Algorithmic estimation of adrenal volume based on body weight and CT landmarks in dogs.

Abstract

Computed tomographic (CT) methods for quantifying adrenal size are helpful for identifying and directing management of adrenal disease in dogs. This retrospective, observational study aimed to use CT to determine anatomic landmarks associated with adrenal gland volume in dogs, and subsequently develop an algorithm to estimate adrenal volume for individual subjects. Abdominal CT images from 150 dogs without adrenal disease were assessed. The volume of the left and right adrenals, as well as dimensions from anatomic structures, were measured. Predictive models for adrenal volume were examined with cross validation. A further 29 dogs were used for external validation and model fit. Dogs in the test cohort weighed from 3.1 to 67.5kg (mean 24.4kg) with left (VLA ) and right (VRA ) adrenal volume ranging from 0.23 to 2.84 cm3 (mean 1.22 cm3 ) and 0.14 to 2.97 cm3 (mean 1.11 cm3 ), respectively. A predictive model for each adrenal based on weight (W) and L1 height (HL1 ) best explained the adrenal volume, with external validation confirming model fit. The final models, adjusted for bias, were: VLA =0.154 + (0.02 × W) + (0.07 × HL1 ) (adjR2 =0.62); and VRA =-0.116 + (0.02 × W) + (0.06 × HL1 ) (adjR2 =0.64). In dogs undergoing CT, these algorithms can be used to estimate expected adrenal volume and allow comparison with the actual volume measured on CT, facilitating interpretation of CT findings, and clinical decision-making.