METHODS: In this work, we introduce a fully automated liver tumour segmentation approach in contrast-enhanced CT datasets. The method is a multi-stage technique which starts with contrast enhancement of the tumours using anisotropic filtering, followed by adaptive thresholding to extract the initial mask of the tumours from an identified liver region of interest. Localised level set-based active contours are used to extend the mask to the tumour boundaries.
RESULTS: The proposed method is validated on the IRCAD database with pathologies that offer highly variable and complex liver tumours. The results are compared quantitatively to the ground truth, which is delineated by experts. We achieved an average dice similarity coefficient of 75% over all patients with liver tumours in the database with overall absolute relative volume difference of 11%. This is comparable to other recent works, which include semiautomated methods, although they were validated on different datasets.
CONCLUSIONS: The proposed approach aims to segment tumours inside the liver envelope automatically with a level of accuracy adequate for its use as a tool for surgical planning using abdominal CT images. The approach will be validated on larger datasets in the future.
MATERIAL AND METHODS: The RFA of a spherical tumor of 2.0 cm diameter along with 0.5 cm clinical safety margin was simulated using Finite Element Analysis software. A total of 86 points inside one-eighth of the tumor volume along the axial, sagittal and coronal planes were selected as the target sites for electrode-tip placement. The angle of the electrode insertion in both craniocaudal and orbital planes ranged from -90° to +90° with 30° increment. The RFA electrode was simulated to pass through the target site at different angles in combination of both craniocaudal and orbital planes before being advanced to the edge of the tumor.
RESULTS: Complete tumor ablation was observed whenever the electrode-tip penetrated through the epicenter of the tumor regardless of the angles of electrode insertion in both craniocaudal and orbital planes. Complete tumor ablation can also be achieved by placing the electrode-tip at several optimal sites and angles.
CONCLUSIONS: Identification of the tumor epicenter on the central slice of the axial images is essential to enhance the success rate of complete tumor ablation during RFA procedures.
METHODS: Radiofrequency and microwave ablation of liver tumours were performed on 20 patients (40 lesions) with the assistance of a CT-guided robotic positioning system. The accuracy of probe placement, number of readjustments and total radiation dose to each patient were recorded. The performance level was evaluated on a five-point scale (5-1: excellent-poor). The radiation doses were compared against 30 patients with 48 lesions (control) treated without robotic assistance.
RESULTS: Thermal ablation was successfully completed in 20 patients with 40 lesions and confirmed on multiphasic contrast-enhanced CT. No procedure related complications were noted in this study. The average number of needle readjustment was 0.8 ± 0.8. The total CT dose (DLP) for the entire robotic assisted thermal ablation was 1382 ± 536 mGy.cm, while the CT fluoroscopic dose (DLP) per lesion was 352 ± 228 mGy.cm. There was no statistically significant (p > 0.05) dose reduction found between the robotic-assisted versus the conventional method.
CONCLUSION: This study revealed that robotic-assisted planning and needle placement appears to be safe, with high accuracy and a comparable radiation dose to patients.
KEY POINTS: • Clinical experience on liver thermal ablation using CT-guided robotic system is reported. • The technical success, radiation dose, safety and performance level were assessed. • Thermal ablations were successfully performed, with an average performance score of 4.4/5.0. • Robotic-assisted ablation can potentially increase capabilities of less skilled interventional radiologists. • Cost-effectiveness needs to be proven in further studies.
MATERIALS AND METHODS: Two hundred fifty-eight patients with primary liver tumors who underwent FDG-PET before LDLT were enrolled in this retrospective study. Unfavorable tumor histology was defined as primary liver tumor other than a well- or moderately differentiated HCC. Thirteen patients had unfavorable tumor histology, including 2 poorly differentiated HCC, 2 sarcomatoid HCC, 5 combined hepatocellular cholangiocarcinoma, 3 intrahepatic cholangiocarcinoma, and 1 hilar cholangiocarcinoma.
RESULTS: FDG-PET positivity was significantly associated with unfavorable tumor histology (P < 0.001). Both FDG-PET positivity and unfavorable tumor histology were significant independent predictors of tumor recurrence and overall survival. In a subgroup analysis of patients with FDG-PET-positive tumors, unfavorable tumor histology was a significant independent predictor of tumor recurrence and overall survival. High FDG uptake (tumor to non-tumor uptake ratio ≥ 2) was a significant predictor of unfavorable tumor histology. Patients with high FDG uptake and/or unfavorable tumors had significantly higher 3-year cumulative recurrence rate (70.8% versus 26.2%, P = 0.004) and worse 3-year overall survival (34.1% versus 70.8%, P = 0.012) compared to those with low FDG uptake favorable tumors.
CONCLUSIONS: The expression of FDG-PET is highly associated with histology of explanted HCC and predicts the recurrence. FDG-PET-positive tumors with high FDG uptake may be considered contraindication for LDLT due to high recurrence rate except when pathology proves favorable histology.
CASE PRESENTATION: The liver progenitor cell proliferation is observed in a patient undergoing ALPPS for a metastatic hepatic tumour. Liver biopsy is acquired before and after ALPPS for the calculation of average number of liver progenitor cell under high magnification examination by stain of immunomarkers. This is the first in vivo evidence of growing liver progenitor cells demonstrated in a regenerating human liver.
METHODS: We report our preliminary experience of performing radiofrequency ablation of the liver using a robotic-assisted CT guidance system on 11 patients (17 lesions).
RESULTS/CONCLUSION: Robotic-assisted planning and needle placement appears to have high accuracy, is technically easier than the non-robotic-assisted procedure, and involves a significantly lower radiation dose to both patient and support staff.
KEY POINTS: • An early experience of robotic-assisted radiofrequency ablation is reported • Robotic-assisted RFA improves accuracy of hepatic lesion targeting • Robotic-assisted RFA makes the procedure technically easier with significant lower radiation dose.