Double Mammary In Situ: Predicting Feasibility of Right Mammary Artery In Situ for Circumflex Coronary Artery System
Margaryan, R.; Della Latta, D.; Bianchi, G.; Martini, N.; Gori, A.; Ripoli, A.; Solinas, M.
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ObjectivesDouble (bilateral) mammary artery in situ revascularization seems less attractive to surgeons because of limited mammary length of right mammary artery, scare, or no means of its length estimation. MethodsWeve selected patients who have used bilateral mammary artery for revascularization and divvied them into two groups: in situ and y-graft groups. We have used preoperative chest x-rays to build a predictive model with neural networks that could predict feasibility of in situ bilateral mammary revascularization. ResultsThe predictive model was able to predict a positive outcome with 96% percent accuracy (p < 0.01). Models sensitivity and specificity were 96% and 95% respectively. Neural networks can be used to predict double mammary feasibility using chest x-rays. Model is capable of predicting positive outcomes with 95% accuracy. ConclusionsChest x-ray base model can accurately predict the feasibility of in situ bilateral mammary artery revascularization.
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