Author: Kolbein K. KolstePublisher:
ISBN:
Category :
Languages : en
Pages : 262
Book Description
In neurosurgical tumor resection, the current standard protocol is to use pre-operative MR image combined with tracking equipment to provide a map for intraoperative guidance. This technology has improved surgical outcomes, but is limited by deformation of the brain during the surgery. A potential supplement to image-guidance is fluorescence-guidance. To date, ALA is being researched as a technique to guide tumor resection by inducing the accumulation of the endogenous fluorophor PpIX. Most research has focused on the use of blue light excitation of PpIX to visual the tumor. However, due to the high attenuation of blue light by in vivo chromophores, such as oxy- and deoxy- hemoglobin, the source of collected fluorescence emissions is confined to the top layer of cells, and the signal is subject to masking by blood on the surface of the surgical field of view. This issue is particularly a problem at the end of the resection, when the surgeon is evaluating the margin for remaining tumor, but the blue-signal is insensitive to residual tumor that may be located several millimeters beneath the surface. PpIX has an absorption band in the near infrared (NIR), where the absorption due to blood is orders of magnitude lower, enabling the excitation of a fluorophore at depth. In this work, we created a hyperspectral imaging system that attaches to a neurosurgical microscope and is capable of detecting PpIX fluorescence that has been excited at 635 nm. We utilize a dual-waveband technique from the hyperspectral to estimate depth of fluorescence origin and characterize the inherent limitations of the estimated depth. One of the major benefits of this technique is that the estimation is independent of the concentration and size of the fluorophore. This is first demonstrated in phantom studies, where the depths of multiple separate inclusions at various depths are accurately estimated. The technique is verified in animal tumor models and translated into the clinical theater, with pilot data showing the first estimation of depth of subsurface tumors during intracranial tumor resection.