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Purpose <p>This study aims to evaluate the diagnostic accuracy of quantitative three-dimensional Single-Photon Emission Computed Tomography (SPECT/CT) analysis for detecting aseptic loosening after total knee arthroplasty (TKA) and to establish component-specific quantitative thresholds.</p> Methods <p>In this retrospective cohort study, patients with painful TKA who underwent standardized assessment, including SPECT/CT after the exclusion of infection, were analyzed. Imaging was performed on a Symbia Intevo Bold (Siemens) and reconstructed using the xSPECT Quant algorithm. Component-specific volumetric uptake parameters, including Maximum, Peak, Mean, and Metabolic Volume, were quantified. Stepwise logistic regression was applied to identify the parameter with the highest diagnostic performance. Optimal cutoff values were established using the Youden Index and the Closest Top method.</p> Results <p>Of 107 screened patients, 86 were included in the final analysis. Intraoperative findings confirmed component loosening in 25 cases. Peak uptake showed the highest diagnostic performance for both femoral and tibial components. For femoral loosening, a Peak uptake threshold of 77.2&#xa0;kBq/ml provided the most balanced diagnostic performance, yielding a sensitivity of 70.6%, specificity of 66.7%, and a negative predictive value (NPV) of 90.2%. For tibial loosening, a threshold of 89.5&#xa0;kBq/ml achieved a sensitivity of 72.7%, specificity of 80%, and an NPV of 95.2%. The area under the curve was 0.87 for tibial loosening and 0.80 for femoral loosening.</p> Conclusion <p>Quantitative SPECT/CT using Peak uptake analysis enables objective and reproducible diagnosis of aseptic loosening. The identified component-specific thresholds show strong predictive value, though the diagnostic accuracy was lower for the femoral component, emphasizing the need for individualized assessment and further prospective validation.</p>

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SPECT/CT peak tracer uptake is a strong predictor of aseptic loosening in painful total knee arthroplasty

  • 期刊论文

  • 发表日期：

    2026年1月30日

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  • Helmut Rasch,
  • Randa Elsheikh,
  • George M Avram,
  • Alexandra Leica,
  • Sabrina Chelli,
  • Felix Amsler,
  • Andrej M Nowakowski,
  • Rolf Huegli,
  • Michael T. Hirschmann

摘要

Purpose

This study aims to evaluate the diagnostic accuracy of quantitative three-dimensional Single-Photon Emission Computed Tomography (SPECT/CT) analysis for detecting aseptic loosening after total knee arthroplasty (TKA) and to establish component-specific quantitative thresholds.

Methods

In this retrospective cohort study, patients with painful TKA who underwent standardized assessment, including SPECT/CT after the exclusion of infection, were analyzed. Imaging was performed on a Symbia Intevo Bold (Siemens) and reconstructed using the xSPECT Quant algorithm. Component-specific volumetric uptake parameters, including Maximum, Peak, Mean, and Metabolic Volume, were quantified. Stepwise logistic regression was applied to identify the parameter with the highest diagnostic performance. Optimal cutoff values were established using the Youden Index and the Closest Top method.

Results

Of 107 screened patients, 86 were included in the final analysis. Intraoperative findings confirmed component loosening in 25 cases. Peak uptake showed the highest diagnostic performance for both femoral and tibial components. For femoral loosening, a Peak uptake threshold of 77.2 kBq/ml provided the most balanced diagnostic performance, yielding a sensitivity of 70.6%, specificity of 66.7%, and a negative predictive value (NPV) of 90.2%. For tibial loosening, a threshold of 89.5 kBq/ml achieved a sensitivity of 72.7%, specificity of 80%, and an NPV of 95.2%. The area under the curve was 0.87 for tibial loosening and 0.80 for femoral loosening.

Conclusion

Quantitative SPECT/CT using Peak uptake analysis enables objective and reproducible diagnosis of aseptic loosening. The identified component-specific thresholds show strong predictive value, though the diagnostic accuracy was lower for the femoral component, emphasizing the need for individualized assessment and further prospective validation.