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Angiosarcoma is a rare soft tissue sarcoma, and the data about its clinicopathological features and prognostic factors are limited. The purpose of the present study was to report a large series of angiosarcoma at a single institution. Clinical data from 200 cases of angiosarcoma from the Shanghai Cancer Center (Shanghai, China) between March 2006 and March 2014 were retrospectively analyzed. The study population included 97 males and 103 females with ages between 4 and 91 years (median, 53 years). According to the tumor location, 200 cases were divided into 4 groups: i) Tumors involving the head and neck; ii) breast; iii) viscera (including internal organs and bone); and iv) soft tissue (including trunk and extremities). Of the 113 patients with follow-up data, 46 patients succumbed to the disease with a median interval of 10 months. Tumor recurrence/metastasis was identified in 66 patients with a median interval of 4 months. The disease-free survival (DFS) rate at 5-years was 19.3% and the overall survival (OS) rate at 5-years was 40.8%. Site of tumor origin, size (≥5 cm) and histological differentiation influenced DFS (P=0.032, 0.038 and <0.001, respectively), and OS (P<0.001, 0.008 and <0.001, respectively) rates. Age (<65 years) and multimodal treatment correlated with improved OS (P=0.003 and <0.001, respectively). Tumor differentiation and treatment modality were identified to be independent determinants of OS (P<0.001 and 0.038, respectively). Tumor recurrence/metastasis was an independent predictor of DFS (P<0.001). The prognosis of angiosarcoma is poor and the mortality rate is high. The site of tumor origin, size, histological differentiation, age, treatment modality and tumor recurrence/metastasis are all significant prognostic factors. In the present study, multimodal treatment may improve the clinical outcome of patients with angiosarcoma.

A malignant gastrointestinal neuroectodermal tumor (GNET) is rare, and it is therefore yet to be completely understood. This study aimed to present the clinicopathologic features of GNET, including treatment information. We included 19 patients with GNET with a mean tumor size of 4.2 cm. The most common site of tumor origin was the small intestine (57.9%), followed by the stomach (15.8%), colon (10.5%), ileocecal junction (5.3%), lower esophagus (5.3%), and anal canal (5.3%). Microscopically, the tumors were composed of epithelioid cells with eosinophilic or clear cytoplasm arranged in nest, sheet-like, papillary, or pseudoalveolar patterns and/or spindle tumor cells with eosinophilic cytoplasm arranged in a fascicular pattern. Immunohistochemically, the tumor cells stained positively for S100 (19/19,100%), SOX10 (14/15, 93.3%), vimentin (17/17, 100%), synaptophysin (Syn) (7/17, 41.2%), CD56 (4/13, 30.8%), CD99 (1/5, 20%), and CD117 (1/15, 6.7%), and negatively for HMB45, Melan A, DOG1, CD34, AE1/AE3, CAM5.2, chromogranin A, smooth muscle actin, and desmin. In total, 14/15 (93.3%) cases showed split Ewing sarcoma breakpoint region 1 gene (EWSR1) signals consistent with a chromosomal translocation involving EWSR1. Within a mean follow-up of 29.7 months (range: 3 to 63 mo), 2/15 (13.3%) patients died of disease, 5 (33.3%) were alive with disease, and 8 (53.3%) had no evidence of disease. Two and 1 patients showed partial response to apatinib and anlotinib, respectively. In conclusion, GNET has distinctive morphologic, immunohistochemical, and molecular genetic features and should be distinguished from other gastrointestinal tract malignancies. Apatinib and anlotinib might be effective for the treatment of advanced GNET and could prolong patient survival.

Background: To explore whether deep convolutional neural networks (DCNNs) have the potential to improve diagnostic efficiency and increase the level of interobserver agreement in the classification of thyroid nodules in histopathological slides.Methods: A total of 11,715 fragmented images from 806 patients' original histological images were divided into a training dataset and a test dataset. Inception-ResNet-v2 and VGG-19 were trained using the training dataset and tested using the test dataset to determine the diagnostic efficiencies of different histologic types of thyroid nodules, including normal tissue, adenoma, nodular goiter, papillary thyroid carcinoma (PTC), follicular thyroid carcinoma (FTC), medullary thyroid carcinoma (MTC) and anaplastic thyroid carcinoma (ATC). Misdiagnoses were further analyzed.Results: The total 11,715 fragmented images were divided into a training dataset and a test dataset for each pathology type at a ratio of 5:1. Using the test set, VGG-19 yielded a better average diagnostic accuracy than did Inception-ResNet-v2 (97.34% vs. 94.42%, respectively). The VGG-19 model applied to 7 pathology types showed a fragmentation accuracy of 88.33% for normal tissue, 98.57% for ATC, 98.89% for FTC, 100% for MTC, 97.77% for PTC, 100% for nodular goiter and 92.44% for adenoma. It achieved excellent diagnostic efficiencies for all the malignant types. Normal tissue and adenoma were the most challenging histological types to classify. Conclusions:The DCNN models, especially VGG-19, achieved satisfactory accuracies on the task of differentiating thyroid tumors by histopathology. Analysis of the misdiagnosed cases revealed that normal tissue and adenoma were the most challenging histological types for the DCNN to differentiate, while all the malignant classifications achieved excellent diagnostic efficiencies. The results indicate that DCNN models may have potential for facilitating histopathologic thyroid disease diagnosis.

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BackgroundTo explore the clinical characteristics and pathological features of epithelioid inflammatory myofibroblastic sarcoma (EIMS) with emphasis on the diagnostic spectrum.MethodsThe clinical data and histological features in 5 additional cases of EIMS were retrospectively reviewed. Immunohistochemical study and interphase fluorescence in situ hybridization (FISH) analysis were carried out.ResultsThere were 2 males and 3 females with age at presentation ranging from 15 to 58 years (mean, 37 years). All 5 tumors were intra-abdominal with 2 arising in the mesentery and 1 each in the omentum, rectum and transverse colon. The tumor size ranged from 5 to 20 cm in maximum diameter (mean, 10.7 cm). Histologically, all 5 tumors were composed predominantly of large epithelioid cells possessing vesicular nuclei, prominent nucleoli, and amphophilic cytoplasm. Mitotic figures were easily identified (mean, 20/10HPF). Tumor cells were arranged in clusters or sheets embedded in a myxoid stroma containing prominent neutrophils. A minor component of spindle cells was present in focal areas. By immunohistochemistry, all 5 cases were positive for anaplastic lymphoma kinase (ALK) with a nuclear membrane pattern in 4 and cytoplasmic staining with perinuclear accentuation in 1. Besides ALK, tumor cells stained variably for desmin (4/5), alpha smooth muscle actin (2/5), muscle-specific actin (1/2) and pan-cytokeratin (1/4). FISH analysis demonstrated the presence of ALK rearrangement in all 5 cases. Of 5 patients, 3 developed local recurrence, 1 died of disease 8 months after surgery.ConclusionEIMS represents a highly aggressive variant of inflammatory myofibroblastic tumor characterized by epithelioid morphology, prominent neutrophilic infiltrate, and nuclear membrane staining of ALK with ALK rearrangement. As patients with ALK-rearrangement tumors may benefit from targeted therapy, accurate diagnosis of EIMS is very important. Familiar with the characteristic features of EIMS will help pathologists avoid misdiagnosing the tumor as other malignancies.

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