Unlike the standard OCT setups (Huang et al., 1991
; Fercher et al., 2003
), our OCT system adapted polarization diversity detection for polarization-insensitive measurement. Brain white matter contains tracts of parallel nerve fibers that are highly birefringent (Ducros et al., 2001
). Birefringent tissue changes the polarization of the transmitted light. In a standard OCT setup that detects only one polarization channel, highly birefringent tissue typically appears as alternating bright and dark layers. The tissue appears dark when the polarization is mismatched and bright when it is matched. Our OCT system detects both polarization channels and adds the optical intensity in the two channels. This allows the system to detect the total reflected optical signal and measure signal attenuation characteristics of different tissues without interference from polarization shifts.
Our OCT images were highly correlated with the histological images, and different tissue optical characteristics were evident. White matter is brighter at the surface than gray matter because it has a higher degree of scattering. The increased scattering in white matter is presumably due to myelination. Scattering causes attenuation of signal with depth. As expected, signal attenuation is also more rapid in white matters. Taken together (), the signal strength and attenuation characteristic allows perfect differentiation of the white and gray matter tissue we studied.
Specific gray and white matter regions in the brain also exhibited differences in optical characteristics. The white matter of the optic tract showed a higher reflectance and scattering than the white matter in the capsule regions. The difference is probably caused by the degree of myelination (Hamano et al., 1998
). We can distinguish the S1BF from the hippocampus by the mean value of attenuation coefficient. However, the standard deviation of attenuation coefficient in the hippocampus is relatively large due to one outlier in the hippocampus data cluster. This might be due to the inclusion of the field CA2(3) of hippocampus, which is clear in the histological sections. The field CA2(3) has a denser cellular structure (stratum pyramidale) than the rest of hippocampus; thus, it should have different optical properties than the remainder of the hippocampus.
The range of tissue distinction using OCT is limited by the “single scattering” regime. Light reflected from deeper layers is overwhelmed by multiple scattered light from more superficial layers that is detected by OCT as having the same delay. Only single scattered light carries information on the local tissue property. The depth at which multiple scattering becomes dominant can be seen on the OCDR A-scan where attenuation slows down and deviates from log linearity. This depth defines the penetration range of our OCT system. The average penetration range in gray matter is 0.77 mm and that of white matter is 0.31 mm. The penetration range from nine different ROIs in gray matter is from 1.2 to 0.4 mm, and the range in white matter is varied from 0.5 to 0.2 mm.
The detection of different cellular layers in the same tissue type indicates potential for precise positioning of the DBS probe during surgery. More consistent and accurate measurement can be achieved by increasing the spatial averaging sample number, which is also an effective way to suppress speckles noise (Schmitt et al., 1994
). One potential application of this technology would be to replace or complement current microelectrode recording techniques. The size of the probe should be the same as or smaller than currently used microelectrodes, which are typically 0.5–1.0 mm in the diameter. OCDR is best suited for DBS lead placement since OCT systems require scanning hardware, which is difficult to build within a 1-mm space. With OCDR there is no transverse scanning, and the information on tissue texture (transverse variation) that is apparent on OCT images is lost. OCDR does capture signal strength and variation in depth. Our in vitro OCT data suggest that this depth variation alone is sufficient for distinguishing tissue types. In the next step, we will measure brain tissue in vivo using an OCDR probe that is integrated into a brain probe. We aim to find similar contrast between brain tissue types even though we expect the absolute signal amplitude and attenuation rate to differ due to differences between in vivo and in vitro tissue characteristics. In addition, the optical setup will be different.
The use of optical properties to differentiate among tissues during DBS has been explored by others. Johns et al. (1998)
and Qian et al. (2003)
utilized diffuse reflectance spectroscopy to differentiate gray and white matter and to assist during neurosurgery. They found that gray matter, white matter, and crebrospinal fluid within the brain scatter light quite distinctively. Optical spatial profiles and the actual anatomical profiles based on the postoperative MRI images showed good correlation from their previous study (Giller et al., 2000
The advantage of OCDR/OCT over spectroscopy is the ability to resolve signals over a range of depths. In spectroscopy and other summed reflectivity measurements, the measured signal comes predominantly from tissue immediately ahead of the probe. OCDR/OCT adds range to the measurement by resolving the tissue optical property as a function of depth up to the limit where multiple scattering predominates. Within this range, it is possible to detect tissue type and tissue boundaries with OCDR/OCT. Thus, OCDR/OCT provides the ability to look ahead, measure the distance to the next tissue boundary, and determine the type of tissue in the next deeper layer.
OCDR brain probe will also be able to detect blood vessels. Flow induces Doppler shift in OCT and OCDR signals. Doppler OCT has been successfully used to visualize blood vessels within various tissue types and measure blood flow dynamics (Chen et al., 1998
; Rollins et al., 2002
). With the addition of Doppler capability to the OCDR brain probe, large blood vessels ahead of the probe can be visualized and avoided, thus reducing the risk of hemorrhages during probe insertion.
In summary, we showed that the tissue classification essential for neurosurgical treatments is possible using optical properties. OCT images were highly correlated with histology images, and quantitative analysis based on signal attenuation and maximum intensity confirmed clear tissue classification among different tissue type. This supports the feasibility for using OCT or OCDR in guiding the insertion of DBS probes.