Fluorescence-Guided Resection of Malignant Glioma with 5-ALA
Malignant gliomas are extremely difficult to treat with no specific curative treatment. On the other hand, photodynamic medicine represents a promising technique for neurosurgeons in the treatment of malignant glioma. The resection rate of malignant glioma has increased from 40% to 80% owing to 5-am...
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Published in | International journal of biomedical imaging Vol. 2016; no. 2016; pp. 1 - 11 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Cairo, Egypt
Hindawi Publishing Corporation
01.01.2016
John Wiley & Sons, Inc Hindawi Limited |
Subjects | |
Online Access | Get full text |
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Summary: | Malignant gliomas are extremely difficult to treat with no specific curative treatment. On the other hand, photodynamic medicine represents a promising technique for neurosurgeons in the treatment of malignant glioma. The resection rate of malignant glioma has increased from 40% to 80% owing to 5-aminolevulinic acid-photodynamic diagnosis (ALA-PDD). Furthermore, ALA is very useful because it has no serious complications. Based on previous research, it is apparent that protoporphyrin IX (PpIX) accumulates abundantly in malignant glioma tissues after ALA administration. Moreover, it is evident that the mechanism underlying PpIX accumulation in malignant glioma tissues involves an abnormality in porphyrin-heme metabolism, specifically decreased ferrochelatase enzyme activity. During resection surgery, the macroscopic fluorescence of PpIX to the naked eye is more sensitive than magnetic resonance imaging, and the alert real time spectrum of PpIX is the most sensitive method. In the future, chemotherapy with new anticancer agents, immunotherapy, and new methods of radiotherapy and gene therapy will be developed; however, ALA will play a key role in malignant glioma treatment before the development of these new treatments. In this paper, we provide an overview and present the results of our clinical research on ALA-PDD. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Academic Editor: Yantian Zhang |
ISSN: | 1687-4188 1687-4196 |
DOI: | 10.1155/2016/6135293 |