2017
DOI: 10.1016/j.joca.2016.12.011
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Subchondral bone in osteoarthritis: association between MRI texture analysis and histomorphometry

Abstract: MRI texture analysis features were significantly associated with ground-truth subchondral bone histomorphometry at the tibial plateau.

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Cited by 35 publications
(27 citation statements)
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“…Furthermore, the neridronate group exhibited a significant decrease in bone marrow lesions evaluated by MRI, 49 suggesting a possible structural effect based on the hypothesis that altered bone metabolism plays a role in the pathogenesis of OA. [50][51][52][53] …”
Section: Osteoarthritismentioning
confidence: 99%
“…Furthermore, the neridronate group exhibited a significant decrease in bone marrow lesions evaluated by MRI, 49 suggesting a possible structural effect based on the hypothesis that altered bone metabolism plays a role in the pathogenesis of OA. [50][51][52][53] …”
Section: Osteoarthritismentioning
confidence: 99%
“…One disadvantage of MRI TA is that it is not always clear what the biological or structural correlates of individual texture features are, despite previous demonstration of association with histomorphometry [ 11 ]. However, as has been shown by the use of texture analysis in imaging applications other than assessment of subchondral bone, this lack of correspondence to an underlying structural ‘ground-truth’ does not preclude the use of this method to improve our understanding of the underlying disease process [ 27 29 ].…”
Section: Discussionmentioning
confidence: 99%
“…The technique has been shown to be reproducible and able to distinguish subjects at different stages of OA from healthy subjects [ 9 ]. Moreover, texture features have shown an improved ability to discriminate between knees with and without OA when compared to microarchitectural analysis and are significantly associated with histomorphometry [ 10 , 11 ].…”
Section: Introductionmentioning
confidence: 99%
“…Although radiomics is used comprehensively for cancer studies, it is applicable for bone diseases management such as osteoporosis diagnosis and therapy response prediction and assessment. Previous studies have identi ed that radiomics features extracted from computed tomography (CT), magnetic resonance imaging (MRI) and radiology images could be used for bone diseases management (9,10). In our previous study, we showed the feasibility of radiomics features extracted from DXA images to classify osteoporosis and osteopenia patients from normal ones (11).…”
Section: Introductionmentioning
confidence: 97%