Communication Dans Un Congrès Année : 2023

Correlating 68Ga-PSMA PET/CT Imaging Features with PSA Variation for Castration-Resistant Prostate Cancer Patients

Résumé

Aim/Introduction: Prostate cancer is a major health concern worldwide, and the treatment of advanced prostate cancer is still challenging. Radiopharmaceutical therapy with 177Lu-PSMA has emerged as a promising approach to address this issue. PET/CT imaging is commonly used to determine the extent of disease and the correlation between PET/CT imaging features and serum PSA levels has been shown to predict treatment outcomes [1]. In this work, we analyzed some correlations between imaging features and PSA levels to highlight the importance of PET/ CT imaging in predicting the response to 177Lu-PSMA therapy. Materials and Methods: We conducted a retrospective analysis of 45 male patients who received 177Lu-PSMA treatment, all patients had a 68Ga-PSMA PET/CT imaging. The images were pre-processed using a deep learning automatic segmentation (TotalSegmentator [2]); the physiological organs uptake, obtained by expanding 68Ga-PSMA-avid known OARs (liver, kidneys, spleen, stomach, pancreas ڮ(, was set to zero to obtain one single whole-body tumor region (WBTR) encompassing all potential tumors without physiological uptake. For each patient, the biological PSA (initial and fnal) was retrieved, and we studied the correlation between the PET radiomics and the PSA values using Spearman’s rank correlation, a Multi-Layer Perceptron with three hidden layers, and a Random Forest. We compared the results to a standard approach where the WBTRstandard is obtained by a threshold set as the kidney’s mean SUV. Results: A signifcant but weak correlation was found between the WBTR volume and the PSA variation. The correlation coefcient was -0.41 (p-value: 0.01), while for the standard approach it was -0.34 (p-value: 0.02). Moreover, we evaluated the predictive performance of MLP and Random Forest models for PSA variation. We obtained a mean absolute error of 163% for MLP and 563% for Random Forest. The standard approach had an error of 149% for MLP and 558% for Random Forest. Conclusion: This preliminary study only showed the presence of a weak correlation between the WBTR volume and the PSA variation. The use of simple statistics is not enough to establish a signifcant improvement. Further research through advanced machine learning techniques is necessary to explore the potential of this method. References: [1] Moazemi, May 2021, Annals of Translational Medicine[2] Wasserthal, 2022, arXiv
Fichier principal
Vignette du fichier
259_2023_6333_OnlinePDF.pdf (77.17 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04894325 , version 1 (22-01-2025)

Identifiants

  • HAL Id : hal-04894325 , version 1

Citer

Eduardo Rios Sanchez, David Sarrut, Jean‐noël Badel. Correlating 68Ga-PSMA PET/CT Imaging Features with PSA Variation for Castration-Resistant Prostate Cancer Patients. EANM 2024, Sep 2023, Vienna (AUSTRIA), France. ⟨hal-04894325⟩
0 Consultations
0 Téléchargements

Partager

More