FDG-PET Radiomics for Response Monitoring in Non-Small-Cell Lung Cancer Treated with Radiation Therapy
The aim of this study is to identify clinically relevant image feature (IF) changes during chemoradiation and evaluate their efficacy in predicting treatment response. Patients with non-small-cell lung cancer<b> (</b>NSCLC) were enrolled in two prospective trials (STRIPE, PET-Plan). We e...
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doaj-cd67adbd50a84b3dae11d15dac8183ce2021-02-16T00:03:26ZengMDPI AGCancers2072-66942021-02-011381481410.3390/cancers13040814FDG-PET Radiomics for Response Monitoring in Non-Small-Cell Lung Cancer Treated with Radiation TherapyMontserrat Carles0Tobias Fechter1Gianluca Radicioni2Tanja Schimek-Jasch3Sonja Adebahr4Constantinos Zamboglou5Nils H. Nicolay6Luis Martí-Bonmatí7Ursula Nestle8Anca L. Grosu9Dimos Baltas10Michael Mix11Eleni Gkika12Department of Radiation Oncology, Division of Medical Physics, University Medical Center Freiburg, Faculty of Medicine, 79106 Freiburg, GermanyDepartment of Radiation Oncology, Division of Medical Physics, University Medical Center Freiburg, Faculty of Medicine, 79106 Freiburg, GermanyDepartment of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, 79106 Freiburg, GermanyDepartment of Radiation Oncology, University Medical Center Freiburg, Faculty of Medicine, 79106 Freiburg, GermanyGerman Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Partner Site Freiburg of the German Cancer Research Center (DKFZ), 69120 Heidelberg, GermanyGerman Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Partner Site Freiburg of the German Cancer Research Center (DKFZ), 69120 Heidelberg, GermanyGerman Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Partner Site Freiburg of the German Cancer Research Center (DKFZ), 69120 Heidelberg, GermanyLa Fe Health Research Institute, Biomedical Imaging Research Group (GIBI230-PREBI) and Imaging La Fe node at Distributed Network for Biomedical Imaging (ReDIB) Unique Scientific and Technical Infrastructures (ICTS), 46026 Valencia, SpainGerman Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Partner Site Freiburg of the German Cancer Research Center (DKFZ), 69120 Heidelberg, GermanyGerman Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Partner Site Freiburg of the German Cancer Research Center (DKFZ), 69120 Heidelberg, GermanyDepartment of Radiation Oncology, Division of Medical Physics, University Medical Center Freiburg, Faculty of Medicine, 79106 Freiburg, GermanyDepartment of Nuclear Medicine, University Medical Center Freiburg, Faculty of Medicine, 79106 Freiburg, GermanyGerman Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Partner Site Freiburg of the German Cancer Research Center (DKFZ), 69120 Heidelberg, GermanyThe aim of this study is to identify clinically relevant image feature (IF) changes during chemoradiation and evaluate their efficacy in predicting treatment response. Patients with non-small-cell lung cancer<b> (</b>NSCLC) were enrolled in two prospective trials (STRIPE, PET-Plan). We evaluated 48 patients who underwent static (3D) and retrospectively-respiratory-gated 4D PET/CT scans before treatment and a 3D scan during or after treatment. Our proposed method rejects IF changes due to intrinsic variability. The IF variability observed across 4D PET is employed as a patient individualized normalization factor to emphasize statistically relevant IF changes during treatment. Predictions of overall survival (OS), local recurrence (LR) and distant metastasis (DM) were evaluated. From 135 IFs, only 17 satisfied the required criteria of being normally distributed across 4D PET and robust between 3D and 4D images. Changes during treatment in the area-under-the-curve of the cumulative standard-uptake-value histogram (δ<sub>AUC</sub>CSH) within primary tumor discriminated (AUC = 0.87, Specificity = 0.78) patients with and without LR. The resulted prognostic model was validated with a different segmentation method (AUC = 0.83) and in a different patient cohort (AUC = 0.63). The quantification of tumor FDG heterogeneity by δ<sub>AUC</sub>CSH during chemoradiation correlated with the incidence of local recurrence and might be recommended for monitoring treatment response in patients with NSCLC.https://www.mdpi.com/2072-6694/13/4/814lung cancerPET radiomicsFDG monitoring and retrospectively gated 4D PET/CT |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Montserrat Carles Tobias Fechter Gianluca Radicioni Tanja Schimek-Jasch Sonja Adebahr Constantinos Zamboglou Nils H. Nicolay Luis Martí-Bonmatí Ursula Nestle Anca L. Grosu Dimos Baltas Michael Mix Eleni Gkika |
spellingShingle |
Montserrat Carles Tobias Fechter Gianluca Radicioni Tanja Schimek-Jasch Sonja Adebahr Constantinos Zamboglou Nils H. Nicolay Luis Martí-Bonmatí Ursula Nestle Anca L. Grosu Dimos Baltas Michael Mix Eleni Gkika FDG-PET Radiomics for Response Monitoring in Non-Small-Cell Lung Cancer Treated with Radiation Therapy Cancers lung cancer PET radiomics FDG monitoring and retrospectively gated 4D PET/CT |
author_facet |
Montserrat Carles Tobias Fechter Gianluca Radicioni Tanja Schimek-Jasch Sonja Adebahr Constantinos Zamboglou Nils H. Nicolay Luis Martí-Bonmatí Ursula Nestle Anca L. Grosu Dimos Baltas Michael Mix Eleni Gkika |
author_sort |
Montserrat Carles |
title |
FDG-PET Radiomics for Response Monitoring in Non-Small-Cell Lung Cancer Treated with Radiation Therapy |
title_short |
FDG-PET Radiomics for Response Monitoring in Non-Small-Cell Lung Cancer Treated with Radiation Therapy |
title_full |
FDG-PET Radiomics for Response Monitoring in Non-Small-Cell Lung Cancer Treated with Radiation Therapy |
title_fullStr |
FDG-PET Radiomics for Response Monitoring in Non-Small-Cell Lung Cancer Treated with Radiation Therapy |
title_full_unstemmed |
FDG-PET Radiomics for Response Monitoring in Non-Small-Cell Lung Cancer Treated with Radiation Therapy |
title_sort |
fdg-pet radiomics for response monitoring in non-small-cell lung cancer treated with radiation therapy |
publisher |
MDPI AG |
series |
Cancers |
issn |
2072-6694 |
publishDate |
2021-02-01 |
description |
The aim of this study is to identify clinically relevant image feature (IF) changes during chemoradiation and evaluate their efficacy in predicting treatment response. Patients with non-small-cell lung cancer<b> (</b>NSCLC) were enrolled in two prospective trials (STRIPE, PET-Plan). We evaluated 48 patients who underwent static (3D) and retrospectively-respiratory-gated 4D PET/CT scans before treatment and a 3D scan during or after treatment. Our proposed method rejects IF changes due to intrinsic variability. The IF variability observed across 4D PET is employed as a patient individualized normalization factor to emphasize statistically relevant IF changes during treatment. Predictions of overall survival (OS), local recurrence (LR) and distant metastasis (DM) were evaluated. From 135 IFs, only 17 satisfied the required criteria of being normally distributed across 4D PET and robust between 3D and 4D images. Changes during treatment in the area-under-the-curve of the cumulative standard-uptake-value histogram (δ<sub>AUC</sub>CSH) within primary tumor discriminated (AUC = 0.87, Specificity = 0.78) patients with and without LR. The resulted prognostic model was validated with a different segmentation method (AUC = 0.83) and in a different patient cohort (AUC = 0.63). The quantification of tumor FDG heterogeneity by δ<sub>AUC</sub>CSH during chemoradiation correlated with the incidence of local recurrence and might be recommended for monitoring treatment response in patients with NSCLC. |
topic |
lung cancer PET radiomics FDG monitoring and retrospectively gated 4D PET/CT |
url |
https://www.mdpi.com/2072-6694/13/4/814 |
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