Differentiating Between Malignant Mesothelioma and Other Pleural Lesions Using Fourier Transform Infrared Spectroscopy.

Histopathology, despite being the gold standard as a diagnostic tool, does not always provide a correct diagnosis for different pleural lesions. Although great progress was made in this field, the problem to differentiate between reactive and malignant pleural lesions still stimulates the search for additional diagnostic tools. Our research using vibrational spectroscopy and principal component analysis (PCA) statistical modeling represents a potentially useful tool to approach the problem. The objective method this paper explores is based on the correlation between different types of pleural lesions and their vibrational spectra. Obtained tissue spectra recorded by infrared spectroscopy allowed us to categorize spectra in different groups using a created PCA statistical model. The PCA model was built using tissues of known pathology as the model group. The validation samples were then used to confirm the functionality of our PCA model. Student's t-test was also used for comparing samples in paired groups. The PCA model was able to clearly differentiate the spectra of mesothelioma, metastasis and reactive changes (inflammation), and place them in discrete groups. Thus, we showed that Fourier transform infrared spectroscopy combined with PCA can differentiate pleural lesions with high sensitivity and specificity. This new approach could contribute in objectively differentiating specific pleural lesions, thus helping pathologists to better diagnose difficult pleural samples but also could shed additional light into the biology of malignant pleural mesothelioma.

Divergent immunohistochemical expression of CD21 and CD23 by follicular dendritic cells with increasing grade of follicular lymphoma.

BACKGROUND: Ultrastructural and immunohistochemical differences have been described in FDCs of primary and secondary follicles, illustrating the highly compartmentalized structure of lymph follicles. Differences in FDC immunophenotype in different grades of FL may reflect some parallelism between reactive and neoplastic conditions in terms of FDC-B cell interaction and may be used as a valuable additional tool for grading FL. METHODS: A total of 60 paraffin blocks from patients with follicular lymphoma, 30 cases each of grade 1 and 3, were retrieved from our archive. Immunohistochemical analysis was carried out for CD21, CD23, cyclin A, and Ki-67. RESULTS: Our study demonstrates that during evaluation, six patterns of FDC distribution were distinguished. The intensity of stain for CD21 was not statistically significant in grade 1 and grade 3 FL (p = 0.340). In contrast, grade 3 FLs exhibited a significant decrease of CD23 expression by the FDCs (p < 0.001). By CD21 stain, there was no significant difference in the distribution of pattern 1 in grades 1 and 3 (p = 0.098). In contrast, in grade 3, this pattern was significantly less observed by CD23 stain (p = 0.016). The same was observed for pattern 2 for CD21 (p = 0.940) and CD23 (p = 0.010) and pattern 4 for CD21 (p = 0.305) and CD23 (p = 0.005), respectively. Distribution of pattern 5 was significantly different between grades 1 and 3 both for CD21 (p = 0.005) and CD23 (p < 0.001). Distribution of patterns 2 and 6 was not significantly different between grades 1 and 3 for CD21 and CD23. The values of cyclin A and Mib-1 were also significantly different between grades 1 and 3 (p < 0.001). CONCLUSIONS: The observed patterns of FDCs lead us to believe that similar to reactive lymph node follicles, neoplastic follicles in FL, at least in early stages, have an organized structure. Hypothetically, with CD21, CD23, and cyclin A immunohistochemistry, the sequence of events in FL progression may be traced.