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Advances in the In Vivo Molecular Imaging of Invasive Aspergillosis.
Gunzer, Matthias; Thornton, Christopher R; Beziere, Nicolas.
Afiliação
  • Gunzer M; Institute for Experimental Immunology and Imaging, University Hospital, University Duisburg-Essen, 45147 Essen, Germany.
  • Thornton CR; Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V., 44227 Dortmund, Germany.
  • Beziere N; ISCA Diagnostics Ltd. and Biosciences, College of Life & Environmental Sciences, University of Exeter, Exeter EX4 4PY, UK.
J Fungi (Basel) ; 6(4)2020 Dec 04.
Article em En | MEDLINE | ID: mdl-33291706
ABSTRACT
Invasive pulmonary aspergillosis (IPA) is a life-threatening infection of immunocompromised patients with Aspergillus fumigatus, a ubiquitous environmental mould. While there are numerous functioning antifungal therapies, their high cost, substantial side effects and fear of overt resistance development preclude permanent prophylactic medication of risk-patients. Hence, a fast and definitive diagnosis of IPA is desirable, to quickly identify those patients that really require aggressive antimycotic treatment and to follow the course of the therapeutic intervention. However, despite decades of research into this issue, such a diagnostic procedure is still not available. Here, we discuss the array of currently available methods for IPA detection and their limits. We then show that molecular imaging using positron emission tomography (PET) combined with morphological computed tomography or magnetic imaging is highly promising to become a future non-invasive approach for IPA diagnosis and therapy monitoring, albeit still requiring thorough validation and relying on further acceptance and dissemination of the approach. Thereby, our approach using the A. fumigatus-specific humanized monoclonal antibody hJF5 labelled with 64Cu as PET-tracer has proven highly effective in pre-clinical models and hence bears high potential for human application.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article