Semiautomatic Volumetric Tumor Segmentation for Hepatocellular Carcinoma: Comparison between C-arm Cone Beam Computed Tomography and MRI
Semiautomatic Volumetric Tumor Segmentation for Hepatocellular Carcinoma: Comparison between C-arm Cone Beam Computed Tomography and MRI
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DOI：
10.1016/j.acra.2012.11.009
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发表时间：
2013-04-01
影响因子：
4.8
通讯作者：
Geschwind, Jean-Francois
中科院分区：
文献类型：
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作者：
Tacher, Vania;Lin, MingDe;Geschwind, Jean-Francois
基本原理和目标：评价半自动肿瘤分割软件在首次肝动脉化疗栓塞术（TACE）前在对比增强磁共振成像（CE-MRI）和术中双相C臂锥形束计算机断层扫描（DP-CBCT）图像上测量肝细胞癌（HCC）肿瘤体积的精确性和可重复性。材料和方法：19例患者（每例患者1例）的19例HCC接受了基线诊断CE-MRI和术中DP-CBCT。在实际栓塞之前，从CE-MRI（静脉造影剂注射的动脉期）和DP-CBCT（动脉内造影剂注射的延迟期）获得图像。三名阅片员使用半自动三维体积分割软件测量肿瘤体积，该软件使用采用非欧几里德径向基函数的区域生长方法。记录分割时间和空间位置。使用线性回归和Student t检验比较图像集之间的肿瘤体积测量值，并使用组内相关分析（ICC）进行评价。评价者间Dice相似性系数（DSC）评估分割的空间定位。在CE-MRI和DP-CBCT检查中，1）平均分段肿瘤体积分别为87 +/- 8 cm（3）（2-873）和92 +/- 10 cm（3）（1-954），在两种成像模式之间，每个肿瘤的阅片者的分割体积没有统计学差异，分割所需的平均时间为66 +/-45秒（21- 45秒）。85 +/- 34秒（17-214）（2）ICC分别为0.99和0.974，阅读者之间有较强的相关性;和3）评价者间DSC在肿瘤分割的空间定位上显示出良好到极好的用户间一致性结论：本研究显示半自动肿瘤分割软件在CE-MRI和DP-CBCT图像上测量肿瘤体积时具有强相关性、高精度和良好的重复性。在DP-CBCT和CE-MRI上使用分割软件可以成为测量肝脏肿瘤体积的有价值且高度准确的工具。
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.