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Abstract #0073

Dynamic evolution of infarct volumes at MRI in ischemic stroke due to large vessel occlusion

Fanny Munsch1, David Planes2, Hikaru Fukutomi3, Thomas Courret2, Emilien Micard4, Bailiang Chen4, Pierre Seners5, Gaultier Marnat2, Vincent Planche6, Pierrick Coupé7, Vincent Dousset1,2,8, Bertrand Lapergue9, Jean-Marc Olivot10, Igor Sibon11, Michel Thiebault de Schotten12, and Thomas Tourdias1,2,8
1Institute of Bioimaging, University of Bordeaux, Bordeaux, France, 2Neuroimagerie diagnostique et thérapeutique, CHU de Bordeaux, Bordeaux, France, 3Neuroimaging department, Kyoto University Hospital, Kyoto, Japan, 4INSERM CIC-IT U1433, University of Nancy, Nancy, France, 5INSERM U1266, Institut de Psychiatrie et Neurosciences de Paris, Paris, France, 6CNRS, UMR 5293, Institut des Maladies Neurodégénératives, University of Bordeaux, Bordeaux, France, 7Bordeaux INP, LABRI, CNRS, UMR5800, University of Bordeaux, Talence, France, 8INSERM, Neurocentre Magendie, University of Bordeaux, Bordeaux, France, 9Service de Neurologie et Unité de Neuro Vasculaire, Hôpital FOCH, Suresnes, France, 10Unité neurovasculaire, CHU de Toulouse, Toulouse, France, 11Unité neurovasculaire, CHU de Bordeaux, Bordeaux, France, 12CNRS, UMR-5293, University of Bordeaux, Bordeaux, France

Synopsis

Keywords: Stroke, Stroke, Image analysis; Prognosis

Motivation: The typical infarct volume courses of stroke patients are still unknown.

Goal(s): We aimed to reveal the spatiotemporal evolutions of infarct volumes and show that such charts help anticipate clinical outcomes.

Approach: On a dataset of large vessel occlusion stroke patients, we performed unsupervised clustering approach to identify groups and then extrapolated pseudo-longitudinal core volume models across time for each group before assessing the growth phenotypes influence on outcome.

Results: We identified three groups with different infarct growth profiles: slow: 11%, intermediate: 62% and fast: 27%, which translated into archetype brain locations. This growth phenotypes significantly predicted the 3-month handicap in two datasets.

Impact: Infarct volumes show stereotypical spatiotemporal courses according to the patient phenotype of resistance to ischemia referred to as slow, intermediate, or fast progressors, which help to anticipate the clinical outcome for new patients.

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Abstract

Keywords