Distinct bone metabolic networks identified in 1 mice vs. wild type mice using [F]FDG total-body PET.

INTRODUCTION

Total-body PET is a recent development in clinical imaging that produces large datasets involving multiple tissues, enabling the use of new analytical methods for multi-organ assessments, such as network analysis-a well-developed method in neuroimaging. The skeletal system provides a good model for applying network analysis to total-body PET, as bone serves many classical whole-body functions as well as being an endocrine regulator of metabolism. Previous reports have suggested an association between the expression of bone-specific phosphatase, orphan 1 and disorders of altered energy metabolism such as obesity and diabetes. Here, we explore how lacking phosphatase, orphan 1 affects the skeletal metabolic networks of mice as a test approach for deploying network analysis in total-body PET.

METHODS

We retrospectively analysed [F]fluorodeoxyglucose total-body PET/CT images from six 13-week-old wild type mice, three 22-week-old wild type mice, and three 22-week-old mice. Pearson correlation networks were created using the dynamic data from seven bone regions, with a Pearson threshold of >0.6 (significant at < 0.005).

RESULTS

The bone metabolic networks of 13-week-old wild type mice were found to robustly resist changes to the data from different PET measurements, increased noise, and shortened scan length. Key features were repeatedly observed, namely that all bones except the spine are highly inter-correlated, while the spine has minimal correlation to other bones. When network analysis was used to compare the three cohorts, the older wild type network had similar features to the young mouse, whereas the network had increased correlations across all bones. An all-cohort network separated the data into one part including only bones from the wild type mice (13 nodes) and one part only bones from the mice (8 nodes, 95% separation purity). Within the wild type section, the same bone from each young and old mouse were correlated.

DISCUSSION

We demonstrated network analysis is a promising method for studying whole-body PET, sensitive to dynamic details in the data without relying on assumptions or modelling. The proposed method could be applied to other total-body PET data-of healthy and diseased subjects, with different radiotracers, and more-to further elucidate tissue interactions at a systems level.