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Investigating the relationship between radiographic joint space width loss and deep learning-derived magnetic resonance imaging-based cartilage thickness loss in the medial weight-bearing region of the tibiofemoral joint.
Minnig, Mary Catherine C; Arbeeva, Liubov; Niethammer, Marc; Nissman, Daniel; Lund, Jennifer L; Marron, J S; Golightly, Yvonne M; Nelson, Amanda E.
Afiliação
  • Minnig MCC; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Arbeeva L; Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Niethammer M; Department of Computer Science, University of North Carolina at Chapel Hill College of Arts and Sciences, Chapel Hill, NC, USA.
  • Nissman D; Department of Radiology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA.
  • Lund JL; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Marron JS; Statistics and Operations Research, University of North Carolina at Chapel Hill College of Arts of Sciences, Chapel Hill, NC, USA.
  • Golightly YM; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Nelson AE; Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Osteoarthr Cartil Open ; 6(3): 100508, 2024 Sep.
Article em En | MEDLINE | ID: mdl-39238657
ABSTRACT

Objective:

To investigate the relationship between measures of radiographic joint space width (JSW) loss and magnetic resonance imaging (MRI)-based cartilage thickness loss in the medial weight-bearing region of the tibiofemoral joint over 12-24 months. To stratify this relationship by clinically meaningful subgroups (sex and pain status).

Design:

We analyzed a subset of knees (n â€‹= â€‹256) from the Osteoarthritis Initiative (OAI) likely in early stage OA based on joint space narrowing (JSN) measurements. Natural logarithm transformation was used to approximate near normal distributions for JSW loss. Pearson Correlation coefficients described the relationship between ln-transformed JSW loss and several versions of deep learning-derived MRI-based cartilage thickness loss parameters (minimum, maximum, and mean) in subregions of the femoral condyle, tibial plateau, and combined femoral and tibial regions. Linear mixed-effects models evaluated the associations between the ln-transformed radiographic and MRI-derived measures including potential confounders.

Results:

We found weak correlations between ln-transformed JSW loss and MRI-based cartilage thickness ranging from R â€‹= â€‹-0.13 (p â€‹= â€‹0.20) to R â€‹= â€‹0.26 (p â€‹< â€‹0.01). Correlations were higher (still poor) among females compared to males and painful compared to non-painful knees. Model results showed weak associations for nearly all MRI-based measures, ranging from no association to ß (95% CI) â€‹= â€‹0.25 (0.11, 0.39). Associations were higher among females compared to males and minimal differences between painful and non-painful knees.

Conclusions:

Despite its recommended use in disease-modifying OA drug clinical trials, results suggest that JSW loss is an ineffective proxy measure of cartilage thickness loss over 12-24 months and within a localized region of the tibiofemoral joint.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Osteoarthr Cartil Open Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Osteoarthr Cartil Open Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Reino Unido