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The presence of p53 mutationscombined with high Ki-67 expression can predict poor prognosis and overall survival in IDH-wildtypeglioblastoma patients. This study aims to use magnetic resonance imaging (MRI) features and apparent diffusion coefficient(ADC) values to predict the expression of p53 and Ki-67 in IDH-wildtype glioblastomas to informclinical treatment. We retrospectively collected clinical and imaging data for 103 IDH-wildtype glioblastoma patients in our hospital between June 2021 and February 2023. The datasets were divided into four groups: p53(+)/Ki-67(+), p53(+)/Ki67(-), p53(-)/Ki67(+), and p53(-)/Ki67(-) according to mutant status of p53 and expression level of Ki-67. Six MRI morphological features and four ADC values for the tumor parenchyma were analyzed. In the 103 patients, 21 had p53(-)/Ki-67(-), 12 had p53(+)/Ki-67(-), 28 had p53(-)/Ki-67(+), and 42 had p53(+)/Ki-67(+). Tumor location showed statistically significant differences among the 4 groups (P < 0.05). ADC parameters were negatively correlated with p53 and Ki-67 expression status and could distinguish the co-expression of p53 and Ki-67 (P < 0.05). In distinguishing between the p53(+)/Ki-67(+) and p53(-)/Ki-67(-) groups, when ADCmin was 0.85×10-3 mm2/s, the sensitivity, specificity and accuracy reached their maximum values of 61.90%, 92.90% and 82.54%, respectively. In conclusion, the expression of p53 and Ki-67 in IDH-wildtypeglioblastoma can be evaluated by ADC values. ADC values can be used as a non-invasive quantitative parameter to assist in the clinical diagnosis of IDH-wildtype glioblastoma molecular states.

Purpose: To investigate the role of apparent diffusion coefficient (ADC) histogram analysis in differentiating atypical meningioma (AtM) from transitional meningioma (TrM) and its correlation with the Ki-67 proliferation index. Methods: Clinical, imaging, and pathological data of 78 patients with AtM and 80 patients with TrM were retrospectively collected. Regions of interest (ROIs) were delineated on axial ADC images using MaZda software and histogram parameters (mean, variance, skewness, kurtosis, 1st percentile (ADCp1), 10th percentile (ADCp10), 50th percentile (ADCp50), 90th percentile (ADCp90), and 99th percentile (ADCp99)) were generated. The Mann–Whitney U test was used to compare the differences in histogram parameters between the two groups; receiver operating characteristic (ROC) curves were used to assess diagnostic efficacy in differentiating AtM from TrM preoperatively. The correlation between histogram parameters and Ki-67 proliferation index was analyzed. Results: All histogram parameters of AtM were lower than those of TrM, and the variance, skewness, kurtosis, ADCp90, and ADCp99 were significantly different (P < 0.05). The optimal cutoff value of 147.00 × 10 – 3 mm2/s, ADCp99 achieved the best diagnostic performance for distinguishing AtM from TrM: area under the curve (AUC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 0.764, 58.75%, 82.05%, 70.25%, 77.05%, and 65.98%, respectively. All histogram parameters were negatively correlated with Ki-67 expression (r = -0.012 to -0.293). Conclusion: ADC histogram analysis is a potential tool for noninvasive differentiation of AtM from TrM preoperatively, and ADC histogram parameters were negatively correlated with the Ki-67 proliferation index.

Rotator cuff tendon-bone healing often leads to scarring and low biomechanical strength, resulting in a tendency to re-tear. This study examined whether combining autologous osteochondral transplantation and periosteum transplantation increases fibrocartilage transition zone regeneration and improves biomechanical fixation.A total of 48 New Zealand white rabbits were divided into the periosteum, autologous osteochondral, combination of autologous osteochondral and periosteum, and control groups. The supraspinatus tendon was cut from the greater tuberosity and repaired by different transplants. A total of 12 rabbits were used for histological examination (haematoxylin and eosin staining, Masson's staining and Safranin-O staining) at 4, 8 and 12 weeks after the repair, and 36 rabbits were used for biomechanical tests (maximal failure load and stiffness).At 4 weeks following the operation, each group had a large tendon-bone gap with a small number of disordered collagen fibres. At 8 weeks, the tendon-bone gap was smaller than that before the operation, and the tendon-bone gap in each experimental group was smaller with neater and denser collagen fibres and chondrocytes than in the control group, with the osteochondral combined periosteum group having the best results. At 12 weeks, the typical tendon-bone transitional structure was observed in the osteochondral combined periosteum group, and more collagen fibres and chondrocytes were generated in each group. The osteochondral combined periosteum group had the largest staining area and the largest amount of cartilage. The maximum tensile strength and stiffness of each group increased over time. There was no significant difference in each group's maximum tensile strength and stiffness at 4 weeks after the operation. However, the maximum tensile strength and stiffness of the osteochondral combined periosteum group at 8 and 12 weeks after operation were significantly higher than those of other groups (P 0.05).Histological and biomechanical results show that autologous osteochondral transplantation combined with periosteum transplantation can effectively promote the regeneration of fibrous cartilage in the tendon-bone junction of the rotator cuff. It is concluded that this technique is a new treatment method to promote tendon-bone healing in the rotator cuff.

Purpose: To assess differences in pericoronary adipose tissue (PCAT) in patients with different plaque types by using several quantitative parameters of PCAT and investigate the relationship between PCAT and different plaque types.Methods: We retrospectively recruited 488 patients diagnosed with stable coronary artery disease (CAD) via coronary computed tomographic angiography, including 279 with calcified plaques (CP), 153 with non-calcified plaques (NCP), and 56 with mixed plaques (MP). Volume, fat attenuation index (FAI), and 10th percentile, 90th percentile, median, and minimum Hounsfield unit (HU) values of PCAT surrounding plaques were quantified using semi-automated software. Clinical features and quantitative PCAT parameters were compared between different plaque types.Results: No between-group differences were observed for age, sex, body mass index, risk factors, and plaque location. Length and PCAT volume in the NCP group were lower than those of the CP and MP groups (P < 0.001), whereas there were no significant differences between the CP and MP groups (P > 0.05). Patients with NCP and MP had a higher FAI and 10th percentile, 90th percentile, median, and minimum HU values of PCAT than CP (P < 0.001); however these values were not significantly different between the NCP and MP groups (P > 0.05). Conclusion: The quantitative parameters of PCAT, as a biosensor for CAD, vary among the different plaque types.

The purpose of this study was to investigate the utility of combining clinical and spectral computed tomography (CT) parameters for the preoperative evaluation of lymphovascular invasion (LVI) and perineural invasion (PNI) in gastric cancers (GCs).Patients with gastric adenocarcinoma who underwent spectral-CT examination were retrospectively examined. All diagnoses were confirmed by pathology, and the patients were divided into positive and negative groups based on LVI/PNI occurrence. Clinical characteristics, including demographic information, serum tumor markers, and gastroscopic pathological information, were collected. The effective atomic number (ZA total of 121 patients (96 men, 25 women; mean age: 59 ± 8.7 [SD] years, range: 36-82 years) with gastric adenocarcinoma were included in the study. The serum level of the tumor marker CA125, as well as ZClinical and spectral-CT parameters exhibit considerable capabilities in the preoperative evaluation of LVI and PNI in GCs. The combination of clinical and spectral-CT parameters effectively predicts LVI and PNI in GCs.

To explore the value of MRI conventional features and apparent diffusion coefficient (ADC) on the differential diagnosis of atypical meningioma (AtM) and anaplastic meningioma (AnM).This retrospective study analyzed the preoperative clinical data, MRI conventional features, and DWI data of 55 AtM and 25 AnM confirmed by pathology in our hospital. The clinical features, MRI conventional features, ADCmean, ADCmin, and relative ADC (rADC) values were compared between the two tumors by Chi-square test or an independent sample t-test. Receiver operating characteristic curve (ROC) and binary logistic regression analysis were used to evaluate the diagnostic efficacy of each parameter to differentiate between these tumors.The MRI conventional features had a certain ability to distinguish AnM and AtM, with an area under the curve value (AUC) of 0.824 (95% CI, 0.723-0.900). The ADCmean, ADCmin, and rADC values were significantly higher in AtM compared to AnM (all P 0.05). ADCmean had the best identification effect with an AUC of 0.867 (95% CI, 0.772-0.933) among them, at an cut-off of 0.817 × 10MRI conventional features combined with ADCmean, as a non-invasive method, has potential clinical value in the preoperative diagnosis of AtM and AnM.

Background: To investigate the spectral computed tomography (CT) findings of peripheral adenocarcinoma (P-AC) and peripheral squamous cell carcinoma (P-SCC) in lung. Methods: In this retrospective study, A total of 273 patients (150 patients with P-AC and 123 patients with P-SCC) confirmed by surgery and pathology who underwent chest contrast enhanced CT scan with GSI mode, including arterial phase (AP) and venous phase (VP). During two phases, The CT40keV, CT70keV, CT100keV values, iodine concentration (IC), water concentration (WC), effective atomic number (Zeff) were measured and the slope of the spectral curve (K) was calculated. Differences between two groups were compared using two-sample t-test, Receiver operating characteristic (ROC) curves were plotted, and the area under the ROC curve (AUC) was also calculated to calculate diagnostic efficacies.Results: There was significant difference in gender between the two groups (P < 0.05), No significant difference between other clinical features and symptoms (P > 0.05). For AP and VP, the CT40keV, CT70keV, K70keV, IC and Zeff of P-AC were significantly higher than those of P-SCC (PConclusions: Spectral CT can provide reference for the differentiation of P-AC and P-SCC.

Patients with epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma can benefit from targeted therapy. However, noninvasively determination of EGFR mutation status before targeted therapy remains a challenge. This study constructed a nomogram based on a combination of radiomics features with the clinical and radiological features to predict the EGFR mutation status. The least absolute shrinkage and selection operator (LASSO) and Wilcoxon test were used for feature selection. Decision tree (DT), logistic regression (LR), and support vector machine (SVM) classifiers were used for radiomics model building. Used the clinical and radiological features establish clinical-radiology (C-R) model. The C-R model with the best radiomics model to establish clinical-radiological-radiomics (C-R-R) model. The predictive performance of the model was evaluated by ROC and calibration curves, and the clinical usefulness was assessed by a decision curve analysis. The current study showed that twelve radiomics features were significantly associated with EGFR mutations. The best radiomics signature model was obtained using the SVM classifier. The C-R-R model had the best distinguishing ability for predicting the EGFR mutation status, with an AUC of 0.849 (95% CI, 0.805-0.893) and 0.835 (95% CI, 0.761-0.909) in the development and validation cohorts, respectively. Our study provides a non-invasive C-R-R model that combines CT-based radiomics features with clinical and radiological features, which can provide useful image-based biological information for targeted therapy candidates.

AIM The purpose of this study was to investigate the relationship between epidermal growth factor receptor (EGFR) mutation status and computed tomography (CT) features in patients with lung adenocarcinoma. MATERIALS AND METHODS A total of 483 patients with lung adenocarcinoma diagnosed between January 2015 and April 2020 were included in this study. All patients underwent a preoperative chest CT, and a total of 31 detailed CT features were quantified. The mutation status of EGFR exon 18–21 was detected by a polymerase chain reaction (PCR)-based amplified refractory mutation system. Student's t and Fisher's exact or chi-square tests were used to compare continuous and categorical variables, respectively. Least absolute shrinkage and selection operator (LASSO) regularisation was used to determine the optimal combination of CT features and clinical characteristics to predict the EGFR mutation status. The model was tested using a validation set consisting of 120 patients. RESULTS EGFR mutations were found in 249 (51.6%) of 483 patients with lung adenocarcinoma. Univariate analysis showed that 14 CT features and two clinical characteristics correlated significantly with the EGFR mutation status. Smoking history, long-axis diameter, bubble-like lucency, pleural retraction, thickened bronchovascular bundles, and peripheral emphysema were independent predictors of the EGFR mutation status, according to LASSO regularisation. In the training and verification cohorts, the areas under the curve of the prediction model were 0.766 and 0.745, respectively. CONCLUSIONS CT features of patients with lung adenocarcinoma can help predict the EGFR mutation status.

Highlights • Tyrosine kinase inhibitors (TKIs) provide clinical benefits to the lung cancer patients with epidermal growth factor receptor (EGFR) mutations. • Non-invasively determine EGFR mutation status in patients before targeted therapy remains a challenge. • The personalized nomogram model of CT features and clinical risk factors can easily and noninvasively predict the EGFR mutation status before surgery., Tyrosine kinase inhibitors (TKIs) provide clinical benefits to the lung cancer patients with epidermal growth factor receptor (EGFR) mutations. However, non-invasively determine EGFR mutation status in patients before targeted therapy remains a challenge. This study aimed to develop and validate a nomogram for preoperative prediction of EGFR mutation status in patients with lung adenocarcinoma. The medical records of 403 patients with lung adenocarcinoma confirmed by histology from January 2016 to June 2020 were retrospectively collected. We combined CT features and clinical risk factors and used them to build a prediction nomogram. The performance of the nomogram was evaluated in terms of calibration, discrimination, and clinical usefulness. The nomogram was further validated in an independent external cohort. Finally, a nomogram that contained CT features and clinical risk factors, which could conveniently and non-invasively predict EGFR mutation status in patients with lung adenocarcinoma before surgery.