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Identifying the individual metabolic abnormities from a systemic perspective using whole-body PET imaging.

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  • معلومة اضافية
    • المصدر:
      Publisher: Springer-Verlag Berlin Country of Publication: Germany NLM ID: 101140988 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1619-7089 (Electronic) Linking ISSN: 16197070 NLM ISO Abbreviation: Eur J Nucl Med Mol Imaging Subsets: MEDLINE
    • بيانات النشر:
      Original Publication: Berlin : Springer-Verlag Berlin, 2002-
    • الموضوع:
      COVID-19* ; Lung Neoplasms*/pathology; Fluorodeoxyglucose F18 ; Humans ; Positron-Emission Tomography/methods ; Whole Body Imaging
    • نبذة مختصرة :
      Introduction: Distinct physiological states arise from complex interactions among the various organs present in the human body. PET is a non-invasive modality with numerous successful applications in oncology, neurology, and cardiology. However, while PET imaging has been applied extensively in detecting focal lesions or diseases, its potential in detecting systemic abnormalities is seldom explored, mostly because total-body imaging was not possible until recently.
      Methods: In this context, the present study proposes a framework capable of constructing an individual metabolic abnormality network using a subject's whole-body 18 F-FDG SUV image and a normal control database. The developed framework was evaluated in the patients with lung cancer, the one discharged after suffering from Covid-19 disease, and the one that had gastrointestinal bleeding with the underlying cause unknown.
      Results: The framework could successfully capture the deviation of these patients from healthy subjects at the level of both system and organ. The strength of the altered network edges revealed the abnormal metabolic connection between organs. The overall deviation of the network nodes was observed to be highly correlated to the organ SUV measures. Therefore, the molecular connectivity of glucose metabolism was characterized at a single subject level.
      Conclusion: The proposed framework represents a significant step toward the use of PET imaging for identifying metabolic dysfunction from a systemic perspective. A better understanding of the underlying biological mechanisms and the physiological interpretation of the interregional connections identified in the present study warrant further research.
      (© 2022. The Author(s).)
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    • Contributed Indexing:
      Keywords: Metabolic abnormality; Network analysis; Systemic disease; Whole-body PET
    • الرقم المعرف:
      0Z5B2CJX4D (Fluorodeoxyglucose F18)
    • الموضوع:
      Date Created: 20220514 Date Completed: 20220621 Latest Revision: 20220902
    • الموضوع:
      20240628
    • الرقم المعرف:
      PMC9106794
    • الرقم المعرف:
      10.1007/s00259-022-05832-7
    • الرقم المعرف:
      35567627