1,721,252 research outputs found
Uso di sensori indossabili in studi clinici: aspetti regolatori
No full text<p>This is a guideline document that the DARE consortium produced to assist the Italian Ethics Committees called to evaluating clinical studies involving wearable devices. As the level of certification depends on the context of use, this guideline became necessary as we submit to various Italian Ethics Committees the many clinical studies the DARE project involves. We hope it can help the Ethics Committees to have a more uniform evaluation of these and other similar studies.</p>
In Silico Medicine: The Practitioners’ Points of View
Full text linkIn this article, which is assembled from interviews, the main issues of in silicomedicine, present and future, are discussed by three scientists who are directly involved in the implementation and development of in silicotechnique
Accuracy of the planned vs achieved position of a cementless hip stem: a finite element study
No full textThe implant of an hip stem into the femoral medullary cavity consists of three steps: the resection of the femoral head,
the rasping of the femoral canal and the placement of the stem. Priority for cemtless hip implants, in order to achieve a
good level of primary stability, is the accuracy with which the stem is positioned in the host bone. An erroneous initial
positioning could lead to the implant instability promoting the ultimate failure of the implant 1. Initial excessive relative
micromotions at the bone-implant interface may inhibit the bony in-growth and secondary long term fixation 2,3.
The final objective of the early researches along this line is to arrange a set of instruments to predict the primary
stability in the pre-operative planning moving toward a less and minimally invasive surgical technique. Nevetheless,
even assuming a perfect surgical planning, there is still the practical problem of correct positioning of the stem in the
femur during surgery.
Aim of the present study was to asses the sensitivity of the relative bone-implant micromotions, stresses and strains to
the implant position as planned and achieved by the surgeon respectively before and after the operation. For this
purpose, the subject-specific finite element (FE) model of a cadaveric femur, accounting for patient and surgeon, was
derived from pre-operative and post-operative CT scans. The overall aim was to verify if the pre-clinical planning
correctly matches the achieved implant stability conditions and hence if it can be considered as a powerful tool to train
the surgeon in taking the appropriate clinical decisions
HOW ACCURATELY PRE-OPERATIVE PLANNING MATCHES THE ACHIEVED SURGERY: A FINITE ELEMENT STUDY
No full textPre-operative planning trains the surgeon in the workshop environment. The final objective of the early researches
along this line is to arrange a set of instruments to predict the primary stability in the pre-operative planning moving
toward a less and minimally invasive surgical technique. Nevetheless, even assuming a perfect surgical planning, there
is still the practical problem of correct positioning of the stem in the femur during surgery. An erroneous initial
positioning could lead to the implant instability promoting the ultimate failure of the implant [1,2]. Initial excessive
relative micromotions at the bone-implant interface may inhibit the bony in-growth and secondary long term fixation
[3,4]. To achieve a good level of primary stability the surgery technique play therefore a fundamental role.
Aim of the present study was to asses the sensitivity of the relative bone-implant micromotions, stresses and strains to
the surgical parameters as planned and achieved by the surgeon respectively before and after the operation. For this
purpose, the subject-specific finite element (FE) model of a cadaveric femur, accounting for patient and surgeon, was
derived from pre-operative and post-operative CT scans. The specific aim was to verify if finite element models based
on pre-clinical planning correctly match the achieved implant stability conditions
Predicting the subject-specific primary stability of cementless implants during pre-operative planning: preliminary validation of subject-specific finite-element models
No full textPre-operative planning help the surgeon in taking the proper clinical decision. The ultimate goal of this work is to develop numerical
models that allow the surgeon to estimate the primary stability during the pre-operative planning session. The present study was aimed to
validate finite-element (FE) models accounting for patient and prosthetic size and position as planned by the surgeon. For this purpose,
the FE model of a cadaveric femur was generated starting from the CT scan and the anatomical position of a cementless stem derived by
a skilled surgeon using a pre-operative CT-based planning simulation software. In-vitro experimental measurements were used as
benchmark problem to validate the bone–implant relative micromotions predicted by the patient-specific FE model. A maximum torque
in internal rotation of 11.4Nm was applied to the proximal part of the hip stem. The error on the maximum predicted micromotion was
12% of the peak micromotion measured experimentally. The average error over the entire range of applied torques was only 7% of peak
measurement. Hence, the present study confirms that it is possible to accurately predict the level of primary stability achieved for
cementless stems using numerical models that account for patient specificity and surgical variability.
r 2006 Elsevier Ltd. All rights reserved
A systematic approach to define intended learning outcomes for different stakeholders for In Silico Trials
No full textDescription File Content
'Definition_stakeholders_and_ILOs.pdf': contains the definition of the stakeholder groups and intended learning outcomes
'Correspondence matrix.xlsx': displays Intended Learning Outcomes (ILOs) vertically, stakeholder groups horizontally, and expert votes with color-coded markings.
Background & Problem statement
In Silico Trial (IST) technologies refer to modeling and simulation tools used for the development and regulatory assessment of medicines and medical devices. These tools can significantly decrease the need for animal and human testing and reduce the costs of developing medical products, while maintaining reliability. However, the use of IST technologies is not widespread due to a lack of trained personnel. There are currently limited opportunities for training and re-training individuals with the technical skills needed to work with IST technologies. To address this issue, dedicated course modules will be developed to train and retrain personnel. To ensure that the courses are effective, Intended Learning Outcomes (ILOs) have to be defined and assigned to the different stakeholder categories. ILOs are statements that describe what a student will learn and be able to do upon completion of a course module [1].
Methods
To identify training needs and ILOs, input from representatives from target groups was sought. This was done using a dual approach. First, online surveys created using Qualtrics software were completed by 187 responders of the different stakeholder categories. Second, online workshops were conducted using Miro to gather the training needs and ILOs. Online workshops were held on 14 occasions for various stakeholder categories, with 88 participants overall. The workshop was structured into three parts: (1) Brainwriting of training needs in break-out rooms; (2) Grouping and prioritization of the identified needs; and (3) Formulation of draft ILOs. ILOs were defined according to [2].
To define the stakeholder categories, the target groups were organized according to their need for education/training at the master's or PhD level, as well as professionals requiring retraining. In a final step, the ILOs were then linked to the stakeholder categories through a voting system, resulting in a correspondence matrix between ILOs and stakeholders' categories.
Results & Discussion
The correspondence matrix provides a clear overview of which stakeholders need to acquire which ILO, and therefore, will serve as the foundation for gathering course materials and developing modules that will help train personnel and provide them with experience in IST technologies
Development and validation of a subject-specific finite element model of pathological lumbar spine
Full text linkSubject -specific FE model for the prediction of the relative micromotion in a total hip implant: verification and validation
No full textThe most common reason for the aseptic loosening of
cementless hip stem is the lack of primary stability as the
presence of an excessive relative micromotion at the boneimplant
interface [1]. Despite pre-clinical validation has
remarkably improved over the last few years, some important
factors affecting implant biomechanics have still to be
considered. Most of the previous numerical studies on hip
arthroplasty were based on models of composite femurs.
However, subject-specific factors (skeletal anatomy,
mechanical properties, implant position) are needed to
produce helpful outcomes for clinical practice. In addition,
these models were developed using time consuming structured
meshes frequently lacking of careful verification and
validation phases.
Aim of the present work is the development of a Finite
Element (FE) model of an implanted femur taking into
account the specificity of subject as well as the planned
surgery technique parameters.
Specific aims are the verification of the numerical accuracy of
the FE model and the analysis of the predicted relative
micromotions compared to experimental results (validation)
Sensitivity of the primary stability of a cementless hip stem to its position and orientation
No full textAbstract: Using computed tomography (CT)-based preoperative
planning software, we can define with good
accuracy the position of a cementless hip stem inside the
host bone, but previous studies suggest that the pose the
surgeon achieves during freehand surgery may differ from
the planned one even by some millimeters. Advances in
simulation now make it possible to predict the primary
stability of the stem in a given position during the preoperative
planning, but is the stability predicted for the
planned pose indicative of that we can expect for the
achieved pose? The aim of the present study was to verify
how this prediction is affected by the differences observed
between the planned and the achieved poses. Two finite
element models of an implanted femur were generated,
one with the stem in the planned pose, and one with the
stem in the achieved pose, as defined from postoperative
CT scans. When compared to experimental measurements,
the model with the achieved position was clearly
more accurate (0.6 vs. 12% error over measured peak
micromotion); however, the predictions of induced micromotions
were different between the two models for less
than 13%. It is thus concluded that while the implant
position does have an effect on primary stability, the
estimate of micromotion we can get from the planned
position remains a clinically relevant indicator
Statistical Properties of a Virtual Cohort for In Silico Trials Generated with a Statistical Anatomy Atlas
Full text linkOsteoporosis-related hip fragility fractures are a catastrophic event for patient lives but are not frequently observed in prospective studies, and therefore phase III clinical trials using fractures as primary clinical endpoint require thousands of patients enrolled for several years to reach statistical significance. A novel answer to the large number of subjects needed to reach the desired evidence level is offered by In Silico Trials, that is, the simulation of a clinical trial on a large cohort of virtual patients, monitoring the biomarkers of interest. In this work we investigated if statistical aliasing from a custom anatomy atlas could be used to expand the patient cohort while retaining the original biomechanical characteristics. We used a pair-matched cohort of 94 post-menopausal women (at the time of the CT scan, 47 fractured and 47 not fractured) to create a statistical anatomy atlas through principal component analysis, and up-sampled the atlas in order to obtain over 1000 synthetic patient models. We applied the biomechanical computed tomography pipeline to the resulting virtual cohort and compared its fracture risk distribution with that of the original physical cohort. While the distribution of femoral strength values in the non-fractured sub-group was nearly identical to that of the original physical cohort, that of the fractured sub-group was lower than in the physical cohort. Nonetheless, by using the classification threshold used for the original population, the synthetic population was still divided into two parts of approximatively equal number
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