In Vivo Early Tumor Detection and Diagnosis by Infrared Luminescence Transient Nanothermometry
The development of technologies capable of early tumor detection is unquestionably demanded by physicians, as early diagnosis is key to achieve more efficient and less invasive treatments with improved outcomes. At the preclinical level, nanotechnology has already provided innovative solutions for t...
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Veröffentlicht in: | Advanced functional materials 2018-10, Vol.28 (43), p.n/a |
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Hauptverfasser: | , , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | The development of technologies capable of early tumor detection is unquestionably demanded by physicians, as early diagnosis is key to achieve more efficient and less invasive treatments with improved outcomes. At the preclinical level, nanotechnology has already provided innovative solutions for tumor imaging and therapy, but it has failed to provide real early tumor diagnosis. In this work, an infrared nanothermometry‐based approach toward early melanoma detection, based on the changes produced in the thermal relaxation dynamics of tissues as the tumor develops, is introduced. In vivo experiments demonstrate that detection of incipient tumors from their very onset is possible through monitoring changes in their thermal relaxation dynamics using Ag2S infrared luminescent nanothermometers. For a total tumor development time of 14 days, luminescence nanothermometry allows tumor detection 6 days before its presence is evident by visual inspection. Simultaneous study of the tumoral vasculature reveals that the premature variation in the thermal relaxation dynamics is a consequence of the interplay between tumor angiogenesis and necrosis during the different tumor development stages.
Early tumor detection becomes possible by transient thermometry using infrared emitting Ag2S nanocrystals as noncontact intratumoral nanothermometers. The drastic changes of vascularization taking place at the early stages of tumor development lie at the heart of this diagnosis approach. |
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ISSN: | 1616-301X 1616-3028 |
DOI: | 10.1002/adfm.201803924 |