Objective To compare the segmenting efficacy of automatic segmentation models for advanced gastric cancer(AGC)on CT virtual monoenergetic images(VMI),non-linear blending images(NLBI)and mixed-energy images(MEI)based on 3D-nnU-Net.Methods Totally 216 cases of AGC were retrospectively enrolled,among them 185 cases were used to construct,train and validate models and divided into training set(n=154)and test set(n=31)at the ratio of 5∶1,while the other 31 cases were used as validation set to evaluate the generalization of the models.The 70 keV energy level VMI(VMI70 keV),NLBI and MEI were reconstructed with whole-abdominal dual-energy mode venous CT,and automatic segmentation models of AGC,including VMI70 keV,NLBI and MEI models were constructed using 3D-nnU-Net,respectively.Taken manually segmented results as golden standards,the efficacy of each model for segmenting all lesions and T2 stage lesions in test set and validation set were evaluated using Dice similarity coefficient(DSC),intersection over union(IoU)and average symmetric surface distance(ASSD).Results For all lesions in test and validation sets,DSC of 3 models were all＞0.80.DSC and IoU of VMI70 keV and NLBI models were both higher,while their ASSD was lower than those of MEI model(all P＜0.05).For T2 stage AGC in both test set and validation set(each n=5),DSC of MEI model was lower than that of VMI70 keV and NLBI models(both P＜0.05),while IoU of MEI model was lower than that of VMI70 keV model(P＜0.05),and its ASSD was higher than that of NLBI model(P＜0.05).Conclusion All 3D-nnU-Net-based VMI70 keV,NLBI and MEI models could effectively segment AGC on dual-energy CT images,and the segmentation efficacy of the former two were better.

Objective To compare the segmenting efficacy of automatic segmentation models for advanced gastric cancer(AGC)on CT virtual monoenergetic images(VMI),non-linear blending images(NLBI)and mixed-energy images(MEI)based on 3D-nnU-Net.Methods Totally 216 cases of AGC were retrospectively enrolled,among them 185 cases were used to construct,train and validate models and divided into training set(n=154)and test set(n=31)at the ratio of 5∶1,while the other 31 cases were used as validation set to evaluate the generalization of the models.The 70 keV energy level VMI(VMI70 keV),NLBI and MEI were reconstructed with whole-abdominal dual-energy mode venous CT,and automatic segmentation models of AGC,including VMI70 keV,NLBI and MEI models were constructed using 3D-nnU-Net,respectively.Taken manually segmented results as golden standards,the efficacy of each model for segmenting all lesions and T2 stage lesions in test set and validation set were evaluated using Dice similarity coefficient(DSC),intersection over union(IoU)and average symmetric surface distance(ASSD).Results For all lesions in test and validation sets,DSC of 3 models were all＞0.80.DSC and IoU of VMI70 keV and NLBI models were both higher,while their ASSD was lower than those of MEI model(all P＜0.05).For T2 stage AGC in both test set and validation set(each n=5),DSC of MEI model was lower than that of VMI70 keV and NLBI models(both P＜0.05),while IoU of MEI model was lower than that of VMI70 keV model(P＜0.05),and its ASSD was higher than that of NLBI model(P＜0.05).Conclusion All 3D-nnU-Net-based VMI70 keV,NLBI and MEI models could effectively segment AGC on dual-energy CT images,and the segmentation efficacy of the former two were better.

Objective:To investigate the value of CT radiomic model based on analysis of primary gastric cancer and the adipose tissue outside the gastric wall beside cancer in differentiating stage T1-2 from stage T3-4 gastric cancer.Methods:This study was a case-control study. Totally 465 patients with gastric cancer treated in Affiliated People′s Hospital of Jiangsu University from December 2011 to December 2019 were retrospectively collected. According to postoperative pathology, they were divided into 2 groups, one with 150 cases of T1-2 tumors and another with 315 cases of T3-4 tumors. The cases were divided into a training set (326 cases) and a test set (139 cases) by stratified sampling method at 7∶3. There were 104 cases of T1-2 stage and 222 cases of T3-4 stage in the training set, 46 cases of T1-2 stage and 93 cases of T3-4 stage in the test set. The axial CT images in the venous phase during one week before surgery were selected to delineate the region of interest (ROI) at the primary lesion and the extramural gastric adipose tissue adjacent to the cancer areas. The radiomic features of the ROIs were extracted by Pyradiomics software. The least absolute shrinkage and selection operator was used to screen features related to T stage to establish the radiomic models of primary gastric cancer and the adipose tissue outside the gastric wall beside cancer. Independent sample t test or χ2 test were used to compare the differences in clinical features between T1-2 and T3-4 patients in the training set, and the features with statistical significance were combined to establish a clinical model. Two radiomic signatures and clinical features were combined to construct a clinical-radiomics model and generate a nomogram. The area under the receiver operating characteristic curve (AUC) was used to evaluate the efficacy of each model in differentiating stage T1-2 from stage T3-4 gastric cancer. The calibration curve was used to evaluate the consistency between the T stage predicted by the nomogram and the actual T stage of gastric cancer. And the decision curve analysis was used to evaluate the clinical net benefit of treatment guided by the nomogram and by the clinical model. Results:There were significant differences in CT-T stage and CT-N stage between T1-2 and T3-4 patients in the training set ( χ2=10.59, 15.92, P=0.014, 0.001) and the clinical model was established. After screening and dimensionality reduction, the 5 features from primary gastric cancer and the 6 features from the adipose tissue outside the gastric wall beside cancer established the radiomic models respectively. In the training set and the test set, the AUC values of the primary gastric cancer radiomic model were 0.864 (95% CI 0.820-0.908) and 0.836 (95% CI 0.762-0.910), and the adipose tissue outside the gastric wall beside cancer radiomic model were 0.782 (95% CI 0.731-0.833) and 0.784 (95% CI 0.702-0.866). The AUC values of the clinical model were 0.761 (95% CI 0.705-0.817) and 0.758 (95% CI 0.671-0.845), and the nomogram were 0.876 (95% CI 0.835-0.917) and 0.851 (95% CI 0.781-0.921). The calibration curve reflected that there was a high consistency between the T stage predicted by the nomogram and the actual T stage in the training set ( χ2=1.70, P=0.989). And the decision curve showed that at the risk threshold 0.01-0.74, a higher clinical net benefit could be obtained by using a nomogram to guide treatment. Conclusions:The CT radiomics features of primary gastric cancer lesions and the adipose tissue outside the gastric wall beside cancer can effectively distinguish T1-2 from T3-4 gastric cancer, and the combination of CT radiomic features and clinical features can further improve the prediction accuracy.

Objective To observe the value of MRI in evaluation on the morphology and function of iliococcygeal muscles in fertile and nulliparous women.Methods Totally 50 healthy fertile women (fertile group,further divided into cesarean section subgroup and spontaneous delivery subgroup according to the mode of delivery) and 17 nulliparous healthy women (nulliparous group) underwent MR scanning in both natural and increased abdominal pressure state.Iliococcygeus thickness (ICT),coronal iliococcygeal angle (cICA) and sagittal iliococcygeal angle (sICA) of different states were measured and compared between the groups.Results In the natural state,the right and bilateral average sICA in the fertile group were larger than those in nulliparous group (both P＜0.05),while no statistical difference of ICT,right,left and bilateral average cICA and left sICA were found between two groups (all P＞0.05);the bilateral average sICA in spontaneous delivery subgroup was larger than that in cesarean section subgroup (P＜0.05).In increased abdominal pressure state,left,right sICA and bilateral average sICA in fertile group were larger than those in nulliparous group (all P＜0.05),while there was no statistical difference of ICT and cICA between two groups (all P＞0.05);no statistical difference of ICT,cICA nor sICA was found between spontaneous delivery subgroup and cesarean section subgroup (all P＞0.05).Conclusion MRI can accurately evaluate morphological and functional changes of iliococcygeal muscle in females.

Objective To analyze CT findings of nasal NK/T-cell lymphoma.Methods The CT findings of 11 nasal NK/T-cell lymphomas, 134 nasal polyps and 24 nasal inverted papillomas were analyzed retrospectively.Fisher exact test was used to compare the differences of the three nasal lesions.Results Compared with the nasal polyps, nasal NK/T-cell lymphoma had a higher occurrence in the unilateral nasal cavity, more presented as nodular mass or mold growth,and more easily to invade nasal vestibule,nasal ala,nasal mucosal,nasopharyngeal wall and causebone destruction.Compared with the inverted papilloma,nasal NK/T-cell lymphoma had a higher incidence of tumor invasion to nasal vestibule, nasal ala, nasopharyngeal cavity, nasal mucosal.Conclusion Nasal NK/T-cell lymphoma is a homogenous tumor and often occurres in the unilateral nasal cavity, which creeps along the lateral wall of the nasal cavity, and causes the damage of nasal mucosal and surrounding soft tissue and slight destruction of bone in the early satge.

Objective To evaluate the accuracy of MSCT in the pre-operative N-staging and diagnosis of metastatic lymph nodes in each group of gastric cancer.Methods Pathological and CT data of 91 patients with gastric cancer proved by surgery and pathology were analyzed retrospectively.Three-phase dynamic enhancements were performed before surgery in a unified way of hypotonic oral water,N-stage and grouping of lymph nodes of the preoperative CT imaging were evaluated by using the established diagnostic criteria and then compared with the results of surgery and pathology,the accuracy of staging and grouping was analyzed by using Kappa test.Results The accuracy of MSCT diagnosing the N-staging as a whole was 86.3%.The accuracy for N0,N1,N2 and N3 was 83.5%,89.0%,83.5% and 89.0%,respectively.The sensitivity was 86.5%,83.3%,50% and 47.4%,respectively.The specificity was 79.5%,89.4%,89.6% and 100.0%, respectively.The sensitivity for N0 was statistically different from that for N2, N0 and N3(P≤0.007).The detected accuracy for the group of left side of the cardium (No.2), periphery of the splenic hilum (No.10), posterior of the pancreastic head (No.13) were higher than other groups on MSCT with the accuracyof 100%.The sensitivity for the group of No.2,periphery of the coeliac trunk(No.9),No.10,and No.13 was 100%.The specificity for the group of No.2,No.10,and No.13 was 98.9%.Conclusion Relatively high accuracy in the preoperative N-staging and diagnosis of metastatic lymph nodes in each group of gastric cancer can be obtained by MSCT, which provide reliable information for preoperative assessment and intraoperative lymph node dissections.