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Table 3 Summary of the major studies related to the prediction of OA radiographic incidence

From: Trabecular bone texture analysis of conventional radiographs in the assessment of knee osteoarthritis: review and viewpoint

  Cohort name
(m, n)
Period Definition Incidence Major findings
Shamir et al. 2009 [35] BLSA
(Unknown, 123)
240 KL = 0 ΔKL ≥ 2 Baseline TBTA, using a Compound Hierarchy of Algorithms Representing Morphology (WND-CHARM) algorithm, of the region adjacent to the tibial spines was predictive of knee Kellgren-Lawrence (KL) incidence (best accuracy = 0.72, KL from 0 to 3)
Woloszynski et al. 2012 [8] Lund University
(CR, 105)
48 KL = 0 ΔJSNM ≥ 1 Baseline TBTA, measured by the signature dissimilarity measure method (SDM), of the tibial plateau was predictive of medial knee JSN incidence (AUC = 0.75)
Podsiadlo et al. 2016 [9] MOST
(CR&RG, 1433)
48–60 KL ≤ 1 ΔJSNM ≥ 1 Baseline TBTA, measured by the variance orientation transform (VOT) method, was associated with incident radiographic OA, independently of risk factors for knee OA. Most of the OA incidence occurred in medial compartments
Janvier et al. 2017 [10] OAI
(CR, 319)
48 KL = 0 ΔJSNM ≥ 1 Baseline TBTA of the tibial plateau at baseline was predictive of medial knee JSN progression. The best model included TBTA, measured by the quadratic Variations estimator (Var) (AUC = 0.73)
  1. n total number of included subjects, m image acquisition modality, BLSA Baltimore Longitudinal Study of Aging