Biomechanical study of spinal cord and nerve root in idiopathic scoliosis: based on finite element analysis.

BACKGROUND: Current research lacks comprehensive investigation into the biomechanical changes in the spinal cord and nerve roots during scoliosis correction. This study employs finite element analysis to extensively explore these biomechanical variations across different Cobb angles, providing valuable insights for clinical treatment. METHODS: A personalized finite element model, incorporating vertebrae, ligaments, spinal cord, and nerve roots, was constructed using engineering software. Forces and displacements were applied to achieve Cobb angle improvements, designating T1/2-T4/5 as the upper segment, T5/6-T8/9 as the middle segment, and T9/10-L1/2 as the lower segment. Simulations under traction, pushing, and traction + torsion conditions were conducted, and biomechanical changes in each spinal cord segment and nerve roots were analyzed. RESULTS: Throughout the scoliosis correction process, the middle spinal cord segment consistently exhibited a risk of injury under various conditions and displacements. The lower spinal cord segment showed no significant injury changes under traction + torsion conditions. In the early correction phase, the upper spinal cord segment demonstrated a risk of injury under all conditions, and the lower spinal cord segment presented a risk of injury under pushing conditions. Traction conditions posed a risk of nerve injury on both sides in the middle and lower segments. Under pushing conditions, there was a risk of nerve injury on both sides in all segments. Traction + torsion conditions implicated a risk of injury to the right nerves in the upper segment, both sides in the middle segment, and the left side in the lower segment. In the later correction stage, there was a risk of injury to the upper spinal cord segment under traction + torsion conditions, the left nerves in the middle segment under traction conditions, and the right nerves in the upper segment under pushing conditions. CONCLUSION: When the correction rate reaches 61-68%, particular attention should be given to the upper-mid spinal cord. Pushing conditions also warrant attention to the lower spinal cord and the nerve roots on both sides of the main thoracic curve. Traction conditions require attention to nerve roots bilaterally in the middle and lower segments, while traction combined with torsion conditions necessitate focus on the right-side nerve roots in the upper segment, both sides in the middle segment, and the left-side nerve roots in the lower segment.

Patient-specific in silico 3D coronary model in cardiac catheterisation laboratories.

Coronary artery disease is caused by the buildup of atherosclerotic plaque in the coronary arteries, affecting the blood supply to the heart, one of the leading causes of death around the world. X-ray coronary angiography is the most common procedure for diagnosing coronary artery disease, which uses contrast material and x-rays to observe vascular lesions. With this type of procedure, blood flow in coronary arteries is viewed in real-time, making it possible to detect stenoses precisely and control percutaneous coronary interventions and stent insertions. Angiograms of coronary arteries are used to plan the necessary revascularisation procedures based on the calculation of occlusions and the affected segments. However, their interpretation in cardiac catheterisation laboratories presently relies on sequentially evaluating multiple 2D image projections, which limits measuring lesion severity, identifying the true shape of vessels, and analysing quantitative data. In silico modelling, which involves computational simulations of patient-specific data, can revolutionise interventional cardiology by providing valuable insights and optimising treatment methods. This paper explores the challenges and future directions associated with applying patient-specific in silico models in catheterisation laboratories. We discuss the implications of the lack of patient-specific in silico models and how their absence hinders the ability to accurately predict and assess the behaviour of individual patients during interventional procedures. Then, we introduce the different components of a typical patient-specific in silico model and explore the potential future directions to bridge this gap and promote the development and utilisation of patient-specific in silico models in the catheterisation laboratories.

Determining the changes in morphology and loading status following medial displacement calcaneal osteotomy for flatfoot using patient-specific finite element models.

Medial displacement calcaneal osteotomy (MDCO) is the standard procedure for flatfoot. We investigated the effect of MDCO on the foot using a finite element analysis. Foot models were created from computed tomography data of 8 patients with flat feet. MDCO was performed on each model with bone translation distance of 4, 8, and 12 mm. The morphological changes, plantar pressures, and stress percentage on the talocrural and subtalar joints were evaluated before and after surgery. Morphological evaluation showed improvement in the medial longitudinal arch. The stress percentage of plantar pressure in the medial area decreased, and the stress percentage of plantar pressure in the mid- and lateral forefoot area increased. At the talocrural joint, the medial and middle stress percentage increased, while the lateral and posterior stress percentage decreased. In the subtalar joint, the stress percentage in the middle subtalar joint increased and that in the posterior subtalar joint decreased. Within the posterior subtalar joint, the anterior and medial stress percentage increased, while the posterior and lateral stress percentage decreased. Preoperative simulation using the finite element analysis may be useful in understanding postoperative morphological changes and loading conditions to perform patient-specific surgery.

Physics-informed neural networks for parameter estimation in blood flow models.

BACKGROUND: Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving inverse problems, especially in cases where no complete information about the system is known and scatter measurements are available. This is especially useful in hemodynamics since the boundary information is often difficult to model, and high-quality blood flow measurements are generally hard to obtain. METHODS: In this work, we use the PINNs methodology for estimating reduced-order model parameters and the full velocity field from scatter 2D noisy measurements in the aorta. Two different flow regimes, stationary and transient were studied. RESULTS: We show robust and relatively accurate parameter estimations when using the method with simulated data, while the velocity reconstruction accuracy shows dependence on the measurement quality and the flow pattern complexity. Comparison with a Kalman filter approach shows similar results when the number of parameters to be estimated is low to medium. For a higher number of parameters, only PINNs were capable of achieving good results. CONCLUSION: The method opens a door to deep-learning-driven methods in the simulations of complex coupled physical systems.

Comparative finite element analysis of contact and stress distribution in tibiotalar articular cartilage: Healthy versus varus ankles.

Background: The distribution of forces within the ankle joint plays a crucial role in joint health and longevity. Loading disorders affecting the ankle joint can have significant detrimental effects on daily life and activity levels. This study aimed to enhance our understanding of the mechanical behavior of tibiotalar joint articular cartilages in the presence of varus deformity using finite element analysis (FEA) applied to patient-specific models. Methods: Two personalized ankle models, one healthy and another with varus deformity, were created based on CT scan images. Four static loading scenarios were simulated at the center of pressure (COP), coupled to the hindfoot complex. The contact area, contact pressure, and von Mises stress were computed for each cartilage. Results: It was found that the peak contact pressure increased by 54% in the ankle with varus deformity compared to the healthy ankle model. Furthermore, stress concentrations moving medially were observed, particularly beneath the medial malleolus, with an average peak contact pressure of 3.5 MPa and 4.7 MPa at the tibial and talar articular cartilages, respectively. Conclusion: Varus deformities in the ankle region have been consistently linked to elevated contact pressure, increasing the risk of thinning, degeneration, and eventual onset of osteoarthritis (OA), emphasizing the need for prompt interventions aimed at mitigating complications.

In silico hemodynamical simulations show additional benefits of artery wall softening induced by antihypertensive drugs.

BACKGROUND AND OBJECTIVES: Age-related arterial stiffening increases peripheral resistance and decreases arterial distensibility, thus contributing to hypertension, an important risk factor of atherosclerosis. It causes abnormal blood flow, endothelial dysfunction, higher pulse wave velocity, and consequently elevated pressure wave amplitude. METHODS: This paper presents the influence of these changes via multiscale 3D-0D transient computational fluid dynamics simulations of blood flow in five patient-specific geometries of human carotid bifurcation using archetypal flow waveforms for young and old subjects. RESULTS: The proposed model shows a significant decrease in the time-averaged wall shear stress (TAWSS) for the old archetypal flow waveform. This is in good agreement with clinical data on a straight segment of common carotid arteries available for young and old subjects. Moreover, our study showed that the decrease of area-averaged TAWSS related to the old flow waveform is much more pronounced (2.5 ÷ 4.5 times higher) at risk areas (areas showing TAWSS below its threshold value of 0.48 Pa) than in straight segments commonly considered in clinical studies. CONCLUSIONS: Since arterial stiffness can be lowered through long-term usage of any of the five basic groups of antihypertensives, possible benefits of such medical therapy could be not only lowering blood pressure and peripheral resistance but also in increasing the TAWSS and thus attenuating an important mechanism of the atherosclerotic process.

Breast simulation pipeline: From medical imaging to patient-specific simulations.

BACKGROUND: Breast-conserving surgery is the most acceptable operation for breast cancer removal from an invasive and psychological point of view. Before the surgical procedure, a preoperative MRI is performed in the prone configuration, while the surgery is achieved in the supine position. This leads to a considerable movement of the breast, including the tumor, between the two poses, complicating the surgeon's task. METHODS: In this work, a simulation pipeline allowing the computation of patient-specific geometry and the prediction of personalized breast material properties was put forward. Through image segmentation, a finite element model including the subject-specific geometry is established. By first computing an undeformed state of the breast, the geometrico-material model is calibrated by surface acquisition in the intra-operative stance. FINDINGS: Using an elastic corotational formulation, the patient-specific mechanical properties of the breast and skin were identified to obtain the best estimates of the supine configuration. The final results are a shape-fitting closest point residual of 4.00 mm for the mechanical parameters Ebreast=0.32 kPa and Eskin=22.72 kPa, congruent with the current state-of-the-art. The Covariance Matrix Adaptation Evolution Strategy optimizer converges on average between 5 to 30 min depending on the initial parameters, reaching a simulation speed of 20 s. To our knowledge, our model offers one of the best compromises between accuracy and speed. INTERPRETATION: Satisfactory results were obtained for the estimation of breast deformation from preoperative to intra-operative configuration. Furthermore, we have demonstrated the clinical feasibility of such applications using a simulation framework that aims at the smallest disturbance of the actual surgical pipeline.

Specimen-specific finite element representations of implanted hip capsules.

The hip capsule is a ligamentous structure that contributes to hip stability. This article developed specimen-specific finite element models that replicated internal-external (I-E) laxity for ten implanted hip capsules. Capsule properties were calibrated to minimize root mean square error (RMSE) between model and experimental torques. RMSE across specimens was 1.02 ± 0.21 Nm for I-E laxity and 0.78 ± 0.33 Nm and 1.10 ± 0.48 Nm during anterior and posterior dislocation, respectively. RMSE for the same models with average capsule properties was 2.39 ± 0.68 Nm. Specimen-specific models demonstrated the importance of capsule tensioning in hip stability and have relevance for surgical planning and evaluation of implant designs.

An In Silico Model for Predicting the Efficacy of Edge-to-Edge Repair for Mitral Regurgitation.

In recent years, transcatheter edge-to-edge repair (TEER) has been widely adopted as an effective treatment for mitral regurgitation (MR). The aim of this study is to develop a personalized in silico model to predict the effect of edge-to-edge repair in advance to the procedure for each individual patient. For this purpose, we propose a combination of a valve deformation model for computing the mitral valve (MV) orifice area (MVOA) and a lumped parameter model for the hemodynamics, specifically mitral regurgitation volume (RVol). Although we cannot obtain detailed information on the three-dimensional flow field near the mitral valve, we can rapidly simulate the important medical parameters for the clinical decision support. In the present method, we construct the patient-specific pre-operative models by using the parameter optimization and then simulate the postoperative state by applying the additional clipping condition. The computed preclip MVOAs show good agreement with the clinical measurements, and the correlation coefficient takes 0.998. In addition, the MR grade in terms of RVol also has good correlation with the grade by ground truth MVOA. Finally, we try to investigate the applicability for the predicting the postclip state. The simulated valve shapes clearly show the well-known double orifice and the improvement of the MVOA, compared with the preclip state. Similarly, we confirmed the improved reverse flow and MR grade in terms of RVol. A total computational time is approximately 8 h by using general-purpose PC. These results obviously indicate that the present in silico model has good capability for the assessment of edge-to-edge repair.

Biomechanical characterization of normal and pathological human ascending aortic tissues via biaxial testing Experiment, constitutive modeling and finite element analysis.

BACKGROUND: Aortic dissection and atherosclerosis are two common pathological conditions affecting the aorta. Aortic biomechanics are believed to be closely associated with the pathological development of these diseases. However, the biomechanical environment that predisposes the aortic wall to these pathological conditions remains unclear. METHODS: Sixteen ascending aortic specimens were harvested from 16 human subjects and further categorized into three groups according to their disease states: aortic dissection group, aortic dissection with accompanied atherosclerosis group and healthy group. Experimental stress-strain data from biaxial tensile testing were used to fit the anisotropic Mooney-Rivlin model to determine material parameters. Computed tomography images or transesophageal echocardiography images were collected to construct computational models to simulate the stress/strain distributions in aortas at the pre-dissection state. Statistical analyses were performed to identify the biomechanical factors to distinguish three groups of aortic tissues. RESULTS: Material parameters of anisotropic Mooney-Rivlin model were fitted with average R2 value 0.9749. The aortic diameter showed no significant difference among three groups. Changes of maximum and average stress values from minimum pressure to maximum pressure (△MaxStress and △AveStress) had significantly difference between dissection group and dissection with accompanied atherosclerosis group (p = 0.0201 and 0.0102). Changes of maximum and average strain values from minimum pressure to maximum pressure (△MaxStrain and △AveStrain) from dissection group were significant different from healthy group (p = 0.0171 and 0.0281). CONCLUSION: Changes of stress and strain values during the cardiac cycle are good biomechanical factors for predicting potential aortic dissection and aortic dissection accompanied with atherosclerosis.

Looking towards the future: patient-specific computational modeling to optimize outcomes for transcatheter mitral valve repair.

Severe mitral valve regurgitation (MR) is a heart valve disease that progresses to end-stage congestive heart failure and death if left untreated. Surgical repair or replacement of the mitral valve (MV) remains the gold standard for treatment of severe MR, with repair techniques aiming to restore the native geometry of the MV. However, patients with extensive co-morbidities may be ineligible for surgical intervention. With the emergence of transcatheter MV repair (TMVR) treatment paradigms for MR will evolve. The longer-term outcomes of TMVR and its effectiveness compared to surgical repair remain unknown given the differing patient eligibility for either treatment at this time. Advances in computational modeling will elucidate answers to these questions, employing techniques such as finite element method and fluid structure interactions. Use of clinical imaging will permit patient-specific MV models to be created with high accuracy and replicate MV pathophysiology. It is anticipated that TMVR technology will gradually expand to treat lower-risk patient groups, thus pre-procedural computational modeling will play a crucial role guiding clinicians towards the optimal intervention. Additionally, concerted efforts to create MV models will establish atlases of pathologies and biomechanics profiles which could delineate which patient populations would best benefit from specific surgical vs. TMVR options. In this review, we describe recent literature on MV computational modeling, its relevance to MV repair techniques, and future directions for translational application of computational modeling for treatment of MR.

The Impact of Technological Innovation on Dentistry.

Technology has revolutionized the way dentists are able to treat their patients. These technological advances have paved the way for the creation of virtual patient models utilizing these 3-dimensional intra-oral patient models, cone bean computer tomography (CBCT) radiograph scans, extraoral 3-dimensional scans, and jaw motion tracings to create a patient-specific model. These models are advantageous in planning surgical treatments by providing 3-dimensional views of vital anatomical structures to accurately identify the location, size, and shape of a structure or defect in order to plan accordingly. Virtual augmentation of either hard tissue (bone) and/or soft tissue (i.e., gingiva) can also be accomplished.Technology has allowed the capture of the dynamic motions of the jaw and combined them with the virtual patient to develop permanent restorations in harmony with the patient's orofacial complex. With the introduction of new technology in the realm of digital dentistry, patient care is being brought to a new and higher level. This creates a level of more optimal care that a dentist can deliver to patients.

Can the response to dialysis treatment be predicted by using patient-specific modeling of fluid and solute exchanges? A multicentric evaluation.

BACKGROUND: Parametric multipool kinetic models were used to describe the intradialytic trends of electrolytes, breakdown products, and body fluids volumes during hemodialysis. Therapy customization can be achieved by the identification of parameters, allowing patient-specific modulation of mass and fluid balance across dialyzer, capillary, and cell membranes. This study wants to evaluate the possibility to use this approach to predict the patient's intradialytic response. METHODS: 6 sessions of 68 patients (DialysIS© project) were considered. Data from the first three sessions were used to train the model, identifying the patient-specific parameters, that, together with the treatment settings and the patient's data at the session start, could be used for predicting the patient's specific time course of solutes and fluids along the sessions. Na+ , K+ , Cl- , Ca2+ , HCO3 - , and urea plasmatic concentrations and hematic volume deviations from clinical data were evaluated. RESULTS: nRMSE predictive error is on average equal to 4.76% when describing the training sessions, and only increases by 0.97 percentage points on average in independent sessions of the same patient. CONCLUSIONS: The proposed predictive approach represents a first step in the development of tools to support the clinician in tailoring the patient's prescription.

Finite element analysis of screw fixation durability under multiple boundary and loading conditions for a custom pelvic implant.

Despite showing promising functional outcomes for pelvic reconstruction after sarcoma resection, custom-made pelvic implants continue to exhibit high complication rates due to fixation failures. Patient-specific finite element models have been utilized by researchers to evaluate implant durability. However, the effect of assumed boundary and loading conditions on failure analysis results of fixation screws remains unknown. In this study, the postoperative stress distributions in the fixation screws of a state-of-the-art custom-made pelvic implant were simulated, and the risk of failure was estimated under various combinations of two bone-implant interaction models (tied vs. frictional contact) and four load cases from level-ground walking and stair activities. The study found that the average weighted peak von Mises stress could increase by 22-fold when the bone-implant interactions were modeled with a frictional contact model instead of a tied model, and the likelihood of fatigue and pullout failure for each screw could change dramatically when different combinations of boundary and loading conditions were used. The inclusion of additional boundary and loading conditions led to a more reliable analysis of fixation durability. These findings demonstrated the importance of simulating multiple boundary conditions and load cases for comprehensive implant design evaluation using finite element analysis.

Patient-specific finite element simulation of peripheral artery percutaneous transluminal angioplasty to evaluate the procedure outcome without stent implantation.

The purpose of this work is to present a patient-specific (PS) modeling approach for simulating percutaneous transluminal angioplasty (PTA) endovascular treatment and assessing the balloon sizing influence on short-term outcomes in peripheral arteries, i.e. without stent implantation. Two 3D PS stenosed femoral artery models, one with a dominant calcified atherosclerosis while the other with a lipidic plaque, were generated from pre-operative computed tomography angiography images. Elastoplastic constitutive laws were implemented within the plaque and artery models. Implicit finite element method (FEM) was used to simulate the balloon inflation and deflation for different sizings. Besides vessel strains, results were mainly evaluated in terms of the elastic recoil ratio (ERR) and lumen gain ratio (LGR) attained immediately after PTA. Higher LGR values were shown within the stenosed region of the lipidic patient. Simulated results also showed a direct and quantified correlation between balloon sizing and LGR and ERR for both patients after PTA, with a more significant influence on the lumen gain. The max principal strain values in the outer arterial wall increased at higher balloon sizes during inflation as well, with higher rates of increase when the plaque was calcified. Results show that our model could serve in finding a compromise for each stenosis type: maximizing the achieved lumen gain after PTA, but at the same time without damaging the arterial tissue. The proposed methodology can serve as a step toward a clinical decision support system to improve angioplasty balloon sizing selection prior to the surgery.

Designing a Novel Asymmetric Transcatheter Aortic Valve for Stenotic Bicuspid Aortic Valves Using Patient-Specific Computational Modeling.

Bicuspid aortic valve (BAV), the most common congenital heart malformation, is characterized by the presence of only two valve leaflets with asymmetrical geometry, resulting in elliptical systolic opening. BAV often leads to early onset of calcific aortic stenosis (AS). Following the rapid expansion of transcatheter aortic valve replacement (TAVR), designed specifically for treating conventional tricuspid AS, BAV patients with AS were initially treated "off-label" with TAVR, which recently gained FDA and CE regulatory approval. Despite its increasing use in BAV, pathological BAV anatomy often leads to complications stemming from mismatched anatomical features. To mitigate these complications, a novel eccentric polymeric TAVR valve incorporating asymmetrical leaflets was designed specifically for BAV anatomies. Computational modeling was used to optimize its asymmetric leaflets for lower functional stresses and improved hemodynamic performance. Deployment and flow were simulated in patient-specific BAV models (n = 6) and compared to a current commercial TAVR valve (Evolut R 29 mm), to assess deployment and flow parameters. The novel eccentric BAV-dedicated valve demonstrated significant improvements in peak systolic orifice area, along with lower jet velocity and wall shear stress (WSS). This feasibility study demonstrates the clinical potential of the first known BAV-dedicated TAVR design, which will foster advancement of patient-dedicated valvular devices.

Patient-Specific Image-Based Computational Fluid Dynamics Analysis of Abdominal Aorta and Branches.

The complicated abdominal aorta and its branches are a portion of the circulatory system prone to developing atherosclerotic plaque and aneurysms. These disorders are closely connected to the changing blood flow environment that the area's complicated architecture produces (between celiac artery and iliac artery bifurcation); this phenomenon is widespread at arterial bifurcations. Based on computed tomography angiography (CTA) scans, this current work offers a numerical analysis of a patient-specific reconstruction of the abdominal aorta and its branches to identify and emphasize the most likely areas to develop atherosclerosis. The simulations were run following the heart cycle and under physiological settings. The wall shear stress (WSS), velocity field, and streamlines were examined. According to the findings, complex flow is primarily present at the location of arterial bifurcations, where abnormal flow patterns create recirculation zones with low and fluctuating WSS (<0.5 Pa), which are known to affect endothelial homeostasis and cause adverse vessel remodeling. The study provides a patient-specific hemodynamic analysis model, which couples in vivo CT imaging with in silico simulation under physiological circumstances. The study offers quantitative data on the range fluctuations of important hemodynamic parameters, such as WSS and recirculation region expansion, which are directly linked to the onset and progression of atherosclerosis. The findings could also help drug targeting at this vascular level by understanding blood flow patterns in the abdominal aorta and its branches.

Fused Deposition Modeling 3D Printing in Oral and Maxillofacial Surgery: Problems and Solutions.

Three-dimensional (3D) printing technology in medicine is one of the new and innovative technology for fabricating 3D models of complex anatomical structures that can be observed both visually and haptically. Patient-specific 3D models fabricated through this process are currently being used for various purposes, including surgical simulation, training, and medical education. Most of the personal use/low-end desktop 3D printers that are becoming widespread are fused deposition modeling (FDM) 3D printers. Compared to professional/high-end 3D printers, the price of the personal use/low-end desktop FDM 3D printer itself, filament, and running costs are lower; it can lower the economic bottleneck for introducing 3D printing technology into clinical practice, such as surgical simulation. With a desktop FDM 3D printer and a general-purpose PC, anyone can now rapidly fabricate 3D models on their own without having to rely on 3D printing labs and specialized technicians. However, it is also true that FDM 3D printers, due to their mechanical characteristics, encounter many difficulties and problems that emerge during the 3D printing process. Knowledge, know-how, and tips about FDM 3D printers have been introduced in various media, and it has become easy to know about them worldwide via the Internet. However, there has been no comprehensive technical review to date to produce osseous 3D models for use in oral and maxillofacial surgery. In this report, to create 3D models according to the characteristics of maxillofacial and oral surgery, we enable surgeons themselves to create 3D models smoothly by presenting ideas for CT scanning, points to note when exporting Digital Imaging and Communications in Medicine (DICOM) image data, how to create optimal stereolithography (STL) models, and problems and solutions for 3D printing.

Computational Fontan Analysis: Preserving Accuracy While Expediting Workflow.

Background: Postoperative outcomes of the Fontan operation have been linked to geometry of the cavopulmonary pathway, including graft shape after implantation. Computational fluid dynamics (CFD) simulations are used to explore different surgical options. The objective of this study is to perform a systematic in vitro validation for investigating the accuracy and efficiency of CFD simulation to predict Fontan hemodynamics. Methods: CFD simulations were performed to measure indexed power loss (iPL) and hepatic flow distribution (HFD) in 10 patient-specific Fontan models, with varying mesh and numerical solvers. The results were compared with a novel in vitro flow loop setup with 3D printed Fontan models. A high-resolution differential pressure sensor was used to measure the pressure drop for validating iPL predictions. Microparticles with particle filtering system were used to measure HFD. The computational time was measured for a representative Fontan model with different mesh sizes and numerical solvers. Results: When compared to in vitro setup, variations in CFD mesh sizes had significant effect on HFD (P = .0002) but no significant impact on iPL (P = .069). Numerical solvers had no significant impact in both iPL (P = .50) and HFD (P = .55). A transient solver with 0.5 mm mesh size requires computational time 100 times more than a steady solver with 2.5 mm mesh size to generate similar results. Conclusions: The predictive value of CFD for Fontan planning can be validated against an in vitro flow loop. The prediction accuracy can be affected by the mesh size, model shape complexity, and flow competition.

Patient-specific stomach biomechanics before and after laparoscopic sleeve gastrectomy.

BACKGROUND: Obesity has become a global epidemic. Bariatric surgery is considered the most effective therapeutic weapon in terms of weight loss and improvement of quality of life and comorbidities. Laparoscopic sleeve gastrectomy (LSG) is one of the most performed procedures worldwide, although patients carry a nonnegligible risk of developing post-operative GERD and BE. OBJECTIVES: The aim of this work is the development of computational patient-specific models to analyze the changes induced by bariatric surgery, i.e., the volumetric gastric reduction, the mechanical response of the stomach during an inflation process, and the related elongation strain (ES) distribution at different intragastric pressures. METHODS: Patient-specific pre- and post-surgical models were extracted from Magnetic Resonance Imaging (MRI) scans of patients with morbid obesity submitted to LSG. Twenty-three patients were analyzed, resulting in forty-six 3D-geometries and related computational analyses. RESULTS: A significant difference between the mechanical behavior of pre- and post-surgical stomach subjected to the same internal gastric pressure was observed, that can be correlated to a change in the global stomach stiffness and a minor gastric wall tension, resulting in unusual activations of mechanoreceptors following food intake and satiety variation after LSG. CONCLUSIONS: Computational patient-specific models may contribute to improve the current knowledge about anatomical and physiological changes induced by LSG, aiming at reducing post-operative complications and improving quality of life in the long run.