Carcinosarcoma of the parotid gland with mucoepidermoid carcinoma component

Santisi, Anthony; DiMarcangelo, Mark T.; Zhang, Xinmin; Ahmad, Nadir; Brody, Joshua

doi:10.1016/j.radcr.2020.05.020

Cited by 3 publications

(1 citation statement)

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“…A modified deep learning model called U-Net was used to automatically segment and delineate tumour targets in CT images in nasopharyngeal cancer [ 12 ]. In this paper, MRI was used for its better resolution when it comes to soft tissues, perineural and skull base invasion as compared to CT [ 13 ]. We trained three different deep learning models to delineate GTVnx in MRI images with thoroughly comparison and analysis.…”

Section: Introductionmentioning

confidence: 99%

Automatic detection and recognition of nasopharynx gross tumour volume (GTVnx) by deep learning for nasopharyngeal cancer radiotherapy through magnetic resonance imaging

et al. 2023

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Background In this study, we propose the deep learning model-based framework to automatically delineate nasopharynx gross tumor volume (GTVnx) in MRI images. Methods MRI images from 200 patients were collected for training-validation and testing set. Three popular deep learning models (FCN, U-Net, Deeplabv3) are proposed to automatically delineate GTVnx. FCN was the first and simplest fully convolutional model. U-Net was proposed specifically for medical image segmentation. In Deeplabv3, the proposed Atrous Spatial Pyramid Pooling (ASPP) block, and fully connected Conditional Random Field(CRF) may improve the detection of the small scattered distributed tumor parts due to its different scale of spatial pyramid layers. The three models are compared under same fair criteria, except the learning rate set for the U-Net. Two widely applied evaluation standards, mIoU and mPA, are employed for the detection result evaluation. Results The extensive experiments show that the results of FCN and Deeplabv3 are promising as the benchmark of automatic nasopharyngeal cancer detection. Deeplabv3 performs best with the detection of mIoU 0.8529 ± 0.0017 and mPA 0.9103 ± 0.0039. FCN performs slightly worse in term of detection accuracy. However, both consume similar GPU memory and training time. U-Net performs obviously worst in both detection accuracy and memory consumption. Thus U-Net is not suggested for automatic GTVnx delineation. Conclusions The proposed framework for automatic target delineation of GTVnx in nasopharynx bring us the desirable and promising results, which could not only be labor-saving, but also make the contour evaluation more objective. This preliminary results provide us with clear directions for further study.

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Section: Introductionmentioning

confidence: 99%

Automatic detection and recognition of nasopharynx gross tumour volume (GTVnx) by deep learning for nasopharyngeal cancer radiotherapy through magnetic resonance imaging

et al. 2023

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Two Extremely Rare Case of Carcinosarcoma Ex Pleomorphic Adenoma

Gozgec

Oğul

2022

Ear Nose Throat J

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Carcinosarcoma ex pleomorphic adenoma (CCPA), also known as true mixed malignant tumor, is an extremely rare high-grade aggressive tumor. The histopathologic examination is the gold standard for diagnosis and radiologic imaging also plays an important role. CCPA should be considered in the differential diagnosis of salivary gland tumors when there are findings suggestive of malignancy such as necrosis and diffusion limitation on imaging.

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Carcinosarcoma of the deep lobe of the parotid gland in the parapharyngeal region: A case report

Tang,

Zhu,

Zheng

et al. 2023

World J Clin Cases

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Type 2 diabetes mellitus (T2DM), which is distinguished by increased glucose levels in the bloodstream, is a metabolic disease with a rapidly increasing incidence worldwide. Nevertheless, the etiology and characteristics of the mechanism of T2DM remain unclear. Recently, abundant evidence has indicated that the intestinal microbiota is crucially involved in the initiation and progression of T2DM. The gut microbiome, the largest microecosystem, engages in material and energy metabolism in the human body. In this review, we concentrated on the correlation between the gut flora and T2DM. Meanwhile, we summarized the pathogenesis involving the intestinal flora in T2DM, as well as therapeutic approaches aimed at modulating the gut microbiota for the management of T2DM. Through the analysis presented here, we draw attention to further exploration of these research directions.

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Carcinosarcoma of the parotid gland with mucoepidermoid carcinoma component

Cited by 3 publications

References 5 publications

Automatic detection and recognition of nasopharynx gross tumour volume (GTVnx) by deep learning for nasopharyngeal cancer radiotherapy through magnetic resonance imaging

Automatic detection and recognition of nasopharynx gross tumour volume (GTVnx) by deep learning for nasopharyngeal cancer radiotherapy through magnetic resonance imaging

Two Extremely Rare Case of Carcinosarcoma Ex Pleomorphic Adenoma

Carcinosarcoma of the deep lobe of the parotid gland in the parapharyngeal region: A case report

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