We developed a miniaturized high-resolution low-cost reflectance-mode fiber microscope (RFM) aimed at optical tissue biopsy applications using a polarized imaging configuration to suppress background noise from specular reflectance. The RFM is equipped with an air-cooled light-emitting-diode illumination module and a single 450-µm outer-diameter fiber bundle image guide compatible with a 20-gauge needle. The dual illumination and image acquisition nature of the fiber bundle simplifies the system and reduces the total cost. Imaging tests with a United States Air Force resolution target demonstrate a lateral resolution of ~3.5 µm. The performance of the imaging system is evaluated by examining samples of cells and excised human tissue. Still and video rate images are obtainable in reflectance mode using intrinsic contrast.
We have analyzed infrared spectra of microtome sections of frozen cervical tissues from the malignant (cancer) and normal histopathological groups. Intensity ratios of the different bands throughout the fingerprint region in the mid-IR are compared for the above groups. The bands are evaluated to show that the peak absorbances for the different groups exhibit statistically significant differences. Among the significant changes observed is the increase in the peak intensity of the 1400 cm-1 band of the normal tissue group. Also, the contribution of the 1240 cm-1 band which is *due to the phosphatediester group of nucleic acids was greater for the malignant tissue group compared to normal tissues. Partial-Least Squares (PLS) factors are used to further analyze the tissues to access the more subtle differences between the cancer and normal groups and to help determine the spectral bands that are most useful for cancer diagnosis. Also, we utilized Linear Discriminant Analysis (LDA) as well as the supervised learning method of Support Vector Machines
(SVM) to study our tissue samples and develop diagnostic algorithms. PLS was used to decompose the spectra to reduce
the spectral variables. The PLS components were then used as variables in SVM procedures to construct algorithms that
produce specificity and sensitivity values greater than 90%.
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