Fluorescence intensity and bright spot analyses using a confocal microscope for photodynamic diagnosis of brain tumors

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Abstract

Background In photodynamic diagnosis using 5-aminolevulinic acid (5-ALA), discrimination between the tumor and normal tissue is very important for a precise resection. However, it is difficult to distinguish between infiltrating tumor and normal regions in the boundary area. In this study, fluorescent intensity and bright spot analyses using a confocal microscope is proposed for the precise discrimination between infiltrating tumor and normal regions. Methods From the 5-ALA-resected brain tumor tissue, the red fluorescent and marginal regions were sliced for observation under a confocal microscope. Hematoxylin and eosin (H&E) staining were performed on serial slices of the same tissue. According to the pathological inspection of the H&E slides, the tumor and infiltrating and normal regions on confocal microscopy images were investigated. From the fluorescent intensity of the image pixels, a histogram of pixel number with the same fluorescent intensity was obtained. The fluorescent bright spot sizes and total number were compared between the marginal and normal regions. Results The fluorescence intensity distribution and average intensity in the tumor were different from those in the normal region. The probability of a difference from the dark enhanced the difference between the tumor and the normal region. The bright spot size and number in the infiltrating tumor were different from those in the normal region. Conclusions Fluorescence intensity analysis is useful to distinguish a tumor region, and a bright spot analysis is useful to distinguish between infiltrating tumor and normal regions. These methods will be important for the precise resection or photodynamic therapy of brain tumors. © 2016 Elsevier B.V.

Embargo Period 12 months

Journal

  • Photodiagnosis and Photodynamic Therapy

    Photodiagnosis and Photodynamic Therapy (17), 13-21, 2017-03-01

    Elsevier B.V.

Codes

  • NII Article ID (NAID)
    120005973607
  • NII NACSIS-CAT ID (NCID)
    AA11969923
  • Text Lang
    ENG
  • Article Type
    journal article
  • ISSN
    1572-1000
  • Data Source
    IR 
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