Objective To assess whether aortic valve calcification (AVC) and mitral annual calcification (MAC) is independent predictors for coronary artery disease (CAD).Methods Coronary CT angiography(CCTA) data in a total of 263 patients were included in this study,including 30 patients with MAC, 82 patients with AVC and 31 patients with MAC+AVC;meanwhile other 120 patients without valvular calcification were regarded as a control group.Five indicators were used to evaluate the extent and severity of CAD, namely, the prevalence of coronary plaque, multi-coronary vessels lesions, degrees of coronary artery narrowing, incidence of moderate to severe coronary artery calcification score and mean number of affected coronary artery segments.The correlations of MAC,AVC,MAC+AVC with CAD were analyzed by Logistic regression analysis.Results The presence and severity of CAD were significantly greater in patients with MAC, AVC and MAC+AVC than those in control group.After adjustment for CAD conventional risk factors,Logistic regression analysis revealed that AVC,MAC and MAC+AVC were independently associated with the presence and severity of CAD.Conclusion AVC and MAC are independent predictors for CAD and often predict the more presence and greater severity of CAD.

Objective To investigate the feasibility and clinical application of prospective ECG-gated scan and adaptive cardio se-quence scan of dual-source CT coronary angiography.Methods 255 patients who underwent coronary CT angiography using a dual-source CT scanner were divided into two groups:group A underwent prospective scan,group B underwent retrospective scan.The two groups were further subdivided into low heart rate group and high heart rate group,recorded as A1(n=51),A2(n=89),B1(n=26), B2(n=89),respectively.Group A1 preceded with prospective ECG gated scan;group A2 performed with adaptive cardio sequence scan;group B1 and B2 underwent retrospective scan.All of them applied ATCM (automatic tube current modulation)technique. Effective dose was recorded.The image quality was assessed by two experienced radiologists with a four-point grading scale.Results The excellent or good image quality (score 1 and 2)of the four groups were above 95%,and no statistical differences in images scores was detected in A1 and B1 (P =0.726),A2 and B2 (P =0.079).Effective dose was significantly different in A1 and B1(P <0.001),A2 and B2 (P <0.001),and the former decreased 50% and 40% as compared with the latter.Conclusion Using prospective ECG gated scan and adaptive cardio sequence scan,assessable image quality of coronary artery can be acquired with dual source CT (heart rate<90 beast per minute),and radiation dose can be obviously reduced.

Objective To study the value of CT and barium radiograpy in diagnosis of gastric schwannoma.Methods A retrospectiveanalysis was made on imaging of 8 patients with pathologically approved gastric schwannoma.Plain abdominal CT scan was performed in all patients, additional enhanced CT scan was carried out in 6 cases and barium radiography of upper digestive tract was carried out in 5 cases. Results The lesions localized in fundus ventriculi in 2 cases, curvatura ventriculi minor in 4 cases and pars pylorica in 2 cases. Three main types were seen: localized mass type (n=4), localized thickening of gastric paries type (n=2) and huge mass type (n=2).Conclusion In comparison with barium radiography of upper digestive tract, CT can accurately demonstrate the shape, the location and internal structure of lesions.Three main patterns of this lesion also can be showed clearly by CT scans and suggestive diagnosis can be made in some patients combined with barium radiography of upper digestive tract images.

PurposePrimary chest wall rhabdomyosarcoma (RMS) is very rare with limited imaging characteristic studies in the literature. This paper analyzes the CT imaging features of chest wall RMS in children to improve the diagnostic accuracy.Materials and MethodsThe imaging data of contrast enhanced CT scan of pathology conifrmed chest wall RMS in ifve children were analyzed.ResultsThe lesion was located in the anterior chest wall in one case, in the posterior chest wall in two cases, and the lateral chest wall in two cases (axillary). The tumors were round or spindle in shape with shallow spiculation. Plain CT showed heterogeneous density with patchy low-density necrotic area in two cases, and homogeneous attenuation in three patients. In all ifve cases there was no calciifcation or fatty tissue. The tumor involvement of adjacent spinal canal was seen in one case. Visceral compression was evident including lung parenchyma in one case, heart and liver in one case. Tumor blood vessel growth was seen in two cases. All ifve lesions were adjacent to the ribs, humerus, scapula and the spine with bone destruction in one case. On contrast enhanced scan, all ifve cases demonstrated heterogeneous mild to moderate enhancement, more prominent in the periphery. There were enlarged feeding arteries. Necrotic areas did not enhance. In two cases there were pulmonary metastases. Pleural effusion and ascites were identiifed in one case. There was lymph node metastasis in one case.ConclusionThe CT manifestation of children's chest wall RMS for chest wall include large soft tissue mass, heterogeneous density, no calciifcation or fatty tissue, partial necrosis, adjacent tissue compression, lymph node or distant metastasis. Combining with clinical manifestations, comprehensive analysis of contrast enhanced CT imaging can improve diagnostic accuracy.

Objective To investigate the influence of liver fat deposition on the quantification of the liver iron overload using fast-kilovolt-peak switching dual-energy CT imaging and material decomposition technique. Methods A total of 20 healthy SD rats were taken to make 18 PVC tube of homogenate of fresh liver tissue. The dextran with concentration of 50, 40, 30, 20, 10 and 0 mg/ml were mixed with rat liver homogenate and triglyceride with three different concentrations (add fat with volume percentage of 60％, 30％, 10％ and to simulate severe, moderate and mild fatty liver respectively). All samples were placed in standard phantom according to the order of iron concentration from high to low and scanned by GE Revolution CT 256 slices scanner in GSI mode with rapid tube voltage switching between 80 and 140 kVp and with tube current 200 mA, 320 mA, 485 mA respectively. The images of iron (fat)-based substance pair were reconstructed and the virtual iron concentration (VIC) value were recorded. The correlation between VIC and the actual liver concentration (LIC) of the three sets of tube currents (200, 320, 485 mA) was analyzed by Spearman correlation analysis and linear regression. Results LIC and VIC were highly positively correlated with the liver iron deposition model under different tube currents (r value was 0.900 to 1.000, P<0.05). The presence of fat will result in the decrease of VIC value. In a certain X-ray energy range and certain liver iron concentration, the higher the fat content, the more liver iron concentration underestimation were happened in VIC. At 200, 320 and 485 mA, the crossing points of linear equations for 30％and 10％fatty liver iron deposition models were located at VIC=12.682, 12.470 and 13.447 mg/cm3, respectively. Conclusions The fast-kilovolt-peak switching dual-energy CT imaging and material decomposition techniques can be used for quantitative evaluation of liver iron with hepatic steatosis. The presence of fat will lead to a decrease in VIC measurement.

Objective:To establish the predictive models for the prognosis of ductal carcinoma in situ (DCIS) at different pathological stages, and to evaluate the predictive performance of the models.Methods:Complete data of 273 patients with confirmed DCIS at different pathological stages who underwent mammography examination in Shenzhen People′s Hospital, Peking University Shenzhen Hospital and Shenzhen Luohu People′s Hospital from November 2014 to December 2020 were retrospectively collected, including 110 cases in the DCIS+ductal carcinoma in situ with microinvasion (DCIS-MI) group and 163 cases in the invasive ductal carcinoma (IDC)-DCIS group. The clinical, imaging and pathological features were analyzed. Mammary Mammo AI fusion model and deep learning-based natural language processing (NLP) structured diagnostic report model were used for image feature extraction. Patients in each group were randomly divided into training set and validation set with a ratio of 6∶4, and the predictors were screened by univariate and multivariate logistic regression analysis. The lowest Akaike information criterion value of each group was selected to construct the final predictive model. The receiver operating characteristic (ROC) curve was drawn to evaluate the performance of each model.Results:Taking estrogen receptor (-) or human epidermal growth factor receptor 2 (3+) as the poor prognostic reference, there were 62 cases considered with poor prognosis and 48 cases with good prognosis in DCIS+DCIS-MI group; while in the IDC-DCIS group, taking the Nottingham prognostic index as the reference, 33 cases were considered with poor prognosis, 73 cases with moderate prognosis, and 57 cases with good prognosis. Four predictive factors were screened to construct the DCIS+DCIS-MI-group predictive model, including DCIS nuclear grade, calcification with suspicious morphology in mammography, DCIS pathologic subtype and DCIS with microinvasion. Five predictive factors were screened to construct the IDC-DCIS-group predictive model, including neural or vascular invasion, Ki67 level, DCIS subtype, DCIS component proportion and associated features in mammography. The area under curve (AUC) for predicting poor prognosis of DCIS+DCIS-MI was 0.92 (95%CI 0.84-1.00) in the training set and 0.90 (95%CI 0.82-0.99) in the validation set; while the AUC for predicting poor prognosis of IDC-DCIS was 0.84 (95%CI 0.76-0.93) in the training set and 0.78 (95%CI 0.64-0.91) in the validation set.Conclusion:The developed models based on deep learning combined with NLP can effectively predict the prognosis of DCIS at different pathological stages, which are beneficial to the risk stratification of patients with DCIS, providing a reference for clinical decision.

Objective:To assess the ultrasonographic features and potential diseases of fetal abnormal sylvian fissure(SF), and to explore the value of whole-genome sequencing (WGS) in prenatal detection.Methods:A total of 28 fetuses with a sonographic diagnosis of abnormal SF in Shenzhen Maternal and Child Health Hospital Affiliated to Southern Medical University between October 2018 and October 2020 were prospectively included. The fetal brain was evaluated by neuroultrasound and intrauterine MRI in detail. Amniotic fluid/cord blood obtained by amniocentesis or tissue samples from umbilical cord after birth were collected for WGS. Pregnancy outcomes and postnatal MRI were recorded, and neurodevelopment of live-born infants was followed up for more than 24 months after delivery.Results:During the study period, 28 fetuses with abnormal SF were identified, with a gestational age of 21.3-30.0 (24.8±2.0) weeks. Abnormal SF presented in MCD ( n=15, 53.6%), chromosomal anomalies ( n=3, 10.7%) or single-gene genetic syndromes ( n=3, 10.7%) with the affected fetuses showing developmental delay, hydrocephalus or leukomalacia ( n=4, 14.2%), corpus callosal agenesis with large interhemispheric cysts ( n=1, 3.6%), benign subarachnoid space enlargement with arachnoid cysts ( n=1, 3.6%), and multiple malformations ( n=1, 3.6%). Among the 15 cases with MCD, the most common pathology was lissencephaly/pachygyria, followed by schizencephaly, severe microcephaly, hemimegalencephaly with paraventricular heterotopia, and polymicrogyria. Abnormal SF presented bilaterally in 23 fetuses and unilaterally in 5. All cases were categorized into six types depending on SF morphology in the transthalamic section: no plateau-like or a small insula, linear type, irregular corrugated SF, Z-shaped, and cyst occupying type. In addition to abnormal SF, associated anomalies or mild variations were identified in all fetuses. There were 17 cases underwent intrauterine MRI, and 13 cases underwent postnatal MRI examination.And 25 pregnancies were terminated; 3 were born alive, and 2 had typical syndromic changes with poor neurodevelopmental prognosis. A related pathogenic genetic variant was detected in 57.1% (16/28) fetus, and the incidence of single nucleotide variants(SNVs) was 42.9% (12/28), among which de novo SNVs accounted for 91.7% (11/12). Conclusions:Fetal abnormal SF could be classified based on the ultrasonographic features of transthalamic section. Fetal abnormal SF may indicate MCD, some chromosomal abnormalities or single-gene genetic syndromes that may lead to poor neurodevelopmental outcomes, and may be affected by extra-cortical factors. It is suggested to carry out targeted prenatal genetic diagnosis for fetuses with abnormal SF.