Combined soft and skeletal tissue modelling of normal anddysmorphic midface postnatal development.

To get individualized facial three-dimensional finite element (FE) model from transformation of a generic one to assist orthodontic analysis and prediction of treatment-related morphological change of facial soft tissue. A generic three-dimensional FE model of craniofacial soft and hard tissue was constructed based on a volunteer's spiral CT data. Seven pairs of main peri-oral muscles were constructed based on a combination of CT image and anatomical method. Individualized model could be obtained through transformation of the generic model based on selection of corresponding anatomical landmarks and radial basis functions (RBF) method. Validation was analyzed through superimposition of the transformed model and cone-beam CT (CBCT) reconstruction data. Pre- and post-treatment CBCT data of two patients were collected, which were superimposed to gain the amount of anterior teeth retraction and anterior alveolar surface remodeling that could be used as boundary condition. Different values of Poisson ratio ν and Young's modulus E were tested during simulation. Average deviation was 0.47 mm and 0.75 mm in the soft and hard tissue respectively. It could be decreased to a range of +0.29 mm and -0.21 mm after a second transformation at the lip-mouth region. The best correspondence between simulation and post-treatment result was found with elastic properties of soft tissues defined as follows. Poisson ratio ν for skin, muscle and fat being set as 0.45 while Young's modulus being set as 90.0 kPa, 6.2 kPa and 2.0 kPa respectively. Individualized three-dimensional facial FE model could be obtained through mathematical model transformation. With boundary condition defined according to treatment plan such FE model could be used to analyze the effect of orthodontic treatment on facial soft tissue.

A finite nonlinear hyper-viscoelastic model for soft biological tissues

Soft Tissue Modeling for Surgery Simulation

Treacher Collins syndrome (TCS) is associated with abnormal differentiation of the first and second pharyngeal arches, occurring during fetal development. Features of TCS include microtia with conductive hearing loss, slanting palpebral fissures with possibly coloboma of the lateral part of lower eyelids, midface hypoplasia, micrognathia as well as sporadically cleft palate and choanal atresia or stenosis. TCS occurs in the general population at a frequency of 1 in 50,000 live births. Four subtypes of Treacher Collins syndrome exist. TCS can be caused by pathogenic variants in the TCOF1, POLR1D, POLR1C and POLR1B genes. Genetically, the TCOF1 gene contains 27 exons which encodes the Treacle protein. In TCOF1, over 200 pathogenic variants have been identified, of which most are deletions leading to a frame-shift, that result in the formation of a termination codon. In the presented article, we review the genetics and phenotype of TCS as well as the management and surgical procedures utilized for treatment.

Imbalance of stress/strain microenvironment can lead to adverse remodelling and pathogenesis in various soft tissues, tumour included. Therefore, there is a critical need for accurate quantification of the biomechanical homeostasis in soft tissue through mathematical modelling, which is critically dependent on constitutive models, the mathematical descriptions that approximate the mechanical behaviours of material under specific conditions by considering information from subcellular, cellular and tissue levels. In most soft biological tissue, collagen is the major component of the extracellular matrix, its architecture largely determines the material property (stiffness). In this work, we will use myocardium as an example to show how we can develop a constitutive law from various ex vivo experiments within the continuum mechanics framework, and demonstrate the applications to real patient data. We will further focus on parameter calibrations from ex/in vivo measurements. We believe this approach of constitutive modelling and calibration can be applied to various soft biological tissues and shed light on physiological and pathological mechanobiology.

Treacher Collins syndrome is the most common mandibulofacial dysostosis of autosomal dominant or, rarely, recessive inheritance. Affected fetuses may be identified by prenatal ultrasound or diagnosed at autopsy in case of perinatal death or pregnancy termination. We describe the ultrasonographic, autopsy, and molecular findings in a 25-week-gestation affected fetus, and review the clinical, prenatal, and postmortem findings in 15 previously reported fetal and perinatal cases. A nearly complete spectrum of the typical facial characteristics can be present by the early second trimester of gestation, including subtle defects such as lower eyelid colobomas. Mandibular hypoplasia and bilateral auricle defects were constant findings in the affected fetal population. Downslanting palpebral fissures were the second more common feature, followed by midface hypoplasia, polyhydramnios, and ocular defects. Association with Pierre Robin sequence was common (38%) in the reviewed series. Previously unreported pectus carinatum was noted in our case bearing a heterozygous TCOF1 mutation. Other unique reported findings include salivary gland hyperplasia, single umbilical artery, and tracheo-esophageal fistula, all in molecularly unconfirmed cases. Treacher Collins syndrome can be prenatally detected by ultrasound and should be included in the wide range of genetic syndromes that can be diagnosed at perinatal autopsy. Affected fetuses tend to have a more severe phenotype than living patients. The reported association of Treacher Collins syndrome type 1 with pectus carinatum expands the phenotype, provides information on genotype-phenotype correlation, and suggests possible pathogenetic interactions between neural crest cell disorders and the formation of the sternum that merit investigation.

Finite element implementation of a stochastic three dimensional finite-strain damage model for fibrous soft tissue

Background: Treacher Collins Syndrome (TCS) is a rare, congenital craniofacial syndrome. Its most characteristic feature is mandibular and midface hypoplasia. Due to malformations of the facial skeleton, airway abnormalities can also be observed, predisposing individuals to obstructive sleep apnoea (OSA). OSA in TCS may contribute to significant morbidity, including developmental delays, cardiovascular disorders and reduced quality of life. Objectives: This narrative review aims to present the true prevalence of OSA and the treatment options for TCS patients. Additionally, the pathophysiology and diagnostic tools for this condition were briefly outlined. Methods: The literature search included publications from PubMed, Scopus, Web of Science and Cochrane Library. The chosen period of time for these publications was 2000-2024. Results: The results showed that OSA is a serious problem among TCS patients. Although there is no standardised treatment protocol, the primary methods often include mandibular distraction osteogenesis (MDO) and continuous positive airway pressure (CPAP). Approaches such as hypoglossal nerve stimulation (HNS) need further investigation, especially with longitudinal observations. Conclusions: The development of treatment options seems to be promising, suggesting a favourable outlook for standardising the treatment protocols.

A nonlinear-elastic constitutive model for soft connective tissue based on a histologic description: Application to female pelvic soft tissue

Virtual surgery is a typical application of virtual reality technology in the medical field, which can help improve the success rate of surgery and reduce medical costs in various aspects such as medical training, surgery planning, and intraoperative navigation, and is becoming a hot research topic and a frontier subject in the medical field. The establishment of virtual surgery simulation system involves the intersection and penetration of various disciplines, and the research is difficult, and many functional modules are still not perfect. This study focuses on the key technologies in the virtual surgery simulation system, focusing on two core modules, the soft tissue modeling method and the collision detection algorithm, to improve the accuracy of the soft tissue model deformation under the condition of meeting the real-time system. The biomechanical properties of soft tissues are studied, the viscoelastic properties are analyzed, and the viscoelastic theory is used as the basis for soft tissue modeling; the geometric model is established by using a complementary method of surface model and tetrahedral mesh cells, with the surface model covering the outer surface for visual rendering and the tetrahedral mesh cells for skeleton support of the physical model, so that the model has a better visual effect and deformation effect, which enhances the model fidelity that is enhanced by the better visual effect and deformation effect; the soft tissue physical modeling method is summarized and summarized to lay the foundation for soft tissue model optimization. The experimental results show that the bilateral teleoperation system under analog control can give the operator a better haptic sensation (smaller value of input impedance felt by the operator when doing free motion from the robot) while ensuring good positional tracking and force tracking effects. This method solves the problems of collapse distortion and lack of viscoelastic properties of the traditional mass-spring model, and improves the accuracy of model deformation. Based on the improved algorithm, the viscoelastic hybrid filled sphere model of the liver organ is successfully established, which proves that the modeling method is feasible and effective.

Soft tissue force modeling with the approach of creating a force-feedback simulator for training medical skills has been the focus of many attempts up to now. The most important parameter considered in soft tissue modeling, is its being real-time along with its precision and high sensitivity. In this article, using ANFIS (Adaptive Neuro Fuzzy Inference System), a neuro-fuzzy model is presented for soft tissue force modeling. In order to evaluate the efficiency of the model, it has been used for simulated training of breast cancerous tumors diagnosis using a haptic interface. Data needed for training neuro-fuzzy network related to the model, is provided from breast tissue modeling in ANSYS 12.0 software. In validating session, numerical data have been confirmed with the experimental data with an average error of less than 3%. Testing session indicates root mean square error of the model to be about 0.02 (N), which shows a high degree of precision for the model. The presented model's real-time feature is about 100 times of the maximum needed amount for force modeling simulations.

Aim:Treacher Collins syndrome is a rare congenital disorder of craniofacial development with a highly variable pheonotype. This syndrome occurs with an incidence of 1:50,000, and more than 60% of the cases have no previous family history and arise as the result of de novo mutations. The disorder displays an intricate underlying dysmorphology. Affected patients may suffer life-threatening airway complications and functional difficulties involving sight, hearing, speech, and feeding. Deformation of facial structures produces a characteristic appearance that includes malar-zygomatic hypoplasia, periorbital soft tissue anomalies, maxillomandibular hypoplasia, and ear anomalies. Management requires a specialized craniofacial team, as comprehensive care starts at birth and may require life-long follow-up. Standard craniofacial procedures for bony and soft tissue reconstruction are used. This article outlines current treatment strategies and future concepts for surgical and regenerative management. Methods:The new field of regenerative medicine and therapy offers the promise to improve some of these treatments. In particular, Structural Fat Grafting (lipostructure) seems to be a good strategy to restore the normal volume and contour of the face, and to provide a source of adipose-derived stem cells (ADSCs) with a multilineage differentiation potential. In this work, we present the case of a young girl with Treacher Collins Syndrome who underwent serial sessions of fat grafting in addition to other surgical bony reconstructive techniques. ADSCs have been isolated from the patient’s lipoaspirate, and compared for their stemness properties with those of a healthy subject. Conclusion:Screening of the genome of the Treacher Collins patient using array-Comparative Genomic Hybridization (array-CGH) allowed us to identify some chromosomal imbalances that are probably associated with the syndrome.Correction of these imbalances and asymmetries by modulating ADSCs could be an innovative approach to improve and stabilize the results of the surgical treatment of Treacher Collin Syndrome.

In the planning of maxillofacial surgery, accurately evaluating the postoperative soft tissue area is crucial. This allows doctors to provide patients with better morphological recovery while ensuring the restoration of normal functional areas. This study aims to develop an advanced automatic algorithm for the completion of soft tissue defects, enhancing the accuracy and effectiveness of surgical planning. We introduce a point cloud completion method based on Generative Adversarial Networks. Firstly, we remove the defective regions, reserving the healthy tissues and converting them into point clouds. Then, using the soft tissue completion network, we reconstruct the defective areas and generate the corresponding point cloud images. Finally, we combine the healthy point cloud with the generated defective regions to produce a complete soft tissue image and model of the patient's face. To validate our approach, we conduct qualitative and quantitative experiments on 20 normal individuals (10 males and 10 females). Compared with several existing algorithms, our method shows superior significance in soft tissue prediction. The Root Mean Squared Error between the generated model and ground truth is 1.45 ± 0.25 mm, and the Surface Distance error is 0.69 ± 0.13 mm. The visualization results show that using our network to generate soft tissue at the defect site is more structurally consistent. This study introduces a novel point cloud generation network for reconstructing facial soft tissue images, which provides accurate and structurally consistent morphological outcomes. The proposed method shows great potential in improving the quality and accuracy of surgical planning in maxillofacial surgery.

Predicting biological soft tissue interaction is of great interest for developing computer-aided decision systems. This study aims to develop and evaluate a novel deep-learning approach based on the recurrent neural network for predicting facial soft tissue impact with a rubber ball. A computational workflow was established including a subject-specific finite element model of the facial soft tissue under interaction with the rubber ball. A series of simulations under different ball velocities was performed to build the learning database. We implemented a long-short-term memory (LSTM) model and then evaluated its performance using root mean square error (RMSE) and regression coefficient metrics. The obtained results showed a RMSE of 3.13 mm and a Pearson correlation coefficient of 0.98 for soft tissue displacement prediction. A RMSE of 0.001 MPa and a Pearson correlation coefficient of 0.94 was also obtained for soft tissue von Mises stress prediction. The present study showed the robustness and accuracy of the recurrent neural network for predicting complex soft tissue interaction behaviours. Our findings open new avenues for deploying novel deep learning workflow for human-facial softtissue interaction. As perspective, this workflow will be integrated into our interactive facial analysis and rehabilitation system.

There is wealth of data from experimental and numerical methods of analysing and modelling soft connective tissues of joints. In recent years, the advances in computational and technological capabilities allowed for several aspects of the function and mechanical behaviour of soft connective tissues of joints to be explored. However, the nature of soft tissue poses a great challenge in characterizing its material behaviour in a repeatable and physiologically or clinically relevant manner. This review article attempts to present, critique, and suggest experimental and numerical methods that are associated with the function and mechanical response of soft connective tissues of joints.