CHARDIN , David

Purpose We evaluated the prognostic value of immunotherapy-induced organ inflammation observed on (18)FDG PET in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICPIs). Methods Data from patients with IIIB/IV NSCLC included in two different prospective trials were analyzed. (18)FDG PET/CT exams were...

Background: Reliable predictive and prognostic markers are still lacking for patients treated with PD1- Inhibitors for non-small cell lung cancer (NSCLC). The purpose of this study was to investigate the prognostic and predictive values of different baseline metabolic parameters, including metabolic tumor volume (MTV), from 18F-FDG PET/CT scans...

Metabolomics is a recent field of research concerning the study of small molecules or « metabolites » in biological samples. The different omics fields: genomics, transcriptomics, proteomics and metabolomics, form a chain in which each link influences the others and is influenced by external factors. Metabolomics represent the last link of this...

International audience

Abstract Background Presently, there is a wide variety of classification methods and deep neural network approaches in bioinformatics. Deep neural networks have proven their effectiveness for classification tasks, and have outperformed classical methods, but they suffer from a lack of interpretability. Therefore, these innovative methods are...

Abstract Background Presently, there is a wide variety of classification methods and deep neural network approaches in bioinformatics. Deep neural networks have proven their effectiveness for classification tasks, and have outperformed classical methods, but they suffer from a lack of interpretability. Therefore, these innovative methods are...

International audience

Abstract Purpose FDOPA PET shows good performance for the diagnosis of striatal dopaminergic denervation, making it a valuable tool for the differential diagnosis of Parkinsonism. Textural features are image biomarkers that could potentially improve the early diagnosis and monitoring of neurodegenerative parkinsonian syndromes. We explored the...

Abstract Background Supervised classification methods have been used for many years for feature selection in metabolomics and other omics studies. We developed a novel primal-dual based classification method (PD-CR) that can perform classification with rejection and feature selection on high dimensional datasets. PD-CR projects data onto a low...

Abstract Background Supervised classification methods have been used for many years for feature selection in metabolomics and other omics studies. We developed a novel primal-dual based classification method (PD-CR) that can perform classification with rejection and feature selection on high dimensional datasets. PD-CR projects data onto a low...

Abstract Background Supervised classification methods have been used for many years for feature selection in metabolomics and other omics studies. We developed a novel primal-dual based classification method (PD-CR) that can perform classification with rejection and feature selection on high dimensional datasets. PD-CR projects data onto a low...

Abstract Purpose We evaluated the prognostic value of immunotherapy-induced organ inflammation observed on 18 FDG PET in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICPIs). Methods Data from patients with IIIB/IV NSCLC included in two different prospective trials were analyzed. 18 FDG PET/CT exams...

Purpose: Identification of metabolomic biomarkers of high SBR grade in non-metastatic breast cancer. Methods: This retrospective bicentric metabolomic analysis included a training set (n = 51) and a validation set (n = 49) of breast cancer tumors, all classified as high-grade (grade III) or low-grade (grade I–II). Metabolomes of tissue samples...

International audience

International audience

International audience