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6 results on '"Radiologie et Imagerie Musculo-Squelettique [CHU Lille]"'

1. Abdominal musculature segmentation and surface prediction from CT using deep learning for sarcopenia assessment

Author

Paul Herent, Olivier Ernst, Nathalie Lassau, Alain Luciani, M. Cadi, Maud Creze, Jean-Baptiste Schiratti, Paul Jehanno, Olivier Lucidarme, Simon Jégou, Nathan Banaste, Frederic Pigneur, Alexandre Sadate, Alex Dallongeville, Paul Blanc-Durand, Imad Bousaid, Y. Benaceur, A. Rouchaud, Kathryn Schutte, Service de médecine nucléaire [Créteil], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Henri Mondor-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), The Lymphoma Academic Research Organisation [Lyon] (LYSARC), 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), 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), Owkin France, Service de Radiologie [Mondor], Service de Radiologie [CHU Pitié-Salpétrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier Universitaire de Nîmes (CHU Nîmes), Radiologie et Imagerie Musculo-Squelettique [CHU Lille], Hôpital Claude Huriez [Lille], CHU Lille-CHU Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Hospices Civils de Lyon (HCL), Unité BioMaps (BIOMAPS), 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), AP-HP Hôpital Bicêtre (Le Kremlin-Bicêtre), Centre hospitalier Saint-Joseph [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Centre Léon Bérard [Lyon], Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Institut Gustave Roussy (IGR), Direction de la Transformation Numérique et des Systèmes d’Information, Direction de la recherche [Gustave Roussy], CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Laboratoire d'Imagerie Biomédicale [Paris] (LIB), Université de Lille, LaBoratoire d'Imagerie biOmédicale MultimodAle Paris-Saclay (BIOMAPS), CCSD, Accord Elsevier, Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-IFR10, Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Hôpital Henri Mondor-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), and Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Sarcopenia, Similarity (geometry), Mean squared error, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, X-ray computed, Convolutional neural network, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Humans, Medicine, Radiology, Nuclear Medicine and imaging, Segmentation, Convolutional neural networks (CNN), Tomography, Abdominal Muscles, Ground truth, Muscular body bass, Radiological and Ultrasound Technology, business.industry, Deep learning, Pattern recognition, General Medicine, 030220 oncology & carcinogenesis, Test set, Neural Networks, Computer, Artificial intelligence, Tomography, X-Ray Computed, business, Algorithms
Abstract

International audience; Purpose :The purpose of this study was to build and train a deep convolutional neural networks (CNN) algorithm to segment muscular body mass (MBM) to predict muscular surface from a two-dimensional axial computed tomography (CT) slice through L3 vertebra.Materials and methods :An ensemble of 15 deep learning models with a two-dimensional U-net architecture with a 4-level depth and 18 initial filters were trained to segment MBM. The muscular surface values were computed from the predicted masks and corrected with the algorithm's estimated bias. Resulting mask prediction and surface prediction were assessed using Dice similarity coefficient (DSC) and root mean squared error (RMSE) scores respectively using ground truth masks as standards of reference.Results :A total of 1025 individual CT slices were used for training and validation and 500 additional axial CT slices were used for testing. The obtained mean DSC and RMSE on the test set were 0.97 and 3.7 cm2 respectively.Conclusion :Deep learning methods using convolutional neural networks algorithm enable a robust and automated extraction of CT derived MBM for sarcopenia assessment, which could be implemented in a clinical workflow.

Published
2020

2. How reproducible are classical and new ct-pelvimetry measurements?

Author

Patrick Devos, T. Fourquet, C. Capelle, Charles Garabedian, P. Verpillat, C. Caudrelier, Laurent Lemaitre, Philippe Puech, CHU Lille, Inserm, Université de Lille, Thérapies Lasers Assistées par l'Image pour l'Oncologie (ONCO-THAI) - U1189, Radiologie et Imagerie Musculo-Squelettique [CHU Lille], Evaluation des technologies de santé et des pratiques médicales - ULR 2694 [METRICS], Hôpital Jeanne de Flandres, Thérapies Laser Assistées par l'Image pour l'Oncologie - U 1189 [ONCO-THAI], Hôpital Claude Huriez [Lille], CHU Lille-CHU Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Evaluation des technologies de santé et des pratiques médicales - ULR 2694 (METRICS), Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Université de Lille, Université de Lille, Droit et Santé-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Thérapies Laser Assistées par l'Image pour l'Oncologie - U 1189 (ONCO-THAI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), and CCSD, Accord Elsevier

Subjects
Adult, [SDV]Life Sciences [q-bio], CT pelvimetry, 030218 nuclear medicine & medical imaging, Cohort Studies, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Pregnancy, medicine, Humans, Radiology, Nuclear Medicine and imaging, Transverse diameter, Pelvis, Retrospective Studies, Reproducibility, Radiological and Ultrasound Technology, business.industry, Reproducibility of Results, General Medicine, Multiplanar reconstruction, Middle Aged, Pelvimetry, Circumference, [SDV] Life Sciences [q-bio], Transverse plane, medicine.anatomical_structure, 030220 oncology & carcinogenesis, Female, Nuclear medicine, business, Tomography, X-Ray Computed
Abstract

Purpose The objective of this study was to assess the reliability and reproducibility of existing and new computed tomography (CT)-pelvimetry measurements. Material and methods A retrospective cohort study of 63 women with a mean age of 33.9 ± 5.2 (SD) years (range: 19–49 years) was conducted. Classical pelvimetry measurements were collected including the obstetric conjugate (OC), median transverse diameter (MTD), and interspinous diameter (ISD). Additionally, we used multiplanar reconstruction (MPR) mode to define two oblique planes: inlet pelvic plane (IPP) and mid-pelvic plane (MPP) and measure new pelvic parameters, including anteroposterior (APD), transverse diameters and circumference of both IPP and MPP (inletAPD, inletMTD, inletCIRC and midAPD, ISD, midCIRC, respectively). The reproducibility (intra- and inter-observer) of our results were assessed. Multivariate analyses using principal component analysis and clustering methods were conducted to analyze the association between pelvimetry measurements and identify patient sub-groups. Results All linear measurements (OC, inletAPD, MTD, inletMTD, midAPD, and ISD) showed statistically “almost perfect” intra- and inter-observer correlation coefficients (range: 0.924–0.980). Circumferences (inletCIRC and midCIRC) showed statistically “almost perfect” intra- (range: 0.847–0.857) and inter-observer correlation coefficients (range: 0.923–0.957). The measurement of 6 pelvimetric parameters allowed determining three groups of pelvis size. Conclusion New pelvic measurements have excellent reproducibility and are similar to the classical measurements, based on the MPR analysis of CT planes adjusted to the inner bony pelvis.

Published
2019

3. Gland and Zonal Segmentation of Prostate on T2W MR Images

Author

Serge Mordon, Moussa Diaf, S. Lakroum, Nacim Betrouni, Philippe Puech, Ouardia Chilali, Thérapies Laser Assistées par l'Image pour l'Oncologie - U 1189 (ONCO-THAI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Département Automatique, Faculté de Génie Electrique et d'Informatique, Université Mouloud Mammeri [Tizi Ouzou] (UMMTO), Radiologie et Imagerie Musculo-Squelettique [CHU Lille], Hôpital Claude Huriez [Lille], CHU Lille-CHU Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), and MORDON, SERGE

Subjects
Male, Databases, Factual, Computer science, zones, [SDV.CAN]Life Sciences [q-bio]/Cancer, 02 engineering and technology, Article, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, [SDV.CAN] Life Sciences [q-bio]/Cancer, Prostate, 0202 electrical engineering, electronic engineering, information engineering, medicine, Humans, Radiology, Nuclear Medicine and imaging, Segmentation, Computer vision, Cluster analysis, Radiological and Ultrasound Technology, business.industry, Atlas (topology), segmentation, Prostatic Neoplasms, Magnetic Resonance Imaging, Computer Science Applications, Entire gland, Peripheral zone, MR T2W images, medicine.anatomical_structure, Focal treatment, 020201 artificial intelligence & image processing, Atlas, Artificial intelligence, Mr images, business, Algorithms
Abstract

International audience; For many years, prostate segmentation on MR images concerned only the extraction of the entire gland. Currently, in the focal treatment era, there is a continuously increasing need for the separation of the different parts of the organ. In this paper, we propose an automatic segmentation method based on the use of T2W images and atlas images to segment the prostate and to isolate the peripheral and transition zones. The algorithm consists of two stages. First, the target image is registered with each zonal atlas image then the segmentation is obtained by the application of an evidential C-Means clustering. The method was evaluated on a representative and multi-centric image base and yielded mean Dice accuracy values of 0.81, 0.70, and 0.62 for the prostate, the transition zone, and peripheral zone, respectively.

Published
2016

4. Quantitative analysis of scapholunate diastasis using stress speckle-tracking sonography: a proof-of-concept and feasibility study

Author

Sammy Badr, Waled Abou Arab, Alain Blum, Anne Cotten, Guillaume Lefebvre, Gabriela Hossu, Pedro Augusto Gondim Teixeira, Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM), Imagerie Guilloz [CHRU Nancy] (Service d'imagerie Guilloz), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Radiologie et Imagerie Musculo-Squelettique [CHU Lille], Hôpital Claude Huriez [Lille], and CHU Lille-CHU Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)

Subjects
Adult, Joint Instability, Male, Wrist Joint, medicine.medical_specialty, Radiography, Stress testing, Dynamic, [SDV.IB.MN]Life Sciences [q-bio]/Bioengineering/Nuclear medicine, Wrist, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, Grip strength, 0302 clinical medicine, Ultrasound, medicine, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Humans, Radiology, Nuclear Medicine and imaging, Retrospective Studies, Ultrasonography, Scaphoid Bone, 030222 orthopedics, business.industry, Carpal instability, General Medicine, Scapholunate ligament, Wrist Injuries, medicine.disease, Healthy Volunteers, medicine.anatomical_structure, Scaphoid bone, Musculoskeletal, Ligaments, Articular, Diastasis, Feasibility Studies, Female, Stress, Mechanical, Radiology, business, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Quantitative
Abstract

International audience; Objective: To evaluate the feasibility and potential clinical applicability of speckle-tracking sonography for the dynamic evaluation of the scapholunate diastasis during stress manoeuvres.Material and methods: Two readers used speckle tracking sonography to evaluate scapholunate diastasis during a clenching fist manoeuver in 30 normal wrists. Scapholunate peak strain, mean scapholunate diastasis and the diastasis variation coefficient were analysed. IRB exemption was granted for this study. Conventional and stress wrist radiographs of 26 patients with and without a scapholunate ligament tear were retrospectively analysed to ascertain the range of variation in scapholunate diastasis.Results: Speckle-tracking parameters in normal wrists were similar between the two readers (p > 0.2061). The maximal scapholunate peak strain during stress was relatively low (

Published
2017

5. Contrast-enhanced 3T MR Perfusion of Musculoskeletal Tumours: T1 Value Heterogeneity Assessment and Evaluation of the Influence of T1 Estimation Methods on Quantitative Parameters

Author

Sammy Badr, Pedro Augusto Gondim Teixeira, Christophe Leplat, Jacques De Verbizier, Bailiang Chen, Anne Cotten, Alain Blum, Marine Beaumont, Imagerie Guilloz [CHRU Nancy] (Service d'imagerie Guilloz), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM), Radiologie et Imagerie Musculo-Squelettique [CHU Lille], Hôpital Claude Huriez [Lille], and CHU Lille-CHU Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)

Subjects
Adult, Male, medicine.medical_specialty, Striated muscle, Value (computer science), Contrast Media, Soft Tissue Neoplasms, [SDV.IB.MN]Life Sciences [q-bio]/Bioengineering/Nuclear medicine, Sensitivity and Specificity, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Neoplasms, medicine, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Humans, Radiology, Nuclear Medicine and imaging, Musculoskeletal Diseases, Quantitative analysis, Muscle, Skeletal, Neuroradiology, Aged, Musculoskeletal system, Mr perfusion, business.industry, Ultrasound, Area under the curve, Contrast (statistics), Perfusion magnetic resonance imaging, General Medicine, Middle Aged, Magnetic Resonance Imaging, 3. Good health, Perfusion, Female, Radiology, Estimation methods, business, 030217 neurology & neurosurgery, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract

To evaluate intra-tumour and striated muscle T1 value heterogeneity and the influence of different methods of T1 estimation on the variability of quantitative perfusion parameters. Eighty-two patients with a histologically confirmed musculoskeletal tumour were prospectively included in this study and, with ethics committee approval, underwent contrast-enhanced MR perfusion and T1 mapping. T1 value variations in viable tumour areas and in normal-appearing striated muscle were assessed. In 20 cases, normal muscle perfusion parameters were calculated using three different methods: signal based and gadolinium concentration based on fixed and variable T1 values. Tumour and normal muscle T1 values were significantly different (p = 0.0008). T1 value heterogeneity was higher in tumours than in normal muscle (variation of 19.8% versus 13%). The T1 estimation method had a considerable influence on the variability of perfusion parameters. Fixed T1 values yielded higher coefficients of variation than variable T1 values (mean 109.6 ± 41.8% and 58.3 ± 14.1% respectively). Area under the curve was the least variable parameter (36%). T1 values in musculoskeletal tumours are significantly different and more heterogeneous than normal muscle. Patient-specific T1 estimation is needed for direct inter-patient comparison of perfusion parameters. • T1 value variation in musculoskeletal tumours is considerable. • T1 values in muscle and tumours are significantly different. • Patient-specific T1 estimation is needed for comparison of inter-patient perfusion parameters. • Technical variation is higher in permeability than semiquantitative perfusion parameters.

Published
2017

6. Chronic Urinary Obstruction: Evaluation of Dynamic Contrast-enhanced MR Urography for Measurement of Split Renal Function

Author

Michel, Claudon, Emmanuel, Durand, Nicolas, Grenier, Alain, Prigent, Daniel, Balvay, Philippe, Chaumet-Riffaud, Kathia, Chaumoitre, Charles-André, Cuenod, Marina, Filipovic, Marie-Agnès, Galloy, Laurent, Lemaitre, Damien, Mandry, Emilien, Micard, Cédric, Pasquier, Guy H, Sebag, Marc, Soudant, Pierre-André, Vuissoz, Francis, Guillemin, Dominique, Sirinelli, Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et nanosciences d'Alsace (FMNGE), Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), CHU de Bordeaux Pellegrin [Bordeaux], AP-HP Hôpital Bicêtre (Le Kremlin-Bicêtre), Paris-Centre de Recherche Cardiovasculaire (PARCC - UMR-S U970), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Imagerie par Résonance Magnétique Médicale et Multi-Modalités (IR4M), Université Paris-Sud - Paris 11 (UP11)-Hôpital Bicêtre-Centre National de la Recherche Scientifique (CNRS), Anthropologie bio-culturelle, Droit, Ethique et Santé (ADES), Aix Marseille Université (AMU)-EFS ALPES MEDITERRANEE-Centre National de la Recherche Scientifique (CNRS), Service de Radiologie [Hôpital Saint-Joseph - Marseille], Hôpital Saint-Joseph [Marseille], Service de Radiologie [CHU HEGP], Hôpital Européen Georges Pompidou [APHP] (HEGP), Service de Radiologie Pédiatrique [CHRU Nancy], Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), IFP Energies nouvelles (IFPEN), Radiologie et Imagerie Musculo-Squelettique [CHU Lille], Hôpital Claude Huriez [Lille], CHU Lille-CHU Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Service de radiologie pédiatrique [AP-HP Hôpital Robert Debré], AP-HP Hôpital universitaire Robert-Debré [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Centre d'investigation clinique - Epidémiologie clinique [Nancy] (CIC-EC), Centre d'investigation clinique [Nancy] (CIC), Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et nanosciences d'Alsace, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), Université Paris Descartes - Paris 5 (UPD5)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Institut National de la Santé et de la Recherche Médicale (INSERM), Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (APHP), CHU Lille, Radiology Department, Claude Huriez Hospital, F-59000 Lille, France, Centre d'Epidémiologie Clinique (CIC-EC), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)-Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL)

Subjects
Adult, Male, medicine.medical_specialty, Urethral Obstruction, Adolescent, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Renal function, Contrast Media, [SDV.IB.MN]Life Sciences [q-bio]/Bioengineering/Nuclear medicine, Hydronephrosis, urologic and male genital diseases, [SDV.MHEP.UN]Life Sciences [q-bio]/Human health and pathology/Urology and Nephrology, Renal scintigraphy, Hospitals, University, Imaging, Three-Dimensional, Lower Urinary Tract Symptoms, medicine, Humans, Radiology, Nuclear Medicine and imaging, Child, ComputingMilieux_MISCELLANEOUS, Aged, Aged, 80 and over, [SDV.MHEP.PED]Life Sciences [q-bio]/Human health and pathology/Pediatrics, business.industry, Infant, Newborn, Infant, Reproducibility of Results, Middle Aged, Magnetic Resonance Imaging, Dynamic contrast, Urinary obstruction, Chronic disease, Multicenter study, Child, Preschool, Chronic Disease, Female, Radiology, Radiopharmaceuticals, business, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Pyelogram
Abstract

International audience; PURPOSE:To evaluate if measurement of split renal function ( SRF split renal function ) with dynamic contrast material-enhanced ( DCE dynamic contrast enhanced ) magnetic resonance (MR) urography is equivalent to that with renal scintigraphy ( RS renal scintigraphy ) in patients suspected of having chronic urinary obstruction.MATERIALS AND METHODS:The study protocol was approved by the institutional ethics committee of the coordinating center on behalf of all participating centers. Informed consent was obtained from all adult patients or both parents of children. This prospective, comparative study included 369 pediatric and adult patients from 14 university hospitals who were suspected of having chronic or intermittent urinary obstruction, and data from 295 patients with complete data were used for analysis. SRF split renal function was measured by using the area under the curve and the Patlak-Rutland methods, including successive review by a senior and an expert reviewer and measurement of intra- and interobserver agreement for each technique. An equivalence test for mean SRF split renal function was conducted with an α of 5%.RESULTS:Reproducibility was substantial to almost perfect for both methods. Equivalence of DCE dynamic contrast enhanced MR urography and RS renal scintigraphy for measurement of SRF split renal function was shown in patients with moderately dilated kidneys (P < .001 with the Patlak-Rutland method). However, in severely dilated kidneys, the mean SRF split renal function measurement was underestimated by 4% when DCE dynamic contrast enhanced MR urography was used compared with that when RS renal scintigraphy was used. Age and type of MR imaging device had no significant effect.CONCLUSION:For moderately dilated kidneys, equivalence of DCE dynamic contrast enhanced MR urography to RS renal scintigraphy was shown, with a standard deviation of approximately 12% between the techniques, making substitution of DCE dynamic contrast enhanced MR urography for RS renal scintigraphy acceptable. For severely dilated kidneys, a mean underestimation of SRF split renal function of 4% should be expected with DCE dynamic contrast enhanced MR urography, making substitution questionable.

Published
2014

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