Fluorescence Guided Resection and Photodynamic Therapy in Meningiomas

  • Martin Hefti
  • Gord von Campe
Part of the Tumors of the Central Nervous System book series (TCNS, volume 14)


Meningiomas represent 30% of all intracranial neoplasms. They are predominantly slow growing extra axial brain tumours arising from arachnoidal cells and usually have an excellent prognosis if completely removed. However, radical tumour removal near vital functional structures and areas of infiltration is not always possible and histologically “benign” meningiomas may exhibit aggressive behaviour like infiltration and early recurrence. Biological markers that would make areas of infiltration visible by fluorescence might therefore have a significant impact on patient survival and quality of life.

5-Aminolevulinic acid (5-ALA) is a precursor in the cellular heme biosynthesis. The application of exogenous 5-ALA leads to an intracellular accumulation of protoporphyrin IX (PpIX), causing these PpIX saturated cells to become fluorescent and photosensitive under light of an appropriate wavelength. 5-ALA induced PpIX fluorescence has the ability to define infiltration zones into dural structures and bone and mark residual meningioma tissue. It has the potential to facilitate meningioma resection and to individualize the extent of dural resection for each patient in order to prevent morbidity.

Specific intracellular accumulation of PpIX can be used for photodynamic therapy (PDT). Induction of selective apoptosis, reduction of tumour vessel density and no risk of secondary carcinogenesis make PDT an ideal treatment option for meningiomas. Due to the variable potentials for PpIX accumulation within different meningioma subtypes, further research is required to ensure sufficiently intense fluorescence to enable PDT in these cases.


Meningioma Cell Bone Invasion Benign Meningioma Simpson Grade Anaplastic Meningioma 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Department of NeurosurgeryUniversity Hospital of Schleswig HolsteinKielGermany
  2. 2.LKH-Univ. Klinikum GrazUniversitätsklinik für NeurochirurgieGrazAustria

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