Validation of a semi-automated technique to accurately measure abdominal fat distribution using CT and MRI for clinical risk stratification

Objective: A valid method for accurate quantification of abdominal fat distribution (AFD) using both CT and MRI is described. This method will be primarily useful in the prospective risk stratification of patients undergoing reconstructive breast surgery. Secondary applications in many other clinical specialities are foreseen.

Methods: 15 sequential patients who had undergone breast reconstruction following both CT and MRI (30 scans) were retrospectively identified at our single centre. The AFD was quantified at the level of the L3 vertebra. Image analysis was performed by at least two independent operators using free software. Intra- and interobserver differences were assessed using Bland–Altman plots. Data were validated between imaging modalities by Pearson's correlation. Linear regression analyses were used to mathematically normalize results between imaging modalities.

Results: The method was statistically independent of rater bias (intra: Pearson's R—0.954–1.00; inter: 0.799–0.999). Strong relationships between imaging modalities were demonstrated and are independent of time between imaging (Pearson's R 0.625–0.903). Interchangeable mathematical models to normalize between imaging modality are shown.

Conclusion: The method described is highly reproducible and independent of rater bias. A strong interchangeable relationship exists between calculations of AFD on retrospective CT and MRI.

Advances in knowledge: This is the first technique to be applicable to scans that are not performed sequentially or in a research setting. Analysis is semi-automated and results can be compared directly, regardless of imaging modality or patient position. This method has clinical utility in prospective risk stratification and will be applicable to many clinical specialities.