RATIONALE AND OBJECTIVES: To evaluate the precision and reproducibility of a semiautomatic tumor segmentation software in measuring tumor volume of hepatocellular carcinoma (HCC) before the first transarterial chemo-embolization (TACE) on contrast-enhancement magnetic resonance imaging (CE-MRI) and intraprocedural dual-phase C-arm cone beam computed tomography (DP-CBCT) images. MATERIALS AND METHODS: Nineteen HCCs were targeted in 19 patients (one per patient) who underwent baseline diagnostic CE-MRI and an intraprocedural DP-CBCT. The images were obtained from CE-MRI (arterial phase of an intravenous contrast medium injection) and DP-CBCT (delayed phase of an intra-arterial contrast medium injection) before the actual embolization. Three readers measured tumor volumes using a semiautomatic three-dimensional volumetric segmentation software that used a region-growing method employing non-Euclidean radial basis functions. Segmentation time and spatial position were recorded. The tumor volume measurements between image sets were compared using linear regression and Student's t-test, and evaluated with intraclass-correlation analysis (ICC). The inter-rater Dice similarity coefficient (DSC) assessed the segmentation spatial localization. RESULTS: All 19 HCCs were analyzed. On CE-MRI and DP-CBCT examinations, respectively, 1) the mean segmented tumor volumes were 87 ± 8 cm(3) (2-873) and 92 ± 10 cm(3) (1-954), with no statistical difference of segmented volumes by readers of each tumor between the two imaging modalities and the mean time required for segmentation was 66 ± 45 seconds (21-173) and 85 ± 34 seconds (17-214) (P = .19); 2) the ICCs were 0.99 and 0.974, showing a strong correlation among readers; and 3) the inter-rater DSCs showed a good to excellent inter-user agreement on the spatial localization of the tumor segmentation (0.70 ± 0.07 and 0.74 ± 0.05, P = .07). CONCLUSION: This study shows a strong correlation, a high precision, and excellent reproducibility of semiautomatic tumor segmentation software in measuring tumor volume on CE-MRI and DP-CBCT images. The use of the segmentation software on DP-CBCT and CE-MRI can be a valuable and highly accurate tool to measure the volume of hepatic tumors.
RATIONALE AND OBJECTIVES: To evaluate the precision and reproducibility of a semiautomatic tumor segmentation software in measuring tumor volume of hepatocellular carcinoma (HCC) before the first transarterial chemo-embolization (TACE) on contrast-enhancement magnetic resonance imaging (CE-MRI) and intraprocedural dual-phase C-arm cone beam computed tomography (DP-CBCT) images. MATERIALS AND METHODS: Nineteen HCCs were targeted in 19 patients (one per patient) who underwent baseline diagnostic CE-MRI and an intraprocedural DP-CBCT. The images were obtained from CE-MRI (arterial phase of an intravenous contrast medium injection) and DP-CBCT (delayed phase of an intra-arterial contrast medium injection) before the actual embolization. Three readers measured tumor volumes using a semiautomatic three-dimensional volumetric segmentation software that used a region-growing method employing non-Euclidean radial basis functions. Segmentation time and spatial position were recorded. The tumor volume measurements between image sets were compared using linear regression and Student's t-test, and evaluated with intraclass-correlation analysis (ICC). The inter-rater Dice similarity coefficient (DSC) assessed the segmentation spatial localization. RESULTS: All 19 HCCs were analyzed. On CE-MRI and DP-CBCT examinations, respectively, 1) the mean segmented tumor volumes were 87 ± 8 cm(3) (2-873) and 92 ± 10 cm(3) (1-954), with no statistical difference of segmented volumes by readers of each tumor between the two imaging modalities and the mean time required for segmentation was 66 ± 45 seconds (21-173) and 85 ± 34 seconds (17-214) (P = .19); 2) the ICCs were 0.99 and 0.974, showing a strong correlation among readers; and 3) the inter-rater DSCs showed a good to excellent inter-user agreement on the spatial localization of the tumor segmentation (0.70 ± 0.07 and 0.74 ± 0.05, P = .07). CONCLUSION: This study shows a strong correlation, a high precision, and excellent reproducibility of semiautomatic tumor segmentation software in measuring tumor volume on CE-MRI and DP-CBCT images. The use of the segmentation software on DP-CBCT and CE-MRI can be a valuable and highly accurate tool to measure the volume of hepatic tumors.
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