Predicting the Location of Glioma Recurrence After a Resection Surgery
Autor: | Bjoern H. Menze, Hervé Delingette, Ezequiel Geremia, Emmanuel Mandonnet, Erin Stretton, Nicholas Ayache |
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Přispěvatelé: | Analysis and Simulation of Biomedical Images (ASCLEPIOS), 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 et Modélisation en Neurobiologie et Cancérologie (IMNC (UMR_8165)), Université Paris-Sud - Paris 11 (UP11)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Hôpital Lariboisière, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Lariboisière-Fernand-Widal [APHP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris Diderot - Paris 7 (UPD7), European Project: 291080,EC:FP7:ERC,ERC-2011-ADG_20110209,MEDYMA(2012), Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Hôpital Lariboisière-Université Paris Diderot - Paris 7 (UPD7) |
Jazyk: | angličtina |
Rok vydání: | 2012 |
Předmět: |
Surgical resection
medicine.medical_specialty business.industry Post surgery medicine.disease [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation 030218 nuclear medicine & medical imaging 3. Good health Resection Surgery 03 medical and health sciences 0302 clinical medicine [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Glioma [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] medicine [INFO.INFO-IM]Computer Science [cs]/Medical Imaging Resection Cavity Radiation treatment planning business [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing 030217 neurology & neurosurgery Tumor segmentation |
Zdroj: | Proceedings of 2nd International MICCAI Workshop on Spatiotemporal Image Analysis for Longitudinal and Time-Series Image Data (STIA'12) Proceedings of 2nd International MICCAI Workshop on Spatiotemporal Image Analysis for Longitudinal and Time-Series Image Data (STIA'12), 2012, Nice, France. ⟨10.1007/978-3-642-33555-6_10⟩ Spatio-temporal Image Analysis for Longitudinal and Time-Series Image Data ISBN: 9783642335549 STIA Lecture Notes in Computer Science |
Popis: | International audience; We propose a method for estimating the location of glioma recurrence after surgical resection. This method consists of a pipeline including the registration of images at different time points, the estimation of the tumor infiltration map, and the prediction of tumor regrowth using a reaction-diffusion model. A data set acquired on a patient with a low-grade glioma and post surgery MRIs is considered to evaluate the accuracy of the estimated recurrence locations found using our method. We observed good agreement in tumor volume prediction and qualitative matching in regrowth locations. Therefore, the proposed method seems adequate for modeling low-grade glioma recurrence. This tool could help clinicians anticipate tumor regrowth and better characterize the radiologically non-visible infiltrative extent of the tumor. Such information could pave the way for model-based personalization of treatment planning in a near future. |
Databáze: | OpenAIRE |
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