Intraprocedural assessment of ablation margins using computed tomography co-registration in hepatocellular carcinoma treatment with percutaneous ablation: IAMCOMPLETE study

Software-based versus visual assessment of the minimal ablative margin in patients with liver tumours undergoing percutaneous thermal ablation (COVER-ALL): a randomised phase 2 trial

BACKGROUND

Tumour coverage with an optimal minimal ablative margin is crucial for improving local control of liver tumours following thermal ablation. The minimal ablative margin has traditionally been assessed through visual inspection of co-registered CT images. However, rates of local tumour control after thermal ablation are highly variable with visual assessment. We aimed to assess the use of a novel software-based method for minimal ablative margin assessment that incorporates biomechanical deformable image registration and artificial intelligence (AI)-based autosegmentation.

METHODS

The COVER-ALL randomised, phase 2, superiority trial was conducted at The University of Texas MD Anderson Cancer Center (Houston, TX, USA). Patients aged 18 years or older with up to three histology-agnostic liver tumours measuring 1-5 cm and undergoing CT-guided thermal ablation were enrolled. Thermal ablation was performed with the aim of achieving a minimal ablative margin of 5 mm or greater. Patients were randomly assigned (1:1) to the experimental group (software-based assessment) or the control group (visual assessment) by use of dynamic minimisation to balance covariates. Randomisation was performed intraprocedurally after placement of the ablation applicator. Assessment of oncological outcomes and adverse events were masked to treatment allocation. All analyses were conducted on an intention-to-treat basis. The primary endpoint was the minimal ablative margin on post-ablation intraprocedural CT. A preplanned interim analysis for superiority was done at 50% patient enrolment. Adverse events were recorded with the Common Terminology Criteria for Adverse Events. This trial is registered with ClinicalTrials.gov (NCT04083378), and recruitment is complete.

FINDINGS

Patients were enrolled and treated with thermal ablation between June 15, 2020, and Oct 5, 2023. 26 patients were randomly assigned to the control group (mean age 58·1 [SD 14·8] years; 18 [69%] male and eight [31%] female; 11 [42%] colorectal cancer liver metastasis; median tumour diameter 1·7 cm [IQR 1·3-2·3]) and 24 to the experimental group (mean age 60·5 [14·4] years; 16 [67%] male and eight [33%] female; ten [42%] colorectal cancer liver metastasis; median tumour diameter 1·8 cm [1·5-2·5]). The interim analysis showed a mean minimal ablative margin of 2·2 mm (SD 2·8) in the control group and 5·9 mm (2·7) in the experimental group (p<0·0001), prompting halting of enrolment in the control group. A further 50 patients were enrolled to a non-randomised experimental group (mean age 56·5 [SD 11·7] years; 27 [54%] male and 23 [46%] female; 30 [60%] colorectal cancer liver metastasis; median tumour diameter 1·5 cm [IQR 1·3-2·2]); among these patients, the mean minimal ablative margin was 7·2 mm (SD 2·8). Grade 1-3 adverse events were reported in five (5%) of 100 patients: three (12%) of 26 in the control group and two (3%) of 74 in the experimental groups. No grade 4-5 adverse events or treatment-related deaths were reported.

INTERPRETATION

Software-based assessment during CT-guided thermal ablation of liver tumours is safe and significantly improves the minimal ablative margin compared to visual assessment. Adoption of software-based assessment as a standard component of thermal ablation should be considered to achieve the intended minimal ablative margin.

FUNDING

US National Institutes of Health and US National Cancer Institute.

Evaluation of navigation and robotic systems for percutaneous image-guided interventions: A novel metric for advanced imaging and artificial intelligence integration

PURPOSE

Navigation and robotic systems aim to improve the accuracy and efficiency of percutaneous image-guided interventions, but the evaluation of their autonomy and integration of advanced imaging and artificial intelligence (AI) is lacking. The purpose of this study was to evaluate the level of automation and integration of advanced imaging and artificial intelligence in navigation and robotic systems for percutaneous image-guided interventions, using established and novel metrics to categorize and compare their capabilities.

MATERIALS AND METHODS

Following PRISMA guidelines, a systematic review was conducted to identify studies on clinically validated navigation and robotic systems published between 2000 and May 2024. The PubMed, Embase, Cochrane Library, and Web of Science databases were searched. Data on navigation devices were extracted and analyzed. The levels of autonomy in surgical robotics (LASR) classification system (from 1 to 5) was used to analyze automation. A novel taxonomy, the Levels of Integration of Advanced Imaging and AI (LIAI2) classification system, was created to categorize the integration of imaging technologies and AI (from 1 to 5). These two scores were combined into an aggregate score (from 1 to 10) to reflect the autonomy in percutaneous image-guided intervention.

RESULTS

The review included 20 studies assessing two navigation systems and eight robotic devices. The median LASR score was 1 (Q1, Q3: 1, 1), the median LIAI2 score was 2 (Q1, Q3: 2, 3), and the median aggregate score was 3 (Q1, Q3: 3, 4). Only one robotic system (10 % of those reviewed) achieved the highest LASR qualification in the literature, a level 2/5. Four systems (40 %) shared the highest rating for LIAI2, which was a score of 3/5. Four systems (40 %) achieved the highest aggregate scores of 4/10.

CONCLUSION

None of the navigation and robotic systems achieved full autonomy for percutaneous image-guided intervention. The LASR and LIAI2 scales can guide innovation by identifying areas for further development and integration.

Robotic Assistance in Percutaneous Liver Ablation Therapies: A Systematic Review and Meta-Analysis

Objective

The aim of this systematic review and meta-analysis is to identify current robotic assistance systems for percutaneous liver ablations, compare approaches, and determine how to achieve standardization of procedural concepts for optimized ablation outcomes.

Background

Image-guided surgical approaches are increasingly common. Assistance by navigation and robotic systems allows to optimize procedural accuracy, with the aim to consistently obtain adequate ablation volumes.

Methods

Several databases (PubMed/MEDLINE, ProQuest, Science Direct, Research Rabbit, and IEEE Xplore) were systematically searched for robotic preclinical and clinical percutaneous liver ablation studies, and relevant original manuscripts were included according to the Preferred Reporting items for Systematic Reviews and Meta-Analyses guidelines. The endpoints were the type of device, insertion technique (freehand or robotic), planning, execution, and confirmation of the procedure. A meta-analysis was performed, including comparative studies of freehand and robotic techniques in terms of radiation dose, accuracy, and Euclidean error.

Results

The inclusion criteria were met by 33/755 studies. There were 24 robotic devices reported for percutaneous liver surgery. The most used were the MAXIO robot (8/33; 24.2%), Zerobot, and AcuBot (each 2/33, 6.1%). The most common tracking system was optical (25/33, 75.8%). In the meta-analysis, the robotic approach was superior to the freehand technique in terms of individual radiation (0.5582, 95% confidence interval [CI] = 0.0167-1.0996, dose-length product range 79-2216 mGy.cm), accuracy (0.6260, 95% CI = 0.1423-1.1097), and Euclidean error (0.8189, 95% CI = -0.1020 to 1.7399).

Conclusions

Robotic assistance in percutaneous ablation for liver tumors achieves superior results and reduces errors compared with manual applicator insertion. Standardization of concepts and reporting is necessary and suggested to facilitate the comparison of the different parameters used to measure liver ablation results. The increasing use of image-guided surgery has encouraged robotic assistance for percutaneous liver ablations. This systematic review analyzed 33 studies and identified 24 robotic devices, with optical tracking prevailing. The meta-analysis favored robotic assessment, showing increased accuracy and reduced errors compared with freehand technique, emphasizing the need for conceptual standardization.