CT-based methods for assessment of metabolic dysfunction associated with fatty liver disease

Metabolic dysfunction-associated fatty liver disease (MAFLD), previously called metabolic nonalcoholic fatty liver disease, is the most prevalent chronic liver disease worldwide. The multi-factorial nature of MAFLD severity is delineated through an intricate composite analysis of the grade of activity in concert with the stage of fibrosis. Despite the preeminence of liver biopsy as the diagnostic and staging reference standard, its invasive nature, pronounced interobserver variability, and potential for deleterious effects (encompassing pain, infection, and even fatality) underscore the need for viable alternatives. We reviewed computed tomography (CT)-based methods for hepatic steatosis quantification (liver-to-spleen ratio; single-energy "quantitative" CT; dual-energy CT; deep learning-based methods; photon-counting CT) and hepatic fibrosis staging (morphology-based CT methods; contrast-enhanced CT biomarkers; dedicated postprocessing methods including liver surface nodularity, liver segmental volume ratio, texture analysis, deep learning methods, and radiomics). For dual-energy and photon-counting CT, the role of virtual non-contrast images and material decomposition is illustrated. For contrast-enhanced CT, normalized iodine concentration and extracellular volume fraction are explained. The applicability and salience of these approaches for clinical diagnosis and quantification of MAFLD are discussed.Relevance statementCT offers a variety of methods for the assessment of metabolic dysfunction-associated fatty liver disease by quantifying steatosis and staging fibrosis.Key points• MAFLD is the most prevalent chronic liver disease worldwide and is rapidly increasing.• Both hardware and software CT advances with high potential for MAFLD assessment have been observed in the last two decades.• Effective estimate of liver steatosis and staging of liver fibrosis can be possible through CT.

Application Potential of Radiomics based on the Unenhanced CT Image for the Identification of Benign or Malignant Pulmonary Nodules

OBJECTIVE

With the rapid development in computed tomography (CT), the establishment of artificial intelligence (AI) technology and improved awareness of health in folks in the decades, it becomes easier to detect and predict pulmonary nodules with high accuracy. The accurate identification of benign and malignant pulmonary nodules has been challenging for radiologists and clinicians. Therefore, this study applied the unenhanced CT imagesbased radiomics to identify the benign or malignant pulmonary nodules.

METHODS

One hundred and four cases of pulmonary nodules confirmed by clinicopathology were analyzed retrospectively, including 79 cases of malignant nodules and 25 cases of benign nodules. They were randomly divided into a training group (n = 74 cases) and test group (n = 30 cases) according to the ratio of 7:3. Using ITK-SNAP software to manually mark the region of interest (ROI), and using AK software (Analysis kit, Version 3.0.0.R, GE Healthcare, America) to extract image radiomics features, a total of 1316 radiomics features were extracted. Then, the minimum-redundancy-maximum-relevance (mRMR) algorithms were used to preliminarily reduce the dimension, and retain the 30 most meaningful features, and then the least absolute shrinkage and selection operator (LASSO) algorithm was used to select the optimal subset of features, so as to establish the final model. The performance of the model was evaluated by using the receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), accuracy, sensitivity and specificity. Calibration refers to the agreement between observed endpoints and predictions, and the clinical benefit of the model to patients was evaluated by decision curve analysis (DCA).

RESULTS

The accuracy, sensitivity, and specificity of the training and testing groups were 81.0%, 77.7%, 82.1% and 76.6%, 85.7%, 73.9%, respectively, and the corresponding AUCs were of 0.83 in both groups.

CONCLUSION

CT image-based radiomics could differentiate benign from malignant pulmonary nodules, which might provide a new method for clinicians to detect benign and malignant pulmonary nodules.

MDM-U-Net: A novel network for renal cancer structure segmentation

Accurate segmentation of the renal cancer structure, including the kidney, renal tumors, veins, and arteries, has great clinical significance, which can assist clinicians in diagnosing and treating renal cancer. For accurate segmentation of the renal cancer structure in contrast-enhanced computed tomography (CT) images, we proposed a novel encoder-decoder structure segmentation network named MDM-U-Net comprising a multi-scale anisotropic convolution block, dual activation attention block, and multi-scale deep supervision mechanism. The multi-scale anisotropic convolution block was used to improve the feature extraction ability of the network, the dual activation attention block as a channel-wise mechanism was used to guide the network to exploit important information, and the multi-scale deep supervision mechanism was used to supervise the layers of the decoder part for improving segmentation performance. In this study, we developed a feasible and generalizable MDM-U-Net model for renal cancer structure segmentation, trained the model from the public KiPA22 dataset, and tested it on the KiPA22 dataset and an in-house dataset. For the KiPA22 dataset, our method ranked first in renal cancer structure segmentation, achieving state-of-the-art (SOTA) performance in terms of 6 of 12 evaluation metrics (3 metrics per structure). For the in-house dataset, our method achieves SOTA performance in terms of 9 of 12 evaluation metrics (3 metrics per structure), demonstrating its superiority and generalization ability over the compared networks in renal structure segmentation from contrast-enhanced CT scans.

[Impact of VA-ECMO combined with IABP and timing on outcome of patients with acute myocardial infarction complicated with cardiogenic shock]

Objective: To investigate the impact of combined use and timing of arterial-venous extracorporeal membrane oxygenation (VA-ECMO) with intra-aortic balloon pump (IABP) on the prognosis of patients with acute myocardial infarction complicated with cardiogenic shock (AMICS). Methods: This was a prospective cohort study, patients with acute myocardial infarction and cardiogenic shock who received VA-ECMO support from the Heart Center of Lanzhou University First Hospital from March 2019 to March 2022 in the registration database of the Chinese Society for Extracorporeal Life Support were enrolled. According to combination with IABP and time point, patients were divided into VA-ECMO alone group, VA-ECMO+IABP concurrent group and VA-ECMO+IABP non-concurrent group. Data from 3 groups of patients were collected, including the demographic characteristics, risk factors, ECG and echocardiographic examination results, critical illness characteristics, coronary intervention results, VA-ECMO related parameters and complications were compared among the three groups. The primary clinical endpoint was all-cause death, and the safety indicators of mechanical circulatory support included a decrease in hemoglobin greater than 50 g/L, gastrointestinal bleeding, bacteremia, lower extremity ischemia, lower extremity thrombosis, acute kidney injury, pulmonary edema and stroke. Kaplan-Meier survival curves were used to analyze the survival outcomes of patients within 30 days of follow-up. Using VA-ECMO+IABP concurrent group as reference, multivariate Cox regression model was used to evaluate the effect of the combination of VA-ECMO+IABP at different time points on the prognosis of AMICS patients within 30 days. Results: The study included 68 AMICS patients who were supported by VA-ECMO, average age was (59.8±10.8) years, there were 12 female patients (17.6%), 19 cases were in VA-ECMO alone group, 34 cases in VA-ECMO+IABP concurrent group and 15 cases in VA-ECMO+IABP non-concurrent group. The success rate of ECMO weaning in the VA-ECMO+IABP concurrent group was significantly higher than that in the VA-ECMO alone group and the VA-ECMO+IABP non-concurrent group (all P<0.05). Compared with the ECMO+IABP non-concurrent group, the other two groups had shorter ECMO support time, lower rates of acute kidney injury complications (all P<0.05), and lower rates of pulmonary edema complications in the ECMO alone group (P<0.05). In-hospital survival rate was significantly higher in the VA-ECMO+IABP concurrent group (28 patients (82.4%)) than in the VA-ECMO alone group (9 patients) and VA-ECMO+IABP non-concurrent group (7 patients) (all P<0.05). The survival rate up to 30 days of follow-up was also significantly higher surviving patients within were in the ECMO+IABP concurrent group (26 cases) than in VA-ECMO alone group (9 patients) and VA-ECMO+IABP non-concurrent group (4 patients) (all P<0.05). Multivariate Cox regression analysis showed that compared with the concurrent use of VA-ECMO+IABP, the use of VA-ECMO alone and non-concurrent use of VA-ECMO+IABP were associated with increased 30-day mortality in AMICS patients (HR=2.801, P=0.036; HR=2.985, P=0.033, respectively). Conclusions: When VA-ECMO is indicated for AMICS patients, combined use with IABP at the same time can improve the ECMO weaning rate, in-hospital survival and survival at 30 days post discharge, and which does not increase additional complications.

A First Report of Thyroid pneumatosis as a Complication of Ultrasound-Guided Thyroid Biopsy

BACKGROUND

Ultrasound-guided needle biopsies, including fine-needle aspirations (FNA) and core needle biopsies (CNB), have become an effective technique in the evaluation of thyroid nodules. In this report, we discuss the first reported case, to our knowledge, of thyroid pneumatosis after ultrasound-guided FNA.

CASE PRESENTATION

A 44-year-old woman underwent ultrasound-guided FNA in other hospitals after thyroid ultrasound revealed a solid lesion in the left lobe classified as TI-RADS 4. Two days later, this female presented to our hospital for an excision of a thyroid mass. Pre- and post-contrast CT scans of the thyroid showed extensive accumulation of gas in the thyroid gland and the retropharyngeal and retrotracheal space. A CT scan of the thyroid two days later revealed obvious absorption of thyroid gas and faint low-density nodules in the left lobe of the thyroid. The lesion was histopathologically confirmed as papillary carcinoma of the thyroid.

CONCLUSION

We thought the aforementioned issues originating from the limited imaging capacity of ultrasound in the context of thyroid biopsy. To avoid these limitations, we highlight the need to thoroughly examine the location of a lesion prior to thyroid biopsy to understand in detail the relationship between the lesion and the adjacent tissues, especially the proximity of the lesion to the trachea, the occurrence of coughing during a biopsy (indicating puncture of the trachea) is what operators need to be aware of so that they can manage such cases. On the other hand, we recommend that pre-operative use of CT before thyroid biopsy and especially if CT is needed anyway later for nodules evaluation before surgery to ensure the CT image quality.

Diagnostic efficiency on ultrasound shear wave elastography in evaluation of steatosis severity for non-alcoholic fatty liver disease: a rat model

BACKGROUND

The pathological feature of steatosis affects the elasticity values measured by shear wave elastography (SWE) is still controversial in non-alcoholic fatty liver disease (NAFLD). The aim of this study is to demonstrate the influence of steatosis on liver stiffness measured by SWE on a rat model with NAFLD and analyze feasibility of SWE for grading steatosis in absence of fibrosis.

METHODS

Sixty-six rats were fed with methionine choline deficient diet or standard diet to produce various stages of steatosis; 48 rats were available for final analysis. Rats underwent abdominal ultrasound SWE examination and pathological assessment. Liver histopathology was analyzed to assess the degree of steatosis, inflammation, ballooning, and fibrosis according to the non-alcoholic fatty liver disease activity score. The diagnostic performance of SWE for differentiating steatosis stages was estimated according to the receiver operating characteristic (ROC) curve. Decision curve analysis (DCA) was conducted to determine clinical usefulness and the areas under DCA (AUDCAs) calculated.

RESULTS

In multivariate analysis, steatosis was an independent factor affecting the mean elastic modules (B = 1.558, P < 0.001), but not inflammation (B =  - 0.031, P = 0.920) and ballooning (B = 0.216, P = 0.458). After adjusting for inflammation and ballooning, the AUROC of the mean elasticity for identifying S ≥ S1 was 0.956 (95%CI: 0.872-0.998) and the AUDCA, 0.621. The AUROC for distinguishing S ≥ S2 and S = S3 was 0.987 (95%CI: 0.951-1.000) and 0.920 (95%CI: 0.816-0.986) and the AUDCA was 0.506 and 0.256, respectively.

CONCLUSIONS

Steatosis is associated with liver stiffness and SWE may have the feasibility to be introduced as an assistive technology in grading steatosis for patients with NAFLD in absence of fibrosis.

DFR-U-Net: Dual residual and feature fusion network for ulna and radius segmentation on dual-energy X-ray absorptiometry images

BACKGROUND

Ulna and radius segmentation of dual-energy X-ray absorptiometry (DXA) images is essential for measuring bone mineral density (BMD).

OBJECTIVE

To develop and test a novel deep learning network architecture for robust and efficient ulna and radius segmentation on DXA images.

METHODS

This study used two datasets including 360 cases. The first dataset included 300 cases that were randomly divided into five groups for five-fold cross-validation. The second dataset including 60 cases was used for independent testing. A deep learning network architecture with dual residual dilated convolution module and feature fusion block based on residual U-Net (DFR-U-Net) to enhance segmentation accuracy of ulna and radius regions on DXA images was developed. The Dice similarity coefficient (DSC), Jaccard, and Hausdorff distance (HD) were used to evaluate the segmentation performance. A one-tailed paired t-test was used to assert the statistical significance of our method and the other deep learning-based methods (P < 0.05 indicates a statistical significance).

RESULTS

The results demonstrated our method achieved the promising segmentation performance, with DSC of 98.56±0.40% and 98.86±0.25%, Jaccard of 97.14±0.75% and 97.73±0.48%, and HD of 6.41±11.67 pixels and 8.23±7.82 pixels for segmentation of ulna and radius, respectively. According to statistics data analysis results, our method yielded significantly higher performance than other deep learning-based methods.

CONCLUSIONS

The proposed DFR-U-Net achieved higher segmentation performance for ulna and radius on DXA images than the previous work and other deep learning approaches. This methodology has potential to be applied to ulna and radius segmentation to help doctors measure BMD more accurately in the future.

Case report: Hepatic tuberculosis mimicking hepatocellular carcinoma in a patient with cirrhosis induced by hepatitis B virus

Hepatic tuberculosis (TB), which is secondary to post-hepatitis B cirrhosis, is extremely rare. We report the case of a 69-year-old man with post-hepatitis B cirrhosis complicated by primary isolated hepatic TB who was initially misdiagnosed as having hepatocellular carcinoma (HCC). The patient was hospitalized with complaints of 2 weeks of fever. He had a 20-year history of post-hepatitis B cirrhosis. The laboratory tests suggested that his serum alpha-fetoprotein (AFP) level was markedly elevated to 1210 ng/ml. From the abdominal ultrasound (US) and magnetic resonance imaging (MRI) images, we confirmed the presence of cirrhosis and discovered a space-occupying lesion of the hepatic left lobe as well as portal vein-filling defects. These results led us to consider primary liver cancer and portal vein tumor thrombus combined with decompensated cirrhosis. Biopsy and histology may be considered the ultimate diagnostic tests, but we excluded needle biopsy because of his high risk of bleeding, in addition, the patient declined the procedure. To cope with his fever, the patient was given broad-spectrum antibiotic treatment initially, followed by intravenous vancomycin. After antibiotic treatment had failed, the patient was treated with anti-TB for 10 days; after that, the patient maintained a normal temperature. The patient continued to receive tuberculostatic therapy for 6 months following his discharge. AFP completely returned to the normal level, and the aforementioned mass disappeared. Finally, hepatic TB secondary to post-hepatitis B cirrhosis with portal vein thrombosis (PVT) was considered to be the final diagnosis. More than two imaging techniques discover a space-occupying liver lesion and that the serum alpha-fetoprotein (AFP) level is extremely elevated, which means that hepatocellular carcinoma (HCC) could be diagnosed. However, some exceedingly rare diseases should not be excluded. This case illustrated that the non-invasive diagnostic criteria for liver cancer should be considered carefully when discovering a space-occupying liver lesion in a patient with cirrhosis and an elevated AFP level. In addition, primary hepatic TB should be considered and included in the differential diagnosis, and a biopsy should be performed promptly.

Recent and current advances in PET/CT imaging in the field of predicting epidermal growth factor receptor mutations in non-small cell lung cancer

Tyrosine kinase inhibitors (TKIs) are a significant treatment strategy for the management of non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutation status. Currently, EGFR mutation status is established based on tumor tissue acquired by biopsy or resection, so there is a compelling need to develop non-invasive, rapid, and accurate gene mutation detection methods. Non-invasive molecular imaging, such as positron emission tomography/computed tomography (PET/CT), has been widely applied to obtain the tumor molecular and genomic features for NSCLC treatment. Recent studies have shown that PET/CT can precisely quantify EGFR mutation status in NSCLC patients for precision therapy. This review article discusses PET/CT advances in predicting EGFR mutation status in NSCLC and their clinical usefulness.

Application of a combined radiomics nomogram based on CE-CT in the preoperative prediction of thymomas risk categorization

Objective

This study aimed to establish a combined radiomics nomogram to preoperatively predict the risk categorization of thymomas by using contrast-enhanced computed tomography (CE-CT) images.

Materials and Methods

The clinical, pathological, and CT data of 110 patients with thymoma (50 patients with low-risk thymomas and 60 patients with high-risk thymomas) collected in our Hospital from July 2017 to March 2022 were retrospectively analyzed. The study subjects were randomly divided into the training set (n = 77) and validation set (n = 33) in a 7:3 ratio. Radiomics features were extracted from the CT images, and the least absolute shrinkage and selection operator (LASSO) algorithm was performed to select 13 representative features. Five models, including logistic regression (LR), support vector machine (SVM), random forest (RF), decision tree (DT), and gradient boosting decision tree (GBDT) were constructed to predict thymoma risks based on these features. A combined radiomics nomogram was further established based on the clinical factors and radiomics scores. The performance of the models was evaluated using receiver operating characteristic (ROC) curve, DeLong tests, and decision curve analysis.

Results

Maximum tumor diameter and boundary were selected to build the clinical factors model. Thirteen features were acquired by LASSO algorithm screening as the optimal features for machine learning model construction. The LR model exhibited the highest AUC value (0.819) among the five machine learning models in the validation set. Furthermore, the radiomics nomogram combining the selected clinical variables and radiomics signature predicted the categorization of thymomas at different risks more effectively (the training set, AUC = 0.923; the validation set, AUC = 0.870). Finally, the calibration curve and DCA were utilized to confirm the clinical value of this combined radiomics nomogram.

Conclusion

We demonstrated the clinical diagnostic value of machine learning models based on CT semantic features and the selected clinical variables, providing a non-invasive, appropriate, and accurate method for preoperative prediction of thymomas risk categorization.

Application of Radiomics Model of CT Images in the Identification of Ureteral Calculus and Phlebolith

OBJECTIVE

To investigate the clinical application of the three-dimensional (3D) radiomics model of the CT image in the diagnosis and identification of ureteral calculus and phlebolith.

METHOD

Sixty-one cases of ureteral calculus and 61 cases of phlebolith were retrospectively investigated. The enrolled patients were randomly categorized into the training set (n = 86) and the testing set (n = 36) with a ratio of 7 : 3. The plain CT scan images of all samples were manually segmented by the ITK-SNAP software, followed by radiomics analysis through the Analysis Kit software. A total of 1316 texture features were extracted. Then, the maximum correlation minimum redundancy criterion and the least absolute shrinkage and selection operator algorithm were used for texture feature selection. The feature subset with the most predictability was selected to establish the 3D radiomics model. The performance of the model was evaluated by the receiver operating characteristic (ROC) curve, and the area under the ROC curve (AUC) was also calculated. Additionally, the decision curve was used to evaluate the clinical application of the model.

RESULTS

The 10 selected radiomics features were significantly related to the identification and diagnosis of ureteral calculus and phlebolith. The radiomics model showed good identification efficiency for ureteral calculus and phlebolith in the training set (AUC = 0.98; 95%CI: 0.96-1.00) and testing set (AUC = 0.98; 95%CI: 0.95-1.00). The decision curve thus demonstrated the clinical application of the radiomics model.

CONCLUSIONS

The 3D radiomics model based on plain CT scan images indicated good performance in the identification and prediction of ureteral calculus and phlebolith and was expected to provide an effective detection method for clinical diagnosis.

Further evidence for Zenker's diverticulum in a slim woman with body figure predisposition: a case report and literature review

Zenker’s diverticulum (ZD) is a bag-like pharyngeal pouch that protrudes to the outside of the pharynx. It is thought to be an acquired disease that occurs following the dysfunction of laryngopharynx muscle, and certain body shapes may be predisposed to this condition. We report a 56-year-old female of slim build with ZD. Computed tomography scanning revealed a hypodense lesion on the left posterior side of her upper esophagus that was filled with air and had no obvious wall. To verify this finding, a barium esophagogram was carried out which showed a round pouch at the level of the 6th cervical vertebral body that communicated with the esophagus through a narrow neck. ZD was subsequently confirmed by endoscopy. These findings provide further evidence in support of a body shape predisposition for ZD.

Deep learning approach for automatic segmentation of ulna and radius in dual-energy X-ray imaging

BACKGROUND

Segmentation of the ulna and radius is a crucial step for the measurement of bone mineral density (BMD) in dual-energy X-ray imaging in patients suspected of having osteoporosis.

PURPOSE

This work aimed to propose a deep learning approach for the accurate automatic segmentation of the ulna and radius in dual-energy X-ray imaging.

METHODS AND MATERIALS

We developed a deep learning model with residual block (Resblock) for the segmentation of the ulna and radius. Three hundred and sixty subjects were included in the study, and five-fold cross-validation was used to evaluate the performance of the proposed network. The Dice coefficient and Jaccard index were calculated to evaluate the results of segmentation in this study.

RESULTS

The proposed network model had a better segmentation performance than the previous deep learning-based methods with respect to the automatic segmentation of the ulna and radius. The evaluation results suggested that the average Dice coefficients of the ulna and radius were 0.9835 and 0.9874, with average Jaccard indexes of 0.9680 and 0.9751, respectively.

CONCLUSION

The deep learning-based method developed in this study improved the segmentation performance of the ulna and radius in dual-energy X-ray imaging.

[Effect of splenectomy on the risk of hepatocellular carcinoma development among patients with liver cirrhosis and portal hypertension: a multi-institutional cohort study]

Objective: To identify whether splenectomy for treatment of hypersplenism has any impact on development of hepatocellular carcinoma(HCC) among patients with liver cirrhosis and hepatitis. Methods: Patients who underwent splenectomy for hypersplenism secondary to liver cirrhosis and portal hypertension between January 2008 and December 2012 were included from seven hospitals in China, whereas patients receiving medication treatments for liver cirrhosis and portal hypertension (non-splenectomy) at the same time period among the seven hospitals were included as control groups. In the splenectomy group, all the patients received open or laparoscopic splenectomy with or without pericardial devascularization. In contrast, patients in the control group were treated conservatively for liver cirrhosis and portal hypertension with medicines (non-splenectomy) with no invasive treatments, such as transjugular intrahepatic portosystemic shunt, splenectomy or liver transplantation before HCC development. All the patients were routinely screened for HCC development with abdominal ultrasound, liver function and alpha-fetoprotein every 3 to 6 months. To minimize the selection bias, propensity score matching (PSM) was used to match the baseline data of patients among splenectomy versus non-splenectomy groups. The Kaplan-Meier method was used to calculate the overall survival and cumulative incidence of HCC development, and the Log-rank test was used to compare the survival or disease rates between the two groups. Univariate and Cox proportional hazard regression models were used to analyze the potential risk factors associated with development of HCC. Results: A total of 871 patients with liver cirrhosis and hypertension were included synchronously from 7 tertiary hospitals. Among them, 407 patients had a history of splenectomy for hypersplenism (splenectomy group), whereas 464 patients who received medical treatment but not splenectomy (non-splenectomy group). After PSM,233 pairs of patients were matched in adjusted cohorts. The cumulative incidence of HCC diagnosis at 1,3,5 and 7 years were 1%,6%,7% and 15% in the splenectomy group, which was significantly lower than 1%,6%,15% and 23% in the non-splenectomy group (HR=0.53,95%CI:0.31 to 0.91,P=0.028). On multivariable analysis, splenectomy was independently associated with decreased risk of HCC development (HR=0.55,95%CI:0.32 to 0.95,P=0.031). The cumulative survival rates of all the patients at 1,3,5,and 7 years were 100%,97%,91%,86% in the splenectomy group,which was similar with that of 100%,97%,92%,84% in the non-splenectomy group (P=0.899). In total,49 patients (12.0%) among splenectomy group and 75 patients (16.2%) in non-splenectomy group developed HCC during the study period, respectively. Compared to patients in non-splenectomy group, patients who developed HCC after splenectomy were unlikely to receive curative resection for HCC (12.2% vs. 33.3%,χ²=7.029, P=0.008). Conclusion: Splenectomy for treatment of hypersplenism may decrease the risk of HCC development among patients with liver cirrhosis and portal hypertension.

A radiomics approach for automated diagnosis of ovarian neoplasm malignancy in computed tomography

This paper develops a two-dimensional (2D) radiomics approach with computed tomography (CT) to differentiate between benign and malignant ovarian neoplasms. A retrospective study was conducted from July 2017 to June 2019 for 134 patients with surgically-verified benign or malignant ovarian tumors. The patients were randomly divided in a ratio of 7:3 into two sets, namely a training set (of n = 95) and a test set (of n = 39). The ITK-SNAP software was used to delineate the regions of interest (ROI) associated with lesions of the largest diameters in plain CT image slices. Texture features were extracted by the Analysis Kit (AK) software. The training set was used to select the best features according to the maximum-relevance minimum-redundancy (mRMR) criterion, in addition to the algorithm of the least absolute shrinkage and selection operator (LASSO). Then, we employed a radiomics model for classification via multivariate logistic regression. Finally, we evaluated the overall performance of our method using the receiver operating characteristics (ROC), the DeLong test. and tested in an external validation test sample of patients of ovarian neoplasm. We created a radiomics prediction model from 14 selected features. The radiomic signature was found to be highly discriminative according to the area under the ROC curve (AUC) for both the training set (AUC = 0.88), and the test set (AUC = 0.87). The radiomics nomogram also demonstrated good calibration and differentiation for both the training (AUC = 0.95) and test (AUC = 0.96) samples. External validation tests gave a good performance in radiomic signature (AUC = 0.83) and radiomics nomogram (AUC = 0.95). The decision curve explicitly indicated the clinical usefulness of our nomogram method in the sense that it can influence major clinical events such as the ordering or abortion of other tests, treatments or invasive procedures. Our radiomics model based on plain CT images has a high diagnostic efficiency, which is helpful for the identification and prediction of benign and malignant ovarian neoplasms.

Retroperitoneal dendritic cell sarcoma: A case report

RATIOANLE

Interdigitating dendritic cell sarcoma (IDCS) is a rare sarcoma that originates from interdigitating dendritic cells in lymphoid tissue, the imaging characteristics of which are poorly defined. Pathological examination can identify the tumor, but reports on the imaging characteristics of IDCS are limited.

PATIENT CONCERNS

Here, we report a case of IDCS in a 48-year-old female involving the retroperitoneal area. The patient had a lumbar mass on her right lower back for 4 years, and which started increasing in size 1 year before.

DIAGNOSES

An irregular soft tissue mass (10.1cm × 8.5 cm in size) in the right lower back of retroperitoneum was detected by CT examination with unclear borders, uneven density, and necrosis. The solid components of the mass were significantly enhanced on postcontrast imaging. The soft tissue was irregular and uneven. Cystic solid masses were observed on MRI examination in the right retroperitoneum, lateral abdominal wall, waist, and back. Necrosis, hemorrhage, and cystic transformation were observed inside the lesion. The cyst wall, separation, and wall nodules were significantly enhanced on the postcontrast image. No distant metastasis was observed. Postoperative pathology confirmed the diagnosis of IDCS.

INTERVENTIONS

The patient underwent surgical resection. The resected margin was positive, and the patient received adjuvant radiotherapy 2 months after the surgery.

OUTCOMES

Twelve months after radiotherapy, the patient's chest CT showed multiple metastases in both lungs. The patient was started on combination chemotherapy of doxorubicin and ifosfamide, and the follow-up is still ongoing.

LESSONS

Imaging provides a unique advantage to determine the extent of the IDCS, the invasion of adjacent tissues, and the presence or absence of distant metastases.

Trimers Conjugated to Fibrin Hydrogels Promote Salivary Gland Function

New strategies for tissue engineering have great potential for restoring and revitalizing impaired tissues and organs, including the use of smart hydrogels that can be modified to enhance organization and functionality of the salivary glands. For instance, monomers of laminin-111 peptides chemically conjugated to fibrin hydrogel (L_1pM-FH) promote cell cluster formation in vitro and salivary gland regeneration in vivo when compared with fibrin hydrogel (FH) alone; however, L_1pM-FH produce only weak expression of acinar differentiation markers in vivo (e.g., aquaporin-5 and transmembrane protein 16). Since previous studies demonstrated that a greater impact can be achieved when trimeric forms were used as compared with monomeric or dimeric forms, we investigated the extent to which trimers of laminin-111 chemically conjugated to FH (L_1pT-FH) can increase the expression of acinar differentiation markers and elevate saliva secretion. In vitro studies using Par-C10 acinar cells demonstrated that when compared with L_1pM-FH, L_1pT-FH induced similar levels of acinar-like cell clustering, polarization, lumen formation, and calcium signaling. To assess the performance of the trimeric complex in vivo, we compared the ability of L_1pM-FH and L_1pT-FH to increase acinar differentiation markers and restore saliva flow rate in a salivary gland wound model of C57BL/6 mice. Our results show that L_1pT-FH applied to wounded mice significantly improved the expression of the acinar differentiation markers and saliva secretion when compared with the monomeric form. Together, these positive effects of L_1pT-FH warrant its future testing in additional models of hyposalivation with the ultimate goal of applying this technology in humans.

WITHDRAWN: Analysis of thin-section CT in patients with coronavirus disease (COVID-19) after hospital discharge

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Coronavirus Disease (COVID-19): Spectrum of CT Findings and Temporal Progression of the Disease

Coronavirus disease is an emerging infection caused by a novel coronavirus that is moving rapidly. High resolution computed tomography (CT) allows objective evaluation of the lung lesions, thus enabling us to better understand the pathogenesis of the disease. With serial CT examinations, the occurrence, development, and prognosis of the disease can be better understood. The imaging can be sorted into four phases: early phase, progressive phase, severe phase, and dissipative phase. The CT appearance of each phase and temporal progression of the imaging findings are demonstrated.

Diagnostic performance on multiple parameters of real-time ultrasound shear wave elastography for evaluating nonalcoholic fatty liver disease: A rabbit model

OBJECTIVE

To study the diagnostic value of real-time ultrasound shear wave elastography (US-SWE) in evaluating the histological stages of nonalcoholic fatty liver disease (NAFLD) in a rabbit model.

MATERIALS AND METHODS

Twenty-one 8-week-old rabbits were fed a high-fat, high-cholesterol diet (experimental groups), and seven rabbits were fed a standard diet (control group). All rabbits underwent real-time US-SWE at various time points to document the histological stages of NAFLD. We categorized the histological stages as normal, NAFL, borderline nonalcoholic steatohepatitis (NASH), and NASH. We measured the elastic modulus of the liver parenchyma and analyzed the diagnostic efficacy of real-time US-SWE using the area under receiver operating characteristic curve (AUC) for the four histological stages.

RESULTS

The mean, minimum, and maximum elastic modulus increase for NAFL, borderline NASH, and NASH. For the mean, minimum, and maximum elastic modulus, AUCs are 0.891 (95% confidence interval [CI]: 0.716-0.977), 0.867 (95% CI: 0.686-0.965), and 0.789 (95% CI:0.594-0.919) for differentiating normal liver from liver with NAFLD, respectively; AUCs are 0.846 (95% CI: 0.660-0.954), 0.818 (95% CI: 0.627-0.937), and 0.797 (95% CI:0.627-0.913) for differentiating normal liver or liver with NAFL from liver with borderline NASH or NASH, respectively; AUCs are 0.889 (95% CI: 0.713-0.976), 0.787 (95% CI: 0.591-0.918), and 0.895 (95% CI:0.720-0.978) for differentiating liver with NASH from liver with lower severity NAFLD or normal liver, respectively.

CONCLUSIONS

Real-time US-SWE is an accurate, noninvasive technique for evaluating the histological stages of NAFLD by measuring liver stiffness. We recommend using the mean elastic modulus to differentiate the histological stages, with the minimum and maximum elastic modulus as valuable complements.

Clinical and computed tomographic (CT) images characteristics in the patients with COVID-19 infection: What should radiologists need to know?

OBJECTIVE

To evaluate the clinical and computed tomographic (CT) features in the patients with COVID-19 pneumonia confirmed by the real-time reverse transcriptase polymerase chain reaction (rRT-PCR) amplification of the viral DNA from a sputum sample.

MATERIAL AND METHODS

Clinical information and CT findings of a total of 14 patients with COVID-19 infection (age range, 12-83 years; females 6) were analyzed retrospectively. The clinical information includes the history of exposure, laboratory results, and the symptoms (such as fever, cough, headache, etc.); CT findings of chest include the extension and distribution of lesion, the ground-glass opacity (GGO), consolidation, bronchovascular enlarged, irregular linear appearances, pleural effusion, and lymphadenopathy.

RESULTS

Eight patients had the exposure history for recent travel to Wuhan of Hubei province (8/14, 57%), 6 had the exposure to patients with COVID-19 infection. Significant statistical differences were observed in lymphocyte percentage decreased and C-reactive protein elevated (p = 0.015). Seven patients had fever, 7 had cough, 2 had headache, 3 had fatigue, 1 had body soreness, 3 had diarrhea, and 2 had no obvious symptoms. In chest CT examination, 10 patients were positive (10/14, 71.43%). Among these patients, 9 had lesions involving both lungs (9/10, 90%), 8 had lesions involving 4 to 5 lobes (8/10, 80%). Most of lesions were distributed peripherally and the most significant lesions were observed in the right lower lobe in 9 patients (9/10, 90%). Nodules were observed in 5 patients (5/10, 50%); GGO, consolidation, and bronchovascular enlarged were shown in 9 patients (9/10, 90%); irregular linear appearances were revealed in 7 patients (7/10, 70%); and pleural effusions were exhibited in 2 patients (2/10, 20%). Last, no patients showed lymphadenopathy.

CONCLUSION

There were some typical CT features for diagnosis of COVID-19 pneumonia. The radiologists should know these CT findings and clinical information, which could help for accurate analysis in the patients with 2019 novel coronavirus infection.

Differentiating pneumonia with and without COVID-19 using chest CT images: from qualitative to quantitative

BACKGROUND

Pneumonia caused by COVID-19 shares overlapping imaging manifestations with other types of pneumonia. How to objectively and quantitatively differentiate pneumonia patients with and without COVID-19 virus remains clinical challenge.

OBJECTIVE

To formulate standardized scoring criteria and an objective quantization standard to guide decision making in detection and diagnosis of COVID-19 virus induced pneumonia in clinical practice.

METHODS

A retrospective dataset includes computed tomography (CT) images acquired from 43 pneumonia patients with COVID-19 virus detected by reverse transcription-polymerase chain reaction (RT-PCR) tests and 49 pneumonia patients without COVID-19 virus. All patients were treated during the same time period in two hospitals. Key indicators of differential diagnosis were identified in relevant literature and the scores were quantified namely, patients with more than 8 points were identified as high risk, those with 6-8 points as moderate risk, and those with fewer than 6 points as low risk for COVID-19 virus. In the study, 3 radiologists determined the scores for all patients. Diagnostic sensitivity and specificity were subsequently calculated.

RESULTS

A total of 61 patients were determined as high risk, among which 42 were COVID-19 positive by RT-PCR tests. Next, 9 were identified as moderate risk, one of whom was COVID-19 positive. Last, 22 were classified into the low-risk group, all of them are COVID-19 negative. Based on these results, the sensitivity of detection COVID-19 positive cases between the high-risk group and the non-high-risk group was 0.98 with 95% confidence interval [0.88, 1.00], and the specificity was 0.61 [0.46, 0.75]. The detection sensitivity between the moderate-/high-risk group and the low-risk group was 1.00 [0.92, 1.00], and the specificity was 0.45 [0.31, 0.60].

CONCLUSION

The proposed quantitative scoring criteria showed high sensitivity and moderate specificity in detecting COVID-19 using CT images, which indicates that these criteria may be beneficial for screening in real-world practice and helpful for long-term disease control.

Analysis of thin-section CT in patients with coronavirus disease (COVID-19) after hospital discharge

PURPOSE

To analyze clinical and thin-section computed tomographic (CT) data from the patients with coronavirus disease (COVID-19) to predict the development of pulmonary fibrosis after hospital discharge.

MATERIALS AND METHODS

Fifty-nine patients (31 males and 28 females ranging from 25 to 70 years old) with confirmed COVID-19 infection performed follow-up thin-section thorax CT. After 31.5±7.9 days (range, 24 to 39 days) of hospital admission, the results of CT were analyzed for parenchymal abnormality (ground-glass opacification, interstitial thickening, and consolidation) and evidence of fibrosis (parenchymal band, traction bronchiectasis, and irregular interfaces). Patients were analyzed based on the evidence of fibrosis and divided into two groups namely, groups A and B (with and without CT evidence of fibrosis), respectively. Patient demographics, length of stay (LOS), rate of intensive care unit (ICU) admission, peak C-reactive protein level, and CT score were compared between the two groups.

RESULTS

Among the 59 patients, 89.8% (53/59) had a typical transition from early phase to advanced phase and advanced phase to dissipating phase. Also, 39% (23/59) patients developed fibrosis (group A), whereas 61% (36/59) patients did not show definite fibrosis (group B). Patients in group A were older (mean age, 45.4±16.9 vs. 33.8±10.2 years) (P = 0.001), with longer LOS (19.1±5.2 vs. 15.0±2.5 days) (P = 0.001), higher rate of ICU admission (21.7% (5/23) vs. 5.6% (2/36)) (P = 0.061), higher peak C-reactive protein level (30.7±26.4 vs. 18.1±17.9 mg/L) (P = 0.041), and higher maximal CT score (5.2±4.3 vs. 4.0±2.2) (P = 0.06) than those in group B.

CONCLUSIONS

Pulmonary fibrosis may develop early in patients with COVID-19 after hospital discharge. Older patients with severe illness during treatment were more prone to develop fibrosis according to thin-section CT results.

A Deep Learning Segmentation Approach in Free-Breathing Real-Time Cardiac Magnetic Resonance Imaging

OBJECTIVES

The purpose of this study was to segment the left ventricle (LV) blood pool, LV myocardium, and right ventricle (RV) blood pool of end-diastole and end-systole frames in free-breathing cardiac magnetic resonance (CMR) imaging. Automatic and accurate segmentation of cardiac structures could reduce the postprocessing time of cardiac function analysis.

METHOD

We proposed a novel deep learning network using a residual block for the segmentation of the heart and a random data augmentation strategy to reduce the training time and the problem of overfitting. Automated cardiac diagnosis challenge (ACDC) data were used for training, and the free-breathing CMR data were used for validation and testing.

RESULTS

The average Dice was 0.919 (LV), 0.806 (myocardium), and 0.818 (RV). The average IoU was 0.860 (LV), 0.699 (myocardium), and 0.761 (RV).

CONCLUSIONS

The proposed method may aid in the segmentation of cardiac images and improves the postprocessing efficiency of cardiac function analysis.

Quantification of hepatic steatosis in histologic images by deep learning method

OBJECTIVE

To develop and test a novel method for automatic quantification of hepatic steatosis in histologic images based on the deep learning scheme designed to predict the fat ratio directly, which aims to improve accuracy in diagnosis of non-alcoholic fatty liver disease (NAFLD) with objective assessment of the severity of hepatic steatosis instead of subjective visual estimation.

MATERIALS AND METHODS

Thirty-six 8-week old New Zealand white rabbits of both sexes were fed with high-cholesterol, high-fat diet and sacrificed under deep anesthesia at various time points to obtain the pathological specimen. All rabbits were performed by multislice computed tomography for surveillance to measure density changes of liver parenchyma. A deep learning scheme using a convolutional neural network was developed to directly predict the liver fat ratio based on the pathological images. The average error value, standard deviation, and accuracy (error <5%) were evaluated and compared between the deep learning scheme and manual segmentation results. The Pearson's correlation coefficient was also calculated in this study.

RESULTS

The deep learning scheme performs successfully on rabbit liver histologic data, showing a high degree of accuracy and stability. The average error value, standard deviation, and accuracy (error <5%) were 3.21%, 4.02%, and 79.10% for the cropped images, 2.22%, 1.92%, and 88.34% for the original images, respectively. The strong positive correlation was also observed for cropped images (R = 0.9227) and original images (R = 0.9255) in comparison to labeled fat ratio.

CONCLUSIONS

This new deep learning scheme may aid in the quantification of steatosis in the liver and facilitate its treatment by providing an earlier clinical diagnosis.

NAFLD evaluation: Which is more appropriate, multislice computed tomography or ultrasound real-time shear wave elastography?

OBJECTIVE

This study aims to assess the value of ultrasound real-time shear wave elastography (US-SWE) for evaluation of nonalcoholic fatty liver disease (NAFLD) in a rabbit model compared with multislice computed tomography (MSCT).

MATERIAL AND METHODS

Twenty-six rabbits were fed with high-fat, high-cholesterol diet and six rabbits were fed with a standard diet. All rabbits were performed with MSCT and US-SWE at various time points to measure changes in liver parenchyma. The diagnostic efficiency of US-SWE was analyzed using receiver operating characteristics (ROC) curves compared with MSCT based on the liver pathology.

RESULTS

The statistically significant differences in the areas under the ROC curves between using MSCT and US-SWE modalities were detected to discriminate between normal vs. NAFLD or higher severity pathology. Similarly, for normal or NAFLD vs. borderline or NASH livers, statistically significant differences between using US-SWE and MSCT modalities were also detected for nonalcoholic steatohepatitis (NASH) vs. lower severity pathology.

CONCLUSIONS

MSCT, but not US-SWE, had a better ability to differentiate normal or NAFLD livers from higher severity NAFLD livers. However, the diagnostic efficiency of US-SWE was superior to that of MSCT for differentiating NASH from normal or lower severity NAFLD.

Effect of Methylprednisolone on Liver Injury and Endotoxin Levels Following Brain Death in Rats

BACKGROUND AND AIM

Brain death impairs liver function in potential donors and is associated with inflammatory activation. Methylprednisolone treatment after brain death has been shown to reduce inflammatory activity. The aim of the present study was to evaluate the effects of methylprednisolone on liver injury and endotoxin levels in brain-dead rats.

METHODS

Thirty-two rats were randomly divided into 4 groups: a sham-operation group (Sham group), a brain death with methylprednisolone treatment group (Methy group), a brain death with saline treatment group (Saline group), and a brain death group (BD group). The rats were anesthetized and induced by gradually increasing the intra-cranial pressure using a Fogarty catheter balloon for brain death. All of the animals were observed and ventilated for 6 h prior to being euthanized. Hepatic pathologic histology (Knodell histology activity index), liver inflammatory cytokine levels, liver function and endotoxin levels were assessed.

RESULTS

After brain death, methylprednisolone markedly alleviated the Knodell histology activity index of liver injury (P < .05). Additionally, significant reductions in the levels of TNF-α, IL-1β, and IL-10 were observed in the Methy group compared to those in the Saline and BD groups (P < .01), whereas no significant differences were found between the Saline and BD groups (P > .05). Interestingly, although the rate of liver injury after brain death in the methylprednisolone treatment group improved, the endotoxin level did not decline in the Methy group compared to the levels in the Saline and BD groups (P > .05).

CONCLUSION

The present study verified that methylprednisolone was protective for liver injury in rats subjected to brain death. This protection appeared to be due to reduced inflammatory activity with no influence on the endotoxin level.

[National experts consensus on tracheotomy and intubation for burn patients (2018 version)]

Airway edema, stenosis, obstruction and even asphyxia are easy to occur in patients with extensive burn, deep burn of head, face, and neck area, inhalation injuries, etc., which threaten life. Timely tracheotomy and intubation is an important treatment measure, but lack of knowledge and improper handling in some hospitals resulted in airway obstruction. The technique of percutaneous tracheotomy and intubation provides convenience for emergency treatment of critical burns and mass burn. The Chinese Geriatrics Society organized some experts in China to discuss the indications, timing, methods, extubation, and precautions of tracheotomy and intubation for burn patients. The national experts consensus on tracheotomy and intubation for burn patients (2018 version) was written to provide a reference standard for clinical treatment.

[National experts consensus on tracheotomy and intubation for burn patients (2018 version)]

Airway edema, stenosis, obstruction and even asphyxia are easy to occur in patients with extensive burn, deep burn of head, face, and neck area, inhalation injuries, etc., which threaten life. Timely tracheotomy and intubation is an important treatment measure, but lack of knowledge and improper handling in some hospitals resulted in airway obstruction. The technique of percutaneous tracheotomy and intubation provides convenience for emergency treatment of critical burns and mass burn. The Burn and Trauma Branch of Chinese Geriatrics Society organized some experts in China to discuss the indications, timing, methods, extubation, and precautions of tracheotomy and intubation for burn patients. The national experts consensus on tracheotomy and intubation for burn patients (2018 version) was written to provide a reference standard for clinical treatment.

Tau-mediated iron export prevents ferroptotic damage after ischemic stroke

Functional failure of tau contributes to age-dependent, iron-mediated neurotoxicity, and as iron accumulates in ischemic stroke tissue, we hypothesized that tau failure may exaggerate ischemia-reperfusion-related toxicity. Indeed, unilateral, transient middle cerebral artery occlusion (MCAO) suppressed hemispheric tau and increased iron levels in young (3-month-old) mice and rats. Wild-type mice were protected by iron-targeted interventions: ceruloplasmin and amyloid precursor protein ectodomain, as well as ferroptosis inhibitors. At this age, tau-knockout mice did not express elevated brain iron and were protected against hemispheric reperfusion injury following MCAO, indicating that tau suppression may prevent ferroptosis. However, the accelerated age-dependent brain iron accumulation that occurs in tau-knockout mice at 12 months of age negated the protective benefit of tau suppression against MCAO-induced focal cerebral ischemia-reperfusion injury. The protective benefit of tau knockout was revived in older mice by iron-targeting interventions. These findings introduce tau-iron interaction as a pleiotropic modulator of ferroptosis and ischemic stroke outcome.

Lithium suppression of tau induces brain iron accumulation and neurodegeneration

Lithium is a first-line therapy for bipolar affective disorder. However, various adverse effects, including a Parkinson-like hand tremor, often limit its use. The understanding of the neurobiological basis of these side effects is still very limited. Nigral iron elevation is also a feature of Parkinsonian degeneration that may be related to soluble tau reduction. We found that magnetic resonance imaging T₂ relaxation time changes in subjects commenced on lithium therapy were consistent with iron elevation. In mice, lithium treatment lowers brain tau levels and increases nigral and cortical iron elevation that is closely associated with neurodegeneration, cognitive loss and parkinsonian features. In neuronal cultures lithium attenuates iron efflux by lowering tau protein that traffics amyloid precursor protein to facilitate iron efflux. Thus, tau- and amyloid protein precursor-knockout mice were protected against lithium-induced iron elevation and neurotoxicity. These findings challenge the appropriateness of lithium as a potential treatment for disorders where brain iron is elevated (for example, Alzheimer's disease), and may explain lithium-associated motor symptoms in susceptible patients.

L1 Peptide-Conjugated Fibrin Hydrogels Promote Salivary Gland Regeneration

Hyposalivation contributes to dental caries, periodontitis, and microbial infections. Additionally, it impairs activities of daily living (e.g., speaking, chewing, and swallowing). Treatments for hyposalivation are currently limited to medications (e.g., the muscarinic receptor agonists pilocarpine and cevimeline) that induce saliva secretion from residual acinar cells and the use of saliva substitutes. However, given that these therapies provide only temporary relief, the development of alternative treatments to restore gland function is essential. Previous studies demonstrated that laminin 1 (L1) is critical for intact salivary cell cluster formation and organization. However, the full L1 sequence is not suitable for clinical applications, as each protein domain may contribute to unwanted effects, such as degradation, tumorigenesis, and immune responses that, when compounded, outweigh the potential benefits provided by their sum. Although the L1 peptides YIGSR and A99 linked to fibrin hydrogels (FHs) promote intact salivary epithelial formation in vitro, little is known about their role during salivary gland regeneration in vivo. Therefore, the goal of this study was to demonstrate whether L1 peptides conjugated to FHs promote tissue regeneration in a wound-healing model of mouse submandibular glands (mSMGs). Our results suggest that YIGSR-A99 peptides, chemically conjugated to FHs and applied to wounded mSMGs in vivo, formed new organized salivary tissue. In contrast, wounded mSMGs treated with FHs alone or in the absence of a scaffold showed disorganized collagen formation and poor tissue healing. Together these studies indicate that damaged salivary gland tissue can grow and differentiate when treated with FHs containing L1 peptides.

Serum Proteomics Analysis in Rats of Immunosuppression Induced by Chronic Stress

The immune system can be damaged by chronic stress. However, for this process, the involved molecular alterations and their regulatory roles played in immunosuppression still remain unclear. This study was aimed to identify the differences in serum protein expressions that are closely associated with the effect of chronic stress on immune function. Serum protein levels of rats in control group and chronic stress group were measured by iTRAQ analysis. Subsequently, among the 121 differentially expressed proteins screened between the two groups, 46 proteins were upregulated (>1.5-fold, P < 0.05), while 75 proteins were downregulated (<0.67-fold, P < 0.05). Bioinformatics analysis revealed that most of the differentially expressed proteins were in relation with the metabolic, cellular, response stimulus and immune system processes. The significantly differential expression of ceruloplasmin, haptoglobin, catalase and peroxiredoxin-1 were picked out for reconfirmation by ELISA analysis. The results were consistent with those obtained by iTRAQ. What is more, the roles of above-mentioned four proteins, apolipoprotein B-100 and heat-shock protein 90 in immunosuppression induced by chronic stress were discussed. Taken together, these findings may provide a new insight into better understanding the molecular mechanisms of immunosuppression induced by chronic stress.

Social networks and health-related quality of life among Chinese old adults in urban areas: results from 4th National Household Health Survey

OBJECTIVE

To examine the associations between components of social networks and health-related quality of life (HRQoL) in community-dwelling old adults in urban areas in China.

STUDY DESIGN

Data from the 4th National Household Health Survey (NHHS) in China, conducted in 2008, were used. HRQoL of respondents aged ≥15 years was assessed using EQ-5D in the NHHS.

METHODS

The sample for the current analysis included 9833 old adults aged ≥60 years. Multiple linear and logistic regression models were used to assess the associations between indicators of social network and HRQoL.

RESULTS

Approximately 6% of the respondents saw their children once a year or less, and approximately 1% reported that they had no children. Thirteen percent of the sample seldom contacted their neighbours and seldom met with relatives or friends; approximately 62% seldom attended social gatherings. The five dimensions of HRQoL (mobility, self-care, usual activities, pain/discomfort and anxiety/depression) were reported to be moderate or severe in 14.5%, 9.4%, 12.6%, 18.3% and 9.3% of the sample, respectively. The mean visual analogue scale (VAS) score and EQ-5D index using the time trade-off method was 70.96 [standard deviation (SD) 14.79] and 0.869 (SD 0.163), respectively. After adjusting for potential confounding variables, old adults with weaker social networks were more likely to report problems on EQ-5D dimensions, lower VAS scores and lower EQ-5D indexes.

CONCLUSIONS

For old adults living in urban communities in China, increased social participation has a positive effect on various dimensions of HRQoL. There is a need for policy considerations that will improve integration of community-level public resources in order to encourage frequent social interaction among old adults, and promote health and social care as a whole.

Advances in tumor markers of ovarian cancer for early diagnosis

Ovarian cancer often occurs in perimenopausal women. The mortality of ovarian cancer is in the first place among gynecological cancers because of no obvious early symptoms and the lack of effective diagnostic approach. Gene chips, proteomics, immunohistochemistry and other methods have become hot topics for early diagnosis of ovarian cancer. However, due to the variety of pathology and not clear enough of mechanism and etiology, there is still no ideal tumor markers with both high specific and sensitivity, which can be applied into clinical early diagnosis for ovarian cancer. Therefore, a new systematic method with high sensitivity and specificity for early diagnosis of ovarian cancer and new tumor markers need to be identified. We should make an examination of ovarian cancer in the early period in the crowd for early diagnosis and early treatment to further improve life quality of patients. This paper reviewed the recent advancements of tumor markers for early diagnosis of ovarian cancer.

Stem Cell-Soluble Signals Enhance Multilumen Formation in SMG Cell Clusters

Saliva plays a major role in maintaining oral health. Patients with salivary hypofunction exhibit difficulty in chewing and swallowing foods, tooth decay, periodontal disease, and microbial infections. At this time, treatments for hyposalivation are limited to medications (e.g., muscarinic receptor agonists: pilocarpine and cevimeline) that induce saliva secretion from residual acinar cells as well as artificial salivary substitutes. Therefore, advancement of restorative treatments is necessary to improve the quality of life in these patients. Our previous studies indicated that salivary cells are able to form polarized 3-dimensional structures when grown on growth factor-reduced Matrigel. This basement membrane is rich in laminin-III (L1), which plays a critical role in salivary gland formation. Mitotically inactive feeder layers have been used previously to support the growth of many different cell types, as they provide factors necessary for cell growth and organization. The goal of this study was to improve salivary gland cell differentiation in primary cultures by using a combination of L1 and a feeder layer of human hair follicle-derived mesenchymal stem cells (hHF-MSCs). Our results indicated that the direct contact of mouse submandibular (mSMG) cell clusters and hHF-MSCs was not required for mSMG cells to form acinar and ductal structures. However, the hHF-MSC conditioned medium enhanced cell organization and multilumen formation, indicating that soluble signals secreted by hHF-MSCs play a role in promoting these features.

Antiemesis effect and brain fMRI response of gastric electrical stimulation with different parameters in dogs

BACKGROUND

The aims of this study were to investigate the effect of gastric electrical stimulation (GES) with different parameters on emesis induced by apomorphine, and possible center mechanisms by brain functional magnetic resonance imaging (fMRI).

METHODS

Six dogs implanted with electrodes on gastric serosa were used in this study. Part 1: Apomorphine was injected in the control session and GES sessions. GESs with different parameters were applied in GES session. Gastric slow waves and emesis and behaviors suggestive of nausea were recorded in each session. Part 2: Each dog was anesthetized and given GESs with different parameters or sham stimulation for 15 min after baseline (5 min), respectively. The location of cerebral activation induced by GES was investigated by fMRI.

KEY RESULTS

Apomorphine induced emesis and behaviors suggestive of nausea, and gastric dysrhythmia. The emesis frequency in control session was 5.5 ± 0.99, and symptoms score was 22.17 ± 1.01. GES with short pulse and long pulse could not improve emesis and symptoms induced by apomorphine. The emesis frequency (4.5 ± 0.76 in short pulse and 6.33 ± 1.05 in long pulse) and symptoms scores had no significant difference compared to control session (each p > 0.05). GES with trains of short pulse reduced emesis time frequency (3.83 ± 0.7, p = 0.042 vs control) and symptoms score (p = 0.037 vs control) obviously. Brain fMRI showed that GES with short pulse and long pulse activated brain stem region, and trains of short pulse made amygdala and occipital lobe activation.

CONCLUSIONS & INFERENCES

Apomorphine induced emesis and gastric dysrhythmia. GES with trains of short pulses relieves emetic responses through activation of amygdala region.