scholarly journals An Unusual Salivary Gland Tumor Mimicking Papillary Thyroid Carcinoma: Mammary Analog Secretory Carcinoma

2018 ◽  
Vol 9 ◽  
Author(s):  
Sylvia L. Asa ◽  
Ozgur Mete
2017 ◽  
Vol 26 (5) ◽  
pp. 459-463 ◽  
Author(s):  
Haihui Liao ◽  
Ashraf Khan ◽  
Patricia M. Miron ◽  
Kristine M. Cornejo

Mammary analogue secretory carcinoma (MASC) harboring ETV6 gene rearrangements was first described in the salivary gland with a relatively favorable prognosis and a possible molecular therapeutic target with pan-Trk inhibitors. Recently, primary MASC of the thyroid gland has been reported. We report a case of a 4.0 cm MASC arising from the left thyroid of a 58-year-old female with extrathyroidal extension. Initially, it was diagnosed by fine needle aspiration as suspicious for papillary thyroid carcinoma (PTC) and subsequently called a poorly differentiated carcinoma on resection. A final diagnosis of primary MASC of the thyroid was confirmed after an expanded immunohistochemical panel and identification of an ETV6 gene rearrangement by fluorescence in situ hybridization. Morphologically, the tumor was composed of solid, microcystic and focally papillary growth with dense fibrotic stroma and necrosis. Overlapping cytological features with PTC were identified, including foci of enlarged cells with irregular nuclear membranes/grooves. However, most of the cells contained prominent nucleoli with intraluminal and intracytoplasmic eosinophilic secretions. Immunohistochemically, the tumor cells were strongly positive for pancytokeratin, cytokeratin 7, PAX8, mammaglobin, and GCDFP-15, with rare staining for GATA3 and S100 and negative for TTF-1 and thyroglobulin. We report a rare case of a primary thyroid MASC, initially misdiagnosed as PTC. Pathologists should be aware of this entity and, given the similarities to PTC, have a high index of suspicion, prompting the addition of immunohistochemical and molecular studies. Furthermore, an accurate diagnosis is important because of the possible prognostic and treatment implications.


2019 ◽  
Vol 2019 ◽  
pp. 1-5
Author(s):  
Joseph Mathew ◽  
Michael Carvalho ◽  
Katherine Chorneyko ◽  
Samih Salama

Mammary analogue secretory carcinoma (MASC) is a rare salivary gland tumor analogous to secretory carcinoma of the breast. The diagnosis of MASC can be challenging due to substantial morphologic and immunohistochemical similarities with other salivary gland tumors. The differential diagnosis of MASC is broad and includes intraductal carcinoma, acinic cell carcinoma, and adenocarcinoma, not otherwise specified. Although molecular testing for ETV6 gene rearrangement is characteristic of MASC and has not been shown in any other salivary gland tumor, a particular challenge arises when such testing is unavailable, or when molecular testing for ETV6 gene rearrangement is negative in a suspected case of MASC. Our study presents the diagnostic workup of a challenging case of MASC with immunohistochemistry, electron microscopy, and cytogenetic studies performed to resolve the diagnosis.


PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257635
Author(s):  
Moritz Böhland ◽  
Lars Tharun ◽  
Tim Scherr ◽  
Ralf Mikut ◽  
Veit Hagenmeyer ◽  
...  

When approaching thyroid gland tumor classification, the differentiation between samples with and without “papillary thyroid carcinoma-like” nuclei is a daunting task with high inter-observer variability among pathologists. Thus, there is increasing interest in the use of machine learning approaches to provide pathologists real-time decision support. In this paper, we optimize and quantitatively compare two automated machine learning methods for thyroid gland tumor classification on two datasets to assist pathologists in decision-making regarding these methods and their parameters. The first method is a feature-based classification originating from common image processing and consists of cell nucleus segmentation, feature extraction, and subsequent thyroid gland tumor classification utilizing different classifiers. The second method is a deep learning-based classification which directly classifies the input images with a convolutional neural network without the need for cell nucleus segmentation. On the Tharun and Thompson dataset, the feature-based classification achieves an accuracy of 89.7% (Cohen’s Kappa 0.79), compared to the deep learning-based classification of 89.1% (Cohen’s Kappa 0.78). On the Nikiforov dataset, the feature-based classification achieves an accuracy of 83.5% (Cohen’s Kappa 0.46) compared to the deep learning-based classification 77.4% (Cohen’s Kappa 0.35). Thus, both automated thyroid tumor classification methods can reach the classification level of an expert pathologist. To our knowledge, this is the first study comparing feature-based and deep learning-based classification regarding their ability to classify samples with and without papillary thyroid carcinoma-like nuclei on two large-scale datasets.


2017 ◽  
Vol 29 (5) ◽  
pp. 379-384 ◽  
Author(s):  
Ryoko Inaki ◽  
◽  
Masanobu Abe ◽  
Liang Zong ◽  
Takahiro Abe ◽  
...  

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