Multi-level patient-specific modelling of the proximal femur. A promising tool to quantify the effect of osteoporosis treatment

2009 ◽  
Vol 367 (1895) ◽  
pp. 2079-2093 ◽  
Author(s):  
Leen Lenaerts ◽  
G. Harry van Lenthe
Keyword(s):  
Bone Strength ◽  
Material Properties ◽  
Bone Structure ◽  
Structural Information ◽  
Response To Treatment ◽  
Patient Specific ◽  
Loading Conditions ◽  
Femoral Bone ◽  
Fe Modelling ◽  
Specific Loading

Preventing femoral fractures is an important goal in osteoporosis research. In order to evaluate a person's fracture risk and to quantify response to treatment, bone competence is best assessed by bone strength. Finite-element (FE) modelling based on medical imaging is considered a very promising technique for the assessment of in vivo femoral bone strength. Over the past decades, a number of different FE models have been presented focusing on the effect of several methodological aspects, such as mesh type, material properties and loading conditions, on the precision and accuracy of these models. In this paper, a review of this work is presented. We conclude that moderate to good predictions can be made, especially when the models are tuned to specific loading scenarios. However, there is room for improvement when multiple loading conditions need to be evaluated. We hypothesize that including anisotropic material properties is the first target. As a proof of the concept, we demonstrate that the main orientation of the femoral bone structure can be calculated from clinical computed tomography scans. We hypothesize that this structural information can be used to estimate the anisotropic bone material properties, and that in the future this could potentially lead to a greater predictive value of FE models for femoral bone strength.

Different Finite Element Strategies to Satisfy Clinical and Engineering Requirements in Modeling a Novel Percutaneous Device

2012 ◽  
Author(s):  
Claudio Capelli ◽  
Giovanni Biglino ◽  
Lorenza Petrini ◽  
Francesco Migliavacca ◽  
Philipp Bonhoeffer ◽  
...  
Keyword(s):  
Finite Element ◽  
Right Ventricular Outflow Tract ◽  
Patient Specific ◽  
In Vitro Tests ◽  
Loading Conditions ◽  
Modeling Tools ◽  
Transcatheter Heart Valve ◽  
Specific Loading ◽  
Valve Implantation

By taking into account patient-specific properties, finite element (FE) models can aid in the optimization of the devices’ mechanical performances, accelerating the time of development and reducing testing costs. Patient-specific cardiovascular modeling can also drive the development of novel devices [1], by means of anatomical elements that are more representative than animal surrogates [2], and integrating standard in vitro tests with patient-specific loading conditions [3]. Transcatheter heart valve implantation can particularly benefit from a modeling approach. In the field of treatment of valve dysfunctions, percutaneous techniques are relatively new or under development, and modeling tools can contribute to improve these procedures (e.g. design modifications or different routes for device insertion) and increase patient safety in the early introduction of new devices into clinical practice. For a feasible clinical application, computational methods need to be fully validated against physical data, to take into account patient-specific properties, and to provide results in a short time. Instead, from an engineering perspective, models can cost-effectively aid the design phase by improving preclinical testing with more realistic loading conditions for accurate simulation of mechanical behaviour and prediction of durability. This study aims to identify optimal modeling strategies to respond to both clinical and engineering requirements. As a case study, simulations were conducted on a new percutaneous pulmonary valve implantation (PPVI) device [4] tested within a patient-specific right ventricular outflow tract model.

scholarly journals 3D Plotting of Silica/Collagen Xerogel Granules in an Alginate Matrix for Tissue-Engineered Bone Implants

Materials ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 830
Author(s):  
Sina Rößler ◽  
Andreas Brückner ◽  
Iris Kruppke ◽  
Hans-Peter Wiesmann ◽  
Thomas Hanke ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Bone Regeneration ◽  
Material Properties ◽  
Viscoelastic Properties ◽  
Viscoelastic Behavior ◽  
Matrix Phase ◽  
Patient Specific ◽  
Active Player ◽  
Alginate Concentration ◽  
Alginate Matrix

Today, materials designed for bone regeneration are requested to be degradable and resorbable, bioactive, porous, and osteoconductive, as well as to be an active player in the bone-remodeling process. Multiphasic silica/collagen Xerogels were shown, earlier, to meet these requirements. The aim of the present study was to use these excellent material properties of silica/collagen Xerogels and to process them by additive manufacturing, in this case 3D plotting, to generate implants matching patient specific shapes of fractures or lesions. The concept is to have Xerogel granules as active major components embedded, to a large proportion, in a matrix that binds the granules in the scaffold. By using viscoelastic alginate as matrix, pastes of Xerogel granules were processed via 3D plotting. Moreover, alginate concentration was shown to be the key to a high content of irregularly shaped Xerogel granules embedded in a minimum of matrix phase. Both the alginate matrix and Xerogel granules were also shown to influence viscoelastic behavior of the paste, as well as the dimensionally stability of the scaffolds. In conclusion, 3D plotting of Xerogel granules was successfully established by using viscoelastic properties of alginate as matrix phase.

Abstract 562: Human Carotid Atherosclerosis Plaque Progression and Vessel Material Stiffness at Follow Up Had Positive Correlation: An in vivo Vessel Stiffness MRI Follow Up Study

2017 ◽  
Vol 37 (suppl_1) ◽  
Author(s):  
Qingyu Wang ◽  
Dalin Tang ◽  
Gador Canton ◽  
Jian Guo ◽  
Xiaoya Guo ◽  
...  
Keyword(s):  
Negative Correlation ◽  
Material Properties ◽  
Stretch Ratio ◽  
Patient Specific ◽  
Plaque Progression ◽  
Material Stiffness ◽  
Variation Rate ◽  
Vessel Material

It is hypothesized that artery stiffness may be associated with plaque progression. However, in vivo vessel material stiffness follow-up data is lacking in the literature. In vivo 3D multi-contrast and Cine magnetic resonance imaging (MRI) carotid plaque data were acquired from 8 patients with follow-up (18 months) with written informed consent obtained. Cine MRI and 3D thin-layer models were used to determine parameter values of the Mooney-Rivlin models for the 81slices from 16 plaques (2 scans/patient) using our established iterative procedures. Effective Young’s Modulus (YM) values for stretch ratio [1.0,1.3] were calculated for each slice for analysis. Stress-stretch ratio curves from Mooney-Rivlin models for the 16 plaques and 81 slices are given in Fig. 1. Average YM value of the 81 slices was 411kPa. Slice YM values varied from 70 kPa (softest) to 1284 kPa (stiffest), a 1734% difference. Average slice YM values by vessel varied from 109 kPa (softest) to 922 kPa (stiffest), a 746% difference. Location-wise, the maximum slice YM variation rate within a vessel was 306% (139 kPa vs. 564 kPa). Average slice YM variation rate within a vessel for the 16 vessels was 134%. Average variation of YM values from baseline (T1) to follow up (T2) for all patients was 61.0%. The range of the variation of YM values was [-28.4%, 215%]. For progression study, YM increase (YMI=YM T2 -TM T1 ) showed negative correlation with plaque progression measured by wall thickness increase (WTI), (r= -0.6802, p=0.0634). YM T2 showed strong negative correlation with WTI (r= -0.7764, p=0.0235). Correlation between YM T1 and WTI was not significant (r= -0.4353, p= 0.2811). Conclusion In vivo carotid vessel material properties have large variations from patient to patient, along the vessel segment within a patient, and from baseline to follow up. Use of patient-specific, location specific and time-specific material properties could potentially improve the accuracy of model stress/strain calculations.

Simplified LBB Guidance: Stage 1 — Development of a New Software Tool and Initial Scoping Calculations

2018 ◽  
Author(s):  
Peter Gill ◽  
John Sharples ◽  
Chris Aird
Keyword(s):  
Fracture Toughness ◽  
Material Properties ◽  
Software Tool ◽  
Pipe Material ◽  
Loading Conditions ◽  
Design Rules ◽  
Inner Radius ◽  
Inner Diameter ◽  
Stage 1 ◽  
Leak Before Break

This study is focussed on establishing more simplified Leak-before-Break (LbB) guidance for inclusion into Section III.11 of the R6 procedure. The approach adopted has involved the development of a universal software tool for LbB simplified assessments which can be used to perform initial scoping calculations to demonstrate typical LbB cases. It is envisaged that this simplified methodology will enable plant assessment engineers to be more informed on which sites on plant are likely to have LbB successfully applied and to be able to undertake LbB assessments in a more simplistic way than is currently available. Using the developed software tool, a range of LbB calculations for different cracks and loading conditions have been performed to provide guidance on where LbB is more likely to be applied on plant. Loading conditions include primary and secondary stresses, where through-wall changes have been accounted for. The pipe geometries included in this study have been defined by the inner radius and the wall thickness, calculated by minimum pipe thickness required according to meet the design rules of ASME III. The pipe inner radius varies from 40mm to 200mm (80mm to 400mm inner diameter (ID)). All pipe outer diameters are less than 0.5m. All cracks considered in this study are through-wall and circumferential. Pipe material properties are chosen to be broadly representative of an Austenitic Stainless Steel, where the fracture toughness varies from 100 to 180MPa√m and the yield stress is 150MPa.

scholarly journals Inference of an Integrative, Executable Network for Rheumatoid Arthritis Combining Data-Driven Machine Learning Approaches and a State-of-the-Art Mechanistic Disease Map

2021 ◽  
Vol 11 (8) ◽  
pp. 785
Author(s):  
Quentin Miagoux ◽  
Vidisha Singh ◽  
Dereck de Mézquita ◽  
Valerie Chaudru ◽  
Mohamed Elati ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Machine Learning ◽  
State Of The Art ◽  
Biological Information ◽  
Response To Treatment ◽  
Patient Specific ◽  
Learning Approaches ◽  
Data Types ◽  
Disease Heterogeneity ◽  
Combining Data

Rheumatoid arthritis (RA) is a multifactorial, complex autoimmune disease that involves various genetic, environmental, and epigenetic factors. Systems biology approaches provide the means to study complex diseases by integrating different layers of biological information. Combining multiple data types can help compensate for missing or conflicting information and limit the possibility of false positives. In this work, we aim to unravel mechanisms governing the regulation of key transcription factors in RA and derive patient-specific models to gain more insights into the disease heterogeneity and the response to treatment. We first use publicly available transcriptomic datasets (peripheral blood) relative to RA and machine learning to create an RA-specific transcription factor (TF) co-regulatory network. The TF cooperativity network is subsequently enriched in signalling cascades and upstream regulators using a state-of-the-art, RA-specific molecular map. Then, the integrative network is used as a template to analyse patients’ data regarding their response to anti-TNF treatment and identify master regulators and upstream cascades affected by the treatment. Finally, we use the Boolean formalism to simulate in silico subparts of the integrated network and identify combinations and conditions that can switch on or off the identified TFs, mimicking the effects of single and combined perturbations.

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