Diffusion tensor imaging of articular cartilage at 3T correlates with histology and biomechanics in a mechanical injury model.
Magn Reson Med
; 78(1): 69-78, 2017 07.
Article
en En
| MEDLINE
| ID: mdl-27455389
ABSTRACT
PURPOSE:
We establish a mechanical injury model for articular cartilage to assess the sensitivity of diffusion tensor imaging (DTI) in detecting cartilage damage early in time. Mechanical injury provides a more realistic model of cartilage degradation compared with commonly used enzymatic degradation.METHODS:
Nine cartilage-on-bone samples were obtained from patients undergoing knee replacement. The 3 Tesla DTI (0.18 × 0.18 × 1 mm3 ) was performed before, 1 week, and 2 weeks after (zero, mild, and severe) injury, with a clinical radial spin-echo DTI (RAISED) sequence used in our hospital. We performed stress-relaxation tests and used a quasilinear-viscoelastic (QLV) model to characterize cartilage mechanical properties. Serial histology sections were dyed with Safranin-O and given an OARSI grade. We then correlated the changes in DTI parameters with the changes in QLV-parameters and OARSI grades.RESULTS:
After severe injury the mean diffusivity increased after 1 and 2 weeks, whereas the fractional anisotropy decreased after 2 weeks (P < 0.05). The QLV-parameters and OARSI grades of the severe injury group differed from the baseline with statistical significance. The changes in mean diffusivity across all the samples correlated with the changes in the OARSI grade (r = 0.72) and QLV-parameters (r = -0.75).CONCLUSION:
DTI is sensitive in tracking early changes after mechanical injury, and its changes correlate with changes in biomechanics and histology. Magn Reson Med 7869-78, 2017. © 2016 International Society for Magnetic Resonance in Medicine.Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Interpretación de Imagen Asistida por Computador
/
Cartílago Articular
/
Fracturas del Cartílago
/
Imagen de Difusión Tensora
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Límite:
Adult
/
Female
/
Humans
/
Male
/
Middle aged
Idioma:
En
Año:
2017
Tipo del documento:
Article