Automatic quantification of brain lesion volume from post-trauma MR Images
| العنوان: | Automatic quantification of brain lesion volume from post-trauma MR Images |
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| المؤلفون: | Jean-François Payen, Alexandre Krainik, Kremer S, Christophe Maggia, Irène Troprès, Senan Doyle, Schmitt E, Thomas Mistral, Michel Dojat, Emmanuel L. Barbier, Alan Tucholka, P Roca, Adrian Kastler, Galanaud D, Florence Forbes |
| المساهمون: | [GIN] Grenoble Institut des Neurosciences (GIN), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Grenoble Alpes (UGA), Pixyl Medical [Grenoble], Laboratoire Jean Kuntzmann (LJK), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Modèles statistiques bayésiens et des valeurs extrêmes pour données structurées et de grande dimension (STATIFY), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), IRMaGe (IRMaGe), CHU Grenoble-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Les Hôptaux universitaires de Strasbourg (HUS), CHU Strasbourg |
| المصدر: | Frontiers in Neurology Frontiers in Neurology, Frontiers, In press, section Neurotrauma, ⟨10.1101/2021.04.24.21255599⟩ |
| بيانات النشر: | HAL CCSD, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | business.industry, Traumatic brain injury, [SDV]Life Sciences [q-bio], Statistical difference, medicine.disease, Mr imaging, 030218 nuclear medicine & medical imaging, Lesion, 03 medical and health sciences, 0302 clinical medicine, Text mining, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Medicine, Brain lesions, Mr images, medicine.symptom, business, Nuclear medicine, 030217 neurology & neurosurgery, Volume (compression) |
| الوصف: | ObjectivesThe determination of the volume of brain lesions after trauma is challenging. Manual delineation is observer-dependent and time-consuming which inhibits the practice in clinical routine. We propose and evaluate an automated atlas-based quantification procedure (AQP) based on the detection of abnormal mean diffusivity (MD) values computed from diffusion-weighted MR images.MethodsWe measured the performance of AQP versus manual delineation consensus by independent raters in two series of experiments: i) realistic trauma phantoms (n=5) where abnormal MD values were assigned to healthy brain images according to the intensity, form and location of lesion observed in real TBI cases; ii) severe TBI patients (n=12 patients) who underwent MR imaging within 10 days after injury.ResultsIn realistic trauma phantoms, no statistical difference in Dice similarity coefficient, precision and brain lesion volumes was found between AQP, the rater consensus and the ground truth lesion delineations. Similar findings were obtained when comparing AQP and manual annotations for TBI patients. The intra-class correlation coefficient between AQP and manual delineation was 0.70 in realistic phantoms and 0.92 in TBI patients. The volume of brain lesions detected in TBI patients was 59 ml (19-84 ml) (median; 25-75th centiles).Conclusionsour results indicate that an automatic quantification procedure could accurately determine with accuracy the volume of brain lesions after trauma. This presents an opportunity to support the individualized management of severe TBI patients.Key pointsThe management of patients with severe traumatic brain injury is complex, and access to objective quantitative information lesion volumes can support clinical decision-making.An automated delineation procedure was developed to determine the nature and volume of brain lesions post-trauma.This procedure was based on diffusion weighted MR-imaging to quantify the volume of vasogenic and cellular edema from realistic phantoms and patients with severe traumatic brain injury.Nature and quantification of the brain lesions volume compared favorably with manual delineation of brain lesions by a panel of experts. |
| اللغة: | English |
| تدمد: | 1664-2295 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f86661cddbd904b9c0ed7eddae9e0d92 https://hal.archives-ouvertes.fr/hal-03498127 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....f86661cddbd904b9c0ed7eddae9e0d92 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 16642295 |
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