The results obtained during the project deal with the testing of different quantitative analysis parameters on images acquired with far-field techniques which were further applied on images acquired with near-field imaging methods. We have also assessed the influence of image acquisition parameters on the quality of fitting PSHG image datasets with theoretical models and proposed the efficiency of fitting as a new parameter which can be taken into account when estimating the collagen model to be used.
1. We have tested an extended set of quantitative analysis parameters including the following: parameters directly related to the gray level distribution of pixel intensities extracted from the 2D SHG images (mean, standard deviation, skewness and kurtosis) were calculated using the histogram; a second set of parameters derived from the gray level co-occurrence matrix (GLCM) method which provides information on the spatial relationships between pixels intensities in a given image; fractal dimension and lacunarity from fractal analysis; Helmholtz analysis for collagen orientation distribution in SHG images. By combining SHG microscopy with quantification parameters for image texture analysis applied on the collagenous capsule surrounding the thyroid gland, follicular adenoma (FA) and papillary thyroid carcinoma (PTC) nodules, we have proven for the first time to our knowledge that the collagen distribution in the thyroid nodule capsules can be used to differentiate between benign and encapsulated malignant thyroid nodules. Our quantitative results are consistent with the observed changes in collagen fibers organization and indicate randomly organized collagen fibers in benign nodule capsules and an organized PTC capsule with fibers aligned parallel with the malignant nodule. We hypothesize that this behavior might be interpreted as a defense mechanism against malignant tumors, since it was previously observed that aligned collagen fibers with the angle relative to the tumor boundary distributed around 90° promote invasion.
2. The same parameters as those mentioned above were applied in the case of areas of the collagen nodule capsule close to an invasion area. We were able to detect changes in the collagen structure which can be linked with an imminent invasion of the capsule. This result can be used for screening thyroid nodules to detect areas where the capsule might present changes suggesting a malignant nodule. Thyroid pathologies of interest would be noninvasive follicular thyroid neoplasm with papillary-like nuclear features vs. encapsulated papillary carcinoma with capsular invasion or follicular adenoma vs. follicular carcinoma with capsular invasion where the differential diagnosis between malignant and benign is placed only when an invasion area is located, which might be a troublesome task.
3. We have proposed a image acquisition protocol regarding both image acquisition parameters and also post-processing steps. The protocol gives the best results in terms of quality of the fitting procedure of PSHG datasets with collagen theoretical models. We also defined fitting efficiency procedure and obtained different values for different skin tissue layers. These results suggest that fitting efficiency might represent an important parameter that can be used to distinguish between different pathologies that involve modifications in the collagen architecture.
4. PSHG imaging was applied on Silicon Carbide (SiC) samples with a high number of defects or different inclusions. PSHG image datasets were fitted with theoretical cubic and hexagonal polytypes theoretical models resulting in polytype-maps with pixel resolution.