Purpose <p>Intracerebral hemorrhage (ICH) is a subtype of stroke associated with high morbidity and mortality. Perihematomal edema (PHE), the swelling of brain tissue surrounding hemorrhage, is an independent predictor of risk stratification and prognosis. Therefore, accurate identification and measurement of PHE volume is crucial for clinical decision-making. Currently, PHE measurement relies on conventional computed tomography (CT), which has limited ability to delineate edema boundaries. This retrospective study aimed to evaluate whether electron density (ED) images derived from dual-layer spectral CT improve interobserver agreement and boundary visualization in PHE volume measurement compared with images derived from conventional CT.</p> Methods <p>This retrospective study enrolled 82 patients with ICH who underwent noncontrast head CT using a dual-layer spectral CT scanner between January 2024 and November 2024. Conventional CT and reconstructed ED images were generated for each patient. Two attending radiologists independently measured PHE volume on both image types and assessed PHE boundary clarity. Boundaries were considered clear if more than 50% of the PHE margin was well defined and distinctly visible. PHE boundaries were manually delineated on a 3D postprocessing workstation. Interobserver agreement was assessed using the intraclass correlation coefficient (ICC) with a two-way random model for absolute agreement, and Bland–Altman analysis was performed for agreement visualization.</p> Results <p>Interobserver agreement for PHE volume was significantly higher on ED images (ICC = 0.931, 95% CI: 0.895–0.955, <i>p</i> &lt; 0.001) than on conventional CT (ICC = 0.799, 95% CI: 0.705–0.866, <i>p</i> &lt; 0.001). The improvement in interobserver agreement on ED images was most pronounced for PHE volume &lt; 30&#xa0;mL and for hemorrhage located in the thalamus or brainstem. However, small subgroup sample sizes (thalamus, <i>n</i> = 12; brainstem, <i>n</i> = 5) limited the generalizability of these subgroup findings. Clear PHE boundary identification was significantly higher on ED images: Reader 1 identified clear boundaries in 70.73% (58/82) of patients on ED images versus 40.24% (33/82) on conventional CT; Reader 2 identified clear boundaries in 78.05% (64/82) versus 45.12% (37/82), respectively (all <i>p</i> &lt; 0.001).</p> Conclusions <p>ED images reconstructed from dual-layer spectral CT demonstrated clearer PHE boundaries and significantly improved interobserver agreement in PHE volume measurement compared with conventional CT. These findings suggest that ED imaging may enhance the reliability and consistency of PHE quantification. However, this single-center retrospective study lacked magnetic resonance imaging (MRI) validation or clinical outcome correlation. Therefore, prospective multicenter studies are warranted to confirm these findings and assess their impact on clinical decision-making.</p> Graphical Abstract <p></p>

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Improved interobserver agreement for perihematomal edema measurement using dual-layer spectral CT electron density imaging in intracerebral hemorrhage

  • Qiaoying Zhang,
  • Wei Du,
  • Wenhua Zhao,
  • Pengfeng Sun,
  • Jiayu Wu,
  • Mingyue Ma,
  • Yan Dong,
  • Xiaoping Wu

摘要

Purpose

Intracerebral hemorrhage (ICH) is a subtype of stroke associated with high morbidity and mortality. Perihematomal edema (PHE), the swelling of brain tissue surrounding hemorrhage, is an independent predictor of risk stratification and prognosis. Therefore, accurate identification and measurement of PHE volume is crucial for clinical decision-making. Currently, PHE measurement relies on conventional computed tomography (CT), which has limited ability to delineate edema boundaries. This retrospective study aimed to evaluate whether electron density (ED) images derived from dual-layer spectral CT improve interobserver agreement and boundary visualization in PHE volume measurement compared with images derived from conventional CT.

Methods

This retrospective study enrolled 82 patients with ICH who underwent noncontrast head CT using a dual-layer spectral CT scanner between January 2024 and November 2024. Conventional CT and reconstructed ED images were generated for each patient. Two attending radiologists independently measured PHE volume on both image types and assessed PHE boundary clarity. Boundaries were considered clear if more than 50% of the PHE margin was well defined and distinctly visible. PHE boundaries were manually delineated on a 3D postprocessing workstation. Interobserver agreement was assessed using the intraclass correlation coefficient (ICC) with a two-way random model for absolute agreement, and Bland–Altman analysis was performed for agreement visualization.

Results

Interobserver agreement for PHE volume was significantly higher on ED images (ICC = 0.931, 95% CI: 0.895–0.955, p < 0.001) than on conventional CT (ICC = 0.799, 95% CI: 0.705–0.866, p < 0.001). The improvement in interobserver agreement on ED images was most pronounced for PHE volume < 30 mL and for hemorrhage located in the thalamus or brainstem. However, small subgroup sample sizes (thalamus, n = 12; brainstem, n = 5) limited the generalizability of these subgroup findings. Clear PHE boundary identification was significantly higher on ED images: Reader 1 identified clear boundaries in 70.73% (58/82) of patients on ED images versus 40.24% (33/82) on conventional CT; Reader 2 identified clear boundaries in 78.05% (64/82) versus 45.12% (37/82), respectively (all p < 0.001).

Conclusions

ED images reconstructed from dual-layer spectral CT demonstrated clearer PHE boundaries and significantly improved interobserver agreement in PHE volume measurement compared with conventional CT. These findings suggest that ED imaging may enhance the reliability and consistency of PHE quantification. However, this single-center retrospective study lacked magnetic resonance imaging (MRI) validation or clinical outcome correlation. Therefore, prospective multicenter studies are warranted to confirm these findings and assess their impact on clinical decision-making.

Graphical Abstract