Recently, clinical treatments applying drug delivery system (DDS) have been being developed. However, it is quite difficult to in vivo diagnose spatiotemporal distribution of drug infiltration, so the validation study should be too insufficient to progress the DDS development. In this study, we propose a visualizing assay of DDS, namely 2-Color Optical Coherence Dosigraphy (2C-OCD). 2C-OCD is based on optical coherence tomography using two waveband "2-Color" light sources having different optical absorbance of drug. This can simultaneously provide microscale tomographic images of scatterer density and drug concentration. In order to evaluate the efficacy of this technique, this was applied to drug-diffusion phenomena in microchannel and lipidrich plaques of rabbit with drug administration, respectively. As a result of diffusion experiment, it was confirmed that 2C-OCD can visualize a cross-sectional map of drug concentration, with spatial resolution 5 micro m × 10 μm and accuracy plus-minus 13.0 μM. In ex vivo animal experiment, the enhancement of absorptivity could be observed inside lipidrich plaques, in which DDS drug could be therein uptaken by drug administration.
The absorption maps corresponding to drug concentration were calculated, comparing with their histological images.
Consequently, they had good coincidence with histological examinations, therefore, it was concluded that 2C-OCD could visualize drug infiltration in biological tissue with almost the same spatial resolution as OCT system.
Recently, Fourier-Domain Optical Coherence Tomography (FDOCT), which is a spectral interferometer having
a high speed scanning system, has been improved as 3-dimensional micro imaging technique. This has attracted
the attention of medical scientists as a promising system of early cancer detection. It, however, has been difficult
to quantitatively detect tumor lesion and its malignancy, because interference signals could be dependent on
optical properties of biological tissue. In this study, we propose a tumor detection system based on FDOCT
and oncotropic dye, namely Fourier-Domain Optical Coherence Dosimetry (FDOCD). OCT signals have the
information of absorption by oncotropic dye as well as scattering from tissue, which are separately extracted by
Windowed Inverse FFT corresponding to wavelength bands of interest. Therefore, FDOCD can simultaneously
obtain two optical kinds of tomography, i.e. absorption profile as disease demarcation and scattering profile from
morphologic distribution. In the present report, the calibration experiment was carried out to verify separate
detection of scattering and absorbance. As a result, it indicated that FDOCD could determine the distribution
of scatterer density, eliminating the signal degradation by optical absorption, e.g. drug concentration. It was
suggested that FDOCD could separately and quantitatively monitor scatterer density and drug concentration.
Acute coronary syndromes, e.g. myocardial infarctions, are caused by the rupture of unstable plaques on coronary arteries. The stability of plaque, which depends on biomechanical properties of fibrous cap, should be diagnosed crucially. Recently, Optical Coherence Tomography (OCT) has been developed as a cross-sectional imaging method of microstructural biological tissue with high resolution 1~10 &mgr;m. Multi-functional OCT system has been promising, e.g. an estimator of biomechanical characteristics. It has been, however, difficult to estimate biomechanical characteristics, because OCT images have just speckle patterns by back-scattering light from tissue. In this study, presented is Optical Coherence Straingraphy (OCS) on the basis of OCT system, which can diagnose tissue strain distribution. This is basically composed of Recursive Cross-correlation technique (RC), which can provide a displacement vector distribution with high resolution. Furthermore, Adjacent Cross-correlation Multiplication (ACM) is introduced as a speckle noise reduction method. Multiplying adjacent correlation maps can eliminate anomalies from speckle noise, and then can enhance S/N in the determination of maximum correlation coefficient. Error propagation also can be further prevented by introducing to the recursive algorithm (RC). In addition, the spatial vector interpolation by local least square method is introduced to remove erroneous vectors and smooth the vector distribution. This was numerically applied to compressed elastic heterogeneous tissue samples to carry out the accuracy verifications. Consequently, it was quantitatively confirmed that its accuracy of displacement vectors and strain matrix components could be enhanced, comparing with the conventional method. Therefore, the proposed method was validated by the identification of different elastic objects with having nearly high resolution for that defined by optical system.
In the field of neurosurgery for brain tumor, it is crucially important to remove almost totally certain brain tumors because of patients' quality of life. However, there has been few effective means of determining the boundaries between tumor tissue and surrounding normal brain parenchyma, making tumor resection totally dependent on the experiencing judgment of surgeons. Therefore, it is quite desirable to construct a real-time and highly sensitive monitoring system to detect tumor margins during surgery. In this study, proposed is the novel photo-dynamic diagnosis method for glioma-surgery. Using excited fluorescence from an oncotropic luminophore dye generally used in PDT and auto-fluorescence from some intracellular enzymes, e.g. NADH (Reduced Nicotinamide Adenine Dinucleotide), the ratio-metric technique in two-color laser-induced fluorescence was experimentally applied to brain tumor detection. The experiment was conducted using brain tumor rat models. An oncotoropic fluorescent dye, NPe6 (mono-L-aspartyl chlorin e6), was injected intravenously and then two fluorescence images were taken with irradiation of violet light, The fluorescence intensities of intracellular enzymes and NPe6 were found to decrease and increase in tumor lesions, respectively. Fluorescence intensity ratio could quantitatively identify tumor margins. Undesirable fluorescence variation could be reduced, which was dependent on inhomogeneous irradiation intensity distribution due to brain surface shape and
illuminating light source itself. Thus, the ratio image could achieve higher contrast enhancement in tumor boundaries than single-color PDD. Furthermore, the histological examination provided correlation with ratio-image enhanced area. Consequently, the present method was clarified to be effective to brain tumor monitoring and quantitative tumor boundary demarcation.