We showed that shape, size, irregularity of edges, the amount of hemoglobin and bilirubin and inhomogeneity of the initial hemoglobin distribution, as well as diffusivity of chromophores [15
], all affect the temporal behavior of simulated bruises. An important consequence is that the observed hemoglobin and bilirubin areas in time vary non-intuitively, so a direct relation between color and age of bruises cannot be assessed, confirming clinical observations [1
]. Thus, understanding individual bruise behavior is impossible without a sophisticated computational model, based on the actual skin pathophysiology. Trends simulated with such models give important information of bruises which cannot easily, if at all, be determined in a clinical setting.
We addressed possible consequences of a nonhomogeneous hemoglobin distribution in the initial blood pool. Such non-homogeneities can be expected when a vessel, or multiple vessels, ruptures at bruise onset and a nonhomogeneous hemoglobin distribution is formed with several areas of high and low concentrations of hemoglobin. We show differences in temporal behavior between bruises with an inhomogeneous gaussian input blood shape and a homogeneous input shape, either of equal area or equal blood volume at bruise onset, indicating that neither the initial area nor the initial blood volume can be used as a single parameter to characterize bruise development. The age determination of inhomogeneous distributed bruises shows the need for taking into account the inhomogeneity of the initial blood pool; in this way the age of the old (simulated) bruise could still be accurately determined. Previously [15
], we determined the age of clinical bruises from the measured hemoglobin and bilirubin areas as a function of time from the moment of first presentation, taking the chromophore concentrations as a constant over the whole area. Although we assessed the spatial distribution of hemoglobin and bilirubin in all measurements [Fig 3 of 16
], this information was not incorporated in the age determination procedure. We emphasize, however, that the irregularities of the bruise edge were taken into account here.
Importantly, we hypothesize that the presented method of age determination of a gaussian input blood pool can serve as a blueprint for future age determinations. Most likely, this requires two steps: first, decomposition of the measured hemoglobin concentration spatial distribution in a set of gaussian functions; and second, construction of a set of blood pool distributions at t = 0 h by enlarging each diameter of the set of functions by factors such as 1.1, 1.2, etc., and simulating bruise development (inhomogeneous hemoglobin and bilirubin distributions) for each choice, until the best agreement between measured and calculated outcomes has been achieved. We are confident that this approach will increase the accuracy of bruise age determination although this obviously has still to be proven.
The visibility of the two compounds in a bruise considered here (hemoglobin and bilirubin) depends on each other; because the two compounds often are both present. The spectra of hemoglobin and bilirubin overlap and an observed color green can mistakenly be attributed to biliverdin [7
], as biliverdin is rapidly converted into bilirubin [6
]. Although visually hemoglobin and bilirubin are difficult to distinguish, when a bruise is measured using reflectance spectroscopy, the compounds can be identified by using a fitting algorithm on the measured spectrum [12
]. A fourth compound sometimes present in bruises is hemosiderin, present in the late phase of the bruise [7
]. We have not considered this compound in our analysis, as the mechanism for hemosiderin production is unclear [6
A limitation of the optics-based methodology is that edge irregularities at hemoglobin blood pool at onset cannot be identified easily in “old” bruises, and certainly not when virtually no hemoglobin is present any more because these irregularities fade away in the bilirubin spatial distribution. Thus, optics-based methodology unlikely can accurately assess the age of “old” bruises where little hemoglobin is still present.
In this paper we focused on the implications of various blood pool properties at onset. Clearly, this is not the only factor influencing the temporal behavior of bruises. Factors such as tissue edema or gravity may also play a role, but as discussed previously [15
], these factors are not (yet) included in the model at this stage. Also, the extent of the trauma to the skin may play a role, as damaged structures cause increased diffusivity of chromophores. All these factors need to be incorporated in the model and considered in future research to estimate their influence on the temporal behavior of bruises.
Multiple (confluent) bruises caused by an additional abuse before the first bruise has healed were not simulated, although the model does allow the addition of a second blood pool [15
]. We felt there is insufficient pathophysiology knowledge available here. For example, how can we get knowledge on the hemoglobin concentration of the second bruise when formed on top of an existing bruise with already decreasing hemoglobin content? Also, what are the hemoglobin and bilirubin diffusivities and the Michaelis–Menten kinetics parameters if such abuses occur frequently and wound healing may have adapted to this situation, e.g. by a faster healing sequence as is shown to occur in experimental animal wounds [2
]. Nevertheless, when more information becomes available, confluent bruises can easily be simulated by our code, which hopefully results in identifying criteria for recognition of multiple abuse events and the time difference between such events.
In conclusion, bruise behavior depends non-intuitively on a large number of bruise and skin parameters. Hence, it would be expected that color behavior would not reveal the age of bruises with any accuracy. Understanding bruise behavior requires a sophisticated computational model of bruise pathophysiology that accounts for all these variables. Future age determination, including inhomogeneous hemoglobin distributions, will likely be based on the presented method for gaussian distributions.