Topographic mapping of subsurface fluorescent structures in tissue using multiwavelength excitation

Abstract

Abstract. Different colors of visible light penetrate to varying depths in tissue due to the wavelength dependence of tissue optical absorption and elastic scattering. We exploit this to map the contour of the closest surface of a buried fluorescent object. This uses a novel algorithm based on the diffusion theory description of light propagation in tissue at each excitation wavelength to derive metrics that define the depth of the top surface of the object. The algorithm was validated using a tissue-simulating phantom. It was then demonstrated in vivo by subsurface brain tumor topography in a rodent model, using the fluorescence signal from protoporphyrin IX that is preferentially synthesized within malignant cells following systemic application of aminolevulinic acid. Comparisons to histomorphometry in the brain post mortem show the spatial accuracy of the technique. This method has potential for fluorescence image-guided tumor surgery, as well as other biomedical and nonbiological applications in subsurface sensing. C 2010 Society of PhotoOptical Instrumentation Engineers.

Fluorescence Optical Tomography of Preclinical Glioma Models Using Spatial Frequency Domain Imaging

“…Future studies will provide more detailed insight into factors that limit SFDI accuracy and performance, and explore the combination of image guidance with probe-based methods. 6,8,9 …”

“…Fortunately, the excitation spectrum of PpIX also possesses several longer wavelength excitation bands up to around λ ∼ 633 nm (Q-bands) and a broad emission spectrum extending up to ∼720 nm that could be used to stimulate (and detect) emissions from subsurface tumor. Despite the potential benefits during surgery, efforts to detect fluorescence at depth using model-based techniques are still in an early stage of development with promising preliminary results reported by Kim et al 8 and Leblond et al 9 Spatial frequency domain imaging (SFDI) is a relatively new method that uses red or near-infrared light together with CCD detection to acquire wide-field images of tissue. Sinusoidal patterns of varying spatial frequencies are projected onto tissue, and the attenuation in the amplitude of the spatial patterns at each CCD pixel is fitted to a model of light propagation in order to form images of the tissue optical properties.…”

Widefield quantitative multiplex surface enhanced Raman scattering imagingin vivo

“…Since light attenuation in tissue varies with wavelength, increasing depth in tissue causes ambiguity: e.g., the signal from S481 measured at 864 nm could be 5% lower than that from S421 measured at 896 nm as a result of a 5% difference in NP concentration or to a 5% change in light attenuation. Hence, it becomes necessary to apply an appropriate tissue optical model: this is certainly possible and has been used in fluorescence applications, 28,29 but adds complexity to the instrumentation required and to the image analysis.…”

Macroscopic optical imaging technique for wide-field estimation of fluorescence depth in optically turbid media for application in brain tumor surgical guidance

“…[3][4][5][6][7] Significant improvement in survival has been demonstrated in patients with high-grade glioma, 7,8 even using qualitative visual assessment of the PpIX fluorescence to identify residual tumor after white-light resection, and we have previously reported on preclinical and clinical techniques to quantify the absolute PpIX concentration in the tissue at the time of surgery, using either a point probe spectroscopy technique 6,[9][10][11][12][13][14][15][16] or wide-field quantitative imaging of the tissue surface. 5,[17][18][19][20][21] In this and other clinical applications, the ability to detect fluorescent tumor foci lying significantly below the surface of the surgical cavity could further increase the completeness of tumor resection to impact survival and also improve patient safety by minimizing the need for blind exploratory resection. 8,[22][23][24] This is the focus of the work reported here.…”

“…Initially, multiple excitation wavelengths in the visible range were used, with a common long-wavelength detection band (>635 nm). 21 The effective optical sampling depth (which depends on the wavelength-dependent tissue optical properties) of the fluorophore then primarily depended on the excitation wavelengths. By ordering the resulting fluorescent images according to the increasing penetration depth of the excitation light and applying a threshold value to the signals, a tomographic two-dimensional depth profile was generated that was experimentally shown to represent the top surface of the subsurface fluorophore distribution.…”