Early Experience of a Commercial Available Robot (Maxio) for CT-guided Radiofrequency Ablation of liver tumours 1 BJJ Abdullah, 1 CH Yeong, 2 KL Goh, 3 BK Yoong, 4 GF Ho, 5 Anjali Kulkarni   1 Department of Biomedical Imaging and University of Malaya Research Imaging Centre, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia. Departments of 2Internal Medicine, 3Surgery and 4Oncology, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia. 5Perfint Healthcare Corporation, Florence, OR 97439, United State.

Challenges in Ablation Visualization Planning Limited Tools Tumor visualization difficult in many cases Current fusion techniques - Cumbersome Impossible to visualize related structures Skill dependent Ablation zone Validation Positioning No tool to validate Needle visualization Complex spatial orientation of organs Patient follow up Multiple needle Big Learning Curve Ablation tool lacks the critical level of control, accuracy, stability, and guaranteed performance (Emad M. Boctor et. Al, 2004) Local tumor progression occurs due to failures in establishing ablative margin (Minami & Kudo, 2011)

Challenges of current CT-guided RFA Real time Target Entry point Angle Depth High CT fluoro dose Repeated Punctures The current practice of CT guided RFA is a challenging procedure by nature. It requires real time assessment from tumour targeting to therapy. Due to the CT-guided properties, it often induce high radiation dose to both patients and working personnel. Repeated needle punctures may be necessary to adjust positioning to the target volume. The whole procedure is often time consuming and challenging. Time Consuming ECR 2014, Vienna

Robotic-Assisted RFA MAXIOTM (Perfint Healthcare Pvt Ltd, Oregon, USA) MAXIO console MAXIO Recently, there is a robotic device introduced to assist tumour targeting in the CT-guided interventional procedures, such as biopsy, cancer ablation, FNAC, drainage and pain management. The device is named ROBIO EX, which is a trademark registered by the Perfint Healthcare, USA. The ROBIO EX can be connected to a CT or PET/CT scanner through InstaReg technology and communicated to the DICOM network using Ethernet. Treatment planning can be done on the robot’s console to accurately target to the tumour volume. The depth of tumour, length of needle and angulation of needle insertion are calculated by the robot. Once confirm and execution, the robotic arm will automatically move to the accurate coordinates for needle insertion. The radiologist will just need to insert the needle through the bush on the robotic arm. MAXIOTM (Perfint Healthcare Pvt Ltd, Oregon, USA) ECR 2014, Vienna

Purpose of Study To assess the accuracy of needle placement, radiation dose and performance level during robotic-assisted radiofrequency ablation (RA- RFA) of liver tumours using a CT-guidance robotic system (MAXIO, Perfint Healthcare, USA). ECR 2014, Vienna

Methodology 19 patients (39 lesions, <5.0 cm diameter) were treated with RA-RFA. All the procedures were performed under GA. Following baseline CT scans the lesions were identified. The CT images (1 mm reconstructed SL) were registered to the MAXIO workstation for treatment planning. Target point (X, Y, Z) and needle entry point were determined during the treatment plan. The needle trajectory path, angulation and depth of lesion were calculated and shown on the treatment plan. ECR 2014, Vienna

Methodology The plan was carefully checked to avoid any critical organs or bone across the trajectory. Once the plan was confirmed, MAXIO was executed. The robotic arm then moved automatically to the planned location and the radiologist inserted the RFA needle through the bush holder at the end-effector of the robotic arm. Post-needle insertion, a CT-fluoro was done to confirm accurate placement of the needle within the target volume. ECR 2014, Vienna

Methodology The accuracy of needle placement, number of readjustments and total radiation dose to each patient were recorded. The performance level was evaluated for each procedure on a five-point scale (5-1: Excellent-Poor) by the operated radiologist. The radiation doses and readjustments were then compared against 30 RFA patients treated without robotic assistance. ECR 2014, Vienna

Adaptive Intra-op. registration Post procedure confirmation Image Registration Segmentation Simulation Adaptive Intra-op. registration SCAN PLAN VISUALISE EXECUTE With the assistance of robotic systems, clinicians can now visualize and plan an entire ablation procedure in 3D - pre-operative registration, segmentation and visualization of multiple VOI, multi probe placement planning, estimated ablation volume and probe placement sequence, before advancing a single probe into the patient. Once the plan is confirmed, the robotic targeting system provides spatial positioning and orientation for a probe guide, through which the clinician then carefully insert each probe and performs the ablative procedure. VALIDATE MaxioTM Robotic Targeting Post procedure confirmation ECR 2014, Vienna

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Results All 39 lesions were targeted successfully. No immediate complications were noted in all the patients. RA-RFA Conventional RFA P-value Average number of needle readjustment 0.8 ± 0.8 Performance level 4.7 ± 0.5 CT Fluoro Dose per Lesion (DLP, mGy.cm) 422.27 ± 370.611 (-16%) 501.20 ± 366.54 P>0.05 Total CTDIvol per patient (mGy) 534.71 ± 397.74 (-6%) 567.33 ± 398.62 Total DLP per patient (mGy.cm) 1390.37 ± 549.02 (-14%) 1611.27 ± 708.38 ECR 2014, Vienna.

Conclusion Robotic-assisted planning and needle placement appears to be technically easier requires fewer number of needle passes fewer check scans lower radiation dose (patient & staff) Study with large sample size is needed to confirm these preliminary findings. ECR 2014, Vienna

Other Potential Advantages of RA-RFA Time Pain Allows access to difficult lesions Accuracy & consistency Level of confidence & safety ECR 2014, Vienna

References BJJ Abdullah, CH Yeong, KL Goh, BK Yoong, GF Ho, Carolyn Yim, Anjali Kulkarni. Robotic-assisted radiofrequency ablation of primary and secondary tumours. European Radiology, Vol 23(9), 2013. Perfint Healthcare Corporation official website. www.perfinthealthcare.com ECR 2014, Vienna