A new system for computer-aided preoperative planning and intraoperative navigation during corrective jaw surgery

A new system for computer-aided corrective surgery of the jaws has been developed and introduced clinically. It combines three-dimensional (3-D) surgical planning with conventional dental occlusion planning. The developed software allows simulating the surgical correction on virtual 3-D models of the facial skeleton generated from computed tomography (CT) scans. Surgery planning and simulation include dynamic cephalometry, semi-automatic mirroring, interactive cutting of bone and segment repositioning. By coupling the software with a tracking system and with the help of a special registration procedure, we are able to acquire dental occlusion plans from plaster model mounts. Upon completion of the surgical plan, the setup is used to manufacture positioning splints for intraoperative guidance. The system provides further intraoperative assistance with the help of a display showing jaw positions and 3-D positioning guides updated in real time during the surgical procedure. The proposed approach offers the advantages of 3-D visualization and tracking technology without sacrificing long-proven cast-based techniques for dental occlusion evaluation. The system has been applied on one patient. Throughout this procedure, we have experienced improved assessment of pathology, increased precision, and augmented control.

Safety of Active Implantable Devices during MRI Examinations: A Finite Element Analysis of an Implantable Pump

The goal of this study was to propose a general numerical analysis methodology to evaluate the magnetic resonance imaging (MRI)-safety of active implants. Numerical models based on the finite element (FE) technique were used to estimate if the normal operation of an active device was altered during MRI imaging. An active implanted pump was chosen to illustrate the method. A set of controlled experiments were proposed and performed to validate the numerical model. The calculated induced voltages in the important electronic components of the device showed dependence with the MRI field strength. For the MRI radiofrequency fields, significant induced voltages of up to 20 V were calculated for a 0.3T field-strength MRI. For the 1.5 and 3.0T MRIs, the calculated voltages were insignificant. On the other hand, induced voltages up to 11 V were calculated in the critical electronic components for the 3.0T MRI due to the gradient fields. Values obtained in this work reflect to the worst case situation which is virtually impossible to achieve in normal scanning situations. Since the calculated voltages may be removed by appropriate protection circuits, no critical problems affecting the normal operation of the pump were identified. This study showed that the proposed methodology helps the identification of the possible incompatibilities between active implants and MR imaging, and can be used to aid the design of critical electronic systems to ensure MRI-safety

Accurate and robust reconstruction of proximal femur from sparse intraoperative data and dense point distribution model for surgical navigation

Constructing a 3D surface model from sparse-point data is a nontrivial task. Here, we report an accurate and robust approach for reconstructing a surface model of the proximal femur from sparse-point data and a dense-point distribution model (DPDM). The problem is formulated as a three-stage optimal estimation process. The first stage, affine registration, is to iteratively estimate a scale and a rigid transformation between the mean surface model of the DPDM and the sparse input points. The estimation results of the first stage are used to establish point correspondences for the second stage, statistical instantiation, which stably instantiates a surface model from the DPDM using a statistical approach. This surface model is then fed to the third stage, kernel-based deformation, which further refines the surface model. Handling outliers is achieved by consistently employing the least trimmed squares (LTS) approach with a roughly estimated outlier rate in all three stages. If an optimal value of the outlier rate is preferred, we propose a hypothesis testing procedure to automatically estimate it. We present here our validations using four experiments, which include 1 leave-one-out experiment, 2 experiment on evaluating the present approach for handling pathology, 3 experiment on evaluating the present approach for handling outliers, and 4 experiment on reconstructing surface models of seven dry cadaver femurs using clinically relevant data without noise and with noise added. Our validation results demonstrate the robust performance of the present approach in handling outliers, pathology, and noise. An average 95-percentile error of 1.7-2.3 mm was found when the present approach was used to reconstruct surface models of the cadaver femurs from sparse-point data with noise added.

Development of a computer-assisted high-pressure Injection device for vertebroplasty

A novel computer-assisted injection device for the delivery of highly viscous bone cements in vertebroplasty is presented. It addresses the shortcomings of manual injection systems ranging from low-pressure and poor level of control to device failure. The presented instrument is capable of generating a maximum pressure of 5000 kPa in traditional 6-ml syringes and provides an advanced control interface for precise cement delivery from outside radiation fields emitted by intraoperative imaging systems. The integrated real-time monitoring of injection parameters, such as flow-rate, volume, pressure, and viscosity, simplifies consistent documentation of interventions and establishes a basis for the identification of safe injection protocols on the longer term. Control algorithms prevent device failure due to overloading and provide means to immediately stop cement flow to avoid leakage into adjacent tissues.

Highly efficient in vivo agonist-induced internalization of sst2 receptors in somatostatin target tissues

The successful peptide receptor imaging of tumors, as exemplified for somatostatin receptors, is based on the overexpression of peptide receptors in selected tumors and the high-affinity binding to these tumors of agonist radioligands that are subsequently internalized into the tumor cells in which they accumulate. Although in vitro studies have shown ample evidence that the ligand-receptor complex is internalized, in vivo evidence of agonist-induced internalization of peptide receptors, such as somatostatin receptors, is missing. METHODS: Rats subcutaneously transplanted with the somatostatin receptor subtype 2 (sst(2))-expressing AR42J tumor cells were treated with intravenous injections of various doses of the sst(2) agonist [Tyr(3), Thr(8)]-octreotide (TATE) or of the sst(2) antagonist 1,4,7,10-tetraazacyclododecane-N,N',N'',N''',-tetraacetic acid (DOTA)-Bass and were sacrificed at various times ranging from 2.5 min to 24 h after injection. The tumors and pancreas were then removed from each animal. All tissue samples were processed for sst(2) immunohistochemistry using sst(2)-specific antibodies. RESULTS: Compared with the sst(2) receptors in untreated animals, which localized at the plasma membrane in pancreatic and AR42J tumor cells, the sst(2) receptors in treated animals are detected intracellularly after an intravenous injection of the agonist TATE. Internalization is fast, as the receptors are already internalizing 2.5 min after TATE injection. The process is extremely efficient, as most of the cell surface receptors internalize into the cell and are found in endosomelike structures after TATE injection. The internalization is most likely reversible, because 24 h after injection the receptors are again found at the cell surface. The process is also agonist-dependent, because internalization is seen with high-affinity sst(2) agonists but not with high-affinity sst(2) antagonists. The same internalization properties are seen in pancreatic and AR42J tumor cells. They can further be confirmed in vitro in human embryonic kidney-sst(2) cells, with an immunofluorescence microscopy-based sst(2) internalization assay. CONCLUSION: These animal data strongly indicate that the process of in vivo sst(2) internalization after agonist stimulation is fast, extremely efficient, and fully functional under in vivo conditions in neoplastic and physiologic sst(2) target tissues. This molecular process is, therefore, likely to be responsible for the high and long-lasting uptake of sst(2) radioligands seen in vivo in sst(2)-expressing tumors.

Quantitative assessment of oral orbicular muscle deformation after cleft lip reconstruction: an ultrasound elastography study

Reconstruction of a cleft lip leads inevitably to scar tissue formation. Scar tissue within the restored oral orbicular muscle might be assessed by quantification of the local contractility of this muscle. Furthermore, information about the contraction capability of the oral orbicular muscle is crucial for planning the revision surgery of an individual patient. We used ultrasound elastography to determine the local deformation (strain) of the upper lip and to differentiate contracting muscle from passive scar tissue. Raw ultrasound data (radio-frequency format; rf-) were acquired, while the lips were brought from normal state into a pout condition and back in normal state, in three patients and three normal individuals. During this movement, the oral orbicular muscle contracts and, consequently, thickens in contrast to scar tissue that will not contract, or even expand. An iterative coarse-to-fine strain estimation method was used to calculate the local tissue strain. Analysis of the raw ultrasound data allows estimation of tissue strain with a high precision. The minimum strain that can be assessed reproducibly is 0.1%. In normal individuals, strain of the orbicular oral muscle was in the order of 20%. Also, a uniform strain distribution in the oral orbicular muscle was found. However, in patients deviating values were found in the region of the reconstruction and the muscle tissue surrounding that. In two patients with a successful reconstruction, strain was reduced by 6% in the reconstructed region with respect to the normal parts of the muscle (from 22% to 16% and from 25% to 19%). In a patient with severe aesthetical and functional disability, strain decreased from 30% in the normal region to 5% in the reconstructed region. With ultrasound elastography, the strain of the oral orbicular muscle can be quantified. In healthy subjects, the strain profiles and maximum strain values in all parts of the muscle were similar. The maximum strain of the muscle during pout was 20% +/- 1%. In surgically repaired cleft lips, decreased deformation was observed.

A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier

In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.