Key result
Automatic multi-atlas VAT segmentation shows excellent agreement with manual measurement.
Why the study?
Visceral adipose tissue volume is a predictive and prognostic factor for many cancers, but automatic measurement methods from CT images are needed.
Does an automatic multi-atlas segmentation method accurately measure total visceral adipose tissue volume from CT images compared to manual segmentation?
Does an automatic multi-atlas segmentation method accurately measure total visceral adipose tissue volume from CT images compared to manual segmentation?
An automatic multi-atlas segmentation method can accurately measure whole abdominopelvic visceral adipose tissue from CT images, showing excellent correlation with manual segmentation.
May support automated visceral adipose tissue quantification on CT; leaves open clinical adoption pending larger validation.
BACKGROUND: The visceral adipose tissue (VAT) volume is a predictive and/or prognostic factor for many cancers. The objective of our study was to develop an automatic measurement of the whole VAT volume using a multi-atlas segmentation (MAS) method from a computed tomography. METHODS: A total of 31 sets of whole-body computed tomography volume data were used. The reference VAT volume was defined on the basis of manual segmentation (VATMANUAL). We developed an algorithm, which measured automatically the VAT volumes using a MAS based on a nonrigid volume registration algorithm coupled with a selective and iterative method for performance level estimation (SIMPLE), called VATMAS_SIMPLE. The results were evaluated using intraclass correlation coefficient and dice similarity coefficients. RESULTS: The intraclass correlation coefficient of VATMAS_SIMPLE was excellent, at 0.976 (confidence interval, 0.943-0.989) (P < 0.001). The dice similarity coefficient of VATMAS_SIMPLE was also good, at 0.905 (SD, 0.076). CONCLUSIONS: This newly developed algorithm based on a MAS can measure accurately the whole abdominopelvic VAT.
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Decazes et al. (2017) studied this question. Automatic measurement of VAT using multi-atlas segmentation (VATMAS_SIMPLE) vs. Manual segmentation (VATMANUAL) was evaluated on Intraclass correlation coefficient for VAT volume measurement (ICC 0.976, 95% CI 0.943-0.989, p=<0.001). Automatic measurement of visceral adipose tissue using a multi-atlas segmentation method showed excellent agreement with manual segmentation (ICC 0.976; 95% CI 0.943-0.989; P<0.001).
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