In the lung, acinic cell carcinoma (ACC) is a rare form of tumor. Reported herein is a unique bronchial gland-type tumor diagnosed as well-differentiated ACC that developed in the B9 bronchus of the left lung. Various immunohistochemical and histochemical staining partly satisfied the diagnosis of ACC. Moreover, this tumor contained various sizes of mucous cysts lined by columnar mucous cells, which produced abundant mucin positive for Alcian blue, which is usually present in mucoepidermoid carcinoma. Therefore, the present case is a unique tumor having a broad spectrum of cell differentiation from the terminal duct--acinar unit to the striated duct and excretory duct. This is the first case of unique bronchial gland-type tumor with mixed histological features of ACC and mucoepidermoid carcinoma.
To re-evaluate adenocarcinoma, mixed subtypes (ADMIX) of the lung, a total of 201 cases were classified into three main subgroups according to the most differentiated histological growth pattern; namely bronchioloalveolar carcinoma (BAC)-mixed, which was the most predominant (73.1%), papillary (PAP)-mixed (21.9%), and acinar-mixed (5%). The PAP-mixed was significantly male predominant and had more progressed clinicopathological features. A significant cytological difference was observed among the three subgroups. A tissue microarray was constructed and immunohistochemistry was undertaken using 15 biomarkers. Hierarchical clustering analysis was separately applied to the immunohistochemical results of ADMIX and ADMIX subgroups, and it was found that most acinar-mixed cases were placed in a separate cluster, while the BAC-mixed and PAPmixed failed to form significant independent clusters. The antibody clustering profile for the acinar-mixed was clearly different from that for the BAC-mixed or PAP-mixed, but the PAP-mixed shared a dendrogram profile with the other two subgroups. Statistically, approximately half of the 15 biomarkers were significant for differentiating between ADMIX subgroups and between different histological growth patterns. In conclusion, ADMIX can be classified into three histopathological subgroups according to the most differentiated growth pattern, of which a PAP growth pattern might indicate more aggressive behavior than that of a BAC growth pattern.
Background: Digital breast tomosynthesis (DBT) now become one of the available diagnostic imaging modalities of the breast, and the present study was done to evaluate its diagnostic value versus that of breast ultrasound (US) in the evaluation of breast asymmetries. This study included 51 patients with 57 mammography identified breast asymmetries; their ages were ranged from 26 to 72 years (mean age 50.05 ± 8.1 SD). For all patients, both digital breast tomosynthesis and ultrasound were done, and their results were compared. Results: Tomosynthesis in this study showed better diagnostic performance compared to mammography; the sensitivity of tomosynthesis was 83.33%, the specificity was 89.74%, the positive predictive value was 78.95%, the negative predictive value was 92.11%, and the accuracy was 87.71% while the sensitivity of mammography was 72.22%, the specificity was 71.79%, the positive predictive value was 54.17%, the negative predictive value was 84.85 %, and the accuracy was 71.92 %. Breast ultrasound showed the highest sensitivity in this study with the sensitivity of ultrasound being 100.00 %, the specificity being 92.31%, the positive predictive value being 85.71%, the negative predictive value being 100.00%, and the accuracy being 94.73%. Conclusion: Tomosynthesis enables better depiction of asymmetries. It can be useful in the screening setting where better lesion detection and accurate description of lesions is desired. Therefore, it can detect more cancers and can reduce the number of biopsies. Breast ultrasound should be coupled with breast mammography and 3D tomosynthesis in the evaluation of the breast asymmetries as it reduces false-negative results, detects solid and cystic lesions, and assesses solid lesion nature.
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