Objective To investigate the utility of combining breast mass growth orientation quantification with the S-Detect technique for predicting axillary lymph node(ALN)metastasis in breast cancer.Methods Data was collected from 163 breast cancer patients admitted to our hospital between March 2023 and October 2024,who were categorized into metastatic(n=62)and non-metastatic(n=101)groups based on ALN pathology results.All patients underwent routine preoperative ultrasound and S-Detect examination.Univariate and multivariate regression analyses were performed to assess the correlation between each observational index and ALN metastasis.Significant indexes were identified through screening,leading to the establishment of a logistic regression prediction model.The predictive value of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Results The univariate analysis revealed statistically significant differences(P<0.05)in the maximum diameter of the mass,border characteristics,margin features,calcification patterns,orientation angle,and blood flow between the two groups.Multifactorial analysis demonstrated that calcification,border characteristics,orientation angle,margin features,and maximum diameter independently influenced the prediction of axillary lymph node(ALN)status in breast cancer patients(P<0.05).Consequently,a logistic regression prediction model was constructed as follows:Y=-7.995+2.299×maximal diameter+1.171×border+2.137×margin+1.397×calcication+0.034×orientation angle.The area under curve(AUC)for this combined prediction model was 0.869 which significantly outperformed each independent influencing factor alone(P<0.05),indicating good agreement between this joint prediction model and pathological results(Kappa=0.701,P<0.05).Conclusions Quantification of the orientation angle of a breast mass aids in predicting axillary lymph node(ALN)metastasis and enhances the interpretation and application of non-parallel orientations.The combination of quantifying growth orientation based on breast mass with artificial intelligence S-Detect technique demonstrates promising predictive value for ALN metastasis in breast cancer,providing a reference basis for personalized treatment.

Objective To evaluate the predictive value of dual-modality ultrasound,incorporating conventional ultrasound and ultrasound elastography,in combination with S-Detect for cervical lymph node metastasis(CLNM)in patients with papillary thyroid carcinoma(PTC).Methods A retrospective analysis was conducted on the clinical data of 135 patients diagnosed with PTC who received treatment at the First Affiliated Hospital of Shihezi University between November 2023 and August 2024.For all patients,clinical baseline characteristics,conventional ultrasound findings,ultrasound elastography results,and S-Detect analysis data were collected.Independent predictors of CLNM in PTC were identified,and predictive models were developed.Receiver operating characteristic(ROC)curves were generated to compare the area under the curve(AUC)of the models.The most effective predictive model was selected to construct a risk probability nomogram,and the predictive performance and clinical applicability of this nomogram were subsequently evaluated.Results Age,maximum nodule diameter,boundary characteristics,capsular invasion,transverse-sectional morphological findings assessed by S-Detect,and ECI-based elasticity grading were identified as independent predictors of CLNM in PTC(all P<0.05).The AUC of the predictive model constructed using these six variables was 0.890(95%CI:0.835～0.945).The calibration curve demonstrated strong agreement between predicted and observed outcomes,and decision curve analysis indicated that the nomogram provided a favorable net clinical benefit within a threshold probability range of 2%to 91.5%.Conclusions Age,maximum nodule diameter,boundary characteristics,capsular invasion,sonographic features assessed by S-Detect in the transverse plane,and ECI-based elasticity grading are independent predictors of CLNM in PTC.A nomogram model incorporating these parameters demonstrates effective performance in predicting the likelihood of CLNM.

Objective To observe the value of 2D SECara-Net and 3D U2-Net models constructed based on 2D maximal intensity projection(MIP)and 3D time-of-flight MR angiography(3D TOF-MRA)images,respectively,also of their combination for MRA detecting unruptured saccular intracranial aneurysms(USIA).Methods Totally 973 patients with single USIA and 300 subjects who underwent healthy physical examination were retrospectively collected and divided into training set(n=923,containing 723 cases of USIA and 200 healthy subjects)and test set(n=350,containing 250 cases of USIA and 100 healthy subjects)at the ratio of 7:3.Pre-processed 3D TOF-MRA and the obtained 2D-MIP images in training set were imported into 3D U2-Net and 2D SECara-Net models for training and adjusting parameters,respectively.The efficiency of 2 models and their combination for detecting USIA were evaluated.Results The sensitivity,specificity and accuracy of 2D SECara-Net model for detecting USIA in test set was 78.80％(197/250),95.00％(95/100)and 83.43％(292/350),of 3D U2-Net model was 82.80％(207/250),86.00％(86/100)and 83.71％(293/350),respectively.The specificity of 2D SECara-Net model was higher than that of 3D U2-Net model(P=0.030),while no significant difference of sensitivity nor accuracy was found between 2 models(both P＞0.05).The specificity of the combination of the 2 models was 99.00％(99/100),higher than that of 3D U2-Net model(P＜0.05),and the sensitivity and accuracy of the combination was 91.20％(228/250)and 93.43％(327/350),respectivelty,both higher than those of 2 single models(all P＜0.05).Conclusion 2D SECara-Net and 3D U2-Net models had similar,sensitivity and accuracy for MRA detecting USIA.Combination of them could improve the detecting efficacy.

Objective To evaluate the predictive value of dual-modality ultrasound,incorporating conventional ultrasound and ultrasound elastography,in combination with S-Detect for cervical lymph node metastasis(CLNM)in patients with papillary thyroid carcinoma(PTC).Methods A retrospective analysis was conducted on the clinical data of 135 patients diagnosed with PTC who received treatment at the First Affiliated Hospital of Shihezi University between November 2023 and August 2024.For all patients,clinical baseline characteristics,conventional ultrasound findings,ultrasound elastography results,and S-Detect analysis data were collected.Independent predictors of CLNM in PTC were identified,and predictive models were developed.Receiver operating characteristic(ROC)curves were generated to compare the area under the curve(AUC)of the models.The most effective predictive model was selected to construct a risk probability nomogram,and the predictive performance and clinical applicability of this nomogram were subsequently evaluated.Results Age,maximum nodule diameter,boundary characteristics,capsular invasion,transverse-sectional morphological findings assessed by S-Detect,and ECI-based elasticity grading were identified as independent predictors of CLNM in PTC(all P<0.05).The AUC of the predictive model constructed using these six variables was 0.890(95%CI:0.835～0.945).The calibration curve demonstrated strong agreement between predicted and observed outcomes,and decision curve analysis indicated that the nomogram provided a favorable net clinical benefit within a threshold probability range of 2%to 91.5%.Conclusions Age,maximum nodule diameter,boundary characteristics,capsular invasion,sonographic features assessed by S-Detect in the transverse plane,and ECI-based elasticity grading are independent predictors of CLNM in PTC.A nomogram model incorporating these parameters demonstrates effective performance in predicting the likelihood of CLNM.

Objective To observe the value of 2D SECara-Net and 3D U2-Net models constructed based on 2D maximal intensity projection(MIP)and 3D time-of-flight MR angiography(3D TOF-MRA)images,respectively,also of their combination for MRA detecting unruptured saccular intracranial aneurysms(USIA).Methods Totally 973 patients with single USIA and 300 subjects who underwent healthy physical examination were retrospectively collected and divided into training set(n=923,containing 723 cases of USIA and 200 healthy subjects)and test set(n=350,containing 250 cases of USIA and 100 healthy subjects)at the ratio of 7:3.Pre-processed 3D TOF-MRA and the obtained 2D-MIP images in training set were imported into 3D U2-Net and 2D SECara-Net models for training and adjusting parameters,respectively.The efficiency of 2 models and their combination for detecting USIA were evaluated.Results The sensitivity,specificity and accuracy of 2D SECara-Net model for detecting USIA in test set was 78.80％(197/250),95.00％(95/100)and 83.43％(292/350),of 3D U2-Net model was 82.80％(207/250),86.00％(86/100)and 83.71％(293/350),respectively.The specificity of 2D SECara-Net model was higher than that of 3D U2-Net model(P=0.030),while no significant difference of sensitivity nor accuracy was found between 2 models(both P＞0.05).The specificity of the combination of the 2 models was 99.00％(99/100),higher than that of 3D U2-Net model(P＜0.05),and the sensitivity and accuracy of the combination was 91.20％(228/250)and 93.43％(327/350),respectivelty,both higher than those of 2 single models(all P＜0.05).Conclusion 2D SECara-Net and 3D U2-Net models had similar,sensitivity and accuracy for MRA detecting USIA.Combination of them could improve the detecting efficacy.

Objective To investigate the utility of combining breast mass growth orientation quantification with the S-Detect technique for predicting axillary lymph node(ALN)metastasis in breast cancer.Methods Data was collected from 163 breast cancer patients admitted to our hospital between March 2023 and October 2024,who were categorized into metastatic(n=62)and non-metastatic(n=101)groups based on ALN pathology results.All patients underwent routine preoperative ultrasound and S-Detect examination.Univariate and multivariate regression analyses were performed to assess the correlation between each observational index and ALN metastasis.Significant indexes were identified through screening,leading to the establishment of a logistic regression prediction model.The predictive value of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Results The univariate analysis revealed statistically significant differences(P<0.05)in the maximum diameter of the mass,border characteristics,margin features,calcification patterns,orientation angle,and blood flow between the two groups.Multifactorial analysis demonstrated that calcification,border characteristics,orientation angle,margin features,and maximum diameter independently influenced the prediction of axillary lymph node(ALN)status in breast cancer patients(P<0.05).Consequently,a logistic regression prediction model was constructed as follows:Y=-7.995+2.299×maximal diameter+1.171×border+2.137×margin+1.397×calcication+0.034×orientation angle.The area under curve(AUC)for this combined prediction model was 0.869 which significantly outperformed each independent influencing factor alone(P<0.05),indicating good agreement between this joint prediction model and pathological results(Kappa=0.701,P<0.05).Conclusions Quantification of the orientation angle of a breast mass aids in predicting axillary lymph node(ALN)metastasis and enhances the interpretation and application of non-parallel orientations.The combination of quantifying growth orientation based on breast mass with artificial intelligence S-Detect technique demonstrates promising predictive value for ALN metastasis in breast cancer,providing a reference basis for personalized treatment.

[摘 要] 目的：采用基于中国人群单核苷酸多态性位点开发的同源重组缺陷（HRD）检测工具评估云南地区卵巢癌患者的HRD状态和BRCA1/2基因突变频率并探讨其临床意义。方法：共纳入2021年1月至2023年5月间在云南省肿瘤医院收治的卵巢癌患者248例，HRD状态采用基因组瘢痕评分法（GSS）（主要依据拷贝数的长度、类型、位置及基因组断片）或HRD评分法（杂合性缺失、端粒等位基因失衡及大片段移位等基因组不稳定事件的总和）进行评估，当组织样本的GSS≥50分或HRD评分≥42分者或检测到有害的BRCA1/2基因突变时HRD被定义为阳性。分析患者HRD状态与临床病理特征的关系。结果：248名卵巢癌患者中70.97%的患者HRD呈阳性，其中BRCA1/2基因突变率为30.65%。Ⅲ~Ⅵ期、高级别浆液腺癌的卵巢癌患者具有更高的HRD阳性率（均P<0.01），HRD评分更高的患者其合并其他基因突变的频率也越高（P<0.05）。HRD状态与卵巢癌的病理类型、临床分期和其他基因突变均有关联（均P<0.01）。结论：云南地区卵巢癌患者HRD阳性率较高，HRD阳性的卵巢癌患者可以从聚ADP核糖聚合酶（PARP）抑制剂治疗中获得更大的收益。

The emergence of immune checkpoint inhibitors holds new promise for patients with small cell lung cancer. Studies have found that PD-L1 expression, tumor mutation burden, genomic characteristics, peripheral blood parameters and other indicators can be used as prognostic predictors in patients with small cell lung cancer receiving immunotherapy. Further exploration and evaluation of relevant predictors can provide a reference for screening patients with potential benefits of immunotherapy.

Objective:To evaluate the effects of left ventricular remodeling on systolic synchronization in patients with severe preeclampsia(SPE) by full-volume imaging technology.Methods:One hundred and nine patients with SPE were randomly selected as SPE group in the First Hospital of Shanxi Medical University from December 2016 to December 2019, which were further divided into systolic synchrony(SS) group ( n=35) and systolic dyssynchrony(SD) group( n=74). And 34 healthy pregnant women during the same period were selected as normal pregnancy(NP) group. The clinical datas were collected. Parameters including left ventricular end diastolic volume(LVEDV), left ventricular end systolic volume(LVESV), left ventricular ejection fraction(LVEF), spherical index(SpI), left ventricular mass index(LVMI) and systolic dyssynchrony index(SDI) were obtained by full-volume imaging technology. The effects of left ventricular remodeling on systolic synchronization in patients with SPE were analyzed by bivariate correlation, multiple linear stepwise regression analysis and binary Logistic regression analysis, respectively. Results:①Bivariate correlation analysis showed that LVEDV, LVESV, SpI and LVMI were positively correlated with SDI( r=0.335, 0.361, 0.635, 0.680; all P<0.01). ②After adjustment for age, body mass index, systolic blood pressure, course of hypertension, antihypertensive and antispasmodic treatments, gestational diabetes mellitus, subclinical hypothyroidism, LVEF, multiple linear regression analysis showed that SpI and LVMI were independent predictors of SDI (β=0.228, 0.319; all P<0.01). ③Binary Logistic regression analysis showed that SpI and LVMI were independently correlated with left ventricular systolic dyssynchrony [ OR(95% CI)=1.288(1.039-1.598), 1.102(1.019-1.192); all P<0.05]. Conclusions:Left ventricular remodeling in patients with SPE leads to the decrease of left ventricular systolic synchronization, which can reflect subclinical myocardial dysfunction early. Full volume imaging technology can accurately evaluate left ventricular systolic synchronization in patients with SPE.

Objective:To investigate the regulatory effects of endogenous nitric oxide (NO) on the activity of superoxide dismutase-1 (SOD1) and apoptosis of human umbilical vein endothelial cells (HUVECs).Methods:HUVECs were taken as the research object.The endothelial NO synthase (eNOS) short hairpin RNA(shRNA) lentivirus was employed to transfect HUVECs to knock down eNOS.HUVECs were divided in 4 groups: the scramble group, the eNOS shRNA group, the eNOS shRNA + sodium nitroprusside(SNP) group and the eNOS shRNA+ SNP+ tris (2-carboxyethyl) phosphine hydrochloride (TCEP) group.The protein expressions of eNOS and SOD1 dimer/monomer in cells were detected by western blot.The activity of SOD was detected by the enzyme-linked immunosorbent assay.The NO content in cells was detected with NO fluorescence probe.The level of superoxide anion in HUVECs was detected with dihydropyridine (DHE). The terminal deoxynucleotidyl transferase (TdT) dUTP nick-end labeling (TUNEL) assay was adopted to detect the apoptosis of HUVECs in situ.Results:Compared with the scramble group, the endogenous NO content (2.690±0.420 vs.15.029±2.193, P<0.01), eNOS protein expression (1.000±0.778 vs.3.141±0.199, P<0.01), SOD1 dimer/monomer ratio (4.6±1.0 vs.7.6±2.0, P<0.05) and SOD activity [(0.432±0.254) Carmen′s unit/10 4 cell vs.(1.000±0.116) Carmen′s unit/10 4 cell, P<0.01] were significantly decreased, while the level of intracellular superoxide anion (11.180±1.560 vs.6.146±1.007, P<0.01) and HUVECs apoptosis [75.0 (55.0, 100.0)% vs.0 (0, 0)%, P<0.01] were significantly increased in the eNOS shRNA group.Compared with the eNOS shRNA group, the content of endogenous NO (16.705±0.116 vs.2.690±0.420, P<0.01), the ratio of SOD1 dimer/monomer (7.3±2.0 vs.4.6±1.0, P<0.05) and the activity of SOD [(0.737±0.060) Carmen′s unit/10 4 cell vs.(0.432±0.254) Carmen′s unit/10 4 cell, P<0.05] were significantly increased, while the level of superoxide anion (6.897±1.648 vs.11.180±1.560, P<0.01) and the HUVECs apoptosis [0 (0, 0)% vs.75.0 (55.0, 100.0)%, P<0.01] were significantly decreased in the eNOS shRNA+ SNP group.Compared with the eNOS shRNA + SNP group, the ratio of SOD1 dimer/monomer (4.4±0.9 vs.7.3±2.0, P<0.05) and the activity of SOD [(0.214±0.084) Carmen′s unit/10 4 cell vs.(0.737±0.060) Carmen′s unit/10 4 cell, P<0.01] were significantly decreased, while the level of superoxide anion (10.917±1.552 vs.6.897±1.640, P<0.01) and the apoptosis level of HUVECs[63.6 (55.0, 90.0)% vs.0 (0, 0)%, P<0.01] were significantly increased in the eNOS shRNA+ SNP+ TCEP group.However, there was no significant difference in the NO content (16.112±0.926 vs.16.705±0.116, P>0.05). Conclusions:Endogenous NO could effectively antagonize the apoptosis of endothelial cells by increasing the cysteine-dependent SOD1 dimer/monomer ratio, enhancing SOD activity and inhibiting the accumulation of reactive oxygen species.