摘要：Different types of adipose tissue can be accurately localized and quantified by tomographic imaging techniques (MRI or CT). One common shortcoming for the abdominal subcutaneous adipose tissue (ASAT) of obese subjects is the technically restricted imaging field of view (FOV). This work derives equations for the conversion between six surrogate measures and fully segmented ASAT volume and discusses the predictive power of these image-based quantities. Clinical (gender, age, anthropometry) and MRI data (1.5 T, two-point Dixon sequence) of 193 overweight and obese patients (116 female, 77 male) from a single research center for obesity were analyzed retrospectively. Six surrogate measures of fully segmented ASAT volume (VASAT) were considered: two simple ASAT lengths, two partial areas (Ap-FH, Ap-ASIS) and two partial volumes (Vp-FH, Vp-ASIS) limited by either the femoral heads (FH) or the anterior superior iliac spine (ASIS). Least-squares regression between each measure and VASAT provided slope and intercept for the computation of estimated ASAT volumes (V~ASAT). Goodness of fit was evaluated by coefficient of determination (R2) and standard deviation of percent differences (sd%) between V~ASAT and VASAT. Best agreement was observed for partial volume Vp-FH (sd% = 14.4% and R2 = 0.78), followed by Vp-ASIS (sd% = 18.1% and R2 = 0.69) and AWFASIS (sd% = 23.9% and R2 = 0.54), with minor gender differences only. Other estimates from simple lengths and partial areas were moderate only (sd% > 23.0% and R2 < 0.50). Gender differences in R2 generally ranged between 0.02 (dven) and 0.29 (Ap-FH). The common FOV restriction for MRI volumetry of ASAT in obese subjects can best be overcome by estimating VASAT from Vp-FH using the equation derived here. The very simple AWFASIS can be used with reservation.
其他摘要：Abstract Different types of adipose tissue can be accurately localized and quantified by tomographic imaging techniques (MRI or CT). One common shortcoming for the abdominal subcutaneous adipose tissue (ASAT) of obese subjects is the technically restricted imaging field of view (FOV). This work derives equations for the conversion between six surrogate measures and fully segmented ASAT volume and discusses the predictive power of these image-based quantities. Clinical (gender, age, anthropometry) and MRI data (1.5 T, two-point Dixon sequence) of 193 overweight and obese patients (116 female, 77 male) from a single research center for obesity were analyzed retrospectively. Six surrogate measures of fully segmented ASAT volume ( V ASAT ) were considered: two simple ASAT lengths, two partial areas ( A p-FH , A p-ASIS ) and two partial volumes ( V p-FH , V p-ASIS ) limited by either the femoral heads (FH) or the anterior superior iliac spine (ASIS). Least-squares regression between each measure and V ASAT provided slope and intercept for the computation of estimated ASAT volumes ( V ~ ASAT ). Goodness of fit was evaluated by coefficient of determination ( R 2 ) and standard deviation of percent differences ( s d% ) between V ~ ASAT and V ASAT . Best agreement was observed for partial volume V p-FH ( s d% = 14.4% and R 2 = 0.78), followed by V p-ASIS ( s d% = 18.1% and R 2 = 0.69) and AWF ASIS ( s d% = 23.9% and R 2 = 0.54), with minor gender differences only. Other estimates from simple lengths and partial areas were moderate only ( s d% > 23.0% and R 2 < 0.50). Gender differences in R 2 generally ranged between 0.02 ( d ven ) and 0.29 ( A p-FH ). The common FOV restriction for MRI volumetry of ASAT in obese subjects can best be overcome by estimating V ASAT from V p-FH using the equation derived here. The very simple AWF ASIS can be used with reservation.
