Immune Analysis Using Vitreous Optical Coherence Tomography Imaging in Rats with Steroid-Induced Glaucoma.

Glaucoma is a multifactorial pathology involving the immune system. The subclinical immune response plays a homeostatic role in healthy situations, but in pathological situations, it produces imbalances. Optical coherence tomography detects immune cells in the vitreous as hyperreflective opacities and these are subsequently characterised by computational analysis. This study monitors the changes in immunity in the vitreous in two steroid-induced glaucoma (SIG) animal models created with drug delivery systems (microspheres loaded with dexamethasone and dexamethasone/fibronectin), comparing both sexes and healthy controls over six months. SIG eyes tended to present greater intensity and a higher number of vitreous opacities (p < 0.05), with dynamic fluctuations in the percentage of isolated cells (10 µm2), non-activated cells (10-50 µm2), activated cells (50-250 µm2) and cell complexes (>250 µm2). Both SIG models presented an anti-inflammatory profile, with non-activated cells being the largest population in this study. However, smaller opacities (isolated cells) seemed to be the first responder to noxa since they were the most rounded (recruitment), coinciding with peak intraocular pressure increase, and showed the highest mean Intensity (intracellular machinery), even in the contralateral eye, and a major change in orientation (motility). Studying the features of hyperreflective opacities in the vitreous using OCT could be a useful biomarker of glaucoma.

The macular retinal ganglion cell layer as a biomarker for diagnosis and prognosis in multiple sclerosis: A deep learning approach.

PURPOSE: The macular ganglion cell layer (mGCL) is a strong potential biomarker of axonal degeneration in multiple sclerosis (MS). For this reason, this study aims to develop a computer-aided method to facilitate diagnosis and prognosis in MS. METHODS: This paper combines a cross-sectional study of 72 MS patients and 30 healthy control subjects for diagnosis and a 10-year longitudinal study of the same MS patients for the prediction of disability progression, during which the mGCL was measured using optical coherence tomography (OCT). Deep neural networks were used as an automatic classifier. RESULTS: For MS diagnosis, greatest accuracy (90.3%) was achieved using 17 features as inputs. The neural network architecture comprised the input layer, two hidden layers and the output layer with softmax activation. For the prediction of disability progression 8 years later, accuracy of 81.9% was achieved with a neural network comprising two hidden layers and 400 epochs. CONCLUSION: We present evidence that by applying deep learning techniques to clinical and mGCL thickness data it is possible to identify MS and predict the course of the disease. This approach potentially constitutes a non-invasive, low-cost, easy-to-implement and effective method.

In silico approach towards neuro-occlusal rehabilitation for the early correction of asymmetrical development in a unilateral crossbite patient.

Neuro-occlusal rehabilitation (N.O.R.) is a discipline of the stomatognathic medicine that defends early treatments of functional malocclusions, such as unilateral crossbite, for the correction of craniofacial development, avoiding surgical procedures later in life. Nevertheless, N.O.R.'s advances have not been proved analytically yet due to the difficulties of evaluate the mechanical response after the treatment. This study aims to evaluate computationally the effect of N.O.R.'s treatments during childhood. Therefore, bilateral chewing and maximum intercuspation occlusion were modelled through a detailed finite element model of a paediatric craniofacial complex, before and after different selective grinding-alternatives. This model was subjected to the muscular forces derived from a musculoskeletal model and was validated by the occlusal contacts recorded experimentally. This approach yielded errors below 2% and reproduced successfully the occlusal, muscular, functional and mechanical imbalance before the therapies. Treatment strategies balanced the occlusal plane and reduced the periodontal overpressure (>4.7 kPa) and the mandibular over deformation (>0.002 ε) on the crossed side. Based on the principles of the mechanostat theory of bone remodelling and the pressure-tension theory of tooth movement, these findings could also demonstrate how N.O.R.'s treatments correct the malocclusion and the asymmetrical development of the craniofacial complex. Besides, N.O.R.'s treatments slightly modified the stress state and functions of the temporomandibular joints, facilitating the chewing by the unaccustomed side. These findings provide important biomechanical insights into the use of N.O.R.'s treatments for the correction of unilateral crossbite, but also encourage the application of computing methods in biomedical research and clinical practise.

Tunable degrees of neurodegeneration in rats based on microsphere-induced models of chronic glaucoma.

This study compares four different animal models of chronic glaucoma against normal aging over 6 months. Chronic glaucoma was induced in 138 Long-Evans rats and compared against 43 aged-matched healthy rats. Twenty-five rats received episcleral vein sclerosis injections (EPIm cohort) while the rest were injected in the eye anterior chamber with a suspension of biodegradable microspheres: 25 rats received non-loaded microspheres (N-L Ms cohort), 45 rats received microspheres loaded with dexamethasone (MsDexa cohort), and 43 rats received microspheres co-loaded with dexamethasone and fibronectin (MsDexaFibro cohort). Intraocular pressure, neuroretinal function, structure and vitreous interface were evaluated. Each model caused different trends in intraocular pressure, produced specific retinal damage and vitreous signals. The steepest and strongest increase in intraocular pressure was seen in the EPIm cohort and microspheres models were more progressive. The EPIm cohort presented the highest vitreous intensity and percentage loss in the ganglion cell layer, the MsDexa cohort presented the greatest loss in the retinal nerve fiber layer, and the MsDexaFibro cohort presented the greatest loss in total retinal thickness. Function decreased differently among cohorts. Using biodegradable microspheres models it is possible to generate tuned neurodegeneration. These results support the multifactorial nature of glaucoma based on several noxa.

Comparison of Machine Learning Methods Using Spectralis OCT for Diagnosis and Disability Progression Prognosis in Multiple Sclerosis.

Machine learning approaches in diagnosis and prognosis of multiple sclerosis (MS) were analysed using retinal nerve fiber layer (RNFL) thickness, measured by optical coherence tomography (OCT). A cross-sectional study (72 MS patients and 30 healthy controls) was used for diagnosis. These 72 MS patients were involved in a 10-year longitudinal follow-up study for prognostic purposes. Structural measurements of RNFL thickness were performed using different Spectralis OCT protocols: fast macular thickness protocol to measure macular RNFL, and fast RNFL thickness protocol and fast RNFL-N thickness protocol to measure peripapillary RNFL. Binary classifiers such as multiple linear regression (MLR), support vector machines (SVM), decision tree (DT), k-nearest neighbours (k-NN), Naïve Bayes (NB), ensemble classifier (EC) and long short-term memory (LSTM) recurrent neural network were tested. For MS diagnosis, the best acquisition protocol was fast macular thickness protocol using k-NN (accuracy: 95.8%; sensitivity: 94.4%; specificity: 97.2%; precision: 97.1%; AUC: 0.958). For MS prognosis, our model with a 3-year follow up to predict disability progression 8 years later was the best predictive model. DT performed best for fast macular thickness protocol (accuracy: 91.3%; sensitivity: 90.0%; specificity: 92.5%; precision: 92.3%; AUC: 0.913) and SVM for fast RNFL-N thickness protocol (accuracy: 91.3%; sensitivity: 87.5%; specificity: 95.0%; precision: 94.6%; AUC: 0.913). This work concludes that measurements of RNFL thickness obtained with Spectralis OCT have a good ability to diagnose MS and to predict disability progression in MS patients. This machine learning approach would help clinicians to have valuable information.

Biomechanical evaluation of the unilateral crossbite on the asymmetrical development of the craniofacial complex. A mechano-morphological approach.

BACKGROUND AND OBJECTIVE: The occlusion effect on the craniofacial development is a controversial topic that has attracted the interest of many researchers but that remains unclear, mainly due to the difficulties on measure its mechanical response experimentally. This mechano-morphological relationship of the craniofacial growth is often explained by the periosteal and capsular matrices of the functional matrix hypothesis (FMH); however, its outcomes have not been analytically demonstrated yet. This computational study aims, therefore, to analytically demonstrate the mechano-morphological relationship in the craniofacial development of children with unilateral crossbite (UXB) using the finite element (FE) method. METHODS: The craniofacial complex asymmetry of ten children, five of whom exhibit UXB, was 3D-analysed and compared with the biomechanical response computed from a FE analysis of each patient's occlusion. Due to the complexity of the geometry and the multitude of contacts involved, the inherent limitations of the model were evaluated by comparing computed occlusal patterns with those recorded by an occlusal analysis on 3D printed copies. RESULTS: Comparison's outcomes proved the reliability of our models with just a deviation error below 6% between both approaches. Out of validation process, computational results showed that the significant elongation of mandibular branch in the contralateral side could be related to the mandibular shift and increase of thickness on the crossed side, and particularly of the posterior region. These morphological changes could be associated with periodontal overpressure (>4.7 kPa) and mandibular over deformation (0.002 ε) in that side, in agreement with the periosteal matrix's principles. Furthermore, the maxilla's transversal narrowing and the elevation of the maxillary and zygomatic regions on the crossed side were statistically demonstrated and seem to be related with their respective micro displacements at occlusion, as accounted by their specific capsule matrices. Our results were consistent with those reported clinically and demonstrated analytically the mechano-morphological relationship of children's craniofacial development based on the FMH's functional matrices. CONCLUSIONS: This study is a first step in the understanding of the occlusion's effect on the craniofacial development by computational methods. Our approach could help future engineers, researchers and clinicians to understand better the aetiology of some dental malocclusions and functional disorders improve the diagnosis or even predict the craniofacial development.

Analysis of Parainflammation in Chronic Glaucoma Using Vitreous-OCT Imaging.

Glaucoma causes blindness due to the progressive death of retinal ganglion cells. The immune response chronically and subclinically mediates a homeostatic role. In current clinical practice, it is impossible to analyse neuroinflammation non-invasively. However, analysis of vitreous images using optical coherence tomography detects the immune response as hyperreflective opacities. This study monitors vitreous parainflammation in two animal models of glaucoma, comparing both healthy controls and sexes over six months. Computational analysis characterizes in vivo the hyperreflective opacities, identified histologically as hyalocyte-like Iba-1+ (microglial marker) cells. Glaucomatous eyes showed greater intensity and number of vitreous opacities as well as dynamic fluctuations in the percentage of activated cells (50-250 microns2) vs. non-activated cells (10-50 microns2), isolated cells (10 microns2) and complexes (>250 microns2). Smaller opacities (isolated cells) showed the highest mean intensity (intracellular machinery), were the most rounded at earlier stages (recruitment) and showed the greatest change in orientation (motility). Study of vitreous parainflammation could be a biomarker of glaucoma onset and progression.

Biomechanical impact of the porous-fibrous tissue behaviour in the temporomandibular joint movements. An in silico approach.

The movement of the temporomandibular joint (TMJ) is a function of its complex geometry and its interaction with the surrounding soft tissues. Owing to an increase in the prevalence of temporomandibular joint disorders (TMDs), many computational studies have attempted to characterize its biomechanical behaviour in the last 2 decades. However, most such studies are based on a single computational model that markedly simplifies the complex geometry and mechanical properties of the TMJ's soft tissues. The present study aims to computationally evaluate in a wider sample the importance of considering their complex anatomy and behaviour for simulating both damping and motion responses of this joint. Hence, 6 finite element models of healthy volunteers' TMJ were developed and subjected to both conditions in two different behavioural scenarios. In one, the soft tissues' behaviour was modelled by considering the porous-fibrous properties, whereas in the other case they were simplified assuming isotropic-hyperelastic response, as had been traditionally considered. The damping analysis, which mimic the conditions of an experimental test of the literature, consisted of applying two different compressive loads to the jaw. The motion analysis evaluated the condylar path during the mandible centric depression by the action of muscular forces. From the results of both analyses, the contact pressures, intra-articular fluid pressure, path features, and stress/strain values were compared using the porous-fibrous and isotropic-hyperelastic models. Besides the great differences observed between patients due patient-specific morphology, the porous-fibrous approach yielded results closer to the reference experimental values and to the outcomes of other computational studies of the literature. Our findings underscore, therefore, the importance of considering realistic joint geometries and porous-fibrous contribution in the computational modelling of the TMJ, but also in the design of further joint replacements or in the development of new biomaterials for this joint.

Machine learning in diagnosis and disability prediction of multiple sclerosis using optical coherence tomography.

BACKGROUND: Multiple sclerosis (MS) is a neurodegenerative disease that affects the central nervous system, especially the brain, spinal cord, and optic nerve. Diagnosis of this disease is a very complex process and generally requires a lot of time. In addition, treatments are applied without any information on the disability course in each MS patient. For these two reasons, the objective of this study was to improve the MS diagnosis and predict the long-term course of disability in MS patients based on clinical data and retinal nerve fiber layer (RNFL) thickness, measured by optical coherence tomography (OCT). MATERIAL AND METHODS: A total of 104 healthy controls and 108 MS patients, 82 of whom had a 10-year follow-up, were enrolled. Classification algorithms such as multiple linear regression (MLR), support vector machines (SVM), decision tree (DT), k-nearest neighbours (k-NN), Naïve Bayes (NB), ensemble classifier (EC) and long short-term memory (LSTM) recurrent neural network were tested to develop two predictive models: MS diagnosis model and MS disability course prediction model. RESULTS: For MS diagnosis, the best result was obtained using EC (accuracy: 87.7%; sensitivity: 87.0%; specificity: 88.5%; precision: 88.7%; AUC: 0.8775). In line with this good performance, the accuracy was 85.4% using k-NN and 84.4% using SVM. And, for long-term prediction of MS disability course, LSTM recurrent neural network was the most appropriate classifier (accuracy: 81.7%; sensitivity: 81.1%; specificity: 82.2%; precision: 78.9%; AUC: 0.8165). The use of MLR, SVM and k-NN also showed a good performance (AUC ≥ 0.8). CONCLUSIONS: This study demonstrated that machine learning techniques, using clinical and OCT data, can help establish an early diagnosis and predict the course of MS. This advance could help clinicians select more specific treatments for each MS patient. Therefore, our findings underscore the potential of RNFL thickness as a reliable MS biomarker.

Monitoring New Long-Lasting Intravitreal Formulation for Glaucoma with Vitreous Images Using Optical Coherence Tomography.

Intravitreal injection is the gold standard therapeutic option for posterior segment pathologies, and long-lasting release is necessary to avoid reinjections. There is no effective intravitreal treatment for glaucoma or other optic neuropathies in daily practice, nor is there a non-invasive method to monitor drug levels in the vitreous. Here we show that a glaucoma treatment combining a hypotensive and neuroprotective intravitreal formulation (IF) of brimonidine-Laponite (BRI/LAP) can be monitored non-invasively using vitreoretinal interface imaging captured with optical coherence tomography (OCT) over 24 weeks of follow-up. Qualitative and quantitative characterisation was achieved by analysing the changes in vitreous (VIT) signal intensity, expressed as a ratio of retinal pigment epithelium (RPE) intensity. Vitreous hyperreflective aggregates mixed in the vitreous and tended to settle on the retinal surface. Relative intensity and aggregate size progressively decreased over 24 weeks in treated rat eyes as the BRI/LAP IF degraded. VIT/RPE relative intensity and total aggregate area correlated with brimonidine levels measured in the eye. The OCT-derived VIT/RPE relative intensity may be a useful and objective marker for non-invasive monitoring of BRI/LAP IF.

Physiological changes in retinal layers thicknesses measured with swept source optical coherence tomography.

PURPOSE: To evaluate the physiological changes related with age of all retinal layers thickness measurements in macular and peripapillary areas in healthy eyes. METHODS: Wide protocol scan (with a field of view of 12x9 cm) from Triton SS-OCT instrument (Topcon Corporation, Japan) was performed 463 heathy eyes from 463 healthy controls. This protocol allows to measure the thickness of the following layers: Retina, Retinal nerve fiber layer (RNFL), Ganglion cell layer (GCL +), GCL++ and choroid. In those layers, mean thickness was compared in four groups of ages: Group 1 (71 healthy subjects aged between 20 and 34 years); Group 2 (65 individuals aged 35-49 years), Group 3 (230 healthy controls aged 50-64 years) and Group 4 (97 healthy subjects aged 65-79 years). RESULTS: The most significant thinning of all retinal layers occurs particularly in the transition from group 2 to group 3, especially in temporal superior quadrant at RNFL, GCL++ and retinal layers (p≤0.001), and temporal superior, temporal inferior, and temporal half in choroid layer (p<0.001). Curiously group 2 when compared with group 1 presents a significant thickening of RNFL in temporal superior quadrant (p = 0.001), inferior (p<0.001) and temporal (p = 0.001) halves, and also in nasal half in choroid layer (p = 0.001). CONCLUSIONS: Excepting the RNFL, which shows a thickening until the third decade of life, the rest of the layers seem to have a physiological progressive thinning.

Analysis of temporomandibular joint dysfunction in paediatric patients with unilateral crossbite using automatically generated finite element models.

The evaluation of temporomandibular joint (TMJ) dysfunction using finite element models is a time consuming process that requires extensive technical knowledge. We combined a statistical active appearance model with automated modelling algorithms to biomechanically study the relationship between TMJ malformations and dysfunction in radiographs from 20 paediatric patients with unilateral crossbite. A fitting algorithm (fitting error < 4%) recognised the TMJ shape and adjusted the dimensions of each patient-specific 2D FE model, which was then used to compute 2 different joint movements. Significant functional differences were observed between the crossbite and non-cross bite sides, and the shape-function relation was verified.

Towards an early 3D-diagnosis of craniofacial asymmetry by computing the accurate midplane: A PCA-based method.

BACKGROUND AND OBJECTIVE: Craniofacial asymmetry is a common growth disorder often caused by unilateral chewing. Although an early orthodontic treatment would avoid surgical procedures later in life, the uncertainty of defining the accurate sagittal midplane potentially leads to misdiagnosis and therefore inaccurate orthodontic treatment plans. This novel study aims to 3D-diagnose craniofacial complex malformations in children with unilateral crossbite (UXB) considering a midplane which compensates the asymmetric morphology. METHODS: The sagittal midplane of 20 children, fifteen of whom exhibited UXB, was computed by a PCA-based method which compensates the asymmetry mirroring the 3D models obtained from cone-beam computed tomography data. Once determined, one side of the data was mirrored using the computed midplane to visualize the malformations on the hard and soft tissues by 3D-computing the distances between both halves. Additionally, 31 skull's landmarks were manually placed in each model to study the principal variation modes and the significant differences in the group of subjects with and without UXB through PCA and Mann-Whitney U test analyses respectively. RESULTS: Morphological 3D-analysis showed pronounced deformities and aesthetic implications for patients with severe asymmetry (jaw deviation > 0.8 mm) in whole craniofacial system, while initial signs of asymmetry were found indistinctly in the mandible or maxilla. We detected significant (p < 0.05) malformations for example in mandibular ramus length (0.0086), maxillary palate width (0.0481) and condylar head width (0.0408). Craniofacial malformations increased the landmarks' variability in the group of patients with UXB over the control group requiring 8 variation modes more to define 99% of the sample' variability. CONCLUSIONS: Our findings demonstrated the viability of early diagnosis of craniofacial asymmetry through computing the accurate sagittal midplane which compensates the individual's asymmetrical morphology. Furthermore, this study provides important computational insights into the determination of craniofacial deformities which are caused by UXB, following some empirical findings of previous clinical studies. Hence, this computational approach can be useful for the development of new software in craniofacial surgery or for its use in biomedical research and clinical practice.

Computational characterization of the porous-fibrous behavior of the soft tissues in the temporomandibular joint.

The prevalence and severity of temporomandibular joint (TMJ) disorders have led to growing research interest in the development of new biomaterials and medical devices for TMJ implant designs. In computational designs, however, the time and stretch direction dependences of the TMJ soft tissues behavior are not considered and they are frequently based on measurements taken from non-human species or from joints that differ markedly from the human TMJ. The aim of this study was to accurately characterize the porous-fibrous properties of the TMJ soft tissues by simulating previously published experimental tests, to assist professionals in the design of new TMJ implants. To that end, material parameters were determined assuming a uniform fiber orientation throughout the entire sample. This assumption was then tested by comparing these results with those of considering multiple regions and distinct fiber orientations in each sample. Our findings validated the use of a transversely isotropic hyperelastic material model to characterize the direction dependent behavior of TMJ soft tissues and its combination with porous hyperfoam material models to mimic the compressive response of the TMJ disc. In conclusion, constitutive model proposed accurately reproduce the mechanical response of the TMJ soft tissues at different strain rates and stretch directions.

In silico study of cuspid' periodontal ligament damage under parafunctional and traumatic conditions of whole-mouth occlusions. A patient-specific evaluation.

BACKGROUND AND OBJECTIVE: Although traumatic loading has been associated with periodontal ligament (PDL) damage and therefore with several oral disorders, the damage phenomena and the traumatic loads involved are still unclear. The complex composition and extremely thin size of the PDL make experimentation difficult, requiring computational studies that consider the macroscopic loading conditions, the microscopic composition and fine detailed geometry of the tissue. In this study, a new methodology to analyse the damage phenomena in the collagen network and the extracellular matrix of the PDL caused by parafunctional and traumatic occlusal forces was proposed. METHODS: The entire human mandible and a portion thereof containing a full cuspid tooth were separately modelled using finite element analysis based on computed tomography and micro-computed tomography images, respectively. The first model was experimentally validated by occlusion analysis and subjected to the muscle loads produced during hard and soft chewing, traumatic cuspid occlusion, grinding, clenching, and simultaneous grinding and clenching. The occlusal forces computed by the first model were subsequently applied to the single tooth model to evaluate damage to the collagen network and the extracellular matrix of the PDL. RESULTS: Early occlusal contact on the left cuspid tooth guided the mandible to the more occluded side (16.5% greater in the right side) and absorbed most of the lateral load. The intrusive occlusal loads on the posterior teeth were 0.77-13.3% greater than those on the cuspid. According to our findings, damage to the collagen network and the extracellular matrix of the PDL could occur in traumatic and grinding conditions, mainly due to fibre overstretching (>60%) and interstitial fluid overpressure (>4.7 kPa), respectively. CONCLUSIONS: Our findings provide important biomechanical insights into the determination of damage mechanisms which are caused by mechanical loading and the key role of the porous-fibrous behaviour of the PDL in parafunctional and traumatic loading scenarios. Besides, the 3D loading conditions computed from occlusal contacts will help future studies in the design of new orthodontics appliances and encourage the application of computing methods in medical practice.

The Innate Immune Cell Profile of the Cornea Predicts the Onset of Ocular Surface Inflammatory Disorders.

Ocular surface inflammatory disorder (OSID) is a spectrum of disorders that have features of several etiologies whilst displaying similar phenotypic signs of ocular inflammation. They are complicated disorders with underlying mechanisms related to several autoimmune disorders, such as rheumatoid arthritis (RA), Sjögren's syndrome, and systemic lupus erythematosus (SLE). Current literature shows the involvement of both innate and adaptive arms of the immune system in ocular surface inflammation. The ocular surface contains distinct components of the immune system in the conjunctiva and the cornea. The normal conjunctiva epithelium and sub-epithelial stroma contains resident immune cells, such as T cells, B cells (adaptive), dendritic cells, and macrophages (innate). The relative sterile environment of the cornea is achieved by the tolerogenic properties of dendritic cells in the conjunctiva, the presence of regulatory lymphocytes, and the existence of soluble immunosuppressive factors, such as the transforming growth factor (TGF)-ß and macrophage migration inhibitory factors. With the presence of both innate and adaptive immune system components, it is intriguing to investigate the most important leukocyte population in the ocular surface, which is involved in immune surveillance. Our meta-analysis investigates into this with a focus on both infectious (contact lens wear, corneal graft rejection, Cytomegalovirus, keratitis, scleritis, ocular surgery) and non-infectious (dry eye disease, glaucoma, graft-vs-host disease, Sjögren's syndrome) situations. We have found the predominance of dendritic cells in ocular surface diseases, along with the Th-related cytokines. Our goal is to improve the knowledge of immune cells in OSID and to open new dimensions in the field. The purpose of this study is not to limit ourselves in the ocular system, but to investigate the importance of dendritic cells in the disorders of other mucosal organs (e.g., lungs, gut, uterus). Holistically, we want to investigate if this is a common trend in the initiation of any disease related to the mucosal organs and find a unified therapeutic approach. In addition, we want to show the power of computational approaches to foster a collaboration between computational and biological science.

A mathematical model to predict the evolution of retinal nerve fiber layer thinning in multiple sclerosis patients.

Multiple sclerosis (MS) is a neurodegenerative disease of the central nervous system (CNS). Many studies of MS patients have described axonal loss in the optic nerve of the retina, and specifically progressive thinning of the retinal nerve fiber layer (RNFL). We hypothesize that RNFL thinning involves the participation of 2 processes that cause CNS damage: autoimmune inflammation and axonal degeneration. To test this hypothesis, we developed a mathematical model based on ordinary differential equations to relate the evolution of RNFL thickness (measured by optical coherence tomography [OCT]) with that of the Expanded Disability Status Scale (EDSS) score in MS patients. Data were obtained from a longitudinal study of 114 MS patients who were followed-up for 10 years. After adjusting the parameters using a genetic algorithm, the model's prediction of the evolution of RNFL thickness accurately reflected the progression revealed by the 10-year clinical data. Our findings suggest that differences in the relative contributions of autoimmune inflammation and axonal degeneration can account for the complex dynamics of MS, which vary from one patient to the next. Moreover, our results show that CNS damage occurs cumulatively from the onset of MS and that most RNFL thinning occurs before the appearance of significant disability. RNFL thickness could therefore serve as a reliable biomarker of MS disease course. Our proposed methodology would enable the use of OCT data from new MS patients to predict the evolution of RNFL thinning and hence the progression of MS in individual patients, and to facilitate the selection of patient-specific therapies.

Swept source optical coherence tomography to early detect multiple sclerosis disease. The use of machine learning techniques.

OBJECTIVE: To compare axonal loss in ganglion cells detected with swept-source optical coherence tomography (SS-OCT) in eyes of patients with multiple sclerosis (MS) versus healthy controls using different machine learning techniques. To analyze the capability of machine learning techniques to improve the detection of retinal nerve fiber layer (RNFL) and the complex Ganglion Cell Layer-Inner plexiform layer (GCL+) damage in patients with multiple sclerosis and to use the SS-OCT as a biomarker to early predict this disease. METHODS: Patients with relapsing-remitting MS (n = 80) and age-matched healthy controls (n = 180) were enrolled. Different protocols from the DRI SS-OCT Triton system were used to obtain the RNFL and GCL+ thicknesses in both eyes. Macular and peripapilar areas were analyzed to detect the zones with higher thickness decrease. The performance of different machine learning techniques (decision trees, multilayer perceptron and support vector machine) for identifying RNFL and GCL+ thickness loss in patients with MS were evaluated. Receiver-operating characteristic (ROC) curves were used to display the ability of the different tests to discriminate between MS and healthy eyes in our population. RESULTS: Machine learning techniques provided an excellent tool to predict MS disease using SS-OCT data. In particular, the decision trees obtained the best prediction (97.24%) using RNFL data in macular area and the area under the ROC curve was 0.995, while the wide protocol which covers an extended area between macula and papilla gave an accuracy of 95.3% with a ROC of 0.998. Moreover, it was obtained that the most significant area of the RNFL to predict MS is the macula just surrounding the fovea. On the other hand, in our study, GCL+ did not contribute to predict MS and the different machine learning techniques performed worse in this layer than in RNFL. CONCLUSIONS: Measurements of RNFL thickness obtained with SS-OCT have an excellent ability to differentiate between healthy controls and patients with MS. Thus, the use of machine learning techniques based on these measures can be a reliable tool to help in MS diagnosis.

Is there any advantage of using stand-alone cages? A numerical approach.

BACKGROUND: Segment fusion using interbody cages supplemented with pedicle screw fixation is the most common surgery for the treatment of low back pain. However, there is still much controversy regarding the use of cages in a stand-alone fashion. The goal of this work is to numerically compare the influence that each surgery has on lumbar biomechanics. METHODS: A non-linear FE model of the whole lumbar spine was developed to compare between two types of cages (OLYS and NEOLIF) with and without supplementary fixation. The motion of the whole spine was analysed and the biomechanical environment of the adjacent segments to the operated one was studied. Moreover, the risk of subsidence of the cages was qualitatively evaluated. RESULTS: A great ROM reduction occurred when supplementary fixation was used. This stiffening increased the stresses at the adjacent levels. It might be hypothesised that the overloading of these segments could be related with the clinically observed adjacent disc degeneration. Meanwhile, the stand-alone cages allowed for a wider movement, and therefore, the influence of the surgery on adjacent discs was much lower. Regarding the risk of subsidence, the contact pressure magnitude was similar for both intervertebral cage designs and near the value of the maximum tolerable pressure of the endplates. CONCLUSIONS: A minimally invasive posterior insertion of an intervertebral cage (OLYS or NEOLIF) was compared using a stand-alone design or adding supplementary fixation. The outcomes of these two techniques were compared, and although stand-alone cage may diminish the risk of disease progression to the adjacent discs, the spinal movement in this case could compromise the vertebral fusion and might present a higher risk of cage subsidence.

A porous fibrous hyperelastic damage model for human periodontal ligament: Application of a microcomputerized tomography finite element model.

The periodontal ligament (PDL) is a soft biological tissue that connects the tooth with the trabecular bone of the mandible. It plays a key role in load transmission and is primarily responsible for bone resorption and most common periodontal diseases. Although several numerical studies have analysed the biomechanical response of the PDL, most did not consider its porous fibrous structure, and only a few analysed damage to the PDL. This study presents an innovative numerical formulation of a porous fibrous hyperelastic damage material model for the PDL. The model considers two separate softening phenomena: fibre alignment during loading and fibre rupture. The parameters for the material model characterization were fitted using experimental data from the literature. Furthermore, the experimental tests used for characterization were computationally modelled to verify the material parameters. A finite element model of a portion of a human mandible, obtained by microcomputerized tomography, was developed, and the proposed constitutive model was implemented for the PDL. Our results confirm that damage to the PDL may occur mainly because of overpressure of the interstitial fluid, while large forces must be applied to damage the PDL fibrous network. Moreover, this study clarifies some aspects of the relationship between PDL damage and the bone remodelling process.