Computed tomography (CT) imaging is the most common imaging modality for the diagnosis and staging of gastric cancer. The aim of this study is was to prospectively explore the ability of quantitative spectral CT parameters in the detection of gastric cancer and its histologic types. A total of 87 gastric adenocarcinoma (43 poorly and 44 well-differentiated) patients and 36 patients with benign gastric wall lesions (25 inflammation and 11 normal), who underwent dual-phase enhanced spectral CT examination, were retrospectively enrolled in this study. Iodine concentration (IC) and normalized iodine concentration (nIC) during arterial phase (AP) and portal venous phase (PP) were measured thrice in each patient by two blinded radiologists. Moreover, intraclass correlation coefficient (ICC) was used to assess the interobserver reproducibility. Differences of IC and nIC values between gastric cancer and benign lesion groups were compared using Mann-Whitney U test. Furthermore, the gender, age, location, thickness and histological types of gastric adenocarcinoma were analyzed by Mann-Whitney U test or Kruskal-Wallis H test. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy of IC and nIC values, and the optimal cut-off value was calculated with Youden J. An excellent interobserver agreement (ICC > 0.6) was achieved for IC. Notably, the values of ICAP, ICPP, nICAP and nICPP were significantly higher in gastric cancer group (Z = 5.870, 3.894, 2.009 and 10.137, respectively; P < 0.05) than those in benign lesion group. Additionally, the values of ICAP, ICPP, nICAP and nICPP were significantly higher in poorly differentiated gastric adenocarcinoma group (Z = 4.118, 5.637, 6.729 and 2.950, respectively; P < 0.005) than those in well-differentiated gastric adenocarcinoma group. There were no statistically significant differences in the values of ICAP, ICPP, nICAP and nICPP between age, gender, tumor thickness and tumor location. Furthermore, the area under the curve (AUC) values of ICAP, nICAP, ICPP and nICPP were 0.745, 0.584, 0.662, and 0.932, respectively, for gastric cancer detection; while 0.756, 0.919, 0.851 and 0.684, respectively, in discriminating poorly differentiated gastric adenocarcinoma. IC values exhibited great potential in the preoperative and non-invasive diagnosis of gastric cancer and its histological types. In particular, nICPP is more effective for the identification of gastric cancer, whereas nICAP is more effective in discriminating poorly differentiated gastric adenocarcinoma.

Carcinosarcoma of the liver is a very rare tumor composed of a mixture of carcinomatous and sarcomatous elements. Less than 25 adequately documented cases have been reported, with inadequate description of imaging features. In order to improve the awareness of this rare tumor, this study aimed to analyze the clinicopathologic and imaging features of six cases of hepatic carcinosarcoma (HCS) confirmed by surgical pathologic evaluation. We retrospectively studied the clinicopathologic and imaging features of six cases of HCS (matching the World Health Organization definition) and discussed the differential diagnosis on the basis of imaging findings. The patients, including five men and one woman, were 38 to 69 years of age. Five patients underwent CT scans, one underwent MRI scans. While 3 patients were positive for hepatitis-B surface antigen, 2 had cirrhosis. The largest tumor diameter ranged from 5.0 to 21.0 cm. Satellite nodules, venous thrombi, and organ invasion (gastric wall, gallbladder, and right adrenal gland) were identified. Pathologically, the carcinomatous components corresponded to hepatocellular carcinoma in three cases, cholangiocellular carcinoma in one case, and adenocarcinoma in two cases. The sarcomatous components exhibited complex features, with undifferentiated spindle cells in five cases and a leiomyosarcoma in one. All tumors showed heterogeneous density/intensity with extensive cystic change and necrosis; spot calcification was observed in one case. Capsule was not identified. While four tumors showed heterogeneous hypervascular enhancement, two showed hypovascular enhancement. All patients underwent surgical resection. The follow-up period ranged from 2 to 18 months. Four patients died from recurrence and metastasis. The clinical and imaging features of HCS are heterogeneous. Due to the heterogenous nature and very low morbidity of HCS, combination of careful analysis of imaging findings and clinical features might be useful for a more accurate diagnosis of HCS.

Background: Named entity recognition (NER) on Chinese electronic medical/healthcare records has attracted significantly attentions as it can be applied to building applications to understand these records. Most previous methods have been purely data-driven, requiring high-quality and large-scale labeled medical data. However, labeled data is expensive to obtain, and these data-driven methods are difficult to handle rare and unseen entities. Methods: To tackle these problems, this study presents a novel multi-task deep neural network model for Chinese NER in the medical domain. We incorporate dictionary features into neural networks, and a general secondary named entity segmentation is used as auxiliary task to improve the performance of the primary task of named entity recognition. Results: In order to evaluate the proposed method, we compare it with other currently popular methods, on three benchmark datasets. Two of the datasets are publicly available, and the other one is constructed by us. Experimental results show that the proposed model achieves 91.07% average f-measure on the two public datasets and 87.05% f-measure on private dataset. Conclusions: The comparison results of different models demonstrated the effectiveness of our model. The proposed model outperformed traditional statistical models.

Inflammatory myofibroblastic tumor (IMT) is a rare tumor with intermediate biologic potential, in which lack of understanding often poses difficulties in preoperative diagnosis and treatment. The aim of the present study was to characterize the computed tomography (CT) features of the bladder IMT. The CT images of nine pathologically confirmed bladder IMT were retrospectively reviewed. All patients underwent both unenhanced CT and contrast‑enhanced CT. The diameter, location, contour, growth pattern, margin, boundary, density and enhancement pattern of the lesions were assessed. The mean Ki67 value of an irregular blood clot was 18% and that of no blood clot was 12%. A total of eight (89%) patients had one tumor and 1 (11%) patient had multiple tumors. An endophytic growth pattern was observed in 4 (44%) patients, an exophytic growth pattern in 2 (22%) patients, and a mixed growth pattern in 3 (33%) patients. The tumor manifests morphologically as either polypoid (n=5), or cauliflower‑like (n=1) soft‑tissue mass with a wide base in the cavity, or a limited thick‑walled (n=3). The tumor margins were smooth (n=8) or lobulated (n=1), and the tumor boundaries were either clear (n=7) or ill‑defined (n=2). The lesions showed either ring‑shaped (n=3) or heterogeneous (n=6). The polypoid and cauliflower‑like soft‑tissue mass showed a symmetrical change in the center of the lesion after enhancement. The bladder IMT is mostly a single polypoid nodule in the superior wall, mostly endophytic growth, with ring‑haped enhancement and symmetrical change after enhancement as its characteristic manifestations.