In Vivo Quantitative Microvasculature Phenotype Imaging of Healthy and Malignant Tissues Using a Fiber-Optic Confocal Laser Microprobe1

Real-time in vivo imaging of the microvasculature may help both earlier clinical detection of disease and the understanding of tumor-host interaction at various stages of progression. In vivo confocal and multiphoton microscopy is often hampered by bulky optics setup and has limited access to intern...

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Published inTranslational oncology Vol. 1; no. 2; pp. 84 - 94
Main Authors Lin, Ken Young, Maricevich, Marco, Bardeesy, Nabeel, Weissleder, Ralph, Mahmood, Umar
Format Journal Article
LanguageEnglish
Published Neoplasia Press Inc 01.07.2008
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Abstract Real-time in vivo imaging of the microvasculature may help both earlier clinical detection of disease and the understanding of tumor-host interaction at various stages of progression. In vivo confocal and multiphoton microscopy is often hampered by bulky optics setup and has limited access to internal organs. A fiber-optic setup avoids these limitations and offers great user maneuverability. We report here the in vivo validation of a fiber-optic confocal fluorescence microprobe imaging system. In addition, we developed an automated fractal-based image analysis to characterize microvascular morphology based on vessel diameter distribution, density, volume fraction, and fractal dimension from real-time data. The system is optimized for use in the far-red and near-infrared region. The flexible 1.5-mm-diameter fiber-optic bundle and microprobe enable great user maneuverability, with a field of view of 423 x 423 µ m and a tissue penetration of up to 15 µ m. Lateral and axial resolutions are 3.5 and 15 µ m. We show that it is possible to obtain high temporal and spatial resolution images of virtually any abdominal viscera in situ using a far-red blood pool imaging probe. Using an orthotopic model of pancreatic ductal adenocarcinoma, we characterized the tumor surface capillary and demonstrated that the imaging system and analysis can quantitatively differentiate between the normal and tumor surface capillary. This clinically approved fiber-optic system, together with the fractal-based image analysis, can potentially be applied to characterize other tumors in vivo and may be a valuable tool to facilitate their clinical evaluation.
AbstractList Real-time in vivo imaging of the microvasculature may help both earlier clinical detection of disease and the understanding of tumor-host interaction at various stages of progression. In vivo confocal and multiphoton microscopy is often hampered by bulky optics setup and has limited access to internal organs. A fiber-optic setup avoids these limitations and offers great user maneuverability. We report here the in vivo validation of a fiber-optic confocal fluorescence microprobe imaging system. In addition, we developed an automated fractal-based image analysis to characterize microvascular morphology based on vessel diameter distribution, density, volume fraction, and fractal dimension from real-time data. The system is optimized for use in the far-red and near-infrared region. The flexible 1.5-mm-diameter fiber-optic bundle and microprobe enable great user maneuverability, with a field of view of 423 x 423 µ m and a tissue penetration of up to 15 µ m. Lateral and axial resolutions are 3.5 and 15 µ m. We show that it is possible to obtain high temporal and spatial resolution images of virtually any abdominal viscera in situ using a far-red blood pool imaging probe. Using an orthotopic model of pancreatic ductal adenocarcinoma, we characterized the tumor surface capillary and demonstrated that the imaging system and analysis can quantitatively differentiate between the normal and tumor surface capillary. This clinically approved fiber-optic system, together with the fractal-based image analysis, can potentially be applied to characterize other tumors in vivo and may be a valuable tool to facilitate their clinical evaluation.
Author Weissleder, Ralph
Bardeesy, Nabeel
Lin, Ken Young
Mahmood, Umar
Maricevich, Marco
AuthorAffiliation Center for Molecular Imaging Research, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
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  surname: Mahmood
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  organization: Center for Molecular Imaging Research, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
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