Abstract
Heart mass can be predicted from heart volume as measured from post-mortem computed tomography (PMCT), but with limited accuracy. Although related to heart mass, age, sex, and body dimensions have not been included in previous studies using heart volume to estimate heart mass. This study aimed to determine whether heart mass estimation can be improved when age, sex, and body dimensions are used as well as heart volume. Eighty-seven (24 female) adult post-mortem cases were investigated. Univariable predictors of heart mass were determined by Spearman correlation and simple linear regression. Stepwise linear regression was used to generate heart mass prediction equations. Heart mass estimate performance was tested using median mass comparison, linear regression, and Bland-Altman plots. Median heart mass (P = 0.0008) and heart volume (P = 0.008) were significantly greater in male relative to female cases. Alongside female sex and body surface area (BSA), heart mass was univariably associated with heart volume in all cases (R
= 0.72) and in male (R
= 0.70) and female cases (R
= 0.64) when segregated. In multivariable regression, heart mass was independently associated with age and BSA (R
adjusted = 0.46-0.54). Addition of heart volume improved multivariable heart mass prediction in the total cohort (R
adjusted = 0.78), and in male (R
adjusted = 0.74) and female (R
adjusted = 0.74) cases. Heart mass estimated from multivariable models incorporating heart volume, age, sex, and BSA was more predictive of actual heart mass (R
= 0.75-0.79) than models incorporating either age, sex, and BSA only (R
= 0.48-0.57) or heart volume only (R
= 0.64-0.73). Heart mass can be more accurately predicted from heart volume measured from PMCT when combined with the classical predictors, age, sex, and BSA.