AIM: To assess whether a simple. diameter-based formula applicable to cross-sectional images can be used to calculate the total liver volume. MATERIALS AND METHODS: On 119 cross-sectional examinations (62 computed tomography and 57 magnetic resonance imaging) a simple, formula-based method to approximate the liver volume was evaluated. The total liver volume was approximated measuring the largest craniocaudal (cc), ventrodorsal (vd), and coronal (cor) diameters by two readers and implementing the equation: Vol(estimated)=cc x vd x cor x 0.31. Inter-rater reliability, agreement, and correlation between liver volume calculation and virtual liver volumetry were analysed. RESULTS: No significant disagreement between the two readers was found. The formula correlated significantly with the volumetric data (r>0.85, p<0.0001). In 81% of cases the error of the approximated volume was <10% and in 92% of cases <15% compared to the volumetric data. CONCLUSION: Total liver volume can be accurately estimated on cross-sectional images using a simple, diameter-based equation.
AIM: To assess whether a simple. diameter-based formula applicable to cross-sectional images can be used to calculate the total liver volume. MATERIALS AND METHODS: On 119 cross-sectional examinations (62 computed tomography and 57 magnetic resonance imaging) a simple, formula-based method to approximate the liver volume was evaluated. The total liver volume was approximated measuring the largest craniocaudal (cc), ventrodorsal (vd), and coronal (cor) diameters by two readers and implementing the equation: Vol(estimated)=cc x vd x cor x 0.31. Inter-rater reliability, agreement, and correlation between liver volume calculation and virtual liver volumetry were analysed. RESULTS: No significant disagreement between the two readers was found. The formula correlated significantly with the volumetric data (r>0.85, p<0.0001). In 81% of cases the error of the approximated volume was <10% and in 92% of cases <15% compared to the volumetric data. CONCLUSION: Total liver volume can be accurately estimated on cross-sectional images using a simple, diameter-based equation.
Authors: D Seppelt; M L Kromrey; T Ittermann; C Kolb; A Haubold; N Kampfrath; D Fedders; P Heiss; S Hoberück; R T Hoffmann; J P Kühn Journal: Sci Rep Date: 2022-07-21 Impact factor: 4.996