Data set from the article Lo Rito M, Romarowski RM, Rosato A, Pica S, Secchi F, Giamberti A, Auricchio F, Frigiola A, Conti M. Anomalous aortic origin of coronary artery biomechanical modeling: Toward clinical application. J Thorac Cardiovasc Surg. 2020 Aug 24:S0022-5223(20)32430-2. doi: 10.1016/j.jtcvs.2020.06.150. Epub ahead of print. PMID: 32950237. This is the abstract: Objectives: Anomalous aortic origin of the coronary artery can be associated with sudden cardiac death and ischemic events. Anatomic static characteristics mainly dictated surgical indications, although adverse events are usually related to dynamic physical effort. We developed a computational model able to simulate anomalous coronary behavior, and we aimed to assess its clinical applicability and to investigate coronary characteristics at increasing loading stress conditions. Methods: We selected 5 patients with anomalous aortic origin of the coronary artery and 5 control subjects. For each of them, we construct a 3-dimensional model resembling the aortic root and coronary arteries based on 25 parameters obtained from computed tomography. Structural finite element analysis simulations were run to simulate pressure increasing in the aortic root during exercise (+40 mm Hg, +100 mm Hg with respect baseline condition, assumed at 80 mm Hg) and investigate coronary lumen characteristics. Results: The 25 parameters were obtainable in all subjects with a consistent interobserver agreement. In control subjects, the right coronary artery had a more significant lumen expansion at loading conditions compared with anomalous aortic origin of coronary artery (6%-19.2% vs 1.8%-8.1%, P = .008), which also showed an inability to expand within the intramural segment. Conclusions: The proposed anomalous aortic origin of coronary artery model is able to represent the pathogenic disease mechanism after being populated with patient-specific data. It can assess the impaired expansion of anomalous right coronary at loading conditions, a process that cannot be quantified in any clinical set-up. This first clinical application showed promising results on quantifying pathological behavior, potentially helping in patient-specific risk stratification.