Compared with surgical resection of tumors, percutaneous radiofrequency ablation (RFA) has emerged as a viable minimally
invasive technique for the treatment of cancers in organs, such as bone, lung or liver. The tumor ablation procedure employs
needle-like probes which can be inserted percutaneously to the target tumor and deliver ?burning heat? to kill the cancerous tissue.
The current practice of ablation planning is highly dependent on the operator?s experience from looking at the preoperative or
intra-operative images. Its success rate is greatly influenced by the biological conditions (critical surrounding organs, tumor
size), thus the need for computer-assisted interventions to provide a more comprehensive description of the surgery. For large
tumors that cannot be completely killed by one ablation even with large electrodes, multiple ablations are needed to cover the
whole tumor and a safety margin. To address these challenges, we present a computer-assisted imaged-guided planning system
incorporating mathematical optimization and augmented reality. Sphere covering optimized by genetic algorithm are used for
complete tumor coverage planning; voxels and optimization equations are employed to calculate optimized needle trajectories.
The patient specific model are derived from the dignostic CT images with the safety margin, then the treatment optimization
module derives optimal probe insertion trajectories as well as optimal placement locations of ablation electrode. The optimization
formulation is structured to satisfy the constraints of complete tumor coverage using multiple overlapping ablations, starting
from specified entry points, avoiding critical no-fly zone, while minimizing the number of ablations and skin punctures. The
proposed multiple-objective optimization for probe insertions incorporates both clinical and technical constraints and has been
validated in the experiments.
Hongliang Ren is currently an Assistant Professor and a PI of medical mechatronics in National University of Singapore (NUS). He received his
Ph.D. in Electronic Engineering from The Chinese University of Hong Kong (CUHK), and conducted postdoctoral research in the The Johns Hopkins
University, Surgical Innovation Institute of Children's National Medical Center, and the Pediatric Cardiac Bioengineering Lab of Children's Hospital
Boston & Harvard Medical School. His research interests are in Computer-Integrated Surgical (CIS) systems, biomedical mechatronics, medical
robotics and sensing technologies.
Peer Reviewed Journals
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals