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Interoperative Molecular Imaging with No Label
Thursday, October 11, 2012
3:30 pm - 5:00 pm
3:30 pm - 5:00 pm
Location: BME 3.204
Seminar Abstract
Real-time microscopic visualization of morphological patterns and molecular signatures of tissues at the cellular level could, ideally, replace tissue extraction biopsy and open up many new vistas for instant diagnosis and intra-operative intervention. At the very least, this capability could improve tissue selection for biopsy and increase diagnostic accuracy. Coupled with intra-operative or image-guided navigation, the in vivo microscopy technique could also allow early detection of cancer, identify surgical margins, and improve surgical outcomes. Nevertheless, existing molecular imaging techniques are limited by low biochemical specificity and by the admittance of exogeneous contrast agents or imaging probes for clinical practice.
Label-free approaches to in vivo microscopy provide an alternate route of molecular imaging that would sidestep the contrast agent issues and shorten the time translating research into clinics. Among label-free approaches, coherent anti-Stokes Raman scattering (CARS) microscopy has gained much attention as it provides high spatial resolution images with good intrinsic contrast and high chemical specificity. Chemical spectra of CARS capture molecular signatures of tissues based on its intrinsic chemical compositions and can be used to form distinct spectra or spectrum-based images. With the proper miniaturization of CARS into a flexible endoscope by using an optical fiber interface, the label-free technology will have the potential to transform surgical practice while enabling early detection and diagnosis of cancer and other diseases.
In this talk, we present our work on the development of full fiber-based CARS imaging and spectroscopy endoscopes, coupled with automated classifiers in order to discriminate tissue molecular signatures and morphological structures at microscopic resolution in vivo. This discrimination will be valuable in differentiating cancer, establishing tumor margins, and nerve-sparing surgery. CARS spectra and images will be captured to obtain the intrinsic molecular information and cellular morphology of tissues, which will be used to develop a real-time decision support system for cancer differentiation.
Speaker Biographical Information
Real-time microscopic visualization of morphological patterns and molecular signatures of tissues at the cellular level could, ideally, replace tissue extraction biopsy and open up many new vistas for instant diagnosis and intra-operative intervention. At the very least, this capability could improve tissue selection for biopsy and increase diagnostic accuracy. Coupled with intra-operative or image-guided navigation, the in vivo microscopy technique could also allow early detection of cancer, identify surgical margins, and improve surgical outcomes. Nevertheless, existing molecular imaging techniques are limited by low biochemical specificity and by the admittance of exogeneous contrast agents or imaging probes for clinical practice.
Label-free approaches to in vivo microscopy provide an alternate route of molecular imaging that would sidestep the contrast agent issues and shorten the time translating research into clinics. Among label-free approaches, coherent anti-Stokes Raman scattering (CARS) microscopy has gained much attention as it provides high spatial resolution images with good intrinsic contrast and high chemical specificity. Chemical spectra of CARS capture molecular signatures of tissues based on its intrinsic chemical compositions and can be used to form distinct spectra or spectrum-based images. With the proper miniaturization of CARS into a flexible endoscope by using an optical fiber interface, the label-free technology will have the potential to transform surgical practice while enabling early detection and diagnosis of cancer and other diseases.
In this talk, we present our work on the development of full fiber-based CARS imaging and spectroscopy endoscopes, coupled with automated classifiers in order to discriminate tissue molecular signatures and morphological structures at microscopic resolution in vivo. This discrimination will be valuable in differentiating cancer, establishing tumor margins, and nerve-sparing surgery. CARS spectra and images will be captured to obtain the intrinsic molecular information and cellular morphology of tissues, which will be used to develop a real-time decision support system for cancer differentiation.
Speaker Biographical Information
