Dataset Information

FDG PET versus CT radiomics to predict outcome in malignant pleural mesothelioma patients.

ABSTRACT: BACKGROUND:Careful selection of malignant pleural mesothelioma (MPM) patients for curative treatment is of highest importance, as the multimodal treatment regimen is challenging for patients and harbors a high risk of substantial toxicity. Radiomics-a quantitative method for image analysis-has shown its prognostic ability in different tumor entities and could therefore play an important role in optimizing patient selection for radical cancer treatment. So far, radiomics as a prognostic tool in MPM was not investigated. MATERIALS AND METHODS:This study is based on 72 MPM patients treated with surgery in a curative intent at our institution between 2009 and 2017. Pre-treatment Fluorine-18 fluorodeoxyglucose (FDG) PET and CT scans were used for radiomics outcome modeling. After extraction of 1404 CT and 1410 FDG PET features from each image, a preselection by principal component analysis was performed to include only robust, non-redundant features for the cox regression to predict the progression-free survival (PFS) and the overall survival (OS). Results were validated on a separate cohort. Additionally, SUVmax and SUVmean, and volume were tested for their prognostic ability for PFS and OS. RESULTS:For the PFS a concordance index (c-index) of 0.67 (95% CI 0.52-0.82) and 0.66 (95% CI 0.57-0.78) for the training cohort (n = 36) and internal validation cohort (n = 36), respectively, were obtained for the PET radiomics model. The PFS advantage of the low-risk group translated also into an OS advantage. On CT images, no radiomics model could be trained. SUV max and SUV mean were also not prognostic in terms of PFS and OS. CONCLUSION:We were able to build a successful FDG PET radiomics model for the prediction of PFS in MPM. Radiomics could serve as a tool to aid clinical decision support systems for treatment of MPM in future.

SUBMITTER: Pavic M

PROVIDER: S-EPMC7359199 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

FDG PET versus CT radiomics to predict outcome in malignant pleural mesothelioma patients.

Pavic M M Bogowicz M M Kraft J J Vuong D D Mayinger M M Kroeze S G C SGC Friess M M Frauenfelder T T Andratschke N N Huellner M M Weder W W Guckenberger M M Tanadini-Lang S S Opitz I I

EJNMMI research 20200713 1

<h4>Background</h4>Careful selection of malignant pleural mesothelioma (MPM) patients for curative treatment is of highest importance, as the multimodal treatment regimen is challenging for patients and harbors a high risk of substantial toxicity. Radiomics-a quantitative method for image analysis-has shown its prognostic ability in different tumor entities and could therefore play an important role in optimizing patient selection for radical cancer treatment. So far, radiomics as a prognostic t ...[more]

PMID: 32661672

Similar Datasets

Project description:ObjectiveThe aim of our study was to evaluate the role of 18F-FDG PET/CT integrated imaging in differentiating malignant from benign pleural effusion.MethodsA total of 176 patients with pleural effusion who underwent 18F-FDG PET/CT examination to differentiate malignancy from benignancy were retrospectively researched. The images of CT imaging, 18F-FDG PET imaging and 18F-FDG PET/CT integrated imaging were visually analyzed. The suspected malignant effusion was characterized by the presence of nodular or irregular pleural thickening on CT imaging. Whereas on PET imaging, pleural 18F-FDG uptake higher than mediastinal activity was interpreted as malignant effusion. Images of 18F-FDG PET/CT integrated imaging were interpreted by combining the morphologic feature of pleura on CT imaging with the degree and form of pleural 18F-FDG uptake on PET imaging.ResultsOne hundred and eight patients had malignant effusion, including 86 with pleural metastasis and 22 with pleural mesothelioma, whereas 68 patients had benign effusion. The sensitivities of CT imaging, 18F-FDG PET imaging and 18F-FDG PET/CT integrated imaging in detecting malignant effusion were 75.0%, 91.7% and 93.5%, respectively, which were 69.8%, 91.9% and 93.0% in distinguishing metastatic effusion. The sensitivity of 18F-FDG PET/CT integrated imaging in detecting malignant effusion was higher than that of CT imaging (p = 0.000). For metastatic effusion, 18F-FDG PET imaging had higher sensitivity (p = 0.000) and better diagnostic consistency with 18F-FDG PET/CT integrated imaging compared with CT imaging (Kappa = 0.917 and Kappa = 0.295, respectively). The specificities of CT imaging, 18F-FDG PET imaging and 18F-FDG PET/CT integrated imaging were 94.1%, 63.2% and 92.6% in detecting benign effusion. The specificities of CT imaging and 18F-FDG PET/CT integrated imaging were higher than that of 18F-FDG PET imaging (p = 0.000 and p = 0.000, respectively), and CT imaging had better diagnostic consistency with 18F-FDG PET/CT integrated imaging compared with 18F-FDG PET imaging (Kappa = 0.881 and Kappa = 0.240, respectively).Conclusion18F-FDG PET/CT integrated imaging is a more reliable modality in distinguishing malignant from benign pleural effusion than 18F-FDG PET imaging and CT imaging alone. For image interpretation of 18F-FDG PET/CT integrated imaging, the PET and CT portions play a major diagnostic role in identifying metastatic effusion and benign effusion, respectively.

Project description:Malignant pleural mesothelioma (MPM) is a highly lethal, poorly understood neoplasm that is typically associated with asbestos exposure. We performed transcriptional profiling using high-density oligonucleotide microarrays containing approximately 22,000 genes to elucidate potential molecular and pathobiological pathways in MPM using discarded human MPM tumor specimens (n=40), normal lung specimens (n=4), normal pleura specimens (n=5), and MPM and SV40-immortalized mesothelial cell lines (n=5). In global expression analysis using unsupervised clustering techniques, we found two potential subclasses of mesothelioma which correlate loosely with tumor histology. We also identified sets of genes with expression levels that distinguish between multiple tumor subclasses, normal and tumor tissues, and tumors with different morphologies. Microarray gene expression data were confirmed using quantitative reverse transcriptase-polymerase chain reaction (RT-PCR) and protein analysis for three novel candidate oncogenes (NME2, CRI1, and PDGFC) and one candidate tumor suppressor (GSN). Finally, we used bioinformatics tools (i.e. software) to create and explore complex physiological pathways that may be relevant in mesothelioma tumorigenesis, pathobiology, or both. Tissues and cell lines profiled using microarrays. Discarded MPM surgical specimens (n=40), normal pleura specimens (n=5), and normal lung specimens (n=4) were freshly collected (and snap frozen) from patients who underwent surgery at Boston's Brigham and Women's Hospital (BWH) between October 1998 and August 2000. All of these patients underwent extrapleural pneumonectomy with heated intra-pleural cisplatin chemotherapy delivered after the specimens were removed. All normal specimens were obtained from patients who were never diagnosed with MPM. Two human MPM cell lines (MS589 and MS428) were kindly provided by Jonathan A. Fletcher, M.D., Department of Pathology, BWH. The JMN1B MPM cell line19,20 has been described previously. The SV40-immortalized, non-tumorigenic mesothelial cell line (Met-5A)21 and the MPM cell line MSTO-211H22 were purchased from the American Type Culture Collection. Normal tissues were obtained from additional consented patients undergoing treatment for diseases other than MPM. All MPM samples used in these studies contained relatively pure tumor (greater than 50% tumor cells per high power field examined in a section adjacent to the tissue used). The microscopic slides from the patients' resection specimens were reviewed by one of the authors (J.G.), and the diagnosis and histologic subclassification of MPM confirmed in all cases. Linked clinical and pathological data were obtained for all patients who contributed tumor specimens. Specimens and data were rendered anonymous to protect patient confidentiality. Studies utilizing human tissues were approved by and conducted in accordance with the policies of the Institutional Review Board at BWH.

Project description:PurposeTo determine if quantitative features extracted from pretherapy fluorine 18 fluorodeoxyglucose (18F-FDG) PET/CT estimate prognosis in patients with locally advanced cervical cancer treated with chemoradiotherapy.Materials and methodsIn this retrospective study, PET/CT images and outcomes were curated from 154 patients with locally advanced cervical cancer, who underwent chemoradiotherapy from two institutions between March 2008 and June 2016, separated into independent training (n = 78; mean age, 51 years ± 13 [standard deviation]) and testing (n = 76; mean age, 50 years ± 10) cohorts. Radiomic features were extracted from PET, CT, and habitat (subregions with different metabolic characteristics) images that were derived by fusing PET and CT images. Parsimonious sets of these features were identified by the least absolute shrinkage and selection operator analysis and used to generate predictive radiomics signatures for progression-free survival (PFS) and overall survival (OS) estimation. Prognostic validation of the radiomic signatures as independent prognostic markers was performed using multivariable Cox regression, which was expressed as nomograms, together with other clinical risk factors.ResultsThe radiomics nomograms constructed with T stage, lymph node status, and radiomics signatures resulted in significantly better performance for the estimation of PFS (Harrell concordance index [C-index], 0.85 for training and 0.82 for test) and OS (C-index, 0.86 for training and 0.82 for test) compared with International Federation of Gynecology and Obstetrics staging system (C-index for PFS, 0.70 for training [P = .001] and 0.70 for test [P = .002]; C-index for OS, 0.73 for training [P < .001] and 0.70 for test [P < .001]), respectively.ConclusionPrognostic models were generated and validated from quantitative analysis of 18F-FDG PET/CT habitat images and clinical data, and may have the potential to identify the patients who need more aggressive treatment in clinical practice, pending further validation with larger prospective cohorts.Supplemental material is available for this article.© RSNA, 2020.

Project description:Background Primary tumor maximum standardized uptake value is a prognostic marker for non-small cell lung cancer. In the setting of malignancy, bone marrow activity from fluorine 18-fluorodeoxyglucose (FDG) PET may be informative for clinical risk stratification. Purpose To determine whether integrating FDG PET radiomic features of the primary tumor, tumor penumbra, and bone marrow identifies lung cancer disease-free survival more accurately than clinical features alone. Materials and Methods Patients were retrospectively analyzed from two distinct cohorts collected between 2008 and 2016. Each tumor, its surrounding penumbra, and bone marrow from the L3-L5 vertebral bodies was contoured on pretreatment FDG PET/CT images. There were 156 bone marrow and 512 tumor and penumbra radiomic features computed from the PET series. Randomized sparse Cox regression by least absolute shrinkage and selection operator identified features that predicted disease-free survival in the training cohort. Cox proportional hazards models were built and locked in the training cohort, then evaluated in an independent cohort for temporal validation. Results There were 227 patients analyzed; 136 for training (mean age, 69 years ± 9 [standard deviation]; 101 men) and 91 for temporal validation (mean age, 72 years ± 10; 91 men). The top clinical model included stage; adding tumor region features alone improved outcome prediction (log likelihood, -158 vs -152; P = .007). Adding bone marrow features continued to improve performance (log likelihood, -158 vs -145; P = .001). The top model integrated stage, two bone marrow texture features, one tumor with penumbra texture feature, and two penumbra texture features (concordance, 0.78; 95% confidence interval: 0.70, 0.85; P < .001). This fully integrated model was a predictor of poor outcome in the independent cohort (concordance, 0.72; 95% confidence interval: 0.64, 0.80; P < .001) and a binary score stratified patients into high and low risk of poor outcome (P < .001). Conclusion A model that includes pretreatment fluorine 18-fluorodeoxyglucose PET texture features from the primary tumor, tumor penumbra, and bone marrow predicts disease-free survival of patients with non-small cell lung cancer more accurately than clinical features alone. © RSNA, 2019 Online supplemental material is available for this article.

Dataset Information

FDG PET versus CT radiomics to predict outcome in malignant pleural mesothelioma patients.

Publications

FDG PET versus CT radiomics to predict outcome in malignant pleural mesothelioma patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets