Computational modelling and optimisation of soft tissue outcome in cranio-maxillofacial surgery planning

Cranio-maxillofacial (CMF) surgery operations are associated with rearrangement of facial hard and soft tissues, leading to dramatic changes in facial geometry. Often, correction of the aesthetical patient's appearance is the primary objective of the surgical intervention. Due to the complexity of the facial anatomy and the biomechanical behaviour of soft tissues, the result of the surgical impact cannot always be predicted on the basis of surgeon's intuition and experience alone. Computational modelling of soft tissue outcome using individual tomographic data and consistent numerical simulation of soft tissue mechanics can provide valuable information for surgeons during the planning stage. In this article, we present a general framework for computer-assisted planning of CMF surgery interventions that is based on the reconstruction of patient's anatomy from 3D computer tomography images and finite element analysis of soft tissue deformations. Examples from our clinical case studies that deal with the solution of direct and inverse surgical problems (i.e. soft tissue prediction, inverse implant shape design) demonstrate that the developed approach provides a useful tool for accurate prediction and optimisation of aesthetic surgery outcome.     

Surgical planning of computer-assisted repositioning osteotomies

Repositioning osteotomies are frequently used in orthopedic surgery and traumatology to correct malpositions. Computed tomography (CT), stereolithographic models, and x-rays are used in planning. However, the precision achieved in the planning phase is usually not translated to patients. The Surgical Segment Navigator (SSN) is a navigation system that allows computer-assisted correction of malpositions. It consists of an infrared positioning device, two dynamic reference frames (DRF), an infrared pointer, and an infrared camera. All data are displayed numerically and graphically on the monitor of the SSN workstation. The Laboratory Unit for Computer-Assisted Surgery (LUCAS) is used for planning surgery in the laboratory. LUCAS requires only a native CT scan. A preparatory operation to implant bone markers that will be visible in x-rays and a further planning CT scan showing the bone markers, which were necessary with previous systems, are not required for the LUCAS and SSN system. This significantly reduces the radiation exposure of the patient and the costs of surgical planning. Measuring anatomical landmarks in the surgical site, which is time-consuming and reduces accuracy, is not required with the SSN system because the position of the infrared transmitters is known during surgical planning on the LUCAS workstation. This makes the surgical approach faster and much more precise. The surgical planning data are transferred to the surgical site using a data file and an individual surface pattern that fits the surface of the navigated bone segment. The data file is exported from the LUCAS-workstation to the SSN workstation. The planned spatial displacement of the infrared transmitters is saved in this file. The individual surface pattern carries the infrared transmitters. This pattern is the mechanical interface between infrared transmitters and navigated bone segment. The individual surface pattern can be polymerized directly on a small stereolithographic model of the navigated bone segment. The surface pattern can also be generated as negative form from a CT data set using a computer-assisted design/manufacture system. In summary, LUCAS and SSN allow for the computer-assisted correction of malpositions and positioning of artificial joints and implants. In principle, the systems can be used in all fields of surgery.     

An in silico target identification using Boolean network attractors: Avoiding pathological phenotypes

Target identification aims at identifying biomolecules whose function should be therapeutically altered to cure the considered pathology. An algorithm for in silico target identification using Boolean network attractors is proposed. It assumes that attractors correspond to phenotypes produced by the modeled biological network. It identifies target combinations which allow disturbed networks to avoid attractors associated with pathological phenotypes. The algorithm is tested on a Boolean model of the mammalian cell cycle and its applications are illustrated on a Boolean model of Fanconi anemia. Results show that the algorithm returns target combinations able to remove attractors associated with pathological phenotypes and then succeeds in performing the proposed in silico target identification. However, as with any in silico evidence, there is a bridge to cross between theory and practice. Nevertheless, it is expected that the algorithm is of interest for target identification.     

Distraction osteogenesis: a new surgical technique for use with the multiplanar mandibular distractor

If distraction osteogenesis is to reach its full potential and achieve the level of accuracy that is possible with orthognathic surgery, its outcomes need to be as predictable. To this end, the authors developed a planning process for distraction osteogenesis similar to that used in orthognathic surgery. However, the success of the planning process depends on the authors' ability to execute the plan at the time of surgery. As a result, the authors needed to develop a surgical technique that would enable them to precisely install the distractor as indicated in the presurgical plan. The surgical technique presented in this article was developed for this purpose. The authors used this technique in seven patients (four boys and three girls; age range, 4 to 10 years). Four patients presented with unilateral deformities, and three patients presented with bilateral deformities. The follow-up period in this group of patients ranged from 12 to 33 months. The purpose of the technique is to replicate the position of the distractor on the mandible as determined by the presurgical plan. To this purpose, a custom drill guide and a surgical template have been developed. Both of these are used following the principles of triangulation to establish the pin position and orientation of the distractor. In the authors' hands, the use of this surgical technique has resulted in outcomes close to those predicted by the planning process.     

MASKER: improved solvent-excluded molecular surface area estimations using Boolean masks

A fast algorithm for computing the solvent-accessible molecular surface area (SAS) using Boolean masks [Le Grand,S.M. and Merz,K.M.J. (1993). J. Comput. Chem., 14, 349-352) has been modified to estimate the solvent-excluded molecular surface area (SES), including contact, toroidal and re-entrant surface components. Numerical estimates of arc lengths of intersecting atomic SAS are used to estimate the toroidal surface and intersections between those arcs are used to estimate the re-entrant surface area. The new method is compared with an exact analytical method. Boolean molecular surface areas are continuous and pairwise differentiable and should be useful for molecular dynamics simulations, especially as the basis for an implicit solvent model.     

Algorithms for identifying Boolean networks and related biological networks based on matrix multiplication and fingerprint function.

Due to the recent progress of the DNA microarray technology, a large number of gene expression profile data are being produced. How to analyze gene expression data is an important topic in computational molecular biology. Several studies have been done using the Boolean network as a model of a genetic network. This paper proposes efficient algorithms for identifying Boolean networks of bounded indegree and related biological networks, where identification of a Boolean network can be formalized as a problem of identifying many Boolean functions simultaneously. For the identification of a Boolean network, an O(mnD+1) time naive algorithm and a simple O (mnD) time algorithm are known, where n denotes the number of nodes, m denotes the number of examples, and D denotes the maximum in degree. This paper presents an improved O(momega-2nD + mnD+omega-3) time Monte-Carlo type randomized algorithm, where omega is the exponent of matrix multiplication (currently, omega < 2.376). The algorithm is obtained by combining fast matrix multiplication with the randomized fingerprint function for string matching. Although the algorithm and its analysis are simple, the result is nontrivial and the technique can be applied to several related problems.     

Automated methodology for determination of stress distribution in human abdominal aortic aneurysm

Knowledge of impending abdominal aortic aneurysm (AAA) rupture can help in surgical planning. Typically, aneurysm diameter is used as the indicator of rupture, but recent studies have hypothesized that pressure-induced biomechanical stress may be a better predictor Verification of this hypothesis on a large study population with ruptured and unruptured AAA is vital if stress is to be reliably used as a clinical prognosticator for AAA rupture risk. We have developed an automated algorithm to calculate the peak stress in patient-specific AAA models. The algorithm contains a mesh refinement module, finite element analysis module, and a postprocessing visualization module. Several aspects of the methodology used are an improvement over past reported approaches. The entire analysis may be run from a single command and is completed in less than 1 h with the peak wall stress recorded for statistical analysis. We have used our algorithm for stress analysis of numerous ruptured and unruptured AAA models and report some of our results here. By current estimates, peak stress in the aortic wall appears to be a better predictor of rupture than AAA diameter. Further use of our algorithm is ongoing on larger study populations to convincingly verify these findings.     

Automated pelvic anatomical coordinate system is reproducible for determination of anterior pelvic plane

Most of computer-assisted planning systems need to determine the anatomical axis based on the anterior pelvic plane (APP). We analysed that our new system is more reproducible for determination of APP than previous methods. A pelvic model bone and two subjects suffering from hip osteoarthritis were evaluated. Multidetector-row computed tomography (MDCT) images were scanned with various rotations by MDCT scanner. The pelvic rotation was calibrated using silhouette images. APP was determined by an optimisation technique. The values of variation of APP caused by pelvic rotation were analysed with statistical analysis. APP determination with calibration and optimisation was most reproducible.The values of variance of APP were within 0.05° in model bone and 0.2° even in patient pelvis. Furthermore, the values of variance of APP with calibration/optimisation were significantly lower in comparison without calibration/optimisation. Both calibration and optimisation are actually required for determination of APP. This system could contribute to the evaluation of hip joint kinematics and computer-assisted surgery.     

Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning

The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost.     

Inferring qualitative relations in genetic networks and metabolic pathways

MOTIVATION: Inferring genetic network architecture from time series data of gene expression patterns is an important topic in bioinformatics. Although inference algorithms based on the Boolean network were proposed, the Boolean network was not sufficient as a model of a genetic network. RESULTS: First, a Boolean network model with noise is proposed, together with an inference algorithm for it. Next, a qualitative network model is proposed, in which regulation rules are represented as qualitative rules and embedded in the network structure. Algorithms are also presented for inferring qualitative relations from time series data. Then, an algorithm for inferring S-systems (synergistic and saturable systems) from time series data is presented, where S-systems are based on a particular kind of nonlinear differential equation and have been applied to the analysis of various biological systems. Theoretical results are shown for Boolean networks with noises and simple qualitative networks. Computational results are shown for Boolean networks with noises and S-systems, where real data are not used because the proposed models are still conceptual and the quantity and quality of currently available data are not enough for the application of the proposed methods.     

An algorithm for abdominal wall reconstruction

Acquired abdominal wall defects result from trauma, previous surgery, infection, and tumor resection. The correction of complex defects is a challenge to both plastic and reconstructive and general surgeons. The anatomy of the abdominal wall, as well as considerations in patient assessment and surgical planning, are discussed. A simple classification of abdominal wall defects based on size, depth, and location is provided. Publications regarding the various abdominal reconstruction techniques are reviewed and summarized to familiarize the reader with the treatment options for each particular defect. Finally, an algorithm is presented to guide the surgeon in selecting the optimal reconstructive technique.     

Interactive and graphic coupling between multiple alignments, secondary structure predictions and motif/pattern scanning into proteins

A computer module that includes multiple alignments, secondarystructure prediction, and site and pattern search has been developedand integrated into our ANTHEPROT software for protein sequenceanalysis. All the programs can be invokeed from within any routine,thus yielding multiple path to obtain final results. All theresults are graphically displayed. The main feature of thismodule is that all methods are connected in an interactive graphicmaimer. This module has been designed to display easily thepotential sites with conserved predicted structures.     

A Parallel Attractor Finding Algorithm Based on Boolean Satisfiability for Genetic Regulatory Networks

In biological systems, the dynamic analysis method has gained increasing attention in the past decade. The Boolean network is the most common model of a genetic regulatory network. The interactions of activation and inhibition in the genetic regulatory network are modeled as a set of functions of the Boolean network, while the state transitions in the Boolean network reflect the dynamic property of a genetic regulatory network. A difficult problem for state transition analysis is the finding of attractors. In this paper, we modeled the genetic regulatory network as a Boolean network and proposed a solving algorithm to tackle the attractor finding problem. In the proposed algorithm, we partitioned the Boolean network into several blocks consisting of the strongly connected components according to their gradients, and defined the connection between blocks as decision node. Based on the solutions calculated on the decision nodes and using a satisfiability solving algorithm, we identified the attractors in the state transition graph of each block. The proposed algorithm is benchmarked on a variety of genetic regulatory networks. Compared with existing algorithms, it achieved similar performance on small test cases, and outperformed it on larger and more complex ones, which happens to be the trend of the modern genetic regulatory network. Furthermore, while the existing satisfiability-based algorithms cannot be parallelized due to their inherent algorithm design, the proposed algorithm exhibits a good scalability on parallel computing architectures.     

Orbital and maxillofacial computer aided surgery: patient-specific finite element models to predict surgical outcomes

This paper addresses an important issue raised for the clinical relevance of Computer-Assisted Surgical applications, namely the methodology used to automatically build patient-specific finite element (FE) models of anatomical structures. From this perspective, a method is proposed, based on a technique called the mesh-matching method, followed by a process that corrects mesh irregularities. The mesh-matching algorithm generates patient-specific volume meshes from an existing generic model. The mesh regularization process is based on the Jacobian matrix transform related to the FE reference element and the current element.This method for generating patient-specific FE models is first applied to computer-assisted maxillofacial surgery, and more precisely, to the FE elastic modelling of patient facial soft tissues. For each patient, the planned bone osteotomies (mandible, maxilla, chin) are used as boundary conditions to deform the FE face model, in order to predict the aesthetic outcome of the surgery. Seven FE patient-specific models were successfully generated by our method. For one patient, the prediction of the FE model is qualitatively compared with the patient's post-operative appearance, measured from a computer tomography scan. Then, our methodology is applied to computer-assisted orbital surgery. It is, therefore, evaluated for the generation of 11 patient-specific FE poroelastic models of the orbital soft tissues. These models are used to predict the consequences of the surgical decompression of the orbit. More precisely, an average law is extrapolated from the simulations carried out for each patient model. This law links the size of the osteotomy (i.e. the surgical gesture) and the backward displacement of the eyeball (the consequence of the surgical gesture).     

A SAT-based algorithm for finding attractors in synchronous Boolean networks

This paper addresses the problem of finding attractors in synchronous Boolean networks. The existing Boolean decision diagram-based algorithms have limited capacity due to the excessive memory requirements of decision diagrams. The simulation-based algorithms can be applied to larger networks, however, they are incomplete. We present an algorithm, which uses a SAT-based bounded model checking to find all attractors in a Boolean network. The efficiency of the presented algorithm is evaluated by analyzing seven networks models of real biological processes, as well as 150,000 randomly generated Boolean networks of sizes between 100 and 7,000. The results show that our approach has a potential to handle an order of magnitude larger models than currently possible.     

Presurgical finite element simulation of scoliosis correction

For surgical correction of scoliotic spinal deformity, internal fixation systems apply lateral and distractive corrective forces. In order to gain maximal correction, a finite-element analysis of the spinal deformity correction technique has been carried out preoperatively, after first employing the spinal deformity correction finite-element model to determine the in vivo spinal stiffness. The presurgical analysis also gives us an appreciation of how the parameters of deformity, stiffness and corrective forces jointly contribute to the value of the correction index. The paper presents the methodology and clinical application. It also summarizes the results for ten patients, whereby the efficacy of presurgical analysis is assessed by comparing the corrective index values by presurgical simulation with the surgical results for equivalent levels of corrective forces.     

Effect of nitrogen addition,form and clipping on competitive interactions between grassland species

Aims Although the effects of N addition on plant biomass are well understood, we know a lot less about the importance of N form even though some studies have shown different impacts from reduced and oxidized forms of N. Furthermore, responses to grazing are likely to interact with the response to N addition. This experiment investigates the interactive effects of N addition and form with clipping on competition between three grassland species.Methods The three species (Anthoxanthum odoratum L., Plantago lanceolata L. and Prunella vulgaris L.) were grown alone and in combination with factorial additions of deionized water, sodium nitrate and ammonium chloride, and a clipping treatment. Above- and belowground biomass was harvested after 4 months.Important findings In monocultures, the results show increases in biomass with N addition, but clipping resulted in fewer changes with species displaying varying degrees of growth compensation. A. odoratum was the strongest competitor when grown with other species. In monocultures without clipping, N form was not important, but in the presence of clipping and in different species combinations, N form became important. Significant two- and three-way interactive effects were observed showing that complex interactions exist between N addition, clipping and species identity. The results have important implications when considering the effects of N deposition.     

Computer-assisted secondary reconstruction of unilateral posttraumatic orbital deformity

Until now, computer-assisted surgery has not been practiced as part of the surgical routine of posttraumatic orbital reconstruction. The purpose of this study was to investigate the use of a navigation system for computer-assisted preoperative planning with virtual reconstruction to obtain symmetry of the orbits and intraoperative control of virtual contours in comparison with the clinically achieved surgical results. A further objective of the computer-assisted orbital analysis was to use an ideal measurement for the two-dimensional and three-dimensional changes following orbital reconstruction and to check the equality of the postoperative values for the affected orbits in comparison with those of the unaffected sides. Patients with unilateral posttraumatic orbital defects (n = 18) underwent computer-assisted surgery and preoperative planning using a spiral computed tomography database. Surgical procedures were preplanned with virtual correction by mirroring an individually defined three-dimensional segment from the unaffected side onto the deformed side, creating an ideal unilateral reconstruction. These computer-models were intraoperatively used as virtual templates to navigate the preplanned contours and the globe projection using the Stryker-Leibinger navigation system. Individual noninvasive registration with an overall inaccuracy of approximately 1 mm was achieved by using a maxillary occlusal splint with four markers. The mirroring of the unaffected side allowed an ideal virtual reconstruction. A mean decrease in enlarged orbital volume of 4.0 (SD +/- 1.9) cm was achieved, as was a mean increase in the sagittal globe projection of 5.88 (SD +/- 2.98) mm. With a paired Student test, the decrease between the preoperative and postoperative differences of the affected and unaffected sides was proved significant for orbital volume, globe projection, and computed tomography-based Hertel scale changes (p < 0.01). In 15 of 18 cases, simultaneous malar bone advancement resulted primarily in an additional increase in orbital volume before intraorbital augmentation with calvarial split-bone grafts could be performed. Intraorbital bony augmentation included one (n = 1), two (n = 7), three (n = 8), and all four (n = 2) orbital walls. Computer-assisted preoperative planning enables the surgeon to predict reconstructive surgical steps before the operation. Highly vulnerable structures such as the optic nerve can be detected and avoided intraoperatively, and virtually preplanned bone graft positions and/or orbital frame contours can be checked. Computer-assisted preoperative planning and surgery thus advance the difficult surgical field of orbital reconstruction, particularly through a greater exploitation of radiologic information without additional radiation to the patient.     

DNA algorithm for an unbounded fan-in Boolean circuit

In this paper, we present a new DNA-based evaluation algorithm for a Boolean circuit that employs standard bio-molecular techniques. The algorithm operates on an unbounded fan-in Boolean circuit consisting of AND and OR gates. The whole simulation of our algorithm is proposed in a single test tube in O(1) time complexity and is much easier to implement in the laboratory than previously described models. Furthermore, the algorithm allows for evaluating any number of Boolean circuits in parallel in a single test tube.