Intratumoral and peritumoral radiomics based on contrast-enhanced MRI for preoperatively predicting treatment response of transarterial chemoembolization in hepatocellular carcinoma.

BACKGROUND: Noninvasive and precise methods to estimate treatment response and identify hepatocellular carcinoma (HCC) patients who could benefit from transarterial chemoembolization (TACE) are urgently required. The present study aimed to investigate the ability of intratumoral and peritumoral radiomics based on contrast-enhanced magnetic resonance imaging (CE-MRI) to preoperatively predict tumor response to TACE in HCC patients. METHODS: A total of 138 patients with HCC who received TACE were retrospectively included and randomly divided into training and validation cohorts at a ratio of 7:3. Total 1206 radiomics features were extracted from arterial, venous, and delayed phases images. The inter- and intraclass correlation coefficients, the spearman's rank correlation test, and the gradient boosting decision tree algorithm were used for radiomics feature selection. Radiomics models on intratumoral region (TR) and peritumoral region (PTR) (3 mm, 5 mm, and 10 mm) were established using logistic regression. Three integrated radiomics models, including intratumoral and peritumoral region (T-PTR) (3 mm), T-PTR (5 mm), and T-PTR (10 mm) models, were constructed using TR and PTR radiomics scores. A clinical-radiological model and a combined model incorporating the optimal radiomics score and selected clinical-radiological predictors were constructed, and the combined model was presented as a nomogram. The discrimination, calibration, and clinical utilities were evaluated by receiver operating characteristic curve, calibration curve, and decision curve analysis, respectively. RESULTS: The T-PTR radiomics models performed better than the TR and PTR models, and the T-PTR (3 mm) radiomics model demonstrated preferable performance with the AUCs of 0.884 (95%CI, 0.821-0.936) and 0.911 (95%CI, 0.825-0.975) in both training and validation cohorts. The T-PTR (3 mm) radiomics score, alkaline phosphatase, tumor size, and satellite nodule were fused to construct a combined nomogram. The combined nomogram [AUC: 0.910 (95%CI, 0.854-0.958) and 0.918 (95%CI, 0.831-0.986)] outperformed the clinical-radiological model [AUC: 0.789 (95%CI, 0.709-0.863) and 0.782 (95%CI, 0.660-0.902)] in the both cohorts and achieved good calibration capability and clinical utility. CONCLUSIONS: CE-MRI-based intratumoral and peritumoral radiomics approach can provide an effective tool for the precise and individualized estimation of treatment response for HCC patients treated with TACE.

Modified Two-Point Correction Method for Wide-Spectrum LWIR Detection System.

Non-uniformity commonly exists in the infrared focal plane, which behaves as the fixed-pattern noise (FPN) and seriously affects the image quality of long-wave infrared (LWIR) detection systems. The two-point correction (TPC) method is commonly used to reduce image FPN in engineering. However, when a wide-spectrum LWIR detection system calibrated with a black body is used to detect weak and small targets in the sky, FPN still appears in the image, affecting its uniformity. The effects of atmospheric transmittance characteristics of long-range paths on the non-uniformity of wide-spectrum long-wave infrared systems have not been studied. This paper proposes a modified TPC model based on spectral subdivision that introduces atmospheric transmittance. Additionally, the effects of atmospheric transmittance characteristics on the long-wave infrared non-uniform correction coefficient are analyzed. The experimental results for a black body scene and sky scene using a weak and small target detection system with a long-wave Sofradir FPA demonstrate that the wide-spectrum LWIR detection system fully considers atmospheric transmittance when performing calibration based on the TPC method, which can reduce the non-uniformity of the image.

Algorithm and its application for automatic measurement of the full-field isoclinic parameter by digital phase-shifting photoelasticity.

The photoelastic method is an experimental technique that combines optics and mechanics for a stress analysis. The photoelastic phase-shifting technique is different from the moiré, holography, and speckle phase-shifting techniques, which only need to measure one parameter. The photoelastic phase-shifting technique needs to assess isoclinic and isochromatic parameters, which affect each other, seriously hindering the development of the phase-shifting photoelasticity method. First, the interaction between the isoclinic and isochromatic parameters is analyzed in detail. Secondly, an algorithm is proposed to adjust the mutation and obtain the correct isoclinic parameter affected by the isochromatic parameter. This method can effectively eliminate the influence of the isochromatic parameter. The isoclinic parameter is consistent with the theoretical value, which verifies the effectiveness of this method. Finally, the photoelastic method uses the proposed algorithm to test the stress at different positions of the turbine blade root. Moreover, the bearing capacity of the turbine blade root is analyzed to provide support for the safe use and optimization design of the turbine.

A Novel Method of Aircraft Detection under Complex Background Based on Circular Intensity Filter and Rotation Invariant Feature.

Aircraft detection in remote sensing images (RSIs) has drawn widespread attention in recent years, which has been widely used in the military and civilian fields. While the complex background, variations of aircraft pose and size bring great difficulties to the effective detection. In this paper, we propose a novel aircraft target detection scheme based on small training samples. The scheme is coarse-to-fine, which consists of two main stages: region proposal and target identification. First, in the region proposal stage, a circular intensity filter, which is designed based on the characteristics of the aircraft target, can quickly locate the centers of multi-scale suspicious aircraft targets in the RSIs pyramid. Then the target regions can be extracted by adding bounding boxes. This step can get high-quality but few candidate regions. Second, in the stage of target identification, we proposed a novel rotation-invariant feature, which combines rotation-invariant histogram of oriented gradient and vector of locally aggregated descriptors (VLAD). The feature can characterize the aircraft target well by avoiding the impact of its rotation and can be effectively used to remove false alarms. Experiments are conducted on Remote Sensing Object Detection (RSOD) dataset to compare the proposed method with other advanced methods. The results show that the proposed method can quickly and accurately detect aircraft targets in RSIs and achieve a better performance.

Radiomics Analysis Based on Multiparametric MRI for Predicting Early Recurrence in Hepatocellular Carcinoma After Partial Hepatectomy.

BACKGROUND: Preoperative prediction of early recurrence (ER) of hepatocellular carcinoma (HCC) plays a critical role in individualized risk stratification and further treatment guidance. PURPOSE: To investigate the role of radiomics analysis based on multiparametric MRI (mpMRI) for predicting ER in HCC after partial hepatectomy. STUDY TYPE: Retrospective. POPULATION: In all, 113 HCC patients (ER, n = 58 vs. non-ER, n = 55), divided into training (n = 78) and validation (n = 35) cohorts. FIELD STRENGTH/SEQUENCE: 1.5T or 3.0T, gradient-recalled-echo in-phase T1 -weighted imaging (I-T1 WI) and opposed-phase T1 WI (O-T1 WI), fast spin-echo T2 -weighted imaging (T2 WI), spin-echo planar diffusion-weighted imaging (DWI), and gradient-recalled-echo contrast-enhanced MRI (CE-MRI). ASSESSMENT: In all, 1146 radiomics features were extracted from each image sequence, and radiomics models based on each sequence and their combination were established via multivariate logistic regression analysis. The clinicopathologic-radiologic (CPR) model and the combined model integrating the radiomics score with the CPR risk factors were constructed. A nomogram based on the combined model was established. STATISTICAL TESTS: Receiver operating characteristic (ROC) curve analysis was used to evaluate the discriminative performance of each model. The potential clinical usefulness was evaluated by decision curve analysis (DCA). RESULTS: The radiomics model based on I-T1 WI, O-T1 WI, T2 WI, and CE-MRI sequences presented the best performance among all radiomics models with an area under the ROC curve (AUC) of 0.771 (95% confidence interval (CI): 0.598-0.894) in the validation cohort. The combined nomogram (AUC: 0.873; 95% CI: 0.756-0.989) outperformed the radiomics model and the CPR model (AUC: 0.742; 95% CI: 0.577-0.907). DCA demonstrated that the combined nomogram was clinically useful. DATA CONCLUSION: The mpMRI-based radiomics analysis has potential to predict ER of HCC patients after hepatectomy, which could enhance risk stratification and provide support for individualized treatment planning. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 4.

A CDR-based approach to generate covalent inhibitory antibody for human rhinovirus protease.

Covalent target modulation with small molecules has been emerging as a promising strategy for drug discovery. However, covalent inhibitory antibody remains unexplored due to the lack of efficient strategies to engineer antibody with desired bioactivity. Herein, we developed an intracellular selection method to generate covalent inhibitory antibody against human rhinovirus 14 (HRV14) 3C protease through unnatural amino acid mutagenesis along the heavy chain complementarity-determining region 3 (CDR-H3). A library of antibody mutants was thus constructed and screened in vivo through co-expression with the target protease. Using this screening strategy, six covalent antibodies with proximity-enabled bioactivity were identified, which were shown to covalently target HRV14-3C protease with high inhibitory potency and exquisite selectivity. Compared to structure-based rational design, this library-based screening method provides a simple and efficient way for the discovery and engineering of covalent antibody for enzyme inhibition.

Depressive symptom as a mediator of the influence of self-reported sleep quality on falls: a mediation analysis.

Objectives: It is well known that sleep quality was associated with falls. This study aimed to examine whether the presence of depressive symptoms mediate the association of self-reported sleep quality with falls.Methods: Data of community-based study including 4,579 adults aged 60 years or older were analyzed. Information regarding sleep quality and falls was self-reported by participants using pre-designed questionnaires. The nine-item Patient Health Questionnaire (PHQ-9) without the sleep item was used to assess the presence of depressive symptoms. A bootstrapping approach was performed to explore whether the relationship between self-reported sleep quality and falls was partially mediated by depressive symptoms. The mediator was considered significant if the 95% confidence interval (CI) did not include 0.Results: Older adults with poor sleep quality had higher odds of falls than their counterparts with normal sleep. In the equation regressed falls on self-reported sleep quality and PHQ-9 score, the association between self-reported sleep quality and falls disappeared. Depressive symptoms partially mediated the association between self-reported sleep quality and falls based on the significance of indirect effect (ß = 0.15, 95% bootstrap CI = 0.08, 0.22).Conclusions: The presence of depressive symptoms might partially mediate the association of self-reported sleep quality with falls among older adults.

Application of cook balloon during aorta replacement in a pregnant Marfan-syndrome patient: a case report.

BACKGROUND: Aortic dissection is a rare and emergent condition. Aortic dissection during pregnancy is not much known but it is quite lethal to both mother and infant. Earlier reports published show that clinicians conducted hysterectomies during cesarean section to avoid anticoagulant-induced uterine bleeding during the following aortic surgery. CASE PRESENTATION: A woman (38, gravida 1, para 0) in the 37th gestational week suffered an acute, severe, sharp pain in the chest and back. She was diagnosed with Standford type A aortic dissection and suspected with Marfan syndrome. An emergency cesarean section was performed immediately to deliver the baby. Since the patient was on anticoagulants during aortic replacement, so Cook balloon was inserted into the uterus to prevent postpartum hemorrhage. This helped to maintain the uterus intact. Family genetic testing showed that the patient was a carrier of FBN1 mutation which was inherited from the patient's mother, and the newborn also carried the mutation. Hence the patient was concluded to be positive for Marfan syndrome. CONCLUSION: It is important that clinicians should pay attention to the possibility of aortic dissection in a pregnant woman with chest, abdominal or back pain. In this case study, we employed Cook balloon during cesarean section to avoid anticoagulant-induced uterine bleeding during the following aortic surgery.

Systematic Detection and Identification of Bioactive Ingredients from Citrus aurantium L. var. amara Using HPLC-Q-TOF-MS Combined with a Screening Method.

Bitter orange, Citrus aurantium L. var. amara (CAVA), is an important crop and its flowers and fruits are widely used in China as a food spice, as well as in traditional Chinese medicine, due to its health-promoting properties. The secondary metabolites that are present in plant-derived foods or medicines are, in part, responsible for the health benefits and desirable flavor profiles. Nevertheless, detailed information about the bioactive ingredients in CAVA is scarce. Therefore, this study was aimed at exploring the phytochemicals of CAVA by high performance liquid chromatography/quadrupole time-of-flight mass spectrometry (HPLC-Q-TOF-MS). Here, a systematic screening method combined with HPLC-Q-TOF-MS was presented. This technique was used to systematically screen metabolites, primarily from the complex matrix of CAVA, and to identify these compounds by their exact masses, characteristic fragment ions, and fragmentation behaviors. A total of 295 metabolites were screened by the screening method and 89 phytochemicals were identified in the flowers, fruits, roots, leaves, and branches of CAVA. For the first time, 69 phytochemicals (flavonoids, alkaloids, terpenoids, etc.) were reported from CAVA. The results highlight the importance of CAVA as a source of secondary metabolites in the food, medicine, and nutraceutical industries.

Correction: Liu, C., et al. A Novel System for Correction of Relative Angular Displacement between Airborne Platform and UAV in Target Localization. Sensors 2017, 17, 510.

The authors wish to make the following correction to this paper [...].

Seamline Determination Based on PKGC Segmentation for Remote Sensing Image Mosaicking.

This paper presents a novel method of seamline determination for remote sensing image mosaicking. A two-level optimization strategy is applied to determine the seamline. Object-level optimization is executed firstly. Background regions (BRs) and obvious regions (ORs) are extracted based on the results of parametric kernel graph cuts (PKGC) segmentation. The global cost map which consists of color difference, a multi-scale morphological gradient (MSMG) constraint, and texture difference is weighted by BRs. Finally, the seamline is determined in the weighted cost from the start point to the end point. Dijkstra's shortest path algorithm is adopted for pixel-level optimization to determine the positions of seamline. Meanwhile, a new seamline optimization strategy is proposed for image mosaicking with multi-image overlapping regions. The experimental results show the better performance than the conventional method based on mean-shift segmentation. Seamlines based on the proposed method bypass the obvious objects and take less time in execution. This new method is efficient and superior for seamline determination in remote sensing image mosaicking.

A Novel System for Correction of Relative Angular Displacement between Airborne Platform and UAV in Target Localization.

This paper provides a system and method for correction of relative angular displacements between an Unmanned Aerial Vehicle (UAV) and its onboard strap-down photoelectric platform to improve localization accuracy. Because the angular displacements have an influence on the final accuracy, by attaching a measuring system to the platform, the texture image of platform base bulkhead can be collected in a real-time manner. Through the image registration, the displacement vector of the platform relative to its bulkhead can be calculated to further determine angular displacements. After being decomposed and superposed on the three attitude angles of the UAV, the angular displacements can reduce the coordinate transformation errors and thus improve the localization accuracy. Even a simple kind of method can improve the localization accuracy by 14.3%.

Airborne Infrared and Visible Image Fusion Combined with Region Segmentation.

This paper proposes an infrared (IR) and visible image fusion method introducing region segmentation into the dual-tree complex wavelet transform (DTCWT) region. This method should effectively improve both the target indication and scene spectrum features of fusion images, and the target identification and tracking reliability of fusion system, on an airborne photoelectric platform. The method involves segmenting the region in an IR image by significance, and identifying the target region and the background region; then, fusing the low-frequency components in the DTCWT region according to the region segmentation result. For high-frequency components, the region weights need to be assigned by the information richness of region details to conduct fusion based on both weights and adaptive phases, and then introducing a shrinkage function to suppress noise; Finally, the fused low-frequency and high-frequency components are reconstructed to obtain the fusion image. The experimental results show that the proposed method can fully extract complementary information from the source images to obtain a fusion image with good target indication and rich information on scene details. They also give a fusion result superior to existing popular fusion methods, based on eithers subjective or objective evaluation. With good stability and high fusion accuracy, this method can meet the fusion requirements of IR-visible image fusion systems.

Two-UAV Intersection Localization System Based on the Airborne Optoelectronic Platform.

To address the limitation of the existing UAV (unmanned aerial vehicles) photoelectric localization method used for moving objects, this paper proposes an improved two-UAV intersection localization system based on airborne optoelectronic platforms by using the crossed-angle localization method of photoelectric theodolites for reference. This paper introduces the makeup and operating principle of intersection localization system, creates auxiliary coordinate systems, transforms the LOS (line of sight, from the UAV to the target) vectors into homogeneous coordinates, and establishes a two-UAV intersection localization model. In this paper, the influence of the positional relationship between UAVs and the target on localization accuracy has been studied in detail to obtain an ideal measuring position and the optimal localization position where the optimal intersection angle is 72.6318°. The result shows that, given the optimal position, the localization root mean square error (RMS) will be 25.0235 m when the target is 5 km away from UAV baselines. Finally, the influence of modified adaptive Kalman filtering on localization results is analyzed, and an appropriate filtering model is established to reduce the localization RMS error to 15.7983 m. Finally, An outfield experiment was carried out and obtained the optimal results: σ B = 1.63 × 10 - 4 ( ° ) , σ L = 1.35 × 10 - 4 ( ° ) , σ H = 15.8 ( m ) , σ s u m = 27.6 ( m ) , where σ B represents the longitude error, σ L represents the latitude error, σ H represents the altitude error, and σ s u m represents the error radius.

Feasibility of spectral imaging with low-concentration contrast medium in abdominal CT angiography of obese patients.

OBJECTIVE: To explore the application value of dual-energy spectral imaging scanning with low radiation dose and low-concentration contrast medium (270 mg I/mL) in abdominal CT angiography (CTA) of obese patients. METHODS: A total of 127 obese patients (BMI≥25 kg/m(2) and waist circumference ≥900 mm) referred for abdominal CTA were prospectively enrolled in the study. The patients were divided into two groups; in group A (n=69), a spectral imaging scan mode and 270 mg I/mL iodine concentration contrast medium was used, and in group B (n=58), a conventional imaging scan mode using 120 kVp and 350 mg I/mL iodine concentration contrast medium was used. The image quality of the right renal artery in the two groups was evaluated by two observers using a 5-point scale, and the scores were compared using the Mann-Whitney U-test; the inter-observer agreement for the scores was analysed using the Kappa test. The CT values of the abdominal aorta, the superior mesenteric artery, the common hepatic artery and the splenic artery, and the CT value and standard deviation (SD) of the erector spinae at the level of the right renal hilum in groups A and B were measured by two observers; the inter-observer agreement of the measurement data was analysed using the inter-class correlation coefficient test. The following parameters were compared between the two groups using an independent sample t-test: the CT values of the abdominal aorta and its main branches; the image contrast-to-noise ratio (CNR) and figure of merit (FOM) of the abdominal aorta; the CT dose index (CTDIvol ); the dose length product (DLP); and the total iodine intake of the patients. P<.05 suggested a statistically significant difference. RESULTS: The image scores of the right renal artery in groups A (4.59±0.60) and B (4.53±0.63) were the same (P=.57), with good inter-observer agreement. The CT values of the abdominal aorta, the superior mesenteric artery, the common hepatic artery and the splenic artery were >300 HU in both the groups; there was no statistically significant difference between the two groups (all P>.05), and inter-observer agreement was also good. Group A had significantly higher CNR and FOM values in the abdominal aorta than group B (all P<.001). Compared with group B, the CTDIvol and DLP values in group A were decreased by 46% and 35%, respectively. The total iodine intake for patients in group A was 27 g, 23% lower than the 35 g intake for patients in group B. CONCLUSION: Compared with conventional CT, spectral CT imaging significantly reduces both radiation dose and contrast dose while maintaining image quality in abdominal CTA for patients with central obesity and high BMI.

Real-Time Multi-Target Localization from Unmanned Aerial Vehicles.

In order to improve the reconnaissance efficiency of unmanned aerial vehicle (UAV) electro-optical stabilized imaging systems, a real-time multi-target localization scheme based on an UAV electro-optical stabilized imaging system is proposed. First, a target location model is studied. Then, the geodetic coordinates of multi-targets are calculated using the homogeneous coordinate transformation. On the basis of this, two methods which can improve the accuracy of the multi-target localization are proposed: (1) the real-time zoom lens distortion correction method; (2) a recursive least squares (RLS) filtering method based on UAV dead reckoning. The multi-target localization error model is established using Monte Carlo theory. In an actual flight, the UAV flight altitude is 1140 m. The multi-target localization results are within the range of allowable error. After we use a lens distortion correction method in a single image, the circular error probability (CEP) of the multi-target localization is reduced by 7%, and 50 targets can be located at the same time. The RLS algorithm can adaptively estimate the location data based on multiple images. Compared with multi-target localization based on a single image, CEP of the multi-target localization using RLS is reduced by 25%. The proposed method can be implemented on a small circuit board to operate in real time. This research is expected to significantly benefit small UAVs which need multi-target geo-location functions.

Apparent diffusion coefficient measurement by diffusion weighted magnetic resonance imaging is a useful tool in differentiating renal tumors.

BACKGROUND: To determine the clinical value of apparent diffusion coefficient (ADC) measurement by diffusion weighted magnetic resonance imaging (DW-MRI) in differentiating renal tumors. METHODS: Electronic databases were searched using combinations of keywords and free words relating to renal tumor, ADC and DW-MRI. Based on carefully selected inclusion and exclusion criteria, relevant case-control studies were identified and the related clinical data was acquired. Statistical analyses were performed using STATA 12.0 (Stata Corporation, College station, TX). RESULTS: Sixteen case-control studies were ultimately included in the present meta-analysis. These 16 high quality studies contained a combined total of 438 normal renal tissues and 832 renal tumor lesions (597 malignant and 235 benign). The results revealed that ADC values of malignant renal tumor tissues were markedly lower than normal renal tissues and benign renal tumor tissues. ADC values of benign renal tumor tissues were also significantly lower than normal renal tissue. CONCLUSIONS: ADC measurement by DW-MRI provided clinically useful information on the internal structure of renal tumors and could be an important radiographic index for differentiation of malignant renal tumors from benign renal tumors.

Use of enhanced T2 star-weighted angiography (ESWAN) and R2* values to distinguish ovarian cysts due to endometriosis from other causes.

PURPOSE: To evaluate the feasibility of enhanced T2 star-weighted angiography (ESWAN) in differentiating endometrial from non-endometrial cysts. METHODS: Forty-nine patients with 60 histopathologically proven ovarian cystic lesions underwent pelvic MRI including T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), liver acquisition with volume acceleration, and ESWAN. Ovarian cystic lesions were divided into endometrial cysts (group 1; n = 28), pyosalpinx and hydrosalpinx (group 2; n = 13), and ovarian cystic and cystic-solid tumors (group 3; n = 19). R2* (effective transverse relaxation rate) values were measured and pairwise comparison of the R2* values among the three groups was made using Kruskal-Wallis test. Receiver operating characteristic curves were used to calculate cutoff values and performance of R2* values for distinguishing among groups. T1WI signal intensity and R2* value were also compared using area under curve values. RESULTS: R2* values for group 1 were statistically higher than groups 2 and 3 (15.37, 1.40, and 1.79 Hz, respectively; P < 0.001). The cutoff value for R2* was 7.43 Hz with a sensitivity, specificity, PPV, NPV, and accuracy of 96.43, 87.50, 87.10, 96.55, and 91.67%, respectively. There was no significant difference between the R2* value and T1WI in diagnosing endometrial cysts. CONCLUSIONS: The R2* value provides an effective way to discriminate endometrial cysts from other ovarian cystic lesions.

[Virtual unehanced image in the single-source dual energy CT for evaluation of renal cell carcinoma:a preliminary study].

OBJECTIVE: To qualitatively and quantitatively evaluate the feasibility of CT virtual unenhanced (VUE) spectral imaging in renal cell carcinoma. METHOD: Thirty-six patients with histopathologically proven renal cell carcinoma underwent gemstone spectral imaging (GSI) including ture unenhanced (TUE), arterial, cortex and medullary phase acquisitions. The triphasic GSI dataset was sent to workstation and 3 sets of VUE images (including VUE a, VUE c, VUE m) were obtained by subtract iodine from iodine-water images in the triphasic enhanced GSI images, respectively. The quality of VUE s and TUE images was evaluated on a five-point scale.Interobserver agreement with regard to image quality was assessed using Cohen's Kappa, and four groups of image quality was compared with ANOVA analysis. The contrast-to-noise ratio (CNR) of mass-to-kidney in the TUE and VUE s images was calculated, and difference between these four datasets was compared with ANOVA analysis. Using appearance of masses on triphasic images as a standard, the masses detection ratio of four groups was calculated and compared with chi-square test. RESULTS: Interobserver agreement with regard to image quality was excellent (κ>0.600). There was no significant difference among the image quality of TUE and triphasic images of VUEs (P>0.05). The CNR of TUE (0.7 ± 0.6) was significant worse than that of triphasic images (1.7 ± 1.0, 1.9 ± 1.2, 2.5 ± 1.4, respectively) (P<0.05). There was no significant difference among the CNR of triphasic images (P>0.05). CONCLUSION: VUE images obtain from triphasic phases may be a surrogate for conventional unenhanced scan in renal cell carcinoma diagnosis.

[A systematic evaluation on the quality of Meta-analysis in articles published in National Medical Journal of China from 1998 to 2014].

OBJECTIVE: To assess qualities on methodologies and reporting on Meta-analysis used in papers being published in National Medical Journal of China. METHODS: Computerized literature searching was performed in Wangfang Medical Online to collect articles that Meta-analysis was used in the National Medical Journal of China since January 1998 until October 2014. Manual retrieval was also conducted.Qualities on methodologies and reporting were evaluated by both Assessment of Multiple Systematic Reviews (AMSTAR) and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) scales. RESULTS: A total of 74 papers were included. The results on the qualities of methodology evaluation in these papers were 3 to 10 (median 7) scores, 10 articles (13.5%) were rated as high, 61 articles (82.4%) as moderate and 3 articles (4.1%) as low. No statistically significant difference existed in each year of AMSTAR score (χ(2) = 10.205, P = 0.423). The titles of AMSTAR scales with a lower coincidence rate were "Was a list of studies (included and excluded) provided?", "Was the conflict of interest stated?", "Was the status of publication (i.e.grey literature) used as an inclusion criterion?" and "Was the likelihood of publication bias assessed?". The results on the qualities of reporting evaluation in these papers were 5.5 to 26 (median 20) scores, 9 articles (12.2%) scored <15 points, 39 articles (52.7%) 15.5-21 points and 26 articles (35.1%) 21.5-27 points. There was statistically significant difference in each year of PRISMA score (F = 4.301, P = 0.000). And the year 2010 was the highest one. The titles of PRISMA scales with a lack of comprehensive reports were "Structured summary", "Objectives of introduction", "Protocol & registration", "Data collection process", "Data items", "Risk of bias in individual studies", "Risk of bias across studies", "Additional analyses", "Study selection","Risk of bias within studies", "Conclusion limitations", "Conclusions" and "Funding support" etc. CONCLUSIONS: Articles of Meta-analysis published in National Medical Journal of China have a high quality so as to provide rationales for clinical decision-making. However, both of qualities on methodology and reports sill call for continual improvements.