Objective <p>To evaluate the diagnostic performance of artificial intelligence–compressed sensing (ACS)-accelerated T1ρ mapping combined with conventional T2 mapping for quantitative differentiation of articular cartilage degeneration and meniscal injury severity in knee osteoarthritis (KOA).</p> Methods <p>We prospectively enrolled 56 KOA patients and 30 age-matched healthy volunteers between August 2025 and February 2026. All underwent 3T knee MRI using ACS T1ρ and conventional T2 mapping. Relaxation times were quantified in predefined cartilage and meniscal regions. Cartilage degeneration was classified by Kellgren–Lawrence (K–L) grade: 0 (normal), I–II (mild), and III–IV (severe). Meniscal injury was graded using the Stoller system: 0 (normal), I–II (mild), and III (severe). Group and subgroup comparisons used appropriate statistical tests.</p> Results <p>T1ρ and T2 values were significantly elevated in KOA versus controls across all regions (<i>P</i> &lt; 0.05). Within KOA, relaxation times differed significantly between mild and severe subgroups (<i>P</i> &lt; 0.05). For cartilage degeneration, AUCs were 0.948 (95% CI: 0.889–1.000) for ACS T1ρ, 0.867 (95% CI: 0.760–0.975) for T2, and 0.964 (95% CI: 0.922–1.000) for the combined model. For meniscal injury, AUCs were 0.851 (95% CI: 0.779–0.922) for ACS T1ρ, 0.802 (95% CI: 0.720–0.885) for T2, and 0.855 (95% CI: 0.784–0.926) for the combined approach.</p> Conclusion <p>Integrating ACS T1ρ and T2 mapping enables precise, quantitative stratification of cartilage and meniscal pathology across KOA severity levels, offering comprehensive biochemical assessment prior to morphological changes and highlighting its potential for early intervention and stage-based management.</p>

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Grading knee cartilage degeneration and meniscal injury with combined ACS-accelerated T1ρ and T2 mapping

  • Shuai Yang,
  • Zhichao Liu,
  • Shuo Huang,
  • Lan Cheng,
  • Zhuang Nie,
  • Qun Yu,
  • Ziqiao Lei,
  • Wenliang Fan

摘要

Objective

To evaluate the diagnostic performance of artificial intelligence–compressed sensing (ACS)-accelerated T1ρ mapping combined with conventional T2 mapping for quantitative differentiation of articular cartilage degeneration and meniscal injury severity in knee osteoarthritis (KOA).

Methods

We prospectively enrolled 56 KOA patients and 30 age-matched healthy volunteers between August 2025 and February 2026. All underwent 3T knee MRI using ACS T1ρ and conventional T2 mapping. Relaxation times were quantified in predefined cartilage and meniscal regions. Cartilage degeneration was classified by Kellgren–Lawrence (K–L) grade: 0 (normal), I–II (mild), and III–IV (severe). Meniscal injury was graded using the Stoller system: 0 (normal), I–II (mild), and III (severe). Group and subgroup comparisons used appropriate statistical tests.

Results

T1ρ and T2 values were significantly elevated in KOA versus controls across all regions (P < 0.05). Within KOA, relaxation times differed significantly between mild and severe subgroups (P < 0.05). For cartilage degeneration, AUCs were 0.948 (95% CI: 0.889–1.000) for ACS T1ρ, 0.867 (95% CI: 0.760–0.975) for T2, and 0.964 (95% CI: 0.922–1.000) for the combined model. For meniscal injury, AUCs were 0.851 (95% CI: 0.779–0.922) for ACS T1ρ, 0.802 (95% CI: 0.720–0.885) for T2, and 0.855 (95% CI: 0.784–0.926) for the combined approach.

Conclusion

Integrating ACS T1ρ and T2 mapping enables precise, quantitative stratification of cartilage and meniscal pathology across KOA severity levels, offering comprehensive biochemical assessment prior to morphological changes and highlighting its potential for early intervention and stage-based management.