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Abstract <p>Prostate-specific membrane antigen radioligand therapy (PSMA-RLT) has emerged as a promising treatment for metastatic castration-resistant prostate cancer (mCRPC). However, current patient selection methods – largely based on qualitative imaging criteria – may impede precision and efficacy of treatment. We aimed to evaluate the predictive value of quantitative imaging biomarkers derived from dual-tracer [<sup>68</sup>&#xa0;Ga]Ga-PSMA-11 and [<sup>18</sup>F]F-FDG PET/CT, with a focus on concordant lesions.</p> Methods <p>Thirty-seven mCRPC patients from two institutions underwent [<sup>68</sup>&#xa0;Ga]Ga-PSMA-11 and [<sup>18</sup>F]F-FDG PET/CT prior to receiving at least two cycles of [<sup>177</sup>Lu]Lu-PSMA therapy. An automated pipeline enabled lesion segmentation, dual-tracer image fusion, and extraction of quantitative features from concordant (PSMA + /FDG +) and non-concordant lesions. A decision tree model was developed on the Vienna cohort (<i>n</i> = 24) and validated on an independent cohort from Augsburg (<i>n</i> = 13). SHAP analysis was used to identify key predictive features.</p> Results <p>The decision tree achieved 95.8% accuracy in the training cohort and 84.6% in external validation. SUV<sub>mean</sub> of concordant lesions was the most predictive features. Patients with SUV<sub>mean</sub>[PSMA Concordant] ≥ 12.1&#xa0;g/mL were more likely to respond. Organ-specific analysis further identified high SUV<sub>max</sub> in bone metastases as a negative prognostic marker.</p> Conclusions <p>Quantitative metrics from dual-tracer PET, particularly those characterizing concordant lesions, show promise for predicting response to PSMA-RLT. These preliminary findings highlight the potential to move beyond binary eligibility criteria toward a more nuanced, biomarker-driven approach to patient selection.</p>

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Quantitative dual-tracer PET/CT biomarkers correlate concordant lesion uptake with PSMA-RLT outcomes in mCRPC: a dual-center study

  • 期刊论文

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  • 发表日期：

    2026年1月5日

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  • Song Xue,
  • Holger Einspieler,
  • Sijie Wen,
  • Dina Muin,
  • Ana Antic Nikolic,
  • Jan Baessler,
  • Gero Kramer,
  • Shahrokh F. Shariat,
  • Constantin Lapa,
  • Marcus Hacker,
  • Sazan Rasul,
  • Xiang Li

摘要

Abstract

Prostate-specific membrane antigen radioligand therapy (PSMA-RLT) has emerged as a promising treatment for metastatic castration-resistant prostate cancer (mCRPC). However, current patient selection methods – largely based on qualitative imaging criteria – may impede precision and efficacy of treatment. We aimed to evaluate the predictive value of quantitative imaging biomarkers derived from dual-tracer [68 Ga]Ga-PSMA-11 and [18F]F-FDG PET/CT, with a focus on concordant lesions.

Methods

Thirty-seven mCRPC patients from two institutions underwent [68 Ga]Ga-PSMA-11 and [18F]F-FDG PET/CT prior to receiving at least two cycles of [177Lu]Lu-PSMA therapy. An automated pipeline enabled lesion segmentation, dual-tracer image fusion, and extraction of quantitative features from concordant (PSMA + /FDG +) and non-concordant lesions. A decision tree model was developed on the Vienna cohort (n = 24) and validated on an independent cohort from Augsburg (n = 13). SHAP analysis was used to identify key predictive features.

Results

The decision tree achieved 95.8% accuracy in the training cohort and 84.6% in external validation. SUVmean of concordant lesions was the most predictive features. Patients with SUVmean[PSMA Concordant] ≥ 12.1 g/mL were more likely to respond. Organ-specific analysis further identified high SUVmax in bone metastases as a negative prognostic marker.

Conclusions

Quantitative metrics from dual-tracer PET, particularly those characterizing concordant lesions, show promise for predicting response to PSMA-RLT. These preliminary findings highlight the potential to move beyond binary eligibility criteria toward a more nuanced, biomarker-driven approach to patient selection.