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

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, SUVMin, kurtosis, the calculated RS, SUVMean, 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.

Evaluating a Machine Learning Tool for the Classification of Pathological Uptake in Whole-Body PSMA-PET-CT Scans

“…First of all, this examination is fast and non-invasive. Second of all, it could be used for therapy prediction and differentiation between low and high-risk patients [27] and for prediction of overall survival [20], as already published before. It could furthermore be the base of individual therapy and treatment tailoring in the future, combining the technique with analysis of textural parameters.…”

“…A higher level of heterogeneity seems to predict a better response to PSMA therapy and may in the future allow a pre-therapeutic selection of responders to the treatment [19]. Moazemi et al have consecutively shown that these parameters also have prognostic potential for the overall survival of prostate cancer patients [20]. In summary, the software could take over and improve the whole process in the future, enabling specialists to focus on more important tasks.…”

“…Please note that the metabolic tumor volume (MTV) is PET-specific. This table is already published in[20].First or Higher Order Statistics Shape and Size Textural Volumetric Zone Length Statistics Volumetric Run Length Statistics…”

“…Please note that the metabolic tumor volume (MTV) is PET-specific. This table is already published in[20].…”

Theranostics in Oncology—Thriving, Now More than Ever

“…Post-therapeutic SPECT, however, is not available prior to treatment and reliable outcome predictors before commencing PSMA-directed treatment would be desirable. As such, Moazemi et al investigated radiomic features from pretherapeutic [ 68 Ga]PSMA PETs and reported on the usefulness of such mathematically extracted scan signatures for outcome prediction in patients scheduled for [ 177 Lu]PSMA [ 27 ].…”