Computer-assisted trajectory planning for percutaneous needle insertions Alexander Seitel a),b) and Markus Engel b) Division of Medical and Biological Informatics, German Cancer Research Center, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany Christof M. Sommer and Boris A. Radeleff Department of Diagnostic Radiology, University of Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany Caroline Essert-Villard and Claire Baegert Laboratoire des Sciences de l’Image, de l’Informatique et de la Te ´le ´de ´tection, Po ˆ le API, F67400 Illkirch, France Markus Fangerau, Klaus H. Fritzsche, Kwong Yung, Hans-Peter Meinzer, and Lena Maier-Hein Division of Medical and Biological Informatics, German Cancer Research Center, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany (Received 15 November 2010; revised 21 April 2011; accepted for publication 21 April 2011; published 1 June 2011) Purpose: Computed tomography (CT) guided minimally invasive interventions such as biopsies or ablation therapies often involve insertion of a needle-shaped instrument into the target organ (e.g., the liver). Today, these interventions still require manual planning of a suitable trajectory to the tar- get (e.g., the tumor) based on the slice data provided by the imaging modality. However, taking into account the critical structures and other parameters crucial to the success of the intervention— such as instrument shape and penetration angle—is challenging and requires a lot of experience. Methods: To overcome these problems, we present a system for the automatic or semiautomatic planning of optimal trajectories to a target, based on 3D reconstructions of all relevant structures. The system determines possible insertion zones based on so-called hard constraints and rates the quality of these zones by so-called soft constraints. The concept of pareto optimality is utilized to allow for a weight-independent proposal of insertion trajectories. In order to demonstrate the bene- fits of our method, automatic trajectory planning was applied retrospectively to n ¼ 10 data sets from interventions in which complications occurred. Results: The efficient (graphics processing unit-based) implementation of the constraints results in a mean overall planning time of about 9 s. The examined trajectories, originally chosen by the phy- sician, have been rated as follows: in six cases, the insertion point was labeled invalid by the plan- ning system. For two cases, the system would have proposed points with a better rating according to the soft constraints. For the remaining two cases the system would have indicated poor rating with respect to one of the soft constraints. The paths proposed by our system were rated feasible and qualitatively good by experienced interventional radiologists. Conclusions: The proposed computer-assisted trajectory planning system is able to detect unsafe and propose safe insertion trajectories and may especially be helpful for interventional radiologist at the beginning or during their interventional training. V C 2011 American Association of Physicists in Medicine. [DOI: 10.1118/1.3590374] Key words: interventional radiology, trajectory planning, radiofrequency ablation, image-guided therapy, computer-aided intervention I. INTRODUCTION Image-guided minimally invasive interventions are gaining in importance in clinical routine today. Thermal ablation therapies, for example, are increasingly applied for treatment of focal malignant diseases. For 20% of all malignancies in the liver, surgical resection cannot be used for treatment, and radiofrequency ablation (RFA) emerged as a favored alterna- tive. 1 This procedure requires insertion of a needle-shaped instrument into the cancerous tissue and therefore relies on precise planning of an appropriate insertion trajectory. Although protocols for manual trajectory planning are well established in clinical routine, the lack of three-dimensional (3D) presentation of the medical imaging data may lead to complications. Because the planning is mostly done on slice- based reformations of the 3D volume, the shape and length of the instrument can only be considered roughly and the penetration angle of the instrument is difficult to determine as well. Several approaches to automatic trajectory planning have been presented in the context of neurosurgery. Although structures in the brain can be considered more rigid compared 3246 Med. Phys. 38 (6), June 2011 0094-2405/2011/38(6)/3246/14/$30.00 V C 2011 Am. Assoc. Phys. Med. 3246