 43-60, wherein the sample is a semen sample.

62. The method according to any one of claims 43-61, wherein the sample is a processed semen sample, for example a semen sample processed by density centrifugation.

63. The method according to any one of claims 43-62, wherein the sample is a semen sample processed for assisted conception.

64. The method according to any one of claims 55 to 60 or any one of claims 61 to 63 when dependent on any one of claims 55 to 60, wherein the TAC value and/or TOS value is obtained from seminal plasma.

65. The method according to any one of claims 43-64, wherein the male subject is a human male subject.

66. A computer-implemented method for the prediction of fertility of a male subject, the method comprising:

reading from a computer memory sperm DNA damage data indicating a population distribution of DNA damage values obtained from a sample of sperm DNA from the subject;

determining at least one percentage of the population distribution having sperm DNA damage values of less than a selected threshold level; and predicting, based on the at least one percentage, whether the subject is fertile.

67. An apparatus for predicting that a male subject is fertile, the apparatus comprising a processor configured to:

read computer readable data to obtain a sperm DNA damage indicator obtained from a sample from the subject;

compare the sperm DNA damage indicator to a comparator value; and predict that the subject is fertile in the event that the sample sperm DNA damage indicator is lower than the comparator value.

68. The apparatus of claim 67 configured to perform the method of any one of claims 43 to 65.

69. The method according to any one claims 43 to 66 or the apparatus according to claim 67 or 68, wherein fertility is the ability to achieve spontaneous conception.

70. The method according to any one of claims 43 to 66 or 69, further comprising administering a fatherhood planning composition to the male subject when he is indicated to be fertile.

71. The method according to claim 70, wherein the fatherhood planning composition comprises one or more antioxidants.

72. A fatherhood planning composition for use in the treatment of a fertile male subject, wherein the method comprises identifying a fertile male subject using the method of any one of claims 43 to 66 or 69, and administering the fatherhood planning composition.

73. The composition for use according to claim 72, wherein the fatherhood planning composition comprises one or more antioxidants.