AUTOMATIC QUANTIFICATION FROM CT SCANS OF MORPHOLOGICAL CHANGES IN PULMONARY ARTERIAL VASCULATURE IN PULMONARY ARTERY HYPERTENSION

Date/Time
Date(s) - 03/02/2012
9:00 am - 11:00 am

Ankit Salgia, Masters Student

Pulmonary Arterial Hypertension (PAH) occurs in idiopathic form and is also associated with such diseases as congenital heart malformation, scleroderma, HIV infection, and cirrhosis. Severe PAH is rare but has a dismal prognosis: even contemporary therapy provides only a 75% three-year survival as found in a recent consecutive cohort of patients followed from 1994-2002.

In PAH, small and medium arterioles are progressively occluded by vascular and inflammatory cells. Better, more convenient therapies are needed and such therapeutic advances will require a more thorough understanding of vascular remodeling, right ventricular (RV) compensation, and RV failure. The current methods of studying the disease are not very quantitative. The quantitative extraction of morphology features of the lung pulmonary vasculature is important for the diagnosis of the extent or progression of PAH. This work will help in identify/quantify key biomarkers of disease progression and the efficacy of the emerging drugs used for therapy in rats intended to improve outcome in patients.

The purpose of this work is to develop automated extraction of pulmonary vascular tree features from 3-D CT images and to quantify/identify morphological changes of the vasculature tree in PAH in rats and subsequently it can be used for humans.  We have identified and labeled each branch/bifurcation point. Following centerline extraction, branch length, angle, diameter and tortuosity are computed, along with overall vascular volume and spatial fractile dimension.

In a representative healthy rat lung, over 9,000 branches were extracted, labeled and characterized.  The PAH-diseased lung was found to have large, measurable differences in total vascular volume, spatial fractile dimension, number of branches, distribution of branch radii, average branch radius, distribution of branch lengths, average branch length, and spatial fractile dimension compared with controls.