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3. Optimization of a Shape Metric Based on Information Theory Applied to Segmentation Fusion and Evaluation in Multimodal MRI for DIPG Tumor Analysis

Author

Jehan-Besson, Stéphanie, Clouard, Régis, Boddaert, Nathalie, Grill, Jacques, Frouin, Frédérique, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Nielsen, Frank, editor, and Barbaresco, Frédéric, editor

Published
2021
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10. Demonstration of the use of LIFEx for radiomic feature extraction from a PET/MR scan from LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characterization of Tumor Heterogeneity

Author

Nioche, Christophe, primary, Orlhac, Fanny, primary, Boughdad, Sarah, primary, Reuzé, Sylvain, primary, Goya-Outi, Jessica, primary, Robert, Charlotte, primary, Pellot-Barakat, Claire, primary, Soussan, Michael, primary, Frouin, Frédérique, primary, and Buvat, Irène, primary

Published
2023
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16. A visual ensemble approach using deep convolutional neural networks for 3D segmentation of breast tumors on dynamic contrast enhanced MRI

Author

Rahimpour, Masoomeh, Saint Martin, Marie-Judith, Frouin, Frédérique, Akl, Pia, Orlhac, Fanny, Koole, Michel, and Malhaire, Caroline

Subjects
Magnetic resonance imaging, Neural networks, computer, Image processing, computer-assisted, Breast neoplasms
Abstract

Objectives: To develop a visual ensemble approach using deep convolutional neural networks for 3D segmentation of breast tumors using T1-weighted dynamic contrast-enhanced (T1-DCE) MRI. Methods: Multi-center 3D T1-DCE MRI (n=141) were acquired for a cohort of patients diagnosed with locally advanced or aggressive breast cancer. Tumor lesions of 111 scans were equally divided between two radiologists and segmented for training. The additional 30 scans were segmented independently by both radiologists for testing. Three 3D U-Net models were trained using either post-contrast images or a combination of post-contrast and subtraction images fused either at the image or feature level. Segmentation accuracy was evaluated quantitatively using the Dice Similarity Coefficient (DSC) and the Hausdorff distance (HD95) and scored qualitatively by a radiologist as excellent, useful, or unacceptable. Based on this score, a visual ensemble approach selecting the best segmentation among these three models was proposed. Results: Mean and standard deviation of DSC and HD95 between the two radiologists were equal to 77.8±9.9% and 5.2±5.8 mm. Using the visual ensemble approach, a DSC and HD95 equal to 79.0±15.7% and 14.0±40.1 mm were reached. The qualitative assessment was excellent (resp. excellent or useful) in 53% (resp. 93%). Conclusion: Using subtraction images in addition to post-contrast images provided complementary information for 3D segmentation of breast lesions by convolutional neural networks. A visual ensemble approach allowing the radiologist to select the most optimal segmentation obtained by three 3D U-Net models achieved comparable results to the inter-radiologist agreement, yielding 93% segmented volumes considered excellent or useful. ispartof: European Radiology vol:33 issue:2 ispartof: location:Germany status: published

Published
2022

18. Classification of Segmental Wall Motion in Echocardiography Using Quantified Parametric Images

Author

Dominguez, Cinta Ruiz, Kachenoura, Nadjia, Mulé, Sébastien, Tenenhaus, Arthur, Delouche, Annie, Nardi, Olivier, Gérard, Olivier, Diebold, Benoît, Herment, Alain, Frouin, Frédérique, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Frangi, Alejandro F., editor, Radeva, Petia I., editor, Santos, Andres, editor, and Hernandez, Monica, editor

Published
2005
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22. Correction for Magnetic Field Inhomogeneities and Normalization of Voxel Values Are Needed to Better Reveal the Potential of MR Radiomic Features in Lung Cancer

Author

Lacroix, Maxime, Frouin, Frédérique, Dirand, Anne-Sophie, Nioche, Christophe, Orlhac, Fanny, Bernaudin, Jean-François, Brillet, Pierre-Yves, Buvat, Irène, Imagerie Moléculaire in Vivo (IMIV - U1023 - ERL9218), Service Hospitalier Frédéric Joliot (SHFJ), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de radiologie [Avicenne], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Avicenne [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Sorbonne Paris Nord, Laboratoire d'Imagerie Translationnelle en Oncologie (LITO ), Institut Curie [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), Hypoxie et Poumon : pneumopathologies fibrosantes, modulations ventilatoires et circulatoires (H&P), UFR SMBH-Université Sorbonne Paris Nord, Université Paris 13 (UP13), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Frouin, Frédérique

Subjects
Cancer Research, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, [SDV.CAN]Life Sciences [q-bio]/Cancer, histological types of lung cancer, MRI normalization, bias field correction, [SDV.MHEP.PSR]Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract, T2-weighted MR images, lung cancer, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, [SDV.CAN] Life Sciences [q-bio]/Cancer, Oncology, radiomics, [SDV.MHEP.PSR] Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract, Original Research
Abstract

International audience; Purpose: To design and validate a preprocessing procedure dedicated to T2-weighted MR images of lung cancers so as to improve the ability of radiomic features to distinguish between adenocarcinoma and other histological types.Materials and Methods: A discovery set of 52 patients with advanced lung cancer who underwent T2-weighted MR imaging at 3 Tesla in a single center study from August 2017 to May 2019 was used. Findings were then validated using a validation set of 19 additional patients included from May to October 2019. Tumor type was obtained from the pathology report after trans-thoracic needle biopsy, metastatic lymph node or metastasis samples, or surgical excisions. MR images were preprocessed using N4ITK bias field correction and by normalizing voxel intensities with fat as a reference region. Segmentation and extraction of radiomic features were performed with LIFEx software on the raw images, on the N4ITK-corrected images and on the fully preprocessed images. Two analyses were conducted where radiomic features were extracted: (1) from the whole tumor volume (3D analysis); (2) from all slices encompassing the tumor (2D analysis). Receiver operating characteristic (ROC) analysis was used to identify features that could distinguish between adenocarcinoma and other histological types. Sham experiments were also designed to control the number of false positive findings.Results: There were 31 (12) adenocarcinomas and 21 (7) other histological types in the discovery (validation) set. In 2D, preprocessing increased the number of discriminant radiomic features from 8 without preprocessing to 22 with preprocessing. 2D analysis yielded more features able to identify adenocarcinoma than 3D analysis (12 discriminant radiomic features after preprocessing in 3D). Preprocessing did not increase false positive findings as no discriminant features were identified in any of the sham experiments. The greatest sensitivity of the 2D analysis applied to preprocessed data was confirmed in the validation set.Conclusion: Correction for magnetic field inhomogeneities and normalization of voxel values are essential to reveal the full potential of radiomic features to identify the tumor histological type from MR T2-weighted images, with classification performance similar to those reported in PET/CT and in multiphase CT in lung cancers

Published
2020

23. Optimisation d'une métrique de forme basée sur la théorie de l'information pour la fusion et l'évaluation de méthodes de segmentation de tumeurs GITC en IRM multimodale 3D

Author

Jehan-Besson, Stéphanie, Clouard, Régis, Boddaert, Nathalie, Grill, Jacques, Frouin, Frédérique, Laboratoire d'Imagerie Translationnelle en Oncologie (LITO ), Institut Curie [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), Equipe Image - Laboratoire GREYC - UMR6072, Groupe de Recherche en Informatique, Image et Instrumentation de Caen (GREYC), Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU), Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Vectorologie et thérapeutiques anti-cancéreuses [Villejuif] (UMR 8203), Université Paris-Sud - Paris 11 (UP11)-Institut Gustave Roussy (IGR)-Centre National de la Recherche Scientifique (CNRS), Département de cancérologie de l'enfant et de l'adolescent [Gustave Roussy], and Institut Gustave Roussy (IGR)

Subjects
ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.2: Design Methodology/I.5.2.1: Feature evaluation and selection, ACM: H.: Information Systems/H.1: MODELS AND PRINCIPLES/H.1.1: Systems and Information Theory/H.1.1.1: Information theory, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.7: Feature Measurement/I.4.7.4: Size and shape, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, ACM: G.: Mathematics of Computing/G.1: NUMERICAL ANALYSIS/G.1.6: Optimization/G.1.6.3: Gradient methods, ACM: G.: Mathematics of Computing/G.1: NUMERICAL ANALYSIS/G.1.2: Approximation/G.1.2.0: Approximation of surfaces and contours, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.5: Computational Geometry and Object Modeling/I.3.5.2: Curve, surface, solid, and object representations, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.2: Geometric, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.10: Vision and Scene Understanding/I.2.10.7: Shape, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2021

27. Preclinical and clinical evaluation of a new method to assess cardiac insulin resistance using nuclear imaging

Author

Perret, Pascale, primary, Slimani, Lotfi, additional, Barone-Rochette, Gilles, additional, Vollaire, Julien, additional, Briat, Arnaud, additional, Ahmadi, Mitra, additional, Henri, Marion, additional, Desruet, Marie-Dominique, additional, Clerc, Romain, additional, Broisat, Alexis, additional, Riou, Laurent, additional, Boucher, François, additional, Frouin, Frédérique, additional, Djaileb, Loïc, additional, Calizzano, Alex, additional, Vanzetto, Gérald, additional, Fagret, Daniel, additional, and Ghezzi, Catherine, additional

Published
2021
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32. Analyse radiomique des gliomes de bas grades : une étude rétrospective

Author

Flory, Violaine, primary, Mondot, Lydiane, additional, Burel-Vandenbos, Fanny, additional, Denis, Eve, additional, Chanalet, Stéphane, additional, Almairac, Fabien, additional, Bourg, Véronique, additional, Goya-Outi, Jessica, additional, Frouin, Frédérique, additional, Fontaine, Denys, additional, Lebrun-Frenay, Christine, additional, and Orlhac, Fanny, additional

Published
2020
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41. Voxel-Based Statistical Analysis of 3D Immunostained Tissue Imaging

Author

Vandenberghe, Michel, Souedet, Nicolas, Herard, Anne-Sophie, Ayral, Anne-Marie, Letronne, Florent, Balbastre, Yael, Sadouni, Elmahdi, Hantraye, Philippe, Dhenain, Marc, Frouin, Frédérique, Lambert, Jean-Charles, Delzescaux, Thierry, Laboratoire des Maladies Neurodégénératives - UMR 9199 (LMN), Service MIRCEN (MIRCEN), Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie François JACOB (JACOB), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie François JACOB (JACOB), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS), Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement - U 1167 (RID-AGE), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Epidémiologie des maladies chroniques : impact des interactions gène environnement sur la santé des populations, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille, Droit et Santé, Institut d'Imagerie BioMédicale (I2BM), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, CEA [Fontenay-aux-Roses] (UGRA / SETA), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Laboratoire d'imagerie fonctionnelle [CHU Pitié-Salpétriêre] (LIF), Université Pierre et Marie Curie - Paris 6 (UPMC)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Département Imagerie et Simulation pour le Contrôle (DISC), Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Centre National de la Recherche Scientifique (CNRS)-Service MIRCEN (MIRCEN), Université Paris-Saclay-Institut de Biologie François JACOB (JACOB), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut de Biologie François JACOB (JACOB), Laboratoire d'imagerie fonctionnelle [Paris] (LIF), Université Pierre et Marie Curie - Paris 6 (UPMC), Laboratoire d'Intégration des Systèmes et des Technologies (LIST), and Hérard, Anne-Sophie

Subjects
[SDV] Life Sciences [q-bio], voxel-based, [SDV]Life Sciences [q-bio], immunohistochemistry, rodent, microscopy, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], [SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Alzheimer's disease, Neuroscience, Original Research, 3D
Abstract

International audience; Recently developed techniques to visualize immunostained tissues in 3D and in large samples have expanded the scope of microscopic investigations at the level of the whole brain. Here, we propose to adapt voxel-based statistical analysis to 3D high-resolution images of the immunostained rodent brain. The proposed approach was first validated with a simulation dataset with known cluster locations. Then, it was applied to characterize the effect of ADAM30, a gene involved in the metabolism of the amyloid precursor protein, in a mouse model of Alzheimer's disease. This work introduces voxel-based analysis of 3D immunostained microscopic brain images and, therefore, opens the door to localized whole-brain exploratory investigation of pathological markers and cellular alterations.

Published
2018

42. Validation of a harmonization method to correct for SUV and radiomic features variability in multi-center studies

Author

Orlhac, Fanny, Humbert, Olivier, Boughdad, Sarah, Lasserre, Maud, Soussan, Michael, Nioche, Christophe, Ayache, Nicholas, Darcourt, Jacques, Frouin, Frédérique, Buvat, Irène, E-Patient : Images, données & mOdèles pour la médeciNe numériquE (EPIONE), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Imagerie Moléculaire in Vivo (IMIV - U1023 - ERL9218), Service Hospitalier Frédéric Joliot (SHFJ), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Transporteurs et Imagerie, Radiothérapie en Oncologie et Mécanismes biologiques des Altérations du Tissu Osseux (TIRO-MATOs - UMR E4320), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-UMR E4320 (TIRO-MATOs), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Côte d'Azur (UCA), Centre de Lutte contre le Cancer Antoine Lacassagne [Nice] (UNICANCER/CAL), UNICANCER-Université Côte d'Azur (UCA), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA), Institut Curie [Paris], Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon), Hôpital Avicenne [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), UMR E4320 (TIRO-MATOs), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Côte d'Azur (UCA)-Service Hospitalier Frédéric Joliot (SHFJ), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, and Orlhac, Fanny

Subjects
[INFO.INFO-IM] Computer Science [cs]/Medical Imaging, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
Abstract

International audience; Objectives: Quantitative characterization of tumor heterogeneity using PET images shows encouraging results to predict patient response or survival, paving the way for precision medicine based on radiomic features. Yet, the vast majority of results are obtained in monocentric studies, without subsequent validation in multicenter settings. One reason is that radiomic features, as well as SUV measurements, are sensitive to the acquisition and reconstruction of PET images, hence a radiomic model established in one center might not be directly applicable to radiomic data from another center. This considerably reduces the dissemination of radiomic models. The goal of this study was to validate the use of the recently described ComBat harmonization method [1] to remove the center effect in a 3-center setting. Methods: 18F-FDG PET images from 190 patients at initial staging for breast cancer from three centers were included. In center A, 63 patients were scanned using a Gemini TF PET/CT scanner (Philips, BLOB-OS-TF, voxel = 4x4x4 mm). In center B, 74 patients underwent a PET on a Discovery 690 PET/CT scanner (GE Healthcare, OSEM, 2.7x2.7x3.3 mm). In center C, 53 patients were scanned using a Gemini GXL PET/CT scanner (Philips, LORRAMLA, 2x2x1.9 mm). For each patient, the primary lesion was segmented using a threshold equal to 40% of SUVmax. In the resulting volume of interest, we computed SUVmax, SUVmean and 6 textural features (resampling step: 64 gray-levels between 0 and 20 SUV units) using the LIFEx software. The ComBat harmonization method was used to estimate the center effect based on the observed tumor feature values in the three patient groups. To validate its efficiency, for each feature, we investigated the differences between the 3 centers using Kruskal-Wallis test. We also determined the best cutoff value in center A to separate triple-negative (TN) from non-TN lesions by maximizing the Youden index (Sensitivity + Specificity-1). Then we applied this optimal cutoff value on the feature values of the other two centers before and after ComBat. Youden index was used to evaluate the accuracy of TN classification in each case. Results: In total, 45 lesions were TN (24%) in proportions similar for all patient groups (25% in center A, 20% in center B and 26% in center C). We observed a shift in feature values between the three patient groups, likely due to the scanner effect with a significant difference between the three centers for 7/8 features (p-values < 0.05, Kruskal-Wallis test). After ComBat harmonization, the scanner effect could no longer be detected (p-values > 0.11 for all features). For instance, without harmonization, Homogeneity in center A was lower than Homogeneity in center B, which was itself lower than in center C. The p value of Kruskal-Wallis was less than 0.001 before ComBat and increased to 0.998 after harmonization for Homogeneity. In center A, Youden indices obtained for the 8 features were all between 0.29 and 0.54 for distinguishing TN from non-TN lesions when the cutoff values were determined based on data from center A. When these cutoff values were applied on data from centers B and C without ComBat harmonization, all Youden indices were between 0.04 and 0.29, corresponding to poor performance in TN identification. After ComBat harmonization, all Youden indices increased and were between 0.28 and 0.42, close to values obtained in center A only. Conclusions: As demonstrated in this study, using ComBat harmonization enables to pool values of radiomic features and SUV measured in PET images acquired in different acquisition and reconstruction conditions. The method is data-driven (no phantom acquisition is needed) and is applied directly to the features values, without requiring any re-calculation of features. ComBat harmonization should facilitate the portability of radiomic models between centers and accelerate their use in clinical practice.

Published
2018

43. Validation d'une méthode d'harmonisation des mesures SUV et des variables radiomiques pour les études TEP multicentriques rétrospectives

Author

Orlhac, Fanny, Humbert, Olivier, Boughdad, Sarah, Lasserre, Maud, Soussan, Michael, Nioche, Christophe, Ayache, Nicholas, Darcourt, Jacques, Frouin, Frédérique, Buvat, Irène, E-Patient : Images, données & mOdèles pour la médeciNe numériquE (EPIONE), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Imagerie Moléculaire in Vivo (IMIV - U1023 - ERL9218), Service Hospitalier Frédéric Joliot (SHFJ), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Transporteurs et Imagerie, Radiothérapie en Oncologie et Mécanismes biologiques des Altérations du Tissu Osseux (TIRO-MATOs - UMR E4320), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-UMR E4320 (TIRO-MATOs), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Côte d'Azur (UCA), Centre de Lutte contre le Cancer Antoine Lacassagne [Nice] (UNICANCER/CAL), UNICANCER-Université Côte d'Azur (UCA), Institut Curie [Paris], Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon), Hôpital Avicenne [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Orlhac, Fanny, Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), UMR E4320 (TIRO-MATOs), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Côte d'Azur (UCA)-Service Hospitalier Frédéric Joliot (SHFJ), and Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay

Subjects
Etude multicentrique, Quantification, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Normalisation, Analyse de texture, Hétérogénéité tumorale
Abstract

International audience; En imagerie TEP, les études multicentriques sont limitées car les mesures effectuées sur les images (SUV et autres index radiomiques) sont sensibles aux protocoles d’acquisition et de reconstruction. Notre but est de valider l’utilisation de la méthode d’harmonisation ComBat afin de supprimer l’« effet centre » dans les études multicentriques rétrospectives.

Published
2018

44. Validation of a method to compensate multicenter effects affecting CT radiomic features

Author

Orlhac, Fanny, Frouin, Frédérique, Nioche, Christophe, Ayache, Nicholas, Buvat, Irene, E-Patient : Images, données & mOdèles pour la médeciNe numériquE (EPIONE), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Imagerie Moléculaire in Vivo (IMIV - U1023 - ERL9218), Service Hospitalier Frédéric Joliot (SHFJ), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Orlhac, Fanny

Subjects
[SDV.IB] Life Sciences [q-bio]/Bioengineering, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, [SDV.CAN] Life Sciences [q-bio]/Cancer, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, [SDV.CAN]Life Sciences [q-bio]/Cancer, [SDV.IB]Life Sciences [q-bio]/Bioengineering, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, ComputingMilieux_MISCELLANEOUS, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
Abstract

International audience

Published
2018

46. Consistency of aortic distensibility and pulse wave velocity estimates with respect to the Bramwell-Hill theoretical model: a cardiovascular magnetic resonance study

Author

De Cesare Alain, Lefort Muriel, Frouin Frédérique, Kachenoura Nadjia, Dogui Anas, Mousseaux Elie, and Herment Alain

Subjects
Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Abstract Background Arterial stiffness is considered as an independent predictor of cardiovascular mortality, and is increasingly used in clinical practice. This study aimed at evaluating the consistency of the automated estimation of regional and local aortic stiffness indices from cardiovascular magnetic resonance (CMR) data. Results Forty-six healthy subjects underwent carotid-femoral pulse wave velocity measurements (CF_PWV) by applanation tonometry and CMR with steady-state free-precession and phase contrast acquisitions at the level of the aortic arch. These data were used for the automated evaluation of the aortic arch pulse wave velocity (Arch_PWV), and the ascending aorta distensibility (AA_Distc, AA_Distb), which were estimated from ascending aorta strain (AA_Strain) combined with either carotid or brachial pulse pressure. The local ascending aorta pulse wave velocity AA_PWVc and AA_PWVb were estimated respectively from these carotid and brachial derived distensibility indices according to the Bramwell-Hill theoretical model, and were compared with the Arch_PWV. In addition, a reproducibility analysis of AA_PWV measurement and its comparison with the standard CF_PWV was performed. Characterization according to the Bramwell-Hill equation resulted in good correlations between Arch_PWV and both local distensibility indices AA_Distc (r = 0.71, p < 0.001) and AA_Distb (r = 0.60, p < 0.001); and between Arch_PWV and both theoretical local indices AA_PWVc (r = 0.78, p < 0.001) and AA_PWVb (r = 0.78, p < 0.001). Furthermore, the Arch_PWV was well related to CF_PWV (r = 0.69, p < 0.001) and its estimation was highly reproducible (inter-operator variability: 7.1%). Conclusions The present work confirmed the consistency and robustness of the regional index Arch_PWV and the local indices AA_Distc and AA_Distb according to the theoretical model, as well as to the well established measurement of CF_PWV, demonstrating the relevance of the regional and local CMR indices.

Published
2011
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47. A pilot study to quantify hepatic perfusion using pseudo-continuous arterial spin labeling in MRI

Author

Cohen, Mike-Ely, Lajoie, Isabelle, Dyson, Kenneth, Lucidarme, Olivier, Hoge, Richard, Frouin, Frédérique, Laboratoire d'Imagerie Biomédicale [Paris] (LIB), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre de recherche de l'Institut universitaire de gériatrie de Montreal (CRIUGM), Université de Montréal (UdeM), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada], Imagerie Moléculaire in Vivo (IMIV - U1023 - ERL9218), Service Hospitalier Frédéric Joliot (SHFJ), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Imagerie Biomédicale (LIB), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Frouin, Frédérique

Subjects
[SDV.IB] Life Sciences [q-bio]/Bioengineering, Image Processing, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Magnetic Resonance Imaging
Abstract

Congrès sous l’égide de la Société Française de Génie Biologique et Médical (SFGBM); National audience; This study aimed at optimizing a pseudo-Continuous Arterial Spin Labeling (pCASL) approach to quantify hepatic perfusion in MRI. Six volunteers were examined using a 3T Siemens scanner, pCASL sequences with 4 and 20 repetitions were acquired in a plane orthogonal to portal vein with a post label delay (PLD) of 600 ms. For two subjects, four additional PLD (varying from 1000 to 1600 ms) were tested. Data were processed using specific software, which computes parametric maps of hepatic perfusion (HP). Global results show a more robust HP estimation when using 20 repetitions. The five PLD values provided hepatic perfusion weighted differently by the hepatic artery and the portal vein blood flows. This strategy could be used to estimate separately these two components.

Published
2015

48. Local classification of microvascular function based on contrast-enhanced ultrasound data: a feasibility study

Author

Doury, Maxime, Dizeux, Alexandre, Barrois, Guillaume, Le Guillou-Buffello, Delphine, Coron, Alain, Bridal, Lori, de Cesare, Alain, Frouin, Frédérique, Frouin, Frédérique, Laboratoire d'Imagerie Biomédicale (LIB), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Imagerie Moléculaire in Vivo (IMIV - U1023 - ERL9218), Service Hospitalier Frédéric Joliot (SHFJ), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), FRM (DBS20131128436), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Laboratoire d'Imagerie Biomédicale [Paris] (LIB)

Subjects
[SDV.IB] Life Sciences [q-bio]/Bioengineering, Tumor, Microvascularization, Image Processing, Ultrasound, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Contrast
Abstract

National audience; Dynamic contrast-enhanced ultrasound can detect microvascular flow changes during tumor development and antiangiogenic therapy. However, the standard method for microvascular flow estimation in tumors is global and can lead to bias in flow estimations in heterogeneous tumors. A new method to segment tumors according to their vascularization was investigated. In addition, parameter normalization with respect to a highly vascularized region of reference was proposed to overcome inter-exam variability in parameters. Results demonstrate the potential to locally classify tumoral tissue using parameters that describes the arrival of an ultrasound contrast agent in the tumor.

Published
2015

49. LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characterization of Tumor Heterogeneity

Author

Nioche, Christophe, primary, Orlhac, Fanny, additional, Boughdad, Sarah, additional, Reuzé, Sylvain, additional, Goya-Outi, Jessica, additional, Robert, Charlotte, additional, Pellot-Barakat, Claire, additional, Soussan, Michael, additional, Frouin, Frédérique, additional, and Buvat, Irène, additional

Published
2018
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