An integrated diagnosis and therapeutic system using intra-operative 5-aminolevulinic-acid-induced fluorescence guided robotic laser ablation for precision neurosurgery

Hongen Liao*, Masafumi Noguchi, Takashi Maruyama, Yoshihiro Muragaki, Etsuko Kobayashi, Hiroshi Iseki, Ichiro Sakuma

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

55 Citations (Scopus)

Abstract

We have developed an integrated diagnosis and therapeutic system for precision malignant gliomas resection during neurosurgery. A combination of three-dimensional (3-D) magnetic resonance imaging (MRI) navigation and 5-aminolevulinic acid (5-ALA)-induced fluorescence based intra-operative tumor diagnosis technique has been incorporated into a robotic laser ablation neurosurgery system with an automatic focusing and robotic scanning mechanism. 5-ALA is a non-fluorescent prodrug that leads to intracellular accumulation of fluorescent protoporphyrins IX (PpIX) in malignant glioma. The PpIX tends to accumulate in pathological lesions, and emits red fluorescence when excited by blue light. This fluorescence is illuminated with laser excitation, enables intra-operative identification of the position of a tumor and provides guidance for resection with laser photocoagulation. The information provided by the MRI is enhanced by the intra-operative 5-ALA fluorescence data, and this enhanced information is integrated into a robotic laser ablation system. The accuracy of the fluorescent measurement of the tumor is improved using high-precision spectral analysis. The fluorescence assists in the detection of malignant brain tumors intra-operatively and improves their removal rate.

Original languageEnglish
Pages (from-to)754-766
Number of pages13
JournalMedical Image Analysis
Volume16
Issue number3
DOIs
Publication statusPublished - 2012 Apr
Externally publishedYes

Keywords

  • 5-Aminolevulinic-acid
  • Fluorescence
  • Integrated diagnosis and therapeutic system
  • Medical robotics
  • Neurosurgery

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Graphics and Computer-Aided Design

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