Voxel-wise body composition analysis using image registration of a three-slice CT imaging protocol: methodology and proof-of-concept studies

BACKGROUND

Computed tomography (CT) is an imaging modality commonly used for studies of internal body structures and very useful for detailed studies of body composition. The aim of this study was to develop and evaluate a fully automatic image registration framework for inter-subject CT slice registration. The aim was also to use the results, in a set of proof-of-concept studies, for voxel-wise statistical body composition analysis (Imiomics) of correlations between imaging and non-imaging data.

METHODS

The current study utilized three single-slice CT images of the liver, abdomen, and thigh from two large cohort studies, SCAPIS and IGT. The image registration method developed and evaluated used both CT images together with image-derived tissue and organ segmentation masks. To evaluate the performance of the registration method, a set of baseline 3-single-slice CT images (from 2780 subjects including 8285 slices) from the SCAPIS and IGT cohorts were registered. Vector magnitude and intensity magnitude error indicating inverse consistency were used for evaluation. Image registration results were further used for voxel-wise analysis of associations between the CT images (as represented by tissue volume from Hounsfield unit and Jacobian determinant) and various explicit measurements of various tissues, fat depots, and organs collected in both cohort studies.

RESULTS

Our findings demonstrated that the key organs and anatomical structures were registered appropriately. The evaluation parameters of inverse consistency, such as vector magnitude and intensity magnitude error, were on average less than 3 mm and 50 Hounsfield units. The registration followed by Imiomics analysis enabled the examination of associations between various explicit measurements (liver, spleen, abdominal muscle, visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), thigh SAT, intermuscular adipose tissue (IMAT), and thigh muscle) and the voxel-wise image information.

CONCLUSION

The developed and evaluated framework allows accurate image registrations of the collected three single-slice CT images and enables detailed voxel-wise studies of associations between body composition and associated diseases and risk factors.

Psychosocial work conditions and prediabetes risks: a cross-sectional study in middle-aged men and women

Prediabetes is a condition between diabetes and normoglycemia, and is a state of major health concern, as a large proportion of people with prediabetes are likely to develop diabetes which is associated with high mortality and morbidity. The purpose of this study was to investigate whether adverse psychosocial work conditions, based on the Job Demand-Control-social support model, increases risk for early dysregulated glucose metabolism in 50-64-year-old men and women. Job conditions were measured with the Swedish Demand-Control-Support questionnaire. Impaired glucose metabolism was assessed by an oral glucose tolerance test. Differences between groups were analyzed with Chi-square test and one-way ANOVA with Bonferroni post-hoc test. Odds ratios (OR) and 95% confidence intervals (95% CI) between Job Demand-control-support and prediabetes outcome were calculated with multiple logistic regression. Results from an adjusted logistic regression model showed that in men and woman separately, an active work situation (high demands-high control) was associated with significantly lower prediabetes risk (OR 0.657, 95% CI 0.513-0.842). This finding is consistent through all logistic regression models with different levels of adjustments. Further, the current study does not lend support for the hypothesis that work conditions characterized by high demands-low control were associated with dysregulated glucose metabolism in men nor women despite accumulation of many life-style related risk factors in the high strain group. In conclusion, we could show that men and women assessing their work conditions as active, had lower risk for prediabetes.