## 3 Results  
Baseline demographical and clinical characteristics of the study population are summarized in Table 1.  
From the 187 patients included in the current study, baseline geometries of 480 arteries were used for blood flow and LDL transport modeling. The final dataset included 174 RCAs, 162 LADs, and 144 LCXs. A total of 4000 3 mm segments were finally analyzed for baseline imaging characteristics, modeling results, and changes from baseline to follow-up. To our knowledge, this is the largest dataset, where blood flow and LDL transport modeling is performed for the prediction of atherosclerotic progression. A post-hoc power analysis was performed to calculate the power of our population for the prediction of atherosclerotic disease progression. We used an effect size \(\ell^{2}\) = 0.135 based on the calculation of \(\tau^{2}\); a = 0.05; total sample size of 187 patients (4000 arterial segments); max 15 tested predictors included in the final model for multiple linear regression analysis. Based on these, we observe that the model is not able to predict the response of the disease progression.  
\begin{table}
\begin{tabular}{c c} \hline \hline  & **All Patients (N = 187)** \\ \hline Age (years) & 60.73 \(\pm\) 8.11 \\ Gender (male) & 107 (57.2\%) \\ BMI & 27.31 \(\pm\) 3.52 \\ Current smoker & 25 (13.4\%) \\ Family history of CAD & 92 (49.2\%) \\ \hline
**Risk factors** & \\ \hline Diabetes mellitus & 27 (14.4\%) \\ Hypertension & 111 (59.4\%) \\ Dyslipidemia & 127 (67.9\%) \\ Obesity & 33 (17.6\%) \\ \hline
**Clinical presentation *** & \\ \hline Atypical angina & 86 (46.0\%) \\ Typical angina & 48 (25.7\%) \\ Other symptoms & 22 (11.8\%) \\ No symptoms & 12 (6.4\%) \\ \hline
**Imaging presentation** & \\ \hline No CAD & 47 (25.1\%) \\ \hline Non-obstructive CAD & 113 (60.4\%) \\ \hline Obstructive CAD & 27 (14.4\%) \\ \hline
**Biohumoral data** & \\ \hline Total cholesterol & 190.60 \(\pm\) 49.50 \\ Low density lipoprotein (LDL) cholesterol & 114.09 \(\pm\) 42.39 \\ High density lipoprotein (HDL) cholesterol & 54.27 \(\pm\) 17.37 \\ Triglycerides & 112.79 \(\pm\) 57.03 \\ Glucose & 105.50 \(\pm\) 24.04 \\ \hline
**Studied vessels** & **(n = 480)** \\ \hline Left anterior descending artery & 162 (33.75\%) \\ Left circumflex coronary artery & 144 (30.00\%) \\ Right coronary artery & 174 (36.25\%) \\ \hline
**Medications at discharge** & \\ \hline Aspirin & 100 (53.77\%) \\ ARB & 32 (17.1\%) \\ Beta-blockers & 67 (35.8\%) \\ ACE inhibitors & 50 (26.7\%) \\ Calcium channel blockers & 28 (15.0\%) \\ Statins & 85 (45.5\%) \\ \hline \hline \end{tabular} BMI, body mass index; CAD: coronary artery disease; ARB, Angiotensin II Receptor Blockers; ACE, Angiotensin-converting enzyme. * Clinical classification was based on European Society of Cardiology (ESC) guidelines [17].  
\end{table}
Table 1: Baseline demographics, clinical and biohumoral data.  
power = 0.90. A patient example with ESS and LDL concentration results is shown in Figure 2.  
Average values of imaging variables including lumen area, plaque volume and plaque burden for the 4000 analyzed coronary segments are reported for baseline and follow up CCTA scans in Table 2 together with computational modeling results at baseline.