Objective:To establish and validate the diagnostic model of acute pulmonary embolism (APE) based on clinical and laboratory variables.Methods:This retrospective analysis was conducted on patients with suspected APE who underwent CT pulmonary angiography at the First Affiliated Hospital of Henan University of Chinese Medicine between February 2015 and December 2023. The patients were randomly divided into a training set and a validation set at a ratio of 7∶3. Clinical and laboratory data of the enrolled patients were collected, and patients were divided into an APE group and a non-APE group according to CT pulmonary angiography results. In the training set, univariate and multivariate logistic regression as well as Lasso regression were used to identify risk factors for APE, and a diagnostic model was developed and validated. Receiver operating characteristic curves were plotted, and calibration and decision curves were used to assess the performance of the diagnostic model. The diagnostic efficacy of the model was compared with that of the Wells score and the revised Geneva score using the DeLong test.Results:A total of 752 patients were enrolled, aged (64±15) years, including 417 (55.5%) males. The training set included 526 patients and the validation set included 226 patients. The incidence of APE in this cohort was 48.7% (366/752), with 366 cases in the APE group and 386 in the non-APE group. Multivariable logistic regression analysis showed that cyanosis ( OR=8.88, 95% CI 2.04-49.11), elevated neutrophil count ( OR=1.82, 95% CI 1.06-3.15), elevated creatine kinase isoenzyme ( OR=3.45, 95% CI 1.76-6.91), decreased partial pressure of carbon dioxide ( OR=12.88, 95% CI 7.64-22.34), elevated age-adjusted D-dimer ( OR=2.53, 95% CI 1.10-6.20), prolonged thrombin time ( OR=4.08, 95% CI 2.06-8.33), and positive lower limb venous ultrasound for thrombus ( OR=4.39, 95% CI 2.59-7.58) were risk factors associated with APE. The area under the curve ( AUC) of the diagnostic model was 0.92 (95% CI 0.90-0.94) in the training set and 0.92 (95% CI 0.89-0.95) in the validation set. The diagnostic efficacy of this model was superior to that of the Wells score ( AUC: 0.92 vs. 0.63, P<0.01) and the revised Geneva score ( AUC: 0.92 vs. 0.59, P<0.01). Conclusion:The diagnostic model for acute pulmonary embolism constructed based on clinical and laboratory parameters demonstrates excellent diagnostic performance and may facilitate rapid and accurate screening in clinical practice.

Purpose To achieve intelligent detection of acute pulmonary embolism(APE)in CT pulmonary angiography based on the Res2Net attention mechanism network.Materials and Methods Retrospectively included patients with suspected of APE who underwent CT pulmonary angiography examination and were diagnosed as APE at the First Affiliated Hospital of Henan University of Chinese Medicine from February 2015 to May 2023.The dataset was randomly divided into training,validation and test set in a ratio of 7∶2∶1.The model was trained based on the Res2Net network,combined with atrous spatial pyramid pooling and attention mechanism modules,and was performed five-fold cross internal validation.Using the area under the receiver operator characteristic curve,sensitivity and specificity to assess the diagnostic performance of the model.Dice similarity coefficient,precision and intersection over union(IOU)were used to assess the segmentation performance of thrombus on the test set and plot the corresponding curves.The performance of the Res2Net attention mechanism network was compared with the classic U-Net and CE-Net model.Results A total of 303 patients with APE were included in this study.There were 212,61 and 30 cases in the training set,validation set and test set,respectively.The model's area under the curve was 0.95,sensitivity was 0.90,specificity was 1.00,Dice similarity coefficient was 0.86,precision was 0.90,Pos-IOU was 0.78 and Neg-IOU was 1.00,respectively.The parameter curves and radar chart showed that the Res2Net attention mechanism network performed better than the U-Net and CE-Net models.The visualization results of the segmentation comparison showed that the Res2Net attention mechanism network achieved higher precision in segmenting pulmonary artery thrombus.Conclusion The Res2Net attention mechanism network has good performance for detection of APE.

Purpose To achieve intelligent detection of acute pulmonary embolism(APE)in CT pulmonary angiography based on the Res2Net attention mechanism network.Materials and Methods Retrospectively included patients with suspected of APE who underwent CT pulmonary angiography examination and were diagnosed as APE at the First Affiliated Hospital of Henan University of Chinese Medicine from February 2015 to May 2023.The dataset was randomly divided into training,validation and test set in a ratio of 7∶2∶1.The model was trained based on the Res2Net network,combined with atrous spatial pyramid pooling and attention mechanism modules,and was performed five-fold cross internal validation.Using the area under the receiver operator characteristic curve,sensitivity and specificity to assess the diagnostic performance of the model.Dice similarity coefficient,precision and intersection over union(IOU)were used to assess the segmentation performance of thrombus on the test set and plot the corresponding curves.The performance of the Res2Net attention mechanism network was compared with the classic U-Net and CE-Net model.Results A total of 303 patients with APE were included in this study.There were 212,61 and 30 cases in the training set,validation set and test set,respectively.The model's area under the curve was 0.95,sensitivity was 0.90,specificity was 1.00,Dice similarity coefficient was 0.86,precision was 0.90,Pos-IOU was 0.78 and Neg-IOU was 1.00,respectively.The parameter curves and radar chart showed that the Res2Net attention mechanism network performed better than the U-Net and CE-Net models.The visualization results of the segmentation comparison showed that the Res2Net attention mechanism network achieved higher precision in segmenting pulmonary artery thrombus.Conclusion The Res2Net attention mechanism network has good performance for detection of APE.

Objective:To establish and validate the diagnostic model of acute pulmonary embolism (APE) based on clinical and laboratory variables.Methods:This retrospective analysis was conducted on patients with suspected APE who underwent CT pulmonary angiography at the First Affiliated Hospital of Henan University of Chinese Medicine between February 2015 and December 2023. The patients were randomly divided into a training set and a validation set at a ratio of 7∶3. Clinical and laboratory data of the enrolled patients were collected, and patients were divided into an APE group and a non-APE group according to CT pulmonary angiography results. In the training set, univariate and multivariate logistic regression as well as Lasso regression were used to identify risk factors for APE, and a diagnostic model was developed and validated. Receiver operating characteristic curves were plotted, and calibration and decision curves were used to assess the performance of the diagnostic model. The diagnostic efficacy of the model was compared with that of the Wells score and the revised Geneva score using the DeLong test.Results:A total of 752 patients were enrolled, aged (64±15) years, including 417 (55.5%) males. The training set included 526 patients and the validation set included 226 patients. The incidence of APE in this cohort was 48.7% (366/752), with 366 cases in the APE group and 386 in the non-APE group. Multivariable logistic regression analysis showed that cyanosis ( OR=8.88, 95% CI 2.04-49.11), elevated neutrophil count ( OR=1.82, 95% CI 1.06-3.15), elevated creatine kinase isoenzyme ( OR=3.45, 95% CI 1.76-6.91), decreased partial pressure of carbon dioxide ( OR=12.88, 95% CI 7.64-22.34), elevated age-adjusted D-dimer ( OR=2.53, 95% CI 1.10-6.20), prolonged thrombin time ( OR=4.08, 95% CI 2.06-8.33), and positive lower limb venous ultrasound for thrombus ( OR=4.39, 95% CI 2.59-7.58) were risk factors associated with APE. The area under the curve ( AUC) of the diagnostic model was 0.92 (95% CI 0.90-0.94) in the training set and 0.92 (95% CI 0.89-0.95) in the validation set. The diagnostic efficacy of this model was superior to that of the Wells score ( AUC: 0.92 vs. 0.63, P<0.01) and the revised Geneva score ( AUC: 0.92 vs. 0.59, P<0.01). Conclusion:The diagnostic model for acute pulmonary embolism constructed based on clinical and laboratory parameters demonstrates excellent diagnostic performance and may facilitate rapid and accurate screening in clinical practice.

Objective To evaluate the clinical value of gemstone spectral imaging (GSI) in preliminary assessment of esophageal carcinoma pathology features.Methods 58 patients were analyzed which were diagnosed with histological pathology as esophageal carcinoma underwent GSI enhanced scans before surgery.The iodine concentrations (IC) in the lesions were measured on the iodine-water based material-decomposition images.The results of IC value were evaluated retrospectively with different pathological grading,locations and pathological morphology according to the final pathologic findings.Results 52 cases patients were squamous cell carcinoma and 6 patients were adenocarcinoma.The IC values were (14.75±4.24) mg/ml and (12.86±5.09) mg/ml.The IC value between the two different pathological types had not statistically difference (P =0.35).The IC of different pathological grading:Well differentiation was (20.08± 4.66)mg/ml,n =19.Medium was (14.13±3.39) mg/ml,n =25.Poor was(11.73±3.21) mg/ml,n =14.The IC values between pathological grading had significant difference(P =0.00).There were four different pathological morphology including m edullar (n =16),m ushroom type (n =21),ulcer (n =13) and narrow type (n =8).Their IC values respectively were (16.34±2.56) mg/ml,(18.70±3.03) mg/ml,(14.31±4.60) mg/ml and (11.18±2.09) mg/ml.The IC value between mushroom and narrow type had statistical difference (P =0.04).The Other types had no statistically difference (P =0.19).Conclusions The results of this study demonstrate that GSI has a certain ability of pathologic stage of esophageal cancer.The GSI has a certain clinical value in guiding treatment and judging prognosis of esophageal carcinoma.

Objective To explore the imaging and clinical pathological features of extranoda and intranoda lymphoma in head and neck characterized by computed tomography (CT) and magnetic resonance imaging (MRI).Methods 46 malignant lymphoma patients were confirmed by surgery and pathology.The CT and MR images data were reviewed and analyzed in comparison with surgical and pathological results.Diagnostic value of the CT and MRI findings were analyzed. Results The subjects enrolled in this study including 38 cases of non-Hodgkin lymphoma(NHL)and 8 cases of Hodgkin Lymphoma(HL).The pathological sites of extranodal lymphomas (45.65 ％,21/46) included nasal (10 cases),Waldeyer ring (7 cases),throat (2 cases),Thyroid(1 case) and parotid (1 case).The lymph nodes metastases in the neck were observed in 13 cases of Extranodal lymphomas.Intranodal lymphoma in neck (54.35 ％,25/46) involved all district lymph nodes especially Ⅱ-Ⅳ districts. According to the Ann Arbor staging,14 cases were Ⅰ staging, 19 cases Ⅱ staging,none Ⅲ staging,Ⅳ staging 13 cases.According tumor form,21 cases were multinodulars,12 cases mass type, 11 cases diffuse swelling type, 2 cases ulcer or necrotic type. Conclusion CT and MR images might indicate the location, morphology, surrounding tissue and lymph nodes metastases of malignant lymphoma in head and neck.Great value in clinical diagnosis and treatment is observed.

Objective To investigate the characteristics and value of nasal area-distance curves.Methods Based on data from CT images, nasal cavity cross-sectional areas in 60 volunteers were reconstructed. The size of each nasal airway and the distance from nostril to the corresponding cross-sectional area were measured. Area-distance curves were then established according to data obtained. t test was used to analysis the data. Results Three types of curves were found and categorized according to their shapes.Type Ⅰ consisted of 56 sides (46.7%) ,type Ⅱ 40 sides(33.3%), and type Ⅲ 24 sides (20. 0% ). Forcurves of nasal valve area, smooth type was seen in 86 sides (71.7%), and concave type in 34 sides(28.3%). Curves in area of inferior turbinate head were seen with shallow notch(48 sides,40.0%) ,deep notch (54 sides,45.0%), and no notch( 18 sides,15.0% ). Curves in area of middle turbinate head wereseen with shallow notch (31 sides, 25.8%), deep notch (38 sides, 31.7%), and no notch ( 51 sides,42. 5% ). Nasal minimal cross-sectional area was located at nasal valve area in76 sides (63.3%), head of inferior turbinate in 26 sides ( 21.7% ), region anterior to nasal valve in 15 sides ( 12. 5% ), head ofmiddle turbinate in 1 side, and region anterior to choana in 2 sides. The cross-sectional area at nasal valve in men and women were (197.9 ±41.2) and (151.2 ±35.5) mm2, respectively. The cross-sectional area at choana in men and women were (361.8±97.9) and (296.3 ± 81.8) mm2, respectively. There wassignificant difference between men and women at both sites (t = 4.707 and 0. 007, P ＜ 0.01). The distance from nostril to nasal valve in men and women were (14. 0 ± 2.4) and ( 11.8 ± 2. 9) mm, which presented significant difference, too (t = 3. 232,P ＜ 0. 01). Conclusions CT nasal area-distance curve varied with individual, CT may provide information for evaluating nasal passage on individual basis