Abstract : Airway remodeling in asthma patients has been studied in vivo by means of endobronchial biopsies allowing to assess structural and inflammatory changes. However, this technique remains relatively invasive and difficult to use in longitudinal trials. The development of alternative non-invasive tests, namely exploiting high-resolution imaging modalities such as MSCT, is gaining interest in the medical community. This paper develops a fullyautomated airway shape assessment approach based on the 3D segmentation of the airway lumen from MSCT data. The objective is to easily notify the radiologist on bronchus shape variations (stenoses, bronchiectasis) along the airway tree during a simple visual investigation. The visual feed-back is provided by means of a volumerendered color coding of the airway calibers which are robustly defined and computed, based on a specific 3D discrete distance function able to deal with small size structures. The color volume rendering (CVR) information is further on reinforced by the definition and computation of a shape variation index along the airway medial axis enabling to detect specific configurations of stenoses. Such cases often occur near bifurcations (bronchial spurs) and they are either missed in the CVR or difficult to spot due to occlusions by other segments. Consequently, all detected shape variations (stenoses, dilations and thickened spurs) can be additionally displayed on the medial axis and investigated together with the CVR information. The proposed approach was evaluated on a MSCT database including twelve patients with severe or moderate persistent asthma, or severe COPD, by analyzing segmental and subsegmental bronchi of the right lung. The only CVR information provided for a limited number of views allowed to detect 78% of stenoses and bronchial spurs in these patients, whereas the inclusion of the shape variation index enabled to complement the missing information.