Estimating the Potential of Radiomics Features and Radiomics Signature from Pretherapeutic PSMA-PET-CT Scans and Clinical Data for Prediction of Overall Survival When Treated with 177Lu-PSMA

Sobhan Moazemi; Annette Erle; Susanne Lütje; Florian C Gaertner; Markus Essler; Ralph A Bundschuh

doi:10.3390/diagnostics11020186

Estimating the Potential of Radiomics Features and Radiomics Signature from Pretherapeutic PSMA-PET-CT Scans and Clinical Data for Prediction of Overall Survival When Treated with ¹⁷⁷Lu-PSMA

Diagnostics (Basel). 2021 Jan 28;11(2):186. doi: 10.3390/diagnostics11020186.

Authors

Sobhan Moazemi^{1

2}, Annette Erle¹, Susanne Lütje¹, Florian C Gaertner¹, Markus Essler¹, Ralph A Bundschuh¹

Affiliations

¹ Department of Nuclear Medicine, University Hospital Bonn, 53127 Bonn, Germany.
² Department of Computer Science, University of Bonn, 53115 Bonn, Germany.

Abstract

Prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PSMA-PET/CT) scans can facilitate diagnosis and treatment of prostate disease. Radiomics signature (RS) is widely used for the analysis of overall survival (OS) in cancer diseases. This study aims at investigating the role of radiomics features (RFs) and RS from pretherapeutic gallium-68 (⁶⁸Ga)-PSMA-PET/CT findings and patient-specific clinical parameters to analyze overall survival of prostate cancer (PC) patients when treated with lutethium-177 (¹⁷⁷Lu)-PSMA. A cohort of 83 patients with advanced PC was retrospectively analyzed. Average values of 73 RFs of 2070 malignant hotspots as well as 22 clinical parameters were analyzed for each patient. From the Cox proportional hazard model, the least absolute shrinkage and selection operator (LASSO) regularization method is used to select most relevant features (standardized uptake value (SUV)_Min and kurtosis with the coefficients of 0.984 and -0.118, respectively) and to calculate the RS from the RFs. Kaplan-Meier (KM) estimator was used to analyze the potential of RFs and conventional clinical parameters, such as metabolic tumor volume (MTV) and standardized uptake value (SUV) for the prediction of survival. As a result, SUV_Min, kurtosis, the calculated RS, SUV_Mean, as well as Hemoglobin (Hb)1, C-reactive protein (CRP)1, and ECOG1 (clinical parameters) achieved p-values less than 0.05, which suggest the potential of findings from ⁶⁸Ga-PSMA-PET/CT scans as well as patient-specific clinical parameters for the prediction of OS for patients with advanced PC treated with ¹⁷⁷Lu-PSMA therapy.

Keywords: computed tomography (CT); overall survival (OS); positron emission tomography (PET); prostate cancer (PC); prostate specific membrane antigen (PSMA); radiomics signature (RS).