To evaluate the therapeutic efficacy and immunological impact of an ultrasound-guided combined cryoablation and thermal ablation system (Co-Ablation System) in the management of Hepa1-6 tumor-bearing mice.

A hepatoma mouse model was established using healthy C57BL/6J mice inoculated with Hepa1-6 tumor cells. Forty tumor-bearing mice were randomly assigned to four groups: a blank control group, a sham operation group, a surgical operation group, and a Co-Ablation System group, with ten mice per group. Utilizing ultrasound, tumor volume alterations were assessed pre-treatment and at 1, 2, 3, and 4 weeks post-treatment. Flow cytometry was employed to quantify the percentages of CD4+ and CD8+ T lymphocytes in peripheral blood samples. Additionally, three mice from each group were euthanized two weeks post-treatment for histological analysis via HE staining and immunohistochemistry to determine the optical density of CD4 + and CD8 + cells.

The tumor tissues in both the blank control group and the sham operation group exhibited gradual growth at each time point, with no statistically significant difference observed between the two groups (P > 0.05). In contrast, the tumor volume in the Co-Ablation System group progressively decreased post-treatment, showcasing a statistically significant difference compared to the blank control and sham operation groups (P < 0.05). Notably, the serum levels of CD4+ T and CD8+ T cells in the Co-Ablation System group were markedly elevated compared to the blank control, sham operation, and surgical operation groups at all post-operative time points (P < 0.05). These levels peaked three weeks after treatment in the Co-Ablation System group, subsequently declining. Additionally, a significant increase in CD4 and CD8 positive cells within tumor tissue was observed in the Co-Ablation System group two weeks post-treatment, as compared to the blank control and sham operation groups, with the difference being statistically significant (P < 0.05).

The utilization of the Ultrasound-guided Co-Ablation System has proven to be highly effective in treating Hepa1-6 tumor mice, not only reducing tumor burden but also activating the immune system and potentiating the body's anti-tumor immune response.

To investigate the effect of building a predictive model of short-term mortality risk in sepsis patients based on NMR metabolomics characteristics.

Sixty patients with sepsis admitted to ICU of our hospital from January 2020 to December 2022 were selected as the study objects. All patients were divided into survival group and death group based on the survival status at 28 d after treatment. General data and laboratory examination data of patients were collected. Serum samples were collected for proton nuclear magnetic resonance specific metabolic markers when patients were enrolled. The top 4 products were selected by LASSO regression to construct a short-term death risk prediction model for sepsis patients. Finally, patients with sepsis treated in ICU of our hospital from January 2023 to December 2023 were included to verify the predictive effect of the model.

APACHE II scores in the death group were higher than those in the survival group, and the difference was statistically significant (P < 0.05). Multivariate statistical analysis method shows that the prediction ability of the original model is greater than that of any one random arrangement of Y variables, which proves that the model is effective. The scatter plot of unsupervised PCA explained 57% of the variables (PC1=50%, PC2=7%), and the metabolic profile was different between the control group and the model group, with significant changes in serum endogenous metabolites in sepsis patients after PCPA modeling. OPLS-DA graphical model has good fitting effect, there are no special points, and the distribution areas of the two groups are completely separated. As shown in the loading matrix, the levels of L-aspartate, indoleacetic acid and alanine increased, while the levels of isoleucine and leucine decreased. The top 50 variables with the largest VIP value in the OPLS-DA model were extracted for non-parametric test. Finally, 34 variables with statistical significance were obtained (P < 0.05), and a total of 19 characteristic metabolites were most likely to be associated with sepsis death. Serum phenylalanine, creatine, acetoacetic acid, glutamic acid, methionine, urea, lactic acid and trimethylamine oxide in death group were significantly higher than those in survival group (P < 0.05). The C-index of short-term death risk in sepsis patients was 0.993 (95%CI: 0.9310.999) in an eriograms of four highly correlated metabolites selected by LASSO. The Nomogram model was of certain value in predicting the short-term mortality risk of sepsis patients (AUC=0.993, 95% CI: 0.978-1.000, P < 0.001). The short-term mortality risk in model-validated sepsis patients with a Nomogram model (AUC=0.934, 95% CI: 0.863-1.000, P < 0.001) was useful. The accuracy, sensitivity and specificity of the model to the training set were 96.66%, 94.11% and 97.60%, respectively. The accuracy, sensitivity and specificity of the model to the validation set were 90.62%, 88.23% and 91.48%, respectively.

The prediction model of short-term death risk in sepsis patients based on serum NMR metabolomic characteristics has a good value in predicting the 28 d death risk of sepsis patients.

To establish a radiomics model to predict Ki67 expression of prostate cancer on multiparameter magnetic resonance imaging(mp-MRI).

A total of 176 prostate cancer patients confirmed by postoperative pathology in our hospital from December 1, 2020 to June 30, 2023 with complete magnetic resonance date were rest retrospectively analyzed, and the patients were divided to the training group (n=140) and validation group (n=36) in a 7:3 ratio. The DICOM images of patients T2-weighted imaging (T2WI), fat-suppression T2-weighted imaging (FS-T2WI), zoomed imaging technique with parallel transmission diffusion weighted imaging (ZOOMit-DWI), the apparent diffusion coefficient (ADC) were exported from the PACS workstation, the three-dimension volume region of interest of the tumor was manually delineated on the four sequential images, and radiomics features were extracted, and the Spearman correlation analysis and LASSO analysis were used to single out the most valuable radiomic features. The radiomics models were built using the radiomics features The diagnostic value of the model was analyzed by using ROC curve and calculating the AUC, and the diagnostic efficacy was verified in the validation group.

A total of 1834 radiomics features were extracted from T2WI, FS-T2WI, ZOOMit-DWI, ADC and 20 features were selected, which were related to Ki67 status. Among the eight radiomics models established for Logistic Regression, Support Vector Machine, K-Nearest Neighbor, RandomForest, ExtraTrees, eXtreme Gradient Boosting, Light Gradient Boosting Machine, Multilayer Perceptron, The Light Gradient Boosting Machine model was optimal with an AUC of 0.948 (95% CI: 0.913-0.982) in the training group and an AUC of the test group of 0.832 (95% CI: 0.698-0.967).

The radiomics models based on mp-MRI can noninvasively predict the expression of Ki67, and the LightGBM model is the best.

To investigate the changes in fetal right ventricular function associated with tricuspid regurgitation by speckle tracking imaging.

A total of 101 fetuses without obvious cardiac malformations detected by prenatal echocardiography from January 2019 to May 2023 at the First Affiliated Hospital of the University of Science and Technology of China (Anhui Provincial Hospital) were selected. The fetuses were divided into a control group with no tricuspid regurgitation (n=41), a mild regurgitation group (n=30), and a moderate regurgitation group (n=30) based on the degree of tricuspid regurgitation. The left and right ventricular global longitudinal strain of endocardial layers (LV/RV-EndoGLS), fractional area change in the left and right ventricles (LV/RV-FAC), right ventricular free wall strain (RVFWLS), tricuspid annular plane systolic excursion (TAPSE), and left ventricular ejection fraction (LVEF) were computed to compare the impact of different degrees of tricuspid regurgitation on biventricular systolic function in fetuses.

There was no significant difference in right ventricular function between the mild regurgitation group and the control group (P > 0.05). The right ventricular function indicators in the moderate regurgitation group were all lower than those in the control group (P < 0.05). The RV-EndoGLS and RVFWLS in the moderate regurgitation group were lower than those in the mild regurgitation group (P < 0.05), while RVFAC and TAPSE showed no significant difference (P > 0.05). There was no significant difference in LV-EndoGLS, LV-FAC, and LVEF among all the groups (P > 0.05).

The speckle tracking imaging can evaluate whether the fetal right ventricular function is impaired in isolated tricuspid regurgitation. RV-EndoGLS and RVFLS are more sensitive indicators.

To predict the HER-2 status in breast cancer by integrating full-field digital mammography (FFDM) radiomics features with deep learning features.

Retrospective analysis was conducted on of breast cancer patients who underwent clinical surgery or biopsy from March 2018 to December 2023 at the Affiliated Hospital of Shanxi University of Chinese Medicine. Regions of interest within FFDM images were manually delineated to extract radiomics and deep learning features. Following LASSO-based feature selection, support vector machine algorithms were used to construct both a radiomics model and a deep learning model. A composite model was developed using multivariate logistic regression analysis. The predictive performance of each model was evaluated by calculating their AUC values, and their effectiveness and practical value in real clinical decision-making were assessed using decision curve analysis curves.

The radiomics model exhibited AUC values of 0.835 (95% CI: 0.761-0.898) in the training set and 0.781 (95% CI: 0.701-0.857) in the test set. The deep learning model demonstrated AUC values of 0.904 (95% CI: 0.855-0.955) in the training set and 0.883 (95% CI: 0.823-0.939) in the test set. The composite model achieved AUC values of 0.921 (95% CI: 0.872-0.967) in the training set and 0.890 (95% CI: 0.828-0.942) in the test set. Decision curve analysis indicated that all three models provided a greater net benefit compared to assuming all cases as either HER-2 positive or negative, with the composite model offering the maximum net benefit at various risk thresholds.

The integration of FFDM radiomics and deep learning features significantly enhances the prediction of HER-2 status in breast cancer, greatly improving both accuracy and reliability. This advancement opens new avenues for the diagnosis and treatment of breast cancer.

To explore the correlation between the quantitative parameters of dual-energy CT combined with CT signs, clinical characteristics and epidermal growth factor receptor (EGFR) gene mutations in patients with advanced lung adenocarcinoma, and to predict the mutation in patients with advanced lung adenocarcinoma.

A retrospective collection was performed for 172 cases of advanced lung adenocarcinoma (clinical stage Ⅲ~Ⅳ) diagnosed by pathology (fiber bronchoscopy, lymph node, percutaneous lung puncture) biopsy in the First People's Hospital of Yancheng City from January 2022 to June 2023. The patient's general clinical features, CT signs, and dual-energy CT (DECT) parameters were collected. According to the results of EGFR gene testing, they were divided into positive group and negative group. The independent samples t-test or rank-sum test were used to analyze the differences between the groups, and a binary logistic regression model based on clinical characteristics, conventional CT signs, DECT quantitative parameters and combination was gradually established for statistically significant parameters, and the prediction performance of the combined model was evaluated.

A total of 172 patients with lung adenocarcinoma during the study period were identified, including 80 positive for EGFR gene expression patients and 92 negative patients. There were significant differences in IC, NIC, slope K40-100kev in arterial phase and IC in venous phase between the two groups (P < 0.001); There were significant differences in air bronchogram sign and pleural traction sign between the two EGFR groups (P < 0.05); Univariate logistic regression analysis showed that arterial phase IC, NIC, slope K40-100 keV, venous phase IC, air bronchogram sign, and pleural traction sign were associated with EGFR gene mutations. The AUC for the DECT model, the DECT model combined with clinical characteristics, and the DECT model combined with clinical characteristics and CT signs were 0.746 (sensitivity 63.75%, specificity 92.39%), 0.787 (sensitivity 65.00%, specificity 91.30%), and 0.819 (sensitivity 77.50%, specificity 82.61%), respectively. According to the DeLong test, there was no significant difference in AUC among the three models (P > 0.05).

The combined DECT model, incorporating clinical characteristics and CT signs, effectively predicts EGFR mutations and performs better than the single model in patients with advanced-stage lung adenocarcinoma.

To investigate the predictive value of non-contrast CT signs in early hematoma expansion in patients with spontaneous intracerebral hemorrhage.

A total of 169 cases of acute spontaneous cerebral hemorrhage in our hospital from January 2021 to June 2023 were analyzed retrospectively. According to the CT results within 24 h, and they were divided into hematoma expansion group (n=55) and non-expansion group (n=114). The baseline CT signs of the patients were analyzed, and three models of "density anomaly group", "morphology abnormal group" and "combined signs group" were established. Independent risk factors were screened by univariate analysis and multivariate Logistic regression analysis, and the accuracy of each sign in predicting hematoma expansion was evaluated by ROC curve.

Eleven imaging features and three combined features were collected for each case. Among them, the initial volume of hematoma, "mixed sign", "black hole sign", "swirl sign", "island sign", "density abnormality group" and "combined sign group" were statistically significant between two groups (P < 0.05); multivariate logistic regression analysis showed that the "density abnormality group" and the "combined sign group" were independent predictors of hematoma expansion (P=0.031); haematoma expansion is more likely to occur when the volume of the relatively low density area in the "mixed sign" and "swirl sign" and the maximum diameter of the largest island in the "island sign" are large. The AUC of initial volume of the hematoma, "mixed sign", "black hole sign", "vortex sign" and "island sign", "Density abnormality group" and the "combined sign group" were 0.686, 0.668, 0.588, 0.693, 0.627, 0.758, 0.713, respectively.

In non-contrast CT scan, the "density abnormality group" representing heterogeneity of hematoma density and the "combined sign group" representing density and morphology abnormalities have certain predictive value for early hematoma expansion in patients with cerebral hemorrhage.

To analyze the clinical features, imaging manifestations and misdiagnosis causes of eosinophilic fasciitis (EF), and to strengthen the understandings of clinical features, diagnostic key points and differential diagnosis of EF.

A retrospective analysis was performed on eleven EF patients admitted to Department of Rheumatology and Immunology of the Second Affiliated Hospital of Anhui Medical University from October 2018 to March 2023, including seven males and four females, with the age of onset ranging from 16 to 71 years old, and their demographics, clinical manifestations, imaging examination, pathological data, and treatment were analyzed.

Clinical manifestations included subcutaneous swelling/stiffness (90.9%), arthralgia/inflammation (63.6%), sticky sensation (63.6%), pigmentation (45.5%), Prayer hand (36.36%), gully sign (18.18%), myalgia and muscle weakness (9.09%), etc. Imaging examination of eleven patients showed muscle MRI examination of the affected myofascial thickening, and one case found abnormal signal of muscle involvement and biopsy pathology suggested muscle involvement. Full-thickness skin and muscle biopsies were performed in eleven patients, and fascial thickening with chronic inflammation, fibrinoid degeneration, lymphocytic or plasma cell infiltration was mostly seen in pathology, and eosinophilic infiltration was seen in seven cases. Among them, ten cases underwent bone marrow biopsy, and seven cases had eosinophilic myelogram, and no hematologic tumors were found.

Eosinophilic fasciitis is a rare connective tissue disease, with many similarities in clinical features, imaging and pathological manifestations, and it is easy to be misdiagnosed. In-depth understanding of clinical and imaging features, analysis of causes of misdiagnosis can avoid misdiagnosis and mistreatment.

To investigate the relationship between interatrial septum thickening rate and the risk of stroke in patients with atrial fibrillation using inverse probability weighting (IPTW).

A total of 265 patients with atrial fibrillation were admitted to Nanjing Hospital of Chinese Medicine from January 1, 2020 to June 30, 2023, were enrolled in this study. The interatrial septum thickening rate was divided into three groups based on tertiles: group 1 (0.01-0.089), group 2 (0.089-0.317), group 3 (0.317-0.69). IPTW was used to adjust for confounding factors and balance group differences. The weighted restricted cubic spline curve was used to explore the relationship between interatrial septum thickening rate and the risk of stroke in patients with atrial fibrillation.

IPTW analysis showed that the risk of stroke in patients with atrial fibrillation in group 2 was not significantly different from that in group 1 (P=0.584). However, the risk in group 3 was reduced by 86% compared to group 1 (OR=0.144, 95% CI: 0.055-0.380, P < 0.001). Restricted cubic spline curve analysis, based on a developed weighting equation, indicated that the cut-off value for interatrial septum thickening rate was 0.321. There was a decreasing trend in the risk of stroke among patients with atrial fibrillation whose interatrial septum thickening rate was greater than 0.321.

There was a non-linear relationship between interatrial septum thickening rate and the risk of stroke in patients with atrial fibrillation.

To investigate the construction and predictive performance of machine learning models based on clinical and CT imaging features for predicting pathological subtypes of thymic epithelial tumors (TETs).

This retrospective study included data from 221 patients with pathologically confirmed TETs at Nanfang Hospital, Southern Medical University, between January 2006 and June 2023. The data collected included clinical information, CT images, and pathological results. According to simplified pathological classification, the patients were classified into low-risk group (type A, AB, B1) and high-risk group (type B2, B3, thymic carcinoma). The included cases were randomly divided into the training set (n=159) and the validation set (n=62) at a ratio of 7:3. In the training set, univariate logistic regression was used to analyze the differences of clinical and CT characteristics between low-risk group and high-risk group. Feature selection was performed using stepwise regression and LASSO regression to construct four machine learning models, that were logistic regression, random forest, decision tree, and support vector machine. Model performance was evaluated in the validation set by AUC.

Among 221 cases of thymic epithelial tumors, 105 cases were low-risk type (74 in training set, 31 in validation set) and 116 cases were high-risk type (85 in training set, 31 in validation set). The results of univariate analysis showed that there were significant differences in sex and chest pain between high-risk group and low-risk group (P < 0.05). Three CT features (tumor enhancement, pericardial or great vessel invasion, and pleural invasion) were selected using stepwise regression to construct a multivariate logistic regression model. Eight clinical and CT imaging features were selected through LASSO regression analysis for constructing random forest, decision tree, and support vector machine models. The AUCs for the models in the training set were 0.793, 0.854, 0.761, and 0.816, and in the validation set, they were 0.819, 0.742, 0.710, and 0.811, respectively. These results indicate that the logistic regression model has better generalization performance than the other three models.

The logistic regression model based on CT imaging features shows good diagnostic performance in predicting pathological subtypes of TETs and has potential for assisting clinicians in the early non-invasive identification of high-risk thymic tumors and thymic cancer.

To investigate the correlation between coronary artery calcium score (CACS) measured by coronary computed tomography (CCTA) combined with the Sukun Technology Intelligence Platform (AI), CT fractional flow reserve (CT-FFR), and plaque characteristics.

Based on the CACS values measured by AI, 208 patients who underwent CCTA examination at the First Affiliated Hospital of Bengbu Medical College from January 2021 to December 2022 were divided into three groups: low calcification group (n=73): 0<CACS<100; moderate calcification group (n=64): 100≤CACS≤400, high calcification group (n=71): CACS>400.Comparison of general clinical data and characteristics of culprit vessels and culprit plaques measured by AI in different CACS groups were analyzed. The correlation between characteristic parameters and CACS groups was assessed, and the diagnostic efficiency of single and combined indicators for two groups (low calcification group vs. moderate calcification group, moderate calcification group vs. high calcification group) was evaluated by drawing ROC curves to calculate the AUC.

Based on AI measurements, there were statistically significant differences (P<0.05) in CT-FFR, plaque length, plaque volume, and minimal lumen area (MLA) among different CACS groups. There was a significant difference in plaque type between the low calcification group and the moderate calcification group(P<0.05), but no statistical significance in differences between the moderate calcification group and the high calcification group (P>0.05). Multifactorial logistic regression analysis indicated that age, CT-FFR, plaque volume, and MLA were risk factors for higher CACS groups. Plaque volume was positively correlated with the severity of CACS (r=0.437, P<0.001), while CT-FFR and MLA were negatively correlated with it (r=-0.640, -0.658, P<0.001). The ROC curve showed that in the low calcification group to the moderate calcification group, the AUC values of CT-FFR, plaque volume, MLA and combined index are 0.731, 0.678, 0.748 and 0.824 respectively; in the moderate calcification group to the high calcification group, the AUC values of CT-FFR, plaque volume, MLA and combined index were 0.741, 0.670, 0.746 and 0.840 respectively. The diagnostic efficiency of the combined index of CT-FFR, plaque volume and MLA was greater than that of a single index in both groups.

AI measurements show significant differences in CT-FFR, plaque volume, and MLA among different CACS groups, indicating that they are risk factors for higher CACS groups. CT-FFR and MLA demonstrate good diagnostic performance across different CACS groups, while the combination of CT-FFR, plaque volume, and MLA significantly improves diagnostic efficacy

To investigate how pitch choice affects positioning errors during megavoltage computed tomography (MVCT) scanning using the Onrad system, a tomography radial radiotherapy system, for cervical cancer treatment.

A total of 16 cervical cancer patients who underwent Onrad system treatment in Department of Radiotherapy Shenzhen People's Hospital from October 2023 to January 2024 were chosen. The patients were split into two groups: Normal group (n=8) and Coarse group (n=8) based on the pitch utilized during MVCT scanning. Every day, an MVCT scan was conducted. By comparing the results with the positioning CT picture, the XYZ three-dimensional translation error and rolling error around the Y axis (Roll) were determined. Both the error data and the scanning time were tracked down and examined.

In the Normal group and the Coarse group, 200 sets of displacement error data in total were collected. The three-dimensional translation errors of Normal group were X=1.80±1.28 mm, Y=2.22 ± 1.43 mm, Z=1.78 ± 1.30 mm, and the rolling error was Roll= 0.32±0.41°. The 3D translation errors of Coarse group were X=1.98 ± 1.18 mm, Y=2.38±1.34 mm, Z=1.96 ± 1.27 mm, and rolling error was Roll=0.31±0.47°.For both the rolling error Roll (P=0.71) and the translation errors X, Y, Z (P=0.15, 0.23, 0.17), there was no discernible difference in the positioning errors between the two groups. When the pitch was set to Normal, the scanning time was substantially greater than when the pitch was set to Coarse in terms of scanning efficiency (253.4 ± 9.7 vs 173.3 ± 7.9 s, P<0.001).

For position calibration, MVCT images are scanned with Normal and Coarse pitch when the Onrad system is utilized for cervical cancer radiation therapy. The XYZ 3D translation errors and rolling error do not differ. Nevertheless, Coarse pitch selection increased scanning efficiency. There fore, Coarse pitch was advised.

To investigate the effect of proximal femoral anti-rotation intramedullary nail (PFNA) assisted by CT three-dimensional reconstruction on hip joint function and the incidence of complications in patients with intertrochanteric fracture of the femur.

Ninety-eight patients with intertrochanteric fracture who received treatment at Lianyungang Hospital affiliated to Xuzhou Medical University from January 2020 to October 2022 were included, and they were divided into the control group and the observation group by random number table method, with 49 cases in each group. The control group was treated with conventional PFNA, while the observation group was treated with PFNA assisted by CT three-dimensional reconstruction. Both groups were followed up for 12 months after operation. The clinical efficacy (12 months after follow-up), score of Harris hip (preoperative, postoperative 6 months, postoperative 12 months), thromboelastogram parameters (preoperative, postoperative 7 d), serum factors (preoperative, postoperative 3 months) and complications (during the study period) were compared between the two groups.

After a follow-up of 12 months, the total effective rate in the observation group was 97.96%, which was higher than that in the control group (85.71%) (P<0.05). Compared with before operation, score of Harris hip increased in both groups from 6 to 12 months after operation, especially in the observation group (P<0.05). Compared with before operation, on 7th day after operation, coagulation reaction time and coagulation formation time in both groups shortened, the observation group was shorter, while blood clot formation rate increased, and the observation group was larger (P<0.05). Compared with before operation, 3 months after operation, the levels of serum D-dimer in both groups decreased, and the values of serum prothrombin time were all shortened, and the levels of serum bone morphogenetic protein-2 and transforming growth factor-β1 all increased, the observation group was higher (P<0.05). During the study period, there was no significant difference in the total incidence of complications between the two groups (P>0.05).

PFNA treatment for patients with intertrochanteric fracture assisted by CT three-dimensional reconstruction could effectively improve the level of fracture healing factors, improve the coagulation function and thromboelastogram parameters of patients, and promote the recovery of hip joint function, with good safety and remarkable curative effect.

To evaluate the differential diagnostic value of ¹⁸F-FDG PET/CT multi-phase imaging after treated with pioglitazone (PIO) in the diagnosis of solitary pulmonary nodules (SPN).

Eighty-six SPN patients in the Department of Nuclear Medicine of Dongguan Tungwah hospital from October 2020 to January 2023 were collected. All patients were performed ¹⁸F-FDG PET/CT multi-phase (1 h, 2 h, 4 h) imaging, and 42 cases of imaging after PIO treatment were in the experimental group (PIO group), while 44 cases of conventional imaging were in the control group (Non-PIO group). The maximum standardized uptake values (SUV_max1, SUV_max2, SUV_max4) of each SPN was measured separately, and the retention index (RI2, RI4) of 2 h and 4 h delayed imaging was calculated. Finally, based on pathology and follow-up, whether the experimental group has improved the diagnostic efficacy in distinguishing between benign and malignant SPN was analyzed. The data was analyzed by using Mann-Whitney U test and ROC curve.

There were statistically significant differences between SUV_max2 and SUV_max4 in each group compared to SUV_max1 (P<0.001).The SUV_max1, SUV_max2, SUV_max4 and RI4 of malignant SPN in the PIO group were significantly higher than those of benign SPN (P<0.05), while there was no statistical significance between RI2 (P=0.214). There was no statistically significant difference in SPN values between malignant and benign SPN within the Non-PIO group (P>0.05). There was a statistically significant difference in RI4 between the two groups of malignant lesions (P=0.034), while there was no statistically significant difference in the other values (P>0.05). There was no statistically significant difference between the above values of benign lesions between the two groups (P>0.05). Using RI>10% as the diagnostic criterion for malignant lesions, the accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of diagnosing malignant SPN in the PIO group were higher than those in the Non-PIO group, and all indicators in the 4 h were higher than those in the 2 h. ROC curves showed that the area under the curve of the PIO group RI4 in diagnosing malignant SPN was 0.732, significantly higher than other groups.

After PIO treatment, the 4 h ¹⁸FFDG PET/CT delayed imaging of SPN can improve the diagnostic efficacy of malignant pulmonary nodules to a certain extent.