Growth pattern analysis of murine lung neoplasms by advanced semi-automated quantification of micro-CT images.

ABSTRACT: Computed tomography (CT) is a non-invasive imaging modality used to monitor human lung cancers. Typically, tumor volumes are calculated using manual or semi-automated methods that require substantial user input, and an exponential growth model is used to predict tumor growth. However, these measurement methodologies are time-consuming and can lack consistency. In addition, the availability of datasets with sequential images of the same tumor that are needed to characterize in vivo growth patterns for human lung cancers is limited due to treatment interventions and radiation exposure associated with multiple scans. In this paper, we performed micro-CT imaging of mouse lung cancers induced by overexpression of ribonucleotide reductase, a key enzyme in nucleotide biosynthesis, and developed a

SUBMITTER: Li M 

PROVIDER: S-EPMC3871568 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature