A focused ultrasound treatment system for moving targets (part I): generic system design and in-silico first-stage evaluation.

BACKGROUND: Focused ultrasound (FUS) is entering clinical routine as a treatment option. Currently, no clinically available FUS treatment system features automated respiratory motion compensation. The required quality standards make developing such a system challenging. METHODS: A novel FUS treatment system with motion compensation is described, developed with the goal of clinical use. The system comprises a clinically available MR device and FUS transducer system. The controller is very generic and could use any suitable MR or FUS device. MR image sequences (echo planar imaging) are acquired for both motion observation and thermometry. Based on anatomical feature tracking, motion predictions are estimated to compensate for processing delays. FUS control parameters are computed repeatedly and sent to the hardware to steer the focus to the (estimated) target position. All involved calculations produce individually known errors, yet their impact on therapy outcome is unclear. This is solved by defining an intuitive quality measure that compares the achieved temperature to the static scenario, resulting in an overall efficiency with respect to temperature rise. To allow for extensive testing of the system over wide ranges of parameters and algorithmic choices, we replace the actual MR and FUS devices by a virtual system. It emulates the hardware and, using numerical simulations of FUS during motion, predicts the local temperature rise in the tissue resulting from the controls it receives. RESULTS: With a clinically available monitoring image rate of 6.67 Hz and 20 FUS control updates per second, normal respiratory motion is estimated to be compensable with an estimated efficiency of 80%. This reduces to about 70% for motion scaled by 1.5. Extensive testing (6347 simulated sonications) over wide ranges of parameters shows that the main source of error is the temporal motion prediction. A history-based motion prediction method performs better than a simple linear extrapolator. CONCLUSIONS: The estimated efficiency of the new treatment system is already suited for clinical applications. The simulation-based in-silico testing as a first-stage validation reduces the efforts of real-world testing. Due to the extensible modular design, the described approach might lead to faster translations from research to clinical practice.

Risk maps for liver surgery.

PURPOSE: Optimal display of surgical planning data in the operating room is challenging. In liver surgery, an expressive and effective intraoperative visualization of 3D planning models is still a pressing need. The objective of this work is to visualize surgical planning information using a map display. METHODS: An approach for risk analysis and visualization of planning models is presented which provides relevant information at a glance without the need for user interaction. Therefore, we present methods for the identification and classification of critical anatomical structures in the proximity of a preoperatively planned resection surface. Shadow-like distance indicators are introduced to encode the distance from the resection surface to these critical structures on a risk map. The work is demonstrated with examples in liver resection surgery and evaluated within two user studies. RESULTS: The results of the performed user studies show that the proposed visualization techniques facilitate the process of risk assessment in liver resection surgery and might be a valuable extension to surgical navigations system. CONCLUSION: The approach provides a new and objective basis for the assessment of risks during liver surgery and has the potential to improve the outcome of surgical interventions.

State of the art in computer-assisted planning, intervention, and assessment of liver-tumor ablation.

Percutaneous, image-guided thermal tumor ablation procedures are used increasingly for minimally invasive, local treatment of tumors in the liver. The planning of these procedures; the support of targeting, monitoring, and controlling during the intervention itself; and the assessment of the treatment response can all benefit significantly from computer assistance. The outcome can be optimized by supporting the physician in the process of determining an intervention strategy that enables complete destruction of the targeted tumor while reducing the danger of complications. During the intervention, computer-assisted methods can be used to guide the physician in the implementation of the intended strategy by providing planning information. Assessment of the intervention result is carried out by comparison of the achieved coagulation with the target tumor volume. Supporting this comparison facilitates the early detection of potential recurrences. This report provides an overview of state-of-the-art computer-assisted methods for the support of thermal tumor ablations in the liver. Proper approaches for image segmentation, access-path determination, simulation, visualization, interventional guidance, and post-interventional assessment, as well as integrated work flow-oriented solutions, are reviewed with respect to technical aspects and applicability in the clinical setting.

Assessment of intraoperative liver deformation during hepatic resection: prospective clinical study.

BACKGROUND: The implementation of intraoperative navigation in liver surgery is handicapped by intraoperative organ shift, tissue deformation, the absence of external landmarks, and anatomical differences in the vascular tree. To investigate the impact of surgical manipulation on the liver surface and intrahepatic structures, we conducted a prospective clinical trial. METHODS: Eleven consecutive patients [4 female and 7 male, median age = 67 years (range = 54-80)] with malignant liver disease [colorectal metastasis (n = 9) and hepatocellular cancer (n = 2)] underwent hepatic resection. Pre- and intraoperatively, all patients were studied by CT-based 3D imaging and assessed for the potential value of computer-assisted planning. The degree of liver deformation was demonstrated by comparing pre- and intraoperative imaging. RESULTS: Intraoperative CT imaging was successful in all patients. We found significant deformation of the liver. The deformation of the segmental structures is reflected by the observed variation of the displacements. There is no rigid alignment of the pre- and intraoperative organ positions due to overall deflection of the liver. Locally, a rigid alignment of the anatomical structure can be achieved with less than 0.5 cm discrepancy relative to a segmental unit of the liver. Changes in total liver volume range from -13 to +24%, with an average absolute difference of 7%. CONCLUSIONS: These findings are fundamental for further development and optimization of intraoperative navigation in liver surgery. In particular, these data will play an important role in developing automation of intraoperative continuous registration. This automation compensates for liver shift during surgery and permits real-time 3D visualization of navigation imaging.

Three-dimensional reconstruction of Echinococcus multilocularis larval growth in human hepatic tissue reveals complex growth patterns.

In this study we present, for the first time, a three-dimensional digital reconstruction of Echinococcus multilocularis larval growth in human tissue. Formalin-fixed, paraffin-embedded hepatic tissues from patients with alveolar echinococcosis were serially sectioned, stained, and areas of larval growth of the parasite were microphotographed. Parasitic structures were reconstructed from multiple digital planes, revealing a root-like network of interconnected vesicles and tubules extending into the periphery of lesions.

Interactive determination of robust safety margins for oncologic liver surgery.

OBJECTIVE: Complex oncologic interventions in the liver require an extensive and careful preoperative analysis. Particularly the achievement of an optimal safety margin around tumors remains a difficult task for surgeons. METHODS: We present new methods for evaluating different safety margins and their effect on the associated interruption of vascular supply or drainage. The characteristic of vascular risk distributions can be evaluated in real-time by exploiting precomputed safety maps that provide a volume curve for each vascular system. By applying fast visualization methods in 3D it is possible to assist the surgeon in the determination of a tumor-free safety margin while preserving sufficient vital hepatic parenchyma. The combination of risk analysis from different vascular systems and their sensitivity is considered. RESULTS: We provide physicians with a novel computer-aided planning tool that allows for interactive determination of safety margins in real-time. The planning tool integrates smoothly into the preoperative workflow. Preliminary evaluations confirm that the width of safety margins can be determined more precisely, which may affect the proposed resection strategy. CONCLUSION: Our new methods provide interactive feedback and support for decision making during the preoperative planning stage and thus might potentially improve the outcome of surgical interventions.

Informatics in radiology (infoRAD): new tools for computer assistance in thoracic CT part 2. Therapy monitoring of pulmonary metastases.

Owing to the rapid development of scanner technology, thoracic computed tomography (CT) offers new possibilities but also faces enormous challenges with respect to the quality of computer-assisted diagnosis and therapy planning. In the framework of the Virtual Institute for Computer Assistance in Clinical Radiology cooperative research project, a software application was developed to assist the radiologist in the analysis of thoracic CT data for the purpose of evaluating the response to tumor therapy. The application provides follow-up support for monitoring of tumor therapy by means of volumetric quantification of tumors and temporal registration. In addition, anatomically adequate three-dimensional visualization techniques for convenient examination of large data sets are included. With close cooperation between computer scientists and radiologists, the application was tested and optimized to achieve a high degree of usability. Several clinical studies were carried out, the results of which indicated that the application improves therapy monitoring with respect to accuracy and time required.

Informatics in radiology (infoRAD): new tools for computer assistance in thoracic CT. Part 1. Functional analysis of lungs, lung lobes, and bronchopulmonary segments.

Owing to the rapid development of scanner technology, thoracic computed tomography (CT) offers new possibilities but also faces enormous challenges with respect to the quality of computer-assisted diagnosis and therapy planning. In the framework of the Virtual Institute for Computer Assistance in Clinical Radiology cooperative research project, a prototypical software application was developed to assist the radiologist in functional analysis of thoracic CT data. By identifying the anatomic compartments of the lungs, the software application enables assessment of established functional CT parameters for each individual lung, pulmonary lobe, and pulmonary segment. Such region-based assessment allows a more localized diagnosis of lung diseases such as emphysema and more accurate estimation of regional lung function from CT data. With close cooperation between computer scientists and radiologists, the software application was tested and optimized to achieve a high degree of usability. Several clinical studies were carried out, the results of which indicated that the software application improves quantification in diagnosis, therapy planning, and therapy monitoring with respect to accuracy and time required.

A digital reference model of the human bronchial tree.

In-vitro preparations of the human lung combined with high-resolution tomography can be used to derive precise models of the human lung. To develop an abstract graph representation, specially adapted image processing algorithms were applied to segment and delineate the bronchi. The graph thus obtained contains topological information about spatial coordinates, connectivities, diameters and branching angles of 1453 bronchi up to the 17th Horsfield order. The graph was analyzed for statistical and fractal properties and was compared with current models. Results indicate a model that exhibits asymmetry and multifractal properties. This newly established reference model is an important step forward in geometrical accuracy of the bronchial tree representation that will improve both analysis of lung images in clinical imaging and the realism of functional simulations.