Semiautomatic Volumetric Tumor Segmentation for Hepatocellular Carcinoma

Abstract

Rationale and Objectives To evaluate the precision and reproducibility of a semi-automatic tumor segmentation software in measuring tumor volume of hepatocellular-carcinoma–(HCC) before the first trans-arterial chemo-embolization–(TACE) on contrast-enhancement magnetic-resonance-imaging–(CE-MRI) and intra-procedural dual-phase C-arm cone-beam computed-tomography–(DP-CBCT) images. Materials and Methods 19HCCs were targeted in 19patients(one per patient) who underwent baseline diagnostic CE-MRI and an intra-procedural DP-CBCT. The images were obtained from CE-MRI–(arterial-phase of an intra-venous 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 semi-automatic 3D-volumetric segmentation software which used a region-growing method employing non-Euclidean radial basis functions. Segmentation time and spatial position were recorded. The tumor volume measurements between images sets were compared using linear-regression and Student t-test, and evaluated with Intraclass-Correlation analysis–(ICC). The inter-rater Dice Similarity Coefficient–(DSC) accessed the segmentation spatial localization. Results All 19 HCCs were analyzed. On CE-MRI and DP-CBCT examinations respectively, A) the mean segmented tumor volumes was 87±8cm3[2–873] and 92±10cm3[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±45seconds [21–173] and 85±34seconds[17–214] (p=0.19), B),the ICCs were 0.99 and 0.974, showing a strong correlation among readers, and C) 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=0.07). Conclusion This study shows a strong correlation, precision and reproducibility of semi-automatic 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.

Radiologic-Pathologic Analysis of Contrast-enhanced and Diffusion-weighted MR Imaging in Patients with HCC after TACE: Diagnostic Accuracy of 3D Quantitative Image Analysis

“…This radiologic-pathologic correlation study provides evidence for the diagnostic value of 3D quantitative imaging with regard to tumor necrosis after TACE. Our methods are based on a semiautomatic, work flow–efficient, and reproducible tumor segmentation software (18,25), which addresses important concerns with regard to clinical practicability of 3D quantitative imaging (9,33). The presented data provide multilayer proof of the precision of 3D quantitative contrast-enhanced and diffusion-weighted MR imaging when correlated with pathologic examination as a standard of reference.…”

“…The resulting 3D segmentation mask was then used for both arterial phase enhancement-based and diffusion-weighted quantitative analysis to achieve high intermethod agreement (8). The precision and reader-independent reproducibility of the utilized segmentation software has been previously described (25). Additional methodologic specifications for the segmentation technique and application are itemized in Appendix E1 (online).…”

Transarterial chemoembolization in soft-tissue sarcoma metastases to the liver – The use of imaging biomarkers as predictors of patient survival

“…Additionally to the conventional non-3D techniques, 3D quantitative image analysis was performed by a radiological reader (AA) with 1 year of experience with the software prototype used in the study (Medisys, Philips Research, Suresnes, France) [17]. The accuracy and reader-independent reproducibility of the semiautomatic tumor segmentation as well as the radiological–pathological correlation of the method have been previously reported [18–21]. The software employed semi-automated 3D tumor segmentation on the arterial phase contrast-enhanced CT or MRI acquired before and after the initial session of cTACE.…”

Semi-automatic cone beam CT segmentation ofin vivopre-clinical subcutaneous tumours provides an efficient non-invasive alternative for tumour volume measurements

“…For orthotopic tumour models such as tumours within the lung or liver, our simple segmentation method will likely not be sufficient, and the more sophisticated methods developed for these purposes will have to be employed. 12,13,15 Although beyond the scope of this study, directly comparing the performance and speed of available segmentation methods for various subcutaneous and orthotopic pre-clinical tumour models may provide useful guidelines for tumour volume measurements. Such an investigation would likely depend both on achievable image resolution and the potential use of contrast agents to highlight tumour tissue.…”

“…Several other methods for semi-automatic tumour segmentation based on CT scans are available in the literature for clinical, [11][12][13] as well as pre-clinical investigations.…”