Objective <p>To determine whether substantial differences in coronal plane alignment of the knee phenotype distribution, as well as systematic angular measurement discrepancies, exist between CT and long-leg radiography.</p> Materials and methods <p>From February 2021 to April 2025, we searched PubMed, Embase, and the Cochrane Central Register of Controlled Trials for studies comparing CT- and long-leg radiography-derived coronal plane alignment classifications of the knee in patients with osteoarthritis. The primary outcome was distribution of coronal plane alignment phenotypes. Secondary outcomes included differences in medial proximal tibial angle, lateral distal femoral angle, arithmetic hip–knee–ankle angle, and joint line obliquity.</p> Results <p>Four studies (1,134 knees) were included. Compared with long-leg radiography-derived classification, CT-derived classification increased type I phenotypes (risk difference: 0.10; 95% confidence interval: 0.01–0.20; <i>P</i> = 0.040) and decreased type III (risk difference: –0.04; 95% confidence interval: –0.07 to –0.01;<i> P</i> = 0.020) and type V phenotypes (risk difference: –0.04; 95% confidence interval: –0.07 to –0.01; <i>P</i> = 0.004). CT yielded significantly lower medial proximal tibial angle (weighted mean difference: − 1.18°; <i>P</i> &lt; 0.001), arithmetic hip–knee–ankle angle (weighted mean difference: − 0.95°; <i>P</i> &lt; 0.001), and joint line obliquity (weighted mean difference: − 1.40°; <i>P</i> &lt; 0.001) than long-leg radiography. Heterogeneity was high for type I phenotype (<i>I</i><sup>2</sup> = 81%), lateral distal femoral angle (<i>I</i><sup>2</sup> = 70%), and joint line obliquity (<i>I</i><sup>2</sup> = 69%).</p> Conclusion <p>Discrepancies between CT-based software-generated and long-leg radiography-derived measurements substantially affect coronal plane alignment classification and angular parameters. Surgeons should consider these modality-specific variations and employ compensatory verification strategies to ensure optimal alignment.</p>

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Discrepancies in CPAK classification between CT and long-leg radiography: a systematic review and meta-analysis

  • Tao Bian,
  • Yunfeng Zhang,
  • Lei Li,
  • Yixin Zhou

摘要

Objective

To determine whether substantial differences in coronal plane alignment of the knee phenotype distribution, as well as systematic angular measurement discrepancies, exist between CT and long-leg radiography.

Materials and methods

From February 2021 to April 2025, we searched PubMed, Embase, and the Cochrane Central Register of Controlled Trials for studies comparing CT- and long-leg radiography-derived coronal plane alignment classifications of the knee in patients with osteoarthritis. The primary outcome was distribution of coronal plane alignment phenotypes. Secondary outcomes included differences in medial proximal tibial angle, lateral distal femoral angle, arithmetic hip–knee–ankle angle, and joint line obliquity.

Results

Four studies (1,134 knees) were included. Compared with long-leg radiography-derived classification, CT-derived classification increased type I phenotypes (risk difference: 0.10; 95% confidence interval: 0.01–0.20; P = 0.040) and decreased type III (risk difference: –0.04; 95% confidence interval: –0.07 to –0.01; P = 0.020) and type V phenotypes (risk difference: –0.04; 95% confidence interval: –0.07 to –0.01; P = 0.004). CT yielded significantly lower medial proximal tibial angle (weighted mean difference: − 1.18°; P < 0.001), arithmetic hip–knee–ankle angle (weighted mean difference: − 0.95°; P < 0.001), and joint line obliquity (weighted mean difference: − 1.40°; P < 0.001) than long-leg radiography. Heterogeneity was high for type I phenotype (I2 = 81%), lateral distal femoral angle (I2 = 70%), and joint line obliquity (I2 = 69%).

Conclusion

Discrepancies between CT-based software-generated and long-leg radiography-derived measurements substantially affect coronal plane alignment classification and angular parameters. Surgeons should consider these modality-specific variations and employ compensatory verification strategies to ensure optimal alignment.