Comparison of Near-Infrared Imaging Camera Systems for Intracranial Tumor Detection
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Distinguishing neoplasm from normal brain parenchyma intraoperatively is critical for the neurosurgeon. 5-Aminolevulinic acid (5-ALA) has been shown to improve gross total resection and progression-free survival but has limited availability in the USA. Near-infrared (NIR) fluorescence has advantages over visible light fluorescence with greater tissue penetration and reduced background fluorescence. In order to prepare for the increasing number of NIR fluorophores that may be used in molecular imaging trials, we chose to compare a state-of-the-art, neurosurgical microscope (System 1) to one of the commercially available NIR visualization platforms (System 2).
Serial dilutions of indocyanine green (ICG) were imaged with both systems in the same environment. Each system’s sensitivity and dynamic range for NIR fluorescence were documented and analyzed. In addition, brain tumors from six patients were imaged with both systems and analyzed.
In vitro, System 2 demonstrated greater ICG sensitivity and detection range (System 1 1.5–251 μg/l versus System 2 0.99–503 μg/l). Similarly, in vivo, System 2 demonstrated signal-to-background ratio (SBR) of 2.6 ± 0.63 before dura opening, 5.0 ± 1.7 after dura opening, and 6.1 ± 1.9 after tumor exposure. In contrast, System 1 could not easily detect ICG fluorescence prior to dura opening with SBR of 1.2 ± 0.15. After the dura was reflected, SBR increased to 1.4 ± 0.19 and upon exposure of the tumor SBR increased to 1.8 ± 0.26.
Dedicated NIR imaging platforms can outperform conventional microscopes in intraoperative NIR detection. Future microscopes with improved NIR detection capabilities could enhance the use of NIR fluorescence to detect neoplasm and improve patient outcome.
Key wordsBrain tumor Comparison Fluorescence Imaging Near-infrared
Thank you to Jun Jeon, a medical student at the Perelman School of Medicine, for helping with the Figures.
Compliance with Ethical Standards
This work was partially supported by the National Institutes of Health R01 CA193556 (SS) and the Institute for Translational Medicine and Therapeutics of the Perelman School of Medicine at the University of Pennsylvania (JYKL). In addition, research reported in this publication was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number UL1TR000003 (JKYL). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
Conflict of Interest
JYKL owns stock options in VisionSense™. SS holds patent rights over technologies presented in this manuscript.
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