As a subclass of interstitial lung diseases, fibrosing idiopathic interstitial pneumonia (IIP), whose cause is mostly unknown, is a continuous and irreversible process, manifesting as progressive worsening of lung function. Quantifying the evolution of the patient status imposes the development of automated CAD tools to depict the pathology occurrence in the lung but also an associated severity degree. In this paper we propose several biomarkers for IIP quantification, associating spatial localization of the disease using lung texture classification, and severity measures in relation with vascular and bronchial remodeling which correlate with clinical parameters. We follow-up our work on lung texture analysis based on convolutional neural networks (reporting an increased performance in sensitivity, specificity and accuracy) on an enlarged training/testing database (110/20 patients respectively). The area under the curve (AUC:2-6) for vessel calibers distribution between 2-6 mm radii (evaluated in 70 patients) showed up as a promising biomarker of the severity of the disease, independently of the extent of lesions, correlating with the composite physiologic index. In the same way, normalized airway lobe length, normalized airway lobe volume and the score of distal airway caliber deviation from the physiologically power decrease law correlated with radiologic severity score, manifesting as potential biomarkers of traction bronchiectasis (assessment in 18 patients).