May 2007
Volume 48, Issue 13
Free
ARVO Annual Meeting Abstract  |   May 2007
Quantitative Imaging of Eye Tumor in the Mouse Model of Retinoblastoma With Spectral-Domain Optical Coherence Tomography
Author Affiliations & Notes
  • S. Jiao
    Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida
  • M. Ruggeri
    Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida
  • H. Wehbe
    Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida
  • G. Gregory
    Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida
  • M. E. Jockovich
    Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida
  • C. A. Puliafito
    Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida
  • T. G. Murray
    Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida
  • Footnotes
    Commercial Relationships S. Jiao, None; M. Ruggeri, None; H. Wehbe, None; G. Gregory, None; M.E. Jockovich, None; C.A. Puliafito, Carl Zeiss Meditec, P; T.G. Murray, None.
  • Footnotes
    Support NIH Grant EY013629 and an unrestricted grant to the University of Miami from Research to Prevent Blindness
Investigative Ophthalmology & Visual Science May 2007, Vol.48, 1588. doi:https://doi.org/
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    • Get Citation

      S. Jiao, M. Ruggeri, H. Wehbe, G. Gregory, M. E. Jockovich, C. A. Puliafito, T. G. Murray; Quantitative Imaging of Eye Tumor in the Mouse Model of Retinoblastoma With Spectral-Domain Optical Coherence Tomography. Invest. Ophthalmol. Vis. Sci. 2007;48(13):1588. doi: https://doi.org/.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose:: To demonstrate the application of high resolution spectral-domain optical coherence tomography in imaging and quantitative information extraction of the tumor volume in the mouse model of retinoblastoma.

Methods:: A high-resolution spectral-domain OCT system with a depth resolution of ~3µm in tissue was built for non-invasive non-contact in vivo imaging of the retina of mouse model of ocular diseases. The system is able to acquire high quality 3D images of the rodent retina in 2.7 seconds (total operation time is ~5 minutes). A 6-axis animal restraint and alignment system was built for the precise positioning of the animals. The system allows imaging the rodent eyes in short time, which is promising for high throughput applications. The system was tested on B6/SJLF2 (normal retina) and LHBETATAG (mouse model for retinoblastoma) mice. 3D segmentation was accomplished by outlining the boundaries of the tumor in each OCT B-scan images. From the segmented images the tumor volume can be calculated.

Results:: High quality OCT images were acquired with our OCT system for both normal mice and mouse model of retinal diseases. The OCT images compared well with the corresponding histology. For the normal mice all the anatomical layers of the retina can be clearly recognized. For the first time to our knowledge, 3D image of the tumor in the retinoblastoma mouse model was successfully imaged in vivo. The tumor can be recognized in the OCT image as a high backscattering region and the location is in the inner nuclear layer, which can be shown more clearly in the 3D display. Quantitative information like the tumor volume was extracted with the voxel count method applied to the segmented OCT images acquired on the LHBETATAG mouse model.

Conclusions:: The results presented in this study demonstrated the capability of our OCT system to image the retinal structures for both normal and diseased rodent eyes. The acquired OCT images have excellent correlation with histology. Our OCT system accomplished the goal of non-invasive non-contact in vivo imaging of the rodent retina with high image quality and short examination time. Noninvasive in vivo examination of the rodent retina without sacrificing the animal is the key to being able to perform longitudinal studies. This allows the monitoring of disease progression and the response to therapies through its entire course in individual animal.

Keywords: imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound) • image processing • tumors 
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