Histomorphological Assessment of Formalin versus Nonformalin Fixatives in Diagnostic Surgical Pathology

Introduction Fixation is the critical step in the preservation of tissues in diagnostic pathology. The formalin is an economical and excellent fixative with the inherent property of adequate fixation. The well-established side effects of formalin include mucosal irritation, upper respiratory diseases, and corrosive injury to the gastrointestinal tract. In addition, substantial evidence exists regarding the potential role of formaldehyde as a human carcinogen. The carcinogenic and toxic effects of formalin encourage searching for alternative fixatives for tissue fixation. However, “the formalin dogma” has severely hampered the search for alternative fixatives for many years. Material and Methods Ninety tissues of liver and skeletal muscle obtained during autopsies were immersed in adequate amounts of the following fixatives: formalin (10%), methyl alcohol (70%), and acetone (100%). The comparison among the three was made based on time for fixation, preservation of tissue architecture, cell borders, cytoplasm, nuclear contours, chromatin texture, and uniformity of staining. Results The tissue preserved in formalin undergoes rapid fixation compared with alcohol and acetone. The tissue architecture, cell border characteristics of alcohol and acetone was found satisfactory compared with formalin. The cytoplasm and nuclear contour were superior with the formalin. The chromatin texture and uniformity of staining were similar with all the three fixatives. Conclusion The formalin is considered superior to most of the parameters, whereas both methyl alcohol and acetone showed nearly equivalent scores. Hence, owing to the potential human health hazards and carcinogenicity of formalin, no rational reasons hamper the complete substitution of formalin with alternative fixatives such as alcohol and acetone in diagnostic pathology and medical research.

Differences in Chromatin Texture and Nuclear Fractal Dimension Between Hashimoto's and Lymphocytic Thyroiditis Lymphocytes

Previous evidence suggested that lymphocytic thyroiditis (LT) was a variant of Hashimoto's thyroiditis (HT), thus the aim of the current study is to quantify structural changes in histological specimens taken from HT and LT patients. A total of 600 images containing a single lymphocyte nucleus (300 nuclei per group) were obtained from 20 patients with HT and LT. In order to quantify changes in the nuclear architecture of investigated lymphocytes, the fractal dimension (FD) and some gray-level co-occurrence matrix texture parameters (angular second moment, inverse difference moment, contrast, entropy, and correlation) were calculated for each nucleus. A statistically significant difference in the FD of the “binary-outlined” nucleus and that of the corresponding “black-and-white” nucleus was detected between HT and LT lymphocyte nuclei. In addition, there was also a statistically significant difference in contrast and correlation between HT and LT lymphocyte nuclei. In conclusion, the results of this study suggested that there was a difference in structural complexity between investigated lymphocyte nuclei; additionally, LT lymphocytes possessed probably more complex texture and larger variations as well as more asymmetrical nuclei compared with HT lymphocytes. Accordingly, these findings indicate that LT is probably not a variant of HT; however, more complex studies are necessary to estimate differences between these types of thyroiditis.

Follicular thyroid lesions: is there a discriminatory potential in the computerized nuclear analysis?

Background Computerized image analysis seems to represent a promising diagnostic possibility for thyroid tumors. Our aim was to evaluate the discriminatory diagnostic efficiency of computerized image analysis of cell nuclei from histological materials of follicular tumors. Methods We studied paraffin-embedded materials from 42 follicular adenomas (FA), 47 follicular variants of papillary carcinomas (FVPC) and 20 follicular carcinomas (FC) by the software ImageJ. Based on the nuclear morphometry and chromatin texture, the samples were classified as FA, FC or FVPC using the Classification and Regression Trees method. Results We observed high diagnostic sensitivity and specificity rates (FVPC: 89.4% and 100%; FC: 95.0% and 92.1%; FA: 90.5 and 95.5%, respectively). When the tumors were compared by pairs (FC vs FA, FVPC vs FA), 100% of the cases were classified correctly. Conclusion The computerized image analysis of nuclear features showed to be a useful diagnostic support tool for the histological differentiation between follicular adenomas, follicular variants of papillary carcinomas and follicular carcinomas.