A system for evaluating tissue characteristics in a patient, comprising: means for obtaining a first image of left ventricle cardiac tissue including a region of interest during a first acquisition; means for obtaining a second image of the left ventricle cardiac tissue including the region of interest during a second, subsequent acquisition; and means for determining a global characteristic of the region of interest of the first image and of the second image so as to allow a comparison of the global characteristic of the first image and the second image to determine a potential for a global cardiac injury of the tissue of the region of interest, wherein a global cardiac injury is a change in tissue composition and/or function that is in a substantially randomly distributed pattern and/or in a pattern that is not detectable at the resolution of the images that are analyzed to detect the injury; wherein determining the global characteristic comprises statistical analysis with a computer system of a characteristic of substantially all of the pixels/voxels, or providing, with a computer system, a histogram of a characteristic of substantially all of the pixel/voxels, in the region of interest; wherein the first and second images are delayed enhancement MRI cardiac images; characterized in that the system includes means for evaluating an autocorrelation coefficient I of substantially all of the pixels in the region of interest, to allow determination of the relationship between the pattern of high intensity pixels, within each image slice of the left ventricle, wherein a high value of I indicates pattern clustering and a low value is indicative of a more random association within the region of interest; and wherein the autocorrelation coefficient I is defined by: I = n ∑ ij δ ij x i − x ̅ x j − x ̅ ∑ ij δ ij ∑ i x i − x ̅ 2 wherein δ ij is a weighting function of the distance between pixels i and j defined by δ ij = exp − 1 2 d x i x j, where d ( x i, x j) is the Euclidian distance between points x i and x j; n is the number of pixels; and x i is the intensity for the i th pixel. means for obtaining a first image of left ventricle cardiac tissue including a region of interest during a first acquisition; means for obtaining a second image of the left ventricle cardiac tissue including the region of interest during a second, subsequent acquisition; and means for determining a global characteristic of the region of interest of the first image and of the second image so as to allow a comparison of the global characteristic of the first image and the second image to determine a potential for a global cardiac injury of the tissue of the region of interest, wherein a global cardiac injury is a change in tissue composition and/or function that is in a substantially randomly distributed pattern and/or in a pattern that is not detectable at the resolution of the images that are analyzed to detect the injury; wherein determining the global characteristic comprises statistical analysis with a computer system of a characteristic of substantially all of the pixels/voxels, or providing, with a computer system, a histogram of a characteristic of substantially all of the pixel/voxels, in the region of interest; wherein the first and second images are delayed enhancement MRI cardiac images; characterized in that the system includes means for evaluating an autocorrelation coefficient I of substantially all of the pixels in the region of interest, to allow determination of the relationship between the pattern of high intensity pixels, within each image slice of the left ventricle, wherein a high value of I indicates pattern clustering and a low value is indicative of a more random association within the region of interest; and wherein the autocorrelation coefficient I is defined by: I = n ∑ ij δ ij x i − x ̅ x j − x ̅ ∑ ij δ ij ∑ i x i − x ̅ 2 wherein δ ij is a weighting function of the distance between pixels i and j defined by δ ij = exp − 1 2 d x i x j, where d ( x i, x j) is the Euclidian distance between points x i and x j; n is the number of pixels; and x i is the intensity for the i th pixel. characterized in that the system includes means for evaluating an autocorrelation coefficient I of substantially all of the pixels in the region of interest, to allow determination of the relationship between the pattern of high intensity pixels, within each image slice of the left ventricle, wherein a high value of I indicates pattern clustering and a low value is indicative of a more random association within the region of interest; and wherein the autocorrelation coefficient I is defined by: I = n ∑ ij δ ij x i − x ̅ x j − x ̅ ∑ ij δ ij ∑ i x i − x ̅ 2 wherein δ ij is a weighting function of the distance between pixels i and j defined by δ ij = exp − 1 2 d x i x j, where d ( x i, x j) is the Euclidian distance between points x i and x j; n is the number of pixels; and x i is the intensity for the i th pixel.