quantitative CT development and clinical applications

National Heart, Lung, And Blood Institute

Investigators

Linked publications & trials

Abstract

This project is the main effort of my lab for the last year. On the clinical application front, we further developed computed-tomography image analysis tools for two clinical protocols: 96-H-0100, LAM and other rare cystic lung diseases, PI Joel Moss, NHLBI Pulmonary Branch We provide weekly CT-derived measurements of the pulmonary cyst burden in LAM patients that visit NIH on a regular basis under this protocol and compile the data into a database for statistical analysis aimed at answering important clinical questions on the diagnosis and prognosis of the disease. This year we developed a fully automatic algorithm to detect and quantify lung nodules in these patients, a hallmark of the disease and an important test that distinguishes different forms of the disease. We also helped Dr. Florian Gothe, a pediatrician from Munich Germany, to characterize pulmonary cysts in his patients with a rare form of genetic disease, using the tools we have developed for LAM. We did the first ever study of the actual accuracy of CT-derived measurement of pulmonary cysts using a chest phantom containing pulmonary cysts, which we designed and fabricated. The study revealed the limitation of CT-based measurements. Although CT has always been the gold standard for quantifying pulmonary cysts, we now have a firm idea of the degree of accuracy of this gold standard. 18-H-0108, Genetic disease ACDC, PI Manfred Boehm, NHLBI Translational Vascular Medicine This protocol studies the rare genetic disease of arterial calcification due to deficiency of CD73, or ACDC. This is a chronic disease. Patients with ACDC have progressive vascular calcification in the extremities and the joints of the hands and feet, with symptoms of pain and cramping in the extremities as early as their twenties. As a collaborator on this protocol, we provide CT-derived quantitative measurements of the amount of calcification in the lower extremity and document the trend of progression over the past 10 to 15 years. We also developed adaptive algorithms to ensure that the measurements are consistent across different scan settings, which is an important requirement for the study of chronic disease that span multiple upgrades of the CT technology.