CT Radiomics Models Did Not Outperform Experts in Predicting [68Ga]Ga-PSMA-PET Positivity in Prostate Cancer Lymph
Thula Cannon Walter-Rittel1, Boris Gorodetski1, Alexander Hartenstein2
1Department of Radiology, Charité Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Augustenburger Platz 1, 13353 Berlin, Germany.
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Background: The use of [68Ga]Ga-PSMA-PET/CT for prostate cancer (PCa) staging is limited by cost and availability. This study evaluates whether radiomic features from contrast-enhanced (CE) CT can predict PSMA-positive lymph nodes (LNs) as a surrogate for metastasis. Methods: A retrospective study of 447 patients included 2537 segmented LNs (425 PET-positive, 2112 PET-negative). Two uroradiologists assessed 417 LNs on CE-CT using a four-point Likert scale. Radiomic features were extracted, selected using four algorithms, and analyzed with six model-building methods. Model performance was compared to radiologist ratings. Results: Radiomic models achieved an accuracy of 0.77-0.85, sensitivity of 0.85-0.91, and specificity of 0.74-0.85. Compared to radiologists, models had higher NPV (0.97-0.98 vs. 0.96) and sensitivity (0.85-0.91 vs. 0.76), but radiologists had superior accuracy (0.95 vs. 0.77-0.85) and specificity (0.97-0.98 vs. 0.74-0.85). In a subanalysis of LNs rated as probably benign or malignant, expert radiologists outperformed the algorithm with greater specificity and PPV (p < 0.005). A density threshold of >27 HU predicted PSMA-positive LNs with 0.79 accuracy, 0.87 sensitivity, and 0.78 specificity. Conclusions: While radiomics did not outperform expert radiologists, the single first-order parameter CT density >27 HU was predictive of PSMA-positive LNs. Clinical Relevance Statement: Radiomic models did not outperform expert uroradiologists. However, in high-volume or resource-limited settings lacking access to [68Ga]Ga-PSMA-PET/CT, they may help improve LN assessment in PCa patients with CT alone.
