Luc Soler

Tree matching applied to vascular system

In this paper, we propose an original tree matching algorithm for intra-patient hepatic vascular system registration. The vascular systems are segmented from CT-Scan images acquired at different time, and then modeled as trees. The goal of this algorithm is to find common bifurcations (nodes) and vessels (edges) in both trees. n nStarting from the tree root, edges and nodes are iteratively matched. The algorithm works on a set of matching hypotheses which is updated to keep best matches. It is robust against topological modification, as the segmentation process can fail to detect some branches. n nFinally, this algorithm is validated on the Visible Human with synthetic deformations thanks to the simulator prototype developed at the INRIA which provides realistic deformations for liver and its vascular network.

Teleeducation in surgery: European Institute for Telesurgery experience.

The information age is revolutionizing the practice and education of surgery. The use of video-conference systems through Integrated Service Digital Network (ISDN) teletransmission connects surgeons around the world without the limits of distance. Teleeducation, teleteaching, teletraining, telementoring, and teleaccreditation have been clearly demonstrated and are now common practice. Pre- and perioperative surgical advice may be obtained from expert networks. Patient data can be reconstructed as virtual tridimensional images analyzed by computers, and the surgical procedure can be simulated to obtain an optimal surgical decision. Finally, the use of the Internet will provide access to this information, whenever and wherever necessary, through dedicated websites. It remains to be adequately demonstrated that these means will allow improvement in patient care.

Real time simulation of organ motions induced by breathing: first evaluation on patient data

In this paper we present a new method to predict in real time from a preoperative CT image the internal organ motions of a patient induced by his breathing. This method only needs the segmentation of the bones, viscera and lungs in the preoperative image and a tracking of the patient skin motion. Prediction of internal organ motions is very important for radiotherapy since it can allow to reduce the healthy tissue irradiation. Moreover, guiding system for punctures in interventional radiology would reduce significantly their guidance inaccuracy. In a first part, we analyse physically the breathing motion and show that it is possible to predict internal organ motions from the abdominal skin position. Then, we propose an original method to compute from the skin position a deformation field to the internal organs that takes mechanical properties of the breathing into account. Finally, we show on human data that our simulation model can provide a prediction of several organ positions (liver, kidneys, lungs) at 14 Hz with an accuracy within 7 mm

PACS-based interface for 3D anatomical structure visualization and surgical planning

The interpretation of radiological image is routine but it remains a rather difficult task for physicians. It requires complex mental processes, that permit translation from 2D slices into 3D localization and volume determination of visible diseases. An easier and more extensive visualization and exploitation of medical images can be reached through the use of computer-based systems that provide real help from patient admission to post-operative followup. In this way, we have developed a 3D visualization interface linked to a PACS database that allows manipulation and interaction on virtual organs delineated from CT-scan or MRI. This software provides the 3D real-time surface rendering of anatomical structures, an accurate evaluation of volumes and distances and the improvement of radiological image analysis and exam annotation through a negatoscope tool. It also provides a tool for surgical planning allowing the positioning of an interactive laparoscopic instrument and the organ resection. The software system could revolutionize the field of computerized imaging technology. Indeed, it provides a handy and portable tool for pre-operative and intra-operative analysis of anatomy and pathology in various medical fields. This constitutes the first step of the future development of augmented reality and surgical simulation systems.

Toward realistic radiofrequency ablation of hepatic tumors 3D simulation and planning

Radiofrequency ablation (RFA) has become an increasingly used technique in the treatment of patients with unresectable hepatic tumors. Evaluation of vascular architecture, post-RFA tissue necrosis prediction, and the choice of a suitable needle placement strategy using conventional radiological techniques remain difficult. In an attempt to enhance the safety of RFA, a 3D simulator and treatment planning tool, that simulates the necrosis of the treated area, and proposes an optimal placement for the needle, has been developed. nFrom enhanced spiral CT scans with 2 mm cuts, 3D reconstructions of patients with liver metastases are automatically generated. Virtual needles can be added to the 3D scene, together with their corresponding zones of necrosis that are displayed as a meshed spheroids representing the 60° C isosurface. The simulator takes into account the cooling effect of local vessels greater than 3mm in diameter, making necrosis shapes more realistic. Using a voxel-based algorithm, RFA spheroids are deformed following the shape of the vessels, extended by an additional cooled area. This operation is performed in real-time, allowing updates while needle is adjusted. This allows to observe whether the considered needle placement strategy would burn the whole cancerous zone or not. nPlanned needle positioning can also be automatically generated by the software to produce complete destruction of the tumor with a 1 cm margin, with maximum respect of the healthy liver and of all major extrahepatic and intrahepatic structures to avoid. If he wishes, the radiologist can select on the skin an insertion window for the needle, focusing the research of the trajectory.

A Real-Time Predictive Simulation of Abdominal Organ Positions Induced by Free Breathing

Prediction of abdominal organ positions during free breathing is a major challenge from which several medical applications could benefit. For instance, in radiotherapy it would reduce the healthy tissue irradiation. In this paper, we present a method to predict in real-time the abdominal organs position during free breathing. This method needs an abdo-thoracic preoperative CT image, a second one limited to the diaphragm zone, and a tracking of the patient skin motion. It also needs the segmentation of the skin, the viscera volume and the diaphragm in both preoperative images. First, a physical analysis of the breathing motion shows it is possible to predict abdominal organs position from the skin position and a modeling of the diaphragm motion. Then, we present our original method to compute a deformation field that considers the abdominal and thoracic breathing influence. Finally, we show on two human data that our simulation model can predict several organs position at 50 Hz with accuracy within 2-3 mm.

Precise determination of regions of interest for hepatic RFA planning

Percutaneous radiofrequency ablation is one of the most promising alternatives to open surgery for the treatment of liver cancer. This operation is a minimally invasive procedure that consists in inserting a needle in targeted tissues that are destroyed by heat. The success of such an operation mainly depends on the accuracy of the needle insertion, making it possible to destroy the whole tumor, while avoiding damages on other organs and minimizing risks of a local recurrence. We are developing a software that applies planning rules on patient-specific 3D reconstructions, in order to suggest relevant options for the choice of a path to the tumor, and that displays various information allowing to adjust the final choice. In this context we propose a method to compute automatically, quickly, and accurately, the possible insertion areas on the skin. Within these areas, an insertion of the probe targeting the tumor respects the numerous strong (boolean) constraints required for a radiofrequency ablation. Besides, these insertion zones define the research domain of the optimization process, taking into account soft constraints to refine the solutions. They are also displayed on the skin of the virtual patient to inform the physician about the different possibilities specific to each case, allowing him at the end of the automatic process, to modify interactively the proposed strategy, with a real-time update of the related information. We discuss in this paper about the importance of a precise delineation of these areas.

Fully automatic anatomical, pathological, and functional segmentation from CT scans for hepatic surgery

OBJECTIVEnTo improve the planning of hepatic surgery, we have developed a fully automatic anatomical, pathological, and functional segmentation of the liver derived from a spiral CT scan.nnnMATERIALS AND METHODSnFrom a 2 mm-thick enhanced spiral CT scan, the first stage automatically delineates skin, bones, lungs, kidneys, and spleen by combining the use of thresholding, mathematical morphology, and distance maps. Next, a reference 3D model is immersed in the image and automatically deformed to the liver contours. Then an automatic Gaussian fitting on the imaging histogram estimates the intensities of parenchyma, vessels, and lesions. This first result is next improved through an original topological and geometrical analysis, providing an automatic delineation of lesions and veins. Finally, a topological and geometrical analysis based on medical knowledge provides hepatic functional information that is invisible in medical imaging: portal vein labeling and hepatic anatomical segmentation according to the Couinaud classification.nnnRESULTSnClinical validation performed on more than 30 patients shows that delineation of anatomical structures by this method is often more sensitive and more specific than manual delineation by a radiologist.nnnCONCLUSIONnThis study describes the methodology used to create the automatic segmentation of the liver with delineation of important anatomical, pathological, and functional structures from a routine CT scan. Using the methods proposed in this study, we have confirmed the accuracy and utility of the creation of a 3D liver model compared with the conventional reading of the CT scan by a radiologist. This work may allow improved preoperative planning of hepatic surgery by more precisely delineating liver pathology and its relationship to normal hepatic structures. In the future, this data may be integrated with computer-assisted surgery and thus represents a first step towards the development of an augmented-reality surgical system.

Virtual Reality, Augmented Reality and Robotics in surgical procedures of the liver

Medical image processing led to a major improvement of patient care. The 3D modeling of patients from their CT-scan or MRI thus allows a better surgical planning. Simulation offers the opportunity to train the surgical gesture before carrying it out. And finally, augmented reality provides surgeons with a view in transparency of their patient which, in the future, will allow to obtain automation of the most complex gestures. We present our latest results in these different fields of research applied to surgical procedures of the liver.

Registration of Preoperative Liver Model for Laparoscopic Surgery from Intraoperative 3D Acquisition

Augmented reality improves the information display during intervention by superimposing hidden structures like vessels. This support is particularly appreciated in laparoscopy where operative conditions are difficult. Generally, the displayed model comes from a preoperative image which does not undergo the deformations due to pneumoperitoneum. We propose to register a preoperative liver model on intraoperative data obtained from a rotational C-arm 3D acquisition. Firstly, we gather the two models in the same coordinate frame according to anatomical structures. Secondly, preoperative model shape is deformed with respect to the intraoperative data using a biomechanical model. We evaluate our method on two in vivo datasets and obtain an average error of 4 mm for the whole liver surface and 10 mm for the vessel position estimation.