Notice bibliographique
Résumé
INTRODUCTION Osteoporosis is a disease characterized by an increase in bone resorption that leads to decreased bone mineral mass density and a deterioration of bone tissue micro-architecture. These structural changes translate in an increase in bone fragility and fracture risk [1] . Intertrabecular bone marrow plays an important role in bone remodeling, transporting cells, oxygen and nutrients that are critical in biological processes [2] . When studying the role of intertrabecular bone marrow in osteoporosis, one of the important parameters is the trabecular bone permeability. Permeability depends on the tissue porosity and the interconnectivity of the trabeculae, and it can vary according to the anatomic site [3] . Because permeability is related to the microstructure of the trabecular tissue, we hypothesize that it can be quantified using micro computed tomography ( μ CT) images. The objectives of this project are 1) to develop an experimental method to measure permeability using trabecular bone cubes and 2) to correlate the permeability with μ CT morphological outcomes. METHODS Cubic specimens (1cm 3 ) of trabecular bone (n=15) from cadaveric human tibiae were used for the project. The cubes were scanned with µCT (Scanco Medical μ CT 35, Switzerland) using a nominal resolution of 20µm. The μ CT images were segmented and evaluated to obtain the outcomes for: bone volume fraction (BV/TV), trabecular thickness (Tb.Th), trabecular separation (Tb.Sp), trabecular number (Nb.N). Subsequently, marrow was removed from the trabecular bone by immersing the specimen in a solution of soap and distilled water, then placing the cube in an ultrasonic bath for 60 min. A constant head permeameter was custom designed and built to measure the permeability. The time required to fill a 500 mL beaker with water was measured using a chronometer. Each cube was tested 5 times to determine precision. Permeability was then calculated using Darcy’s Law and an analysis of correlation between the permeability and the μ CT outcomes were conducted. RESULTS The mean permeability measured from the 15 cubes was 5.3e10 -6 +/- 3.0e10 -6 m 2 . The maximum standard deviation found for the five trials was 9.1e10 -8 m 2 (Fig.1). The correlations between μCT outcomes and permeability were 0.338, 0.002, 0.366, 0.590 for BV/TV, Tb.Sp., Tb.N., and Tb.Th. respectively; with the last one being statistically significant. Figure 1. The permeability of the cubic human bone specimen sample (n=15). The largest relative error found based on 5 trials was 1.42%. The figure is used to express the precision of the permeameter as well as the variability in permeability’s obtained through the samples. DISCUSSION AND CONCLUSIONS An experimental device to measure trabecular bone permeability was successfully developed. The low standard deviation of the permeability demonstrated the excellent precision of the permeameter. The high variability of the permeability among samples is consistent with the heterogeneity of the microarchitecture of the trabecular bone cubes. The largest correlation between permeability and a morphometric variable was found for Tb.Th.; h owever, it was not significant. The other μCT outcomes exhibited low correlation. These results suggest that permeability cannot be determined using only morphometric variables. However, the μCT images can be used to reconstruct the real architecture of the bone samples and perform more advance studies (i.e finite element modelling). Utilizing a permeameter that generates precise measurements combined with μCT images will offer information of sample specific permeability. This information will then provide new insights into the transport functions and biomechanics of trabecular bone.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».