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Multi-observation PET image analysis for patient follow-up quantitation and therapy assessment. ; Multi-observation PET image analysis for patient follow-up quantitation and therapy assessment.: Multi observation PET image fusion for patient follow-up quantitation and therapy response

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  • معلومة اضافية
    • Contributors:
      Laboratoire de Traitement de l'Information Medicale (LaTIM); Université européenne de Bretagne - European University of Brittany (UEB)-Télécom Bretagne-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-Université de Brest (UBO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Mines-Télécom Paris (IMT)
    • بيانات النشر:
      HAL CCSD
      IOP Publishing
    • الموضوع:
      2011
    • Collection:
      Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe)
    • نبذة مختصرة :
      International audience ; In positron emission tomography (PET) imaging, an early therapeutic response is usually characterized by variations of semi-quantitative parameters restricted to maximum SUV measured in PET scans during the treatment. Such measurements do not reflect overall tumor volume and radiotracer uptake variations. The proposed approach is based on multi-observation image analysis for merging several PET acquisitions to assess tumor metabolic volume and uptake variations. The fusion algorithm is based on iterative estimation using a stochastic expectation maximization (SEM) algorithm. The proposed method was applied to simulated and clinical follow-up PET images. We compared the multi-observation fusion performance to threshold-based methods, proposed for the assessment of the therapeutic response based on functional volumes. On simulated datasets the adaptive threshold applied independently on both images led to higher errors than the ASEM fusion and on clinical datasets it failed to provide coherent measurements for four patients out of seven due to aberrant delineations. The ASEM method demonstrated improved and more robust estimation of the evaluation leading to more pertinent measurements. Future work will consist in extending the methodology and applying it to clinical multi-tracer datasets in order to evaluate its potential impact on the biological tumor volume definition for radiotherapy applications.
    • Relation:
      info:eu-repo/semantics/altIdentifier/pmid/21846937; inserm-00707280; https://www.hal.inserm.fr/inserm-00707280; https://www.hal.inserm.fr/inserm-00707280/document; https://www.hal.inserm.fr/inserm-00707280/file/inserm-00707280_edited.pdf; https://www.hal.inserm.fr/inserm-00707280/file/David_et_al._PMB_2012_.pdf; PUBMED: 21846937
    • الرقم المعرف:
      10.1088/0031-9155/56/18/001
    • الدخول الالكتروني :
      https://www.hal.inserm.fr/inserm-00707280
      https://www.hal.inserm.fr/inserm-00707280/document
      https://www.hal.inserm.fr/inserm-00707280/file/inserm-00707280_edited.pdf
      https://www.hal.inserm.fr/inserm-00707280/file/David_et_al._PMB_2012_.pdf
      https://doi.org/10.1088/0031-9155/56/18/001
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.D0B5E5C2