Versatile multi-constrained planning for thermal ablation of large liver tumors

The surgical planning of large hepatic tumor ablation remains a challenging task that relies on fulfilling multiple medical constraints, especially for the ablation based on configurations of multiple electrodes. The placement of the electrodes to completely ablate the tumor as well as their insertion trajectory to their final position have to be planned to cause as little damage to healthy anatomical structures as possible to allow a fast rehabilitation. In this paper, we present a novel, versatile approach for the computer-assisted planning of multi-electrode thermal ablation of large liver tumors based on pre-operative CT data with semantic annotations. This involves both the specification of the number of required electrodes and their distribution to adequately ablate the tumor region without damaging too much healthy tissue. To determine the insertion trajectory of the electrodes to their final position, we additionally incorporate a series of medical constraints into our optimization, which allows a global analysis where obstacles such as bones are taken into account and damage to healthy tissue is mitigated. Compared with the state-of-the-art method, our method achieves compact ablation regions without relying on assumptions on a potential needle path for optimal global search and, hence, is suitable for guiding clinicians through the planning of the tumor ablation. We also demonstrate the feasibility of our approach in various experiments of clinical data and demonstrate that our approach not only allows completely ablating the tumor region but also reducing the damage of healthy tissue in comparison to the previous state-of-the-art method.

[1]  C. Couinaud,et al.  Liver Anatomy: Portal (and Suprahepatic) or Biliary Segmentation , 2000, Digestive Surgery.

[2]  Fa Wu,et al.  An analytical solution for temperature distributions in hepatic radiofrequency ablation incorporating the heat-sink effect of large vessels , 2018, Physics in medicine and biology.

[3]  Luc Soler,et al.  Multi-criteria Trajectory Planning for Hepatic Radiofrequency Ablation , 2007, MICCAI.

[4]  J Crezee,et al.  Temperature uniformity during hyperthermia: the impact of large vessels. , 1992, Physics in medicine and biology.

[5]  Aaron Fenster,et al.  Multiple objective planning for thermal ablation of liver tumors , 2020, International Journal of Computer Assisted Radiology and Surgery.

[6]  Dexing Kong,et al.  Semiautomatic Radiofrequency Ablation Planning Based on Constrained Clustering Process for Hepatic Tumors , 2018, IEEE Transactions on Biomedical Engineering.

[7]  Christof Büskens,et al.  Towards Optimization of Probe Placement for Radio-Frequency Ablation , 2006, MICCAI.

[8]  Masatoshi Kudo,et al.  Radiofrequency Ablation of Liver Metastases from Colorectal Cancer: A Literature Review , 2012, Gut and liver.

[9]  Jorge Nocedal,et al.  An interior algorithm for nonlinear optimization that combines line search and trust region steps , 2006, Math. Program..

[10]  Christian Schumann,et al.  Interactive multi-criteria planning for radiofrequency ablation , 2015, International Journal of Computer Assisted Radiology and Surgery.

[11]  Ping Liang,et al.  Malignant liver tumors: treatment with percutaneous microwave ablation--complications among cohort of 1136 patients. , 2009, Radiology.

[12]  Luc Soler,et al.  Optimal Trajectories Computation Within Regions of Interest for Hepatic RFA Planning , 2005, MICCAI.

[13]  Ashley F. Emery,et al.  The use of heat transfer principles in designing optimal diathermy and cancer treatment modalities , 1982 .

[14]  Jorge Nocedal,et al.  An Interior Point Algorithm for Large-Scale Nonlinear Programming , 1999, SIAM J. Optim..

[15]  Heinz-Otto Peitgen,et al.  Fast automatic path proposal computation for hepatic needle placement , 2010, Medical Imaging.

[16]  S. Curley,et al.  Radio-frequency ablation of liver tumors: assessment of therapeutic response and complications. , 2001, Radiographics : a review publication of the Radiological Society of North America, Inc.

[17]  Nobuhiko Hata,et al.  Treatment Planning and Image Guidance for Radiofrequency Ablation of Large Tumors , 2014, IEEE Journal of Biomedical and Health Informatics.

[18]  Shuzhi Sam Ge,et al.  Coverage planning in computer-assisted ablation based on Genetic Algorithm , 2014, Comput. Biol. Medicine.

[19]  William W Mayo-Smith,et al.  Microwave ablation: principles and applications. , 2005, Radiographics : a review publication of the Radiological Society of North America, Inc.

[20]  O. Minet,et al.  Determination of the specific heat capacity of healthy and tumorous human tissue , 1995 .

[21]  R. Ma,et al.  State of the ablation nation: a review of ablative therapies for cure in the treatment of hepatocellular carcinoma. , 2017, Future oncology.

[22]  Lena Maier-Hein,et al.  Computer-assisted trajectory planning for percutaneous needle insertions. , 2011, Medical physics.

[23]  H. Rhim,et al.  Intrahepatic recurrence after percutaneous radiofrequency ablation of hepatocellular carcinoma: analysis of the pattern and risk factors. , 2006, European journal of radiology.

[24]  Luc Soler,et al.  Trajectory optimization for the planning of percutaneous radiofrequency ablation of hepatic tumors , 2007, Computer aided surgery : official journal of the International Society for Computer Aided Surgery.

[25]  Aaron Fenster,et al.  Automatic Radiofrequency Ablation Planning for Liver Tumors With Multiple Constraints Based on Set Covering , 2020, IEEE Transactions on Medical Imaging.

[26]  Jorge Nocedal,et al.  A trust region method based on interior point techniques for nonlinear programming , 2000, Math. Program..

[27]  Luigi Solbiati,et al.  Treatment of focal liver tumors with percutaneous radio-frequency ablation: complications encountered in a multicenter study. , 2003, Radiology.

[28]  Jing Li,et al.  A practical pretreatment planning method of multiple puncturing for thermal ablation surgery , 2020 .

[29]  W. Stadler A survey of multicriteria optimization or the vector maximum problem, part I: 1776–1960 , 1979 .

[30]  Aaron Fenster,et al.  Development of a Multi-objective Optimized Planning Method for Microwave Liver Tumor Ablation , 2019, MICCAI.