Computer‐assisted analysis of immunohistological parameters in oral giant cell granulomas

Towards better understanding of giant cell granulomas of the oral cavity

Giant cell granulomas are enigmatic lesions of the oral cavity characterised by a peculiar combined proliferation of mononuclear and multinucleated giant cells in a mesenchymal stromal background. Central and peripheral giant cell granulomas may have similar pathogenesis and histology but differ in their location and biological behaviour. It is important to differentiate them from other giant cell lesions that can occur in the oral cavity, such as giant cell tumour of the bone, aneurysmal bone cyst, brown tumour of hyperparathyroidism, and giant cell lesions of Ramon syndrome, Noonan syndrome, neurofibromatosis and Jaffe-Campanacci syndrome. A recent insight into their molecular genetics and pathogenesis, with identification of KRAS, FGFR1 and TRPV4 mutations, allows for better diagnostic differentiation and opens the door to the use of pathway inhibitors in the treatment of recurrent or dysmorphic lesions. In this review, we provide an updated summary of the clinical and pathological features of oral cavity giant cell granulomas that help with their precise diagnosis and management.

Assessment of bisphosphonate treated-osteoblast behaviors by conventional assays and a simple digital image analysis

The main objective of this study was to analyze the changes in osteoblast behaviors by two different methods, a simple digital image analysis method and conventional assays. Osteoblast progenitor cells and osteoblasts were treated with alendronate (ALN; a nitrogen-containing bisphosphonate). Osteoblast behaviors such as the uptake of ALN, cell proliferation, cell differentiation, and mineralized nodule formation were examined. Quantitative assessments were conducted using a publically available ImageJ software along with conventional methods. Furthermore, ImageJ method and conventional assay for mineralized nodule formation were performed simultaneously and were compared in order to demonstrate the reliability of ImageJ analysis. Osteoblast precursors and osteoblasts responded to ALN treatments. The software could identify various colors and allowed for the quantification of staining intensity and area coverage. Both image analysis and conventional assays detected the changes in cell behaviors between treated and untreated samples. For alizarin red S assay, the staining intensity calculated by ImageJ analysis was comparable to the absorbance measured by conventional assay. These findings showed that digital image analysis along with conventional assays could be used for quantitative assessment to evaluate osteoblast alteration by drug treatment. Image analysis method is practical and might be useful for other applications in the field of biology and medical sciences. It could also be employed in a combination with the conventional assays to strengthen the data.