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Objective:To explore the value of the deep learning image reconstruction (DLIR) algorithm in improving the CT image quality of abdominal phantoms under different radiation doses by comparing the DLIR algorithm with the conventional Adaptive Statistical Iterative Reconstruction-V (ASIR-V) technique.Methods:Two groups with tube voltages of 100 kV and 120 kV (also referred to as the 100 kV and 120 kV groups, respectively) were involved. Each group was further divided into six subgroups based on different volumetric CT dose indices (CTDI vol: 2, 4, 6, 8, 10 and 15 mGy). Subsequently, CT images based on the filtered back projection (FBP) algorithm were obtained and were then reconstructed using the ASIR-V algorithm with different weights (ASIR-V 50%, 80%, and 100%) and the DLIR algorithm with different levels (DLIR-L, M, and -H). As a result, 84 groups of images were obtained in total. Afterward, this study compared and analyzed the variations in CT values, noise, signal-to-noise ratios (SNRs), contrast-to-noise ratios (CNRs), and subjective scores of various parts in various CTDI vol subgroups under different reconstruction conditions. In addition, the subjective scores of the image quality were compared using the Kruskal-Wallis H test, while objective indices and radiation doses were compared through the univariate analysis of variance (ANOVA) and the paired t test. Results:Under the same tube voltage, there were statistically significant differences in the noise, SNRs, and CNRs of various parts in various CTDI vol subgroups under different reconstruction conditions ( F = 415.39, 315.30, P < 0.001), while there was no statistically significant difference in the noise, SNRs, and CNRs of images constructed using ASIR-V 50% and DLIR-L ( P > 0.05). Under different tube voltages, the subjective scores of both groups show statistically significant differences (100 kV group: H = 13.47, P = 0.036; 120 kV group: H = 12.99, P = 0.043). Moreover, two physicians offered consistent subjective scores, with Kappa values > 0.70. Among these images, DLIR-H images showed the highest subjective scores, followed by DLIR-M and ASIR-V 50% images, which had roughly consistent subjective scores. Moreover, the subjective scores of the 100 kV group were slightly higher than those of the 120 kV group. With the ASIR-V 50% images of the subgroup with a CTDI vol of 15 mGy as references, the DLIR-L, -M, and -H reduced radiation doses by more than 30%, 70% and 85%, respectively on the premise that diagnostic requirements were met. Conclusions:The DLIR algorithm can not only significantly reduce the image noise and improve the image quality, but also effectively decrease the radiation doses on the premise of meeting the diagnostic requirements. It is recommended that 100 kV tube voltage combined with a medium- or high-level DLIR algorithm should be applied to low-dose abdominal CT scans in clinical applications.
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Objective:To evaluate the value of preoperative prediction of vessel invasion (VI) of locally advanced gastric cancer by machine learning model based on the venous phase enhanced CT radiomics features.Methods:A retrospective analysis of 296 patients with locally advanced gastric cancer confirmed by pathology in the First Affiliated Hospital of Zhengzhou University from July 2011 to December 2020 was performed. The patients were divided into VI positive group ( n=213) and VI negative group ( n=83) based on pathological results. The data were divided into training set ( n=207) and test set ( n=89) according to the ratio of 7∶3 with stratification sampling. The clinical characteristics of patients were recorded, and the independent risk factors of gastric cancer VI were screened by multivariate logistic regression. Pyradiomics software was used to extract radiomic features from the venous phase enhanced CT images, and the minimum absolute shrinkage and selection algorithm (LASSO) was used to screen the features, obtain the optimal feature subset, and establish the radiomics signature. Four machine learning algorithms, including extreme gradient boosting (XGBoost), logistic, naive Bayes (GNB), and support vector machine (SVM) models, were used to build prediction models for the radiomics signature and the screened clinical independent risk factors. The efficacy of the model in predicting gastric cancer VI was evaluated by the receiver operating characteristic curve. Results:The degree of differentiation (OR=13.651, 95%CI 7.265-25.650, P=0.003), Lauren′s classification (OR=1.349, 95%CI 1.011-1.799, P=0.042) and CA199 (OR=1.796, 95%CI 1.406-2.186, P=0.044) were independent risk factors for predicting the VI of locally advanced gastric cancer. Based on the venous phase enhanced CT images, 864 quantitative features were extracted, and 18 best constructed radiomics signature were selected by LASSO. In the training set, the area under the curve (AUC) of XGBoost, logistic, GNB and SVM models for predicting gastric cancer VI were 0.914 (95%CI 0.875-0.953), 0.897 (95%CI 0.853-0.940), 0.880 (95%CI 0.832-0.928) and 0.814 (95%CI 0.755-0.873), respectively, and in the test set were 0.870 (95%CI 0.769-0.971), 0.877 (95%CI 0.788-0.964), 0.859 (95%CI 0.755-0.961) and 0.773 (95%CI 0.647-0.898). The logistic model had the largest AUC in the test set. Conclusions:The machine learning model based on the venous phase enhanced CT radiomics features has high efficacy in predicting the VI of locally advanced gastric cancer before the operation, and the logistic model demonstrates the best diagnostic efficacy.
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Objective:To investigate the value of spectral CT based iodine concentration (IC) parameters for preoperative prediction of lymphovascular invasion (LVI) in gastric cancer.Methods:Between January 2021 and November 2021, 266 patients diagnosed as gastric adenocarcinomas by endoscopy and undergoing gastrectomy at the Affiliated Cancer Hospital of Zhengzhou University were recruited prospectively. They were divided into LVI and non-LVI groups according to pathological reports. Triple phase contrasted enhanced CT scans, including arterial phase (AP), venous phase (VP) and delayed phase (DP) were performed on a spectral CT platform within one week before surgery. The IC of gastric cancer lesions at three enhanced phases were measured based on iodine maps, and the normalized IC (nIC) was calculated. The thickness of the tumor was measured. Clinicopathological features were collected, including ulceration, pathological tumor staging (pT), pathological node staging (pN), histodifferentiation, Lauren subtype, perineural invasion (PNI), positive node numbers and positive node ratio. Student′s t tes t or Mann-Whitney U test were used to compare the differences of continuous variables between the two groups, while Chi-square test or Fisher′s exact test was used for categorical data. Multivariable logistic regression analysis was used to screen independent risk factors of LVI, and to build a combined parameter based on risk factors. The receiver operating characteristic curve analysis was performed to determine the predictive efficacy of IC parameters and the combined parameter for LVI. DeLong′s test was used to compare the differences among different area under the curve (AUC). Results:There were statistical differences in tumor thickness, ulceration, pT, pN, histodifferentiation, positive node numbers, positive node ratio, Lauren subtype and PNI between LVI and non-LVI groups ( P<0.05). The values of IC VP, IC DP, nIC VP, nIC DP in LVI group were statistically higher than those in non-LVI group ( t=3.77, 4.23, 4.25, 6.12, all P<0.001), with the AUC (95%CI) of 0.674 (0.610-0.738), 0.677 (0.614-0.741), 0.731 (0.671-0.792), 0.700 (0.636-0.764) for predicting LVI, respectively. Multivariable logistic regression analysis revealed that tumor thickness (OR=1.148, 95%CI 1.085-1.237, P<0.001) and nIC VP (OR=209.904, 95%CI 14.874-644.362, P<0.001) were independent predictors for LVI, the combined parameter incorporating these two factors yielded an AUC (95%CI) of 0.790 (0.736-0.937), which was statistically higher than any single parameter of IC VP, IC DP, nIC VP and nIC DP ( Z=3.07, 3.29, 2.10, 2.60, P=0.002, 0.001, 0.036, 0.009). Conclusion:The IC and nIC values of gastric cancer lesions derived from the VP and DP on spectral CT can effectively predict LVI status in gastric adenocarcinomas, and the combination of nIC VP and tumor thickness can further improve the predictive efficacy.
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Objective:To construct of a computed tomography (CT) based radiomics model for predicting the prognosis of patients with gastric neuroendocrine neoplasm (GNEN) and inves-tigate its application value.Methods:The retrospective cohort study was conducted. The clinico-pathological data of 182 patients with GNEN who were admitted to 2 medical centers, including the First Affiliated Hospital of Zhengzhou University of 124 cases and the Affiliated Cancer Hospital of Zhengzhou University of 58 cases, from August 2011 to December 2020 were collected. There were 130 males and 52 females, aged 64(range, 56-70)years. Based on random number table, all 182 patients were divided into the training dataset of 128 cases and the validation dataset of 54 cases with a ratio of 7:3. All patients underwent enhanced CT examination. Observation indicators: (1) construction and validation of the radiomics prediction model; (2) analysis of prognostic factors for patients with GNEN in the training dataset; (3) construction and evaluation of the prediction model for prognosis of patients with GNEN. Measurement data with skewed distribution were represented as M(range), and comparison between groups was conducted using the Mann-Whitney U test. Count data were described as absolute numbers, and the chi-square test, corrected chi-square test or Fisher exact probability were used for comparison between groups. The Kaplan-Meier method was used to calculate survival rate and draw survival curve, and the Log-rank test was used for survival analysis. The COX regression model was used for univariate and multivariate analyses. The R software (version 4.0.3) glmnet software package was used for least absolute shrinkage and selection operator (LASSO)-COX regression analysis. The rms software (version 4.0.3) was used to generate nomogram and calibration curve. The Hmisc software (version 4.0.3) was used to calculate C-index values. The dca.R software (version 4.0.3) was used for decision curve analysis. Results:(1) Construction and valida-tion of the radiomics prediction model. One thousand seven hundred and eighty-one radiomics features were finally extracted from the 182 patients. Based on the feature selection using intra-group correlation coefficient >0.75, and the reduce dimensionality using LASSO-COX regression analysis, 14 non zero coefficient radiomics features were finally selected from the 1 781 radiomics features. The radiomics prediction model was constructed based on the radiomics score (R-score) of these non zero coefficient radiomics features. According to the best cutoff value of the R-score as -0.494, 128 patients in the training dataset were divided into 64 cases with high risk and 64 cases with low risk, 54 patients in the validation dataset were divided into 35 cases with high risk and 19 cases with low risk. The area under curve (AUC) of radiomics prediction model in predicting 18-, 24-, 30-month overall survival rate of patients in the training dataset was 0.83[95% confidence interval ( CI ) as 0.76-0.87, P<0.05], 0.84(95% CI as 0.73-0.91, P<0.05), 0.91(95% CI as 0.78-0.95, P<0.05), respectively. The AUC of radiomics prediction model in predicting 18-, 24-, 30-month overall survival rate of patients in the validation dataset was 0.84(95% CI as 0.75-0.92, P<0.05), 0.84 (95% CI as 0.73-0.91, P<0.05), 0.86(95% CI as 0.82-0.94, P<0.05), respectively. (2) Analysis of prognostic factors for patients with GNEN in the training dataset. Results of multivariate analysis showed gender, age, treatment method, tumor boundary, tumor T staging, tumor N staging, tumor M staging, Ki-67 index, CD56 expression were independent factors influencing prognosis of patients with GNEN in the training dataset ( P<0.05). (3) Construction and evaluation of the prediction model for prognosis of patients with GNEN. The clinical prediction model was constructed based on the independent factors influen-cing prognosis of patients with GNEN including gender, age, treatment method, tumor boundary, tumor T staging, tumor N staging, tumor M staging, Ki-67 index, CD56 expression. The C-index value of clinical prediction model in the training dataset and the validation dataset was 0.86 (95% CI as 0.82-0.90) and 0.80(95% CI as 0.72-0.87), respectively. The C-index value of radiomics prediction model in the training dataset and the validation dataset was 0.80 (95% CI as 0.74-0.86, P<0.05) and 0.75(95% CI as 0.66-0.84, P<0.05), respectively. The C-index value of clinical-radiomics combined prediction model in the training dataset and the validation dataset was 0.88(95% CI as 0.85-0.92) and 0.83 (95% CI as 0.77-0.89), respectively. Results of calibration curve show that clinical prediction model, radiomics prediction model and clinical-radiomics combined prediction model had good predictive ability. Results of decision curve show that the clinical-radiomics combined prediction model is superior to the clinical prediction model, radiomics prediction model in evaluating the prognosis of patients with GNEN. Conclusions:The predection model for predicting the prognosis of patients with GNEN is constructed based on 14 radiomics features after selecting. The prediction model can predict the prognosis of patients with GNEN well, and the clinical-radiomics combined prediction model has a better prediction efficiency.
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Objective:To explore the clinical efficacy of CT-guided 125I seed implantation in patients with oligometastatic non-small cell lung cancer (NSCLC) harboring epidermal growth factor receptor (EGFR) activating mutations (EGFRm+ ) without progression after first-line EGFR-tyrosine kinase inhibitors (TKIs) treatment. Methods:From January 2015 to January 2019, 89 eligible patients (38 males, 51 females; age: (62±11) years) in the First Affiliated Hospital of Zhengzhou University were retrospectively analyzed. They were divided into 2 groups according to different treatment methods. The 125I seeds were implanted for oligometastatic lesions and/or primary tumors without progression after first-line EGFR-TKIs therapy in local consolidation treatment group (Group A, n=32). The maintenance treatment group (Group B, n=57) only received EGFR-TKIs until disease progression. The progression-free survival (PFS) and overall survival (OS) of the 2 groups were estimated by Kaplan-Meier curves, and were compared by using log-rank test. Complications in Group A were observed. Results:The follow-up time of the group A and group B were 36.5(31.0, 43.3) months and 30.0(24.0, 35.0) months respectively. The median PFS and OS in group A were 15.0(95% CI: 12.8-17.2 ) months and 37.0(95% CI: 33.9-40.1) months, both of which were significantly longer than those in group B (12.0(95% CI: 10.9-13.1) months and 31.0(95% CI: 28.9-33.1) months; χ2 values: 8.80, 7.15, P values: 0.003, 0.007). In Group A, the total incidence of complications in CT-guided 125I seed implantation was 21.9%(7/32), and the common complications and adverse events were pneumothorax and hemoptysis. Only 1 patient underwent chest tube insertion, and the rest were treated with conservative treatment. No operation related death occurred. Conclusion:CT-guided 125I seed implantation is safe and feasible for patients with EGFRm+ oligometastatic NSCLC without progression after first-line EGFR-TKIs treatment, and can prolong the PFS and OS of patients.
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Objective:To explore the value of multiphasic CT-based radiomics signature in predicting the invasive behavior of pancreatic solid pseudopapillary neoplasm (pSPN).Methods:The multiphasic CT images of patients with pSPN confirmed by postoperative pathology in the First Affiliated Hospital of Zhengzhou University from January 2012 to January 2021 were analyzed retrospectively. There were 23 cases of invasiveness and 59 cases of non-invasiveness. The region of interest(ROI) was artificially delineated layer by layer in the plain scan, arterial-phase and venous-phase images, respectively. The 1 316 image features were extracted from each ROI. The data set was divided into training and validation sets with a ratio of 7∶3 by stratified random sampling, and synthetic minority oversampling technique (SMOTE) algorithm was used for oversampling in the training set to generate invasive and non-invasive balanced data for building the training model. The constructed model was validated in the validation set. The receiver operating characteristic(ROC) analysis was used to evaluate model performance and the Delong′s test was applied to compare the area under the ROC curve (AUC) of different predict models. The improvement for classification efficiency of each independent model or their combinations were also assessed by net reclassification improvement (NRI) and integrated discrimination improvement (IDI) indices.Results:After feature extraction, 2, 6 and 3 features were retained to construct plain-scanned model, arterial-phase and venous-phase models, respectively. Seven independent-phase and combined-phase models were established. Except the plain-scanned model, the AUC values of other models were greater than 0.800. The arterial-phase model had the best efficiency for classification among all independent-phase models. The AUC values of arterial-phase model in the SMOTE training and validation sets were 0.913 and 0.873, respectively. By combining the radiomics signature of the arterial-phase and venous-phase models, the AUC values of training and validation sets increased to 0.934 and 0.913 respectively. There were no significant differences of the AUC values between the scan-arterial venous-phase model and arterial venous-phase model in both training and validation sets (both P>0.05). The NRI and IDI indexes showed that the combined form of plain-scan model and arterial-venous-phase model could not significantly improve the classification efficiency in the validation set (both NRI and IDI<0). Conclusions:The arterial-phase CT-based radiomics model has a good predictive performance in the invasive behavior of pSPN, and the combination with a venous-phase radiomics model can further improve the model performance.
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Objective:To understand the clinical features and computed tomography (CT) imaging performance of mediastinal giant malignant synovial sarcoma (SS) and to improve the clinicians′ diagnosis and treatment of this disease.Methods:We report the clinical data of 2 cases of primary mediastinal giant malignant SS, and reviews the literature for CT presentation and differential diagnosis.Results:Primary giant malignant SS of mediastinum is rare in clinic. CT showed irregular cystic and solid mass with mural nodules, adjacent osteolytic destruction, unclear boundary with adjacent tissues. The enhancement showed that the solid components of the tumor and mural nodules were enhanced, while the cystic necrosis area had no enhanced uneven enhancement. The two cases in this paper showed " borehole-like" growth above the clavicle and growth into the left thoracic cavity, with pulmonary metastasis and lymphatic metastasis respectively.Conclusions:Mediastinal malignant SS is a rare disease with high malignancy and easy to metastasize, which emphasizes " early detection, early diagnosis and early treatment" . It should be taken into account in the differential diagnosis of mediastinal tumors, but the confirmation of diagnosis needs to be combined with pathological and immunohistochemical findings. Clinicians need to take advantage of imaging examinations to provide auxiliary guidance on the diagnosis, metastasis assessment and surgical treatment options of SS.
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Objective:To assess the ability of the acute physiology and chronic health evaluation Ⅱ (APACHEⅡ) and trauma-injury severity score (TRISS) in predicting mortality in intensive care unit (ICU) trauma patients.Methods:Databases of PubMed, Cochrane Library, SinoMed, CNKI were retrieved from January 1980 to December 2020. The ability of the APACHE Ⅱ and the TRISS to predict mortality in the ICU trauma patients was compared in the retrieval literatures. The relevant literatures were screened by two researchers independently. The data of the included literatures were extracted, and the quality of the included literatures was evaluated. MetaDiSc 1.4 software was used to test the heterogeneity among studies. Meta-analysis was performed on diagnostic accuracy indicators and the summary receiver operator characteristics curve (SROC curve) was fitted. The area under SROC curve (AUC) of the two scores was compared. Deek test was used to analyze literature publication bias.Results:Six studies were selected with 4 054 patients involved with medium and high quality. Meta-analysis results showed that APACHE Ⅱ and TRISS had low sensitivity [the pooled sensitivity and 95% confidence interval (95% CI) was 0.48 (0.41-0.55) and 0.51 (0.41-0.62)], high specificity [the pooled specificity and 95% CI was 0.96 (0.93-0.97) and 0.98 (0.95-0.99)], the pooled diagnostic odds ratio ( DOR) and 95% CI was 20 (14-28) and 46 (18-120), and overall good performance in terms of AUC [the AUC and 95% CI was 0.79 (0.75-0.82) and 0.80 (0.76-0.83)] in predicting the prognosis of ICU trauma patients. There was no statistical difference in AUC between the two scores ( Z = 1.542, P > 0.05). Deek funnel plot showed little publication bias. Conclusion:Both APACHE Ⅱ and TRISS scores could accurately predict mortality in ICU trauma patients.
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Objective:To use quantitative computed tomography (QCT) technology to measure the bone mineral density of the spine of the Chinese healthy population, and to explore its correlation with hemoglobin and serum albumin.Methods:The data in this study came from the China Health Quantitative CT Big Data Project (China Biobank). The spine bone density was measured by using QCT Pro Image Analysis System and all cooperating centers used the European spine phantom (NO.145) for quality control. Total of 50 053 healthy persons who met the criteria for entry were selected as the research subjects. The subjects were divided into 7 groups according to age. The general data, spine bone density, serum albumin, hemoglobin of the subjects were collected. The single-factor analysis of variance, Pearson correlation analysis and multi-classification logistic regression model were applied to analyze the correlation between bone density and hemoglobin and serum albumin.Results:The bone mineral density of healthy people decreased with age ( P<0.05), and there were significant differences in hemoglobin, serum albumin and body mass index (BMI) among different age groups (all P<0.05). Linear correlation analysis showed that there were positive correlation between bone mineral density and hemoglobin in healthy males in different age groups ( r=0.086, 0.101, 0.076, 0.090, 0.072, 0.123, 0.100, all P<0.01). There were negative correlation between bone mineral density and hemoglobin in certain age groups in women (40-49 years group: r=-0.027; 70-79 yearsgroup: r=-0.077; both P<0.05). And corelation were found between bone mineral density and serum levels of albumin in certain age groups of healthy subjects (among men, 30-39 years group: r=-0.048; 40-49 years group, r=-0.027; 70-79 years group, r=-0.051; among women, 30-39 years group: r=-0.044; 40-49 years group, r=-0.042; 50-59 years group, r=-0.086; 70-79 years group, r=-0.070; all P<0.05). After adjusting for age and BMI, the multi-category logistic regression analysis showed that the hemoglobin level was protective factor of normal bone density ( OR=1.022, 95% CI:1.017-1.027) and decreased bone density ( OR=1.012, 95% CI:1.007-1.016) in healthy males, and the serum albumin was risk factor for normal bone density ( OR=0.926, 95% CI:0.905-0.948) and decreased bone density ( OR=1.006, 95% CI:0.951-1.011) in healthy women. Conclusion:There is a correlation between bone mineral density and hemoglobin and serum albumin in Chinese healthy population. Hemoglobin is a protective factor for bone mineral density in men, and serum albumin is a risk factor for bone mineral densityin women.
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Objective:To establish the normal reference value of lumbar bone mineral density (BMD) under quantitative CT (QCT) in Chinese healthy adult females and to explore the regional differences.Methods:Total of 35 431 healthy women who met the inclusion criteria of Chinese health quantitative CT big data program were selected in this study. The BMD of the central plane of L 1 and L 2 vertebrae was measured by Mindways′s QCT system, and the mean value was taken. One-way analysis of variance was used to compare the BMD differences of lumbar vertebrae in women of different ages and regions. The subjects were grouped by an age interval of 10 years, and the level of BMD in different regions of the same age group were compaired. Results:The peak BMD of Chinese healthy adult women appeared in the age group of 20-29 years (Northeast China(183.01±24.58) mg/cm 3, North China (188.93±24.80) mg/cm 3, East China (187.54±27.71) mg/cm 3, South China (186.22±33.72) mg/cm 3, Central China (176.33±24.91) mg/cm 3, Southwest China(182.25±28.00) mg/cm 3), and then it decreased with age. The level of BMD in different regions decreased with the age. Before the age of 70 years, BMD in Central and Southwest China was always at a low level((176.23±24.91) to (90.38±28.12) mg/cm 3, 182.25±28.00 to (88.55±25.68) mg/cm 3), lower than those in Northeast China ((183.01±24.58) to (99.69±27.85) mg/cm 3), North China ((188.93±24.80) to (95.89±26.12) mg/cm 3), East China ((187.54±27.71) to (95.65±27.86) mg/cm 3). After 70 years of age, BMD tended to be the same in different regions ( P>0.05). The BMD values in Central China and Southwest China were similar in the age group of 40-60 years ( P>0.05). The BMD values in the health adult femles in the age group of 60 years in different regions of Chinawere all lower than those of bone mass abnormality (all P<0.05). The detection rate of osteoporosis in females over 50 years was the highest in Southwest China (25.65%) and it was the lowest in North China (17.30%). Conclusions:This study establishes reference values of BMD under QCT in healthy Chinese women, which can be used as a reference basis for identifying women with low BMD who are at risk of osteoporosis. The BMD value is the lowest in Southwest China and the highest in South China.
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Objective:To investigate the normal reference values of spinal bone mineral density measured by quantitative computed tomography (QCT) and the differences of bone mineral density (BMD) in different regions of in Chinese adult males.Methods:Men who underwent low-dose CT lung scan for cancer screening in regions of Northeast, North, East, South, Central and Southwest of China from January 2018 to December 2019 were selected. And the lumbar vertebrae BMD values in the male subjects were measured by the QCT system (Mindways Software, Inc.). The mean BMD values and their decline rates were calculated at an age interval of 10 years, and the prevalence of osteoporosis was calculated according to the American College of Radiology spine QCT osteoporosis diagnostic criteria.Results:A total of 50 682 males with a mean age of (50.22±12.79) years (ranged 20 to 98 years) were included in this study. The peak BMD of (173.11±28.56) mg/cm 3 in the healthy Chinese adult male population appeared in the age group of 20 to 29 years and then declined with age. Before the age of 70 years, the BMD was relatively higher in males in South China, and it was lower in Central China and Southwest China, and it was intermediate in Northeast, North and East of China, with statistically significant differences. There was no significant differences in BMD in the males in the two age groups of 70 to 79 years and 80 and older among the regions in China. The overall decline rate of spinal BMD in Chinese males under QCT was about 46.92% over the lifetime, and it declined obviouslyin the 40-49 age group. The overall prevalence of osteoporosis in Chinese male population aged 50 years and above was approximately 11.42%, with the highest prevalence in Southwest China and Central China (14.72% and 13.87%, respectively) and the lowest in North China and South China (8.53% and 7.71%, respectively). Conclusions:A reference of lumbar spine BMD values for healthy males in China based on QCT is established. BMD values were highest in South China and Lowest in Central China.
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Objective:To describe the baseline characteristics of the subjects enrolled in the China Quantitative CT (QCT) big data program in 2018—2019.Methods:Based on baseline data from the Chinese health big data project from January 2018 to December 2019 from the eligible enrolled population, measurements of bone mineral density (BMD) and visceral adipose tissue (VAT) were performed using Mindways′ QCT Pro Model 4 system. The baseline data of age, gender, regional distribution, height, weight, abdominal circumference, blood pressure, blood routine and blood biochemical tests were analyzed. And the single factor analysis of variance (ANOVA) was used to check the age related trend of BMD and VAT in both genders.Results:After screening the inclusion exclusion criteria and outliers of the main indicators, 86 113 people were enrolled in the project. The enrollment rate was 92.47%, including 35 431 (41.1%) women and 50 682 (58.9%) men, and the ratio of men to women was 1.43. The mean age was (50.3±12.7) years in all the subjects, and it was (50.2±12.8) years and (50.4±12.5) years in men and women, respectively, and there was no statistical difference between the two genders ( P>0.05). Total of 43 833 people were enrolled in east China, it was the largest group by region (50.90%), it was followed by central China (16 434 people, 19.08%), and the number of people enrolled in Northeast China was the lowest (2 914 people, 3.38%). The rate of completing of health information indicators related to the main outcome of the study were all above 70%, and there were significant differences between men and women (all P<0.05). The mean BMD was (139.33±46.76) mg/cm 3 in women, (135.90±36.48) mg/cm 3 in men, which showed a decreasing trend with age in both gender (both P<0.001); the mean intra-abdominal fat area was (116.39±56.23) cm 2 in women, (191.67±77.07) cm 2 in men, and there was an increasing trend with age in both men and women (both P<0.001). Conclusions:There are gender differences in BMD and VAT measured by QCT with different age tendency, and there are gender differences in health information index. Regional factors should also be taken into account for regional differences in the inclusion of data.
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Objective:To compare the safety and clinical value of percutaneous computed tomography (CT)-guided fine-needle aspiration biopsy (CT-FNA) with CT-guided core-needle biopsy (CT-CNB) in diagnosis of pancreatic lesions.Methods:We retrospectively analyzed the clinical data of patients with pancreatic lesions who underwent percutaneous CT-guided biopsy from January 2017 to January 2022 at the First Affiliated Hospital of Zhengzhou University. A total of 454 patients (251 men, 203 women) were enrolled in this study with age of (60.5±11.6) years old. They were divided into the CT-FNA group ( n=300) and the CT-CNB group ( n=154) according to the biopsy method. The one-time diagnosis rate, accuracy, sensitivity, false negative rate and incidence rate of complications of the two groups were compared. Results:The one-time diagnosis rate and accuracy rate in the CT-CNB group were slightly higher than those in the CT-FNA group, but the differences were not statistically significant [92.2%(142/154) vs. 86.0%(258/300), χ 2=3.74, P=0.053; 97.4%(150/154) vs. 92.0%(276/300), χ 2=0.16, P=0.690]. Compared with the CT-FNA group, the CT-CNB group had a higher sensitivity and a lower false negative rate, and the differences were statistically significant [97.2%(138/142) vs. 91.5%(260/284), χ 2=4.89, P=0.036; 2.8%(4/142) vs. 8.5%(24/284), χ 2=4.89, P=0.036]. Common complications in the two groups were pain, hematoma and pancreatitis, and there was no statistically significant difference in the incidences of complication [9.0%(27/300) vs. 9.1%(14/154), χ 2<0.01, P=0.975]. Conclusions:Both CT-FNA and CT-CNB were safe for diagnosis of pancreatic lesions, with high diagnostic yields and with similar safety and accuracy. When compared with CT-FNA, CT-CNB has a higher sensitivity and a lower false negative rate.
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Objective:To investigate the predictive value of visceral adipose tissue (VAT) in occult peritoneal metastasis (OPM) of gastric cancer.Methods:A total of 93 patients with gastric cancer admitted to the First Affiliated Hospital of Zhengzhou University from October 2018 to October 2021 were retrospectively collected. None of the patients had typical peritoneal metastasis on CT. Patients were divided into OPM group (31 cases) and non-OPM group (62 cases) according to laparoscopic exploration. The clinical, pathological and CT features were recorded. The parameters related to adipose tissue (VAT and subcutaneous adipose tissue) within the range of 15 mm and 25 mm below the largest layer of gastric cancer lesions in preoperative CT images were measured, including the volume, average CT attenuation and standard deviation. The independent-sample t test, Wilcoxon rank-sum test, χ 2 test or Fisher′s exact probability were used to compare the clinical, pathological and CT imaging parameters between OPM and non-OPM groups. Multivariate logistic regression analysis was used to explore the independent risk factors for OPM of gastric cancer and establish a combined model. The receiver operating characteristic curve was used to evaluate the efficacy of each indicator and the combined model in predicting OPM of gastric cancer. Results:There were statistically significant differences in age, pathological type, CA125, ascites, cT stage, the thickest diameter of lesion, average CT attenuation of 15 mm VAT and 25 mm VAT between the OPM group and the non-OPM group ( P<0.05). Multivariate analysis showed that ascites, cT stage and average CT attenuation of 25 mm VAT were independent risk factors for OPM of gastric cancer, with the OR (95%CI) of 4.940 (1.287-18.967), 4.284 (1.270-14.455), and 1.149 (1.013-1.303), respectively. A combined model was established. The area under the curve (AUC) of ascites, cT stage, average CT attenuation of 25 mm VAT, average CT attenuation of 15 mm VAT and combined model were 0.685, 0.718, 0.703, 0.674 and 0.813, respectively. There were statistically significant differences in AUC between the combined model and each four single indicators above ( Z=2.98, 2.63, 2.09, 2.54, P=0.003, 0.009, 0.037, 0.011). Conclusions:The ascites, cT stage and average CT attenuation of 25 mm VAT are independent risk factors for OPM in gastric cancer. The combined model based on the above three indicators has the best performance in predicting OPM in gastric cancer.
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Objective:To investigate the efficiency of deep learning image reconstruction (DLIR) algorithm in the image quality and detection of hypovascular hepatic metastases under low radiation doses in comparison with adaptive statistical iterative construction-V (ASiR-V).Methods:Fifty-six patients with suspected hypovascular hepatic metastases who needed abdominal enhanced CT scans were collected prospectively in the First Affiliated Hospital of Zhengzhou University from January to April 2021. The patients received conventional radiation dose with tube current-time products of 400 mA CT scans in the first venous phase, low-dose CT scans in the second venous phase, which were set as tube current-time products of 280 mA for group A (19 cases), 200 mA for group B (19 cases) and 120 mA for group C (18 case), respectively. The images of first venous phase and 3 groups of second venous phase were both reconstructed with ASiR-V60% and high-DLIR (DLIR-H). Quantitative parameters [image noise, liver and portal vein signal to noise ratio (SNR), contrast to noise ratio (CNR)] and qualitative parameters (overall image quality, lesion conspicuity, diagnostic confidence) were compared between ASiR-V60% and DLIR-H images, and the effective radiation dose (ED) and the lesion detectability of each group was recorded. The paired t test was used to compare quantitative parameters, whereas the Wilcoxon signed-rank test of paired data was used to compare qualitative parameters. Results:In the second venous phase, ED was (5.56±0.35) mSv in group A, (3.88±0.23) mSv in group B, and (2.42±0.23) mSv in group C, with a decrease of 30%, 50% and 70% compared with the first venous phase, respectively. Moreover, with the decrease of radiation dose, the noise gradually increased, and the CNR lesions, SNR liver and SNR portal vein all gradually decreased. DLIR-H images had statistically better quantitative scores than ASiR-V60% images when the same radiation dose was applied (all P<0.001). Furthermore, the qualitative parameters of each group decreased with the decrease of radiation dose. Under the same radiation dose, the overall image quality, lesion conspicuity and diagnostic confidence of DLIR-H were higher than those of ASiR-V60% (all P<0.001). All lesions [100% (84/84)] were detected by ASIR-V60% and DLIR-H in group A, 92.0% (75/81) in group B, and 88.0% (79/89) in group C. Conclusions:Compared with ASiR-V60%, DLIR-H could reduce image noise, improve overall image quality and lesion conspicuity of hypovascular hepatic metastases as well as increase diagnostic confidence under different radiation doses.
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Objective:To investigate the clinicopathological features and computed tomography (CT) findings of tracheal glomus tumor (GT) in order to improve the understanding and diagnosis of tracheal GT.Methods:The clinical and CT imaging data of 2 patients with tracheal GT diagnosed in the First Affiliated Hospital of Zhengzhou University were analyzed retrospectively. The image characteristics based on previous reports were analyzed.Results:The clinical manifestations of trachea GT were dyspnea, chest tightness, hemoptysis, etc., which were easy to be misdiagnosed. The CT manifestations were spherical or nodular protrusions in the trachea cavity, with uneven edges, which can be lobulated. Cystic changes can be seen in the focus. After enhancement, it showed progressive filling and obvious enhancement, without deep infiltration and distant metastasis.Conclusions:Chest CT can accurately localize tracheal GT, provide its morphological size, blood supply, growth characteristics and other characteristics, accurately display the overall morphology of the lesion, and provide some help for the development of the surgical plan, and its definitive diagnosis still relies on pathological examination.
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Objective:To investigate the relationship between abdominal visceral adipose tissue (VAT) and cardiometabolic risk (CMR) through quantitative computed tomography (QCT).Methods:The present study included 76226 participants. Abdominal fat areas were measured using the QCT Pro Model 4 system. Cardiometabolic indices were collected, including systolic and diastolic blood pressures, fasting plasma glucose, total cholesterol, triglyceride, and low-density and high-density lipoprotein cholesterols CMR score was the sum of abnormal blood pressure, fasting glucose, triglyceride, and high-density lipoprotein cholesterol. Restricted cubic spline and ordered logistic regression models were applied.Results:The mean age was 50±13 years and the percentage of men was 58.8%. The level of VAT area was higher in men than in women (191.7±77.1 cm 2 vs 116.4±56.2 cm 2, P<0.0001 for all). After adjustment for age, the cardiometabolic indices except high-density lipoprotein cholesterol increased with increasing VAT area. When VAT area was 300 cm 2, age-adjusted odds ratios and 95% confidence intervals of a CMR score ≥ 1 were 14.61 (13.31, 16.04) for men and 5.46 (4.06, 7.36) for women, and the age-adjusted probability of a CMR score ≥ 3 was 31.7% for men and 31.3% for women. Conclusions:QCT-derived VAT is closely related to CMR. The findings suggest that measurement of visceral fat is recommended for the management of abdominal obesity in subjects who agree to undergo lung cancer screening via low-dose CT without additional radiation exposure.
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Objective:To evaluate the clinical effect of Toric design orthokeratology in myopic teenagers with mild-to-moderate astigmatism.Methods:A non-randomized controlled clinical study was conducted.Eighty juvenile myopia patients (160 eyes) diagnosed with mild to moderate astigmatism with myopia after mydriatic computer optometry and received the treatment of orthokeratology at Zhejiang Rongjun Hospital from January 2016 to June 2017 were enrolled.The patients were divided into regular spherical design orthokeratology group and Toric design orthokeratology group, with 80 eyes (40 cases) in each group.The patients wore orthokeratology for 8 to 10 hours every night and were re-examined at 1 day, 1 week and 1, 3, 6, 12 and 18 months after wearing, respectively.The visual acuity, refraction, corneal health status and central deviation of the treatment area in the corneal topography map were measured and recorded during the 18-month treatment.The complications during treatment were recorded.After 12-month wearing, the uncorrected visual acuity and the center deviation of the treatment area were compared between the two groups.After 18-month wearing, patients in the two groups stopped wearing the orthokeratology lens for 1 month, and then the refraction examination, IOLMaster and corneal topography were performed to compare the spherical equivalent, axial length and degree of astigmatism.This study protocol adhered to the Declaration of Helsinki and was approved by an Ethics Committee of Zhejiang Rongjun Hospital (No.2020-10). Written informed consent was obtained from guardians prior to any medical examination.Results:After 12-month wearing, the center deviation of the shaping treatment area was (0.86±0.23)mm in the Toric design orthokeratology group, which was significantly lower than (1.16±0.44)mm in the regular spherical design orthokeratology group ( t=5.404, P<0.001). After 12-month wearing, the uncorrected visual acuity was (0.03±0.08) LogMAR in the Toric design orthokeratology group, which was significantly higher than (0.09±0.10) LogMAR in the regular spherical design orthokeratology group ( t=2.963, P=0.004). The spherical equivalent and the axial length of Toric design orthokeratology group were significantly smaller than those of the regular spherical design orthokeratology group ( t=2.542, 2.107; both at P<0.05), and there was no statistically significant difference in the degree of astigmatism between the two groups ( t=0.821, P=0.413). During the 18-month follow-up, the adverse reaction, punctate corneal epithelial opacity, occurred in 18 eyes.The incidence of adverse effect was 6.26%(5/80) in the Toric design orthokeratology group, which was significantly lower than the 16.25% (13/80) in the regular spherical design orthokeratology group ( χ2=3.897, P=0.048). Conclusions:The Toric design orthokeratology shows better efficacy in myopia control as well as reducing the adverse reaction rate in juvenile myopia, and it can better solve the deviation in corneal shaping in the use of regular spherical design orthokeratology.
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Objective:To investigate the application value of spectral computed tomo-graphy (CT) multi-parameter imaging in predicting gastric cancer lymph node metastasis.Methods:The retrospective case-control study was conducted. The clinicopathological data of 86 patients with gastric cancer who were admitted to the First Affiliated Hospital of Zhengzhou University from January 2014 to June 2017 were collected. There were 53 males and 33 females, aged from 22 to 87 years, with a median age of 53 years. All patients received abdominal plain scan and arterial and venous phase contrast spectral scan. Images of plain scan, 70 keV monochromatic and iodine-based images in arterial and venous phase were analyzed on post-processing working station. Observation indicators: (1) gastric cancer lymph node metastasis; (2) analysis of influencing factors for lymph node metastasis in gastric cancer; (3) introduction of special cases. Count data were described as absolute numbers. Univariate analysis was performed using the chi-square test or rank sum test. Multivariate analysis was conducted using the Logistic regression model.Results:(1) Gastric cancer lymph node metastasis: of the 86 patients, 64 cases had lymph nodes metastasis and 22 had no lymph nodes metastasis. (2) Analysis of influencing factors for lymph node metastasis in gastric cancer: results of univariate analysis showed that tumor growth pattern, tumor diameter, infiltration of peritumor fat, CT value in arterial phase, CT value in venous phase, iodine value in venous phase were related factors affecting lymph nodes metastasis in gastric cancer ( χ2=6.753, Z=-3.180, χ2=7.649, Z=-2.051, -2.971, -2.547, P<0.05). Results of multivariate analysis showed that infiltration of peritumor fat and the iodine value in venous phase were greater than 12(100 μg/cm 3) and not greater than 16(100 μg/cm 3), or greater than 16(100 μg/cm 3) were independent risk factors affecting lymph nodes metastasis in gastric cancer ( odds ratio=13.154, 3.761, 7.583, 95% confidence interval as 2.597-66.620, 1.893-8.572, 4.769-16.692, P<0.05). (3) Introduction of special cases: case 1 was male, aged 46 years. Results of preoperative spectral CT enhanced scan showed gastric antrum space occupying lesion combined with enlarged lymph nodes. During enhancement arterial phase, spectral CT 70 keV monochromatic images and corresponding iodine-based images of primary lesion layer in the transverse view showed gastric wall thickening with mild to moderate enhancement, clear fat space in serosa and enlarged lymph nodes in lesser curvature. The spectral CT 70 keV monochromatic images and corresponding iodine-based images below pylorus level in the transverse view showed subpyloric enlarged lymph nodes. During enhancement venous phase, the 70 keV monochromatic images and corresponding iodine-based images of primary lesion layer in the transverse view showed layered enhancement of gastric antrum lesions and mucosal enhancement, with a high iodine value. The patient was diagnosed as gastric antrum cancer with lymph node metastasis, no serosal or peritumoral fat invasion. Results of postoperative pathological examination showed moderately differentiated adenocarcinoma of gastric antrum with serosal invasion and lymph node metastasis. Case 2 was male, aged 53 years. Results of preoperative spectral CT enhanced scan showed gastric cancer of lesser curvature combined with enlarged lymph nodes. During enhancement arterial phase, 70 keV monochromatic images and corresponding iodine-based images of primary lesion layer in the transverse view showed gastric wall heterogeneous thickening of lesser curvature, with moderate enhancement, obscure peritumor fat space, unclear serosa, and multiple enlarged lymph nodes in lesser curvature. During enhancement venous phase, 70 keV monochromatic images in the transverse view showed unclear boundary between lesions and enlarged lymph nodes in lesser curvature, obscure peritumor fat. During enhancement arterial phase, 70 keV monochromatic images of celiac trunk layer in the transverse view showed parasplenic artery lymph nodes, with circular enhancement and no enhancement in central necrotic elements. The patient was diagnosed as gastric cancer of lesser curvature with lymph node metastasis, serosal and peritumor fat invasion. Results of postoperative pathological examination showed poorly differentiated adenocarcinoma of gastric antrum with serosal invasion and lymph node metastasis. Conclusion:The infiltration of peritumor fat and iodine value in venous phase are independent factors affecting gastric cancer lymph node metastasis.
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OBJECTIVE：To provide reference for the c onstruction of subject diagnosis and treatment scheme in drug clinical trials. METHODS ：The subject diagnosis and treatment module was developed and implemented in our hospital on the basis of CTMS，and its effects were evaluated. RESULTS ：A subject diagnosis and treatment module was established in CTMS of our hospital. Within one year from the launch of the module in the middle of October ，2019，the overall number of subjects in the group showed an increasing trend ，and the overall mean dropout rate of subjects was 0.16％. The data interface of CTMS system ， hospital information system （HIS），laboratory information management system ，medical imaging information system had been established，so as to realize the synchronization of subject information （displaying subject identification in HIS system ）and the interaction of diagnosis and treatment information and billing data （patients and subjects were charged separately ）. Since the launch of the module ，the amount of data generated by the interface had been increasing ，and the number of departments producing the subject diagnosis and treatment business had been increasing month by month. Compared with subject diagnosis and treatment project based on HIS system ，the number of subject diagnosis and treatment business based on CTMS system was increased significantly（P＜0.05）. CONCLUSIONS ：The subject diagnosis and treatment module based on CTMS improves the efficiency of subject diagnosis and treatment project implementation and financial settlement ，and realizes the efficient implementation of drug clinical trial projects in large general hospitals.