Evaluation of automated computed tomography segmentation to assess body composition and mortality associations in cancer patients.

ABSTRACT:

Background

Body composition from computed tomography (CT) scans is associated with cancer outcomes including surgical complications, chemotoxicity, and survival. Most studies manually segment CT scans, but Automatic Body composition Analyser using Computed tomography image Segmentation (ABACS) software automatically segments muscle and adipose tissues to speed analysis. Here, we externally evaluate ABACS in an independent dataset.

Methods

Among patients with non-metastatic colorectal (n = 3102) and breast (n = 2888) cancer diagnosed from 2005 to 2013 at Kaiser Permanente, expert raters annotated tissue areas at the third lumbar vertebra (L3). To compare ABACS segmentation results to manual analysis, we quantified the proportion of pixel-level image overlap using Jaccard scor

SUBMITTER: Cespedes Feliciano EM 

PROVIDER: S-EPMC7567141 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature