  Excessive loads near wounds produce pathological scarring and other
complications. Presently, stress cannot easily be measured by surgeons in the
operating room. Instead, surgeons rely on intuition and experience. Predictive
computational tools are ideal candidates for surgery planning. Finite element
(FE) simulations have shown promise in predicting stress fields on large skin
patches and complex cases, helping to identify potential regions of
complication. Unfortunately, these simulations are computationally expensive
and deterministic. However, running a few, well-selected FE simulations allows
us to create Gaussian process (GP) surrogate models of local cutaneous flaps
that are computationally efficient and able to predict stress and strain for
arbitrary material parameters. Here, we create GP surrogates for the
advancement, rotation, and transposition flaps. We then use the predictive
capability of these surrogates to perform a global sensitivity analysis,
ultimately showing that fiber direction has the most significant impact on
strain field variations. We then perform an optimization to determine the
optimal fiber direction for each flap for three different objectives driven by
clinical guidelines. While material properties are not controlled by the
surgeon and are actually a source of uncertainty, the surgeon can in fact
control the orientation of the flap. Therefore, fiber direction is the only
material parameter that can be optimized clinically. The optimization task
relies on the efficiency of the GP surrogates to calculate the expected cost of
different strategies when the uncertainty of other material parameters is
included. We propose optimal flap orientations for the three cost functions and
that can help in reducing stress resulting from the surgery and ultimately
reduce complications associated with excessive mechanical loading near wounds.
