CT attenuation changes across freeze–thaw preservation states in donated bodies: a preliminary multi-organ anatomical analysis

To establish the thermal preservation state as a critical pre-analytical variable in quantitative post-mortem CT of donated bodies, with the aim of enabling reliable multi-donor comparisons, improving the performance of automated segmentation tools, and providing a translational experimental model applicable to CT-guided thermal interventions. Eight body donors underwent whole-body CT in up to three preservation states: fresh, frozen (− 20 °C), and thawed. CT datasets were automatically segmented using TotalSegmentator in 3D Slicer. Mean Hounsfield unit (HU) values were extracted for major organs and tissue groups. The primary analysis was within-donor: Friedman tests with Wilcoxon signed-rank post-hoc comparisons in donors with complete data (n = 7), complemented by linear mixed-effects models using all available scans. Freezing produced a consistent reduction in CT attenuation across all soft tissues and muscle, with near-complete recovery after thawing. In the primary repeated-measures analysis, preservation state had a significant effect after FDR correction in six of the nine tissue groups (liver, spleen, brain, aorta, pancreas and muscle; q = 0.023–0.042), but not in kidney, heart or bone. Brain and pancreas showed the strongest effects (Kendall’s W = 0.80 and 0.76). In the liver, the median within-donor change was − 59.7 HU at freezing and + 60.3 HU at thawing. Mixed-effects models confirmed a significant reduction at freezing in liver, spleen, brain, kidney, pancreas and muscle (β = −35.1 to −52.7 HU) and no residual difference after thawing in any tissue group. Bone attenuation remained stable across all preservation states. Freeze–thaw preservation systematically alters CT attenuation in soft tissues while minimally affecting bone. Preservation state should therefore be considered a critical pre-analytical variable in quantitative post-mortem CT, particularly for studies relying on automated segmentation, radiomics, and translational applications involving thermal tissue imaging.