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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 (177)Lu-PSMA

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 investig...

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Autores principales: Moazemi, Sobhan, Erle, Annette, Lütje, Susanne, Gaertner, Florian C., Essler, Markus, Bundschuh, Ralph A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7912143/
https://www.ncbi.nlm.nih.gov/pubmed/33525456
http://dx.doi.org/10.3390/diagnostics11020186
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author Moazemi, Sobhan
Erle, Annette
Lütje, Susanne
Gaertner, Florian C.
Essler, Markus
Bundschuh, Ralph A.
author_facet Moazemi, Sobhan
Erle, Annette
Lütje, Susanne
Gaertner, Florian C.
Essler, Markus
Bundschuh, Ralph A.
author_sort Moazemi, Sobhan
collection PubMed
description 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 ((68)Ga)-PSMA-PET/CT findings and patient-specific clinical parameters to analyze overall survival of prostate cancer (PC) patients when treated with lutethium-177 ((177)Lu)-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 (68)Ga-PSMA-PET/CT scans as well as patient-specific clinical parameters for the prediction of OS for patients with advanced PC treated with (177)Lu-PSMA therapy.
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spelling pubmed-79121432021-02-28 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 (177)Lu-PSMA Moazemi, Sobhan Erle, Annette Lütje, Susanne Gaertner, Florian C. Essler, Markus Bundschuh, Ralph A. Diagnostics (Basel) Article 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 ((68)Ga)-PSMA-PET/CT findings and patient-specific clinical parameters to analyze overall survival of prostate cancer (PC) patients when treated with lutethium-177 ((177)Lu)-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 (68)Ga-PSMA-PET/CT scans as well as patient-specific clinical parameters for the prediction of OS for patients with advanced PC treated with (177)Lu-PSMA therapy. MDPI 2021-01-28 /pmc/articles/PMC7912143/ /pubmed/33525456 http://dx.doi.org/10.3390/diagnostics11020186 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Moazemi, Sobhan
Erle, Annette
Lütje, Susanne
Gaertner, Florian C.
Essler, Markus
Bundschuh, Ralph A.
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 (177)Lu-PSMA
title 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 (177)Lu-PSMA
title_full 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 (177)Lu-PSMA
title_fullStr 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 (177)Lu-PSMA
title_full_unstemmed 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 (177)Lu-PSMA
title_short 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 (177)Lu-PSMA
title_sort 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 (177)lu-psma
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7912143/
https://www.ncbi.nlm.nih.gov/pubmed/33525456
http://dx.doi.org/10.3390/diagnostics11020186
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