A high-throughput semi-automated bone segmentation workflow for murine hindpaw micro-CT datasets.

ABSTRACT:

Introduction

Micro-computed tomography (μCT) is a valuable imaging modality for longitudinal quantification of bone volumes to identify disease or treatment effects for a broad range of conditions that affect bone health. Complex structures, such as the hindpaw with up to 31 distinct bones in mice, have considerable analytic potential, but quantification is often limited to a single bone volume metric due to the intensive effort of manual segmentation. Herein, we introduce a high-throughput, user-friendly, and semi-automated method for segmentation of murine hindpaw μCT datasets.

Methods

In vivo μCT was performed on male (n = 4; 2-8-months) and female (n = 4; 2-5-months) C57BL/6 mice longitudinally each month. Additional 9.5-month-old male C57BL/6 hindpaws (

SUBMITTER: Kenney HM 

PROVIDER: S-EPMC8816671 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature