Coronary arteries are susceptible to atherosclerosis, a chronic inflammation characterized by progressive intimal thickening due to plaque accumulation, leading to lumen constriction. Arterial geometry significantly influences hemodynamics, which in turn is crucial in both the initiation and progression of the disease. Given the key role of vascular geometry, Statistical Shape Modeling (SSM) has emerged as a well-established method for anatomical characterization. This computational approach enables the quantification of anatomical variations and has gained prominence in cardiovascular research for capturing complex morphological features in cardiovascular districts. In this context, this thesis project is aimed at the application of SSM to derive the main pathological shape features of a cohort of diseased Left Anterior Descending (LAD) coronary arteries.