Maxio - Perfint Healthcare

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Transcript Maxio - Perfint Healthcare

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
Tumor visualization difficult in many cases
Impossible to visualize related structures
Skill dependent
Positioning
Needle visualization
Complex spatial orientation of organs
Multiple needle
Big Learning Curve
Local tumor progression occurs due to
failures in establishing ablative margin
(Minami & Kudo, 2011)
Planning
Limited Tools
Current fusion techniques Cumbersome
Ablation zone
Validation
No tool to validate
Patient follow up
Ablation tool lacks the critical level of
control, accuracy, stability, and guaranteed
performance (Emad M. Boctor et. Al, 2004)
Challenges of current CT-guided RFA
Real time
Depth
Entry point
High CT fluoro dose
Angle
Target
Repeated Punctures
Time Consuming
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Robotic-Assisted RFA
Integrated monitor
(ROBIO EX-Console)
MAXIO console
MAXIO EX
ROBIO
Coordinate
system
Y
Y
X
RS485 thro USB/
Serial to 485
converter to ROBIO
console
Z
X
CT Gantry
Coordinate
system
Foot Switch
om
w ro
e
Revi
l
l
wa
CT
Console
Ethernet connection
either thro hospital
Network or thro a
Ethernet Hub to CT
MAXIOTM (Perfint Healthcare Pvt Ltd, Oregon, USA)
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Purpose of Study
• To assess the accuracy of needle placement,
radiation dose and performance level during
robotic-assisted radiofrequency ablation (RARFA) of liver tumours using a CT-guidance
robotic system (MAXIO, Perfint Healthcare,
USA).
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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.
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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.
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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.
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Image Registration
Segmentation
SCAN
PLAN
Simulation
VISUALISE
Adaptive Intra-op.
registration
EXECUTE
VALIDATE
MaxioTM
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Post procedure
confirmation
Robotic
Targeting
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Results
• All 39 lesions were targeted successfully.
• No immediate complications were noted in all the patients.
RA-RFA
Average number of
needle readjustment
0.8 ± 0.8
Performance level
4.7 ± 0.5
Conventional RFA P-value
CT Fluoro Dose per Lesion 422.27 ± 370.611
(DLP, mGy.cm)
(-16%)
501.20 ± 366.54
P>0.05
Total CTDIvol per patient
(mGy)
534.71 ± 397.74
(-6%)
567.33 ± 398.62
P>0.05
Total DLP per patient
(mGy.cm)
1390.37 ± 549.02
(-14%)
1611.27 ± 708.38 P>0.05
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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.
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Other Potential Advantages of RA-RFA
•
Time
•
Pain
•
Allows access to difficult lesions
•
Accuracy & consistency
•
Level of confidence & safety
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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
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